FAMILY HEALTH AND WEALTH STUDY · FAMILY HEALTH AND WEALTH STUDY INSIGHTS ON WEALTH MEASUREMENT AND...
Transcript of FAMILY HEALTH AND WEALTH STUDY · FAMILY HEALTH AND WEALTH STUDY INSIGHTS ON WEALTH MEASUREMENT AND...
February 20, 2013
FAMILY HEALTH AND WEALTH STUDY
INSIGHTS ON WEALTH MEASUREMENTAND CHANGE
To assess the effect of childbearing patterns on family health and wealth outcomesNumber and timing of births
Role of contraception
Family wealth and health outcomes
Household income, employment
Child schooling, nutrition
Maternal health
To assess using a longitudinal design
STUDY AIMS
Addis Ababa UniversityAssefa SemeMeselech Roro
Assiut UniversityOmaima El GibalyGhada Al-Attar
Kwame Nkrumah University of Science and Technology
Easmon OtupiriDenis Yar
Makerere UniversityFred MakumbiVivian Zalwango
Obafemi Awolowo UniversityPeter OgunjuyigbeAbimbola Phillips
University of IbadanMichael OkunlolaImran Morhason-BelloNathanael Afolabi
University of MalawiFrank TauloEddie MalungaWanangwa Chimwaza
FHWS SITE LEADS/DATA COORDINATORS
Andreea CreangaAlain KoffiFunmi OlaOlorunNadia Diamond SmithQingfeng LiAdel TakruriLinnea ZimmermanTimothee FruhaufAnd the rest of the
FHWS team
Saifuddin AhmedMichelle HindinStan BeckerDavid Bishai Julia DriessenWilliam Pan
FHWS ACKNOWLEDGEMENTS (US)
Three rounds of observation
Probability sample of families in peri-urban areaWife of childbearing age (15-49 years)
Husband of childbearing age (20-54 years)
GPS mapping of area (waypoints, households)
Data collection began by Ghana site January 2010Round 2 approximately 2 years later
STUDY DESIGN
Household roster on occupants and their characteristics, GPS Focal woman questionnaire Background characteristics Childbearing history, fertility preferences and contraceptive calendar Child schooling (5 to 24 years) and health history (births in <5 years) Marital relationship quality, decision-making autonomy Self-reported health
Focal man questionnaire Background characteristics Parity, fertility preferences and contraceptive use Marital relationship quality, decision-making autonomy Adult morbidity and self-reported health
Wealth module Housing construction quality, asset ownership, expenditures in <1 year
Physical assessment Height, weight of household members Blood pressure, pulse Anemia (Ghana, Uganda)
MEASUREMENT STRUCTURE AND CONTENT
Country Site Sample size
Egypt Waldeya 548
Ethiopia Sebeta 998
Ghana Asawasa 800
Malawi Lunzu 605
Nigeria Ipetumodu 787
Nigeria Akinyele 502
Uganda Wakiso 505
Total 4745
PERI-URBAN FHWS SITES
SITES VARIED IN ‘PERI-URBAN-NESS’
TRAINING IS EVERYTHING
FHWS Round 2 training for Sebeta site
LEARNING TO TAKE BLOOD PRESSURE, MAPPING AND COMMUNITY SENSITIZATION
July 2011 workshopBlantyre, Malawi
PRECISION AND ENTHUSIASM
KNUST FHWS Team and some of equipment fieldstaff transported during interviews
Analysis workshops in July 2011 and July 2012 Data sharing and authorship agreements Gates Institute role is facilitating comparative analyses on pre-defined
set of topics Panel at International FP Conference 2011, Dakar
Each site has autonomy to share data with analysts within and outside Ghana: Two dissertations Ethiopia: One dissertation
One year spent on data cleaning and linking rounds Follow-up rates and who is missed
Analyses underway Comparative description of 4745 families’ health and wealth Childbearing patterns and child schooling and nutrition Childbearing and family wealth Couple concordance in fertility preferences and contraceptive use Parity and self-rated health (and gender differences)
PROGRESS TO DATE
0%
10%
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50%
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100%
Ibadan Ife Kumasi Lunzu Wakiso Sebeta
Parity Composition among Married Women Aged 15‐44 in Six FHWS Sites
6+
4‐5
2‐3
0‐1
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15-19 20-24 25-29 30-34 35-39 40-44
% u
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Modern Contraceptive Prevalence among Married Women Ages 15-44 by Age Group across Six Africa-based FHWS Sites
Ibadan
Ife
Kumasi
Lunzu
Wakiso
Sebeta
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% using
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Parity group
Modern Contraceptive Prevalence among Married Women Ages 15‐44 by Parity across Six Africa‐based FHWS Sites
Ibadan
Ife
Kumasi
Lunzu
Wakiso
Sebeta
CAPTURING HOUSEHOLD TRANSITORY WEALTH THROUGH AN INDEX ON
EXPENDITURES AND NON-DURABLES
J. Driessen, P. Ogunjuyigbe, A. Phillips, Q. Li, FHWS Study Team, A. Fatusi, A. Tsui
Common use of wealth quintiles from assets assessed in surveys (EDHS)Wealth measure can be broken down intoPermanent wealth (house, housing quality,
vehicle, ownership of durable goods)Transitory wealth (expenditures on entertainment,
eating out, other consumption reflective of ‘middle class’ lifestyle)
Such data are challenging to collectProxied with asset ownership of durables and non-
durables, expenditures, income, household quality
ANALYSIS OF PERMANENT AND TRANSITORY WEALTH MEASURES
Address overlapping measurement of wealth
Deconstruct household wealth into permanent and transitory components
Create a summative index
Selection of index items
Weights for each item
Dichotomous versus continuous measures
DHS wealth quintiles based on PCA with dichotomous measures
Used principal components analysis
RATIONALE FOR INDEX CONSTRUCTION
Self-rated wealth
9-step ladder of perceived relative economic status
Satisfaction with current income
4-step rating scale
Aspirational wealth
5-step rating scale of relative well-being in one year
OUTCOMES OF INTEREST
PERCENT DISTRIBUTION FOR SATISFACTION WITH CURRENT INCOME
0%
10%
20%
30%
40%
50%
60%
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90%
100%
Fully satisfied Rather satisfied Less than satisfied Not at all satisfied
Regress self-reported economic wellbeing measures on
Permanent wealth index (Fixed Asset Index)
Transitory wealth index (Middle Class Index)
Covariates
Male years of schooling
Number of persons in HH under age 5
Number of persons in HH age 5-14
ANALYTIC APPROACH
Sites Ethiopia Ghana Malawi Nigeria/IfeNigeria/
Ibadan UgandaEigenvalue of component 1 4.89 3.27 4.67 2.87 3.40 4.28% variance explained by component 1 10.4 7.4 14.1 6.2 8.5 10.4Cronbach's alpha 0.774 0.638 0.758 0.575 0.604 0.710Range of predicted score (min max) (-3.92
9.78)(-4.22 6.14)
(-2.67 17.44)
(-5.13 6.12)
(-4.10 11.06)
(-3.20 9.99)
% variance explained by component 1with all fixed asset and middle class index items
9.0 5.9 12.9 6.1 8.2 13.7
PCA RESULTS FOR FIXED ASSETS
EXAMPLE OF FACTOR LOADINGS FOR FIXED ASSET INDEX
Ethiopia Ghana MalawiNigeria/
IfeNigeria/Ibadan Uganda
FurnishingsHas bed 0.12 0.00 0.21 0.21 0.24 0.14Has table 0.08 -0.03 0.21 0.24 0.27 0.21Has chair 0.08 0.01 0.19 0.23 0.26 0.19Has dresser 0.26 0.13 0.17 0.18 0.20 0.23Has refrigerator 0.29 0.24 0.30 0.30 0.25 0.30Has landline telephone 0.28 0.04 0.15 0.04 0.14 0.14Has motorcycle 0.01 0.03 0.06 0.04 0.03 0.06Has bicycle 0.09 0.01 0.05 0.02 0.07 0.13Has car/truck 0.20 0.12 0.25 0.26 0.26 0.29Has horse cart -0.01 0.00 ‐‐ 0.03 ‐‐ 0.15Has generator 0.10 0.03 0.07 0.29 0.27 0.20
PCA RESULTS FOR MIDDLE CLASS INDEX
Sites Ethiopia Ghana MalawiNigeria/
IfeNigeria/
Ibadan UgandaEigenvalue 3.79 3.60 4.83 3.20 3.30 7.67% variance explained by component 1 11.2 10.6 15.1 9.4 9.7 22.6Cronbach's alpha 0.671 0.660 0.755 0.677 0.668 0.522
Range of predicted score (min max)(-2.67
12.64)(-1.57
18.15)(-2.12
11.82)(-4.09 7.77)
(-2.70 14.61)
(-0.93 23.65)
EXAMPLE OF FACTOR LOADINGS FOR MIDDLE CLASS INDEX
Sites Ethiopia Ghana MalawiNigeria/
IfeNigeria/Ibadan Uganda
Consumption/expenditure behaviorsSpent >$2.5 eating out in last 7 days 0.19 0.30 0.14 0.21 0.10 -0.02Spent >$10 in last month on clothes/shoes 0.07 0.29 0.14 0.22 0.16 -0.01Spent >$10 in last month on daily household items 0.19 0.30 0.20 0.30 0.15 -0.01Spent >$5 in last month on medicines 0.07 0.30 0.14 0.23 0.09 0.01Spent >$10 in last month on books, newspapers, school supplies and entertainment 0.18 0.22 0.23 0.22 0.16 0.00Spent >$5 in last month on other products and services 0.12 0.24 0.05 0.22 0.13 -0.01Spent >$20 in last month on child care 0.13 0.26 0.24 0.20 0.10 0.00Spent >$15 in last 7 days on food (less amount spent eating out) 0.23 -0.25 0.20 0.07 0.13 0.00Spent >$10 in last month on utilities 0.28 -0.01 0.25 0.20 0.24 0.01Paid any amount for taxes last year 0.23 0.26 0.20 0.17 0.15 -0.02Household has no debt 0.01 -0.16 0.00 -0.06 -0.04 0.00Household has lent any amount to others 0.05 0.11 0.07 0.11 0.14 -0.01Household currently has savings 0.18 0.08 0.22 0.14 0.18 -0.01
Red frame indicates statistical significance at 5% level.Adjusted for male education, presence of children and youth in household
Red frame indicates statistical significance at 5% level.Adjusted for male education, presence of children and youth in household
Red frame indicates statistical significance at 5% level.Adjusted for male education, presence of children and youth in household
WHAT WE’VE LEARNED ABOUT WEALTH MEASUREMENT
PCA can be applied to other non-asset variables and reduce reliance on reported expenditure data
Constructed Middle Class Index reflective of consumption and short-term well-being
MCI performs similarly to Fixed Asset Index in predicting self-reported wealth outcomes
Middle class index sensitive to Expenditure ‘shocks’ (e.g., unanticipated health expenses) Health expenditure shock likely associated with having
sick children Presence of children Children may drive expenses captured in transitory
wealth score
THE DISTRIBUTION OF THE PERMANENT WEALTH SCORES IN ROUND 1 AND 2 (ETHIOPIA)
0.0
5.1
.15
.2.2
5D
ensi
ty
-5 0 5 10Fixed Assets Scores
Round 1 Round 2
THE DISTRIBUTION OF THE TRANSITORY WEALTH SCORES IN ROUND 1 AND 2 (ETHIOPIA)
0.0
5.1
.15
.2.2
5D
ensi
ty
-5 0 5 10 15MCI Scores
Round 1 Round 2
Factor Adj OR p level
Family income (Round 1/log) 1.011 0.011Length of residence (Husband) 0.997 0.687Length of residence (Wife) 0.988 0.199Borrowed money last year for health expenses 0.609 0.051Own house 0.619 0.010Duration of marriage (Wife report) 0.953 0.001Regret marrying spouse (Husband) 1.470 0.164Regret marrying spouse (Wife) 1.358 0.164Husband has other wives (Wife report) 1.265 0.543Husband has other wives (Husband report) 0.474 0.211
*Model also controls for occupation type of husband and wives (ns)n=950 couples, weighted for loss to follow up
FACTORS ASSOCIATED WITH COUPLE LOSS-TO-FOLLOW UP (ETHIOPIA)
ROC (RECEIVING OPERATING CHARACTERISTICS) CURVE TO ASSESS
PROPENSITY SCORE
0.2
5.5
.75
1S
ensi
tivity
0 .25 .5 .75 11 - Specificity
Area under curve = 0.6743 se(area) = 0.0196
01
23
4D
ensi
ty
0 .2 .4 .6 .8Propensity Score
Captured in 2nd roundMissed in 2nd round
Closeness of curve to diagonal line is favorable to constructed propensity score model
Distribution of propensity scores of those missed and relocated are similar(Ethiopia results only)
Factor Reg Coeff p level
Middle class score (Round 1) 0.777 0.000Fixed asset score (Round 1) 0.088 0.000Husband's years of education (Round 1) 0.020 0.007Borrowed money last year for health expenses -0.126 0.122Number of children < age 71 0.128 0.0612 0.088 0.365
n=693 couples, weighted for loss to follow up
FACTORS AFFECTING ROUND 2 TRANSITORY WEALTH SCORE
Critical importance of training and supervision It’s not worth doing, if it’s not done well
Standardized data-entry formats
Importance of longitudinal study design Under-estimated loss-to-follow up which impacts Round 2 sample
power
Challenges with relocating couples in peri-urban areas Couple follow-up rates are not surprisingly lower than individual
follow-up rates
Household loss due to logical events (marital disruption, migration, death)
Ability to decompose overall wealth into permanent and transitory components
This type of study is rare in the African setting.
WHAT WE’VE LEARNED ABOUT CHANGE THROUGH FHWS
Whether childbearing patterns consistently influence family health and wealth outcomes
WHAT WE HAVEN’T LEARNED AS YET
THANK YOU AND MANY THANKS TO THE PRODIGIOUS EFFORTS OF THE
EXTENDED FAMILY OF RESEARCHERS AND FHWS STUDY PARTICIPANTS AND SUPPORT FROM
THE BILL & MELINDA GATES FOUNDATIONTHROUGH THE GATES INSTITUTE.