Positive Family Functioning
29 September 2010
Final Report by Access Economics Pty Limited for
Department of Families, Housing, Community Services and Indigenous Affairs
© Access Economics Pty Limited
This work is copyright. The Copyright Act 1968 permits fair dealing for study, research, news reporting, criticism or review. Selected passages, tables or diagrams may be reproduced for such purposes provided acknowledgment of the source is included. Permission for any more extensive reproduction must be obtained from Access Economics Pty Limited through the contact officer listed for this report.
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Report prepared by Lynne Pezzullo Penny Taylor Scott Mitchell Laze Pejoski Khoa Le Anam Bilgrami
2
Positive Family Functioning
Contents
Acknowledgements.........................................................................................................................i
Glossary ii
Executive Summary .........................................................................................................................i
1 Introduction ........................................................................................................................ 5
2 Methodological overview ................................................................................................... 6
2.1 Definition of family functioning and the outcomes of interest ............................................. 6
2.2 Data review............................................................................................................................ 7
2.3 Literature review.................................................................................................................. 10
2.4 Concepts and data underlying lifetime costing ................................................................... 10
2.5 Model construction.............................................................................................................. 11
2.6 Cost benefit/cost effectiveness analysis (CBA/CEA) and the process for selecting interventions for analysis..................................................................................................... 18
3 Findings from the LSAC data investigation ....................................................................... 21
3.1 LSAC variables ...................................................................................................................... 21
3.2 LSAC analysis........................................................................................................................ 24
4 Findings from the ATP data investigation......................................................................... 31
4.1 ATP variables........................................................................................................................ 31
4.2 ATP analysis ......................................................................................................................... 34
5 The costing model............................................................................................................. 38
5.1 Health outcomes.................................................................................................................. 38
5.2 Productivity outcomes......................................................................................................... 44
5.3 Criminality outcomes........................................................................................................... 45
5.4 Lifetime costing framework ................................................................................................. 49
6 Cost benefit analysis ......................................................................................................... 52
6.1 Communities for children (CfC)............................................................................................ 52
6.2 Positive Parenting Program (PPP) ........................................................................................ 56
6.3 Reconnect ............................................................................................................................ 62
6.4 Shocking all variables – the value of PFF ............................................................................. 69
7 Conclusions ....................................................................................................................... 71
References................................................................................................................................... 77
Appendix A : LSAC children and future addictive behaviours .................................................... 85
Appendix B : Literature review sources, ATP ............................................................................. 88
Appendix C : LSAC regression outcomes .................................................................................... 91
Appendix D : LSAC variable specification ................................................................................. 104
Appendix E : Mean and standard deviation of LSAC variables................................................. 108
Appendix F : ATP variable interpretation.................................................................................. 111
Appendix G : ATP Regression outcomes ................................................................................... 118
Appendix H : Mean and standard deviation of ATP variables................................................... 128
Appendix I : Detailed costing methodology and tables ........................................................... 133
Charts
Chart 3.1 : Explanatory power of regressions, by age................................................................ 26
Chart A.1 : Differences in cognitive development by socio‐economic status............................ 86
Tables
Table 2.1 : Characteristics of family functioning domains ........................................................... 6
Table 2.2 : FF variables used for each intervention .................................................................... 16
Table 3.1 : Regression constructs in LSAC .................................................................................. 23
Table 4.1 : Regression constructs................................................................................................ 32
Table 5.1 : Summary of total costs of obesity (2010)................................................................. 39
Table 5.2 : Summary of total costs of anxiety and depression (2010) ....................................... 41
Table 5.3 : Summary of total costs of daily smoking (2010) ...................................................... 42
Table 5.4 : Summary of total costs of alcohol abuse (2010) ...................................................... 43
Table 5.5 : Summary of total costs of illicit drug use (2010)...................................................... 44
Table 5.6 : Estimated effects* (%) of year 12 and undergraduate completion* on probability of participation and average earnings ............................................................................ 45
Table 5.7 : Social costs of crime by cost type (2010) ................................................................. 46
Table 5.8 : Net recurrent expenditure on criminal courts (2008‐09) and % criminal court finalisations by court type .......................................................................................... 47
Table 5.9 : Total real net operating expenditure on prisons and community corrections in Australia in 2008‐09.................................................................................................... 48
Table 5.10 : Discounted lifetime costs of adverse health outcomes (a) (2010 dollars) ............. 49
Table 5.11 : Discounted lifetime costs of adverse productivity outcomes (a) (2010 dollars).... 50
Table 5.12 : Discounted lifetime costs of criminality outcomes (a) (2010 dollars).................... 51
Table 6.1 : Communities for Children target areas and related LSAC variables ......................... 54
Table 6.2 : Outcomes of Communities for Children variables used in this report...................... 55
Table 6.3 : Outcomes of CfC as delivered over 2004‐05 to 2007‐08 .......................................... 56
Table 6.4 : PPP target areas and LSAC variables ......................................................................... 58
Table 6.5 : Impact of large scale Queensland PPP trial ............................................................... 58
Table 6.6 : Impact of large scale Western Australian PPP trial ................................................... 59
Table 6.7 : Improvement in means scores of European PPP trial .............................................. 60
Table 6.8 : Outcomes of PPP variables used in this analysis....................................................... 60
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Table 6.9 : PPP costs ($US) .......................................................................................................... 61
Table 6.10 : Outcomes of PPP as delivered over 2004‐05 to 2007‐08 in Queensland................ 61
Table 6.11 : ATP variables associated with the Reconnect Program .......................................... 66
Table 6.12 : Estimate of effect size — young person’s perception of their ability to manage family conflict before Reconnect and now................................................................. 67
Table 6.13 : Estimate of effect size — young person’s perception of their family’s ability to manage family conflict before Reconnect and now................................................... 68
Table 6.14 : Outcomes of the Reconnect Program, as delivered over 2004‐05 to 2008‐09....... 69
Table 6.15 : The value of PFF....................................................................................................... 69
Table 7.1 : Summary of costs and benefits of modelled interventions ...................................... 72
Table B.1 : Antisocial behaviour ................................................................................................. 88
Table B.2 : Anxiety and depression ............................................................................................ 88
Table B.3 : Smoking .................................................................................................................... 89
Table B.4 : Alcohol...................................................................................................................... 89
Table B.5 : Illicit drug use ........................................................................................................... 89
Table B.6 : Productivity .............................................................................................................. 90
Table B.7 : Overweight/obesity.................................................................................................. 90
Table C.1 : Obesity B1 (ahs23c2) ................................................................................................ 91
Table C.2 : Obesity B2 (bcbmi) ................................................................................................... 92
Table C.3 : Obesity B3 (ccbmi).................................................................................................... 92
Table C.4 : Obesity K2 (dcbmi) ................................................................................................... 93
Table C.5 : Obesity K3 (ecbmi).................................................................................................... 93
Table C.6 : Productivity B1 (awlrnoi) .......................................................................................... 94
Table C.7 : Productivity B2 (bwlrnoi).......................................................................................... 94
Table C.8 : Productivity B3 (cwlrnoi) .......................................................................................... 95
Table C.9 : Productivity K2 (dwlrnoi).......................................................................................... 95
Table C.10 : Productivity K3 (ewlrnoi) ........................................................................................ 96
Table C.11 : Anxiety and depression B1 (apedsgc)..................................................................... 96
Table C.12 : Anxiety and depression B2 (bpedsef)..................................................................... 97
Table C.13 : Anxiety and depression B3 (cpedsef) ..................................................................... 97
Table C.14 : Anxiety and depression K2 (daemot) ..................................................................... 98
Table C.15 : Anxiety and depression K3 (eaemot) ..................................................................... 98
Table C.16 : Antisocial B1 (apedsgc)........................................................................................... 99
Table C.17 : Antisocial B2 (babitp) ............................................................................................. 99
Table C.18 : Antisocial B3 (caconda) ........................................................................................ 100
Table C.19 : Antisocial K2 (daconda) ........................................................................................ 100
Table C.20 : Antisocial K3 (eaconda) ........................................................................................ 101
Table C.21 : Addictions B1 (apedsgc) ....................................................................................... 101
Table C.22 : Addictions B2 (babitp) .......................................................................................... 102
Table C.23 : Addictions B3 (casdqta) ........................................................................................ 102
Table C.24 : Addictions K2 (dasdqta)........................................................................................ 103
Table C.25 : Addictions K3 (easdqta)........................................................................................ 103
Table D.1 : Standard LSAC variables......................................................................................... 104
Table D.2 : Combinations of LSAC variables............................................................................. 106
Illustrative distribution of categorical variables........................................................................ 109
Table G.1 : Underengagement predictor variables................................................................... 118
Table G.2 : Completion of high school(a)(b) ............................................................................. 118
Table G.3 : Completion of high school (only) v University degree(a)(b) ................................... 119
Table G.4 : Body mass index at 23‐24 years(a)(b)..................................................................... 120
Table G.5 : ATP anxiety/depression 2002 crosstabulation ....................................................... 122
Table G.6 : Logistic regression results — child age 19‐20 years (year 2002)(a)(b) ................... 122
Table G.7 : Logistic regression results — child age 19‐20 years (year 2002)(a)(b) ................... 124
Table I.1 : Obesity prevalence rates and estimated obese people (number) in 2010 ............. 136
Table I.2 : Anxiety and depression prevalence rates and estimated people with anxiety and depression (number) in 2010 ................................................................................... 136
Table I.3 : Smoking prevalence rates and estimated current daily smokers in 2010............... 137
Table I.4 : Prevalence rates for tobacco‐caused diseases and conditions(a)........................... 138
Table I.5 : Prevalence rates ‐ drinking at risky‐high risk(a) levels of long term health harm and estimated risky‐high risk drinkers in 2010................................................................ 138
Table I.6 : Prevalence rates for recent use(a) of illicit drugs and estimated recent users in 2010139
Table I.7 : Offender age‐gender prevalence profile and estimated offenders in 2008‐09 ...... 139
Table I.8 : Prisoner age‐gender prevalence rates and estimated prisoners in 2009 ............... 140
Table I.9 : Annual per‐person costs of obesity ‐ males (in 2010 dollars) ................................. 140
Table I.10 : Annual per‐person costs of obesity ‐ females (in 2010 dollars) ............................ 141
Table I.11 : Annual per‐person costs of anxiety and depression ‐ males (in 2010 dollars)...... 142
Table I.12 : Annual per‐person costs of anxiety and depression ‐ females (in 2010 dollars) .. 142
Table I.13 : Annual per‐person costs of current daily smoking ‐ males (in 2010 dollars) ........ 143
Table I.14 : Annual per‐person costs of current daily smoking ‐ females (in 2010 dollars)..... 143
Table I.15 : Annual per‐person costs of alcohol abuse ‐ males (in 2010 dollars)..................... 144
Table I.16 : Annual per‐person costs of alcohol abuse ‐ females (in 2010 dollars).................. 144
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Table I.17 : Annual per‐person costs of illicit drug abuse ‐ males (in 2010 dollars)................. 145
Table I.18 : Annual per‐person costs of illicit drug abuse ‐ females (in 2010 dollars) ............. 145
Table I.19 : Age‐gender employment in the general population............................................. 146
Table I.20 : Age‐gender average weekly earnings(a) for the general population ($) .............. 146
Table I.21 : Annual costs of year 12 non‐completion ($ 2010) ................................................ 147
Table I.22 : Annual costs of undergraduate degree non‐completion ($ 2010)........................ 147
Table I.23 : Age‐specific undergraduate non‐completion rates in 2007.................................. 148
Table I.24 : Annual policing cost per offender ($) .................................................................... 149
Table I.25 : Annual court system cost per offender ($)............................................................ 149
Table I.26 : Annual prison system cost per prisoner ($)........................................................... 149
Table I.27 : Annual per‐person societal costs of crime for males ($)....................................... 150
Table I.28 : Annual per‐person societal costs of crime for females ($).................................... 150
Table I.29 : Crime under‐reporting multipliers and derived probabilities ............................... 151
Table I.30 : Probabilities of court action on reported crimes .................................................. 152
Table I.31 : Court finalisation outcome probabilities............................................................... 153
Table I.32 : Custodial sentence probabilities in guilty verdict court cases .............................. 153
Figures
Figure 2.1 : Approximate age of study cohorts and bridging the current information gap......... 8
Figure 2.2 : Diagram of data map................................................................................................. 9
Figure 2.3 : Conceptual map for valuing costs of NFF................................................................ 10
Figure 2.4 : Incidence versus prevalence approach .................................................................... 10
Figure 2.5 : Cost effectiveness analysis model map.................................................................... 17
Figure 2.6 : CEA model pathway for interventions .................................................................... 18
Figure 6.1 : Value of PFF by benefit type, 2010 (total $5.4 billion), $bn and % total ................. 70
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Acknowledgements
Access Economics would like to acknowledge with gratitude the expert knowledge and inputs provided by members of the Expert Reference Group for this project. Professor Ann Sanson Department of Paediatrics, University of Melbourne, ARC/NHMRC Research Network Coordinator, Australian Research Alliance for Children and Youth Brian Babington Chief Executive Officer, Families Australia Carol Ey Branch Manager, Research and Analysis Branch, Department of Families, Housing, Community Services and Indigenous Affairs Dr Lance Emerson Chief Executive Officer, Australian Research Alliance for Children and Youth (ARACY) Dr Marian Esler Section Manager, Research Section, Family and Child Support Policy Branch, Department of Families, Housing, Community Services and Indigenous Affairs Dr Matthew Gray Deputy Director, Australian Institute of Family Studies Megan Shipley Research Section, Family and Child Support Policy Branch, Department of Families, Housing, Community Services and Indigenous Affairs Paula Mance Research Projects and Publications Section, Department of Families, Housing, Community Services and Indigenous Affairs Rachel Henry Research Section, Family and Child Support Policy Branch, Department of Families, Housing, Community Services and Indigenous Affairs Professor Stephen Zubrick Co‐Director for Developmental Health, Curtin University of Technology Access Economics would like to acknowledge in particular the staff of the Australian Institute of Family Studies (AIFS), who analysed the Australian Temperament Project (ATP) data and modelled those regressions. Apart from Dr Gray, particular thanks go to Dr Ben Edwards and Dr Diana Smart.
Glossary
ABS Australian Bureau of Statistics
AE‐DEM Access Economics Demographic Model
AEM Access Economics Macroeconomics Model
AIFS Australian Institute of Family Studies
AIHW Australian Institute of Health and Welfare
AWE average weekly earnings
ATP Australian Temperament Project
B1, B2, B3 Baby cohort, waves 1, 2 and 3 in LSAC
BOD burden of disease
CALD Culturally and Linguistically Diverse
CBA cost benefit analysis
CEA cost effectiveness analysis
CFC Communities for Children
DALY disability adjusted life year
DCBA disease cost‐burden analysis
DEEWR Department of Education, Employment and Workplace Relations
DOFD Department of Finance and Deregulation
DSM Diagnostic and Statistical Manual
DSP Disability Support Pension
DWL deadweight loss
FAHCSIA Australian Government Department of Families, Housing, Community Services and Indigenous Affairs
FF family functioning
FRS family relationship services
GP general practitioner
HILDA Household Income and Labour Dynamics in Australia
International Classification of Diseases (10th revision) ICD‐10
K1, K2, K3 Kindy cohort, waves 1, 2 and 3 in LSAC
LSAC Longitudinal Study of Australian Children
LSAY Longitudinal Study of Australian Youth
NHS National Health Survey
NDHS National Drug Strategy Household Survey
NPV net present value
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NSA Newstart Allowance
NFF negative family functioning
MBS Medicare Benefits Schedule
OLS Ordinary Least Squares
PBS Pharmaceutical Benefits Scheme
PC Productivity Commission
PFF positive family functioning
PPP Postive Parenting Program
PS Parenting Scale
PSOC Parental Sense of Competency
PUP Parents under Pressure
QOL quality of life
REACH Responding Early Assisting Children
SCRGSP Steering Committee for the Review of Government Service Provision
SDAC Survey of Disability, Ageing and Carers (ABS)
SDQ Strengths and Difficulties Questionnaire
SES socioeconomic status
SFCS Stronger Families and Communities Strategy
TILA Transition to Independent Living Allowance
VSLY value of a statistical life year
WHO World Health Organization
W1,2,3 waves 1,2,3 of LSAC
YLD year(s) of healthy life lost due to disability
YLL year(s) of healthy life lost due to premature mortality
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i
Executive Summary
Access Economics was commissioned by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) to quantify, in economic terms, the value of ‘goods and services’ provided by positive family functioning (PFF) and to conduct a cost benefit analysis (CBA) to establish the returns to government and society for investments made in supporting family functioning (FF). This report follows a scoping study, also conducted by Access Economics, to establish the methodology for the project. The scoping study explains the equivalence of measuring the value of PFF as the costs of negative family functioning (NFF). This study was overseen by a panel of experts.
Methods
FF is defined through a variety of domains – emotional, governance, cognitive, physical, intra‐familial and social (Table 2.1). Literature review revealed three broad areas of outcomes associated with FF.
■ Health outcomes were observed through the occurrence of anxiety and depression, obesity and substance abuse (smoking, alcohol and drug abuse) later in life. These are associated with health expenditures, productivity losses (through lower workforce participation and premature death), other financial costs, and loss of quality of life (QoL) (measured in disability adjusted life years or DALYs).
■ Productivity outcomes were reflected in secondary and tertiary educational achievement completion, flowing on to impact lifetime earnings.
■ Social outcomes were primarily measured through negative manifestations – antisocial behaviour such as delinquency and crime, resulting in criminal justice system costs.
Two longitudinal studies — the Longitudinal study of Australian Children (LSAC) aged up to 9 years and the Australian Temperament Project (ATP) for older children were selected to analyse the relationship between FF and child outcomes. Regression analysis was conducted to establish relationships between ‘transition’ health, productivity and social outcome variables in LSAC and FF variables. The latter were selected on the basis of literature evidence, after controlling for other factors such as socioeconomic status (SES). Transition variables were carefully selected to match similar or identical ATP variables. Further regression analysis was undertaken using the transition variables, together with ATP FF and control independent variables, to establish relationships with ATP ‘interim’ health, productivity and social outcomes in early adulthood. The interim outcomes were then used to predict lifetime health, productivity and social costs, based on an extensive costing process utilising multiple data sources (Chapter 5).
Findings
The net present value (NPV) of benefits from intervening in childhood and adolescence to prevent poor outcomes later in life are substantial, despite the fact that such intervention
incurs costs today but discounted benefits are realised a long time into the future.
In total, the potential NPV of benefits to be realised is in the order of $5.4 billion per annum in 2010 dollars. This can be considered the cost of NFF currently, or the value of PFF gains possible. Over half these gains (53% or $2.9 billion) are productivity gains, with a further 22% ($1.2 billion) of the benefits deriving from savings from fewer
■
ii
addictions. Fewer cases of anxiety and depression would save $0.6 billion (11%), while lower rates of criminality and antisocial behaviour would accrue $0.5 billion (10%). A reduction in obesity would save $0.3 billion per annum (5% of the total) ‐ Figure i.
Figure i: Value of PFF by benefit type, 2010 (total $5.4 billion), $bn and % total
261 , 5%
2,882 , 53%
581 , 11%
547 , 10%
1,176 , 22%
Obesity Productivity Anxiety and depression Anti‐social Addictions
Source: Access Economics calculations. Note: Shares may not sum to 100% due to rounding.
is has focused on three interventions selected on ba
■
efit:cost ratio
tio
benefit:cost ratio for this return on investment.
Costs and benefits are summarised in Table ii.
There are also marked social and economic benefits if cost effective prevention programs can be identified and implemented. This analysthe ses of a range of criteria (section 2.6)
The Communities for Children program, targeting pre‐school and primary school aged children, is one of the major Australian Government investments in families. The program improves outcomes in various FF areas including hostile parenting, parenting self‐efficacy, parent mental health, quality of the home learning environment, parental relationship conflict, child total emotional and behavioural problems, childhood overweight, receptive vocabulary achievement and verbal ability. The benfor this program was estimated as 4.8:1, a 377% return on investment.
■ The Positive Parenting Program is one of the best evaluated FF programs for younger children. The program improves FF outcomes in parental sense of competency, the dyadic adjustment scale, the Strengths and Difficulties Questionnaire (SDQ) emotional and conduct scales, the Eyberg Child Behaviour Intensity score, parental depression, parental laxness, parental over‐reactivity, and parental verbosity. The benefit:cost rafor this program was estimated as 13.8:1, a substantial 1,283% return on investment.
■ The Reconnect program targets an older cohort of children and was found to improve outcomes in school bonding and conflictual relationships, with proxied effect sizes estimated for attachment to parents and harsh parenting. The program was estimated as 1.8:1, an 81%
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iii
Table ii: Summary of costs and benefits of modelled interventions
CfC PPP Reconnect
Program cost ($m)* 113.6 19.7 112.1
Unit cost ($) 840/child aged 0‐5 34/child aged 2‐12 3,800/person aged 12‐21
Benefit ($m, lifetime NPV) 541.4 272.4 202.8
Benefit:cost ratio 4.76 13.82 1.81
Source: Access Economics calculations. * Costs estimated over 2004‐05 to 2007‐08 except for Reconnect which extends to 2008‐09.
Many of the family ‘inputs’ incorporated in the analysis were found to be statistically significant explanators of child outcomes with the relationship consistent with that predicted by the literature.
■ Obesity was explained by key drivers such as previous obesity, parental obesity, lack of child persistence, and parent‐child conflict.
■ Anxiety and depression were dependent on previous emotional problems, difficult temperament, lower socioeconomic status (SES), harsh discipline, parental anxiety/depression, alienation from parents and lack of child persistence.
■ Smoking in young adulthood (19‐20 years) was determined by previous smoking in adolescence, parental permission to smoke at home and a conflictual parent‐teenager relationship. Alcohol abuse (binge drinking) in young adulthood was dependent on teen bingeing, lack of parental monitoring, father drinking and initiating drinking at an older age (over 15 compared to 14 or younger). Illicit drug use in 23‐24 year olds was dependent on the child’s temperament, lack of parental monitoring, and mother smoking.
■ Predisposition to smoking, alcohol abuse and illicit drug use was established in early years by parental smoking, temperament, harsh and/or inconsistent discipline, poor
nce,
king and low SES, along with parental anxiety/depression and the child’s temperament.
te these findings internationally as well as continue to enhance the evidence base in Australia.
Access Economics
family cohesion and parental anxiety depression.
■ Productivity was driven by previous learning outcomes, consistent discipline, temperament, socioeconomic status, parent education and, in adolescence, persisterelationship quality/warmth, parental monitoring and a positive attitude to school.
■ Antisocial behaviour and outcomes were determined by child lack of persistence, previous social/conduct problems and, importantly, were largely influenced by early life FF variables such as poor family cohesion, harsh discipline, parental smo
The greatest value in this project has been primarily to showcase how a broad, quantitative approach to social policy evaluation can work. With better quality data in the future, there is scope to refine and continue to develop the modelling and elaborate on findings further. The scope of this project has been both ambitious and challenging but, we believe, the methods developed and many findings and insights are of global significance. The novelty of the research inspires further work in this field that we hope can be used to triangula
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5
1 Introduction
Access Economics was commissioned by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) to quantify, in economic terms, the value of ‘goods and services’ provided by positive family functioning (PFF) and to conduct a cost benefit analysis (CBA) and/or cost effectiveness analysis (CEA) to establish the returns to government and society for investments made in supporting family functioning.
This report follows a scoping study, also conducted by Access Economics. The scoping study in 2009 determined:
■ the feasibility of quantifying, in economic terms, the value of ‘goods and services’ provided by PFF;
■ a method for measuring the benefits of PFF; and
■ a method to conduct CBA and CEA of interventions to improve FF.
The methods developed in the scoping study form the basis for the analysis in this report. The scoping study explains the equivalence of measuring the value of PFF as the costs of negative family functioning (NFF).
Both the scoping study and this full study were overseen by a panel of experts, as listed in the acknowledgements section of each report. In addition, this study was undertaken with assistance from the Australian Institute of Family Studies (AIFS), which analysed the Australian Temperament Project (ATP) data.
The of this report is as follows. structure
■ The methodology is explained in chapter 2.
■ The findings from the investigation of the Longitudinal Survey of Australian Children
f the ATP are detailed in chapter 4.
nd the CEA results are explained.
etailed information is provided in the Appendices in relation to the methods, LSAC and ATP investigations, and the costing model.
(LSAC) are outlined in chapter 3.
■ The findings from the investigation o
■ The costing model is described in 5.
■ In chapter 6, the interventions analysed a
■ Conclusions are elaborated in chapter 7.
■ D
2 Methodological overview
2.1 Definition of family functioning and the outcomes of interest
The focus of the scoping study was on the outcomes of family functioning for the child, without pursuing any family ‘ideal’ or promoting any specific type of family structure. Children are not able to explicitly control their family environment and they are often viewed as the main victims of NFF.
The scoping study identified that while no simple definition of PFF exists, consistent themes (or ‘domains’) of FF emerged from the literature. These were developed and agreed, in consultation with the Expert Reference Group for the scoping study and with FaHCSIA. These domains provide an overarching definition of the FF environment. A summary is provided below.
Family functioning (FF) – positive and negative – is defined through a variety of emotional attributes, family governance frameworks, cognitive engagement and development characteristics, physical health habits, intra‐familial relationships and social connectedness. PFF is characterised by emotional closeness, warmth, support and security; well‐communicated and consistently applied age‐appropriate expectations; stimulating and educational interactions; the cultivation and modelling of physical health promotion strategies; high quality relationships between all family members; and involvement of family members in community activities.
The domains of FF are not mutually exclusive, but interact, complement each other and co‐exist.
Table 2.1: Characteristics of family functioning domains
Domain Characteristics / Proxies
Emotional Closeness of parent‐child relationships, warmth, responsiveness, sensitivity, perceived parental and family support as well as healthy open communication, and security/safety.
Governance Establishment of age‐appropriate rules, expectations and consistency
Engagement and cognitive development
Reading and verbal engagement, quality time fostering the development of educational, language and interaction skills.
Physical health
Healthy/unhealthy physical activities or environments as well as access – including in‐utero – to specific products (e.g. fruit and vegetables, cigarettes and alcohol).
Intra‐familial relationships (dyadic family relationships)
Quality of relationships between all members of the family. For example sibling rivalries, parent‐child relationships as well as the health of the parents’ relationship.
Social connectivity Involvement of parents and children in activities outside of the family unit (e.g. school, community service, volunteer work). Also includes relationships with extended family and work/life balance.
Source: Access Economics in consultation with the Expert Reference Group and FaHCSIA.
6
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7
The literature review for the scoping study revealed three broad areas of outcomes associated with FF.
■ Health outcomes were mostly observed through the occurrence of mental illnesses such as anxiety and depression later in life, but also included eating disorders, health behaviours (e.g. unsafe sex, physical inactivity, overweight and obesity) and substance abuse (e.g. smoking, alcohol and drug abuse), with the consequent physical impacts of these risk factors on morbidity and mortality outcomes.
■ Productivity outcomes were reflected in rates of labour force participation, employment and hourly wage rates, with a number of intermediate measures reported in the literature, such as reduced levels of literacy and numeracy and other measures of educational achievement.
■ Social outcomes were measured primarily through their negative manifestations –involvement in antisocial behaviour such as delinquency, and the probability of criminal behaviour during youth and later in life. In contrast it was harder to quantitatively associate PFF with positive manifestations such as the quality of inter‐personal relationships and future community contributions.
The iteria used to select the specific outcomes for analysis in this report were: cr
■ each outcome domain was covered (health, productivity and social);
■ outcomes were associated with high economic and social costs, including burden of
were able to be measured by the data sets used as the basis for analysis (see below).
this
ree);
sion, obesity, smoking, drinking, illicit drug use); and
ile
aic of
thy study timeframes. For example, intermediate outcomes y and literacy cannot easily be converted into specific types of jobs and streams.
investigated but the LSAY did not
disease (BoD), based on prevalence and/or existing studies of costs and BoD;
■ the outcomes
In report, the correlation between FF is thus examined for the following outcomes:
■ productivity (school completion and completion of an undergraduate university deg
■ health (anxiety and/or depres
■ social (antisocial behaviour).
Wh the literature provided valuable insights into potential linkages between FF and child outcomes, the following cautions apply.
■ Many of the concepts are difficult to capture and measure and there is a mosdifferent and overlapping instruments and metrics.
■ Statistical techniques can be used to determine correlation rather than causation.
■ While measures of intermediate outcomes are available, it is difficult to convert these to final outcomes without lengsuch as numeraclifetime earnings
2.2 Data review
Two longitudinal studies — the Longitudinal study of Australian Children (LSAC) and the Australian Temperament Project (ATP) were selected to analyse the correlation between FF and child outcomes. The Longitudinal Survey of Australian Youth (LSAY) and the Household, Income and Labour Dynamics in Australia (HILDA) were also
8
col t information on FF variables and HILDA is limited to relationships between the family nment and parent’s participation in the labour force.
LSAC has the advantage of containing a breadth of data, valuable for testing confo
lecenviro
■ unding factors. However, a disadvantage is the relatively short timeframe of data
years. However, measures
gers du , however, eptual consistencies in measurement of FF between the two data sets.
collection as the eldest participants from the child cohorts are currently 10‐11 years of age.
■ ATP is currently the only study in Australia that allows the determination of long term impacts of FF on health, economic and social outcomes as the most recent data for participants in this study were collected at the age of 23‐24of FF and parenting have only been recorded since the participants were in their early teens, with no measures during infancy or early childhood.
Variables from the ATP and LSAC within each of FF domains were mapped to the specific outcomes selected for analysis so that the likelihood of one of the events of interest occurring could be established across different age groups (Figure 2.1) and linked with outcomes. The ability to join information from LSAC and ATP is limited by slightly different methods in each data set of measuring FF and differences in the generations (ATP children were teena
ring the 1990s, whereas LSAC children are growing up during the new century). There are conc
Figure 2.1: Approximate age of study cohorts and bridging the current information gap
LSAC (1)
LSAC (2) Current Age Cohort Data Gap
ATP
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Approximate Age of Cohort in 2009 LSAC (1) is the Birth cohort and LSAC (2) is the Kindy cohort.
Ideally, one or two more waves of information from the LSAC is required to successfully bridge the gap in ages between the two studies, to enable mapping outcomes for children aged
analys
■ observations in the oldest groups i.e. the third wave of the Kindy cohort in LSAC. Early and mid‐period FF and control
P ep
analys
9 years to those aged 13 years. This approach is considered acceptable, given the alternative is to wait some years for additional study waves to be completed.
Figure 2.2 shows how LSAC provides the dependent (end‐period ‘transition’) variables and independent (early and mid‐period family functioning and control) variables in regression
is of children aged up to 9 years.
End‐period transition variables are those that relate to
variables relate to observations in all the other age groups (the first and second wave observations and the third wave for the birth cohort).
AT data then provide the dependent (end‐period ‘interim outcome’) variables and ind endent (early and mid‐period family functioning and control) variables in regression
is of people aged up to 25 years.
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9
■
ion completed, illicit drug use and body mass index were assessed at age 23‐24 years, while other variables (completing year 12, smoking, binge drinking,
n be modelled by ‘shocking’ the LSAC variables, while adolescent interventions1 can by ‘shocking’ the ATP variables. ‘Shocking’ the model refers to changing inpu simulating the effects of an intervention, and then observing the consequent change in model outputs (health,
End‐period interim outcome variables are those that relate to observations in the oldest groups of ATP relevant to the cost data and the circumstance. For example, highest level of educat
anxiety/depression, and anti‐social behaviour) were assessed at adulthood (18‐19 years). Early and mid‐period FF and control variables relate to younger age observations.
The interim outcomes can then be used to predict, in an Excel model, lifetime health costs, lifetime productivity losses, social costs of crime and disability adjusted life years (DALYs). The impact of childhood programs ca
be modelledt parameters from one level to another,
productivity and social outcomes).
Figure 2.2: Diagram of data map
LSAC ‐ early and mid‐period
CfC, PPP shock FF variables
control variables (confounding)
Regression analysis
LSAC ‐ end‐period ATP ‐ early and mid‐period
Transition variables FF variables shock Reconnect
control variables (confounding)
Regression analysis
ATP ‐ end‐period
Interim outcomes
Excel model
Lieftime health costs
Productivity (lifetime earnings)
Social (lifetime costs of crime)
DALYs
In laymen’s terms, LSAC was used to establish the impact of FF on children up to the age of 9 years, at which age transitional outcomes from childhood were spliced into the ATP analysis by matching this set of transitional outcomes across the two datasets. Health, productivity
ng adequate data to establish hip between family functioning and outcomes, collaborative relationships were
chers and FaHCSIA data specialists. Both were important participants in the project. Furthermore, AIFS currently manages the ATP data set and access
and social interim outcomes in early adulthood thus depended on FF during adolescence as well as the transitional outcomes from childhood. From the interim outcomes in early adulthood, lifetime cost impacts were predicted using a variety of other datasets.
Given the identification of the ATP and LSAC databases as providithe relationsestablished with AIFS resear
arrangements require that AIFS undertake any in depth analysis.
1 The Communities for Children (CfC) and Positive Parenting Program (PPP) were selected for younger children, while the Reconnect program was selected for adolescents (see Section 2.6).
10
2.3 Literature review
Evidence from the literature was used to edify the selection of family functioning inputs from es. The findings are briefly
outlined in chapter 3, and chapter 4, and evidence is summarised in Appendix A and Appendix
2.4 Concepts a
the ATP and LSAC that would be likely to be correlated with outcom
B.
nd data underlying lifetime costing
Costs were attached to each outcome as depicted in Figure 2.3.
Figure 2.3: Conceptual map for valuing costs of NFF
Emotional Health Health system expenditures
Governance Productivity losses
Cognitive Productivity Criminality costs
Physical Social/criminality DWLs
Intra‐familial Other financial impacts
Social Burden of disease
Source: Access Economics. Blue – health impacts. Red – productivity impacts. Green – Social/criminality impacts.
An incidence or ‘life aetiology of lagged outcomes – i.e. ‘lifetime’ costs (hazard model). An incidence approach is distinguished from a
time’ costing approach was adopted in line with the
prevalence approach in Figure 2.4.
Figure 2.4: Incidence versus prevalence approach
2000 2009 2018
A* A
B* B B**
C C*
Incidence costs (2009) = C + present value of C*
Prevalence costs (2009) = A + B + C
The lifdiseas
■ Cost Data Collection
(Department of Health and Ageing), the Pharmaceutical Benefits Scheme (PBS), the
Note: The years are illustrative and do not relate to this analysis.
etime costs associated with each outcome include the standard cost categories for e cost burden analysis from the health economics literature:
Direct health costs – estimated with cost data sourced primarily from the Australian Institute of Health and Welfare (AIHW) data, National Hospital
Positive Family Functioning
11
Medicare Benefits Schedule (MBS) and epidemiological data sourced from the Australian Bureau of Statistics (ABS) National Health Survey (NHS), AIHW and other specific epidemiological studies reported in the peer reviewed literature.
re (unpaid care provided by family and friends), health aids and appliances, deadweight
sources of these estimates are previous studies by Access Economics, and the ABS
and Carers (SDAC) (ABS, 2004), and Lattimore et al (1997).
is sthe co lected for analysis. The net
se
■ nt a direct input into the cost benefit analysis.
analyses) change as a result of the intervention
pact of a 'shock' to consistent
■ Costs of crime – estimated with data primarily from the Steering Committee for the Review of Government Service Provision (SCRGSP) Report on Government Services, and reports from the Australian Institute of Criminology and ABS. .
■ Productivity costs – are estimated using the human capital approach and reflect reduced labour force participation and absenteeism due to the outcomes selected. Parameters and labour force data were drawn primarily from the ABS and reports by the Productivity Commission (PC), as well as peer reviewed literature.
■ Burden of disease (BoD) – was estimated using DALYs and determined using the same disability weights and methodology used by the AIHW (Begg et al, 2007). Monetary values were estimated for the BoD using the value of a statistical life year from DOFD (2009).
■ Other financial costs – include costs associated with the provision of informal ca
losses (DWLs) (efficiency losses which arise due to transfer payments). The main
Survey of Disability, Ageing
Further detail on costing methods, cost categories and data sources is provided in Appendix I.
2.5 Model construction
Th ection provides an outline of the model developed to investigate the benefits of PFF and sts and benefits of the three family functioning programs se
benefits for each program were derived under a scenario with the intervention compared to a ‘ba case’ without the intervention.
The costs for the CfC program, PPP and Reconnect programs are reported in chapter 6 and represe
■ The benefits are based on the extent to which each intervention improves FF and reduces its associated costs. The effectiveness of each intervention is reported in chapter 6 while the associated costs (health, productivity and social) are detailed in chapter 5.
The underlying principle of the model (developed in Microsoft Excel 2007) is that outcomes (dependent variables in the regression affecting early and mid‐period family functioning (independent) variables in the regression. The size of the intervention is a direct function of the effectiveness of the program on impacted functioning variables (chapter 6) and the size of the coefficients derived in the regressions (Appendix C and Appendix G).
A simple example illustrates the model construction using the imdiscipline on anxiety in children aged 4‐5 (so the analysis starts with the B3 cohort of this age – incidentally the same age as the K1 cohort). The ‘shock’ in this example was derived from PPP improvements in ‘parental laxness’ and mapped directly to parental consistent discipline as both in practice are aspects of parental consistency (Table 6.20).
12
The 'shock' can be viewed as changing the input parameters (e.g. parental consistent discipline) from one level to another, simulated by the effects of an intervention. Before the shock, the multivariate regressions for anxiety are given below for age group 4‐5 (B3), 6‐7 (K2) and 8anxiet child, and discipline is towards that child).
‐9 (K3), respectively. In each case, i represents the observational child in the dataset (so y is that of the
Where:
B3 = Cohort of children aged 4‐5 in the ("Baby") group B2 = Cohort of children aged 2‐3 in the ("Baby") group
= Beta coefficient for 'Anxiety' in group B2
= Beta coefficient for 'Consistent discipline' in group B3
= Regression error term
Where:
K2 = Cohort of children aged 6‐7 in the ("Kindergarten") group B3 = Cohort of children aged 4‐5 in the ("Baby") group
= Beta coefficient for 'Anxiety' in group B3
= Beta coefficient for 'Consistent discipline' in group K2
= Regression error term
Where: K3 = Cohort of children aged 8‐9 in the ("Kindergarten") group K2 = Cohort of children aged 6‐7 in the ("Kindergarten") group
= Beta coefficient for 'Anxiety' in group K2
= Beta coefficient for 'Consistent discipline' in group K3
= Regression error term
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13
As a result of the intervention, the new level of childhood anxiety for children aged 4‐5 includes changes in parental consistent discipline. The change in parental consistent discipline from the shock was calculated by multiplying the effectiveness of the program by the average onsistent discipline value for children aged 4‐5.
c
Where:
= New 'Anxiety' value after intervention
= (mean consistent discipline x effectiveness of program)
= Beta coefficient for 'Anxiety' in group B2
= Beta coefficient for 'Consistent discipline' in group B3
B3 = Cohort of children aged 4‐5 in the ("Baby") group B2 = Cohort of children aged 2‐3 in the ("Baby") group
= Regression error term
As a result of the shock, the consequent change in the model output (Anxiety') is given by a ercentage change.
p
Where:
= Percentage change in 'Anxiety'
= New 'Anxiety' value after intervention
= Baseline 'Anxiety' value
B3 = Cohort of children aged 4‐5 in the ("Baby") group B2 = Cohort of children aged 2‐3 in the ("Baby") group
Consequently, the direct percentage change in anxiety levels for children in the 4‐5 age group is captured through to the next LSAC age group (6‐7 year group) through the use of the lagged ependent variable changing by the intervention effectiveness.
d
Where:
= Percentage change in 'Anxiety'
= New 'Anxiety' value after intervention
= Baseline 'Anxiety' mean value
B3 = Cohort of children aged 4‐5 in the ("Baby") group B2 = Cohort of children aged 2‐3 in the ("Baby") group
Where:
= New 'Anxiety' value after intervention in the previous age group
= New 'Anxiety' lagged dependent variable = as above
= Beta coefficient for 'Anxiety' in group B2
= Beta coefficient for 'Consistent discipline' in group B3
K2 = Cohort of children aged 6‐7 in the ("Kindergarten") group B3 = Cohort of children aged 4‐5 in the ("Baby") group
= Regression error term
Following this pattern, Anxiety’’K2,i and Anxiety’K3,i are similarly calculated. The change in the final period of LSAC compared with the actual outcome is then included in the ATP multinomial logit regression i.e. the new anxiety levels for K3 children aged 9 (the final regression in the LSAC analysis) is fed directly into the ATP logistic regression for children aged 13 years.
14
Positive Family Functioning
Where:
= New 'Anxiety' value in children aged 8‐9 in the ("Kindergarten") group
= Base 'Anxiety' value in children aged 8‐9 in the ("Kindergarten") group
This effectively assumes that no change occurs in outcomes between the ages of 10 to 12. As mentioned before, this approach is considered acceptable, given the alternative is to wait some years for additional study waves to be completed.
The multinomial logit regression models were used to analyse the impact of an intervention on the probability of each family functioning outcome for children aged 13‐23 years. Unlike the multivariate linear regressions, the results presented in the logit regression represent the probability of an outcome for a person with ‘average’ attributes. Like the LSAC multivariate linear regressions, the interventions were modelled as a deviation from the mean of a particular explanatory variable (e.g. anxiety). The baseline logistic regression is given below, where e is a mathematical constant, i is again each child observed (in ATP this time), βs are
again coefficients, and εs are again error terms. X is the sample mean.
After the percentage change from anxiety in the 8‐9 year old age group, the new logistic regression is given, with changes to the lagged dependent variable.
In using the multinomial logit model, coefficient estimates are not directly interpretable so do not provide the same type of information as coefficients from an Ordinary Least Squares (OLS) model. A more natural way of interpreting results from a multinomial logit model is to determine the impact on the probability of an outcome by changing the variables that would be impacted by the intervention while holding all others constant. The impact of the intervention on the probability can therefore be represented by:
The impact of the intervention was therefore measured as the difference between the probability of an outcome for an average person with and without the intervention. As such, the model projects the probabilistic change in the outcome as a result of the intervention and calculates the economic benefits attached (detailed in chapter 5). The net economic gains
15
16
between the scenario and the ‘base case’ (no intervention) can therefore be evaluated to determine the intervention’s overall return on investment using a dollar value.
Table 2.2 summarises all the FF variables in the model for each intervention modelled (i.e. found to be significant in the regression analysis reported later on). A conceptual map of the model is provided in Figure 2.5.
Table 2.2: FF variables used for each intervention
CfC PPP Reconnect
Hostile parenting Hostile parenting Harsh parenting
Parenting self‐efficacy Parental self‐efficacy
Consistent parental discipline
Attachment to parents Parental warmth*
Parental relationship conflict Family cohesion Conflictual relationships
Parent mental health Parental anxiety and depression
Child total emotional and behavioural problems (SDQ)
SDQ total score, SDQ emotional score, SDQ conduct problems
Quality of the home learning environment
Home learning environment*
Receptive vocabulary achievement and verbal ability
Inductive reasoning School bonding (positive affect towards school); Under‐engagement (not in education or training and not employed)*
Child overweight
Source: Access Economics (2010). Note: See Chapters 3, 4 and 6 for derivation. * These variables are in the Reconnect model but the effect size was estimated as zero.
Positive Family Functioning
Figure 2.5: Cost effectiveness analysis model map
Source: Access Economics (2010)
17
2.6 Cost benefit/cost effectiveness analysis (CBA/CEA) and the process for selecting interventions for analysis
The concept of CEA modelling of FF interventions is outlined in Figure 2.6. All analyses compare the outcomes for children with the interventions, against outcomes for children without the intervention. The efficacy of a selected intervention in improving FF is derived from previous evaluations of the programs. The Excel model is then used to explore how this improvement in FF (the ‘shock’) reduces lifetime costs (in dollars and DALYs). These lifetime benefits can then be compared with the intervention costs, in net present value (NPV) terms.
Figure 2.6: CEA model pathway for interventions
Intervention
Improvement in
family functioning in
Yr x (efficacy)
Reduces lifetime costs
(NPV in Yr x, discounted
DALYs saved )
Cost in 09‐10$ Benefit in 09‐10$ CBA $:$ Benefit:Cost ratio
DALYs saved CEA $/DALY saved
As noted in Section 2.2, ‘shocking’ the model for CBA and CEA involves comparing what happens in the absence of an intervention (the status quo), with what would happen if a particular target population received an intervention. The intervention improves FF based on evaluated effectiveness of the program, which in turn improves transition and/or interim outcomes (based on the coefficients derived from the modelling). Better outcomes are associated with lower costs, so the NPV of the benefits (lower costs of NFF) can then be compared with the costs of the intervention. Benefits minus costs provide the ‘net benefit’ in dollars, while benefits divided by costs provide the ‘benefit:cost ratio’.
The process of selecting appropriate FF interventions commenced in the scoping study, when a preliminary assessment was undertaken of 12 types of interventions:
1. family assistance and income support payments;
2. family relationship services (FRS);
3. Stronger Families and Communities Strategy, including Communities for Children and Invest to Grow;
4. Positive Parenting Program (PPP);
5. Early childhood education;
6. Peel Child Health Survey;
7. Responding Early Assisting Children (REACh);
8. Reconnect;
9. Youthlinx;
10. Transition to Independent Living Allowance (TILA);
11. SureStart; and
12. Parents under Pressure (PuP).
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Positive Family Functioning
For this full study, criteria were established in the first Reference Group meeting for assessing appropriate interventions for CEA. These four criteria were:
1. Model data: the LSAC and ATP datasets will be able to accommodate ‘shocks’ to the intervention;
2. Target age: the interventions will target different age groups (e.g. pre‐school, primary school, youth)
3. Reach: the interventions have ‘reach’ i.e. they effectively target relevant (disadvantaged) groups; and
4. Efficacy data: adequate information is available from Australian (preferably) or international sources in order to provide an indication of the efficacy of interventions.
A follow‐up meeting with Steve Zubrick identified three further criteria.
5. Specificity: Interventions specifically target family functioning, rather than indirectly affect it (e.g. income supplementation can assist with FF, but is in essence a poverty alleviation method).
6. Sustainability: Interventions are current, and likely to continue into the future.
7. Relevance: Interventions have strong connections to or relevance for FaHCSIA.
We also reviewed literature provided by the Reference Group – Karoly et al (2007) and Wise et al (2005). The interventions selected from this process are summarised below.
2.6.2 Communities for children (CfC)
CfC meets all criteria for the CEA.
1. Model data: LSAC FF data can be linked with CfC interventions.
2. Target age: CfC is targeted to pre‐school and primary school age children.
3. Reach: CfC targets all Australian population sub‐groups.
4. Efficacy data: CfC has been evaluated with efficacy outcomes that can be imputed to the Excel model.
5. Specificity: CfC aims to improve family functioning and outcomes for children.
6. Sustainability: The CfC program has forward funding.
7. Relevance: CfC is a FaHCSIA program.
Conclusion: CfC is one of the major Australian Government investments in families. It has already been shown to be efficacious, and the CEA evaluation can also determine at what cost its effective outcomes are achieved.
2.6.3 Positive Parenting Program
PPP meets all criteria for the CEA.
1. Model data: LSAC FF data can be linked with PPP interventions.
2. Target age: PPP is targeted to pre‐school and primary school age children.
3. Reach: PPP targets all Australian population sub‐groups.
4. Efficacy data: PPP has been evaluated with efficacy outcomes that can be imputed to the Excel model.
19
20
5. Specificity: PPP aims to improve family functioning and outcomes for children.
6. Sustainability: The PPP program is successful and growing.
7. Relevance: PPP is a program relevant to FaHCSIA core business.
Conclusion: PPP is one of the best evaluated programs targeted at improving family functioning and outcomes for younger children. While its efficacy is well‐proven, there are fewer studies on its cost effectiveness and this CEA can also act as a tool to test/triangulate the power of the model.
2.6.4 Reconnect
In the Scoping Study Reference Group and in the 13 January Reference Group meeting the Reconnect program was identified as being a good candidate for CEA. Again it meets all criteria for the CEA.
1. Model data: ATP FF data can be linked with Reconnect interventions.
2. Target age: Reconnect targets youth aged 12‐18 (who are homeless or at risk of homelessness) and their families.
3. Reach: Reconnect targets all Australian population sub‐groups.2
4. Efficacy data: Reconnect has been evaluated with efficacy outcomes that can be imputed to the Excel model (based on two longitudinal studies).
5. Specificity: Reconnect aims to improve family functioning and outcomes for high school aged children.
6. Sustainability: The Reconnect program is funded into the future.
7. Relevance: Reconnect is a FaHCSIA program.
Conclusion: Reconnect provides a complementary intervention targeted at an the older cohort of children, which has been evaluated as effective, but where nothing is yet known regard cost effectiveness.
2 Indigenous youth comprised 9% of the respondents to the longitudinal survey that formed a key element of the 2003 evaluation by the Australian Government Department of Family and Community Services (FACS, 2003:34) and ‘No differences exist between entering and exiting clients in relation to country of birth or language background’ (FACS, 2003:35). Youth were represented from all jurisdictions, from both sexes and with varying levels of case complexity.
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21
3 Findings from the LSAC data investigation
LSAC consists of two cohorts ‘B’ (for Baby) and ‘K’ (for Kindergarten). Each of these cohorts has three sets of time data ‐‘waves’ of survey data taken at two yearly intervals. Information is collected through self‐reporting and also observational measures (such as parent‐child interactions). Child outcomes are measured as: behavioural and emotional adjustment; language and cognitive development; and social competence.
LSAC contains specific research questions. One question focuses particularly on the impacts of family relationships, composition and dynamics on child outcomes, and changes to these over time. The question includes the analysis of:
■ the size and make‐up of family;
■ the involvement of extended family;
■ roles of family members;
■ character of parental relationships and level of conflict in the family;
ies, particularly in times of stress.
to represent se
Appendix D provides a detailed description of each individual variable.
Cases
■
lationships between children and parents. In
■ parenting practices;
■ child’s temperament;
■ impact of family break‐up and re‐formation; and
■ family coping strateg
3.1 LSAC variables
Evidence from the literature was used to edify the selection of family functioning inputs from the ATP and LSAC that would be likely to be correlated with outcomes. The evidence is
in Appendix B. In most cases, the choice of relevant LSAC variablessummarisedthe general literature categories in the model is fairly straightforward.
■ Appendix C provides a complete list of LSAC variables included in the model.
■ ■ Appendix E provides a distribution of LSAC variables.
that involved more consideration are discussed below.
In some cases, concepts linked in the literature to negative outcomes for children — either as control variables or family functioning variables — were not available from the datasets. In the LSAC, no variables were identified for child abuse, school bonding, enmeshment, or negative conflictual readdition, some literature concepts were not relevant to LSAC children such as study child’s alcohol consumption or smoking.
■ For the obesity regression, the category ‘Sedentary activities’ is not derived directly from the literature discussed in Appendix B. The FF variable used here (e‐tainment) measures total hours per week of electronic entertainment: using computers, playing video games and watching television. The concept is that too much sedentary activity contributes to obesity.
22
■ Also, under obesity, the control variable ‘needs extra medical care’, while a direct LSAC variable, is not derived directly from the literature in Appendix B. The rationale here is that some children may be physically unable to exercise, which could in turn contribute to weight gains.
■ Under productivity, academic competency (learning outcomes) is derived from the literature but, given the young age of the children involved, academic competency could vary considerably within the two‐year span of each wave. Accordingly, the LSAC variable ‘study child age in months’ was added as a control variable.
For the very young cohorts (particularly B1 and sometimes B2 and older), there were no distinct measures of addictions, antisocial behaviour, or anxiety and depression. In some cases the best proximate dependant variable was the same (such as apedsgc for the B1 cohort across all three regressions). Since the only impact of these early cohorts is to feed into older age groups as a general indicator of previous problems, this was considered sensible, since the same
■
predisposing factor can be a risk for two different
d
d highest level of parent education .
■ Alcohol consumption has been recoded from six categories down to three categories –
missinbetwePrefer ple sizes
outcomes later. Note that for B2, babitp is used as the dependent variable with identical independent variables except that parental overprotection is used to predict addiction but not antisocial behaviour, based on the literature (Emmelkamp an Heeres, 1988), which reported that parental overprotection was a significant factor in adult drug addiction, hence its inclusion there.
■ Parental anxiety and depression has been recoded from an average to a sum of component measures.
■ The literature category ‘socio‐economic status’ is proxied by the LSAC variables household income3 an 4
abstain, safe and unsafe.
■ In an effort to obtain a ‘cradle to grave’ coverage for the full model, where the same dependant variable for the regressions is not available for all age groups, close substitutes are used.
There were also issues around sample size. The initial sample for both cohorts was around 5,000 children. After excluding children who have not participated in all three waves, the sample size is reduced to between 4,000 and 4,500. Using standard regressions, for any givenvariable, participants with nil responses are excluded. That is, the variable with the most
g observations determines the sample size for the regression. Thus, there is a trade off en more variables (greater explanatory power) and fewer variables (larger sample size). ence has been given here to greater explanatory power, but this does limit sam
to between 2,000 and 3,000 observations.
■ Certain participants are more likely to drop out as the study proceeds or to be non‐responders (which will affect sample size and bias in the analysis sample) – e.g. people with low socioeconomic status (SES), Indigenous Australians and those from non‐English speaking backgrounds. To account for this, sample weightings were employed.
3 For some groups, weekly income had to be used, but for compatibility this was converted to annual income.
4 Highest level is ‘post secondary’ (which includes the majority of parents, so there may be a lack of precision in the high end of the scale).
Positive Family Functioning
23
■ The model did not adjust for complex survey design, as this is not usually an issue unless location‐specific factors are important.
■ Also, to maintain sample size, the primary carer was used to represent parents, rather than having separate (and thus smaller) equations for mothers and fathers. This is also consistent with the ATP, which generally does not differentiate parents by gender. However, to allow for gender differences, sex of parent was included as a control variable.
■ The LSAC variable ‘family cohesion’ was used as a proxy for the literature category LSAC ‘argumentative gh this ed of sole parent families, who are an important subsample to retain
from the Strengths (SDQ) re utilised from LSAC and depression, ).
Table 3.3: Regression constructs in LS
Concept
‘marital conflict’. also measures relationships’, althouvariable is not askin the modelling.
■ Scales and Difficulties Questionnaire wein relation to anxiety anti‐social behaviour and addictions (Table 3.3
AC
Literature LSAC Measure LSAC Variable Name
Dependent variables#
Obesity Body mass index *cbmi (ahs23c2)
Productivity Learning Outcome Index *wlrnoi
Anxiety and depression SDQ emotional symptoms scale pedsgc, bpedsef,
*aemot (acpedsef)1
Antisocial SDQ conduct problems scale (apedsgc, babitp) *aconda
Addictions SDQ total score *asdqta (apedsgc, babitp)
FF variables
Harsh discipline Hostile parenting scale *ahostc (caang K1)
Parental monitoring / supervision
Importance of monitoringsupervising child
/
*pa08a1
Relationship quality / warmth Parental warmth scale *awarm
Inductive reasoning Inductive reasoning scale *aireas
Inconsistent discipline Consistent parenting scale *acons
Parental self efficacy Global rating of self‐efficacy *pa01a
Family cohesion Family ability to get along wieach other
th *re06a
Eating behaviour (obesity) Food diary (fat) *hfat
Eating behaviour (obesity) Food diary (sugary drink) *hsdrnk
Exercise (obesity)‡ Choice of physical activity in free time
*hb14c4
Sedentary activities (obesity) Hours per week electronic entertainment†
*he06c1, *he07b2,*egweek (combo) *he06b1,
Parental involvement in education (productivity) index
Home (education) activities *ahact
Parental involvement in uctivity)
volvement in class activities assc education (prod
In *
24
Literature Concept LSAC Measure LSAC Variable Name
Parental smoking (addictions, tisocial)
ette smoking anxiety & depression, an
Frequency of cigar *hb15a1
Parental alcohol (addictions, anxiety & depression, antisocial)
Alcohol consumption groups *balcgp
Overprotection (anxiety & on scale depression, addictions)
Parental overprotecti *aoverp
Control variables
Temperament Temperament *se06
Parental anxiety & depression K‐6 depression scale *ak6
Gender Sex of study child zf02m1
Socioeconomic status Household annual income2 *hinc (*fn05)
Parental education level Highest level of education completed†
*fd08a1, *fd08b2 (combo)
Parent gender Sex of primary carer zf02m2
Parental body mass index (obesity)
primary carer body mass index *abmi
Disability (obesity)‡ Special health care needs *hs14d
Age (productivity)‡ study child age in months *scagem
Notes: In the left column, variables in normal font are universal, variables in italics are particular to the individual right column, variables outside brackets are those used mostly or exclusively and used when the main variable was not available. Appendix D provides greater
description of these variables.
ildcard (*) it covers all age groups (represented by first letters a,b,c,d,e) unless them d 1 in Excel).
■ While this should yield a total of six time series observations, the two cohorts overlap at
ual difficulties in splicing the two together to create one ‘continuous’ time
The sigreat ohort groups. This is to some extent
regressions in brackets. In thevariables in brackets are those
# Previous wave of the dependent variable is also used as a control variable. † = LSAC variables that have been combined to form new variables. ‡ = variable not directly suggested by literature search. * Where a variable code contains a wano r age‐specific variable code is included next to the variable name. 1 cae ot would have been preferred, but yielded nonsensical results (R‐squared of 0 in Stata an
2 Household annual income was categorical, converted to dollars per year.
3.2 LSAC analysis
The LSAC presents a number of methodological issues for time series analysis. As noted in the preamble to chapter 3, the Baby and Kindergarten cohorts each have three waves of time data taken at two yearly intervals.
ages 4‐5 years (intentionally), leaving only five time series observations.
■ Moreover, as each cohort of children are entirely distinct populations, this creates conceptseries.
tuation is further complicated by the fact that, despite having over 16,000 variables, the majority of them are not common across all wave/c
unavoidable given the great differences between newborns and nine year olds, but it still makes it difficult to track variables continuously over time periods.
Positive Family Functioning
25
Accordingly, a number of approaches were investigated for modelling LSAC data. A hypothetical obesity regression is used here to illustrate the differences between these approaches.
■ 1) a straightforward longitudinal analysis. This derives averages across each total age group (e.g. average obesity for 4‐5 year olds) and uses them as regression variables. However, this approach
was not satisfactory for a number of reasons, including the lack
to W3. Also, because
was usually around 1,500, which was low.
■ 3) a stepped nction of W2 diet, other W2 control and FF variables, and previous period (W1) obesity. While explanatory
of suitable variables which covered all age groups.
■ 2) a semi‐panel approach, combining elements of longitudinal and cross sectional. Illustratively, obesity in wave (W) 3 is a function of obesity in W2, obesity in W1, diet in W3, diet in W2, diet in W1. This had the advantage that if the same variable cannot be found for diet across all groups, it does not matter, as different diet variables can be used for each age group. On the other hand, the number of variables with significant explanatory power was not high, and most of them belongedeffective sample size for regression analysis was limited to the smallest variable among any of the constituent age groups, the number of observations
time series model. Illustratively, obesity in W2 is a fu
power was good for the older groups, and average for intermediate ages, it was verypoor for the B1 infants group (Chart 3.1). A further issue with this approach is that theK1 group could not be utilised, as they lacked a link to previous periods.5 Fortunately,this age group (four to five year olds) is the only one covered with two sets of surveydata, so B3 could be used instead to represent this age group.
While none of the methods were optimal, method three was adopted as it had the leastshortcomings. Outcomes for individual regressions are discussed below.
5 For the 6‐7 year old group (K2), the coefficient for the lagged variable is derived from regressing against the K1 4‐5 year olds, but in the final regression the values used for lagged obesity are from the B3 4‐5 year olds to enable continuity with B2 and B1.
26
Chart 3.1: Explanatory power of regressions, by age
‐
0‐1 2‐3 4‐5 6‐7 8‐9
Age Cohort
0.10
0.20
0.70
0.30
0.40
0.50
0.60
R squared
0.80
0.90
Obesity Productivity Anxiety Antisocial Addictions
2
n lowest e
always significant.
gend the B1 cohort, while male gender was a risk for K2
t,
of physical activity.
The explanatory power (R2) for productivity regressions ranged from .07 to .51.
3.2.2 Obesity
Overall, obesity had the best explanatory power (R ) among the regressions, ranging from .08 for B1, up to 0.77 for K3. As in all regressio s, B1 was and K3 high st in terms of explanatory power.
As with all regressions, the lagged dependant variable (in this case, last period’s obesity) was significant for every age group. Previous obesity also had the largest coefficients. Parental obesity was also
Female er for the child was a risk forand K3. Male gender of the primary carer was a risk factor in two cohorts.
Interestingly, fatty foods, electronic entertainment and exercise tended not to be significanand when they were, occasionally had an unexpected sign in the younger cohorts (when the children were aged 2 and 4). When children are young, body mass index is a less reliable indicator and this may explain why some of the findings are not intuitive. Moreover, children in the younger cohorts may be less likely to use electronic entertainment and eat fatty foods. It should also be noted that the model captures children’s preference to being active or not, not to actual measures
3.2.3 Productivity
Positive Family Functioning
27
Previous learning index outcomes were always significant, as were consistent discipline, temperament (easy temperament effect), SES and parent education6. SES, however, had an unexpected sign for the B1 cohort. This may reflect that higher income is associated with
g to be associated with less ability to spend time the baby and poorer early learning outcomes as a consequence.
nsistently strong coefficients.
K
bles also sometimes had unexpected signs – such as parental warmth (B2, B3, K2), parental monitoring (K2), and parental involvement in education (K3). This is discussed further
sion
o had a strong impact and SES had a significant impact in some age groups, mostly with the expected sign. Harsh discipline/hostile parenting and parental
dep gnificant. Family cohesion and over‐protection also sometimes had signs.
or functioning). This is important to understand when interpreting the coefficients in Appendix C.
had explanatory power ranging from 0.01 (B1) to 0.50 (K3).
Inductive reasoning was significant for children aged 4 years and older, but with an
returnin work which may, in turn,
Both temperament and child gender had co
Being a girl was an advantage up to the K2 age group, when being a boy was significant (neither gender was significant for 3).
Other varia
in Section 3.2.7.
3.2.4 Anxiety and depres
Anxiety and depression, as measured by the LSAC’s Strengths and Difficulties Questionnaire (SDQ) emotional symptoms scale had explanatory power ranging from 0.01 (B1) to 0.36 (K3).
Previous emotional problems was always significant with the expected sign, while difficult temperament als
anxiety/ ression were siunexpected
Note that some outcome measures used are coded in less than intuitive directions. For example, while in the PEDS global concerns item (apedsgc and *pedsef), lower scores represent concern, but for the SDQ high scores equate with more problems (i.e. po
3.2.5 Anti‐social behaviour
Antisocial behaviour, as measured by the LSAC’s SDQ conduct problems scale,
Previous conduct problems, family cohesion, harsh discipline, parental smoking, low SES and the child’s temperament were always significant with the expected signs. Difficult temperament had consistently large coefficients, along with parental anxiety/depression in the B2 cohort.
Parental efficacy, parental anxiety/depression, gender (with risk for boys), and household income were mostly significant. Consistent discipline was mostly significant but with an unexpected sign in the K2 cohort.
unexpected sign. It may be that parents are more likely to use inductive reasoning with children who have conduct issues (i.e. reverse causation). Parental alcohol consumption had
6 The scale of parental education is provided in Appendix D.
28
an unexpected sign in the two younger cohorts cases where it was significant, possibly due to the same issue7.
3.2.6 Addictions
‘Addictions’ is a composite measure covering the literature concepts of smoking, drinking and drug use. It is rare for children in the LSAC age groups to smoke, drink or take other drugs. Thus, some LSAC variable needed to be found as an intermediate outcome that could act as a
inal surveys, there is no focus on transitional outcomes in nine year old children, as is needed here to bridge between the LSAC and the ATP.
There is evidence from paediatric and neurological studies (Shonkoff et al, 2010) to suggest
emotions such as fear and aggression while simultaneously diminishing the forward‐thinking and reasoning capacities which normally moderate reactions to such
Appendix A.
was sometimes significant with the expected sign. Inductive reasoning was sometimes
pointer to future addictive problems when the children reach ATP age and later adulthood.
There is abundant literature showing clear links between poor FF inputs in childhood and crime and addiction outcomes in adulthood. However, because such literature is frequently based on contiguous longitud
that anti‐social behaviour in primary school children may be linked to both addictions and anti‐social behaviour in adulthood, with stress as the common factor. Continual environmental stress – such as that occasioned by NFF – can cause structural changes in the brain that strengthen negative
emotions. While longitudinal studies on the influence of high stress have only been covered in animals so far, retrospective studies show that people who experienced trauma as children are much more likely as adults to smoke, drink and use drugs (Felitti et al, 1998) and become criminals (Currie and Tekin, 2006).
High levels of childhood stress can manifest as psychological and emotional dysregulation in childhood (Evans and Kim, 2007). Thus, for the purposes of regression modelling, ‘addictions’ are represented by the LSAC variable ‘total SDQ score’. A detailed rationale for this choice can be found in
The addictions regression, thus defined, had explanatory power ranging from 0.01 (B1) to 0.62 (K3). No variables were significant in the youngest B1 cohort.
In the four older cohorts, previous total SDQ problems, harsh discipline, inconsistent discipline, family cohesion, smoking, temperament, gender (risk for boys), and parental anxiety/depression were always significant with the expected signs. Temperament and parental anxiety/depression consistently had the largest coefficients.
Parental warmth and overprotection were mostly significant with expected signs, while SES
significant, but with unexpected signs – possibly for the same reasons as for antisocial behaviour (e.g. reverse causation). Parental alcohol consumption had an unexpected sing in the B2 and B3 cohorts also. 7
7 Reverse causality with alcohol has also been discussed in the literature. That is, parents of problem children may use alcohol as a coping mechanism, as reported by Pelham and Lang (1999): “Studies strongly support the assumption that the deviant child behaviours that represent major chronic interpersonal stressors for parents of ADHD children are associated with increased parental alcohol consumption. Studies also have demonstrated that parenting hassles may result in increased alcohol consumption in parents of "normal" children.” However, this does not explain the significant inverse relationship. Another possible reason, although we could find no literature
Positive Family Functioning
29
3.2.7 General observations
A number of variables in the LSAC analysis had unexpected signs. Family cohesion and ren
indicahas go
Inducparen eing disciplined / talk it over’. Note that most studies of the PPP include a variable to measure parental verbosity, which has a
sitively associated with conduct and total emotional problems because parents are more likely to use this parenting technique with children with difficult
link between caring for pets, swimming and learning outcomes may not be as clear as activities
d sign in the older cohort is reverse causation. That is, if a child has learning difficulties, a parent may have to spend more time helping them.
■ Indeed, in general it should be noted that these analyses are largely cross‐sectional so direction/causation cannot be perfectly tested, although to some extent this is overcome by including lagged dependent variables in subsequent stages of the modelling. However, in some cases (notably this variable and inductive reasoning), rather than the parents’ behaviour causing the child’s problem, it may be that the parents’ behaviour is in reaction to the child.
Parental alcohol consumption often has an unexpected sign, being significantly negatively associated with anxiety and depression (K2, K3), anti‐social behaviour (B2, B3) and addictions (B2, B3). This might possibly be due to reverse causation together with other factors in these toddler and pre‐school cohorts.
Finally, income sometimes has unexpected signs. This may be improved by standardising for household size. That is, a household with higher income may not have better outcomes than another household with lower total income, if income per child is in the first house is actually
pa tal warmth may be in this category because of their skewed distributions; LSAC data tes that a large proportion of people report that they are warm parents and their family od cohesion.
tive reasoning usually has an unexpected sign. In the LSAC, ‘inductive reasoning’ asks ts if they ‘explain to children why they are b
consistent negative effect on behaviour. It is possible that ‘inductive reasoning’ is in fact capturing ‘verbosity’ instead. In other words, the parent may perceive a detailed explanation, while the child may perceive ‘going on about it’ (at worst, nagging or harassment). It may also be that inductive reasoning is po
behaviour.
Parental involvement in education at home was negatively associated for the K3 cohort but positively correlated for the children aged 2 and 4 as expected. It should be noted that the measure changes (due to developmental differences) between the cohorts. When the children are younger, the measure includes activities such as reading stories, drawing, music and singing. These activities are likely to have a link to educational outcomes. In the K3 cohort, there are only three home activities questions – everyday activities (e.g. cooking, caring for pets), outdoor activities (e.g. swimming) and an adult in the family reading to the child. The
such as drawing and music. By the age of 8‐9 a child may spend more time reading to themselves and/or their parents than vice versa, particularly higher performing children. Another possible explanation of the unexpecte
supporting this conjecture, might be that parents of toddlers and pre‐schoolers drink either little or nothing, rather than a lot. It is a time of life when mothers may be pregnant or breastfeeding and when the young family is not as involved in social activities. If children have difficult behaviours, parents may find themselves even less likely to be able to participate in social functions, whereas if children are well‐behaved, they may be more able to relax and enjoy a drink (without abusing). However, this conjecture is purely speculative.
30
lower than income per child in the second house. In two wave 1 regression variables, income sity. We think this can be
– so in this case the is as expected – higher income is associated with heavier babies (low SES with
income goes up, learning in babies may be negatively impacted by mothers returning to work earlier (Ruhm, 2000), which could explain the productivity finding.
ion achieved and family cohesion — and at first glance may appear to have unexpected signs.
coefficients had an unexpected sign – for B1 productivity and obeexplained as follows. For the babies, the obesity metric is in fact weightresultunderweight babies). As
Readers should note that some variables are reverse coded in the LSAC database, including parental depression, parental highest educat
Positive Family Functioning
31
4 Findings from the ATP data investigation
4.1 ATP variables
Access Economics and the Australian Institute of Family Studies (AIFS) worked to specify appropriate models of family functioning based on the literature and variables available from
In the literature, positive outcomes for young people were commonly associated with authoritative parenting mode of parenting in Baumrind’s categorisation (see Wise 2003) — authoritative parenting is characterised by high levels of both c eptance ( rents on n of affection) and control (which into control based on the use of inductive
d con
Authoritative parenting poorer outcomes are on acceptance), permissive arenting (low on both control
Other features of parenting or family functioni ed in the literature as influencing outcomes for children include:
■ family conflict and family cohesion;
■ marital relationships;
relati
child abuse (including physical, sexual and
■ parental smoking and/or drinking.
The tables in Appendix B provide a summary of
Confounding variables available in the ATP and
■ the child’s innate temperament (persistence, );
■ parents’ education (as a proxy for socio
■ family stress (e.g. death of a parent or divorce) — some of which may reflect family functioning (such as the circumstances surrounding marriage breakup).
the Australian Temperament Project (ATP).
ATP variables were mapped to family functioning domains (emotional, governance, engagement and cognitive development, physical health, intra‐familial relationships and social connectivity — and to outcomes (in the domains of health, productivity and criminal behaviour). A literature review was also conducted to inform the selection of family functioning and other variables from the ATP likely to be correlated with the selected outcomes. Statistical analysis determined the final model specifications, and only variables found to be significantly correlated with outcomes were included in the CEA model.
ls. Based on the two dimensions
a c which entails emphasis by pa can be divided
warmth and the expressio
reasoning an trol based on parents’ use of pow
is to be distinguished
er).
from alternatives often associated with for children — authoritarian p nting (high on control and low parenting (high on warmth and low on and acceptance) (see Wise 2003).
control) and neglectful p
ng commonly identifi
■ sibling
■ onships;
emotional abuse) and neglect; and
the literature reviewed.
included in the analysis included:
reactivity and approach
economic status);
32
In rare cases, variables o
con either as control r family functioning variables — were example,
in the ATP we were unable to allow for paren post natal depression or parent’s anxiety/depression linke pression (Rapee 1997, van Gastel et al, 2009) — or parent’s body mass ked to child’s overweight or obesity outcomes (Wardle et al, 2001, Danielzik nother variable not available from the ATP. However, s were found, for example, in place of family income, the ATP parent’s highest education level attained’. Positive affect towards indicator of school bonding based on AIFS advice about the findings
l regressi
It is importa mily functioning’ olated from other influences such as environmental factors or cult to measure. The ATP variables selected inevitably reflect a d other factors and are at times difficult to interpret as either tioning or some other factor external to the family. In addition, there s where variables do not completely capture the conc there are missing variables within the ATP. The statistical relationships in this context.
Table 4.4: Regressi
variables s
cepts linked in the literature to outcomes for children — not available from the datasets. For
tal ental health — mother’smd to child’s anxiety/de index as a factor lin
et al, 2004). Family income was a in some cases, proxie
parameter: ‘each resident school was selected as an of previous research.
The initia on constructs investigated are summarised in Table 4.4.
nt to note that ‘fa cannot always be is child temperament, and is diffi
an mixture of family functioning reflecting family func
is the potential for omitted variable biaept being measured or where
reported here need to be viewed
on constructs
Interim outcome (dependent) Family functioning variable
Productivity Underengagement (childrenemployed and not studying)
Did not complete Yr 12
Completed Yr 12, Post secondary(non‐University), University degree
ision
ctual parent‐child
an earlier age
n level
not Harsh discipline
Parental monitoring/superv
Inconsistent discipline
Attachment to parents
Negative conflirelationship
School bonding
Academic competence at
Parental educatio
Temperament
Overweight/ obesity
Body mass index (normal orunderweight/overweight/o
rents
e
er eating behaviours
g/supervision
‘intact’)
Parental education level
bese) Negative conflictual parent‐child
Attachment to pa
relationship
Inconsistent disciplin
Harsh discipline
Teenag
Parental monitorin
Inductive reasoning
Family status (i.e.
Positive Family Functioning
33
Anxiety and/or Anxdepression
iety and/or depression Attachment to parents
Relationship quality/warmth
Experience of child abuse/neglect
Marital relationship
Harsh discipline
Enmeshment
Inductive reasoning
Stressful life event
Temperament
Alcohol/ smoking
Alcohol consumption including binge drinking
Parental management of teen substance use
Daily Smoking Inductive reasoning
Attachment to parents
Harsh discipline
Parental monitoring/supervision
Inconsistent discipline
Negative conflictual parent‐child relationship
Parental smoking
Temperament
Illicit drug use Illicit drug use including marijuana Experience of child abuse/neglect
marital relationship (conflict)
Mother/Father smoking and drinking habits
Temperament
Attachment to parents
Parent adolescent conflict
Parental monitoring/supervision
Antisocial behaviour
3 or more antisocial acts in the past year including illicit drugs
Relationship with parents
Attachment to parents
Family cohesion
Relationship quality/warmth
Harsh discipline
Parental monitoring/supervision
History of parental separation and its effect
Parental smoking
Inconsistent discipline
Marital relationship
Parental use of alcohol
Temperament
34
4.2 ATP analysis
The statistical analysis was undertaken by AIFS using ordinary least squares, logistic and multinomial regressions. The variables are described in Appendix F and details of each of the
ndix H. In summary:
instances, composite variables were constructed which included data for were computed to assist
ables. Composite variables were
itial ATP sample comprised 2,443 families from urban and rural areas of Victoria in still participating after 24 years. However, were determined by the samples available
P for which data are available (2006) reports on ATP children at
r children aged 19‐20 were
■ For the first two (obesity and completion of a university degree), dependent variables e for this age group.
■
ent variable was a lot less — 574 children of whom only 58 children re and not studying.
Completed
12) based on young adult report at age 19‐
The
redictor variables were significant:
■ Relationship warmth (inverse relationship with completion of high school);
regression outcomes are in Appendix G. The means and standard deviations of the regression variables are in Appe
■ Variables were constructed at various child ages depending on the most appropriate sample size for that variable in any given year.
■ In somechildren at a range of different ages. Inter‐correlationsdecisions about the viability of using across‐time varionly constructed for variables which were highly correlated across time.
■ Tests for multicollinearity suggest this was not a problem in any of the final equations.
■ The in1983, approximately two‐thirds of whom arethe sample sizes for the regression analysesfor all of the variables included in the regression analysis — and were affected by missing data and drop outs over time.
The most recent wave of the ATthe age of 23‐24 years. While regression analysis was conducted on the transitional outcomes for children aged 19‐20 as well as 23‐24, dependent variables fogenerally preferred on the basis that family influences were likely to be stronger at this age. Exceptions are obesity, completion of a university degree and illicit drug use.
were not availabl
For illicit drug use, the regression equation for the older group was preferred because one of the independent variables was of an unexpected sign (see Appendix G).
4.2.1 Productivity
A logistic regression was also conducted for under‐engagement (children not employed and not studying versus other children) but none of the predictor variables was significant. The sample size for this dependwe not employed
high school versus did not complete
A logistic regression was conducted comparing children who completed secondary school (year with those who did not. The responses are
20 years. There were 687 children in the sample, 65 of whom did not complete high school. Nagelkerke R2 was 0.309.
The following p
Positive Family Functioning
35
■ Parental monitoring/supervision of teen’s activities/associates, teenager report 17‐18 years (an increase in supervision was associated with an increased chance of completing
■ with a greater
■
■ School bonding (better bonding was associated with a greater likelihood of completing
■ Persistent temperament style, composite mean score of parent report at 11‐12, 13‐14,
l versus completed university degree
The following predictor variables were significant:
are only completing high school);
ssociated with a greater likelihood of only
(higher educational achievement of the father was associated with a the child completing a university degree)
rs. The sample size was 513, with 44 obese, 128 overweight and
on analysis comparing the chance of being overweight or obese at age 23‐24 rweight found the following significant variables. The
school);
Mother’s education (higher educational achievement was associatedchance of the child completing high school);
The child’s academic competence at 11‐12 years based on teacher report (greater academic competence was associated with a greater likelihood of completing school);
8
school); and
& 15‐16 years (persistence was associated with a greater likelihood of completing school).
Completed high schoo
In the sample of 595 young adults at age 23‐24 included in a logistic regression, 143 had completed high school only, and 277 had completed a university degree. The Nagelkerke R2 was 0.276.
■ more likely to complete a university degree thanAttachment to parents child age 17‐18 (children with higher levels of attachment
■ Relationship warmth (greater warmth is acompleting high school);
■ Father’s educationgreater chance of
■ School bonding9 (better bonding was associated with a greater likelihood of completing a university degree).
4.2.2 Obesity
In the ATP, body mass index is generated from self report (rather than actual measurements) at 15‐16 years and 23‐24 yeathe rest underweight or normal.
A logistic regressicompared with ‘normal’ or undeNagelkerke R2 was 0.518.
■ Overweight
Body mass index in 1998 (child age 15‐16) (a high index at age 15‐16 is associated with a greater chance of being overweight at age 23‐24);
8 positive affect towards school, teenager report 15‐16 years
9 positive affect towards school, teenager report 15‐16 years
36
Father’s education (lower levels of education are associated with a greater chance of being overweight at age 23‐24); and
h a lower chance of being overweight at
ild age 15‐16) (a high index at age 15‐16 is associated obese at age 23‐24);
conflictual parent‐teenager relationship, (parent report 17‐18 years), with a greater chance of obesity at age 23‐24;
tion (lower levels of education are associated with a greater chance 23‐24); and
4.2.3 Anxiety and/or depression
pression were combined for this analysis. The ATP scales for anxiety and ), which lead to similar prevalence
istical Manual of Mental Disorders (DSM IV) used more
adults aged 19‐20 who were at risk of being in the ssion with those who were not was conducted using a
sample of 642 children, 166 of whom were anxious and/or depressed. The Nagelkerke R2 was
ely associated with:
■ previous experience of anxiety/depression.
4.2.4 Drinking
A logistic regression was conducted using a sample of 580 young adults aged 19‐20, divided into those who spent 1‐4 days per month binge drinking (245 young adults), those who spent 5 or more days per month binge drinking (196 young adults) and those who did not binge drink (0 days per month). The Nagelkerke R2 was 0.121.
Binge drinking on 1‐4 days per month at age 19‐20 was significantly positively associated with drinking at age 13‐14 years.
Binge drinking on 5 or more days per month at age 19‐20 was significantly positively associated with:
■ drinking at age 13‐14 years;
■ less parental monitoring at age 15‐16;
A persistent temperament style (composite mean score of parent report at 11‐12, 13‐14, & 15‐16 years) is associated witage 23‐24.
■ Obesity
Body mass index in 1998 (chwith a greater chance of being
A negative/is associated
Father’s educaof obesity at age
A persistent temperament style (composite mean score of parent report at 11‐12, 13‐14, & 15‐16 years) is associated with a lower chance of obesity at age 23‐24.
Anxiety and dedepression are based on Lovibond and Lovibond (1995results to the Diagnostic and Statbroadly in Australia.
A logistic regression comparing youngclinical range for anxiety and/or depre
0.213.
Anxiety and/or depression at age 19‐20 was significantly positiv
■ alienation of the child from his or her parents;
■ not having a persistent temperament; and
Positive Family Functioning
37
■ father drinking, (composite mean score of parent report at 13‐14, and 17‐18 years); and
enager was first allowed to drink at home (this variable has two categories — the teen was allowed to drink at home at 15 years or older or the teen
19‐20 years, 121 of whom smoked daily. The Nagelkerke R was 0.297.
ositively associated with:
■ ■
riables which were significantly positively associated with the dependent
A logistic regression was conducted using 755 young adults aged 19‐20, 112 of whom reported
(including illicit substance use). Tne Nagelkerke R was 0.145.
age 13‐14 years and not having a persistent temperament were
■ a higher age at which the te
was allowed to drink at home at 14 years or younger — (based on parent report at 17‐18 years).
4.2.5 Smoking
A logistic regression was conducted on a sample of 830 young adults aged2
Daily smoking in this group was significantly p
■ Smoking at age 13‐14 years;
■ Being allowed to smoke at home;
Negative conflictual parent‐child relationship at age 17‐18; and
Mother smoking.
4.2.6 Illicit drugs
A regression was based on a sample of 664 young adults aged 23‐24 years who reported the number of differing types of illicit drugs used on one or more day/s in past month (range 0‐4). The R2 was 0.076.
Independent vavariable were:
■ Less parental supervision/monitoring at age 17‐18;
■ A mother who smoked; and
■ An approaching temperament.
4.2.7 Antisocial behaviour
that they were involved in 3 or more differing types of antisocial activities in past 12 months2
Antisocial behaviour in 1996 atthe only independent variables significantly positively associated with antisocial behaviour.
38
5 The costing model
As explained in the introductory chapter, FF was defined as having six domains, and variables from the ATP and LSAC within each of these domains were mapped to specific outcomes. The outcomes were drawn from three domains: health (anxiety and/or depression, obesity, smoking, alcohol abuse and illicit drug use), productivity (not completing year 12 and not completing a university undergraduate degree) and social/criminality (antisocial behaviour). The cost of each adverse outcome was then estimated (recall Figure 2.3).
This chapter describes the method for estimating the social and economic costs associated with adverse outcomes attributable to NFF.
s of include:
elfare (AIHW) data and Australian Bureau of Statistics (ABS) National Health Survey (NHS) primarily.
■ Productivity costs – estimates of reduced participation and absenteeism related to
tion, TER and post‐secondary education outcomes are from the PC and other sources.
■ Burden of dis al (2007) BoD study he year 2003 (with extrapolations modelled to future d the value of a stical life year (based on DOFD, 2009).
costs – these include costs associated with the of informal and appliances, deadweight efficiency losses and other costs for
g term substance abuse and other health pro The main sources ious studies by Access Economics and the Surve sability, Ageing and
) 2003 (ABS, 2004).
in Appendix I.
5.1 Health outcomes
■ alcohol abuse; and
■ illicit drug abuse.
The cost each outcome
■ Health costs – of five main conditions: tobacco use, alcohol abuse, illicit drug use, obesity, and anxiety and depression. These were sourced from the Australian Institute of Health and W
■ Costs of crime – using data sources from the PC’s Report on Government Services for 2009, as well as reports from the Australian Institute of Criminology.
health impacts are based on Access Economics cost of illness methods, plus other sources for alcohol and illicit drugs. Productivity costs associated with school comple
ease (BoD)– was determined using the AIHW Begg et for t years) anstati
■ Other financialcare, aids
provision various
people with lon blems.comprise prev y of DiCarers (SDAC
Further detail on costing methods, cost categories and data sources is provided
Analysis of the LSAC and ATP data‐sets led to the identification of the following main health conditions and behaviours associated with NFF:
■ anxiety and depression;
■ obesity;
■ current daily smoking;
Positive Family Functioning
39
In line Access Economics’ Diseaseoutcomes
with Cost Burden Analysis (DCBA) framework, health are associated with health system costs, productivity losses, DWLs, other financial
an
Collinssely categories. It is noted that there are
te of 3.5% per annum (based on
(Table
costs and BoD.
For xiety and depression, obesity and smoking, past Access Economics studies were used to collate total costs in 2010 and calculate per‐person costs. For alcohol abuse and drug abuse,
and Lapsley (2008) was used. Total reported costs were disaggregated and matched, as as possible, with Access Economics’ DCBAclo
limitations matching costs from Collins and Lapsley (2008) with the DCBA categories, due to differences in costing methodologies. However, Collins and Lapsley (2008) is the most recent and relevant source for costs of drug abuse in Australia and is thus employed. This report can be referred to for details on the methodology it uses.
5.1.1 Obesity
Obesity is the accumulation of excessive body fat, defined here as a body mass index of over 30 for adults. For children and adolescents aged 2 to 18 years, a set of age‐gender specific thresholds was used.
The cost of obesity was estimated for this project using Access Economics (2008) — that report included the costs of type 2 diabetes, cardiovascular disease, osteoarthritis and cancer attributable to obesity.
The 2008 costs were inflated to 2010 using a health inflation rahistorical averages reported by the AIHW). and 3% per annum for non health expenditure
5.5).
Table 5.5: Summary of total costs of obesity (2010)
Cost type Cost ($m)
Health system expenditure 2,098
Productivity losses 3,850
Other financial costs(a) 2,860
52,935
Total financial costs 8,808
BoD (DALYs x VSLY)
Total costs 61,743
(a)‘Other financial’ category includes DWL from transfers, carer costs and other indirect costs. Source: Access Economics (2008 and 2010 calculations)
Obesity prevalence rates were also drawn from Access Economics (2008). The rates were applied to 2010 population projections from Access Economics Demographic Model (AE‐Dem). Total costs were divided by the estimated number of obese people in 2010 (around 4 million)
ed to the correct total, a minor level adjustment downwards was applied while preserving the prevalence profile.
to obtain a per‐person annual cost for each cost type. The age‐gender prevalence profile for obesity was then applied to these per‐person costs to further refine costs into per‐person annual costs by age and gender. To ensure per‐person costs multiplied by estimated obese people summ
40
5.1.2
d depression are defined consistent with the clinical de d for prevalence
orders are those in which ‘anxiety is a predom (American ciation, 2009) such as panic disorder, obsessi pulsive disorder, a
anxiety disorder.
related affective disorders are defined in the ional Classification seases Tenth Revision (ICD‐10) by the World Health Orga (WHO, 2010) as a
. Capacity for is reduced, and marked tiredness after even
minimum effort is common. Sleep is usually disturbed and appetite diminished. Self‐
king in the several hours before the usual time, depression worst in the morning, marked
rdation, agitation, loss of appetite, weight loss, and loss of libido.
ce abuse disorders, anxiety disorders, affective disorders, bipolar disorder, schizophrenia and other mental illness. The
nxiety and
ts of all mental illness were used to proxy anxiety and
nment welfare payment rates in 2009 (Centrelink, 2009)
one disease category due to a high degree of co‐
m for non health
Anxiety and depression
Anxiety an finitions usestudies as follows:
■ Anxiety dis inant feature’Psychiatric Asso ve‐comphobia, or generalised
■ Depression and Internatof Di nizationlowering of mood, reduction of energy, and decrease in activityenjoyment, interest, and concentration
esteem and self‐confidence are almost always reduced and, even in the mild form, some ideas of guilt or worthlessness are often present. The lowered mood varies little from day to day, is unresponsive to circumstances and may be accompanied by so‐called ‘somatic’ symptoms, such as loss of interest and pleasurable feelings, wamorningpsychomotor reta
Cost data were drawn from Access Economics (2009) — a study of the costs of six categories of mental illness in the 12 to 25 years age group including substan
costs were adjusted so that they applied to all age groups by:
■ applying 2003 age‐gender prevalence rates, relative risks of mortality attributable to anxiety and depression and applying the relevant disability weights for adepression from Begg et al (2007);
■ expanding productivity losses to incorporate all age groups using NHS data for 2004‐05 (special request from the ABS for Access Economics, 2009) ‐ parameters for employment/productivity effecdepression;
■ adjusting carer costs to apply to the prevalent group of those with anxiety and depression; and
■ applying average annual goverto total recipients with mental illness.
The prevalence profile for anxiety and/or depression was obtained from Begg et al (2007), which grouped anxiety and depression asmorbidity and similarity in psychological and drug treatment between these conditions. The number of people with anxiety and/or depression was calculated by applying the prevalence rates to 2010 population projections from the AE‐Dem.
The total aggregated cost of anxiety and depression in 2010 is presented in Table 5.6 by cost type. The 2009 costs were inflated to 2010 using a health inflation rate of 3.5% per annum (based on historical averages reported by the AIHW)) and 3% per annuexpenditure.
Positive Family Functioning
41
Table 5.6: Summary of total costs of anxiety and depression (2010)
Cost type Costs ($m)
Health system expenditure 3,818
Productivity losses 17,992
Other financial costs(a) 3,491
Total financial costs 25,301
BoD (DALYs x VSLY) 41,162
Total costs 66,463
(a)‘Other financial’ category includes DWL from transfers, carer costs and other indirect costs. Source: Access Economics (2008 and 2010 calculations)
Total costs were divided by the estimated number of people with anxiety and/or depression in 2010 (around 2 m The age‐gender prevalence profile for anxiety and depression was then applied to these per‐person costs.
ts were made to ensure per‐person costs summed to th otal.
being a smoker if he or she currently smokes daily basis. Others eople smoking less frequently are excluded.
ere estimating using the findings of Access Economics (2 usted as follows:
from all relevant y smoking rather than ‘excess’ costs;
e ABS) for
■ applying welfare payment rates (Centrelink, 2009) to estimated recipients with tobacco‐Economics, 2006a) and tobacco‐caused cardiovascular illness
(Access Economics 2006b) in 2005.
lence rates for current daily smoking for people aged 18 and over, from Access Economics (2007). This prevalence profile displays falling prevalence rates
and conditions. This profile displays higher prevalence rates for older age groups, and was
illion) to obtain a per‐person annual cost for each cost type.
Adjustmen e relevant t
5.1.3 Smoking
A person is defined as on a e.g. ex‐smokers or p
The costs w 007), adj
■ removing the stipulation of having a mental illness and being a smoker costs to obtain total costs of current dail
■ applying 2007 age‐gender prevalence rates for current daily smoking for those without a mental illness from Access Economics (2007);
■ calculating relative risks of mortality attributable to current daily smoking for all age groups using Begg et al (2007);
■ adjusting BoD estimates to incorporate average disability weights for tobacco‐caused diseases for males and females using unpublished data from the AIHW requested for preparation of Access Economics (2007);
■ calculating productivity losses using NHS 2004‐05 data (special request from thall current daily smokers; and
caused cancer (Access
Two separate prevalence profiles were applied to estimate per‐person costs of daily smoking. The first profile employed preva
with higher age groups and was applied to estimate per‐person productivity costs, DWLs from transfers, carer costs and indirect costs. This profile was also applied to AE‐Dem 2010 population estimates to calculate estimated current daily smokers in 2010.
The second prevalence profile employed prevalence rates for tobacco‐attributable diseases
42
applied to health system and BoD costs. An increasing‐prevalence profile was deemed to be more suitable for these categories due to the cumulative nature of health deficits from smoking with increasing age (Hubbard et al, 2009). Thus, annual health expenditures and loss of wellbeing costs are likely to increase with age.
4 prevalent cases of total tobacco‐caused diseases per age group by the 2004 population in that age group (from AE‐Dem).
te of 3.5% per annum (based on historical averages reported by the AIHW ) and 3% per annum for non health
Table 5.7: Summary of total costs of daily smoking (2010)
Prevalence data for this second profile was obtained from the AIHW via a special data request in 2004 for Access Economics’ past study (2007). Prevalence rates were calculated by dividing the 200
The total aggregated cost of current daily smoking in 2010 is presented in Table 5.7 by cost type. The 2005 costs were inflated to 2010 using a health inflation ra
expenditure.
Cost type Cost ($m)
Health system expenditure 1,779
Productivity losses 12,400
Other financial cos
Total financial costs 16,440
x VSLY)
1
ts(a) 2,261
BoD (DALYs 167,197
Total costs 83,637
(a)‘Other financial’ catSource: Access Economics
egory includes DWL from transfers, carer costs and other indir s. (2008 and 2010 calculations)
d other financial costs were divided by the esti mber of smokers r‐person annual cost for these categories. The smoker age‐
valence profile was then applied to these per‐person co rther refine costs
ated prevalent cases of tobacco‐caused disease in 2010 (692,523) to obtain a per‐person annual cost for these
Alcohol abuse
Collins and Lapsley (2008) note that the definition of ‘abuse’ in relation to alcohol is
and ‘high risk’ drinking were summed. ‘Risky’ drinking is defined by the AIHW as 29 to
ect cost
Total productivity an mated nuin 2010 (2.9 million) to obtain a pegender pre sts to fuinto per‐person annual costs by age and gender.
Total health system costs and the value of the BoD were divided by estim
categories. The tobacco‐caused disease prevalence profile was then applied to these per‐person costs to further refine costs into per‐person annual costs by age and gender.
Adjustments were made to ensure per‐person costs summed to the relevant total.
5.1.4
problematic, with the National Alcohol Strategy showing no preference or separation between the terms ‘misuse’ and ‘abuse’.
For the purposes of this report, alcohol abuse is defined as consumption of alcohol at a level that produces sufficient risk of long‐term harm to health. This definition was taken from the 2004 National Drug Strategy Household Survey (NDHS) (AIHW, 2005). The categories of ‘risky’ drinking
Positive Family Functioning
43
42 drinks per week for males and 15 to 28 drinks per week for females. ‘High risk’ drinking is defined as 43+ drinks per week for males and 29+ drinks per week for females. Short term risk was not included as the data were insufficient in LSAC and ATP to identify short term risk (e.g. from bingeing).
for costs was Collins and Lapsley (2008). The prevalence profile for long‐term risky drinking was obtained from the 2004 NDHS (AIHW, 2005). These rates were applied to AE‐De ople affected in 2010.
s of alcohol abuse in 2010 are in Table 5.8. 2004‐05 costs were inflation rate of 3.5% per annum (based historical averages
IHW) and 3% per annum for non health expenditure
s were excluded to avoid double‐counting — the of crime related to .
tes of the BoDfrom alcohol abuse appear small when ared to those for e
ey study categories with Access Economics disease cost burden analysis
The primary data source
m 2010 population projections to estimate the number of pe
The total aggregated cost a health
Theinflated to 2010 usingreported by the A
on.
Notably, crime cost costs substance abuse are included in section 5.3
The estima compsmoking, anxiety and depression, and obesity. This is partly due to limitations in matching thCollins and Lapslcategories due to differences in study methodologies.
Table 5.8: Summary of total costs of alcohol abuse (2010)
Cost type Costs ($m)
Health system expenditure 2,347
Productivity losses
Other
4,102
financial costs(a) 4,511
163
Total financial costs 10,960
BoD (loss of life + pain and suffering) 5,204
Total costs 16,
(a)‘Other financial’ category includes accidents not elsewhere included, fires not elsewhere included and abusive consumption costs. Source: Collins and Lapsley (2008) – costs adapted to Access Economics DCBA categories
Total costs were divided by the estimated number of people with the condition in 2010 (1.8 million) to obtain a per‐person annual cost for each cost type. The age‐gender prevalence profile was then applied to these costs to develop a set of per‐person annual costs by age and gender group. Adjustments were made to ensure per‐person costs summed to the relevant
5.1.5 Illicit drug abuse
it dwith t
The p2005),were Dem.
total.
Illic rug abuse in this report is defined to include all illicit drugs (e.g. marijuana), consistent he source of the cost data (Collins and Lapsley, 2008).
revalence profile for recent use of illicit drugs was obtained from the 2004 NDHS (AIHW with recent use defined as use within the last 12 months. Recent drug users in 2010 calculated by applying prevalence rates to the 2010 population estimates from the AE‐
44
The toinflate torical averages
As witavoid
(2010)
Cost t
tal aggregated cost of illicit drug abuse in 2010 is in Table 5.9. The 2004‐05 costs were d to 2010 using a health inflation rate of 3.5% per annum (based on his
reported by the AIHW) and 3% per annum for non health expenditure.
h alcohol abuse, the costs of crime associated with illicit drug abuse were excluded to double‐counting.
Table 5.9: Summary of total costs of illicit drug use
ype Costs ($m)
He system expenditure 240 alth
Pro tivity losses 1,912
financial costs(a) 1,647
inancial costs 3,798
ss of life + pain and suffering from road nts) 1,477
osts
duc
Other
Total f
BoD (loaccide
Total c 5,275
(a)‘Other financial’ category includes accidents not elsewhere included, fires not elsewhere included and abusive consuSource: Collins and Lapsley
Total costs were divided by estima ition in 2010 (around 2.8 million) n annual cost age‐g
then applied to these costs to develop annual costs by age and gender tments were made to ensure per‐ costs summed to the rele nt total.
oductivity outcomes
e LSAC and ATP data‐sets, and parameters available from the literature, ss of earnings from not complet 12 and not comp a tertiary
te) degree (if completed year 12) able to be costed.
ucation levels display higher Additionally, those with
ing these workers to the labour force (La Plagne et al, 2007).
e form of forgone income) associated with non‐completion s.
ses were estimated as follows:
the effect of not completing year 12 and/or a university degree on d productivity were drawn from La Plagne et al (2007) and Forbes et al
007), through econometric modelling, estimated the effects of attainment levels on the probability of participation in the labour
force, relative to the baseline of year 11 completion only. A more recent study (Forbes et al 2010) estimated the impact of different education levels on average hourly wages
mption costs. (2008) – costs adapted to Access Economics DCBA categories
ted people with the condfor each cost type. The
a set of per‐personto obtain a per‐perso ender prevalence profile was
group. Adjus person va
5.2 Pr
Based on analysis of th the lo ing year leting (undergradua were
Human capital theory supports the idea that people with higher edlabour productivity, as proxied by their earnings (Forbes et al, 2010).higher education are more likely to participate in the workforce, due to higher labour demand for these workers, and labour supply factors such as expectations of higher wages and derivation of greater utility from the social and intellectual stimulation work provides attract
Consequently, there are costs (in thof year 12 and/or undergraduate studie
A number cost components for productivity los
■ Parameters foremployment an(2010). La Plagne et al (2different educational
Positive Family Functioning
45
(taken as an indicator of labour productivity), relative to the baseline of year 11 completion. Parameters from these studies are presented in Table 5.10.
ion depending on educational attainment were used as a proxy r di loyment. This difference was combined with average weekly
, 2009b) and employment rates (ABS, 2009a) for each age‐gender st earnings. The ABS AWE data were for 2008 and were inflated to
).
ational attainment on (ABS, 2009b) and
lculating taxation revenue
arnings. The tax rates for 2010 (19.48% and 11.68% respectively) were drawn from Access Economics’ Macroeconomic Model (AEM). DWLs were then
tion
effects* (%) of year 12 and undergraduate completion* on probability of participation and average earnings
n probability of participation*
Effect on average earnings*
■ Differences in participatfo fferences in empearnings (AWE) (ABSgroup to estimate lothe end of 2009 using labour price index data (ABS, 2010a
■ Wage differences were used as a proxy for the impact of educlabour productivity. These calculations were also based on ABS AWEemployment rate data (ABS, 2009a).
■ DWLs arising from foregone earnings were estimated by caforegone by applying the average personal income tax rate and average indirect taxation rate to foregone e
calculated by applying a DWL rate of 28.75% of each tax dollar foregone (Lattimore, 1997; PC, 2003) and Access Economics estimates of Federal Government administracosts).
Table 5.10: Estimated
Level of attainment Effect o
Year 12
Males 5.7% 12.8%
7.7% 10.1% Females
Undergraduate degree
Males 8.7% 38.4%
Females 16.4% 36.7%
* Relative to the baseSource: Productivity
line of year 11 completion Commission ‐ La Plagne et al (2007) and Forbes et al (2010)
The proportion of ee was based on data on undergraduate award for 2007 n, Employment and Work EEWR) via a est in
comes
s of costs were included
cietal costs ‐ due to the impacts on v and society;
s;
and
■ prison system costs.
the population not completing an undergraduate degrunpublishedof Educatio
course completionsplace Relations (D
from the Departmentspecial data requ
2009.
5.3 Criminality out
Four broad categorie :
■ so ictims
■ policing cost
■ court system costs;
46
The cos ere matched withresulting
ts w the relevant probability e.g. of the crime being prosecuted and in a conviction and prison sentence.
property‐related costs incurred by individuals and businesses due to property
er services and those costs non‐separable into the categories.
Estimates of societal costs were taken from an Australian Institute of Criminology report
g individual, commercial, burglary, thefts of vehicles, thefts from vehicles, shop theft and other theft;
r annum (based on historical averages reported by the AIHW) and 3% per annum for non health expenditure. Societal costs were divided by th t type (Table 5.11).
Table 5.11: Social costs of crim 0)
Cost type os Per o
5.3.1 Societal costs
Societal costs can include:
■ medical costs for victims of violent interpersonal crimes;
■ productivity losses for hospitalised and non‐hospitalised victims;
■ the costs of pain, suffering and lost quality of life (Rollings, 2008);
■ damaged/destroyed and non‐recovered stolen property; and
■ other costs such as cost of volunteabove
(Rollings, 2008). Rollings (2008) quantified societal costs for the following types of crime:
■ homicide;
■ assault;
■ sexual assault;
■ robbery – includin
■ criminal damage;
■ arson;
■ fraud; and
■ drug offences.
The total social cost in 2010 is in Table 5.11. The 2005 costs from Rollings (2008) were inflated to 2010 using a health inflation rate of 3.5% pe
e number of offenders in 2008‐09 (344,274) to determine a set of per offender costs by cos
e by cost type (201
ts ($m) Total C ffender ($)
Medical costs 791 2,296
Lost output (productivity) 3,392 9,85
uffering 3,467 10,07
9,819 28,5
21,197
Total societal costs 24,767 71,939
3
Costs of pain and s(intangible costs)
damage/loss
2
Property 21
Other(a) 7,298
(a)Those costs non‐separable into above categories Source: Rollings (2008)
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47
5.3.2 Policing costs
Policing costs are defined here as recurrent government expenditures on crime‐related serv Data on policing expenditures were obtained from SCRGSP (2010)
and adjusted down by 30% consistent with Rollings (2008) to account for the fact that not all
274 total offenders in Australia for all crime types in 2008‐09 (ABS, 2010b). An age‐gender distribution of offenders based on 2007‐08 data
stimates by population estimates from the AE‐Dem.
urt:
■■ District/County courts;
■ and
■ courts.
t expenditures on criminal courts were obta m SCRGSP (2010). timates of recurrent expenditur lisation for each
5.12, by court level. A weighted average net recurrent expenditure per finalisation for all courts was calculated by applying
base court finalisations at each court level. These weights are presented in the last column of Table 5.12.
ourt Net recurrent
expenditure per % of court
policing ices in a year.
police time is spent on crime.
A prevalence profile of offenders was developed using ABS data on offenders in Australia (ABS 2009c; 2010b). There were approximately 344,
(ABS, 2009c) was applied to this figure to estimate offenders by age‐gender group.
A set of offender prevalence rates was developed by dividing these offender e
5.3.3 Court system costs
Court system costs are defined here as recurrent government expenditures for all levels of criminal co
Supreme courts;
Magistrate courts;
Children’s
Data on total recurren ined froThis publication also contained es es per finacourt level.
Total recurrent expenditure on criminal courts in Australia in 2008‐09 and recurrent expenditure per court finalisation is presented in Table
weights d on the percentage of total criminal
Table 5.12: Net recurrent expenditure on criminal courts (2008‐09) and % criminal court finalisations by court type
Criminal cNet recurrent
expenditure ($m ) court finalisation ($)
finalisations
Suprem ts 85 15,118 0.6% e cour
District/County courts 204 7,553 3.0%
Magistrate courts 327 414 89.2%
85 ‐ 100.0%
Children’s courts 32 503 7.0%
Total
Source: Access Economics calculations using data from (SCRGSP, 2010)
48
Th ffender prevalence profile wae o s applied to the weighted average expenditure per ender annual court costs based on age‐gender group.
ures by the government on expenditure per prisoner were obtained from
figures for real net operating expenditure on prisons and in 2008‐09.
ped using data on prisoners in Australia from the ner prevalence rates was developed by dividing prisoner estimates
m the AE‐Dem.
community corrections in Australia in 3. Overall, total real net operating expenditure on prisons
s approximately $2.5 billion in 2008‐09. This figure was divided by the number of prisoners in 2008‐09 (29,319) to determine a cost per prisoner of
Expenditure type Amount ($’000)
finalisation estimate to develop per‐off
5.3.4 Prison costs
Prison costs are defined here as real net operating expenditprisoners in a year. Data on real net operatingSCRGSP (2010). This contained community corrections in Australia
An age‐gender profile of prisoners was develoABS (2009d). A set of prisoin each age‐gender group by age‐gender population estimates fro
Total real net operating expenditure on prisons and2008‐09 is presented in Table 5.1and community corrections wa
approximately $85,064.
Table 5.13: Total real net operating expenditure on prisons and community corrections in Australia in 2008‐09
Prisons 2,140,154
Community corrections 353,823
Total real net operating expenditure 2,493,977
Source: (SCRGSP, 2010)
The prisoner prevalence profile was applied to the cost per prisoner to attain a set of per‐prisoner annual prison system costs by age‐gender group.
. dependent on visibility of crime, severity),
reported. However a schematic set of probabilities was developed to g, court and prison system costs. This set
included:
■ em cost);
ability of court action on a reported e (thus attracting a court ;
■ of a ‘guilty verdict’ in a cou isation; and
of a guilty verdict involvin stodial sentence (thus attracting a prison ).
e types were based on ABS (2010b) for the cation of probabilities as
5.3.5 Probabilities of incurring costs
Since not all crimes incur all cost types (i.eprobabilities based on crime type were applied to costs within the final costing model. All crimes were assumed to attract the societal costs mentioned in section 5.3.1, regardless of whether they weredetermine whether a crime attracted policin
probability of a crime being reported to the police (thus attracting a policing syst
■ prob crim system cost)
probability rt final
■ probability g a cusystem cost
Crim appli follows:
Positive Family Functioning
49
■ homicide and related offences;
use inj
ssault and related offences;
or negligent acts endangeri ple;
abduction/harassment/other offences t the person;
robbery, extortion and related offenc
wful entry with intent;
d related offences;
and related offences;
illicit drug offences;
prohibited/regulated weapons and ex offences;
damage and environmental pollution;
rder offences; and
justice.
Lifetime costing framework
g framework was based on e application of each set of per‐head annual ender, across an estimated life Total lifetime costs were dent on an
set for the condition and assumed life‐span over which cos ld apply.
ese costs across life‐spans total lifetime, undiscoun st from the nce of that NFF outcome. Application scount rate across the life the tion of discounted lifetime costs (net values) in 2010 dollars.
‐completion, was 19 years. For undergraduate degree non‐
Lifetime costs were discounted back to 2010 at an annual real discount rate of 7%, consistent w interventions (Australian Government, 2010).
Assumed on life for males and females taken from ABS life
bles
Females
■ acts intended to ca ury;
■ sexual a
■ dangerous ng peo
■ agains
■ es;
■ unla
■ theft an
■ fraud, deception
■ ■ plosives
■ property
■ public o
■ offences against
5.4
The lifetime costin thcosts by age‐g time. depenassumed age of on ts wou
Summation of th gave a ted coprese of a di span allowedestima present
The assumed age of onset for all health, productivity and criminality outcomes, excludingundergraduate degree noncompletion, the assumed age of onset was 21 years.
ith the Australian Government’s choice of discount rate for assessing regulatory
life spans were basedtables (2009e).
expectancies
The costs are summarised in the ta below.
Table 5.14: Discounted lifetime costs of adverse health outcomes (a) (2010 dollars)
Cost type Males
Obesity
Health system 1,968 1,510
Productivity losses 3,617 2,777
50
Other financia 2,687 2,063 l(b)
BoD 49,728 38,186
Total 57,999 44,536
Anxiety and depression
Health system 8,739 6,340
Productivity losses 40,749 29,445
Other financial(b) 7,959 5,766
BoD 95, 75 69, 19 0 2
Total 152,522 110,771
Smoking
Health system 6,596 6,440
Productivity losses 58,075 62,149
Other financial(b) 10,588 11,331
BoD 57 56 6,799 3,150
Total 652,059 643,069
Alcohol abuse
Health system 14,780 16,199
Productivity losses 26,017 28,497
Other financial(c) 28,610 31,338
BoD 33,006 36,153
Total 102,413 112,188
Illicit drug abuse
Health system 904 1,045
Productivity losses 7,337 8,461
Other financial(b) 6,320 7,288
BoD 5,671 6,540
Total 20,232 23,334
(a) Assuming an age of onset of 19 years, life expectancies from ABS and 7% discount rate (b) ‘Other financial’ category for obesity, anxiety and depression and smoking includes DWL from transfers, carer costs and other indirect costs. (c) ‘Other financial’ category for alcohol abuse and drug abuse includes accidents not elsewhere included, fires not elsewhere included and abusive consumption costs. Source: Access Economics calculations.
Table 5.15: Discounted lifetime costs of adverse productivity outcomes (a) (2010 dollars)
Cost type Males Females
Year 12 non‐completion
Total productivity losses(b) 95,865 54,963
Undergraduate non‐completion
Total productivity losses(c) 312,768 198,282
(a) Including costs from lower employment/participation, productivity and DWL due to lower taxation revenue. (b) Assuming an age of onset of 19 years, life expectancies from ABS and 7% discount rate. (c) Assuming an age of onset of 21 years, life expectancies from ABS and 7% discount rate. Source: Access Economics calculations.
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51
Table 5.16: Discounted lifetime costs of criminality outcomes (a) (2010 dollars)
Cost type Males Females
Policing costs
Total 99,278 85,439 discounted costs
Court system costs
Total discounted costs 9,087 8,512
Prison system costs
Total discounted costs 928,696 865,222
Societal costs
Medical 15,869 13,660
Lost output 68,092 58,611
Intangible(b) 69,604 59,913
Property damage 197,108 169,664
Oth 126,09er(c) 146,493 6
Total discounted costs 497,166 427,945
(a) Assuming an age of onset of 19 years, life expectancies from ABS and 7% discount rate.
Those costs non‐separable into above categories. (b) ‘Intangible’ costs are those due to pain, suffering and lost QoL (Rollings, 2008).(c)Source: Access Economics calculations.
52
6 Cost benefit analysis
The Communities for Children (CfC), Positive Parenting Program (PPP) and Reconnect programs were selected for analysis. The reasons for selection of these is explained in section 2.6.
6.1 Communities for children (CfC)
sectionThis is based on the evaluation of the Strongerrep (FaHCSIA, 2009). CfC is one of the major Au
Families and Communities Strategy ort stralian Government investments in
CEA evaluation can also .
Underdisadvcomm ildhood development. CfC was one of three
munities, which is not
conducted in 2008, approximately one year after CfC program activities were under way.
, child and parent physical health, children’s experiences of emotional and behavioural problems, children’s prosocial behaviour, children being overweight, and parents’ mental health;
families. It has already been shown to be efficacious, and the determine at what cost its effective outcomes are achieved
The CfC program was an initiative funded by the Australian Government from 2004–2009. The program aimed to:
■ improve coordination of services for children 0 to 5 years and their families;
■ identify and provide services to address unmet needs;
■ build community capacity to engage in service delivery; and
which ■ improve the community context in children grow up.
the CfC, FaHCSIA funded non‐government organisations as ‘Facilitating Partners’ in 45 antaged geographic areas around Australia to develop and implement a whole‐of‐unity approach to enhancing early ch
models of service delivery funded under the Australian Government’s Stronger Families and Communities Strategy (SFCS) 2004–2009.
Most of the outcomes targeted by CfC are included as LSAC variables within Access Economics’ model (Table 6.17). The main exception is building child‐friendly comdirectly related to family functioning.
FaHCSIA (2009) presented the results of the evaluation of the short‐run impacts of the CfC initiative on child, family and community outcomes. The evaluation study was based on a three‐wave longitudinal study of 2,202 families living in 10 sites that had a CfC program and five sites that did not have a CfC program but were in other ways comparable to the CfC sites (contrast sites). The study had a large sample, representing 42 per cent of the population of 2 year‐old children in 10 CfC sites and five contrast sites at wave 1. Follow up (wave 3) was
The effects of the CfC initiative were estimated using statistical techniques that allowed child, family and community outcomes in the CfC sites to be compared to what they would have been in the absence of the CfC intervention (using outcomes in the contrast sites). The outcomes measures related to four priority areas:
■ healthy young families—child injuries requiring medical attention
Positive Family Functioning
53
■ supporting families and parents—harsh parenting, parenting self‐efficacy or self‐confidence, parent relationship conflict, and living in a jobless household;
needs.
The ove ositive impacts:
hildren were livi ess household;
■ parents reported less hostile or harsh parenting practices; and
parents felt more effec
t initial follow up, any impac all, given t was of short‐run effects and the i as intended to have an impact on all families living CfC sites and not just thos cessed services. As exp for many of the utcome measures, the estim s not statistically significant, which is not urprising given that any effe small in the short‐r epending on the
ated, b ds and three‐quarters of ome variables d a positive, although not necessarily statistically significant, effect.
Although non‐significa not possible to sa high level of confidence that the ind s not different from zero, wed pattern of results towards positiv rt for the conclu on that CfC has had
pacts i
The effect sizes of the es were small, be considered wh d in the early phase of Sure Start (a large‐scale
parable old
re developed programs from birth.
■ Also important is the extent to which CfC outcomes compare with alternative early
nd that most studies reported effect sizes on parenting and child outcomes that were negligible to small. It should also be noted that most of these evaluations measured
ident irrespective of whether parents and children in the CfC communities had actually received services, seems to point towards an additional effect over and above the provision of new, stand‐alone services,
■ early learning and care—children’s receptive vocabulary achievement and verbal ability, and the quality of the home learning environment; and
■ child‐friendly communities—parents’ involvement in community service activities, the level of support parents receive from others to raise children, the quality of the neighbourhood as a place to raise children, parents’ sense of community social cohesion, their perception of the quality of facilities in the community, and the level of unmet service
rall conclusion is that, on balance, there is evidence that CfC had the following p
■ fewer c ng in a jobl
■ tive in their roles as parents.
A t of CfC was expected to be smntervention w
hat the evaluation
in e who directly ac ected, o ated impact of CfC was cts were likely to be un. Dstatistical model estimindicate
etween two‐thir the outc
■ nce means that it is y with aividual effect wa the skee effects provides suppo si
some positive im n the short‐run.
■ CfC impacts on all outcom but can positive relative to at was observearea‐based initiative in the United Kingdom). The current results were also comin size to those found in the later impacts evaluation of Sure Start, where 3 year‐children were exposed to mo
childhood interventions that target specific client groups and seek to enhance child outcomes through other processes, such as centre‐based programs, home visiting programs, case management interventions and parenting programs. Wise et al (2005) fou
outcomes for children who were directly enrolled in the program, whereas CfC is aimed at improving outcomes for children in the whole community.
The fact that the effect sizes of CfC were comparable to, if not greater than, many alternative early childhood interventions, and that these effects were ev
54
possib d/or other enhancements to the community context in which children develop.
6.1.1
LSAC categories used as interim variables in this report e used as p in FaHCSIA (2009): emotional social problems, (obesiverbal ability (learning outco Four more C riables ‐ hcipline), parental self‐efficacy, tal mental he (depressio
esion) are as inputs to t her two intvariable, quality of th e learning environment (par
as an into the lear outcome ine (Table 6.17).
17: Communities for Children target s and related LSAC
LSAC variable
ly as the result of a better coordinated local system of early childhood services an
CfC outcomes
Three of the fivefor variables modelled
can b overweight
roxies ty) and
and vocabulary and mes). fC va ostile parenting (harsh dis paren alth n) and parental relational conflict (family coh used he ot erim outcomes. The last CfC e hom ental involvement in education at home) is used variabl
input ning terim
Table 6. area variables
Priority area Outcome modelled
Healthy young families Child injuries ‐
Child physical health ‐
Child emotional and behavioural *asdqta development
Child overweight *cbmi
Parent general health ‐
Parent mental health *ak6
Supporting families and parents
Hostile parenting *ahostc
Parenting self‐efficacy *pa01a
Parental conflict *re06a
Living in jobless household ‐
Early learning and care Vocabulary and verbal achievement *wlrnoi
Home learning environment *ahactd
Child‐frie communities Various ndly ‐
Note: Variables in bold are mapped to LSAC dependent variables. Variables in normal font (not bold) are explanatory variables. Variables with dashes do not occur in our model as the literature review did not support them as being significant for our model. Source: FaHCSIA (2009).
All of the relevant outcomes of the CfC, as modelled in FaHCSIA (2009) had the expected signs (that is, they were all improvements.) The LSAC sample includes 364 children who were also participants in the CfC program. The data were drawn from the K1 cohort to match these children.
By comparing CfC effect sizes against LSAC averages for the same variables, it is possible to estimate the magnitude of the average improvements under the program (Table 6.18).
Positive Family Functioning
55
Most of the e smallest effects were on child outcomes – but they were still all positive.
Table 6.18: Outcomes of dre
Domain CfC
outcomes
LSAC standarddeviation
Improvement
substantial effects from CfC were improvements to parenting10. Th
Communities for Chil n variables used in this report
s1
Hostile parenting ‐0.14 10.9% 1.28 ‐
Parenting self‐efficacy 0.11 0 13.1% .84
Parent mental health ‐0.07 12.5% 0.56 ‐
Quality of the home learning environment 0.02 0.56 3.6%
Parental relationship conflict ‐0.02 0.84 ‐2.4%
Child t(SDQ)
‐0.9% otal emotional and behavioural problems ‐0.04 4.68
Child o ‐2.5% verweight ‐0.04 1.59
Recepability
‐2.0% tive vocabulary achievement and verbal
‐0.19 9.73
Source: FaHCSIA (2009). Note: Variables in bold are mapped to LSAC dependent variables. Variables in normal font
of this investment was spent on service delivery, with Community Partners (the local service provider that delivered the services/activities) receiving 60% of the funding, Facilitating
the economic benefits and costs under a scenario with the
in the le affected by each outcome. Under the CFC, the resulting reductions in
ble 6.19, along with the intervention effect in percentage terms. The net
(not bold) are explanatory variables. 1 Obtained from LSAC database observations on CfC children.
6.1.2 CfC costs
The cost of funding CfC over the four years from 2004‐05 to 2008‐09 was $142 million. The majority
Partners receiving 7% of the funding and 3% was used for local evaluation. The remaining 30% was for community resource funding (development, implementation, project management and community development).
Based on the number of 0 to 5 year olds in each CfC site in 2006 (n=28,810), $840 was spent on each 0 to 5 year‐old child living in the CfC communities between 2004–05 and 2007–08. This four year period was thus selected for the costing – estimated as 4/5ths of $142 million or $113.6 million.
6.1.3 Cost benefit results
The difference betweenintervention and one without was estimated by using an incidence approach i.e. the difference
number of peopthe incidence of negative outcomes and the increases and improvements in positive outcomes are shown in Taeconomic gains between the scenario and the ‘base case’ (no intervention) were evaluated to determine the intervention’s overall return on investment.
a 2% change. 10 Defining substantial here as roughly
56
The total financial benefits represent discounted social and economic savings associated with improvements in outcomes attributable to CFC over the life of each individual. Consequently, the benefits were estimated to be $541.4 million, or $135.4 million per annum (assessed over 2004‐05 to 2007‐2008).
Table 6.19: Outcomes of CfC as delivered over 2004‐05 to 2007‐08
Intervention effect* (change in incidence rate compared with no intervention)
Difference in the number of people affected
Obesity ‐22.44% ‐8,546
Productivity (yr 12 completion) 1.42% 804
y and Depression ‐0.87% ‐46
cial ‐0.01% ‐1
Anxiet
Antiso
Addictions ‐0.5% ‐47
Source: Access Economics (2010). * The intervention as modelled targets children aged 0‐1 years.
Given the cost of funding over four years 2004–05 to 2007–08 was $113.6 million (Section 6.1.2), the average annual cost of the program was therefore $28.4 million per year. As a result, the total benefit cost ratio of the CfC program was calculated to be 4.77, suggesting a 377% return on investment from the CfC program.
6.2 Positive Parenting Program (PPP)
PPP is one of the best evaluated programs targeted at improving family functioning and outcomes for younger children. While its efficacy is well‐proven, there are fewer studies on its
A can also act as a tool to test/triangulate the power of the
discipthe taperiod e
ope of the interventi
11
o promote the development, growth, health and social competencies of children and
cost effectiveness and this CEmodel.
Developed at the University of Queensland, the PPP (also referred to as ‘Triple‐P’) is a multi‐level system of parenting and family support. It can be provided individually, in a group, or a
‐directedself format. It incorporates five levels of intervention on a tiered continuum of increasing strength for parents of children and adolescents from birth to age 16. The multi‐
linary nature of the program allows utilisation of the existing professional workforce in sk of promoting competent parenting. The program targets five different developmental s from infancy to adolescence. Within each developmental period, the reach of th
intervention can vary from being very broad (targeting an entire population) to quite narrow (targeting only high‐risk children). The PPP enables practitioners to determine the sc
on given their own service priorities and funding.
The aims of PPP are:
■ Tyoung people.
t/?pid=65 11 http://www26.triplep.ne
Positive Family Functioning
57
■ ent protective and nurturin for children.
independenc hancing paren ge,
competence, and self‐sufficiency of pa raising n.
ness.
nt; positive learning en and taking care of self as parent. The
■ Level 1 – provides universal access to parenting information through print and electronic media. l aim aw ne ng resources,
e parent participation in PPP create a sense of optimism
Level 2 – or tw pri health sessions th ovides pdevelopmen to parents who h h problems.
eets and videotapes are commonly used t this leve
Level 3 – Fo imary re intervention sessions for ren hildren ilmoderate beh u ems ions p id e sk ning for parents.
nsive program of eight to ten sessions that are either individual sessions,group base self‐directed. level is paren of children with sbehaviour p ms
n enhanced behavioural family intervention program for parents whosedifficulties mplicated by r issu h as r tion rdepression le refor gets ly ting but also distressing
ional reactions (including depression, anger and via cognitivebehavioura iques.
PPP m
has been th ect of zen eer‐reviewed journal art the .rity of the dependent variables ana been reported
ood problem solving skills (which is similar to the dependant variable
■ PPP also targets health, of which obesity is a factor. Again, no studies were found that reported on obesity directly, but a number of input variables have been studied.
To promote the developm of non‐violent, g environments
■ To promote the e and health of families by en ts' knowledskills and confidence.
■ To enhance the resourcefulness rents intheir childre
■ To reduce the incidence of child abuse, mental illness, behavioural problems, delinquency and homeless
PPP is prevention oriented, multi‐disciplinary and has five levels. The program has been developed through over 20 years of clinical trials. Five different developmental periods are targeted at each level – infants, toddlers, preschoolers, primary school aged children and teenagers. The program aims to promote parental competence and enable parents to become independent problem solvers. Five key principles of parenting – safe, engaging environme
vironment; assertive discipline; reasonable expectations program has five levels, as outlined below.
This leve s to increase community are ss of parenti encourag and .
■ One o mary care at pr ‘antici atory tal guidance’ ave c ildren with mild behaviour
Parenting tip sh a l.
■ ur pr ca pa ts of c with m d to avio r probl . The sess rov e activ ills trai
■ Level 4 – Inte d or This for ts more evere roble .
■ Level 5 – A are co othe es suc ela ship conflict and pa ental . This vel the e tar not on paren skills
parental emot stress) l techn
6.2.1 outco es
PPP e subj do s of p icles over years The majo LSAC regression in this lysis have directly in Australian PPP studies (Table 6.20).
■ PPP targets childhin the productivity regression (learning outcomes). While the literature search did not uncover any quantitative reporting for this outcome, several input variables (or common psychological variables that can be used as proxies for input variables) were reported.
58
Table 6.20: PPP target areas and LSAC variables
PPP target LSAC measure LSAC variable
Parental Sense of Competency Parental self‐efficacy *apa01a (PSOC)
Dyadic Adjustment Scale Family cohesion *re06a
SDQ emotional score SDQ emotional score *aemot
SDQ conduct problems SDQ conduct problems *aconda
ECBI SDQ total score *asdqta
Parental depression Parental anxiety and depression *ak6
Parental laxness1 Consistent parental discipline *pa01a
Parental overreactivity1 Hostile parenting *fhostc
Parental verbosity1 Inductive reasoning *areas
Note: Text in bold indicates LSAC regression dependent variables. 1 – these three variables are often reported upon collectively as the Parenting Scale (PS).
Sanders et al (2 all five stages of PPP for four to seven year old Australian children with follow up at two years. The authors found (Table 6.21) that PPP produced substantial improvem emotional difficulties
SDQ (b ch nt re in parental depression (26. es n con
T Impact of larg le Queensland trial
Control Tarones χ2 Sig
008) conducted a large scale (n = 3,000) controlled evaluation of
ents in SDQ ildren, and significa
o better, in the(by 17.6%) and total difficulties
2%). All of thy 21.6%) in
e worsened, or gotductions
trol groups.
able 6.21:
PPP
e sca PPP
% Clinical 95%CI ical OR %CI OR % Clin 95
SDQ emotional
Pre 15.3 1 0.653 12.1 1 909 4.96 26 0. 9* 0.0
Post 12.6 0.988 13.4 1.128 1.398 0.803*
SDQ conduct problems
Pre 18.7 0.685 16.8 1 661 0.0 0.85 1 0. 36
Post 16 1.001 14 .806* 0.822 0.828
SDQ total difficulties
Pre 13.9 1 0.608 9.7 1 0.855 4.783* 0.029
Post 10.9 .757* 0.941 10.4 1.085 1.37
Parental depression
Pre 26.70 1 .570 19.10 1 0.802 7.673* 0.006
Post 19.70 0.676 .802 18.60 0.963 1.157
Parenting consistency
Pre 91.10 1 .808 86.10 1 0.915 0.243 0.622
Post 91.40 1.04 1.34 87.50 1.13 1.397
Parental confid ence
Pre 99.70 0.148 61 1 99.50 1 0.263 0.193 0.6
Post 99.40 1 1.634 30 0.694 27 0.49 99. 1.8
Note: * indicates signSource: Sanders et a
ificant difference (at p=0.05) betw tervention and co oups. l (2008).
een in ntrol gr
Positive Family Functioning
59
De Graaf et al (2008) conducted a meta analysis on the impact of PPP Level 4 on two parenting first, Parenting Scale (PS) is a of laxne (inconsistent ne),
ity (harsh pare ) and verbosity uctive reasoni 12. The second, Competency (PSOC), approximates the LSAC variable Parental self‐efficacy. The
weighted e effect sizes 8 for PS and for PSOC, bo hich ated to be large.
PPP trial in Western icipants in the intervention group and the control group. This was
randomised risk
Attribute R
t Me
clinical e)
Estimated ffect
a onths
Implied improvem
factors. Theover‐reactivSense of
nting
composite (ind
ss ng)
discipli Parental
authors found averag of 0.6 0.65 th of wwere st
Zubrick et al (2005) conducted a large, community based Level Four Australia with over 800 partnot a trial, as the intervention was targeted towards at families (as measured by likelihood of having clinically significant issues), but it was a controlled trial. Results were reported immediately after the intervention and at 12 and 24 months. In all cases there were significant positive results directly after the intervention, and most of these gains were still preserved after two years. Not all of the measures used in the study had direct LSAC equivalents that used in our model, so closest substitutes were chosen. On this basis, child social and emotional problems, parental depression and family cohesion all recorded improvements equivalent to ten percent or better. As the authors reported means for the intervention group, the implied improvement in (Table 6.22) is simply the estimated intervention effect as a proportion of the mean.
Table 6.22: Impact of large scale Western Australian PPP trial
elevant LSAC equivalen
an (% in rang
intervention et 24 m
ent
Parental depression Parental depression
16.2 4.41 27.2%
Marital satisfaction Family Cohesion 10.0 0.73# 7.3%
Parental laxness Inconsistent discipline
8 % 39.6 0.3 1.0
Parental over‐reactivity
3 %
Hostile parenting
69.5 0.3 0.5
Parental verbosity Inductive reasoning
40.6 9 % 0.2 0.7
Eyberg Child Behaviour Intensity
92 %
(ECBI)
SDQ total problems
121.6* 12. 10.6
Notes: *ECBI mean is a score, not percent in clinical range, # Abbreviated Dyadic Adjustment Scale.
demonstrated P is cultures. For example, Bodenmann et al (2008) in a smaller n c l (n = 50 families) found significant improvements in parenting,
Source: Zubrick et al (2005).
While the focus of this report is on Australian parenting, several studies havethat PP effective in otherEuropea ontrolled triaparental esteem and child misbehaviour, most of which were maintained after 12 months.
12‘Inductive reasoning’ as recorded by LSAC often had counter‐intuitive results, so it is possible that what parents think of as inductive reasoning may in fact be closer to what clinicians would describe as verbosity.
60
Table 6.23: Impro ropean PPP trial
Post‐trial s % change
vement in means scores of Eu
Topic Pre‐trial After 12 month
PS laxness 5 13.2 12.3 12.3% 13.
PS over 24.7 18.7 21.0 reactivity 15.0%
Parental self e
26.9 28.7 28.8 7.1% fficacy
EC s 7.2 104.7 99.9 1BI problem 11 4.8%
DA
6.3 111.0 109.6 3yadic djustment Scale*
10 .1%
Note *measures quality of the couple’s relationship, approximates LSAC family cohesion.
ere available (SDQ emotional and total scores, parental anxiety and depression), as this was the largest study and Australian. Variables from the
Au second preference (used for family cohesion, parental parental over‐reactivity and parental verbosity), as this study was also Australian, and
than the total score so it is probably that the conduct score at least reflected the total score (or more).
variable improvement WA EU
Source: Bodenmann et al (2007).
Table 6.24 shows the outcomes of PPP variables that were used in the modelling. Variables from Queensland study were used wh
Western stralian study were the laxness,larger than the European study. Note, however, that the effect sizes for laxness and over‐reactivity were much smaller in the Western Australian study than in the European study. The European study provided the inputs for parental self‐efficacy. The SDQ conduct problems score was based on the total score, since the emotional score was less
Table 6.24: Outcomes of PPP variables used in this analysis
PPP outcome Model concept Specific % QLD
ParenCompetency (PSOC) efficacy
tal Sense of Parental self‐ *apa01a 7.1% n/s n/a 7.1%
Dyadic Adj st nt Scale
Family co %u me
hesion *re06a 7.3 n/a 7.3% 3.1%
SDQ emotional score SDQ emotional score
28.4% 28.4% n/a n/a *aemot
SDQ conduct SDQ coproblems problems
nduct
*aconda 28.8% n/s n/a n/a
ECBI SDQ total score 28.8% 28.8% .6% 14.8% *asdqta 10
Parental depression Parental anxiety and 23.6% 23.6% .2% n/a depression
*ak6 27
Parental laxness Consistent parental *pa01a 1.0% n/s% 1.0% 12.3% discipline
Parentreactiv
0% al over‐ity
Hostile parenting *fhostc 0.5% n/a 0.5% 15.
Parent % n/a al verbosity Inductive reasoning *areas 0.7% n/a 0.7
Source: Based on Table 6.21, Table 6.22 and Table 6.23. QLD=Queensland. WA = Western Australia.
Positive Family Functioning
61
6.2 PPP costs
et al (2005) report that cost effectiveness analyses of PPP have found that that its costs rson range from 75c at Level 1 to $422.45 at Level 4. Foster et al (2007)
.2
Wise per pe reported the
Table 6.25: PPP costs ($US)
following estimated costs of PPP, by level, in the United States (Table 6.25). As an overall average, the authors estimated the costs of PPP were $US11.27 per child.
Level Provider costs
Participant costs
Attending Preparation Total Grand Total training
Primary care 707 500 32 532 1,239
L4 Group 719 726 44 769 1,488
L4 Standard 740 800 57 857 1,598
L5 Enhanced 660 587 18 605 1,266
Mihalopoulos et al (2007) state that the cost of implementing PPP in Queensland to 572,701
Cost benefit results
no intervention)
e number of people affected
children aged between 2 and 12 years of age (315,378 families) was A$19.7 million (Level 1, $240,000; Level 2, $5.8 million; Level 3, $5.7 million; Level 4, $4.4 million; Level 5, $3.6 million) with an average cost of $34 per child.
6.2.3
Similar to CfC in section 6.1.3, the difference between the economic benefits and costs under a scenario with the PPP intervention and one without was estimated using an incidence approach, and was based on the costs from the Queensland study as presented above. The change in outcomes and intervention effects are shown in Table 6.26.
The net economic gains between the scenario and the ‘base case’ (no intervention) were evaluated to determine the intervention’s overall return on investment. The benefits were estimated to be $68.1 million per year (assessed over 2004‐05 to 2007‐2008).
Table 6.26: Outcomes of PPP as delivered over 2004‐05 to 2007‐08 in Queensland
Intervention effect* (change in incidence rate compared with
Difference in th
Obesity 0.00% 0
Productivity (yr 12 completion) 0.00% 0
Anxiety and Depression ‐0.69% ‐161
‐0.13% ‐96 Antisocial
Addictions ‐1.02% ‐266
Source: Access Economics (2010). * The intervention as modelled targets children aged 4‐5 years.
62
Given the cost of the intervention in Queensland over the four years 2004–05 to 2007–08 was $19.7 million, the average annual cost of the program was therefore $4.925 million. The total benefit cost ratio was therefore calculated to be 13.83, suggesting substantial 1, a 283% return on investment from the PPP program.
6.3 Reconnect
The Reconnect program aims to assist
who are homeless, or at risk of homelessness, and a number of specialist Reconnect services including
Indigenous, Culturally and Linguistically Diverse (CALD), Mental Health, Gay, Lesbian,
homeless or at risk of homelessness through the Newly Arrived Youth Specialist Services.
me’ rate (where appropriate) is available to young people who are
clude counselling, group work, mediation and practical support and are
h as specialised mental health services. Services are provided where the client is most comfortable, such as in homes, schools, and other sites in the community.
munity service
■ young people aged 12 to 18 yearstheir families. This includes
Bisexual, Transgender, Intersex and Newly Arrived Youth specialists; and
■ young people aged 12‐21 years who have arrived in Australia in the previous five years, focussing on people entering Australia on humanitarian visas and family visas, and who are
The objective of Reconnect is to assist young people to stabilise their living situation13 and improve their level of engagement with family, work, education, training and their local community through:
■ using family focussed early intervention strategies to achieve family reconciliation;
■ improving coordination and integration of services delivered by government and the community sector; and
■ working with Centrelink, young people, and their parents to ensure that income support at the ‘away from hoproperly entitled to it (FaHCSIA 2003a).
Reconnect services inprovided to the whole family. Reconnect providers also 'buy in' services to target individual needs of clients, suc
The program is funded by FaHCSIA and services are delivered by (generally) non‐government organisations. Participants may be self‐referred or referred from a range of sources, including: schools, education and training organisations; parents or family; community agencies; Centrelink; juvenile justice; police; child protection agencies; accommodation services; specialist services, such as English language centres; and state/territory comdepartments.14
g/funding/reconnect/recon_operation_guidelines/Pages/2_overview.aspx accessed August 2010
13 The aim is to achieve family reconciliation, wherever practicable, between homeless young people, or those at risk of homelessness and their family. Family reconciliation outcomes include: the young person returns home; ongoing positive family relationships are created which provide the young person with emotional and physical support; reconciling the young person with other family members e.g. grandparents or siblings; both parent (s) and the young person accept that independence is appropriate for the young person; and establishing a viable support system for the independent young person that includes a member of his/her family (http://www.fahcsia.gov.au/sa/housing/funding/reconnect/recon_operation_guidelines/Pages/2_overview.aspx accessed August 2010).
14 http://www.fahcsia.gov.au/sa/housin
Positive Family Functioning
63
Reconnect services are located in areas of high need having regard to factors such as the size of the adolescent population, indicators of socio‐economic disadvantage, particularly vulnerable population groups such as Indigenous people or newly arrived refugees or immigrants from non‐English speaking backgrounds, the range of other services in a region and
ere are Reconnect services located in major metropolitan tre
typica
Recon lia. In
tudies were conducted on Reconnect in 2001 and 2002 (reported in 2003) — a
ng
geographic location. As a result, thcen s, rural towns and more remote locations (FaHCSIA 2003). Reconnect services are small,
lly employing two to three practitioners with some administrative support.
nect services are located in disadvantaged communities throughout Austra2008‐09, there were 101 services, and around 5,215 cases15. The data available suggests activity each year between 2004‐05 and 2008‐09 was as follows:
■ 2004‐05: 6,301 cases;
■ 2005‐06: 6,025 cases;
■ 2006‐07: 5,890 cases;
■ 2007‐08: 6,078 cases; and
■ 2008‐09: 5,215 cases.
6.3.1 Reconnect outcomes
Two evaluative scommunity study investigating service structures and whether these had changed in accordance with Reconnect objectives, and a longitudinal survey of Reconnect clients which aimed to assess the potential benefits of Reconnect on the lives of young people and their parents.
The community study (FaHCSIA 2003a) investigated 12 Reconnect services over a one‐year period (end 2001 to end 2002) to assess their contribution to an improvement in community capacity for early intervention around youth homelessness. The 12 services were selected to be reflective of the broader Reconnect program, and were located in remote, rural and urban locations and included specifically targeted as well as generalist services. The study concluded that the 12 services had a significant impact, relative to their own capacity, on buildicommunity capacity for early intervention for youth homelessness in three key ways:
■ by building community infrastructure for early intervention for example, by improving access to services and through training of service providers, community members, parents and clients;
■ by strengthening service networks, collaboration and resource sharing between agencies; and
■ through assisting other organisations to have a greater focus on effective early intervention.
15 When a client engages with a service, a case is commenced for that client. The case work will involve providing whatever services that client needs. The case can continue to deal with the initial issues and/or any issues identified while working with the client. The case is closed when: a) all issues are resolved, ie as mutually agreed by the worker and the client, or b) can be closed if either the worker or the client feels that is appropriate. c) If a client does not have contact with the service for over 30 days, the case can also be closed. A new case would be opened if the client comes back to the service after the previous case has been closed. A new case cannot be created if there is an open case for that client.
64
The longitudinal survey (FaHCSIA 2003b) was sent to selected clients at two points in time, around 10 months apart. The first wave of the survey commenced in November 2001 and the second wave was administered in October 2002. At each time point, both new clients and clients who were exiting Reconnect were surveyed. 1,001 cases participated — 516 new
Cases could consist of a young person only,
■
■ es were received for 260 cases—this represents a
ificantly across entering and exiting client groups. It is
in conflict management are lasting, and indeed increase over time.
clients and 485 whose support period had ended. adult(s) only (in most cases, parents), or both a young person and adult(s).
In the first wave of the survey, responses were received for 455 cases, making an overall case response rate of 45.5%. The response rate for exiting cases (46.0%) was slightly higher than for entering cases (45.0%).
In the second survey wave, responswave 2 response rate of 57.1%. The response rate for entering cases (59.1%) was higher than for exiting cases (55.2%).
The longitudinal survey concluded:
■ There was no difference in the extent to which entering and exiting clients were participating in employment or education at wave 1. As entering clients are used as a de facto control group, this suggests that Reconnect intervention has little immediate impact on improving young people’s participation in education or employment.
■ Self‐reported school performance, interest in school, perceived importance of school subjects, expectations of educational attainment, and psychological sense of school membership did not vary signdifficult, therefore, to conclude that Reconnect significantly improves clients’ connectedness to employment or education using the measures studied.
■ There was a significant improvement across time in the extent to which young people felt liked and respected at school, which could not be explained by sex, age or case complexity. It is difficult to conclusively attribute this to Reconnect. However, clients were also asked separately about the impact of Reconnect, and the finding from the longitudinal survey is consistent with young clients’ self‐reported impact of Reconnect on how they feel about themselves, their school, and their ability to deal with their teachers.
■ Young people responding to wave 2 of the survey reported improvements in their own ability to manage family conflict. About two thirds of respondents rated their ability in this area as poor or very poor before entering the Reconnect program, but just 16% felt their ability was poor or very poor after receiving Reconnect support. The proportion who felt they had good or very good skills in managing family conflict increased from 12% before Reconnect to 44% after Reconnect. Young people also reported that their family, as a whole, was better able to manage conflict after Reconnect. Those rating their family’s abilities as good or very good increased from 14% to 37%. Exiting clients reported higher levels of improvement than entering clients, suggesting that improvementsSimilar levels of improvement in conflict management were also reported by parents.
■ Respondents reported positive shifts in communication between family members. About 7% of young people and 2% of parents felt their family communicated very well
Rebefore receiving connect support. Comparable figures reported at the time of the wave 2 survey were 17% and 13%. No significant difference was found in changes in communication between entering and exiting clients.
Positive Family Functioning
65
■ Among young people, although there was no significant impact of Reconnect found for family closeness or attachment to parents (measured by three scales of Trust and communication, Alienation, and Relationship with father), parents as a whole
epression and anxiety’ across the two
■ The extent to which parents felt their child was likely to engage in undesirable social behavi of entering and exiting parents, suggesting little, if any, impact by Reconnect services. However, it
d that li Avera th ering and exiting parents on the index of parental‐assessed lik f children
able 2.35, respectively out of a
IA, 2003c) concluded that:
t in the stability of young people’s living situations — Young temporary situations fell from 16.5% at Reconnect’s initial intervention m the ntion also increa stability of
ople’s living situations in relation to parents—young people living with parents a ort, ase which
ross all age categories.
en ic r nal survey above.
■
e evaluation found that, for the
ng been expelled. The longitudinal study found a significant improvement over time in the extent to which young people felt liked and respected at school.
experienced a significant decline in feelings of ‘dwaves. There were no statistically significant differences between exiting and entering clients, or between wave 1 and wave 2 clients in response to scales administered relating to ‘depression and anxiety’ and ‘self‐worth and coping’.
ours was also examined. There was no difference in the assessments
should be note ttle improvement was to be made. ge scores for boent elihood oengaging in undesirpossible 10).
The final report (FaHCS
■ There was improvemenpeople living in
behaviours were very low (2.39 and
to 5% at exit froyoung pe
services. Reconnect interve sed the
increased from 57.5% was found ac
t the start of support to 62% after supp an incre
■ There was improvemthe longitudi
t in young people’s ability to manage confl
t — as reported fo
■ There were improvements in communication within families — Young people and parents reported improvements in communication following the Reconnect intervention. The proportion of young people who felt their family communicated well increased from 22% before Reconnect intervention to 41% afterwards. Parents’ reported improvement was more pronounced: the proportion of parents reporting their family communicated well or very well increased from 11% before Reconnect intervention to 42% at the second survey. Parents reported feeling increased closeness with their children and less alienation after Reconnect intervention, although this effect was not sustained over time.
Improvements in young people’s attitudes to school — The majority of young people using Reconnect services were in full‐time education (76%) — a participation level which was unchanged by Reconnect intervention. However, thmajority of young people using Reconnect, experience of school was not a happy one. Reconnect clients tend to change school frequently: 52% of young people had been at their current school for less than two years. Just over one third of young people (36%) reported being bullied, 18% saying that it happened on ‘most days’; more than half (53%) of the young people surveyed reported hating school often or almost always; 43% reported having been suspended and 10% havi
■ Improvements in engagement with education and employment — The proportion of young people employed full time or part time increased from 2% at the start of support to 5% at completion. The proportion of young people who were not in education,
66
training or employment dropped from 15% at program entry to 11% at exit. Educationand unemployed (looking for work) statu
participation rates s remained unchanged. However, in the light of the findings on case complexity of Reconnect clients,
g people’ education can be vie s a positive achievement.
■ Engagement with com though s orted im in youn ple’s agement wit commu ere found, o easures u the longitu
study to track increases in ation in com y activitie nd no signiimprovements over time.
Clients’ views o — e quarters o ng peopl parents repall improvement in the s n that led t Recon ore than h
e (55%) and parents attribut lot’ of this improvement tontervention.
P d
Based pselecttable.
Evaluavariab
maintaining youn s participation in wed a
munity — al elf‐rep provements g peoeng h the nity w ther m sed in dinal
particip munit s fou ficant
■ f outcomes Thre f you e and orted over ituatio hem to nect. M alf of young peoplReconnect i
(52%) ed ‘a the
AT ata for the Reconnect cost effectiveness analysis
on the findings of the evaluation, ATP variables relevant to the Reconnect rogram were ed (see Table 6.27). The method for estimating the effect sizes is described after the
Table 6.27: ATP variables associated with the Reconnect Program
tion outcome le
ATP variable(s) tested in regressions Effect size on FF variable
Youngschoolwagginexpulsion, hated school, cnot respect students)
people's attitudes to (school changes, g, suspension or
School bonding (positive affect towards school)
18.6%
urriculum irrelevant, teachers
Young people's ability to Conflictual relationships 55% manage conflict
Communication within families and family closeness
nt to enti 37%Attachme parents, harsh par ng
Engagementployme
with educat nt
Unde ement (young in education training and no nt)
nservatively
ionand em
r‐engag adult not or t in employme modelled
Co not
Source: Australian Governm Department and Community (2003)
School bonding: e longitudi rvey of Reco ents m clients’ seng to school (or students’ in across
ensions (FaHCSIA, 2003b:5 espect and (school membership concets get along with, and are viewed ir peers) and elongingne
a given student feels they ‘fit in’ to the school. There was a significant difference in mean scores on the ‘respect and affect’
not reported. While scores on the ‘belongingness scale’ did not vary significantly
ent of Family Services
■ Th nal su nnect cli easured the
se of belongindim
psychological3): ‘R
membershipaffect’
school) two rning
how studen by, the ‘b ss’ (a more internal measure of the extent to which
scale across time (scores on this scale increased from wave 1 to wave 2), across all categories of client status, age, sex and case complexity. However, the effect size was
between the two waves, there was a significant effect for cases classed as medium
Positive Family Functioning
67
complexity16 where the mean increased from 5.06 in wave 1 to 6.00 in wave 2. The effect size was therefore modelled as 6/5.06‐1 = 18.6%.
■ Conflictual relationships: The longitudinal survey found that young people perceived an improvement in their ability to manage family conflict before Reconnect and when
, 2003b). While the extent of the change was derived and clear (see the reporting around the analysis of variance,
surveyed (‘now’) (FaHCSIAreported, the units were notFaHCSIA. 2003b:70). Hence, we used data from the report shown in Table 6.28 to estimate an effect size of 55% (3.326/2.144‐1).
Table 6.28: Estimate of effect size — young person’s perception of their ability to manage family conflict before Reconnect and now
Likert scale categories Before Reconnect Now
% survey ts
Score multiplied by %
% survey respondents
Score multiplied by % responden
Very poor 1 35.0% 0.350 6.8% 0.068
Poor 2 30.7% 0.614 9.3% 0.186
OK 3 22.7% 0.681 39.5% 1.185
Good 4 8.6% 0.344 33.3% 1.332
Very good 5 3.1% 0.155 11.1% 0.555
Weighted average 2.144 3.326
Source: FaHCSIA (2003b:76) and Access Economics calculations.
■ s
for young people who connect and those who were exiting Reconnect.17 However, increa % . communica ely
family’s ability to resol , and is also th reduce harsh parenting, to the extent th is indicative of and associated with poorer mmunication. As such, we h d a proxy for attachment harsh parenting
similar t for conflictual relationsh ere the child’s eir family’s abili manage conflict is utilised a proxy for intra‐
lial attachment, in the absen a more specific direct effec and given the ficant improvement in com ion and parental wellbeing d. We used data the report shown in Table 6.29 to estimate an effect size of 37% (3.070/2.234‐1).
Communication within families and family closeness. For ‘attachment to parents’specifically, the longitudinal survey found no significant difference between the score
were entering Regood communicationtion is considered likve conflict improvedat such parenting
sed significantly, by 86% (22% toto be related to the finding that the
ought to 41 ) Good
co ave use and based on a method o that ip, whperception of th ty to as fami ce of t sizesignifrom
municat foun
(30.3% of respondents) or high (34.9% of dents). Case managers measured complexity according to conflict with authority, physical or emotional
parent‐child attachment over time, but for young people no significant differences were found. The nature of the
16 Complexity was measured as low (34.8% of respondents), mediumresponviolence, sexual abuse, mental illness, substance abuse, disability, child protection, poverty, homelessness or living situation, living skills, and identity conflict.
17 Analysis of variance was used to examine whether Reconnect clients experienced a change in their perceived
reporting did not allow use of the means in the model.
68
Table 6.29: Estimate of effect size — young person’s perception of their family’s ability to manage family conflict before Reconnect and now
Likert scale categories Before Reconnect Now
% survey respondents
Score multiplied by %
% survey respondents
Score multiplied by %
Very poor 1 34.0% 0.335 11.6% 0.116
Poor 2 27.4% 0.548 15.9% 0.318
OK 3 25.6% 0.768 36.0% 1.080
Good 4 9.2% 0.368 27.4% 1.096
Very good 5 9.2% 0.460 4.3% 0.215
Weighted average 234 3.070 2.
Source: (2003b:76) an ics
t with education an yment w rvatively not led. Althougome variable imp % (4%/1 connectio ot through
se. be m aluating Rec overall, to int as well. Howeve is on the inte ns that lead nts which in turn provemen erim outco direct ben that bypass the FF been excl from this analysis.
The budget for Reconnect is around $20 million per year (FaHCSIA portfolio Budget papers from 2001‐02 to 2006‐07). Unpublished data from FaHCSIA suggest the average cost per case across all services and all cases in 2008‐09 was $3,800, i.e. an average of $22.4 million per annum over all cases 2004‐05 to 2008‐09. The distribution of costs per case across each service was skewed, with 50% of services having a cost per case less than $4,000 and 92% with a cost per case less than $10,000. This is likely to reflect location and case mix, together with other factors.
6.3.3 Cost benefit results
Similar to CfC and PPP, the difference between the economic benefits and costs with and without Reconnect was estimated using an incidence approach, with the change in outcomes and intervention effects shown in Table 6.30.
The net economic gains between the scenario and the ‘base case’ (no intervention) were evaluated to determine the intervention’s overall return on investment. Benefits were estimated to be $40.6 million per year (assessed over 2004‐05 to 2008‐09).
FaHCSIA d Access Econom calculations.
Engagemen d emplo as conse model h this interim outc roved 27 5%), the n was n family functioning variables per A case could ade in ev onnect clude this benefi r, as this analysis focused rventio to FF improveme
nectlead to imdomain
ts in intuded
mes, the efits of Recon have
6.3.2 Reconnect costs
Positive Family Functioning
69
T able 6.30: Outcomes of the Reconnect Program, as delivered over 2004‐05 to 2008‐09
Intervention effect (change in incidence rate compared with no intervention)
Difference in the number of people affected
Obesity ‐6.73% ‐377
Productivity (yr 12 completion) 13.68% 1,690
Anxiety and Depression 0% 0
Antisocial 0% 0
Addictions ‐1.18% ‐18
Source: Access Economics (2010). * The intervention as modelled targets children aged 12‐13 years.
With the cost of Reconnect estimated to be $22.4 million per year (Section 6.3.2), this yields a benefit cost ratio of 1.81, suggesting an 81% return on investment from the Reconnect program.
6.4 Shocking all variables – the value of PFF
A final economic shock was specified which set the values of all the consistently significant18 FF variables to their optimum values, some being maxima and others minima19 – depending on the specific relationship to the health, productivity and social outcome variables
the variables. By setting the transition variables in ATP to their optimum values,and the
coding of this equated to optimal FF in the early age groups.
The ta od in 2010 in the absence of the shock, 6.5% would be obese, 41.9% would have completed secondary school, 8.0% would have anxiety/depression, 5.2%
viours, and 19.2% would have addictions (4.3% abusing alcohol, % u d
Table 6.31: The value of PFF
ople Benefit $m
rget population was set as the population of Australian children entering adultho(313,577 people turning 19) of whom,
would exhibit antisocial beha2.3 sing illicit drugs and 12.6% smoking). The effect on each outcome from optimal FF anthe l value of the benefit is shown in Tab e 6.31 and Figure 6.7.
NPV lifetime PFF
% pecost per case effectiveness*
Obesity $51,268 ‐24.75% 6.55% 260.6
Productivity $75,414 29.06% 41.93% 2,881.7
Anxiety and depression $131,647 ‐17.66% 7.97% 581.1
Anti‐social $462,556 ‐7.28% 5.18% 546.7
Addictions $258,883 ‐7.53% 19.23% 1,175.5
Total 5,445.7
Source: Access Economics calculations. * The maximum that PFF can affect each outcome.
18 Variables shoes coefficient signs changed across different age groups were excluded from the shock.
19 For ATP variables, maxima and minima were proxied by taking two standard deviations from the mean.
70
PFF by benefit type, 2010 (total $5.4 billion), $bn and % total Figure 6.7: Value of
261 , 5%
1,176 , 22%
2,882 , 53%
581 , 11%
547 , 10%
Obesity Productivity Anxiety and depression Anti‐social Addictions
Source: Access Economics calculations. Note: Shares may not sum to 100% due to rounding.
The outcomes for health, productivity and social costs were then compared to the base case of no shock to estimate the total value of gains from PFF in 2010 dollar NPV terms as $5.4 billion per annum.
Of the total annual benefits:
productivity gains comprise the largest component (52.9■ % or $2.9 billion per annum);
■ savings from fewer addictions comprise the second largest component (21.6% or $1.2 billion);
■ savings from fewer cases of anxiety and depression are 10.7% or $0.6 billion;
■ reduced costs of criminality comprise 10.0% or $0.5 billion; and
■ reduced costs of obesity represent 4.8% or $0.3 billion per annum.
Positive Family Functioning
71
7
The s we believe, the
ve and detailed ‘cost of
t that such intervention incurs costs today as a down‐payment for discounted benefits realised a long time into the
■ In to billion per annu value of PFF gains possible. Over h gains (53%) productivity gain rther 21% of the benefits deriving savings from fewer Fewer
ion would sa .6 billion (11%), e lower rates of criminality and cial behaviour bil ctio
um (5% total).
ts accrue from:
er rates of smoking, alcohol abuse and illicit drug abuse);
ime earnings due to better secondary and tertiary education outcomes); and
erventions selected on the basis that they specifically target
■ The Communities for Children program, targeting pre‐school and primary school aged children, is one of the major Australian Government investments in families. The
Conclusions
cope of this project has been both ambitious and challenging but, methods developed and many findings and insights are of global significance. The novelty of the research inspires further work in this field that we hope can be used to triangulate these findings internationally as well as continue to enhance the evidence base in Australia.
Key findings
The main finding of this report is that positive family functioning is economically and socially valuable, and that value can be quantitatively measured using extensiillness’ methodology traditionally adopted to analyse interventions in the health sector. By demonstrating and quantifying the value of PFF, it is then also possible to systematically and consistently evaluate interventions employed by the Government and the community to enhance FF in Australia.
Value of PFF: The potential benefits of intervening in childhood and adolescence to prevent poor outcomes later in life are substantial, even (or despite) the fac
future.
tal, the potential NPV of benefits to be realised is in the order of $5.4 m in 2010 dollars. This can be considered the cost of NFF currently, or the
alf these from
are addictions.
s, with a fu cases of anxiety
and depress ve $0 whilantiso would accrue $0.5 lion (10%). A redu n in obesity would save $0.3 billion per ann of the
■ The benefi
health benefits (from lower levels obesity, anxiety and depression, and low
productivity benefits (from improvements in lifet
social benefits (from lower rates of criminality and reduced court and prison system costs).
Value of interventions to enhance FF: There are clearly marked social and economic benefits to be gained if cost effective prevention programs can be identified and implemented. This analysis has focused on three intFF in a mixture of age groups, they have reach, relevance and sustainability, and they have been previously evaluated and shown to be efficacious in the short term in improving particular aspects of FF. Moreover, these particular FF aspects were ones that, in the main, were able to be measured in our analysis of FF variables in LSAC and ATP, and were, at least in part, found to be significant factors ultimately influencing to improved health, productivity and social outcomes in early adulthood – with lifelong impacts.
72
program has been shown to improve outcomes in various FF areas including areas significant in our analysis as impacting lifelong outcomes – namely, hostile parenting, parenting self‐efficacy, parent mental health, quality of the home learning environment, parental relationship conflict, child total emotional and behavioural problems, childhood overweight, receptive vocabulary achievement and verbal ability. The benefit:cost ratio for this program was estimated as 4.8:1, a 377% return on investment.
d as 13.8:1, a substantial 1,283% return on investment.
r under‐engagement (in education and employment) and the home
ary of costs and benefits of modelled interventions
■ The Positive Parenting Program is one of the best evaluated programs targeted at improving FF and outcomes for younger children. The program has been shown to improve outcomes in FF areas significant in our analysis – namely, parental sense of competency, the dyadic adjustment scale, the SDQ emotional and conduct scales, the Eyberg Child Behaviour Intensity score, parental depression, parental laxness, parental over‐reactivity, and parental verbosity. The benefit:cost ratio for this program was estimate
■ The Reconnect program targets an older cohort of children and was found to improve outcomes in school bonding and conflictual relationships, with proxied effect sizes estimated for attachment to parents and harsh parenting. No impact was modelled for the program folearning environment, which may be conservative, since these impacts were found to be direct, rather than occurring through FF variables. The benefit:cost ratio for this program was estimated as 1.8:1, an 81% return on investment.
Costs and benefits are summarised in Table 7.32.
Table 7.32: Summ
CfC PPP Reconnect
Program cost ($m)* 113.6 19.7 112.1
Un st ($) 840/child aged 0‐5 34/child aged 2‐12 3,800/person aged 12‐21
($m, lifetime NPV) 541.4 272.4 202.8
it co
Benefit
efitBen :cost ratio 4.76 13.82 1.81
Sou : Access Economics calculations. * Costs estimated over 2004‐05 to 2007‐08 except for Reconnect which to 2008‐09.
ing the evidence b
rceextends
Build ase – critical assets and challenges
ett, 2002; Schweinhart et al, 1993, Wise et al, 2005; Weissberg et al, 2003) there has historically been little investment in rigorous economic evaluation in the sector.
ic gaps in evidence of the long term benefits and cost effectiveness of programs.
prove FF provide useful tools to assist in policy choices but that ongoing emphasis needs to continue to supply evidence of individual program efficacy and effectiveness in Australia, and development of appropriate data sets and collection of longitudinal data to feed in to policy making and program development. Moreover, program
While evidence of the success of family programs is slowly growing (Nation et al, 2003; Manning et al, 2010; Katz, 2009; Aos et al, 2004; Durlak and Wells, 1997; Hawkins et al, 2009; Masse and Barn
Wise et al (2005) concluded there are specif
The analysis in this report provides further confirmation that current economic methods for comparing interventions to im
evaluation needs to have a greater focus on the inputs required for economic analysis.
Positive Family Functioning
73
Th p in economic evaluation has meant that many program evaluations do not measure or concepts required for economic analysis.
e gareport An example is the Reconnect program for
of the
■ n the oldest LSAC children and the youngest ATP children TP, FF
variables remain unchanged over this gap in the modelling.
was attempting to map the impact of parenting in
family income, and parental anxiety/depression are not available. Parents’ educational achievement was used as a proxy for the former in this
Findings from the econometric analysis
orporated in the analysis were found to be statistically significant explanators of child outcomes with the relationship consistent with that
which the evaluation found substantial program related benefits (FaHCSIA, 2003b) but which did not report well on some of the key effect sizes necessary for quantitative economic analysis.
The LSAC and ATP data sets are rich and offer many avenues for research. Their complexity can potentially diminish their accessibility. There are important implications for governments in continuing to fund longitudinal data sets so that quality and accessibility endure through the maintenance of specialist and corporate knowledge about these data sets. Those managing the ATP and LSAC were extremely important collaborators for this project. Advice and inputs from the experts on the Reference Group for this project were also critical to the success of the analysis. ‘
■ Family functioning’ can be difficult to measure and LSAC and ATP variables reflect a mixture of FF and other factors which, at times, can be difficult to interpret. In addition,
there is the potential for omitted variable bias where variables do not completely capture the concept being measured or where there are missing variables within the LSAC and ATP.
■ There were a number of obstacles to overcome with the LSAC dataset, to try to consistently capture desired information (such as depression/anxiety, antisocial behaviour or addiction tendencies in babies, toddlers or pre‐schoolers). This largely arises due to the vast developmental differences between newborns and nine year olds, and means that many of the LSAC regressions had to use three different versionsdependent variable.20
■ Also, there were a few unexpected but statistically significant results. Most of these could be explained on reflection, while a small remainder were less intuitive (see Section 3.2.7).
There is a four year gap betweefor whom FF data are available. To transition between the LSAC and the A
■ Another difficulty encounteredchildhood on addictive behaviour (use of alcohol, nicotine and other drugs). LSAC has childhood FF data, but no drug use data, while the ATP has drug use data, but no childhood FF data.
■ In the ATP, variables measuring
analysis and its significance for child outcomes was demonstrated via the statistical analysis.
Not surprisingly, many of the family ‘inputs’ inc
predicted by the literature.
20 (For example, anxiety and depression is proxied by apedsgc in 0 to 1 year olds, babitp in 2 to 3 year olds, and caemot in 4 to 5 year olds).
74
■ Obesity was explained by key drivers such as previous obesity, parental obesity, lack of child persistence, and parent‐child conflict.
■ Anxiety and depression were dependent on previous emotional problems, difficult temperament, lower SES, harsh discipline, parental anxiety/depression, alienation from parents and lack of child persistence.
■ Smoking in young adulthood (19‐20 years) was determined by previous smoking in
king and initiating drinking at an older age (over 15 compared to 14 or younger). Illicit drug use in 23‐24 year olds was dependent on the child’s temperament, lack of parental monitoring, and mother smoking.
■ Predisposition to smoking, alcohol abuse and illicit drug use was established in early years by parental smoking, temperament, harsh and/or inconsistent discipline, poor family cohesion and parental anxiety depression.
■ Productivity was driven by previous learning outcomes, consistent discipline, temperament, socioeconomic status, parent education and, in adolescence, persistence, relationship quality/warmth, parental monitoring and a positive attitude to school.
■ Antisocial behaviour and outcomes were determined by child lack of persistence, previous social/conduct problems and, importantly, were largely influenced by early life FF variables such as poor family cohesion, harsh discipline, parental smoking and low SES, along with parental anxiety/depression and the child’s temperament.
There were, however, some notable exceptions.
■ An ATP variable denoting parental ‘warmth’ was inversely related to high school outcomes for children, but can potentially be understood in the context of being task‐focused, which may come across as less ‘warm’ but (without harshness) may achieve better high school outcomes.
■ None of the ATP FF variables were significant explanators of antisocial behaviour.
Areas for further research
It would be desirable in the future to bridge the gap between the age of children in the most recent wave of the LSAC and the youngest age of children involved in the ATP for which FF variables are available. A repeat analysis might be conducted in five years time, re‐estimating equations and triangulating findings.
In addition, some of the transition variables available for matching LSAC with ATP participants are not perfectly matched in this analysis, and there might be scope to address this in future waves of LSAC, to provide a more seamless transition between the two datasets.
Moreover, probabilistic analysis around the realisation of future benefits would be an important further step, but is out of scope here.
However, the finding in relation to the PPP suggests the model constructed for the project provides a sound basis for development, since this finding is consistent with other CBA/CEA studies of this program.
adolescence, parental permission to smoke at home and a conflictual parent‐teenager relationship. Alcohol abuse (binge drinking) in young adulthood was dependent on teen bingeing, lack of parental monitoring, father drin
Positive Family Functioning
75
Due to the compsome variables,
lexities of the analysis and issues such as potential two‐way causation for we caution readers in making overly strong statements about conclusions
to refine and continue to develop the modelling and elaborate on
We coand globally to bring an evidence basis fully in focus in social policy decision making, even in
presented. Rather, the greatest value in this project has been primarily to showcase how a broad, quantitative approach to social policy evaluation can work. With better quality data in the future, there is scopefindings further.
mmend the ongoing research focus of FaHCSIA, which is proving so valuable in Australia
areas previously deemed unquantifiable or intangible.
Positive Family Functioning
77
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Appendix A: LSAC children and future addictive behaviours
the li tle
arents did so when they were little.
entify some factor that is:
dictive behaviour in adulthood;
our (reported in both the LSAC and the ATP). In the long‐term, these changes make adults more prone to engage in anti‐social behaviour and/or become addicted.
Because there is no one piece of literature that makes all these connections, a potted summary is laid out below.
Recent work by paediatricians and neuroscientists (Shonkoff et al, 2010) shows that childhood stress – such as that caused by poor FF – can have permanent effects that cause deleterious outcomes in adulthood. And, of relevance to this study, these childhood stresses also cause negative social and emotional outcomes, of the types that are captured by the LSAC and the ATP. In the brain, under such high ‘allostatic loads’ the amygdala grows more neurons, causing the brain to generate more fear and anxiety. Simultaneously, the prefrontal cortex loses neurons, reducing the brain’s ability to plan and prioritise – and also to keep the amygdala’s negative emotions in check.
Studies of animals show that such early, stress‐related changes in brain circuitry can persist into adult life and alter emotional states, decision‐making capacities and processes which in humans contribute to substance abuse, aggression, obesity and stress‐related mental disorders (Isgor et al, 2004 and Kaufman at al, 2007).
■ The extent to which such temperaments are genetic or environmental is debated. Animal studies have shown that higher levels of environmental stress can develop into a generational susceptibility to stress through epigenetic changes in DNA methylation (Francis and Meaney, 1999).
As indicated in the scoping study, there are numerous studies showing that the impact of family functioning variable x is that children who experience it will become adults with outcome y. For example, parents who have substance abuse problems (tobacco, alcohol, drugs) are likely to see their children grow up to have similar abuse problems (e.g. Latendresse et al, 2008).
However, there are some unusual aspects of the current study that are not directly covered by terature. For example, the LSAC has parents who drink and smoke, but only lit
children, who do not; the ATP has teenagers who may drink and smoke, but no record of whether their p
Our approach was thus to id
■ a consequence of poor family functioning;
■ contributes to ad
■ has symptoms that are recorded in young children (LSAC); and
■ those symptoms are also recorded in teens / young adults (ATP).
The factor identified was stress (allostatic load). It is caused by (among other factors) poor parenting. Stress causes changes in brain structure and functioning which, in the short term, can make children more prone to anti‐social behavi
86
No longitudinal studies have been conducted on the influence of high stress in humans. tween traumatic childhoods
smoking, depression and other mental illnesses, 1998). Further, adults with depression also exhibit smaller prefrontal cort
ork shows that there are c differences in brain circuitries between children low SES (Kishiyama, 2009). In particular, low SES children have smaller prefrontal
be the ng itself from chronic stress, but may at
78 months f h (Chart A.1). low SES children also have greater
rs.
es in cognitive development by socio‐economic status
However, retrospective studies have shown strong associations beand adverse adult outcomes including alcoholism, drug abuse, obesity,
(Felitti et al, exes (Drevets, 1997).
Recent w systematiof high and cortexes, which appear to
developmentbrain’s way of protecti
affect their intellectual22 months of age, by
— low SES children who have high cognitive (Q) scores all below the Q scores of high SES children who started wit
low 22‐month scores Also, adults who wereamygdale activity than othe
Chart A.1: Differenc
documented that children with low SES are i) exposed to high degrees of itive parental behaviour and ii) have more prevalent mental disorders and
cLoyd, 1998).
n that low SES er disease‐specific and all‐cause morbidity rtality rates that ca r
lower access to health serv erts are beginning to consider that the long‐term ress a explained gap.
so, an important implicat tions to reduce childhood stress may be trying to target risky health behaviour later in life. For example, in
Source: Marmot (2010).
It is also wellconflictive / punsubstance abuse (M
■ It well know groups have highand mo nnot be explained just by material deprivation, illiteracy o
ices. Expeffects of childhood st ccount for much of this hitherto un
■ If ion is that intervenmore effective than
Positive Family Functioning
87
the UK only 15% of men w ications smoke, but over 40% of unskilled workers do – despite quit campaigns and punitive taxation.
also have lity. This stands to reason as both s, while reducing reasoning and
Empirically, there link between childhood stressful events and s an adult. Cu at the US National Bureau of Economic
national s the effects of childhood maltreatment use) on adult crime. They found that:
ately doubled the probability of engaging in many types of crime n other effects such as unemployment, low wages, or access to guns);
dren are both more likely to be mistreated and suffer more damaging
the largest effects, and
■ the probability of engaging in the experience of multiple forms of maltreatment.
Finally, and of direct relevance for this study, high levels of childhood stress manifest in chological and emotional dysregulation in chronically stressed children (Evans and Kim,
to ca ional difficulties is the Strengths and s Questionnaire (SDQ) Total Score, which is a composite measure of social and
ment. A highe w
ith professional qualif
Childhood stress appears tochildhood stress increases
an impact on adult criminaanger and aggressivenes
control mechanisms.committing crime aResearch used a large(including neglect as well as ab
■ maltreatment approxim(far greater tha
is a strongrrie and Tekin (2006)ample to examine
■ low SES chileffects;
■ (arguablysexual abusenegative
most stressful form of abuse) appears to have the
crime increases with
psy2007). The variable chosenDifficultie
pture social and emot
emotional developthis LSAC measure is compatible
r SDQ score represents more difficulties. AIFS advised that ith ATP measures.
88
Appendix B: Literature review so
Table B.1: Antiso
Evidence
urces, ATP
cial behaviour
Variable
FF variables
Relationship with parents Vassallo et al (2002)
Attachment to parents Weatherburn (2001), Catalano et al (2007), Vassallo et al (2002)
Family cohesion Vassallo et al (2 02) 0
Relationship quality/warmth Harsh discipline Parental monitoring/supervision Inconsistent discipline
Farrington (199 ), Prior et al (2000), Vassallo et al (2002) 5
Control variables
Marital relationship History of parental separation and its effect
Vassallo et al (2002) Fergusson and Horwood (2002)
Parental smoking FeParental alcohol
rgusson and (2002), Vassallo et al (2002) Horwood
Temperament AIFS advised (from previous ATP analysis)
Social and emotional difficulties Shonkoff et al (2010) and others, see discussion above
Table B.2: Anxiety sion
Variable
and depres
Evidence
FF variables
Attachment to parents Prior et al (2000)
Relationship quality/wInductive reas
armth oning
Unpublished rk by Primose Letcher at University of Melbourne and AIFS Heider et al (2Whiteside (20
Harsh discipline
wo
007), Betts et al (2009), Rapee (1997), Brown and 08), Bruce et al (2006)
Enmeshment Unpublished ourne and AIFS Betts at al (2009), Rapee (1997), Bogels and Bergman‐Toussaint (2006)
work by Primose Letcher at University of Melb
Experience of child(retrospective)
abuse/neglect Evidence cited in Taylor et al (2008)
Control variables
Marital relationship Bogels and Bergman‐Toussaint (2006)
Stressful life event Bruce et al (2006)
Temperament Betts et al (2009), Bogels and Bergman‐Toussaint (2006), Prior et al (2000)
* Parental anxiety/depression Rapee (1997), van Gastel et al (2009)
Gender Letcher et al (2009)
* Not available in the ATP
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Table B.3: Smoking
Variables Evidence
Parental management of teen substance use
Scragg and Laugesen (2007)
Inductive reasoning Harsh discipline Attachment to parents Parental monitoring/supervision
Dick et al (2007) Cohen et al (1994)
Negative conflictual relationship Inconsistent discipline
Control variables
Parental smoking Latendresse et al (2008)
Social and emotional difficulties Shonkoff et al (2010) and others, see discussion above
Temperament Clark et al (2008)
Table B.4: Alcohol
les Evidence Variab
FF
Parental management ofdrinking
teen Latendresse et al (2008)
Inductive reasoning Attachment to parents Harsh discipline Parental monitoring/supervision Inconsistent discipline Negative conflictual relationship
Latendresse et al (2008), Dick et al (2007), Arria et al (2008), Webbet al (2002), Cohen et al (1994)
Control variables
Parental use of alcohol Latendresse et al (2008)
Social and emotional difficulties Shonkoff et al (2010) and others, see discussion above
Temperament Clark et al (2008)
Table B.5: Illicit drug use
Variables Evidence
Family functioning
Experience of child abuse/neglect (retrospective) Dube et al (2003), Brens et al (2004), Kilpatrick et al, (2000), Smith et al, (2005), Pires and Jenkins, (2007)
Attachment to parents Parent adolescent conflict
Brechting (2004)
Parental monitoring/supervision Bahr et al (2005)
Marital relationship (conflict — proxy for witnessing violence)
Dube et al (2003), Kilpatrick et al, (2000)
Control
90
Variables Evidence
Mother/Father smoking and drinking habits Dube et al (2003), Brechting (2004), Kilpatrick et al (2000), Bierut et al (1998)
Social and emotional difficulties Shonkoff et al (2010) and others, see discussion above
Temperament AIFS advised
Table B.6: Productivity
Productivity variables
Family functioning variables
Harsh discipline Parental monitoring/supervision Inconsistent discipline Attachment to parents Negative conflictual relationship
Parental involvement in education
Dornbusch et al (1987), Steinberg et al (1992), Cohen and Rice (1997) Radziszewska et al (1996), Berthelsen and Walker (2008)
Control variables
Academic and social progress at school
School bonding
Parental education level
Academic competence and reading Plomin et al (1997) and Miller et al (2001)
Temperament AIFS advised
Table B.7: Overweight/obesity
Variables Evidence
FF variables
Attachment to parents Negative conflictual re
eenager ea
nd Crawford (2001) Campbell et al (200 , Gabel lationshipInconsistent discipline Harsh discipline Parental monitoring/supervision Inductive reasoning T ting behaviours
Moens et al (2009), Savage et al (2007), Campbell a ; 2)and Lutz (2000), Kratt et al (2000), Lissau and Sorensen (1994); Moens et al (2009)
Control variables
Family status (single parent household etc) Gabel and Lutz, 2000; Gibson et al. 2007
Socioeconomic status Garasky et al, (2009), Campbell et al, (2002), Danielzik et al, (2004), Gabel and Lutz, (2000)
Positive Family Functioning
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Appendix C: LSAC regression outcomes
Va P>|t| [95% Conf Intervals]
Harsh discipline a 0.01 0.02 0.13
Relationship quality / warmth aawarm 0.17‐ 0.08 2.02‐ 0.04 0.33‐ 0.01‐
Results in bold are significant. Results in bold red are significant, but have unexpected signs.Several variables, including parental depression are reverse coded in the LSAC database. Giventhe experimental nature of this exercise, significance was chosen to equal 0.10 in order to castthe net relatively broadly for possible substantiative FF effects. In the tables in this appendix,p values of ‘‐‘ represent values less than 0.001 (which is how Stata reports the output).
As K1 has no antecedents, lagged dependent variables cannot be derived, thus B3 (for whichprior observations are available) was chosen instead to represent this 4‐5 year age group.
Temperament does not have a clearly expected sign and is not coloured red. Wheretemperament is significant, for normally coded dependent variables, a negative sign indicateseasy temperament is operative, and a positive sign indicates difficult temperament.
■ It could be argued that an easy temperament should lead to better outcomes. Butconversely, if difficult temperament results from perfectionism, for example, that childmight do better academically than a child with an easy temperament but less attentionto detail. Similarly, a fussy eater (difficult temperament) may be less prone to obesitythan an easy‐going omnivore.
Table C.1: Obesity B1 (ahs23c2)
riable Coef. Std. Err t
ahost 0.08 0.03 2.53
Parental efficacy apa01a 0.03 0.04 0.89 0.37 0.04‐ 0.10
Temperament ase06i 0.00‐ 0.06 0.02‐ 0.98 0.13‐ 0.12
Parental anxiety & depression aak6 0.05 0.06 0.84 0.40 0.07‐ 0.16
Gender zf02m1 0.72‐ 0.06 11.64‐ ‐ 0.84‐ 0.60‐
Socioeconomic status afn05 0.08 0.00 1.88 0.06 0.00‐ 0.17
Parental education level acomboed 0.00 0.03 0.06 0.95 0.06‐ 0.06
Parent gender zf02m2 0.03‐ 0.32 0.10‐ 0.92 0.66‐ 0.60
Parent BMI aabmi 0.02 0.01 3.10 0.00 0.01 0.03
Needs extra medical care ahs14d 0.05 0.09 0.58 0.56 0.13‐ 0.24
Constant _cons 9.96 0.83 11.98 ‐ 8.33 11.59
R2=0.08, F = 14.44, No. observations = 2,155.
92
Table C.2: Obesity B2 (bcbmi)
Variable Coef. Std. Err t P>|t| [95% Conf Intervals]
Prev dep var ahs23c2 0.32 0.03 12.36 ‐ 0.27 0.37
Harsh discipline bahost 0.00 0.03 0.05 0.96 0.06‐ 0.06
Parental monitoring / supervision bpa08a1 0.00 0.07 ‐ 1.00 0.14‐ 0.14
Relationship quality / warmth bawarm 0.12 0.09 1.25 0.21 0.07‐ 0.30
Inductive reasoning baireas 0.03‐ 0.06 0.48‐ 0.63 0.15‐ 0.09
Parental efficacy bpa01a 0.03 0.04 0.58 0.56 0.06‐ 0.11
Family cohesion bre06a 0.02‐ 0.05 0.50‐ 0.62 0.11‐ 0.07
fatty foods bhfat 0.07‐ 0.04 1.69‐ 0.09 0.15‐ 0.01
Sugary Drinks bhsdrnk 0.03‐ 0.03 0.97‐ 0.33 0.09‐ 0.03
Exercise bhb14c4 0.08 0.05 1.64 0.10 0.02‐ 0.17
0.00‐ 0.00 0.64‐ 0.52 0.01‐ 0.01 E‐tainment betain
Temperament bse06a 0.08‐ 0.06 1.34‐ 0.18 0.21‐ 0.04
Parental anxiety & depression 0.92 0.14‐ 0.15
Gender zf02m1 0.05‐ 0.07 0.66‐ 0.51 0.19‐ 0.09
Socioeconomic status bhinc 0.05‐ 0.00 1.57‐ 0.12 0.11‐ 0.01
bak6 0.01 0.07 0.11
Parental education level bcomboe 0.08‐ 0.03 2.33‐ 0.02 0.14‐ 0.01‐
Parent gender zf02m2 0.59 0.24 2.45 0.01 0.12 1.07
Parent BMI babmi 0.06 0.01 7.20 ‐ 0.04 0.07
Needs extra medical care bhs14d 0.01‐ 0.09 0.14‐ 0.89 0.18‐ 0.16
Constant _cons 11.25 0.93 12.13 ‐ 9.43 13.07 R2=0.15, F = 13.49, No. observations = 2,156.
Table C.3: Obesity B3 (ccbmi)
Variable Coef. Std. Err t P>|t| [95% Conf Intervals]
Prev dep var bcbmi 0.68 0.02 28.13 ‐ 0.63 0.73
Harsh discipline cahostb 0.02 0.02 1.00 0.32 0.02‐ 0.07
Parental monitoring / supervision cpa08a1 0.00 0.02 0.20 0.84 0.04‐ 0.05
Relationship quality / warmth cawarm 0.02‐ 0.07 0.25‐ 0.80 0.15‐ 0.11
Inductive reasoning caireas 0.05 0.05 1.02 0.31 0.04‐ 0.14
Consistent discipline cacons 0.02‐ 0.05 0.46‐ 0.64 0.12‐
Parental self efficacy cpa01a
0.07
0.08 0.03 2.36 0.02 0.01 0.15
Family cohesion cre06a 0.02 0.04 0.61 0.54 0.05‐ 0.09
fatty foods chfat 0.02‐ 0.03 0.60‐ 0.55 0.07‐ 0.03
Sugary Drinks chsdrnkb 0.01 0.02 0.47 0.64 0.03‐ 0.05
Exercise chb14c4 0.05‐ 0.04 1.30‐ 0.19 0.13‐ 0.03
E‐tainment cetain 0.00‐ 0.00 1.86‐ 0.06 0.01‐ 0.00
Temperament cse06a 0.01 0.05 0.18 0.86 0.09‐ 0.10
Parental anxiety & depression cak6 0.06 0.06 1.14 0.26 0.05‐ 0.17
Gender zf02m1 0.01‐ 0.05 0.19‐ 0.85 0.12‐ 0.10
Socioeconomic status chinc 0.01 0.00 0.56 0.58 0.02‐ 0.04
Parental education level ccomboed 0.01‐ 0.03 0.44‐ 0.66 0.07‐ 0.05
Parent gender zf02m2 0.22 0.20 1.08 0.28 0.18‐ 0.62
Parent BMI cabmi 0.05 0.01 8.06 ‐ 0.03 0.06
Needs extra medical care chs14d 0.13‐ 0.10 1.38‐ 0.17 0.32‐ 0.06
Constant _cons 3.36 0.84 4.03 ‐ 1.73 5.00 R2=0.45, F = 50.58 No. observations = 2,955.
Positive Family Functioning
93
Table C.4: Obesity K2 (dcbmi)
Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Prev dep var ccbmi 1.01 0.03 31.56 ‐ 0.95 1.07
Harsh discipline dahostc 0.03‐ 0.02 1.25‐ 0.21 0.08‐ 0.02
Parental monitoring / supervision dpa08a1 0.09 0.06 1.52 0.13 0.02‐ 0.19
Relationship quality / warmth dawarm 0.01‐ 0.07 0.10‐ 0.92 0.14‐ 0.13
Inductive reasoning daireas 0.10 0.05 1.80 0.07 0.01‐ 0.20
Consistent discipline dacons 0.10‐ 0.05 2.19‐ 0.03 0.19‐ 0.01‐
Parental self efficacy dpa01a 0.07 0.04 1.90 0.06 0.00‐ 0.15
Family cohesion dre06a 0.01 0.04 0.35 0.73 0.07‐ 0.10
fatty foods dhfat 0.03 0.03 1.06 0.29 0.03‐ 0.09
Sugary Drinks dhsdrnk 0.09 0.03 3.31 0.00 0.03 0.14
Exercise dhb14c4 0.05 0.04 1.47 0.14 0.02‐ 0.13
E‐tainment detain 0.00‐ 0.00 1.23‐ 0.22 0.01‐ 0.00
Temperament dse06a 0.05 0.05 0.99 0.32 0.05‐ 0.15
Parental anxiety & depression dak6 0.06‐ 0.05 1.23‐ 0.22 0.17‐ 0.04
Gender zf02m1 0.09 0.05 1.69 0.09 0.01‐ 0.19
Socioeconomic status dhinc 0.00‐ 0.00 0.11‐ 0.92 0.05‐ 0.04
Parental education level dcomboed 0.04 0.03 1.34 0.18 0.02‐ 0.10
Parent gender zf02m2 0.14 0.17 0.83 0.41 0.19‐ 0.47
Parent BMI 0.03 0.01 5.15 ‐ 0.02 0.05
Needs extra medical care 0.40 0.11‐ 0.27
Constant cons 1.85‐ 0.74 2.50‐ 0.01 3.30‐ 0.40‐
dabmi
dhs14d 0.08 0.10 0.84
R2=0.67, F = 98.73 No. observations = 2,701.
Table C.5: Obesity K3 (ecbmi)
Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Prev dep var dcbmi 1.14 0.02 72.98 ‐ 1.11 1.17
Harsh discipline eahostc 0.01‐ 0.02 0.55‐ 0.58 0.06‐ 0.03
Parental monitoring / supervision epa08a1 0.03 0.03 0.91 0.37 0.03‐ 0.08
Relationship quality / warmth eawarm 0.02 0.06 0.37 0.71 0.09‐ 0.13
Inductive reasoning eaireas 0.03‐ 0.04 0.66‐ 0.51 0.11‐ 0.06
Consistent discipline eacons 0.06‐ 0.05 1.22‐ 0.22 0.15‐ 0.03
Parental self efficacy epa01a 0.02‐ 0.03 0.46‐ 0.64 0.08‐ 0.05
Family cohesion ere06a 0.01‐ 0.03 0.23‐ 0.82 0.08‐ 0.06
fatty foods ehfat 0.03 0.03 1.18 0.24 0.02‐ 0.08
Sugary Drinks ehsdrnkb 0.02 0.02 1.00 0.32 0.02‐ 0.07
Exercise ehb14c4 0.09‐ 0.04 2.37‐ 0.02 0.16‐ 0.02‐
E‐tainment eetain 0.00‐ 0.00 0.99‐ 0.32 0.01‐ 0.00
Temperament ese06a 0.05 0.05 0.92 0.36 0.05‐ 0.14
0.08 0.05 1.40 0.16 0.03‐ 0.18
Gender zf02m1 0.10 0.05 1.79 0.07 0.01‐ 0.20
Parental anxiety & depression eak6
Socioeconomic status ehinc 0.02‐ 0.00 0.97‐ 0.33 0.06‐ 0.02
Parental education level ecomboed 0.04 0.03 1.55 0.12 0.01‐ 0.09
Parent gender zf02m2 0.28 0.14 1.97 0.05 0.00 0.56
Parent BMI eabmi 0.03 0.01 5.83 ‐ 0.02 0.05
Needs extra medical care ehs14d 0.11 0.07 1.64 0.10 0.02‐ 0.25
Constant _cons 2.86‐ 0.68 4.20‐ ‐ 4.19‐ 1.52‐ R2=0.77, F = 326.88 No. observations = 3,018.
94
Table C.6: Productivity B1 (awlrnoi)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Harsh discipline aahost 0.22 0.16 1.34 0.18 0.10‐ 0.54
Parental monitoring / supervision aawarm 5.66 0.51 11.17 ‐ 4.67 6.66
Relationship quality / warmth apa01a 0.52 0.21 2.41 0.02 0.10 0.94
Parental anxiety & depression aak6 0.35‐ 0.34 1.04‐ 0.30 1.01‐ 0.31
Gender zf02m1 0.66 0.35 1.86 0.06 0.03‐ 1.36
Age ascagem 0.00 0.08 ‐ 1.00 0.16‐ 0.16
Socioeconomic status afn05 0.64‐ 0.00 2.58‐ 0.01 1.13‐ 0.16‐
Parental education level acomboed 0.05 0.18 0.29 0.77 0.30‐ 0.40
Parent gender zf02m2 0.08 1.44 0.05 0.96 2.75‐ 2.91
Constant _cons 72.30 4.01 18.03 ‐ 64.44 80.16 R2=0.07, F = 21.80 No. observations = 3,162.
Table C.7: Productivity B2 (bwlrnoi)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Learning outcome index awlrnoi 0.22 0.02 10.67 ‐ 0.18 0.26
Harsh discipline bahost 0.01‐ 0.16 0.04‐ 0.97 ‐0.31 0.30
Parental monitoring / supervision bpa08a1 0.39‐ 0.45 0.88‐ 0.38 ‐1.28 0.49
Relationship quality / warmth bawarm 0.98‐ 0.54 1.81‐ 0.07 ‐2.04 0.08
nductive reasoning baireas 3.17 0.38 8.36 ‐ 2.43 3.92
Parental self efficacy bpa01a 0.37‐ 0.26 1.38‐ 0.17 ‐0.88 0.15
Family cohesion ‐1.08 0.02
Parental involvement in education bahact 2.57 0.39 6.63 ‐ 1.81 3.33
Temperament bse06a 2.15‐ 0.38 5.70‐ ‐ ‐2.89 1.41‐
I
bre06a 0.53‐ 0.28 1.90‐ 0.06
Parental anxiety & depression bak6 1.30 0.42 3.07 0.00 0.47 2.13
Gender zf02m1 3.04 0.38 7.99 ‐ 2.30 3.79
Age bscagem 0.00‐ 0.07 0.06‐ 0.95 ‐0.15 0.14
Socioeconomic status bhinc 0.92 0.00 4.99 ‐ 0.00 0.56
Parental education level bcomboe 0.42‐ 0.22 1.92‐ 0.06 ‐0.86 0.01
Parent gender zf02m2 2.03 1.39 1.46 0.15 ‐0.70 4.75
Constant _cons 58.06 5.42 10.72 ‐ 47.44 68.68 R2=0.21, F = 42.85 No. observations = 2,678. Note, the productivity dependent variable (learning outcome index) is normally coded, while parental education level is reverse coded (lower score = higher education). Thus, the expected sign of parental education is negative.
Positive Family Functioning
95
Table C.8: Productivity B3 (cwlrnoi)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Learning outcome index bwlrnoi 0.30 0.02 15.94 ‐ 0.26 0.34
Harsh discipline cahostb 0.02 0.15 0.11 0.91 ‐0.28 0.31
Parental monitoring / supervision cpa08a1 0.01‐ 0.15 0.06‐ 0.96 ‐0.31 0.29
Relationship quality / warmth cawarm 0.92‐ 0.47 1.97‐ 0.05 ‐1.83 0.01‐
Inductive reasoning caireas 0.21 0.33 0.65 0.52 ‐0.43 0.85
Consistent discipline cacons 1.03 0.32 3.24 0.00 0.41 1.65
Parental self efficacy cpa01a 0.34 0.23 1.46 0.14 ‐0.11 0.79
Family cohesion cre06a 0.06‐ 0.23 0.27‐ 0.79 ‐0.52 0.40
Parental involvement in education cahactd 0.73 0.33 2.19 0.03 0.08 1.38
Temperament cse06a 1.40‐ 0.33 4.24‐ ‐ ‐2.05 0.75‐
Parental anxiety & depression cak6 0.02 0.35 0.05 0.96 ‐0.67 0.70
Gender zf02m1 3.33 0.35 9.51 ‐ 2.65 4.02
Age cscagem 0.22 0.06 3.38 0.00 0.09 0.34
Socioeconomic status chinc 0.98 0.00 8.71 ‐ 0.00 0.75
Parental education level ccomboe 1.11‐ 0.20 5.53‐ ‐ ‐1.50 0.72‐
Parent gender zf02m2 0.61 1.44 0.42 0.67 ‐2.22 3.44
Constant _cons 51.43 5.80 8.87 ‐ 40.06 62.80 R2=0.26, F = 49.54 No. observations = 2,679.
Table C.9: Productivity K2 (dwlrnoi)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Learning outcome index cwlrnoi 0.54 0.02 29.15 ‐ 0.50 0.57
Harsh discipline dahostc 0.28‐ 0.12 2.31‐ 0.02 ‐0.53 0.04‐
Parental monitoring / supervision dpa08a1 0.98‐ 0.41 2.40‐ 0.02 ‐1.79 0.18‐
Relationship quality / warmth dawarm 0.73‐ 0.40 1.81‐ 0.07 ‐1.51 0.06
Inductive reasoning daireas 0.43 0.29 1.46 0.15 ‐0.15 1.00
Consistent discipline dacons 0.77 0.28 2.75 0.01 0.22 1.31
Parental self efficacy dpa01a 0.54‐ 0.22 2.47‐ 0.01 ‐0.97 0.11‐
Family cohesion dre06a 0.07‐ 0.21 0.35‐ 0.72 ‐0.48 0.34
Parental involvement in education dahact 0.15‐ 0.32 0.47‐ 0.64 ‐0.78 0.48
Parental involvement in school dassc 0.23 0.15 1.47 0.14 ‐0.08 0.53
Temperament dse06a 1.18‐ 0.29 4.10‐ ‐ ‐1.75 0.62‐
Parental anxiety & depression dak6 0.12 0.33 0.36 0.72 ‐0.52 0.75
Gender zf02m1 1.52‐ 0.33 4.64‐ ‐ ‐2.16 0.88‐
Age dscagem 0.01 0.06 0.24 0.81 ‐0.10 0.12
Socioeconomic status dhinc 1.09 0.00 7.58 ‐ 0.00 0.81
Parental education level dcomboe 0.32‐ 0.16 2.02‐ 0.04 ‐0.63 0.01‐
Parent gender zf02m2 0.29‐ 1.18 0.25‐ 0.80 ‐2.62 2.03
Constant _cons 54.63 6.43 8.49 ‐ 42.02 67.24 R2=0.34, F = 69.80 No. observations = 2,936.
96
Table C.10: Productivity K3 (ewlrnoi)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Learning outcome index dwlrnoi 0.66 0.02 42.26 ‐ 0.63 0.69
Harsh discipline eahostc 0.09‐ 0.11 0.88‐ 0.38 ‐0.30 0.11
Parental monitoring / supervision epa08a1 0.11 0.13 0.81 0.42 ‐0.15 0.37
Relationship quality / warmth eawarm 0.38‐ 0.29 1.33‐ 0.18 ‐0.95 0.18
Inductive reasoning eaireas 0.17‐ 0.23 0.75‐ 0.46 ‐0.62 0.28
Consistent discipline eacons 0.60 0.25 2.38 0.02 0.11 1.10
Parental self efficacy epa01a 0.02‐ 0.17 0.12‐ 0.90 ‐0.36 0.32
Family cohesion ere06a 0.19 0.17 1.16 0.25 ‐0.13 0.52
Parental involvement in education eahacte 0.67‐ 0.23 2.95‐ 0.00 ‐1.11 0.22‐
Parental involvement in school eassc 0.55 0.11 5.14 ‐ 0.34 0.76
Temperament ese06a 1.27‐ 0.25 5.00‐ ‐ ‐1.77 0.78‐
Parental anxiety & depression eak6 0.17‐ 0.25 0.67‐ 0.50 ‐0.66 0.32
Gender zf02m1 0.25 0.27 0.95 0.34 ‐0.27 0.78
Age escagem 0.01 0.05 0.11 0.91 ‐0.09 0.10
Socioeconomic status ehinc 0.17 0.00 1.69 0.09 ‐0.03 0.38
Parental education level ecomboe 0.55‐ 0.13 4.33‐ ‐ ‐0.80 0.30‐
Parent gender zf02m2 0.88‐ 0.82 1.07‐ 0.29 ‐2.49 0.74
Constant _cons 37.45 5.91 6.33 ‐ 25.85 49.05 R2=0.51, F = 146.42 No. observations = 3,195.
Anxiety and depression B1 (apedsgc) Table C.11:
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Harsh discipline aahost 0.00‐ 0.00 0.63‐ 0.53 0.01‐ 0.01
Relationship quality / warmth aawarm 0.00 0.01 0.39 0.69 0.02‐ 0.03
Parental Efficacy apa01a 0.01 0.00 1.90 0.06 0.00‐ 0.02
Smoking ahb15a1 0.01‐ 0.01 0.83‐ 0.41 0.02‐ 0.01
Alcohol consumption aaalcgpm 0.01 0.01 1.12 0.26 0.01‐ 0.04
Parental anxiety & depression aak6 0.02 0.01 1.97 0.05 0.00 0.04
Gender zf02m1 0.01 0.01 1.03 0.30 0.01‐ 0.03
Socioeconomic status afn05 0.00‐ 0.00 0.56‐ 0.57 0.02‐ 0.01
Parental education level acomboed 0.00 0.00 1.23 0.22 0.00‐ 0.01
Parent gender zf02m2 0.00 0.03 ‐ 1.00 0.07‐ 0.07
Constant _cons 1.77 0.10 17.62 ‐ 1.58 1.97 R2=0.01, F = 2.07 No. observations = 2,584. Note: parental anxiety and depression (*ak6) is reverse coded, such that a higher score indicates less anxiety and depression. For childhood anxiety and depression in B1, apedsgc is also reverse coded, thus the expected sign of *ak6 is positive. However, all other childhood anxiety and depression dependent variables (B2 through K3) are coded normally, thus the expected sign of *ak6 is negative.
Positive Family Functioning
97
Table dsef)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
09
C.12: Anxiety and depression B2 (bpe
Lag dep var apedsgc 3.50 1.18 2.97 0.00 1.19 5.81
Harsh discipline bahost 2.11‐ 0.24 8.95‐ ‐ ‐2.57 ‐1.65
Parental monitoring / supervision bpa08a1 0.25‐ 0.60 0.42‐ 0.68 ‐1.44 0.93
Relationship quality / warmth bawarm 1.83 0.72 2.54 0.01 0.42 3.24
Inductive reasoning baireas 0.47‐ 0.49 0.95‐ 0.34 ‐1.44 0.50
Parental efficacy bpa01a 0.55 0.35 1.55 0.12 ‐0.15 1.24
Family cohesion bre06a 1.44‐ 0.37 3.89‐ ‐ ‐2.16 ‐0.71
Smoking bhb15a1 0.01 0.37 0.02 0.99 ‐0.72 0.74
Alcohol consumption baalcgpm 0.46‐ 0.65 0.71‐ 0.48 ‐1.73 0.82
Overprotection baoverp 1.22‐ 0.39 3.13‐ 0.00 ‐1.98 ‐0.45
Temperament bse06a 3.73‐ 0.51 7.30‐ ‐ ‐4.73 ‐2.73
3
90
Parental anxiety & depression bak6 5.12 0.62 8.30 ‐ 3.91 6.3
Gender zf02m1 0.09‐ 0.50 0.18‐ 0.86 ‐1.08 0.
Socioeconomic status bhinc 0.59‐ 0.00 2.31‐ 0.02 ‐1.09 ‐0.
Parental education level bcomboe 0.52 0.28 1.87 0.06 ‐0.02 1.07
Parent gender zf02m2 2.68‐ 2.16 1.24‐ 0.22 ‐6.92 1.57
Constant ‐ 49.73 76.95_cons 63.34 6.94 9.13 R2=0.19, F = 31.85 No. observations = 3,000.
Table C.13: Anxiety and depression B3 (cpedsef)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var bpedsef 0.36 0.02 17.78 ‐ 0.32 0.40
Harsh discipline cahostb 1.25‐ 0.25 4.93‐ ‐ ‐1.74 ‐0.75
Parental monitoring / supervision cpa08a1 0.03 0.21 0.13 0.90 ‐0.39 0.45
Relationship quality / warmth cawarm 1.90 0.65 2.91 0.00 0.62 3.18
Inductive reasoning caireas 1.44‐ 0.48 3.02‐ 0.00 ‐2.38 ‐0.51
Consistent discipline cacons 0.39 0.52 0.75 0.45 ‐0.63 1.41
Efficacy cpa01a 0.08 0.34 0.24 0.81 ‐0.58 0.74
Cohesion cre06a 0.63‐ 0.33 1.94‐ 0.05 ‐1.28 0.01
Smoking chb15a1 0.36‐ 0.37 0.99‐ 0.32 ‐1.08 0.36
Alcohol consumption caalcgpmo 0.08‐ 0.76 0.10‐ 0.92 ‐1.56 1.40
Overprotection caoverp 0.29‐ 0.39 0.73‐ 0.47 ‐1.06 0.49
Temperament cse06a 2.94‐ 0.52 5.70‐ ‐ ‐3.95 ‐1.93
Parental anxiety & depression cak6 4.55 0.73 6.23 ‐ 3.12 5.98
Gender zf02m1 0.46‐ 0.51 0.89‐ 0.37 ‐1.46 0.55
Socioeconomic status chinc 0.39‐ 0.00 2.13‐ 0.03 ‐0.75 ‐0.03
Parental education level ccomboed 0.19 0.30 0.61 0.54 ‐0.41 0.78
Parent gender zf02m2 0.54‐ 2.11 0.26‐ 0.80 ‐4.68 3.59
Constant _cons 37.39 6.82 5.48 ‐ 24.02 50.77 R2=0.30, F = 51.34 No. observations = 2,679.
98
Table mot) C.14: Anxiety and depression K2 (dae
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var caemot 0.39 0.02 19.03 ‐ 0.35 0.44
Harsh discipline dahostc 0.08 0.02 3.39 0.00 0.03 0.13
Parental monitoring / supervision dpa08a1 0.04 0.07 0.48 0.63 ‐0.11 0.18
Relationship quality / warmth dawarm 0.05‐ 0.07 0.73‐ 0.46 ‐0.20 0.09
Inductive reasoning daireas 0.06 0.05 1.29 0.20 ‐0.03 0.15
Consistent discipline dacons 0.07‐ 0.05 1.35‐ 0.18 ‐0.18 0.03
Efficacy dpa01a 0.04 0.04 0.92 0.36 ‐0.04 0.11
Cohesion dre06a 0.04 0.04 1.06 0.29 ‐0.04 0.12
Smoking dhb15a1 0.01‐ 0.04 0.23‐ 0.82 ‐0.09 0.07
Alcohol consumption daalcgpm 0.26‐ 0.09 3.00‐ 0.00 ‐0.42 ‐0.09
Overprotection daoverp 0.05 0.04 1.30 0.19 ‐0.03 0.14
Temperament dse06a 0.32 0.06 5.53 ‐ 0.21 0.43
Parental anxiety & depression dak6 0.48‐ 0.07 7.21‐ ‐ ‐0.61 ‐0.35
Gender zf02m1 0.14 0.06 2.57 0.01 0.03 0.25
Socioeconomic status dhinc 0.01‐ 0.00 0.38‐ 0.71 ‐0.07 0.05
Parental education level dcomboed 0.00‐ 0.03 0.01‐ 0.99 ‐0.05 0.05
Parent gender zf02m2 0.03‐ 0.21 0.14‐ 0.89 ‐0.44 0.38
2.28 0.79 2.88 0.00 0.73 3.84Constant _cons R2=0.29, F = 42.86 No. observations
Table C.15: Anxiety and depression K3 (eaemot)
= 2,939.
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var daemot 0.50 0.02 23.24 ‐ 0.46 0.55
Harsh discipline eahostc 0.06 0.02 2.32 0.02 0.01 0.11
Parental monitoring / supervision epa08a1 0.00 0.03 0.07 0.94 ‐0.05 0.06
Relationship quality / warmth eawarm 0.01 0.06 0.18 0.86 ‐0.11 0.14
Inductive reasoning eaireas 0.04 0.05 0.96 0.34 ‐0.05 0.13
Consistent discipline eacons 0.04‐ 0.05 0.82‐ 0.41 ‐0.15 0.06
Efficacy epa01a 0.02 0.04 0.67 0.51 ‐0.05 0.09
Cohesion ere06a 0.03 0.04 0.96 0.34 ‐0.04 0.10
Smoking ehb15a1 0.02 0.04 0.46 0.65 ‐0.06 0.09
Alcohol consumption eaalcgpm 0.16‐ 0.08 1.93‐ 0.05 ‐0.31 0.00
Overprotection eaoverp 0.09 0.04 2.19 0.03 0.01 0.17
Temperament ese06a 0.36 0.06 5.85 ‐ 0.24 0.47
Parental anxiety & depression eak6 0.40‐ 0.06 7.25‐ ‐ ‐0.51 ‐0.29
Gender zf02m1 0.05 0.06 0.96 0.34 ‐0.06 0.16
Socioeconomic status ehinc 0.04‐ 0.00 1.74‐ 0.08 ‐0.08 0.00
Parental education level ecomboed 0.00‐ 0.03 0.07‐ 0.95 ‐0.05 0.05
0.06‐ 0.18 0.33‐ 0.74 ‐0.41 0.29Parent gender zf02m2
Constant _cons 1.61 0.59 2.73 0.01 0.45 2.77 R2=0.36, F = 55.04 No. observations = 3,191.
Positive Family Functioning
99
Table C.16: Antisocial B1 (apedsgc)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Harsh discipline aahost 0.00‐ 0.00 0.63‐ 0.53 0.01‐ 0.01
Relationship quality / warmth aawarm 0.00 0.01 0.39 0.69 0.02‐ 0.03
Parental Efficacy apa01a 0.01 0.00 1.90 0.06 0.00‐ 0.02
Smoking ahb15a1 0.01‐ 0.01 0.83‐ 0.41 0.02‐ 0.01
Alcohol consumption aaalcgpm 0.01 0.01 1.12 0.26 0.01‐ 0.04
Parental anxiety & depression aak6 0.02 0.01 1.97 0.05 0.00 0.04
Gender zf02m1 0.01 0.01 1.03 0.30 0.01‐ 0.03
Socioeconomic status afn05 0.00‐ 0.00 0.56‐ 0.57 0.02‐ 0.01
Parental education level acomboed 0.00 0.00 1.23 0.22 0.00‐ 0.01
Parent gender zf02m2 0.00 0.03 ‐ 1.00 0.07‐ 0.07
Constant _cons 1.77 0.10 17.62 ‐ 1.58 1.97 R2=0.01, F = 1.77 No. observations = 3,476. Note: Parental anxiety and depression (*ak6) is reverse coded, such that a higher score indicates less anxiety and depression. For childhood antisocial behavior (B1), apedsgc is also reverse coded, thus the expected sign of *ak6 is positive. However, all other childhood antisocial behaviour dependent variables (B2 though K3) are coded normally, thus the expected sign of *ak6 is negative.
Table C.17: Antisocial B2 (babitp)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var apedsgc 0.47 0.20 2.39 0.02 0.08 0.85
Harsh discipline ‐ 0.41 0.68
Parental monitoring / supervision bpa08a1 0.24 0.16 1.49 0.14 0.07‐ 0.55
Relationship quality / warmth bawarm 0.20‐ 0.22 0.93‐ 0.35 0.63‐ 0.22
bahost 0.55 0.07 7.86
Inductive reasoning baireas 0.21‐ 0.14 1.49‐ 0.14 0.49‐ 0.07
Parental efficacy bpa01a 0.05 0.10 0.49 0.63 0.15‐ 0.25
Family cohesion bre06a 0.61 0.10 5.97 ‐ 0.41 0.81
Smoking bhb15a1 0.21 0.11 1.90 0.06 0.01‐ 0.42
Alcohol consumption baalcgpm 1.02‐ 0.20 5.20‐ ‐ 1.40‐ 0.63‐
Temperament bse06a 1.80 0.16 11.57 ‐ 1.50 2.11
Parental anxiety & depression bak6 2.32‐ 0.19 12.13‐ ‐ 2.70‐ 1.95‐
Gender zf02m1 0.54‐ 0.15 3.68‐ ‐ 0.82‐ 0.25‐
Socioeconomic status bhinc 0.14‐ 0.00 1.90‐ 0.06 0.28‐ 0.00
Parental education level bcomboe 0.15 0.09 1.66 0.10 0.03‐ 0.32
Parent gender zf02m2 1.09‐ 0.75 1.45‐ 0.15 2.56‐ 0.39
Constant _cons 39.11 2.19 17.85 ‐ 34.81 43.40 R2=0.30, F = 55.95 No. observations = 3,011.
100
Table C.18: Antisocial B3 (caconda)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var babitp 0.06 0.01 6.85 ‐ 0.04 0.08
Harsh discipline cahostb 0.36 0.03 11.99 ‐ 0.30 0.42
Parental monitoring / supervision cpa08a1 0.01‐ 0.03 0.47‐ 0.64 0.07‐ 0.04
Relationship quality / warmth cawarm 0.35‐ 0.07 4.73‐ ‐ 0.50‐ 0.21‐
Inductive reasoning caireas 0.31 0.05 5.74 ‐ 0.20 0.41
Consistent discipline cacons 0.36‐ 0.06 6.36‐ ‐ 0.47‐ 0.25‐
Parental efficacy cpa01a 0.11‐ 0.04 2.82‐ 0.01 0.19‐ 0.03‐
Family cohesion cre06a 0.09 0.04 2.02 0.04 0.00 0.17
Smoking chb15a1 0.18 0.05 3.90 ‐ 0.09 0.27
Alcohol consumption caalcgpm 0.18‐ 0.08 2.27‐ 0.02 0.34‐ 0.02‐
Temperament cse06a 0.83 0.06 13.48 ‐ 0.71 0.95
Parental anxiety & depression cak6 0.13‐ 0.07 1.88‐ 0.06 0.26‐ 0.01
Gender zf02m1 0.02‐ 0.06 0.31‐ 0.75 0.13‐ 0.09
Socioeconomic status chinc 0.04‐ 0.00 1.86‐ 0.06 0.08‐ 0.00
Parental education level ccomboed 0.03 0.04 0.98 0.33 0.04‐ 0.10
Parent gender zf02m2 0.15‐ 0.29 0.53‐ 0.60 0.73‐ 0.42
Constant _cons 0.92 0.86 1.07 0.29 0.77‐ 2.61 R2=0.37, F = 76.00 No. observations = 3,120.
Table C.19: Antisocial K2 (daconda)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var caconda 0.23 0.01 15.41 ‐ 0.20 0.26
Harsh discipline dahostc 0.21 0.02 11.01 ‐ 0.18 0.25
Parental monitoring / supervision dpa08a1 0.05 0.06 0.83 0.41 0.06‐ 0.16
Relationship quality / warmth dawarm 0.14‐ 0.06 2.33‐ 0.02 0.26‐ 0.02‐
Inductive reasoning daireas 0.07 0.04 1.95 0.05 0.00‐ 0.15
Consistent discipline dacons 0.25‐ 0.05 5.28‐ ‐ 0.34‐ 0.16‐
Parental efficacy dpa01a 0.01 0.03 0.26 0.79 0.05‐ 0.07
Family cohesion dre06a 0.14 0.03 4.59 ‐ 0.08 0.20
Smoking dhb15a1 0.12 0.03 3.61 ‐ 0.06 0.19
Alcohol consumption daalcgpm 0.07 0.06 1.13 0.26 0.05‐ 0.19
Temperament dse06a 0.42 0.04 9.32 ‐ 0.33 0.51
Parental anxiety & depression dak6 0.07‐ 0.05 1.37‐ 0.17 0.18‐ 0.03
Gender zf02m1 0.18‐ 0.05 4.06‐ ‐ 0.27‐ 0.09‐
Socioeconomic status dhinc 0.05‐ 0.00 2.56‐ 0.01 0.09‐ 0.01‐
Parental education level dcomboed 0.04 0.02 1.48 0.14 0.01‐ 0.08
Parent gender zf02m2 0.15‐ 0.17 0.84‐ 0.40 0.49‐ 0.20
Constant _cons 0.84 0.66 1.29 0.20 0.44‐ 2.13 R2=0.41, F = 90.99 No. observations = 2,042.
Positive Family Functioning
101
Table C.20: Antisocial K3 (eaconda)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Lag dep var daconda 0.42 0.02 20.00 ‐ 0.38 0.46
Harsh discipline eahostc 0.19 0.02 8.99 ‐ 0.15 0.23
Parental monitoring / supervision epa08a1 0.02‐ 0.02 0.93‐ 0.36 0.06‐ 0.02
Relationship quality / warmth eawarm 0.04‐ 0.05 0.97‐ 0.33 0.13‐ 0.04
Inductive reasoning eaireas 0.06 0.03 1.87 0.06 0.00‐ 0.13
Consistent discipline eacons 0.18‐ 0.04 4.25‐ ‐ 0.26‐ 0.09‐
Parental efficacy epa01a 0.05‐ 0.03 1.84‐ 0.07 0.11‐ 0.00
Family cohesion ere06a 0.06 0.03 2.22 0.03 0.01 0.12
Smoking ehb15a1 0.08 0.03 2.50 0.01 0.02 0.14
Alcohol consumption eaalcgpm 0.03 0.06 0.50 0.62 0.09‐ 0.15
Temperament ese06a 0.45 0.04 10.65 ‐ 0.37 0.53
Parental anxiety & depression eak6 0.16‐ 0.05 3.49‐ ‐ 0.25‐ 0.07‐
Gender zf02m1 0.15‐ 0.04 3.55‐ ‐ 0.23‐ 0.07‐
Socioeconomic status ehinc 0.03‐ 0.00 2.21‐ 0.03 0.06‐ 0.00‐
Parental education level ecomboed 0.00 0.03 0.01 0.99 0.05‐ 0.05
Parent gender zf02m2 0.13‐ 0.10 1.27‐ 0.21 0.33‐ 0.07
Constant _cons 1.25 0.43 2.91 0.00 0.41 2.09 R2=0.50, F = 96.27 No. observations = 3,194.
Table C.21: Addictions B1 (apedsgc)
Category Var Coef. Std. Err t P>|t| [95% Conf Intervals]
Harsh discipline aahost 0.00‐ 0.00 0.63‐ 0.53 0.01‐ 0.01
Relationship quality / warmth aawarm 0.00 0.01 0.39 0.70 0.02‐ 0.03
Parental efficacy apa01a 0.01 0.00 1.90 0.06 0.00‐ 0.02
Smoking ahb15a1 0.01‐ 0.01 0.83‐ 0.41 0.02‐ 0.01
Alcohol consumption aaalcgpm 0.01 0.01 1.12 0.26 0.01‐ 0.04
Parental anxiety & depression aak6 0.02 0.01 1.97 0.05 0.00 0.04
Gender zf02m1 0.01 0.01 1.03 0.30 0.01‐ 0.03
Socioeconomic status afn05 0.00‐ 0.00 0.56‐ 0.57 0.02‐ 0.01
Parental education level acomboed 0.00 0.00 1.23 0.22 0.00‐ 0.01
Parent gender zf02m2 0.00 0.03 ‐ 1.00 0.07‐ 0.07
Constant _cons 1.77 0.10 17.62 ‐ 1.58 1.97 R2=0.01, F = 1.77 No. observations = 3,476. Note: Parental anxiety and depression (*ak6) is reverse coded, such that a higher score indicates less anxiety and depression. For childhood addictive behavior (B1) , apedsgc is also reverse coded, thus the expected sign of *ak6 is positive. However, all other childhood addictive behaviour dependent variables (B2 though K3) are coded normally, thus the expected sign of *ak6 is negative.
102
Table C.22: Addictions B2 (babitp)
P>|t| [95% Conf Intervals]
Lag dep var apedsgc 0.48 0.20 2.43 0.02 0.09 0.87
Harsh discipline ‐ 0.42 0.69
Parental monitoring / supervision bpa08a1 0.12 0.16 0.75 0.45 0.19‐ 0.42
rmth rm 0.40‐ 0.22 0.83 0.03
eas as 0.22‐ 0.14 0.49 0.06
l efficacy bpa01a 0.03 0.10 5 0.73 0.16‐ 0.23
he 9 0.10
Smoking 8 0.11 1.68 0.40
Alcohol cons baalcgp
Category Var Coef. Std. Err t
bahost 0.56 0.07 7.97
Relationship
Inductive r
Parenta
quality / wa
oning
bawa
baire
1.83‐
1.52‐
0.3
0.07 ‐
0.13 ‐
Family co sion
umption
bre06a 0.5
bhb15a1 0.1
5.77 ‐ 0.39 0.79
0.09 0.03‐
m 0.91‐ 0.20 4.65‐
Overprotection baoverp 0.72 0.12 6.24 5
Temperament bse06a 1.81 0.15 11.66 1
Parental anxiety & depression bak6 2.26‐ 0.19 11.86‐ 2.63 1.89‐
r 0.86 0.29‐
conom 0 0.24 0.04
Parental educ
‐ 1.30‐ 0.53‐
‐ 0.50 0.9
‐ 1.50 2.1
‐ ‐
Gende
Socioe
zf02m1 0.57‐ 0.14
bhinc 0.10‐ 0.0
bcomboe
3.98‐
1.40‐
‐ ‐
0.16 ‐ ic status
ation level d 0.11 0.09
zf02m2 1.07‐ 0
_cons 37.61 2.
1.21 0.23 0.07‐ 0.28
Parent gender .72 1.48‐ 0.14 2.49‐ 0.35
Constant 17 17.35 ‐ 33.36 41.86 2 , F = 5 ervati
3: Addictions B3 (casdqta)
Category t P>|t| [95% Conf Intervals]
Lag dep var 2 12.54 ‐ 0.24 0.33
Harsh discipline 0.07 8.67 ‐ 0.50 0.79
Parental monitoring / supervisio 0.07 0.48 0.63 0.11‐ 0.17
Relationship quality / warmth warm 0.70‐ 0.21 3.28‐ 0.00 1.12‐ 0.28‐
ve re 0.14 0.18 0.72
Consistent d 0.16 4.11‐ ‐ 0.96‐ 0.34‐
Parental eff a01a 0.20‐ 0.10 1.89‐ 0.06 0.40‐ 0.01
ohe 0.03 0.40
ng 0.09 0.52
Alcohol cons
R =0.31 5.66 No. obs ons = 3,003.
Table C.2
Var Coef. Std. Err
babitp 0.29 0.0
cahostb 0.64
n cpa08a1 0.03
ca
Inducti asoning
iscipline
icacy
caireas 0.45
cacons 0.65‐
cp
3.29 0.00
Family c
Smoki
sion
umption
cre06a 0.18 0.11
chb15a1 0.30 0.11
caalcgp
1.65
2.73
0.10 ‐
0.01
m 0.47‐ 0.2
caoverp 0.24 0.1
cse06a 1.95
cak6
1 2.25‐ 0.03 0.87‐ 0.06‐
Overprotec 2 2.05 0.04 0.01 0.47
Temperame 0.16 12.40 ‐ 1.64 2.26
Parental anxiety & depression 1.00‐ 0.20 4.89‐ ‐ 1.40‐ 0.60‐
0.15 0.73 0.16‐
Socioeconom chinc 0.16‐ 0.00 3.13‐ 0.00 0.26‐ 0.06‐
l edu vel 0.10 0.08 0.45
Parent gende zf02m2 0.02‐ 0.82 0.02‐ 0.98 1.62‐ 1.59
Constant _cons 2.95 2.33 1.27 0.21 1.62‐ 7.53
tion
nt
Gender zf02m1 0.44‐ 3.04‐ 0.00 ‐
ic status
Parenta cation le
r
ccomboe 0.27 2.75 0.01
, F = 7 servatiR2=0.41 3.14 No. ob ons = 3,116.
Positive Family Functioning
103
Table C.24: Addictions K2 (dasdqta)
Cate
Lag de
gory r P> Conf Intervals]
p var 02 0.37 0.45
Harsh discip 0.06 7.08 ‐ 0.32 0.56
mo rvisio .21 0.25 0.55
Relationship h dawarm 0.47‐ 0.19 2.52‐ 0.01 0.83‐ 0.10‐
ive re 12 42 0.05 0.52
Consistent d dacons 0.44‐ 0.15 .96 0.00 0.73‐ 0.15‐
al effi 0.10 89 0.29
ohe 0.10 78 0.46
Smoking 15a1 0.27 0.10 .55 0.01 0.06 0.47
cons on 0.20 7 0.12
Overprotection daoverp 0.16 0.11 4 0.15 0.06‐ 0.38
erame 4 .87
Parental an n 0.17
Gender 0.14 4.75‐ 0.40
Socioeconomic status 1.60‐ 0.11 0.24‐ 0.02
Parental education level
Var Coef. Std. Er
casdqta 0.41 0.
dahostc 0.44
t
20.39
|t| [95%
‐
line
Parental nitoring / supe
quality / warmt
n dpa08a1 0.15 0 0.73 0.47 ‐
Induct asoning
iscipline
daireas 0.29 0. 2.
2‐
0.02
Parent
Family c
cacy
sion
dpa01a 0.09
dre06a 0.27
dhb
0.
2.
2
0.37 0.11‐
0.01 0.08
Alcohol umpti daalcgpm 0.28‐ 1.3‐
1.4
0.17 0.68‐
Temp nt
xiety & depressio
dse06a 1.57 0.1
dak6 1.02‐
zf02m1 0.68‐
dhinc 0.11‐ 0.00
dcomboe
10
5.95‐
‐ 1.29 1.86
‐ 1.36‐ 0.68‐
‐ 0.96‐ ‐
d 0.05
zf02m2 0.79‐
0.07 0.70 0.48 0.09‐ 0.19
Parent gender 0.59 1.34‐ 0.18 1.95‐ 0.37 R2=0.49, F = 105.48 No. observat
K3 (easdqta)
ions = 2,938.
Table C.25: Addictions
Category t P> s]
Lag dep var dasdqta 0.59 0.02 32.91
Harsh discipline eahostc 0.38 0.06 6.60
Parental monitoring / supervision epa08a1 0.02‐ 0.07 0.36‐ 0.11
Relationship quality / warmth eawarm 0.18‐ 0.14 1.34‐
Inductive reasoning eaireas 0.17 0.11 1.58
Consistent discipline eacons 0.40‐ 0.13 3.04‐
Parental efficacy epa01a 0.08‐ 0.09 0.90‐
Family cohesion ere06a 0.14 0.08 1.71 0.02‐ 0.31
0.10 8
Alcohol cons 0.25 0.18 1.38‐
Overprotec eaoverp 0.22 0.10 2.25 0.41
erame 13 .23 1.34 1.85
Parental anxiety & depression eak6 1.02‐ 0.13 ‐ 1.28‐ 0.76‐
13 4.72 0.86 0.36‐
nom 00 0.17 0.01
Parental edu el
Var Coef. Std. Err |t| [95% Conf Interval
‐ 0.56 0.63
‐ 0.26 0.49
0.72 0.16‐
0.18 0.45‐ 0.09
0.11 0.04‐ 0.37
0.00 0.66‐ 0.14‐
0.37 0.25‐ 0.09
0.09
Smoking ehb15a1 0.19
eaalcgpm ‐
1.90 0.06 0.01‐ 0.3
0.17 0.60‐ 0.10
0.02 0.03
umption
tion
Temp nt ese06a 1.60 0. 12
7.69‐
‐
Gender
Socioeco
zf02m1 0.61‐ 0.
ehinc 0.08‐ 0.
ecomboe
‐
1.74‐
‐ ‐
0.08 ‐ ic status
cation lev d 0.01
zf02
0.06 0.90 0.12‐ 0.13
Parent gender m2 0.12 0.44 0.28 0.78 0.73‐ 0.98
nt 43 3.98 8.48
0.12
Consta _cons 5.68 1. ‐ 2.88 R2=0.49, F = 1 serva05.48 No. ob tions = 2,938.
104
Appendix D: LSAC variable specification
Table D.1: Standard LSAC variables
Variable Name
Person Label
Measure Question Values
aalcgp* n
t 1 (not in the last year); 2 Moderate (occasional to <4 day men, or to <2 day women); 3 Harmful (>=4 men, >=2
Alcohol consumptiogroups
primary carer alcohol consumption groups
Paren 1 Abstain
women)
abitp
05a2a, b, c, d, e, f, g, u,
Number
abmi Body mass index
Parent 1 Number
aconda SDQ Conduct problems scale
e be a integer
er items are
Parent 1 Number
acons Consistent
5. se
Parent 1
aemot Mean of cse03a3a, b, c, d and e r fewer
nent items are ing
Parent 1 Number
hacte Home activities index
Mean of che02a1d, 6d, 7d Parent 1 Number
ahostc Hostile parenting sc
umber
Inrescale
Mean of cpa09a1 and cpa09a2 P Number
ak6** K‐6 Depression Sc
ah a6 Parent 1 Number
aoverp Parental overprotection scale
P N
asdqta SDQ total score
Sum of cahy eer and cacond
Parent 1 N
BITSEA problems scale
Sum of bseh, i, j, k, l, m, n, o, p, q, r, s, t, v, w where fewer than 5 are missing (no contact counts as missing)
Weight in kg/(height in metres)**2
Mean of cse03a4a, b, c, d andrescaled to
Parent 1
between 0 and 10 where fewthan 3 componentmissing, cse03a4b reverse coded
Mean of cpa11a1, 2, 3, 4,parentingscale
SDQ
With cpa11a3, 4 &5 revercoded
Number
Emotional symptoms scale
rescaled to be a integebetween 0 and 10 wherethan 3 compomiss
a
ale
ductive
Mean of apa04a1, 2 and 4 Parent 1 N
aireas asoning
arent 1
ale
Mean of s24a1 to ahs24
Mean of bpa15a1 to 3
pr, caemot, capa
arent 1 umber
umber
Positive Family Functioning
105
VariabName
le Measure n Person Label
VQuestio alues
assc Involvement inclass activities
to
Parent 1 N
Number ofdhe15a1a
'yes' responses to dhe15a5a
umber
awarm Parental warmth scale
Mean of ap Parent 1 N
cbmi Body mass index
Weight in kg Study Child
N
f02m1 Sex Is the Studyfemale?
Study Child
1 Male; 2 Female
2m2 Se 1 m Parent 1
1 emale
fn05 Combined yearly income before tax
cohat is you
income (forcombined)? pensions
lowan , annua
e) ( om
Not Applicable
Categories were converted to dollars taking the mean of each category.
hb14c4 Choice of physical activity in free time
What does ly do when she/h about how to spend free time?
Study Child
1pcr t as likely to c as inactive pastimes; 3 Usually chooses active pastimes like bike riding, dancing, games or sports; (‐2 Don't know)
smoke at all; 2 3 At
least once a day
hfat Food diary Sum of chb21c1a to chb21c4a Not Applicable
Number
hinc*** Usual weekly income
Sum of bfn09a, b and o (if not missing any, other than skipped)
Not Applicable
Number
hs14d Special health care needs screener
Does child need or use more medical care than is usual for most children of the same age?
Not Applicable
1 Yes; 2 No; (‐2 Don't know)
hs23c2 Weight Weight of child Study Child
Number
hsdrnk Food diary sum of bhb21b1a & bhb21b2a Not Applicable
Number
pa01a Global rating of self‐efficacy
Overall, as a parent, do you feel that you are…
Parent 1 1 Not very good at being a parent; 2 A person who has some trouble being a parent; 3 An average parent; 4 A better than
a03a1 to apa03a6
/(Height in m)**2
Child male or
umber
umber
f0 x Is Parent
Before inw
ale or female?
me tax is taken out, r present yearly you and partner (Include
@W1 Male; 2 F
and alsuperinsurancPartner c
ces) (before taxtion or health Parent 1 andbined) (Before tax)
child usuale has a choice
Usually chooses inactive astimes like TV, omputer, drawing or eading; 2 Jushoose active
hb15a1 Frequency of cigarette smoking
How often do you currently smoke cigarettes?
Parent 1 1 Do notLess than once a day;
106
Variable Measure Question Person Values Name Label
average parent; 5 A very good parent
pa08a1 Importance of monitoring / supervising child
It is im pknow whe ir childwhat he/s g alltime. Do
P S reDisag eithernor disagree; 4 AgreStron e
DS QL emotional
Mean of c 1a to cgd04b1e so th1=100, 2= 50, 4=25=0, only value if than 3 ite missin
NotAppl
Number
c PEDS Global n
agd01a w codwith yes.
Not App
1 Yes/ ; 2 No
Family ability along
other
Sometime ily membmay have lty gettialong with another. don't alw ree and tmay get ang . In genera would you rate your famability to with another?
Pare 1 Exce 2 Very g Good; ; 5 Poor
d's age (months)
Study child in monthtime of survey
Not Appl
Numb
temperament Overall, com ared to othechildren of t e same age, do you think is...?
Pare 1 Easi averagAbout ge; 3 Modifficu averag
wlrnoiOutcome
Learning Outcome Indexcontinuou e
Not Appl
Number
portant that arents re the is and he is doin the you:
arent 1 1 trongly disag e; 2 ree; 3 N agree
e; 5 gly agre
pedsef PE
functioning
gd04b recoded at 75, 3= 5, and has a fewer ms are g
icable
pedsgConcer
ith 'a little' ed licable
A little
re06ato getwith each
s fam ers difficu ng oneays ag
Theyhey
ry l, howily's
get along one
nt 1 llent; ood; 3 4 Fair
scagem Study Chil age s at icable
er
se06a General p r histh child
nt 1 er than e; 2 averalt than
re e
Learning
Index
s scor icable
Notes: Variable name is in the LSAC ‘without age’ format. s from the original six.
converted to a sum, original is mean. annum.
Table D.2: Combinatio LSAC variables
put
variables Measure uestion Pe
LabValu
* truncated to three categorie***** converted to dollars per
ns of
New Invariable
Q rson el
es
etain1 egweek Amount of weekend electronic games
otal minutlaying an estem on verage we
NotApplicable
NumT es p game sy an a ek
ber.
he06b1 Amount of weekday TV
ut how rs on a t
would u that chiches TV
ideos at ho
NotApplicable
1 Do watch Tvide thanhour; to 3 hours; 4 3 up urs; 5 5mor s; (‐2 Doknow
houAbo many
ypicalweekday,say
yold
wat or v me?
es not V or os; 2 Less one 3 1 up to 5 ho
or
e hour n't )
Positive Family Functioning
107
New variable
Input variables
Measure Question Person Lab
Values el
he06c1 Amount of weekend TV
ut how rs on a t ekend da s d watchos at hom ? (If
for urday and day, givrage hou
NotApplicable
1 Do watch Tvide thanhour to 3 h 3 up urs; 5 5mor s; (‐2 Don'tknow)
houAbo many
ypicalwe y, doechil TV or vide edifferentSatSun e ave rs)
es not V or os; 2 Less one ; 3 1 up ours; 4 to 5 ho or e hour
he07b2 Amount of weekday computer use
ut how rs on a t ekday wo u that study a comp at e?
NotApplicable
Num
dn2 fd08a1 Highest
level of schooling
at was theest yeaary or
ondary sent 1
Paren 1 1 Ye equivalent; 2 Year quivalYear equivaleYear alenYear w; 6 attended school; 7
(‐
post‐secondary
completed a trade certificate or any
qualification?
Abo many hou ypicalwe uld yosay child
uter useshom
ber
comboe
completed
Wh high r of primsec chool Parcompleted?
t ar 12 or 11 or e ent; 3 10 or nt; 4 9 or equiv t; 5 8 or belo
NeverStill at
school; (‐2 Don't know);3 Refused)
fd08a2a Completed Has Parent 1 Parent 1 1 Yes; 2 No
qualification other educational
N am ’1 etain is the sum of the four electronic entertainment variables measured in hours per week.
de e 8a1 with tion of 0 parent has co ry tion from fd08a2.
otes: Variable N e is in the LSAC ‘without age format.
2 comboedn is coeduca
d as the sam as fd0 the addi if mpleted post‐seconda
108
Appendix E n d stan deviation of les
Category 0‐1 years 2‐3 years 4‐5 yea 7 years 8‐9 years
: Mea an dard LSAC variab
rs 6‐
Obesity 9.22 16.84 16.84 16.49 17.59
1.44 1.59 1.59 2.13 2.84
00
9.72 10.18 9.73 9.81 9.90
Anxiety and depression 1.94 74.06* 74.66 1.58* 1.57
0.24 14.06 14.18 1.68 1.75
Antisocial 1.94 30.21* 2.14* 2.43 1.45
0.24 4.46 1.78 1.98 1.47
Addictions 1.94 30.21* 8.18* 7.81 7.49
0.24 4.46 4.68 5.02 5.32
Harsh discipline 1.93 3.09 3.17 3.36 3.29
1.14 1.30 1.28 1.45 1.41
Parental monitoring 4.82 4.51 4.85 4.64
0.44 1.07 0.40 0.94
Relationship warmth 4.55 4.61 4.50 4.44 4.32
0.41 0.42 0.47 0.48 0.55
Inductive reasoning 4.24 4.23 4.24 4.14
0.65 0.63 0.64 0.68
consistent discipline 4.19 4.16 4.19
0.61 0.61 0.61
Parental self‐efficacy 4.08 4.09 3.85 4.07 3.84
0.96 0.80 0.84 0.82 0.86
Family cohesion 1.99 2.05 2.17 2.16
0.81 0.84 0.85 0.87
Parental home education 1.96 1.69 1.36 1.46
0.55 0.56 0.53 0.63
Parental involve school 3.79 3.32
1.15 1.38
Fatty foods 1.14 1.69 1.22 1.88
0.84 1.12 0.85 1.18
Sugary Drinks 1.28 1.33 1.41 1.37
1.11 1.30 1.15 1.32
Exercise 2.16 2.02 1.99 1.96
0.72 0.76 0.75 0.77
E‐tainment 41.80 54.75 55.17 57.48
10.35 27.95 10.90 11.58
Smoking 1.35 1.30 1.34 1.32 1.38
0.74 0.70 0.74 0.73 0.77
Alcohol consumption 1.82 1.80 1.81 1.83 1.82
0.38 0.41 0.40 0.39 0.40
Overprotection 3.65 3.58 3.51 3.54
Productivity 99.63 100.49 100.94 101.06 101.
Positive Family Functioning
109
Category 0‐1 years 2‐3 years 4‐5 years 6‐7 years 8‐9 years
0.69 0.69 0.73 0.72
Temperament 1.73 1.72 1.73 1.68 1.67
0.51 0.56 0.56 0.59 0.59
depression 4.43 4.52 4.47 4.47 4.42
0.56 0.53 0.56 0.59 0.61
nths 5
8
income ($'0 0.6
.0
Parental education leve 1.57 1.52 1.47 1.65 1.58
1.13
Parent gender
Parent body mass index 25.44 25.03 25.70 25.42 25.88
Needs extra medical ca 0 1.89 1.88
&Parental anxiety
Gender 1.49 1.49
Age in mo
0.50 0.50
8.78 33.89 57.58 81.87 105.5
Household
2.56 2.91 2.83 2.94 2.8
00 pa) 52.2 80.8 99.0 83.4 10
35.1 51.1 70.8 53.9 68
l
1.08 1.05 1.00 1.18
1.99 1.97
0.12 0.16
5.39 5.06 5.50 5.12 5.29
re 1.92 1.92 1.9
0.37 0.35 0.34 0.35 0.38
Notes. Numbers in ordinar in italics are standard deviations of sample. Text i
text in the ‘Category’ colum 4‐5 year cohort is B3 not K1 (see Appendix C anriable.
ries Varia
y text are means of the analysis sample. Numbersthe analysis n bold indicates dependent variables. Ordinary text is common input variables. Italic
n is variables peculiar to specific regressions. Thepreamble tochange of va
d footnote 5). Appendix D provides greater description of these variables. *indicates
Illustrative distribution of categorical variables
Catego ble Answer=1 Answer=2 Answer=3 Values
infant anxiety and
*
apeds
depression
gc 267 3,985 1 Yes/A little; 2 No
smoking ahb1 1 Do not smoke at all; 2 Less
once a day
consumption aalcg r);
derate ( <4 drinks /day
Hazardous (>=4 men, >=2
Choice of ivity
hb14c 1939 1506 1 Usually chooses inactive
to choose active as tive pastimes; 3 Usually
bike riding, dancing, games or
gender child zf02m
5a 3034 116 600 than once a day; 3 At least
alcohol pm 649 3,010 6 1 Abstain (not in the last yea2 Momen, <2 women); 3
women)
4 808 physical actin free time
pastimes like TV, computer, drawing or reading; 2 Just aslikelyinacchooses active pastimes like
sports; (‐2 Don't know)
1 2178 2,075 1 Male; 2 Female
110
Categories Varia er=1 Answer=2 Answer=3 Values ble Answ
gender adult zf02m2 58 4,195 1 Male; 2 Female temperament ase06 2,181 98 1 Easier than average; 2 About
average; 3 More difficult than average
xtra medical care
ahs14d 264 3,987 1 Yes; 2 No; (‐2 Don't know)
a 984
e
Note: Only the first age at which a given variable is used is shown in the table. * Also used for infant antisocial t addic
behaviour and infan tions.
Positive Family Functioning
111
Appendix F: AT
Productivity Variable name
P variable interpretation
Description
attach96 parents, high score = high attachment, adolescent report, 13‐
attach00 report, 17‐
alientn96 gh alienation, adolescent report,
alientn00 igh alienation, adolescent report,
totrelqual th, quality rship,
chrqual00 ager report at 17‐18
totharshd
superv96 , parent report 13‐14 years
Parental monitoring/supervision of teen’s activities/associates, high score = high supervision, parent report 15‐16 years
Parental monitoring/supervision of teen’s activities/associates, high score = high supervision, teenager report 17‐18 years
cipline, high score = inconsistent, parent report 17‐18 years
n, parent report at 17‐18 years, high score = high cohesion
/conflictual parent‐teenager relationship, parent report 17‐18 years
7‐18 years, high score = low education
7‐18 years, high score = low education
2 years
s
15‐
acht98 e = lower achievement, teenager
totpersist very persistent, composite mean
enter02 e, available for 766 cases only
e, ‐20 years
, university), young adult report
Attachment to14 years
Attachment to parents, high score = high attachment, adolescent 18 years
Alienation from parents, high = score = hi13‐14 years, 2 ITEMS ONLY
Alienation from parents, high = score = h17‐18 years
Relationship quality/warmth, high score = high warmcomposite mean score of parent report at 13‐14, 15‐16 & 17‐18 years
Relationship quality, high score = high quality rship, teenyears
Harsh discipline, high score = high harsh discipline, composite mean score of parent report at 13‐14, 15‐16 and 17‐18 years
Parental monitoring/supervision of teen’s activities/associates, high score = high supervision
superv98
parsup00
inconst00 Inconsistent dis
hesiocohes00
negpt00
Family co
Negative
totmothed Mother’s education, composite mean score, parent report at 13‐14, 15‐16 &1
totfathed Father’s education, composite mean score, parent report at 13‐14, 15‐16 &1
tacp94 Academic competence, high score = high competence, teacher report at 11‐1
totmschprb Academic and social school problems, composite mean score,s parent reportat 13‐14 & 15‐16 years, high score more problem
posaff98 Positive affect towards school, high score = lower affect, teenager report16 years
Perceived achievement at school, high scorreport 15‐16 years
Persistent temperament style, high score =score of parent report at 11‐12, 13‐14, & 15‐16 years
Tertiary entrance scor
cmplsch # Did, or did not, complete secondary school (year 12), dichotomous variablyoung adult report 19
educ06_2 + Highest level of education completed‐ ‐ 4 level variable (less than year 12, year 12, post‐secondary but not university
112
23‐24 years
ed_empl_2 # ous variable, young adult Fully engaged vs. not fully engaged, dichotomreport 23‐24 years
# = dichotomous outc
outcome v
Obesity me
ome score
+ = ordinal ariable
Variable na Description
attach96 port, 13‐
attach00 lescent report, 17‐
Alientn96 olescent report,
alientn00 from parents, high = score = high alienation, adolescent report,
negpt00 onflictual parent‐teenager relationship, parent report 17‐18 years, high score = high conflict
ve reasoning, composite mean score of parent report at 13‐14, 15‐16 7‐18 years, high score = high use of reasoning
hd Harsh discipline, composite mean score of parent report at 13‐14, 15‐16 and 17‐18 years, high score = high harsh discipline
arental monitoring/supervision of teen’s activities/associates, parent report igh score = high supervision
t high score = high supervision
ion
*
‐16 years
*
* years
* ent
*
2 *
Attachment to parents, high score = high attachment, adolescent re14 years
Attachment to parents, high score = high attachment, ado18 years
Alienation from parents, high = score = high alienation, ad13‐14 years, ONLY 2 ITEMS
Alienation17‐18 years
Negative/c
totusereas Inducti& 1
tothars
superv96 P13‐14 years, h
superv98 Parental monitoring/supervision of teen’s activities/associates, parent repor15‐16 years,
parsup00 Parental monitoring/supervision of teen’s activities/associates, teenager report 17‐18 years, high score = high supervis
menc98_2 Mother encourages child to lose weight – 1 = no, 2 = yes responses, parent report 15‐16 years
fenc98_2 * Father encourages child to lose weight ‐ 1 = no, 2 = yes responses, parent report 15
mdiet98_2 Mother diets to lose weight ‐ 1 = no, 2 = yes responses, parent report 15‐16 years
fdiet98_2 * Father diets to lose weight ‐ 1 = no, 2 = yes responses, parent report 15‐16 years
curr9801_2 Child overeats at mealtimes currently, 1 = no, 2 = yes responses, parent report 15‐16
curr9802_2 Child eats a lot at between meals currently, 1 = no, 2 = yes responses, parreport 15‐16 years
past9801_2 Child overate at mealtimes in the past, 1 = no, 2 = yes responses, parent report 15‐16 years
past9802_ Child ate a lot at between meals in the past, 1 = no, 2 = yes responses, parentreport 15‐16 years
soc9830 ** Child participates in school sports teams, 3 level var, high = high participation, parent report 15‐16 years
soc9834 ** Child participates in community sports teams, 3 level var, high = high
Positive Family Functioning
113
participation, parent report 15‐16 years
diets98 ** Child has dieted to lose weight, 4 level var (no, once, 2‐3 times, many times),
hen upset, eats moderately in public but not in private, eats in ,
t able
# young adult report at 23‐24
high = high dieting, teenager report, 15‐16 years
eatprb98 Composite variable assessing eating behaviours and perceptions of weight (eats wsecrecy, thinks self is too fat, dissatisfied with body shape), teenager report15‐16 years
Intactf * Intact/non‐intact family over child’s lifetime to 18 years (non‐intact = separated, divorced, death of parent), parent report 17‐18 years
totmothed Mother’s education, composite mean score, parent report at 13‐14, 15‐16 &17‐18 years, high score = low education
totfathed Father’s education, composite mean score, parent report at 13‐14, 15‐16 &17‐18 years, high score = low education
totreact Reactive temperament style, composite mean score of parent report at 11‐12, 13‐14, & 15‐16 years, high score = very reactive
totpersist Persistent temperament style, composite mean score of parent report at 11‐12, 13‐14, & 15‐16 years, high score = very persistent,\
totapprch Approach/sociability temperament style, composite mean score of parenreport at 11‐12, 13‐14, & 15‐16 years, high score = very approaching/soci
Weight_3 Body mass index at 23‐24 years, 3 level outcome var in which 1 = underweight/normal, 2 = overweight, 3 = obese,years (n = 902)
* = dichotomous var
r
# = ordinal outcome var
Anxiety and/or d Desc
** = ordinal va
epression Variable name ription
attach96 Attachment to parents, high score = high attachment, adolescent report, 13‐14 years
to parents, high score = high attachment, adolescent report, 17‐18
from parents, high = score = high alienation, adolescent report, 17‐18 years
Relationship armth, high score = high quality/warmth, composite mean score ort at 13‐14, 15‐16 & 17‐18 years
Rela
totusereas Indupare
Hars f pare years
Enmpare
Maripare ‐18 years
Mariqual ship, parent report 17‐18 years
attach00 Attachmentyears
alientn00 Alienation
totrelqual quality/w of parent rep
chrqual00 tionship quality, high score = high quality, adolescent report, 17‐18 years
ctive reasoning, high score = high use of reasoning, composite mean score of nt report at 13‐14, 15‐16 & 17‐18 years
totharshd h discipline, high score = high harsh discipline, composite mean score ont report at 13‐14, 15‐16 and 17‐18
enmesh00 eshment/overprotection, high score = high enmeshment/overprotection, nt report 17‐18 years
mconflic tal conflict over life of ATP child to 17‐18 years, high score = high conflict, nt report 17
marqual tal relationship quality over life of ATP child to 17‐18 years, high score = high ity relation
114
totmaltr* Expe lt retro rt at 23‐24 years, range 0 to 3
rience of child maltreatment/neglect during first 18 years of life, young aduspective repo
totfamstrss Occucom report at 13‐14, 15‐16 & 17‐18 years
Reac n score of pare
totpersist Pers igh score = very persistent, composite mean score of pa
Appr re = very approaching/sociable, com
anx_dep02** Anxi r very severe levels of depr
anx_dep06** Anxi severe levels of depression,
meananxdep02# Anxiety/depression outcome: mean of depression and anxiety, young adult report at 19
meananxdep06# Anxiety/depression outcome: mean of depression and anxiety, young adult report at 23
rrence of family life events (changes, problems) in previous 12 months, posite mean score of parent
totreact tive temperament style, high score = very reactive, composite meant report at 11‐12, 13‐14, & 15‐16 years
istent temperament style, hrent report at 11‐12, 13‐14, & 15‐16 years
oach/sociability temperament style, high sco totapprchposite mean score of parent report at 11‐12, 13‐14, & 15‐16 years
ety/depression outcome: moderate, severe oession, and/or anxiety, young adult report at 19‐20 years
ety/depression outcome: moderate, severe or very and/or anxiety, young adult report at 23‐24 years
‐20 years
‐24 years
= ordinal score
omous outcome
# = continuous outcome sc
SmokingVariable name
** = dichot score
ore
Alcohol/ Description
smokeh_2* nt report 17‐18
Agedrh* allowed to drink at home, 1 = 15 years or older, 2 = 14
Talkdr** little, 3 = a lot, parent
attach96 report, 13‐
attach00 lescent report, 17‐
alientn96 t report, 13‐14 years, 2 ITEMS ONLY
ienation from parents, high = score = high alienation, adolescent report, 17‐18 years
reasoning, high score = high reasoning, composite mean score of at 13‐14, 15‐16 & 17‐18 years
‐16 and 17‐18 years
rvision, parent report 13‐14 years
rvision, parent report 15‐16 years
Teenager is allowed to smoke at home, 1 = no, 2 = yes, pareyears
Age teenager was firstyears or younger, parent report 17‐18 years
Parent talks with teenager about drinking 1 = no, 2 = a report 17‐18 years
Attachment to parents, high score = high attachment, adolescent14 years
Attachment to parents, high score = high attachment, ado18 years
Alienation from parents, high = score = high alienation, adolescen
alientn00 Al
totusereas Use of
parent report
totharshd Harsh discipline, high score = high harsh discipline, composite mean score of parent report at 13‐14, 15
superv96 Parental monitoring/supervision of teen’s activities/associates, high score = high supe
superv98 Parental monitoring/supervision of teen’s activities/associates, high score = high supe
parsup00 Parental monitoring/supervision of teen’s activities/associates, high score =
Positive Family Functioning
115
high supervision, teenager report 17‐18 years
inconst00 s
s
totmsmoke 13‐14, & 17‐18
years
daysm02_1 the past month, continuous outcome,
daysm02_2 # port at 19‐20 years
2 +
1
daysm06_2 remainder of sample, young adult report at 23‐24 years
e, young adult report at 23‐24 years
at 23‐24 years
Inconsistent discipline, high score = inconsistent, parent report 17‐18 year
negpt00 Negative/conflictual parent‐teenager relationship, parent report 17‐18 year
Mother smoking, composite mean score of parent report atyears
ttotfsmoke Father smoking, composite mean score of parent report at 13‐14, & 17‐18 years
totmdrink Mother drinking, composite mean score of parent report at 13‐14, & 17‐18 years
totfdrink Father drinking, composite mean score of parent report at 13‐14, & 17‐18 years
totreact Reactive temperament style, high score = very reactive, composite mean score of parent report at 11‐12, 13‐14, & 15‐16
totpersist Persistent temperament style, high score = very persistent, composite meanscore of parent report at 11‐12, 13‐14, & 15‐16 years
Number of days smoked cigarettes inyoung adult report at 19‐20 years
Daily smoker vs remainder of sample, young adult re
binged02 Number of days in past month had 5+ drinks in a session, continuous outcome, young adult report at 19‐20 years
binged02_ 0, 1‐4, and 5+ days in past month had 5+ drinks in a session, young adult report at 19‐20 years
daysm06_ Number of days smoked cigarettes in the past month, continuous outcome, young adult report at 23‐24 years
Daily smoker vs
binged06 Number of days in past month had 5+ drinks in a session, continuous outcom
binged06_2 0, 1‐4, and 5+ days in past month had 5+ drinks in a session, young adult report
* = dichotomous var
** = ordinal variable
mous outcome
+ = ordinal outcome variab
Illicit Drugs ame
# = dichoto score
le
Variable n Description
totmaltr * 18 years of life, young ent
cohes00
marqual TP child to 17‐18 years, high score = high quality relationship, parent report 17‐18 years
ent to parents, high score = high attachment, adolescent report, 13‐14 years
attach00 Attachment to parents, high score = high attachment, adolescent report, 17‐18 years
Experience of child maltreatment/neglect during first adult retrospective report at 23‐24 years, range 0 to 3 types of maltreatm
Family cohesion, parent report at 17‐18 years, high score = high cohesion
mconflic Marital conflict over life of ATP child to 17‐18 years, high score = high conflict, parent report 17‐18 years
Marital relationship quality over life of A
attach96 Attachm
116
alientn00 Alienation from parents, high = score = high alienation, adolescent report, 17‐18 years
negpt00 Negative/conflictual parent‐teenager re
high scolationship, parent report 17‐18 years,
pospt00 Positive, communicative, good problem solving, parent‐teenager relationship, parent report 17‐18 years, high score = high communication/closeness
ivities/associates, high score = high supervision, parent report 13‐14 years
parsup00 iates, high score = high supervision, teenager report 17‐18 years
e n score of parent report at 13‐14, & 17‐18
ttotfsmoke
totmdrink Mother drinking, composite mean score of parent report at 13‐14, & 17‐18
totfdrink Father drinking, composite mean score of parent report at 13‐14, & 17‐18
totreact Reactive temperament style, high score = very reactive, composite mean
totpersist Persistent temperament style, high score = very persistent, composite mean
14, & 15‐16 years
+
totilldrg02_2 + l outcome variable: number of illicit drugs used on one or more day/s rt at 19‐20 years
+ (range 0‐4), young adult report at 23‐24 years
2 + month: 0, 1, 2+ drugs; young adult report at 23‐24 years
re = high conflict
superv96 Parental monitoring/supervision of teen’s act
superv98 Parental monitoring/supervision of teen’s activities/associates, high score = high supervision, parent report 15‐16 years
Parental monitoring/supervision of teen’s activities/assoc
totmsmok Mother smoking, composite meayears
Father smoking, composite mean score of parent report at 13‐14, & 17‐18 years
years
years
score of parent report at 11‐12, 13‐14, & 15‐16 years
score of parent report at 11‐12, 13‐14, & 15‐16 years
totapprch Approach/sociability temperament style, high score = very approaching/sociable, composite mean score of parent report at 11‐12, 13‐
totilldrg02 Number of differing types of illicit drugs used on one or more day/s in past month (range 0‐4), young adult report at 19‐20 years
3 levein past month: 0, 1, 2+ drugs; young adult repo
totilldrg06 Number of differing types of illicit drugs used on one or more day/s in past month
totilldrg06_ 3 level outcome variable: number of illicit drugs used on one or more day/s in past
* = ordinal variable
Antisocial behaviouVariable name Description
+ = ordinal outcome variable
r
selfcptpar conce about h pare ts, child t at 1 = c
attach96 Attachment to parents, high score = high attachment, adolescent report, 13‐ars
hme are h sco = hig chment, scen rt, 17ars
ation pare igh = re = lienation esce rt,
Selfscore
pt high self
relationsoncept
ip with n repor 1‐12 years, high
14 ye
attach00 Attac nt to p nts, hig re h atta adole t repo ‐18 ye
alientn00 Alien from nts, h sco high a , adol nt repo
Positive Family Functioning
117
17‐18 years
cohes00 Family cohesion, parent report at 17‐18 years, high score = high cohesion
ionsh ality/ th, hi scor qualit compositen sco ar rt at 14, 1 17‐18
ionsh ality, h q , adoles port ye
h disc , high = hi hars pline, c te me orent re 1 16 an 17‐1 s
ntal m ring/ vision f tee ivities/ es, hi ore supervision, parent rt 13‐14 ye
8 ntal m rin vision f tee ivities/ es, ore supervision, parent rt 15‐16 ye
monitoring/s teen’s hi ore =supervision, te repo ‐18
sis cipl h sco inconsistent, pa ort 17‐18 rs
conflict, parent report 17‐18 years
to 17‐18 years, high score =
Intactf* = separated, divorced, death of parent), parent report 17‐18 years
fdivsep Effect ntal h on high scparen ort at
divsep00 Effect of paren al separation, divorce, death on child, high score = bad effect, age at 1 s. IS US UT IF MISSIN PARENT PORT TITU
er smoking, co te mean scor re 13 7‐1s
er smoking, composite mea score rent rep ‐14 ‐18
drinki com mean score report 13‐14 ‐18s
er dri composite mea score rent repo 3‐14 ‐18s
tive t rame le, hi score ry reactiv posi n of p re ‐12, ‐14, 16 years
stent eram tyle, high sco ery persis omp me of paren report ‐12, ‐14, ‐16 years
e/an l behaviour outc e: involvement in 3 re differing s of antisocial s in past 12 months (includ it s e youn lt re t 19‐2
fering types of antisocial activities in past 12 months (including illicit substance use), young adult report at 23‐24 years
totrelqual Relat ip qu warm gh e = high y/warmth, mea re of p ent repo 13‐ 5‐16 & years
chrqual00 Relat ip qu high score = hig uality cent re , 17‐18 ars
totharshd Hars ipline score gh h disci omposi an sc of pare port at 3‐14, 15‐ d 8 year
superv96
Pare onito super o n’s act associat gh sc = high repo ars
superv9 Pare onito g/super o n’s act associat high sc = high
Parental
repo
upervision
ars
activities/associates,parsup00 of gh sc high enager rt 17 years
inconst00 Incon tent dis ine, hig re = rent rep yea
mconflic Marital conflict over life of ATP child to 17‐18 years, high score = high
marqual Marital relationship quality over life of ATP child high quality relationship, parent report 17‐18 years
Intact/non‐intact family over child’s lifetime to 18 years (non‐intact
ef of paret rep
separation,17‐18 years
divorce,
deat child, ore = bad effect,
tr reportteen 7‐18 year TH ED, B G, RE
SUBS TED
totmsmoke Moth mposi e of parent port at ‐14, & 1 8 year
ttotfsmoke Fath n of pa ort at 13 , & 17 years
Mothertotmdrink ng, posite of parent at , & 17 year
totfdrink Fath nking, n of pa rt at 1 , & 17 year
totreact Reac empe nt sty gh = ve e, com te meascore arent port at 11 13 & 15‐
totpersist Persiscore
tempt
ent s at 11
re = v& 15
tent, c osite an 13
anti02** Crim tisocia om or motype activitie ing illic ubstancuse), g adu port a 0 years
anti06** Crime/antisocial behaviour outcome: involvement in 3 or more dif
* = dichotomous var
** = dichotomous outcome score
118
Appendix G: ATP
Descriptions of the variable names below are in Appendix F.
Productivity
agement (children no oy no tudyi
predictor variables in G.1 found to be cant logistic
G.1: ren en dic ariab
Attachm pare ild 18;
Regression outcomes
Undereng t empl ed and t s ng)
None of the Table was signifi in a regression.
Table Unde gagem t pre tor v les
attach00 ent to nts ch age 17‐
totrelqual Relation ualit th, sit ean s par ort at age14, 15‐1 ‐18 y nterp as w ithou iplin
Harsh d e, co ite m ore paren rt at , 15‐1 17‐1years
Parental teen’s activities/associates, nt re 13‐14years
Parental orin rvi tee activi soci rent 15‐1years
Parental orin rv tee activi socia enage rt 17years
Negative ictua nt‐teenager re ionsh ent ‐18
Inconsisten scipline, gh score inconsistent, pa nt report ‐18 years
Mother atio posit n s e, par port a , 15 ‐1years
Father’s tion osite sc , pare ort at , 15‐1 7‐18
Academic a social school problems, composite mean scores parent repor 13‐14 &15‐16 y
Academ pet ache rt ‐12
Positive aff towards hool, teenage port 15‐1 years (Note that this s reversecoded)
Persiste pera style, osi mean of pa port a , 1& 15‐16 yea
ship q y/warm compo e m core of ent rep child 13‐6 & 17 ears (Note that this is i reted armth w t disc e)
totharshd isciplin mpos ean sc of t repo 13‐14 6 and 8
superv96 monitoring/supervision of pare port
superv98 monit g/supe sion of n’s ties/as ates, pa report 6
parsup00 monit g/supe ision of n’s ties/as tes, te r repo ‐18
negpt00 /confl l pare lat ip, par report 17 years
inconst00 t di hi = re 17
totmothed ’s educ n, com e mea cor ent re t 13‐14 ‐16 & 17 8
totfathed educa , comp mean ore nt rep 13‐14 6 & 1 years
totmschprb_2 nd t at ears
tacp94 ic com ence, te r repo at 11 years
posaff98 ect sc r re 6 wa
totpersist nt tem ment comp te score rent re t 11‐12 3‐14, rs
Completion of high sch
ble G.2: ompleti of gh school(a)(b)
95 for E
ool
Ta C on hi
% C.I. XP(B)
B S.E. Wald df Sig. Exp(
Lowe Upper B)
r
attach00 .3 .2 1.1 . 02 86 14 1 291 1.353 .772 2.370
totrelqual ‐1.0 .3 7.9 . 93 87 93 1 005 .335 .157 .715
totharshd ‐.4 .3 1.9 . 73 41 20 1 166 .623 .319 1.217
superv96 ‐.092 .461 .040 .842 .912 .36 2.25 1 9 4
Positive Family Functioning
119
95% C.I.f EXP(B) or
superv98 .145 .369 .154 1 . 1.1 .56 2.38695 56 1 1
parsup00 .7 .2 1 . 29 11 1.941 1 001 2.073 1.371 3.134
negpt00 .3 .5 . 83 03 .580 1 446 1.467 .547 3.936
inconst00 .0 .2 .0 . 39 92 18 1 894 1.040 .587 1.842
totmothed ‐. .1 12 . 480 37 .329 1 000 .619 .473 .809
totfathed .0 .1 .1 . 42 05 57 1 692 1.043 .848 1.281
totmschprb_2 ‐.4 .4 1.1 . 97 71 15 1 291 .608 .242 1.531
tacp94 . .0 9 . 023 07 .659 1 002 1.023 1.008 1.037
posaff98 ‐.6 .2 6 . 30 53 .196 1 013 .533 .324 .875
totpersist .8 .2 9 . 72 80 .717 1 002 2.392 1.382 4.139
Constant 3.3 3.2 1.0 . 72 42 82 1 298 29.128
(a) Base for comparison is not ting school. iables highlighted in bold nificant 0.05.
n of high s rsu ple university e
G.3: pletio high (only) v Uni
95% or
comple high (b) Var are sig at
Completio chool ve s com ting a degre
Table Com n of school versity degree(a)(b)
C.I.f EXP(B)
B df Sig. Exp(
Lo US.E. Wald B)
wer pper
Intercept ‐1.434 2.439 .346 .557 1
attach00 ‐.5 4.8 . 22 .237 39 1 028 .593 .373 .945
totrelqual21 . 4.7 . 607 .278 52 1 029 1.835 1.063 3.166
totharshd .099 .258 .147 .701 1.1 .66 1.83 1 04 6 0
superv96 .0 .0 . 02 .339 00 1 995 1.002 .516 1.947
superv98 ‐. . 202 .300 .453 1 501 .817 .454 1.471
parsup00 ‐.119 .167 .509 .476 .888 .63 1.23 1 9 2
negpt00 ‐.1 .3 . 16 55 .106 1 745 .891 .444 1.785
inconst00 .0 .2 .0 . 36 21 26 1 872 1.036 .672 1.598
totmothed ‐.016 .082 .038 .846 .984 .83 1.15 1 9 5
totfathed .3 .0 15.4 . 05 78 30 1 000 1.357 1.165 1.579
totmschprb_2 ‐.3 .5 . 01 91 .259 1 611 .740 .232 2.359
tacp94 ‐.007 .005 1.953 .162 .993 .98 1.00 1 3 3
posaff9822 .7 14.8 . 98 .207 55 1 000 2.220 1.480 3.331
totpersist ‐.3 3.1 . 77 .214 17 1 077 .686 .451 1.042
(a) Base for comparison is university de ) Vari in e sig at 0.05
gree. (b ables highlighted bold ar nificant .
21 This is interpreted as warmth without discipline.
22 This was reverse coded.
120
Obesity
Table G.4: Body mass index at 23‐24 years(a)(b)
B Error Wald df Sig. Exp(B)
Bound
Upper Bound
Std. Lower
Overweight
Intercept ‐9.801 3.29 .853 4 8 1 .003
bmi98 .409 .058 50.528 1 .000 1.505 1.685 1.345
eatprb98 .1 .187 98 .29 1.2 .843 1.96 1.0 1 5 16 753
attach00 ‐.2 .253 92 .40 .81 .493 1.11 .6 1 6 0 331
negpt00 ‐.4 72 .27 .6 .285 1.46 .412 1.1 1 9 40 436
totusereas .2 .255 94 1 .25 1.33 .811 2.290 1.2 5 7 05
totharshd .2 99 15 1 .339 1.3 .74 2.386 .2 .9 31 1 94
superv96 .4 .392 1.286 1 .257 1.560 .723 3.364 45
superv98 ‐.202 .338 .549 .817 .421 1.5.359 1 83
parsup00 .083 .189 .193 1 .660 1.087 .750 1.573
totmothed ‐.009 .094 .010 1 .921 .991 .824 1.191
totfathed 1.581 .279 .091 9.311 1 .002 1.322 1.105
totreact 1.278 ‐.247 .251 .970 1 .325 .781 .477
totpersist ‐.740 .234 10.021 1 .002 .477 .302 .755
totapprch .173 .203 31 .7 1 .393 1.189 .799 1.768
[intactf=1.00] 09 9 4 1 .3 1.3 .33 .83 61 .362 .702 2.646
[intactf=2.00] 0b . . 0 . . . .
[losewt2=.00] 60 0 7 1 .7‐.4 1.24 .13 11 .631 .056 7.178
[losewt2=1.00] 56 0 5 1 .7 .‐.4 1.29 .12 24 634 .051 7.942
[losewt2=2.00] 0b . . 0 . . . .
[diet2=.00] ‐.209 9 8 1 .81.06 .03 45 .811 .100 6.597
[diet2=1.00] 23 1 0 1 .9 1.0 1.07 .00 83 .024 .126 8.346
[diet2=2.00] 0b . . 0 . . . .
[overeat2=.00] ‐ 92 5 1 .2 .553 .221 1.38.5 .469 1.59 07 7
[overeat2=1.00] 64 7 6 1 .8‐.0 .49 .01 98 .938 .354 2.487
[overeat2=2.00] 0b . . 0 . . . .
[soc9830=0] .122 1 1 1 .7 1.43 .08 76 .130 .486 2.629
[soc9830=1] 96 5 0 1 .7‐.0 .30 .10 52 .908 .499 1.651
[soc9830=2] 0b . . 0 . . . .
[soc9834=0] 49 2 2 1 .6 1..1 .33 .20 53 161 .606 2.226
[soc9834=1] 21 3 1 1 .1 1. .809 2.87.4 .32 1.70 92 524 0
[soc9834=2] 0b . . 0 . . . .
[diets98=1] .276 .601 .211 1 .646 1.318 .406 4.284
[diets98=2] ‐.518 .631 .673 1 .412 .596 .173 2.054
[diets98=3] .041 .588 .005 1 .944 1.042 .329 3.299
[diets98=4] 0b . . 0 . . . .
Positive Family Functioning
121
Obese
Intercept ‐32.698 7.322 19.941 1 .000
bmi98 .992 .119 69.293 1 .000 2.696 2.135 3.405
eatprb98 ‐.477 .36 904 1.716 1 .1 .621 .304 1.267
attach00 ‐.333 .506 .433 1 .510 .717 .266 1.932
negpt00 1.940 .75 6.673 1 .010 6 2 .597 .346 1 .96 1 30
totusereas .475 1 1 1.607 .568 4.55.53 .799 1 .37 1
totharshd ‐.009 8 6 .9.51 .000 1 .98 91 .359 2.736
superv96 1.487 3 2 5 4.4 .8 2.86 .971 1 .08 26 15 4.020
superv98 ‐.819 5 1 0 .44 .1.62 .718 1 .19 1 29 1.501
parsup00 .727 1 3 6 2.07 .9.38 .647 1 .05 0 81 4.367
totmothed ‐.158 9 4 .8 .5.18 .697 1 .40 54 90 1.237
totfathed .831 18 2.2 1.5.194 .408 1 .000 96 71 3.356
totreact ‐.879 8 3 2 .41 .1.48 .248 1 .07 5 60 1.080
totpersist ‐1.055 4 .3 .1.476 .921 1 .027 48 37 .884
totapprch .235 4 8 1.2 .5.43 .293 1 .58 65 40 2.960
[intactf=1.00] .189 3 9 1.2 .3.67 .079 1 .77 08 23 4.520
[intactf=2.00] 0b . . 0 . . . .
[losewt2=.00] .362 2 7 1.4 .0 342.79 .017 1 .89 36 06 1.757
[losewt2=1.00] ‐1.236 9 0 .29 .0 72.80 .194 1 .66 1 01 1.418
[losewt2=2.00] 0b . . 0 . . . .
[diet2=.00] .106 6 5 1.1 .0 122.42 .002 1 .96 12 10 9.144
[diet2=1.00] 1.039 9 .18 1 9 2.827 .024 329.922.42 3 .66 1
[diet2=2.00] 0b . 0 . . . . .
[overeat2=.00] .407 7 2 1.503 .095 23.691.40 .084 1 .77 5
[overeat2=1.00] 1.750 7 1 0 5.7 91.42 .503 1 .22 54 .351 4.412
[overeat2=2.00] 0b . . 0 . . . .
[soc9830=0] .781 7 1 9 2.1 .4.76 .037 1 .30 84 86 9.823
[soc9830=1] .390 2 2 1.47 .4.58 .450 1 .50 8 73 4.619
[soc9830=2] 0b . . 0 . . . .
[soc9834=0] ‐.077 2 1 .9 .2.62 .015 1 .90 26 74 3.130
[soc9834=1] .868 3 2 0 2.38 .7 7.60 .071 1 .15 1 30 .761
[soc9834=2] 0b . . 0 . . . .
[diets98=1] .061 6 2 1.06 .11.02 .004 1 .95 3 42 7.938
[diets98=2] ‐.558 4 3 .5 .01.07 .270 1 .60 72 70 4.697
[diets98=3] .373 9 2 1.4 .2 11.00 .137 1 .71 52 01 0.493
[diets98=4] 0b . . 0 . . . .
(a) Base for comparison is normal/underweight. (b) les te sign at 0
analysis of ATP
Variab highligh d in bold are ificant .05.
Source: AIFS
122
Anxiety and depression
‐20 years is inTable G.5.
lovibond clinical depression levels 2002
The overlap between anxiety and depression at 19
Table G.5: ATP anxiety/depression 2002 crosstabulation
moderate severe
s
normal mild extremely
evere
Total
normal 68 18 4 823 2 62 57
mild 56 17 20 5 4 102
moderate 4 7 3 1 32 40 13 13
severe 9 3 10 9 4 35
lovibond clinical anxiety
extremely
re
3 8 9 12 22 54
levels 2002
seve
Total 79 1 122 136 57 41 1147
Dependent variable is anxious an depressed.
G.6: Logis ession resul child age 19‐ 2002)(a)(b)
B .E. Wal d S Ex9 L
d/or
Table tic regr ts — 20 years (year
S d f ig. p(B)
5% CIower
95% CIUpper
anx_dep96 .809 .16 23.1 8 89 1 .000 2.245 1.615 3.120
alientn00 .636 .18 11.8 1 5 21 .001 1.888 1.314 2.712
relqual00 .090 .24 .1 1 3 37 .711 1.094 .680 1.761
totusereas ‐.083 .22 .1 1 1 42 .706 .920 .597 1.419
totharshd ‐.242 24 .9 1 .487 1.264 . 3 92 .319 .785
enmesh00 .055 .131 .174 1 .677 1.056 .816 1.367
mconflic .220 .134 2.707 1 .100 1.246 .959 1.619
marqual ‐.157 .169 .871 1 .351 .854 .614 1.189
totmaltr .045 2 .978
totmaltr(1) .069 .376 .033 1 .855 1.071 .513 2.238
totmaltr(2) .091 .043 .835 1.095 .438 1 .464 2.586
totfamstrss .083 4 81 7 .151 .30 1 .5 1.08 .809 1.461
totreact .337 6 3.295 1 .070 1.401 .973 2.017 .18
totpersist ‐.329 3.166 .920 1 .048 .720 .519 .997
totapprch ‐.208 1 1.166 .569 1 .210 .813 .587 .124
Constant ‐2.461 11.894 .687 1 .194 .085
(a) Base for comparison is
Source: AIFS ana
not anxious/depressed. (b) Variables highlighted in bold are significant at 0.05.
lysis of ATP.
Positive Family Functioning
123
Alcohol
Dependent variable is no/some/high binge drinking(a) age 19‐20
Std r d . Exp(B) 9 L
95Up
B . Erro Wald f Sig5% CIower
% CIper
1‐4 days binge drinking
Intercept .334 2.515 .018 1 .894
drink96 .645 .234 1 37.587 .006 1.905 1.204 .014
Talkdr .048 .195 .060 1 .806 1.049 .715 1.539
attach00 ‐.087 .212 2 .168 1 .68 .917 .606 1.388
Totusereas ‐.079 .226 .122 1 .727 .924 .594 1.438
Totharshd .345 .274 1.577 1 .209 1.411 .824 2.416
superv96 .072 .351 6 2.043 1 .83 1.075 .541 .137
superv98 ‐.408 .320 1.628 1 .202 .665 .355 1.244
parsup00 .100 6 1.5.162 .383 1 .536 1.10 .804 20
inconst00 .100 .222 2 1.204 1 .65 1.105 .716 .707
negpt00 .013 .360 .001 1 .970 1.014 .501 2.052
Totmdrink .046 .159 4 1.082 1 .77 1.047 .767 .428
Totfdrink .091 .159 .327 1 .567 1.095 .802 1.497
Totreact ‐.252 .206 1 11.495 1 .22 .777 .519 .164
Totpersist .037 .188 .039 1 .844 1.038 .718 1.499
[agedrh=1.00] .259 .283 0 2.837 1 .36 1.295 .744 .256
[agedrh=2.00] 0b . . . . . 0 .
5+ days binge drinking
Intercept 1.283 2.682 .229 1 .632
drink96 .841 .248 11.479 1 .001 2.319 1.426 3.773
Talkdr .160 .213 .566 1 .452 1.174 .773 1.781
attach00 .103 .232 .196 1 .658 1.108 .703 1.748
Totusereas ‐.293 .242 1.472 1 .225 .746 .464 1.198
Totharshd ‐ 57 .299 .037 1 .848 .944 .526 1.695 .0
superv96 59 .3 35 .333 .432 .3 71 .9 1 1 .692 2.967
superv98 .813 .3 8 1 .013 .444 3 ‐ 28 6.12 .23 .844
parsup00 ‐.294 3.038 81 5 .169 1 .0 .74 .535 1.037
inconst00 ‐.343 32 54 0 1.241 2.0 1 .1 .71 .443 .137
negpt00 .377 54 29 8 3.386 .9 1 .3 1.45 .684 .106
Totmdrink .261 .178 2.153 1 .142 1.298 .916 1.839
totfdrink .355 .175 4.105 1 .043 1.426 1.012 2.009
Totreact ‐.228 .222 54 1.21.0 1 .305 .796 .515 30
Totpersist ‐.134 .199 1.2.448 1 .503 .875 .592 94
[agedrh=1.00] .899 .333 5 07 8 4.7.27 1 .0 2.45 1.279 726
[agedrh=2.00] 0b . . . . 0 . .
(a) The reference category is: 0 days binge drinking.
124
Smoking
Dependent variable: Daily smoker at 19‐20 years
gistic ts — age years r 2002)(a)(b)
B S.E. Wald df Sig. Exp(B)
9 Lower
95Upper
Table G.7: Lo regression resul child 19‐20 (yea
5% CI % CI
smoke96 1.384 .250 30.738 1 .000 3.989 2.446 6.505
smokeh_3 2.87 4 0 2 .000
smokeh_3(1) Missing compared to allowed
‐2.459 .653 14.197 1 .000 .085 .024 .307
smokeh_3(2) Not allowed compared to
‐1.8 .292 9.417 .0 .28
allowed
35 3 1 .000 .160 90 3
attach00 .180 .215 .699 1 .403 1.197 .785 1.824
Totusereas ‐.21 .239 80 . 1.21 .7 1 .377 .809 506 94
Totharshd ‐.063 .281 .541 1.6 .050 1 .822 .939 28
superv96 .371 .350 1.124 1 .289 1.449 .730 2.878
superv98 ‐.4 .293 .984 . 1.113 1 1 .159 .662 372 76
parsup00 .288 .166 3.029 1 .082 1.334 .964 1.846
inconst00 ‐.321 .236 1.856 1 .173 .725 .457 1.151
negpt00 1.1 .365 .840 1 6.45 9 1 .002 3.142 .537 425
totmsmoke .286 .113 6.426 1 .011 1.331 1.067 1.660
Totfsmoke ‐.16 .107 .335 . 1.04 2 1 .126 .849 687 47
Totpersist ‐.272 .187 2.099 1 .147 .762 .528 1.101
Totreact .068 .214 .100 1 .751 1.070 .704 1.627
Constant ‐2.853 2.413 1.398 1 .237 .058
(a) Base for comparison is not a daily smoker. (b) Variables highlighted in bold are significant at 0.05.
Illicit drugs
sed in the past month, child aged 23‐24 years(a).
Unstandd
Standardised B
Lo Upp
Source: AIFS analysis of ATP
Dependent variable: number of illicit drugs u
ardise B
SE T Sig. 95% CI
wer 95% CI
er
(Constant) ‐ ‐1.009 .714 ‐.012 .990 .410 1.393
init_illicit96 .06 1.184 .107 7 .728 .084 ‐.025 .394
total n of types of nt/neglecd
.01maltreatme t experience
.025 .059 7 .430 .667 ‐.090 .141
marital conflict ‐.00‐.002 .034 2 ‐.053 .958 ‐.069 .065
attachmen2000
t to paren .03ts .061 .067 8 .916 .360 ‐.070 .193
Positive Family Functioning
125
Unstandardised
SE Standardised B
T Sig. 95% CI Lower
95% CIUpper
B
parent‐teen conflict .06 12000 .154 .104 8 .478 .140 ‐.051 .359
new monitoring/scale 1996
supervis‐.00
ion ‐.004 .102 2 ‐.042 .966 ‐.205 .197
new monitoring/supervisi
8
.00on
scale 199
.002 .089 1 .027 .979 ‐.173 .178
parental supervision/monito
‐.10 ‐2ring
M & F 2000
‐.120 .048 0 .496 .013 ‐.214 ‐.026
composite mother smoking 96 & 00
.084 .037 .096 2.255 .024 .011 .158
composite father smoking 96 & 00
.044 .033 .058 1.336 .182 ‐.021 .110
composite mother drinking 96 & 00
.087 .046 .081 1.880 .061 ‐.004 .177
composite father drinking 96 & 00
.056 .047 .053 1.200 .231 ‐.036 .149
composite reactivity temperament 94, 96 & 98
‐.096 .062 ‐.072 ‐1.533 .126 ‐.218 .027
composite persistent temperament 94, 96 & 98
‐.103 .058 ‐.077 ‐1.782 .075 ‐.216 .010
composite approach temperament 94, 86 & 98
.104 .053 .078 1.962 .050 .000 .207
(a) Variables highlighted in bold are significant at 0.05.
Source: AIFS analysis of ATP
Dependent variable: number of illicit drugs used in the past month, child aged 19‐20 years(a). This equation was not used because attachment to parents has an unexpected sign.
Unstandardised B
SE Standardised B
T Sig. 95% CI Lower
95% CIUpper
(Constant) 1.246 .568 2.194 .029 .131 2.361
init_illicit96 .143 .084 .067 1.699 .090 ‐.022 .309
total n of types of maltreatment/neglect experienced 0‐18 years
.041 .048 .035 .856 .392 ‐.054 .136
marital conflict hi=hi ‐.007 .027 ‐.010 ‐.245 .806 ‐.060 .047
attachment to parents 2000
.116 .053 .091 2.182 .029 .012 .221
parent‐teen conflict 2000
.161 .083 .090 1.944 .052 ‐.002 .324
126
dardise SE Standardised B
T Sig. 95% CI Lower
9U
Unstan
d B
5% CIpper
new monitoring/supervisio
‐.102 .081 ‐.053 ‐1.258 .209 ‐.262 .057
n scale 1996 ‐ hi = hi
new monitoring/supervision scale 1998 ‐ hi = hi
‐.096 .071 ‐.058 ‐1.350 ‐ .044.177 .236
parental ‐.115 .038 supervision/monitoring M & F 2000 ‐ hi = hi
‐.122 ‐3.016 3 ‐.00 ‐.190 .040
composite mother smoking 96 & 00
.080 .030 .115 2.656 8 .00 .021 .139
composite father .022 .027 smoking 96 & 00
.037 .835 ‐ .075.404 .030
composite mother .013 .037 .016 drinking 96 & 00
.352 5 .72 ‐.059 .085
composite father .005 .038 .0drinking 96 & 00
07 .144 6 .88 ‐.069 .080
composite reactivity ‐.065 .04temperament 94, 96 & 98; hi = very reactive
9 ‐.063 ‐1.333 3 .18 ‐.162 .031
composite persistent ‐.125 .046 ‐.119 ‐temperament 94, 96 98; hi = persistent
2.701 7 ‐
&
.00 ‐.215 .034
composite approach temperament 94, 86 &
.045 .042 .043 1.072 4 ‐ 8 8
98; hi = approaching
.28 .03 .12
(a) Variables highlighted in bold are significant at 0.05.
at age 19‐20 years. rator the c
Sig. ) 9L
95%Up
Source: AIFS analysis of ATP
Antisocial behaviour
Dependent variable is antisocial behaviour Compa is that hild does not engage in antisocial behaviour (a).
B S.E. Wald df Exp(B
5% CI ower
CIper
anti96 .273 .072 14.445 1 .000 4 1.1.31 1.141 513
attach00 ‐.214 .212 1.023 1 .312 7 1.80 .533 .222
cohes00 ‐.026 .016 2.459 1 .117 5 1.97 .944 .006
totrelqual .058 .275 .044 1 .834 9 1 1.05 .617 .817
totharshd .275 .274 1.014 1 .314 7 21.31 .771 .251
superv96 .167 .317 .278 1 .598 2 21.18 .635 .201
superv98 ‐.086 .287 .089 1 .765 .918 .523 1.612
parsup00 ‐.270 .157 2.962 1 .085 .764 .561 1.038
inconst00 ‐.299 .222 1.807 1 .179 .742 .480 1.147
Positive Family Functioning
127
B S.E. Wald df Sig. Exp(B)
95% CI r
95% CIUpper Lowe
mconflic ‐.068 .123 .304 1 .581 1.1 9 .935 .735 8
intactf .062 .292 .045 1 .832 4 11.06 .601 .884
totmsmoke .212 .114 3.460 1 .063 6 11.23 .989 .546
totfsmoke ‐.005 .108 .002 1 .965 5 1 .99 .806 .230
totmdrink .061 .160 .145 1 .703 3 11.06 .777 .454
totfdrink .154 .164 .885 1 .347 6 11.16 .846 .607
totreact ‐.248 .200 1.533 1 .216 0 1.78 .527 .156
totpersist ‐.457 .180 6.433 1 .011 .633 .445 .901
Constant 1.975 2.426 .663 1 .416 6 7.20
(a) Variables highlighted in bold are significant at 0.05.
Source: AIFS analysis of ATP
128
Appendix H: Mean and standard deviation of ATP variables
vity
school Devia
N
Producti
Completed Mean Std.
tion
completed year 12 ‐ yes/no .9054 .29289 687
attachment to parents 2000 ‐ hi = hi 3.1398 .54840 687
composite relationship quality/warmth 96, 98 & 00 4.1655 .50427 687
composite harsh discipline 96, 98 & 00 2.1112 .47871 687
new monitoring/supervision scale 1996 ‐ hi = hi 4.7496 .32698 687
new monitoring/supervision scale 1998 ‐ hi = hi 4.5288 .40174 687
parental supervision/monitoring M & F 2000 ‐ hi = hi 3 .0963 .71075 687
parent‐teen conflict 2000 1 .4620 .38030 687
new inconsistent discipline scale 2000 ‐ hi = inconsistency 2.1219 .55519 687
composite across‐time mother education 96, 98 & 2000 4.2120 1.57588 687
composite across‐time father education 96, 98 & 2000 4.1218 1.70045 687
high school problems .0728 .25996 687
Academic competence teacher report 1994 54.3333 22.87801 687
Positive affect towards school 1998 2.2098 .59730 687
composite persistent temperament 94, 96 & 98; hi = persistent 3.7486 .65941 687
DeNUniversity degree Mean
Std. viation
highest level of education completed by 23‐24 years 3.1277 .94128 595
attachment to parents 2000 ‐ hi = hi 3. .51464 3231 595
composite relationship quality/warmth 96, 98 & 00 4. .41811 9797 595
composite harsh discipline 96, 98 & 00 2.0943 .47935 595
new monitoring/supervision scale 1996 ‐ hi = hi 4.7518 .32839 595
new monitoring/supervision scale 1998 ‐ hi = hi 4.5211 .41039 595
parental supervision/monitoring M & F 2000 ‐ hi = hi 3.0953 .71004 595
parent‐teen conflict 2000 1.4493 .37525 595
new inconsistent discipline scale 2000 ‐ hi = inconsistency 2.1158 .56214 595
composite across‐time mother education 96, 98 & 2000 4.1919 1.58055 595
composite across‐time father education 96, 98 & 2000 4.0849 1.73357 595
high school problems .0538 .22578 595
Academic competence teacher report 1994 5 24.5849 2.67426 595
Positive affect towards school 1998 2.1934 .57797 595
composite persistent temperament 94, 96 & 98; hi = persistent 3.8037 .62737 595
Positive Family Functioning
129
Obesity
Mean Std.
Deviation N
bmi 3 level variable at 23‐24 years 1.4211 .64507 513
parental separation/divorce/death 1. 1930 .39502 513
bmi98 2 1.2532 3.07313 513
mother encourages child to lose weight 1.0585 .23488 513
father encourages child to lose weight 1.0468 .21138 513
child overeats at meal times ‐ currently 1.0390 .19375 513
child eats large amounts between meals currently 1.1520 .35942 513
Participates in school sports 1.36 .730 513
Participates in community sports 1.09 .870 513
attachment to parents 2000 ‐ hi = hi 3.1483 .52077 513
parent‐teen conflict 2000 1.4380 .36924 513
composite use of reasoning 96, 98 & 00 4.1118 .52027 513
composite harsh discipline 96, 98 & 00 2.0943 .48829 513
new monitoring/supervision scale 1996 ‐ hi = hi 4.7405 .34842 513
new monitoring/supervision scale 1998 ‐ hi = hi 4.5312 .40604 513
parental supervision/monitoring M & F 2000 ‐ hi = hi 3.0943 .71580 513
composite across‐time mother education 96, 98 & 2000 4.1777 1.59412 513
composite across‐time father education 96, 98 & 2000 4.0058 1.76050 513
composite reactivity temperament 94, 96 & 98; hi = very reactive 2.7694 .63242 513
composite persistent temperament 94, 96 & 98; hi = persistent 9 53.837 .62523 13
composite approach temperament 94, 86 & 98; hi = approaching 3.4076 .63324 513
130
Anxiety and/or depression
N MeanStd.
Deviation
anx_dep02 .2586 .43819 642
anx_dep96 1.0280 .63240 642
alienation from parents 2000 ‐ hi = hi 2.0366 .59188 642
new relationship quality/warmth scale 00 ‐ hi = hi 4.1555 .51807 642
composite use of reasoning 96, 98 & 00 4.1046 .53143 642
totharshd 2.0945 .50073 642
enmeshment 2000: hi = hi 3.0466 .79637 642
marital conflict hi=hi 4.3032 1.06109 642
marqual 4.1509 .73759 642
totmaltr .2617 .57785 642
composite family stress 96, 98 & 2000 .6225 .64771 642
composite reactivity temperament 94, 96 & 98; hi = very reactive .62.7746 5687 642
composite persistent temperament 94, 96 & 98; hi = persistent .63.8017 4665 642
composite approach temperament 94, 86 & 98; hi = approaching 3.4044 .63991 642
Drinking
Mean St
Deviation N
d.
no/some/high binge drinking 2.0983 .75426 580
age teen was first allowed to drink at home: 0‐14 yrs (=2) vs 15+ yrs (=1)
1.1603 .36724 580
drunk 3+ alcoholic drinks in life 1996 1.45 .498 580
talk with teen about drinking 2.12 .564 580
attachment to parents 2000 ‐ hi = hi 3.1532 .54560 580
composite use of reasoning 96, 98 & 00 4.0794 .53893 580
composite harsh discipline 96, 98 & 00 2.1328 .46651 580
new monitoring/supervision scale 1996 ‐ hi = hi 4.7189 .35225 580
new monitoring/supervision scale 1998 ‐ hi = hi 4.4981 .42076 580
parental supervision/monitoring M & F 2000 ‐ hi = hi 3.0410 .73866 580
new inconsistent discipline scale 2000 ‐ hi = inconsistency 2.1578 .57251 580
parent‐teen conflict 2000 1.4745 .38534 580
composite mother drinking 96 & 00 2.8888 .70414 580
composite father drinking 96 & 00 3.2836 .71330 580
composite reactivity temperament 94, 96 & 98; hi = very reactive 2.8178 .65228 580
composite persistent temperament 94, 96 & 98; hi = persistent 3.7125 .67262 580
Positive Family Functioning
131
Smoking .
Deviation N Mean
Std
daily smokers vs rest of sample 2002, 2 = smoker, 1 =non 1.1458 .35310 830
smoked 3+ cigarettes in life 1.20 .397 830
teen allowed to smoke at home, 1 = no, 2 = yes, 3 = missing item 1.0518 .42363 830
attachment to parents 2000 ‐ hi = hi 3.1422 .54909 830
composite use of reasoning 96, 98 & 00 4.0848 .54455 830
composite harsh discipline 96, 98 & 00 2.1211 .48385 830
new monitoring/supervision scale 1996 ‐ hi = hi 4.7292 .35711 830
new monitoring/supervision scale 1998 ‐ hi = hi 4.5301 .40831 830
parental supervision/monitoring M & F 2000 ‐ hi = hi 3.0842 .71412 830
new inconsistent discipline scale 2000 ‐ hi = inconsistency 2.1298 .56146 830
parent‐teen conflict 2000 1.4692 .38367 830
composite mother smoking 96 & 00 1.6934 1.01063 830
composite father smoking 96 & 00 1.9627 1.16174 830
composite persistent temperament 94, 96 & 98; hi = persistent 3.7477 .67210 830
composite reactivity temperament 94, 96 & 98; hi = very reactive 2.8222 .66110 830
IllicitStd. tion
N
drugs
Variable MeanDevia
number of illicit drugs used in past month, 23‐24 years .3840 .86587 664
init_illicit96 .1130 .31677 664
total n of types of maltreatment/neglect experienced 0‐18 years .2726 .58599 664
marital conflict hi=hi 4.3380 1.06986 664
attachment to parents 2000 ‐ hi = hi 3.1527 .53278 664
parent‐teen conflict 2000 1. 54 .37971 664 44
new monitoring/supervision scale 1996 ‐ hi = hi 4.7343 .35209 664
new monitoring/supervision scale 1998 ‐ hi = hi 4.5241 .40790 664
parental supervision/monitoring M & F 2000 ‐ hi = hi 3.0853 .72539 664
composite mother smoking 96 & 00 1.6506 .98207 664
composite father smoking 96 & 00 1.9066 1.12507 664
composite mother drinking 96 & 00 2.7447 .81045 664
composite father drinking 96 & 00 3.1212 .81971 664
composite reactivity temperament 94, 96 & 98; hi = very reactive 2.7751 .65045 664
composite persistent temperament 94, 96 & 98; hi = persistent 3.7982 .65138 664
composite approach temperament 94, 86 & 98; hi = approaching 3.4103 .64846 664
132
Antisocial behaviour
Mean Std.
Deviation N
highly antisocial (3+ anti‐social acts) 2002, including drug use .1470 .35436 755
anti96 .8464 1.38300 755
alienation from parents 2000 ‐ hi = hi 2.0507 .60259 755
Family cohesion scale 2000 62.4993 8.25190 755
composite relationship quality/warmth 96, 98 & 00 4.1424 .50802 755
composite harsh discipline 96, 98 & 00 2.1181 .48623 755
new monitoring/supervision scale 1996 ‐ hi = hi 4.7307 .35280 755
new monitoring/supervision scale 1998 ‐ hi = hi 4.5212 .41065 755
parental supervision/monitoring M & F 2000 ‐ hi = hi 3.0849 .72262 755
new inconsistent discipline scale 2000 ‐ hi = inconsistency 2.1322 .56067 755
marital conflict hi=hi 4.3287 1.05601 755
parental separation/divorce/death 1.1735 .37894 755
composite mother smoking 96 & 00 1.6609 .98207 755
composite father smoking 96 & 00 1.9291 1.13887 755
composite mother drinking 96 & 00 2.7258 .83344 755
composite father drinking 96 & 00 3.1099 .83315 755
composite reactivity temperament 94, 96 & 98; hi = very reactive
2.8076 .65792 755
composite persistent temperament 94, 96 & 98; hi = persistent 3.7442 .68217 755
Positive Family Functioning
133
Appendix I: Detailed costing methodology and tables
Disease‐cost burden analysis (DCBA) cost categories
Health system expenditures
Financial costs to the Australian health system comprise the costs of running hospitals and
ivate), allied health services, research, and ‘other’ costs such as health administration. Australian Institute of Health and
er employment and workforce participation, including those due to
absenteeism and premature death result in reduced taxation revenue collected by the
product of the average
n revenue is considered a transfer payment, rather than an economic cost per se. However, raising additional taxation revenues imposes real efficiency costs on the
as deadweight losses (DWLs), which are described below.
This section provides further detail on Access Economics’ standard DCBA categories used in past studies, and the data sources employed to estimate different cost components.
nursing homes (buildings, care, consumables), General Practitioner (GP) and specialist services reimbursed through Medicare and private funds, the cost of prescribed and over‐the‐counter pharmaceuticals (Pharmaceutical Benefits Scheme and pr
Welfare (AIHW) data are used to estimate health expenditures relating to a condition, using a top‐down approach which aggregates the total cost of different elements.
Productivity losses
Productivity losses are costs of lost production imposed when a person with a condition is unable to work because of that condition. Productivity losses include:
■ costs of lowpremature death;
■ costs of absenteeism;
■ costs of lower productivity of a person at work (‘presenteeism’ costs); and
■ additional search and hiring costs due to premature death of a person.
Reduced earnings resulting from reduced workforce participation, lower productivity,
Government. This includes both forgone income (personal) tax, and indirect (consumption) tax, as those with lower incomes spend less on the consumption of goods and services.
Personal income tax forgone was estimated in this report as thepersonal income tax rate of 19.48% and forgone earnings. Consumption tax foregone was estimated by applying an indirect taxation rate of 11.68% to foregone earnings. These average taxation rates were derived for 2010 from the Access Economics Macroeconomic Model (AEM). Lost taxatio
Australian economy, known
Access Economics adopts a human capital approach in estimating productivity losses in developed countries. Productivity loss estimates are informed by employment participation and absenteeism data from the National Health Survey (NHS), produced by the ABS
134
DWLs from transfers and foregone taxation revenue
Peop ent, including Newstart Allowance (NSA) or the Disability Support Pension (DSP), and carers of
requir ents. These ft of sources from one econo entity to anothe and are therefor ke taxation revenue lost),
themselves econom ts but rather transfer om taxpayers to are ients.
al resource cost nsfer payme d taxation foregone the ted DWL. DWLs r costs of administering welfare s and raisin onal n revenues. The resent the l consumer ducer surp to ion to the equilibr ciety preferr l of output
te of DWL applied sfer paymen ccess Econo A studies nts of tax revenue plus 1.25 cen dollar of tax raised for Office administra based on Productivity Commission ) in turn derived om
ore (1997), i.e. 28. erall.
costs
are people who p informal care ers in need tance or su ost al carers are fami iends of the receiving c rers may t off to accompany peopl a particular h condition cal appointme stay em in hospital, o for them at . Carers m take time k to ake many unpaid the pers h a conditio do thems the e of the health condition.
al care is distingu rom services ed by peo yed in th the
recipient and is not regulated by the government. While informal care is provided free of conomic sense, as time spent caring is time that cannot be directed
to other activities such as paid work, unpaid work (such as housework or yard work) or leisure.
Economics DCBAs use three p timate costs of informal care provision:
ity cost: the
replacement valuation: the cost of buying a similar amount of services from the formal care sector; and
self‐valuation: what s themselves should be
ccess Economics D ave utilised m the ABS f Disability, and (SDAC) to estim al number hours prov people wi alth ion, employment s f carers and weekly ear regone by c
financial costs
financial costs res a healt on can inc eral costs s of home modifica If prematu h results, t an ‘additio t of
le with a health condition may require income support payments from the governm
these people could e carer‐related paym payments represent a shire mic r, e (linot ic cos a financial fr welfrecip
The re of tra nts an revenue is only associa efer to pension g addititaxatio se rep oss of and pro lus, duedistort ium (so ed) leve and prices.
The ra to tran ts in A mics DCB is 27.5 ceper dollar raised, ts per revenue AustralianTaxationLattim
tion, 75% ov
(2003 fr
Carer
Carers rovide to oth of assis pport. Minform ly or fr person are. Ca ake time
work with th
e withr care
healt home
to mediay also
nts,off wor
undert tasks that on wit n would elves inabsenc
Inform ished f provid ple emplo e health andcommunity sectors (formal care) as this care is generally provided free of charge to
charge, it is not free in an e
As such, informal care has associated costs in the use of economic resources. Past Access otential methodologies to es
■ opportun value of lost wages foregone by the carer;
■
■ carer feel they paid.
Past A CBAs h data fro Survey o AgeingCarers ate tot of care ided to th a hecondit tatus o average nings fo arers.
Other
Otheraids and
ulting from h conditi lude fun and costtions. re deat here is nal’ cos
Positive Family Functioning
135
funerals borne by family and friends of people with the condition, due to increased likelihood th. Since death a lting funera ses are eve inevitable son r without a health the true the funeral forward e likelihood of dy way in a g ar). The B Transpo oad
(2000) calcul weighted cost of a l across all and ries as an average $3,200 per 1996.
rson with a partic ndition requ s or home tions, asso s t captured in form lth sector or lity services Past Access mics have estimated co and modifications, often bas ABS SDAC
of disease (BoD
le costs of alth condition or injury. These costs of disability, loss of re difficult to measure.
esents a year of perfect health, while a DALY of 1 represents by exper alth
l DALYs lost from sum of mortality ents – Life Lost due LLs) and the Yea to
isability (YLDs).
ain monetary val this non‐ approach, ess Econo dies ed DALYs i ar figures b ng an estim lue of a S Life
SLY). This represents estimate of society places an anonymous of is financial conve nds to utili gness to p k‐based la rket Thorough expla the appr istory and logy of Bo g is
ned in the earlier study for tive family ing (Acces ics
partment of Fina Deregulati D, 2009) ha ided an esti the appears to represent a fixed est f the net VS estimate w ,000
6 which inflates to $166,604 2010 dollars.
oted that the BoD od for deter measures ty of life o eing ng from aspects o y functionin nservative a ly measures and s and excludes as f overall fam and ing not asso with outcomes.
lence profiles
This section presents prevalence profiles for all the identified outcomes in the health, productivity and social/criminality domains. These profiles assisted the estimation of numbers of people with a condition in 2010 (for health and criminality outcomes) and to develop a set of per‐person costs by age and gender for each outcome.
of dea nd resu l expen ntually for a perwith o condition,
ing any cost is iven ye
cost broughtureau of
(adjustedrt and Rfor th
Economicsterrito
ated a average funera states cost of person in
If a pe ular co ires aid modifica ciated costare no al hea disabi costs. EconoDCBAs sts of aids ed from data.
Burden )
Burden of disease refers to the qualitative and quantitative analysis of the intangibpain and suffering from a particular hewellbeing and premature death are mo
In the last decade, a non‐financial approach to valuing human life has been derived, where loss of wellbeing and premature mortality – called the ‘BoD and injury’ – are measured in Disability Adjusted Life Years (DALYs). A DALY of 0 repr
death. Other health states are attributed values between 0 and 1 as assessedts on the basis of literature and other evidence of the quality of life in relative he
states. Totathe Year(s) of
a condition are theto premature death (Y
and morbidity componr(s) of healthy life Lost due
D
To obt ues from financial past Acc mics stuhave convert nto doll y applyi ated Va tatistical Year (V an
rsion te the valuese ‘willin
onay’ or ris
yearbour malife. Th
studies.contai
nation of oach, h methodo D costin scoping on posi function s Econom
2009).
The De nce and on (DOF ve prov mate ofVSLY, which imate o LY. This as $151in 200 approximately in
It is n meth mining of quali r wellbresulti f famil g is co s it on illness injurie pects o ily happiness wellbe ciated health
Preva
136
Obesity
Table I.1: Obesity prevalence rates and estimated obese people (number) in 2010
Age group Prevalence rate (%) Number of obese people
M F M F
0‐4 0.0% 0.0% 0 0
5‐9 7.8% 54,846 005 6.2% 41,
10‐14 7.8% 56,438 ,609 6.2% 42
15‐19 7.8% 172,013 716 6.2% 45,
20‐24 11.1% 92,429 232 9.3% 73,
25‐29 19.4% 161,874 09,684 13.5% 1
30‐34 19.4% 148,512 02,624 13.5% 1
35‐39 19.9% 160,138 72,271 21.2% 1
40‐44 19.9% 154,016 65,360 21.2% 1
45‐49 23.2% 181,347 31,562 29.2% 2
50‐54 23.2% 168,478 16,549 29.2% 2
55‐59 28.5% 35.6% 186,882 238,237
60‐64 28.5% 35.6% 172,046 216,496
65‐69 22.2% 31.9% 99,989 146,567
70‐74 22.2% 31.9% 76,382 117,054
75‐79 14.2% 16.9% 36,254 49,869
80‐84 14.2% 16.9% 26,871 42,280
85‐89 14.2% 16.9% 14,340 28,662
90+ 14.2% 16.9% 5,644 15,960
Total 2,055,736 16.8% 18.5% 1,968,499
Source: Access Economics calculations using Access Economics (2008) and AE‐Dem 2010 population estimates.
d depression
I.2: Anxiety and prevale s and estim ople with a nd depression r) in 2010
group alence rate Peop ty and ion
Anxiety an
Table depression nce rate ated pe nxiety a (numbe
Age Prev (%) le with anxie depress
M F M F
0‐4 0.00% 0.00% 0 0 5‐9 0.25% 0.53% 1,733 3,494 10‐14 2.52% 3.45% 18,225 23,724 15‐19 6.72% 8.43% 148,283 62,168 20‐24 9.24% 11.99% 76,937 94,451 25‐29 9.74% 13.96% 81,303 113,401 30‐34 9.81% 15.11% 75,066 114,840 35‐39 9.66% 15.78% 77,758 128,197 40‐44 9.38% 16.40% 72,623 127,935 45‐49 8.93% 16.68% 69,810 132,310
Positive Family Functioning
137
Age group Prevalence rate (%) People with anxiety and depression
50‐54 8.22% 16.34% 59,698 121,163 55‐59 7.36% 15.16% 48,274 101,452 60‐64 6.52% 13.33% 39,354 81,039 65‐69 5.9 % 3% 11.38 26,711 52,274 70‐74 5 9. 19 3 34, 1 .55% 30% ,11 1175‐79 5.23% 7.47% 13,358 22,041 80‐84 4.89% 6.02% 9,246 15,054 85‐89 4.58% 4.85% 4,626 8,230 90+ 4.35% 3.85% 1,730 3,639 Total 6.73% 11 1 .16% 843,848 ,239,522
Source: Access Economics cal Begg et a d AE‐Dem 2 on estimat
ed to estimate the number of current daily smokers in 2010 and estimate per‐person annual costs by age and gender for the categories of productivity los
I.3: Smoking prevalence da
oup Prevalence rate Current da ers
culations using l (2007) an 010 populati es.
Smoking – prevalence profile one
These prevalence rates were us
ses, indirect costs, DWLs and carer costs.
Table rates and estimated current ily smokers in 2010
Age gr (%) ily smok
M M F F 18‐19 28.01% 89,257 029 15.94% 48,20‐24 24.37% 202,902 3,883 15.73% 1225‐29 23.92% 199,595 6,341 15.55% 1230‐34 24.18% 185,096 3,229 14.90% 1135‐39 24.36% 196,042 9,566 19.64% 1540‐44 24.62% 190,582 3,404 19.67% 1545‐49 23.17% 181,083 7,283 14.79% 1150‐54 22.87% 166,068 5,604 15.59% 1155‐59 13.48% 88,405 1,459 12.17% 860‐64 16.29% 12.37% 98,316 75,247 65‐69 9.57% 7.53% 43,106 34,596 70‐74 9.40% 32,349 580 7.52% 27,75‐79 3.67% 9,381 607 3.59% 10,80‐84 2.90% 5,487 9,046 3.62% 85‐89 3.64% 3,677 6,133 3.62% 90+ 3.64% 1,447 3,375 3.57% Total 19.97% 1,692,793 205,383 13.85% 1,
Source: Access Economics calculations using Access E and AE‐Dem 2010 popu timates. conomics (2007) lation es
138
Smoking – prevalence profile two
These disease in 2010 and estimate per‐person annual costs by age and gender for the categories of
m costs and BoD cos
Table I.4: Prevalence tes for to used diseas and conditions(a)
group Females
prevalence rates were used to estimate the number of cases of tobacco‐attributable
health syste ts.
ra bacco‐ca es
Age Males
15‐24 0.06% 0.08%
25‐34 0.04% 0.14%
35‐44 1.20% 0.73%
45‐54 7.42% 2.76%
55‐64 11.81% 4.58%
65‐74 11.92% 5 .01%
75+ 16.30% 7
2
.97%
Total 4.61% .86%
(a) Included diseases and conditions: asthma, bladder ronic obstructive pulmonary d e injuries, flammatory bowel disease, kidney cancer, larynx cancer, low birth‐weight, lower respiratory infections, lung
and orapharynx cancer, oesophagus cancer, otitis media, pancreatic cancer, Parkinson’s disease, fant death syndrome, stomach uterus cancer, age‐related vision disorders, cervical cancer,
mic heart disease, peripheral arterial disease, stce: Access Economics calculations using AIHW Bo 04 special request) for Access Economics (2007), AE‐Dem 2010 population estimates.
l abuse
: Prevalence rates ‐ drinking at ris a) levels of long term h harm and estimated risky‐h drinkers in 2010
oup Prevalence ratePersons drinking a y/high risk
levels of long‐ harm
cancer, ch isease, firincancer, mouthsudden in cancer,ischae roke. Sour D data (20and
Alcoho
Table I.5 ky‐high risk( healtigh risk
Age gr (%) t riskterm
M M F F 14–19 7.70% 71,312 7,863 12.30% 1020–29 14.40% 15.10% 240,062 241,586 30–39 10.30% 9.80% 161,735 154,132 40–49 9.30% 10.30% 144,672 162,021 50–59 10.70% 7.40% 147,866 104,400 60+ 8.00% 5.20% 158,672 116,679 14+ 10.10% 9.60% 917,526 890,619
(a) ‘Risky’ drinking defined as 29 to 42 drinks per week for males, and 15 to 28 drinks per week for females. ‘High defined as 43+ drinks per week for males and 29+ drinks per week for females. ess Economics calculations using AIHW’s ‘2004 National Drug Strategy Household Survey’ (2005) and AE‐
Dem population estimates (2010).
risk’ drinkingSource: Acc
Positive Family Functioning
139
Drug abuse
le I.6: Prevalence for recen a) of illicit ugs and estima d recent use 2010
oup Prevalenc e (%) Recen of illicit
Tab rates t use( dr te rs in
Age gr e rat t users drugs
M F M F 14–19 20.90% 21.80% 193,5 1962 1,172 20–29 37.50% 25.60% 625,1 4061 9,576 30–39 25.50% 15.10% 400,4 2311 7,489 40–49 15% 9.50% 233,34 142 9,437 50–59 0% 4.80% 105,0 67.6 26 7,719 60+ 4.10% 4% 81,32 80 9,753 14+ 18.20% 12.50% 1,653, 1,1363 59,660
(a) ‘Recent use’ is defined within the l onths. Access Economics ations using NDSHS (2005) and AE‐Dem estimates.
der prevalenc ofile
ble I.7: Offend e‐gender p ence profil estimated ders in 2
group preval ted offe
as use ast 12 mSource: calcul AIHW 2004 2010 population
Offen e pr
Ta er ag reval e and offen 008‐09
Age Offender ence Estima nders
Male 10‐14 2.286% 16,474 15‐19 8.821% 67,695 20‐24 25‐29 4.452% 35,764
34 00% 27,655 07 24,099
2.286% 17,361 9 1.539% 11,975 4 0.955% 6,804
0.644% 4,167 0.494% 2,889 0.136% 1,815 2.838% 268,525
1.096% 7,497 2.950% 21,427 1.471% 11,351 1.104% 8,626 0.984% 7,322 0.856% 6,932 0.666% 5,110 0.449% 3,556 0.257% 1,866 0.155% 1,023 0.102% 599 0.028% 440 0.786% 75,749
6.398% 51,828
30‐35‐39
3.73.0 %
40‐4445‐450‐555‐59 60‐64 65+ Total
Female10‐14 15‐19 20‐24 25‐29 30‐34 35‐39 40‐44 45‐49 50‐54 55‐59 60‐64 65+ Total
Source: Access Economics ations using AB (2009c; 2010b) and AE‐Dem estimates. calcul S 4519.0 2009 population
140
Prisoner prevalence profile
Table I.8: Prison age‐gender valence rates d estimate ers in 2009
prisoners
er pre an d prison
Age group Prisoner prevalence rate (%) Estimated
Male <18 0.001% 37 18 0.175% 273 1920–24 0.545% 4,418 25–29 0.633% 5,088
34 16 4,602 39 0.526% 4,214
0.390% 2,963 0.255% 1,987
0.181% 1,290 0.112% 724
0.084% 492 0.037% 492 0.250% 27,192
0.000% 3 0.009% 14 0.025% 38 0.034% 266 0.053% 416 0.052% 390 0.045% 363
0.033% 256 0.024% 186 0.014% 102 0.007% 49 0.005% 30 0.001% 14
0.019% 2,127
0.382% 612
30– 0.6 % 35–
40–4445–4950–54 55–59 60–6465+ Total
Female<18 18 19 20–24 25–29 30–34 35–39 40–4445–49 50–54 55–59 60–64 65+ Total
Source: Access Economics calculations using ABS 4517.0 (2009) and AE‐Dem 2009 population estimates.
H
The sections below present the sets of calculated per costs for each health outcome, nd gender. osts w ing costs
sity
Table I.9: nual per‐pe costs of obesity ‐ males (in dollars)
H Pro ity Other
financi l(a)
ealth outcomes – per person annual costs
‐person to the modellby age a These c ere used as inputs of lifetime .
Obe
An rson 2010
ealth ductiva
BoD Total
0‐4 ‐ ‐ ‐ ‐ ‐ 5‐9 225 415 308 5,701 6,649
Positive Family Functioning
141
Health Productivity Other
financial(a) BoD Total
10‐14 226 415 309 5,712 6,661 15‐19 256 472 350 6,484 7,562 20‐24 324 596 443 8,195 9,557 25‐29 534 981 729 13,492 15,737 30‐34 530 975 724 13,403 15,633 35‐39 544 999 742 13,735 16,020 40‐44 542 996 740 13,694 15,972 45‐49 612 1,124 835 15,450 18,020 50‐54 608 1,117 830 15,364 17,920 55‐59 698 1,282 953 17,632 20,566 60‐64
16,853
1,039 772 14,291 16,669
386 710 527 9,760 11,383
384 705 524 9,697 11,310 85‐
90+ 378 695 516 9,555 11,144
694 1,275 947 17,533 20,450 65‐69 572 1,051 781 14,449 70‐74 566 75‐79
80‐84
89 380 699 519 9,613 11,212
(a) ’Other finaSource: Access
ncial’ cate des DW , carer other indir Econom ions.
Table I.10: ual per‐pe osts of obe females ( dollars)
Heal Pro ty Other
fina
gory incluics calculat
L from transfers costs and ect costs.
Ann rson c sity ‐ in 2010
th ductivincial(a)
BoD Total
0‐4 0 0 0 0 0 5‐9 146 269 200 3,704 4,320 10‐14 146 270 201 3,715 4,332 15‐19 147 272 202 3,734 4,355 20‐24 228 420 312 5,772 6,732 25‐29 329 604 449 8,310 9,692 30‐34 327 601 447 8,265 9,640 35‐39 486 893 664 12,285 14,328 40‐44 484 890 661 12,241 14,277 45‐49 613 1
1 1
19,816
621 1,141 848 15,687 18,297 70
75‐79 380 699 519 9,610 11,208
85‐89 375 689 9,474 11,050
,126 837 15,485 18,060 50‐54 609 ,119 831 15,389 17,948 55‐59 678 ,246 925 17,129 19,978 60‐64 1,236 918 16,990 673 65‐69
‐74 614 1,127 837 15,499 18,077
80‐84 378 695 517
512
9,561 11,151
142
Health Productivity Other
financial(a) BoD Total
90+ 371 683 507 9,393 10,955
(a) ’Other financial’ catego cludes DWL fr sfers, carer c nd other indi s. Access Economics cal ulations.
and depression
le I.11: Annu person co anxiety an pression ‐ n 2010
H Pro ity Other
fina
ry in om tran osts a rect costSource: c
Anxiety
Tab al per‐ sts of d de males (i dollars)
ealth ductivncial(a)
BoD Total
0‐4 ‐ ‐ ‐ ‐ ‐ 5‐9 71 333 65 763 1,231 10‐14 401 1,787 359 4,532 7,080 15‐19 1,723 8,016 1
1 2
39,517
10,447 2,040 24,346 39,072
2,166 10,105 1,973 23,562 37,806
2,059 9,601 1,876 22,411 35,947 50‐54 75 55‐59 1,655 7,696 1,506 18,050 28,907
1
1,270 5,882 13,901 22,207
,568 18,783 30,089 20‐24 2,144 9,998 ,953 23,319 37,414 25‐29 2,264 10,568 ,063 24,621 39,516 30‐34 2,265 10,568 2,063 24,621 35‐39 2,239 40‐44
45‐49
1,877 8,743 1,709 20,446 32,7
60‐64
651,438 6,673 1,307
1,154
5,710 25,128 ‐69
70‐74 1,163 5,378 1,056 12,748 20,345 75‐79 1,072 4,949 973 11,767 18, 76180‐84 979 4,508 887 10,757 17,131 85‐89 893 4,106 809 9,838 15,646 90+ 830 3,809 752 9,158 14,549
(a) ’Other financial’ category includes DWL from transfers, carer costs and other indirect costs. Source: Access Economics calculations.
2: Annual per‐person costs of anxiety and depression ‐ females (in 2010 dollars)
Health Productivity Other
fin ) BoD Total
Table I.1
ancial(a
0‐4 ‐ ‐ ‐ ‐ ‐ 5‐9 ‐ ‐ ‐ ‐ ‐ 10‐14 91 431 84 986 1,592 15‐19 276 1,194 244 3,176 4,889 20‐24 1,053 4,857 955 11, 18, 25‐29 1,566 7,277 1,425 17,093 27,361 30‐34 1,833 8,534 1,669 19,968 32,004 35‐39 1,969 9,175 1,793 21,435 34,372
557 423
Positive Family Functioning
143
Health Productivity Other
financial(a) BoD Total
40‐44 2,065 9,626 1,880 22,467 36,038 45‐49
1,955 9,110 1,780 21,287 34,133
1,710 7,953 1,556 18,639 29,858
1,426 6,617 1,297 15,583 24,923 75‐79 5 80‐84 861 3,952 779 9,486 15,078
464 2,080 5,203 8,163
2,134 9,953 1,944 23,214 37,244 50‐54 2,172 10,129 1,978 23,618 37,897 55‐59 2,117 9,872 1,928 23,030 36,947 60‐64
65‐69
70‐74
1,128 5,213 1,024 12,370 19,73
85‐89
90644 2,931 581
416
7,150 11,306 +
(a) ’Other financial’ catego cludes DWL fro nsfers, carer c nd other indir Access Economics lations.
ng
I.13: Annua er‐person co current da oking ‐ ma (in 2010 doll )
financial(a)
ry in m tra osts a ect costs.Source: calcu
Smoki
Table l p sts of ily sm les ars
Age group Health Productivity Other
BoD Total
18‐19 48 4,473 815 4,197 9,533 20‐24
25‐29 83 4,240 773 7,260 12,356 30‐34 7 12,
37, 42,
4 3
1 1
1 4 1 1
2 2 2 23 2 3 23 0 23
4,623 774 141 404,218 409,756 0‐84 4,623 613 112 404,218 409,565
404,218 409,736
404,218 409,732
48 4,295 783 4,197 9,323
83
424
4,244
4,283
774
781
,260
047
360
53435‐39
40‐44 424 ,302 784 7,047 42,557 45‐49 1,598 4,123 752 39,737 46,20950‐54 ,598 ,063 741 39,737 46,13855‐59 ,653 ,650 483 32,030 7,81760‐64 ,653 ,089 563 2,03 8,33665‐69 2,907 1,928 351 254,182 259,368 70‐74 2,907 1,880 343 254,182 259,312 75‐79
8
85‐89 4,623 758 138 90+ 4,623 754 137
(a) ’Other financial’ category includes DWL from transfers, carer costs and other indirect costs. Source: Access Economics calculations.
Table I.14: Annual per‐person costs of current daily smoking ‐ females (in 2010 dollars)
Age group Health Productivity Other
financial* BoD Total
18‐19 46 4,271 779 3,987 9,082
144
Age group Health Productivity Other
BoD financial*
Total
20‐24 9,281 46 4,439 809 3,987 25‐29 79 804 6,897 12,186
79 ,89735‐39 402 96 35,194 41,884
40 5,306 967 35,1 41,871
1,518 ,218 769 132,750 255
1,518 ,386 800 132,750 453
2,521 ,529 643 220,429 121
2,521 ,558 649 220,429 156
2,761 ,247 410 241,473 891
2,761 ,224 405 241,473 863
4,391 ,100 201 384,007 699
4,391 ,102 201 384,007 701
4,391 ,094 199 384,007 691
4,391 196 384,007 668
4,407
4,230
5,318
30‐34 771 6
9
11,977
40‐44 2 9445‐49 4 139,50‐54 4 139,55‐59 3 227,60‐64 3 227,65‐69 2 246,70‐74 2 246,75‐79 1 389,80‐84 1 389,85‐89 1 389,90+ 1,074 389,
(a) ’Other financial’ category DWL from transfers, carer costs and other indirect sts. cess Economics cal ations.
l abuse
Table I.15: Annual per‐p costs of alcohol ab males (in 2010 d
up Health uctivity Othe
financiaBoD al
includes coSource: Ac cul
Alcoho
erson use ‐ ollars)
Age gro Prodr l(a)
Tot
14–19 837 ,481 1,629 1,879 27 1 5,820–29
1,680 ,953 3,248 3,747 28 1,204 ,121 2,33 2,691
1,083 2,10 2,423 17
6,666
2 11,630–39 2 2 8,34840–49 1,910 1 7,5
,52950–59 1,230 2,167 2,383 2,749 860+ 959 1,694 1,863 2,149
(a) ‘Ot ve consuSource: Access Economics calculations using Collins and Lapsley (2008) – costs adapted to Access Economics DCBA
Table I.16: Annual per‐person costs o hol abuse ‐ females (in 201 llars)
up Health ProductivitOther
nancial(a) BoD Total
her financial’ category includes accidents not elsewhere included, fires not elsewhere included and abusimption costs.
categories.
f alco 0 do
Age gro y fi
14–19 1,440 2,534 2,787 3,215 9,975 20–29 1,877 3,298 3,626 4,183 12,984
1,233 2,173 2,389 2,757 8,552 1,297 2,284 2,511 2,897 8,989
30–39 40–49
Positive Family Functioning
145
Age group Health Productivity Other
financial(a) BoD Total
50–59 6,288 905 1,598 1,758 2,028 60+ 660 1,171 1,288 1,485 4,603
(a) ‘Other financiaconsumption costs
l’ category i cidents not el fi include .
Access Economics calculations using Collins and Lapsley (2008) – costs adapted to Access Economics DCBA es
rug abuse
I.17: Annua erson costs o drug abuse ‐ s (in 2010 do
up Healt ProductivitOther
nancial(a) BoD
ncludes ac sewhere included, res not elsewhere d and abusive
Source:categori
Illicit d
Table l per‐p f illicit male llars)
Age gro h y fi
Total
14–19 65 528 455 408 1,45720–29 114 919 791 710
84 684 589 528 0–49 48 398 343 307 1
16 143 123 111 93 1 19 17 15
2,53430–39 1,8854 ,09650–59 360+ 52
(a) ‘Other financial’ category in not els included, fires no where included a ive tion costs.
ss Economics calc using Collins an y (2008) – costs adapted to Access Econ CBA s .
ble I.18: Annual rson costs of drug abuse ‐ females (in 2010 do
up Healt ProductivitOther
al(a) BoD l
cludes accidents ewhere t else nd abusconsumpSource: Acce ulations d Lapsle omics Dcategorie
Ta per‐pe illicit llars)
Age gro h y financi
Tota
14–19 109 877 756 678 2,420 20–29 136 1,095 943 847 3,021
668 576 516 1,842 40–49 48 393 338 304 1,082
131 113 101 360 60+ 11 102 88 79 280
30–39 82
50–59 15
(a) ‘Other usive consumptionSource: Access Economics calc using Collins and (2008) – cos Access Economics DCBA
ctivity outcom per perso ual costs
tions below pre e sets of calculated per‐perso s for each vity e, by age and ge s well as th urces used rive these. ed as inputs to th elling of lifet ts.
financial’ category includes accidents not elsewhere included, fires not elsewhere included and ab costs.
ulations Lapsley ts adapted to categories.
Produ es – n ann
The sec sent th n cost productioutcom nder a e data so to de These costswere us e mod ime cos
146
Data sources: age‐gender employment rates and average weekly earnings
Table I.19: Age‐gender employment in the general population
up people
yed in 2008(‘000)
opulation in 2(‘000)
Employ te Age groTotal
emplo P 008
ment ra
Males 15 ‐ 19 361 757 47.
592 783 75.652 766 85.637 736 86.678 794 85.
4 632 754 83.7768 84.45%
569 699 81.45% 456 639 71.46%
Females 15 ‐ 19 0% 20 ‐ 24 542 748 72.56%
516 4 499 737 67.70%
39 540 804 67.18% 44 552 762 72.47% 49 593 782 75.82% 54 500 711 70.39% 59 384 646 59.40% 64 204 563 36.30% 78 1,546 5.05% l 4,767 8,762 54.41%
77% 20 ‐ 24 64% 25 ‐ 29 11% 30 ‐ 34 57% 35 ‐ 39 42% 40 ‐ 4 9% 45 ‐ 49 648 50 ‐ 54 55 ‐ 59 60 ‐ 64 311 564 55.18% 65 + 168 1,286 13.03% Total 5,705 8,544 66.77%
357 715 50.0
25 ‐ 2930 ‐ 3
747 69.04%
35 ‐40 ‐45 ‐50 ‐55 ‐60 ‐65 +Tota
Source: Access Economics calculations using ABS 6105.0 (2009) and AE‐Dem 2008 population estimates.
Table I.20: Age‐gender average weekly earnings(a) for the ge opulation ($)
oup Males Females
neral p
Age gr
15 ‐ 19 336 236 20 ‐ 24 750 598
1,038 849 1,264 905 1,406 865
823 45 ‐ 49 1,380 861
848 55 ‐ 59 1,239 807
25 ‐ 2930 ‐ 3435 ‐ 3940 ‐ 44 1,452
50 ‐ 54 1,345
60 ‐ 64 1,251 749 65 + 336 632
(a) 2008 figures for full‐time and part‐time workers were inflated to December 2009. Source: ABS 6310.0 (2009b) and ABS 6345.0 (2010a).
Positive Family Functioning
147
Year 12 non‐completion
Table 010)
p Lower
employment(a) prod y(b) Deadweight
losses l cost
I.21: Annual costs of year 12 non‐completion ($ 2
Age grouLower uctivit
Tota
Males 15 ‐ 19 475 133 ,614
1,683 470 ,715 2,619 731 8,895 3,242 906 11,013 3,560 994 12,092 3,606 1,007 12,249 3,454 965 11,733 3,248 907 11,033 2,624 733 8,912 2,046 4 572 6,951
789 104 1,266
15 ‐ 19 1,138 20 ‐ 24 4,182
2,348 465 ,655 2,452 486 906
2,326 2 461 5,602 2,387 473 5,750 2,615 518 6,298 2,389 473 5,755 1,918 2 380 4,621 1,089 1 216 2,622
128 25 308
1,006 120 ‐ 24 3,563 525 ‐ 29 5,545 30 ‐ 34 6,866 35 ‐ 39 7,538 40 ‐ 44 7,636 45 ‐ 49 7,314 50 ‐ 54 6,878 55 ‐ 59 5,556 60 ‐ 64 ,334 65 + 373
Females 472 572 94 1,736 2,102 344
25 ‐ 29 30 ‐ 34
2,842 2,969
55,
35 ‐ 39 ,816 40 ‐ 44 2,890 45 ‐ 49 3,166 50 ‐ 54 2,893 55 ‐ 59 ,323 60 ‐ 64 ,318 65 + 155
(a) Proxied by reduced probability of workforce participaied by reduced AWE. Access Economics calculations.
ergraduate non‐completion
Table I.22: Annual costs of undergraduate degree non‐completion ($ 2010)
Age group Lower Lower Deadweight
Total cost
tion. (b) ProxSource:
Und
employment(a) productivity(b) losses
Males 20 ‐ 24 2,568 1,157 ,074
3,997 1 1,801 21,904 34 4,949 2,230 120 39 5,433 2,448 777
5,504 2,480 163 5,272 2,376 8,892 4,958 2,234 7,169 4,005 1,804 946 3,123 1,407 118 569 256 ,117
10,349 1425 ‐ 29 6,10730 ‐ 19,942 27,35 ‐ 21,895 29,40 ‐ 44 22,179 30,45 ‐ 49 21,245 250 ‐ 54 19,978 255 ‐ 59 16,137 21,60 ‐ 64 12,587 17,65 + 2,292 3
148
Age group Lower
employment(a) Lower
prod (b) Deadweight
losses Total cost
uctivity
Females 951 11,566
9,354 1,286 15,640 5,223 9,770 1,343 16,336 4,953 9,267 1,274 15,494
40 ‐ 44 15,904 45 ‐ 49 17,420 50 ‐ 54 5,089 9,521 1,309 15,918 55 ‐ 59 4,086 12,
2,319 6 765 + 272 70 85
20 ‐ 24 3,698 25 ‐ 29 5,000
6,918
30 ‐ 34 35 ‐ 39
5,084 9,512 1,308 5,569 10,419 1,432
7,644 4,338 509
1,05159
781 ,253 1
60 ‐ 64
(a) Proxied by reduce bility of workforce participied by reduce Access Econ lculation
graduate n pletio were derived to as applica under e mpletion the A ort who ned TE compl r 12). d present le I.2
Table : Age‐sp ergr non‐completion rat 007
% who t comp dergrastudi
d proba ation. (b) Prox d AWE.Source: omics ca s.
Under on‐com n rates sist the tion of graduatnon‐co costs to TP coh obtai Rs (i.e. eted yea Deriverates are ed in Tab 3.
I.23 ecific und aduate es in 2
Age did no lete un duate
es
20 72.6% 21 58.1%
53.3% 23 24 25 68.4% 26 72.
75.28 76.
77.79.79.78.78.77.77.377.877.8
22 56.3% 64.0%
3% 3% 5%
27
29 3% 30‐34 1% 35‐39 1% 40‐44 1% 45‐49 1% 50‐54 3% 55‐59 % 60‐64 % 65+ %
Source: Access Econo culations a DEEWR uest from
inality outcomes – p rson ual cos
lated per‐person costs in terms of policing, prison and societal costs, by age and gender. These costs were used
as inputs to the modelling of lifetime costs.
mics cal using data req 2009.
Crim er pe ann ts
The sections below present the sets of calcusystem costs, court system costs
Positive Family Functioning
149
Policing costs
Table I.24: Annual policing cost per offender ($)
Age group Males Females
10‐14 6,438 10,234 15‐19 24,848 27,554
18,023 13,739 25‐29 12,540 10,316 20‐24
30‐34 10,423 9,187 35‐39 8,471 7,993 40‐44 6,439 6,225 45‐49 4,335 4,196 50‐54 2,689 2,402 55‐59 1,814 1,452 60‐64 1,393 956 65+ 384 259
Source: Access Economics calculations.
Court sys
Table I.25: Annual court system (
Males Fem
tem costs
cost per offender $)
Age group ales
10‐14 589 1,020 15‐19 20‐24
2,275 2,7451,650 1,3
1,0954 915 775 79589 620
45‐49 7 41850‐54 6 2355‐59 6 14
127 9535 26
69
25‐29 1,148 28 30‐34 35‐39 6 40‐44
3924
9
16 5 60‐64 65+
Source: Access Economics calculations.
Prison system costs
Table I.26: An co r prisoner ($)
Males Femal
nual prison system st pe
Age group es
<18 253 262 18 31,155 20,41
964 54,3,037 74,2
112,682 114,109,548 112,93,558 96,51
71,899 50,615
6 19 67,20–24 97
07 37
25–29 718 30–34 840 35–39 0 40–44 69,412 45–49 45,434
150
Age group Males Females
50–54 32,206 30,269 55–59 19,910 60–64 14,982
16,037 11,036
65+ 6,580 1,899
Source: Access Economics calculations.
Societal costs
Table I.27: Annual per‐person societal costs of crime for males ($)
Age group Medical output cost(a)
damage/ cost(b)
societal Lost Intangible
Property Other
Total
loss cost
10‐14 1,029 4,416 4,514 12,783 9,501 32,243 15‐19 3,972 17,043 17,421 49,334 36,666 124,436 20‐24 2,881 12,362 12,636 35,783 26,595 90,257
24,898 18,504 62,800 30‐34 1,666 7,149 7,308 20,694 15,380 52,196 35‐39 42,422 40‐44 4,416 4,515 12,784 9,501 32,246
693 2,973 8,607 10 430 1,845 5,340 68
1,244 3,602 2,67 9,086 955 2,765 2,05 6,975 264 269 763 567 1,924
25‐29 2,005 8,601 8,792
1,354 5,810 5,939 16,819 12,500 1,029
45‐49 50
3,039 1,886
6,397 21,73,968 13,4‐54
55‐59 290 1,272 7 60‐64 223 976 5 65+ 61
(a) ‘Intangible’ costs are those due(b) Those c
to pain, suffering a L (Rollings, 2008). osts non‐separable into above categories.
ual per‐person societal costs of crime for females ($)
Medical Lost
output Intangible cost(a)
Property damage/
loss
Other cost(b)
Total societal cost
nd lost Qo
Source: Access Economics calculations.
Table I.28: Ann
Age group
10‐14 7,021 20,323 15,10 51,261 1,636 7,177 4 15‐19 4,405 20‐24 2,196 25‐29
18,902 19,322 54,717 40,667 138,014 9,425 27,282 20,2 68,814
1,649 7,077 20,485 15,22 51,669 6,302 6, 18,244 13,559 46,017
35‐39 1, 5,483 15,872 11,7 40,035 40‐44 4,270 12,361 9,18 31,178 45‐49 6 2,879 8,333 6,19 21,019 50‐54 38 1,647 4,769 3,544 12,029 55‐59 2 996 2,883 2,14 7,271
656 671 1,899 1,411 4,790 41 177 514 382 1,296
9,634 7,234
77 5
30‐34 1,469 442278 5,605 96 995 4,365 7 71 2,943 3 4 32
1,684 1,018
3
60‐64 153 65+ 181
(a) ‘Intangible’ costs are those due to pain, suffering a L (Rollings, 2008). ove categories. s.
nd lost Qo(b) Those costs non‐separable into abSource: Access Economics calculation
Positive Family Functioning
151
Crime probabilities
detail on the derivation of crime probabilities. Crime rtain which crime c s (i.e. policing, court, would be crime type. Soc ts were assumed to ap all crimes,
Probability of crime being reported
Probabilities of a crime being reported to police were derived from the Australian Institute of
s’ fear of reprisal. The inverse of the relevant multiplier was taken as a proxy for the probability of the crime being reported to p tched and adapted as best as possible to the ABS crime categories presented in section 5.3.5. The final set of crime categories, multipliers and attached probab sented in Table I.29.
Table I.29: Crime under‐reporting multip nd derived probabilities
ory lier of
rep
The sections below providewere derived to asce
probabilitiesprison) ost type
incurred, dependent on ietal cos ply to regardless of the crime being reported.
Criminology report (Rollings 2008). Rollings (2008) presented a set of multipliers for each crime type, which were applied to crime frequencies in her study, to account for crimes which were not reported to police due to non‐detection, being ‘victimless’ or victim
olice. The crime categories in Rollings (2008) were ma
ilities are pre
liers a
Crime categ MultipProbability crimebeing orted
Homicide and related 100%offences 1.0
Acts intended to cause injury* 5.2 19%
Sexual assault and related offences 5.3 19%
eople* 5.2 19%
Abduction/harassment/other offences against 5.2
‐ against commercial 1.2 83%
Unlawful e
Theft and related offences
‐ o
‐ from vehic 2.8
‐ shop the 100
‐ other the 2.7
4.0
Illicit drug offences*** ‐ ‐
Prohibited/regulated weapons and explosives offences***
‐ ‐
Property damage and environmental pollution** 4.3 23%
Public order offences** 4.3 23%
Offences against justice** 4.3 23%
Miscellaneous offences*** ‐ ‐
Dangerous or negligent acts endangering p
the person* 19%
Robbery, extortion and related offences
‐ against individual 7.2 14%
ntry with intent (ie: burglary) 3.4 29%
f vehicles 1 100%
les 36%
ft 1%
ft 37%
Fraud, deception and related offences 25%
* These crimes were all assumed to have the same multiplier – ‘physical assault’. ** These crimes were all assumed to have the same multiplier – ‘criminal damage’.
152
*** No relevant multipliers given for these crime categories in Rollings (2008). Source: Access Economics calculations using Rollings (2008) and crime categories from ABS 4519.0 (2010b).
118BProbability of court action on a reported crime
Probabilities of court action for a reported crime were derived from 2008‐09 data on police proceedings from the ABS publication, ‘Recorded Crime – Offenders, 2008‐09’ (ABS 2010b).
Some limitations are noted, which were due to indivisibilities in the available ABS data:
■ It was assumed both commercial and individual robberies had the same court action probability.
■ It was assumed that all theft and related offences had the same court action probability.
Since robbery and theft types can differ in their seriousness and thus probability of court action, assuming the same probabilities may not be the ideal approach, but is the best approach warranted by the available data.
The final set of probabilities is presented in XTable I.30 X.
Table I.30: Probabilities of court action on reported crimes
Crime category Court action Non‐court action
Homicide and related offences 99.19% 0.81%
Acts intended to cause injury 94.09% 5.91%
Sexual assault and related offences 92.63% 7.37%
Dangerous or negligent acts endangering people 86.18% 13.82%
Abduction/harassment/other offences against the person 92.30% 7.70%
Robbery, extortion and related offences*
‐ against individual 96.49% 3.51%
‐ against commercial 96.49% 3.51%
Unlawful entry with intent (ie: burglary) 84.31% 15.69%
Theft and related offences**
‐ of vehicles 58.26% 41.74%
‐ from vehicles 58.26% 41.74%
‐ shop theft 58.26% 41.74%
‐ other theft 58.26% 41.74%
Fraud, deception and related offences 92.57% 7.43%
Illicit drug offences 57.33% 42.67%
Prohibited/regulated weapons and explosives offences 90.18% 9.82%
Positive Family Functioning
153
Crime category Court action Non‐court action
Property damage and environmental pollution** 71.86% 28.14%
Public order offences 58.71% 41.29%
Offences against justice 81.77% 18.23%
Miscellaneous offences 20.67% 79.33%
* Same court‐action probability assumed for both types of robbery – individual and commercial. ** Same court‐action probability assumed for all types of theft. Source: Access Economics calculations using ABS 4519.0 (2010b).
119BProbability of ‘guilty’ verdict in a court finalisation
Probabilities of a guilty verdict in court finalisations were derived from 2008‐09 data on criminal court finalisations from the ABS publication, ‘Criminal Courts, Australia, 2008‐09’ (ABS 2010c). The final set of probabilities by court level is presented in XTable I.31 X.
Table I.31: Court finalisation outcome probabilities
Court level Guilty Acquitted Transferred to other court
Withdrawn Other
Higher courts 6.64% 78.61% 0.81% 13.64% 0.30%
Magistrate 3.96% 86.86% 2.07% 7.03% 0.08%
Children’s 3.88% 77.15% 3.47% 10.27% 5.23%
All courts 4.02% 86.07% 2.12% 7.39% 0.40%
Source: Access Economics calculations using ABS 4513.0 (2010c).
120BProbability of a custodial sentence
Probabilities of a custodial sentence being given in ‘guilty verdict’ court finalisations were derived from 2008‐09 data on criminal court finalisations from the ABS publication, ‘Criminal Courts, Australia, 2008‐09’ (ABS 2010c). The final set of probabilities by court level is presented in XTable I.32 X.
Table I.32: Custodial sentence probabilities in guilty verdict court cases
Court level Custodial sentence Non‐custodial sentence
Higher courts 84.57% 15.43% Magistrate 8.63% 91.25% Children’s 9.36% 90.14% All courts 10.39% 89.48%
Source: Access Economics calculations using ABS 4513.0 (2010c).
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