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INEQUALITIES IN

HEALTH

Report of the Measuring Inequalities in Health Working Group

November 2003

CONTENTS Page 1. Introduction 3 2. Background 4 3. Measuring Inequalities in Health 3.1 Overview 5 3.2 Indicators of Health 5 3.3 Population Groups 6 3.4 Socio-economic measure 6 3.5 Statistical Measure of Inequality 10 3.6 Geographical Level 12 4. Selection of Health Indicators 4.1 National Monitoring 13 4.2 NHS Health Board Monitoring 15 5. Results and Trends 5.1 Results 17 5.2 Trends – Summary 18 5.3 Results and Trends – By Indicator 19 6. Targets for Reducing Health Inequalities 29 7. Further Work 30 Annex A Appendix 1 – Membership of Working Group 31 Appendix 2 – Potential Indicators of Health Inequalities 33 Appendix 3 – Proposed Indicators of Health Inequalities 37 Definition and Data Sources Annex B Appendix 1 – Concentration Index 41 Annex C Appendix 1 – Ratios in Health Inequalities (Summary Table) 43 Appendix 2 – Trends and Ratios in Health Inequalities 45 Results and Charts for each Indicator

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1. INTRODUCTION 1.1 In Our National Health, the Scottish Executive gave a commitment to:

"… develop the health indicators within our Social Justice framework of targets and milestones to track progress in tackling health inequalities"1

The Measuring Inequalities in Health Working Group was set up by the Scottish Executive to determine the most appropriate indicators to use to monitor progress in tackling health inequalities. The 23 indicators recommended by the Working Group in this report were adopted in Improving Health in Scotland – The Challenge (2003). These indicators are listed in Table 2 under section 4.1.5 of this report. 1.2 The remit of the Working Group was to consider alternative methods of measuring health inequalities in Scotland and to advise on possible targets. More specifically, the remit of the Group was to: ♦ identify the information required to monitor changes in health inequalities; ♦ collect and analyse the information currently available; ♦ identify data gaps and advise on alterations to existing data streams/generation of new

data streams; ♦ advise on a range of measurement issues (e.g. which socio-economic and statistical

measures to use) ♦ identify possible targets which could be set for reducing health inequalities in Scotland,

and to consider the advantages and disadvantages of each and make recommendations. 1.3 This report describes the work that the group has carried out and their conclusions and recommendations. The membership of the group is shown at Annex A Appendix 1. 1.4 Our National Health gave a clear commitment to tackling inequalities in health through a range of policies which include measures to address the underlying socio-economic circumstances that influence the health of the population. This report focuses inequalities in health between deprived and affluent population groups, though it is recognised that health inequalities may arise in other ways - e.g. between urban and rural areas, or between different ethnic groups. We recommend that further work should be done to assess whether indicators need to be developed to monitor trends in health inequalities in these areas. This report has concentrated on the measurement of health inequalities between socio-economic groups because this has been the major area of public concern. The scale of these socio-economic inequalities in health within Scotland has contributed significantly to Scotland's poor overall health record compared with that of other EU countries.

1 Our National Health: A plan for action a plan for change, 2000

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2. BACKGROUND 2.1 It has long been recognised that substantial inequalities in health exist between socio-economic groups. This can be seen in differences across geographic areas, for example among mainland local government districts in Scotland, for the period 1998-2000, there was a difference in life expectancy of 7.4 years for males (76.1 in East Dunbartonshire and 68.7 in Glasgow City) and 4.9 years for females (80.6 in East Renfrewshire and 75.7 in Glasgow City)2. 2.2 It can also be seen across Social Classes, for example Figure 1 shows that the rate of early deaths among males in Scotland was almost four times greater for those in Social Class V than for those in Social Class I, for the period 1991-93. 2.3 Figure 1 also shows that Scotland has poorer rates of early deaths than England for each of the Social Classes. This is particularly pronounced for Social Class V and gives rise to greater inequalities between the most affluent and most deprived in Scotland than in England. Figure 1: Age-standardised mortality rates by Social Class, England and Scotland, all

causes, males aged 20-64, 1991-93

.4 Recent trends in health inequalities within Scotland are considered in Section 5.

0

200

400

600

800

1000

1200

1400

I II IIIN IIIM IV V

Social Class

England Scotland

Source: Geographic Variations in Health: National Statistics

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2 Life expectancy 1998-2000, Health Statistics Quarterly 13, Office of National Statistics

3 MEASURING INEQUALITIES IN HEALTH 3.1 Overview 3.1.1 To monitor the progress in reducing health inequalities, reliable indicators are needed of the changes that take place over time in the relative health of different socio-economic groups. In producing these indicators, the following aspects of measuring inequalities were explored: The indicators of health that should be used;

The population groups that should be monitored;

The socio-economic measure to use;

The statistical method for estimating inequalities;

The geographical level (e.g. Scotland, NHS Boards, etc.).

Each of these aspects are further examined below. 3.2 Indicators of Health 3.2.1 There are many different indicators of health that can be used to monitor trends in inequalities in health. The following criteria were adopted by the Group for selecting potential indicators: They should provide information on inequalities in important areas of health and should

reflect the targets adopted in Towards a Healthier Scotland and the health milestones in Social Justice;

They should include lifestyle, morbidity and mortality indicators to ensure a balanced

coverage of different aspects of health experience;

They should cover a broad range of health conditions (e.g. physical as well as mental health, and different diseases);

They should be capable of being updated at least every 2-3 years;

They should provide statistically robust measures of inequalities.

3.2.2 Annex A Appendix 2 shows the set of 30 health indicators that the Group initially considered. Many of these indicators were selected on the basis that they cover aspects of health which had already been adopted as overall health targets in Towards a Healthier Scotland, or had been included in the milestones Social Justice: A Scotland Where Everyone Matters. In addition, a number of other indicators were considered which it was felt may provide useful measures of inequalities in health, for example, accidents in children, self-reported health, and infant mortality.

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3.3 Population groups 3.3.1 A range of indicators were selected to provide coverage of a wide range of population groups including children and younger people as well as adults. Where possible, the extent of inequalities in males and females were monitored separately. The indicators cover the following population groups: children young people adults older people

3.3.2 Where the indicators cover a wide age range, they have been standardised to the European Standard Population. This adjustment accounts for changes in the population age structure, which makes comparisons across years more meaningful. 3.4 Socio-economic measure 3.4.1 The Group considered two measures of socio-economic status: (a) Social Class, and (b) the Carstairs area-based measure of deprivation. 3.4.2 Social class has long been used as a socio-economic measure of inequalities in health. This is because much of the previous evidence on inequalities is based on mortality data drawn from death certificates which also record information about occupation. This information forms the basis of the classification scheme based on social class.3 However, there are a number of difficulties with the use of social class as a measure of socio-economic circumstances, as follows. The method of attributing occupations to different social classes is somewhat arbitrary.

Population denominators by social class are only available for census years.

A significant proportion of women are not assigned to any social class in either mortality

data or population data. The number of women who are not attributed to any social class in the mortality data accounts for between 30% and 40% of deaths. This non-classification of mortality data is much smaller in men accounting for on average only 3% of deaths. The population data from the 1991 census show a similar problem with a much larger proportion of women unassigned by social class.

Finally, this approach can only be applied where health records provide information about

social class. In practice many health records do not include this information. For example, information about smoking during pregnancy, breastfeeding, low birthweight babies, the

3 The system of social classification used in the past was based on the Registrar General’s social class scheme which served as the official measure of social class in each Census from 1911 to 1991. It has now been replaced with a new system - the National Statistics Socio-Economic Classification which replaces skill and social standing with employment relations as the main determinant of class position.

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dental health of children, accidents in children, and teenage pregnancy rates cannot be classified by social class.

3.4.3 Some of these problems are overcome by the use of survey data, and the Group concluded that social class should be examined further following the release of the next Scottish Health Survey results and after the new National Statistics Socio-Economic Classification has been embedded. 3.4.4 The alternative measure which the Group has considered is the Carstairs index of deprivation, which is a small area based measure of socio-economic circumstances. Typically these areas are based on postcode sectors of which there are almost 1,000 in Scotland with an average population of around 5,000. The main source of data about the socio-economic characteristics of each area is the 10 yearly census which records information about the social and economic characteristics of the population living in each area. The Carstairs index is based on 4 variables from the census: male unemployment rates; the proportion of households in social classes 4 and 5; car ownership; and overcrowding (more than 1 person per room in private households)

These 4 variables are measured against the Scottish average and re-scaled so that they have the same degree of variation across Scotland. The resulting transformed variables (z-scores) are given equal weight and combined to form an overall index of deprivation.4 3.4.5 The Carstairs index of deprivation has become widely used in Scotland as a means of measuring socio-economic inequalities in health, though it has certain limitations. First, postcode sectors generally do not have populations which are socially and economically homogeneous. Many postcode sectors will contain a mix of relatively deprived and relatively affluent households. Figure 2, for example, shows the distribution of the Scottish Health Survey sample by social class across different postcode areas classified by the Carstairs index of deprivation in the 1998 Scottish Health Survey. The postcode sectors have been ranked according to the Carstairs index of deprivation and grouped into quintiles. Carstairs quintile 1 contains the most affluent postcode sectors while quintile 5 contains the most deprived postcode sectors.

4 Reference to Vera Carstairs’s study of Deprivation and Health in Scotland

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Figure 2: Distribution of Households from the Scottish Health Survey by Social Class

and Carstairs Deprivation Quintile, 1998

.4.6 While there is clearly a strong association between the distribution of social classes

• Carstairs quintile 5 includes the 20% most deprived postcode sectors in Scotland,

• Carstairs quintile 1 contains the 20% most affluent postcode sectors in Scotland.

.4.7 An inevitable consequence of using an area-based method of estimating socio-

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.4.8 A second criticism of the Carstairs deprivation index is that the choice of socio-i

Social Class as a Percentage of Carstairs deprivation quintiles

0%

20%

40%

60%

80%

100%

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

Carstairs deprivation quintiles

VIVIIIMIIINMIII

Scottish Health Survey 1998

3and the area-based deprivation quintiles, Figure 2 also shows that the social class structure of each Carstairs quintile is quite mixed. For example:

and the 1998 Scottish Health Survey covered 2,436 people in this quintile. While this group included 1,539 people (63%) in Social Classes 3 (manual), 4 and 5, no less than 474 people (19%) were in Social Classes 1 and 2, while a further 423 (17%) were in Social Class 3 (non-manual).

More than 50% of the survey population in this Carstairs quintile were in Social Classes 1 and 2, but almost 10% of the survey population were in Social Classes 4 and 5.

3econom c inequalities in health is that the degree of health inequalities will tend to be under-stated. Since postcode sector areas generally contain a mixture of socio-economic groups, the effect will be that differences in inequalities between the most affluent and deprived areas will be less than would be found in measures of inequalities between the most affluent and deprived individuals. 3econom c indicators used in the construction of the index is somewhat arbitrary, as is the assignment of equal weight to each indicator. A specific criticism of the Carstairs index is the use of car ownership as an indicator of relative deprivation. This has been questioned on the grounds that although car ownership may be a useful indicator of deprivation in urban areas it

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is less suitable in rural areas where car ownership is seen as essential given the limited availability of public transport. 3.4.9 A third concern about the Carstairs index is that since it is based on census

at

.4.10 The choice between social class and the Carstairs area-based deprivation index as

• Since social classes are likely to provide more homogeneous groups than the

A serious weakness of the social class approach, however, is that, at best, it is only

.4.11 The Group has concluded that, on balance, the Carstairs area-based measure

• First, the use of area-based measures greatly increases the range of indicators that

Second, it might be expected that trends in health inequalities between affluent

further advantage of using the Carstairs measure area-based inequalities in health is that

.4.12 In 2002 a research team from the Social Disadvantage Research Centre (SDRC)

he new Scottish Index of Multiple Deprivation (SIMD) is a ward level index made up of

he Scottish Indices at ward level are : Income Deprivation, Employment Deprivation, Health Deprivation and Disability, Education, Skills and Training Deprivation and

inform ion it can only be updated every 10 years. The use of this index to monitor trends in inequality between the 10 yearly census assumes that the relative socio-economic position of each postcode sector does not change significantly between each census. 3the socio-economic measure against which health status is measured reflects a number of considerations.

postcode sectors used in the Carstairs area-based measure, measures of health inequalities based on social class are more likely to reflect the real extent of these inequalities.

•available for a limited range of indicators. It cannot be used for health indicators that are based on data recorded by the NHS, and nor can it provide reliable measures of inequalities in mortality rates in women.

3provides the more appropriate method of measuring trends in inequalities in health. Although this approach understates the extent of socio-economic inequalities in health two points are worth noting.

can be used to monitor trends in inequalities;

•and deprived areas should broadly reflect trends between affluent and deprived person based data - though the extent to which this is the case needs further research.

Athis approach has become widely used and accepted as a method of measuring inequalities in the NHS. 3based in Oxford University’s Department of Social Policy and Social Work was contracted by the Scottish Executive to construct Indices of Deprivation for Scotland. Tfive ward level Domain Indices. Summary measures of the SIMD are presented at local authority level. The ward level Indices, together with the local authority level summaries are referred to as the Scottish Indices of Deprivation 2003. T

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Geographical Access to Services Deprivation. The Summary Report ‘Scottish Indices of Deprivation 2003’ was published in February 2003. Future work on measuring health inequalities ought to consider the benefits of using these

ew Indices of Deprivation in comparison to the Carstairs and Social Class measures.

.5 Statistical Measures of Inequality

. tistical measures that can be used to measure cio-economic inequalities in health and trends in these inequalities over time.

alth status of the most affluent and the most deprived socio-economic groups - for example, the

• fferent method is to compare the absolute differences between the

most affluent and deprived groups - whether measured by social class or by the

3.5.2 A ethods to measure trends in inequalities in mortality rates from coronary heart disease in Scotland between 1995

ase Among People Under 75 (Rate per 100,000 Population)

Males Females Males Females ost Affluent Areas 120.03 48.58 79.54 24.13 ost Deprived Areas 258.39 186.19

uent) ce

ffluent) 138.36 52.07 106.65 47.13

2001 the ratio of the mortality rate in the most deprived areas and the

n 3 3.5.1 There are a number of different staso

• The most commonly used measure has been the ratio between the he

ratio of the mortality rates in Social Classes 5 and 1, or the ratio of the mortality rates among people in the most deprived group of postcode sectors compared with the mortality rate in the most affluent group. These are relative measure of health inequalities.

A slightly di

area-based Carstairs deprivation index. The ratio and absolute difference methods can provide quite different measures of trends in inequalities.

s an example, Table 1 shows the effects of using these two m

and 2001 based on the Carstairs index of deprivation.

Table 1 : Mortality Rates from Coronary Heart Dise

1995 2001 MM 100.65 71.26 Ratio (deprived to affl

2.15 2.07 2.34 2.95

Absolute differen(deprived less a Between 1995 andmost affluent areas increased from 2.15 to 2.34 for males and 2.07 to 2.95 for females i.e. inequality ratios have worsened. However, measured by the absolute difference, the gap between the most affluent and the most deprived areas narrowed from 138.36 to 106.65 for males and from 52.07 to 47.13 for females. Estimates of trends in health inequalities can therefore be quite sensitive to whether the differences are measured by the ratio of the health status measure in the affluent and deprived groups or by the absolute difference.

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3.5.3 Another statistical measure is : • To compare the position of the most deprived group (whether measured by Social

Class or Carstairs area-based measure) to the national average or to a middle group in the population. Again, these measures may show quite different trends from estimates based on the ratio of the most deprived to the most affluent or the absolute difference between these groups.

3.5.4 The Group has concluded that the most appropriate method of measuring trends in socio-economic inequalities in health is to compare the ratio of the most deprived to the most affluent : (i) While the absolute difference in the health of different population groups is of

interest, there is little doubt that much of the debate about health inequalities reflects a concern about the relative probability of experiencing poor health in different socio-economic groups. It is the relative difference in the health status of deprived and affluent groups which has been the focus of concern rather than the absolute difference. The methods that we adopt for monitoring trends in health inequalities need to reflect this concern.

(ii) The Group also concluded that differences between the most deprived and the

most affluent were of more interest than the position of the most deprived compared with the national average or with a middle group.

3.5.5 Within these methods, there is a further choice to be made about the size of the deprived/affluent population groups. For example, should the 10% most deprived areas be compared against the 10% most affluent, or should the top and bottom 20% or 40% be used. The smaller the groups that are used for comparison, the greater the risk that trends in the ratio of deprived to affluent will show erratic year-on-year movements because of the ‘small numbers’ problem. At the same time using relatively large groups - e.g. the top and bottom 40% of the population - may provide an indicator which masks the scale of inequalities between the most deprived and most affluent populations. The Group has concluded that comparisons between the top and bottom 20% of postcode sectors provides a reasonable compromise between these different considerations. 3.5.6 A criticism of measures such as the ratio of the most deprived to the most affluent is that they take into account the ‘extremes’ of the socio-economic distribution of health - e.g. the top and bottom 20% - but ignore the other 60% of the distribution. People living in the postcode sectors classified as Carstairs Quintile 4 (i.e. people living in areas ranked as 21-40% in terms of deprivation) also have much poorer health than people living in Carstairs Quintile 1 and it is important that progress should also be made in improving their relative health. A number of more sophisticated methods of measuring health inequalities have been developed that take into account the total distribution of health in the population. One such method is the ‘Concentration Index’, which is described in Annex B Appendix 1. 3.5.7 The Group considers that the more sophisticated methods of measuring inequalities are potentially useful. However, they are statistically more complex and the results are more difficult to present to a wider audience. Tackling inequalities in health is a key policy aim, and it is important therefore that progress can be monitored and assessed through indicators that are readily understood by the wider public. Indicators which compare the ratio of the

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health status of the most deprived areas of Scotland against the most affluent areas are relatively easy to interpret, and this is an important consideration. Nevertheless we recommend that further work should be done to compare trends in health inequalities over time between relatively simple statistical measures based on the ‘extremes’ of the distribution and the more complex measures which take into account the total distribution of health across socio-economic groups. 3.6 The Geographical Level 3.6.1 A specific issue that the Group has considered is the need to identify a small number of indicators that can be used in the Performance Assessment Framework (PAF) which the Health Department has established to monitor the performance of Health Boards and Trusts. The PAF uses a wide range of indicators to assess performance, and one of the areas in the PAF is the performance of Health Boards in tackling health inequalities.

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4 SELECTION OF HEALTH INDICATORS 4.1 National Monitoring 4.1.1 We have not considered measures of inequalities in socio-economic circumstances e.g. measures of poverty, education, and housing conditions. The focus of our work has essentially been indicators of inequalities in health status between different socio-economic groups. While socio-economic factors are clearly important influences on health experience, Social Justice: A Scotland Where Everyone Matters has already identified a wide range of indicators which potentially can be used to monitor trends in inequalities in social and economic circumstances. Nor, at this stage has the Group considered inequalities related to access to and use of healthcare; however we recognise that this is an important issue that needs further work. 4.1.2 Initial analysis of the evidence about socio-economic inequalities in health in the indicators listed in Annex A Appendix 2 suggested that some of these measures would not, in fact, provide useful indicators of trends in inequalities for two reasons. First, for some of these indicators there do not appear to be significant differences in health status between socio-economic groups. Indicators which have been excluded for this reason are:

• excess consumption of alcohol where the analysis showed that there is very little difference in rates of excess consumption in affluent and deprived areas;

• exercise in older people where the socio-economic differences also appear quite small.

4.1.3 A second reason for excluding indicators is that in some cases the numbers are quite small and, even when 3 year moving averages are used, the estimates of inequalities are unreliable and trends over time are very erratic. Indicators excluded on this basis are:

• the number of accidental deaths annually among children aged 14 and under;

• chronic respiratory disease in people aged 65-74. The source of this data is the Continuous Morbidity Recording (CMR) scheme which collects information from a sample of GP practices. The number of cases of chronic respiratory disease by this sample is too small to provide statistically reliable estimates of socio-economic inequalities;

• admission to hospital for drugs misuse among people aged 10-54. The number of patients admitted from affluent areas is very small and the trend in inequalities is very erratic.

4.1.4 The Group also decided to exclude mortality rates from Stroke among people aged under 75, as mortality from all causes, coronary heart disease and cancer were already included.

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4.1.5 On the basis of this initial analysis the number of indicators was reduced to the set of 23 shown in Table 2. Table 2: Recommended Indicators of Health Inequalities Population Group Indicator of Inequality

Children 1. Smoking during pregnancy

2. Breastfeeding 3. Dental health of children 4. Low birthweight babies 5. Accidents in children aged 0-9 (hospital admissions) 6. Infant mortality

Young People 7. Accidents in children aged 10-14 (hospital admissions) 8. Teenage pregnancies (females aged 13-15) 9. Teenage pregnancies (females aged 13-19) 10. Suicides among young people aged 10-24

Adults 11a Diet - consumption of fresh fruit 11b Diet - consumption of green vegetables 12. Adult smoking 13a Self-reported general health in people aged 16-44 13b Self-reported general health in people aged 45-64 14. Self-reported limiting long-standing illness 15. Obesity 16 Mental health (GHQ12 scores) 17 All cause mortality rate among people under 75 18 Mortality rates from coronary heart disease among

people under 75 19 Mortality rates from cancer among people under 75 20 Life expectancy

Older People 21 All cause mortality rate among people over 75. 22 Mortality rates from coronary heart disease among

people 75 and over. 23 Mortality rates from cancer among people 75 and over.

4.1.6 The indicators in Table 2 are strongly weighted toward two population groups: children and adults. It has proved more difficult to find suitable indicators on inequalities in health among younger people. To some extent this is inevitable, since morbidity and mortality are relatively uncommon in this age group. It is perhaps more surprising to have only three indicators for older people i.e. people over 75. The main reason for this is that health inequalities inevitably tend to narrow in older age groups. The incidence and prevalence of health problems is more evenly distributed among those who have survived into old age. For example, the difference in all cause mortality rates among people over 75 between affluent and deprived areas is much smaller than the difference found among people under 75. Nevertheless, it is no less important to monitor the extent of health inequalities in older people and the trend in these inequalities over time. 4.1.7 A more detailed definition of the proposed indicators of health inequalities and a description of the sources of data are given in Annex A Appendix 3.

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4.2 NHS Health Board Monitoring 4.2.1 All of the indicators outlined in Table 2 (section 4.1.5) can be monitored at national level. It is also important that trends in health inequalities should be monitored within each Health Board to assess the progress that is being made locally in tackling these inequalities. It is, of course, for each NHS Board to determine how best to monitor trends in health inequalities and NHS Boards may wish to adopt different measures to reflect particular local circumstances. However, it is important that there should be a core set of indicators that can be applied consistently across Scotland, and that will allow comparisons to be made between NHS Boards. This Working Group recommended 5 core indicators which are currently being used in the Performance Assessment Framework (PAF) to monitor health inequalities at the NHS Board level. These 5 core PAF indicators are listed in Table 3 under section 4.2.6. 4.2.2 There are two problems in applying indicators of health inequalities at NHS Board level. First, a difficulty in developing indicators at national level has been the problem of ‘small numbers’. This problem becomes even more serious at NHS Board level. For example, it is difficult to monitor at NHS Board level indicators that are drawn from the Scottish Health Survey. The sample size of this survey is generally too small to enable any reliable estimates to be made of inequalities at NHS Board level. This means that the following indicators have to be excluded.

• diet (consumption of fresh fruit and green vegetables) • obesity • self-reported health • self-reported long-standing illness • GHQ12 scores

4.2.3 Other indicators where numbers would be too small at NHS Board level to provide reliable measures of inequalities include:

• low birthweight babies • infant mortality • accidents in children (aged 0-4 and 5-14) • teenage pregnancies (13-15) • suicides among young people

4.2.4 The mortality indicators for persons aged over 75 were excluded because they did not show significant inequalities for all Health Boards.

• All cause mortality rate among people over 75 • Mortality rates from coronary heart disease among people 75 and over • Mortality rates from cancer among people 75 and over.

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4.2.5 This leaves a relatively small group of indicators that might provide suitable measures of inequalities at NHS Board level.

• smoking during pregnancy • breastfeeding rates • dental health of children • teenage pregnancies (13-19) • adult smoking • all cause mortality rates among people under 75 • mortality rates from coronary heart disease among people under 75 • mortality rates from cancer among people under 75 • life expectancy

A problem with breastfeeding rates is that at present only 9 NHS Boards collect this data on a consistent basis. 4.2.6 The Group recommends that the following set of 5 indicators should be adopted in the PAF for monitoring trends in health inequalities. Table 3: Recommended Indicators of Inequalities at NHS Board Level Population Group Indicator of Inequality Children 1. Smoking during pregnancy

2. Dental health of children Adults 3. Adult smoking

4. Mortality rates from coronary heart disease among people under 75

5. Life expectancy 4.2.7 The second difficulty in monitoring trends at NHS Board level and in making comparisons between Boards is that differences in health inequalities between NHS Boards reflect two factors:

• inequalities in socio-economic circumstances; and • inequalities in health status associated with these circumstances.

For example, inequalities in health in Greater Glasgow might be expected to be greater than inequalities in health in Borders simply because Greater Glasgow has much wider inequalities in socio-economic circumstances. Comparisons of inequalities between NHS Boards would therefore be difficult to interpret because of these underlying differences in socio-economic circumstances. 4.2.8 The methodology used is therefore to calculate for each Board the inequality in health between its own most deprived and affluent postcode sectors. It would then be possible to compare each Board’s progress over time in reducing inequalities between its own deprived and affluent areas. This approach of using each Board’s own starting position as the yardstick has been adopted for other indicators in the PAF.

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5 RESULTS AND TRENDS 5.1 Results 5.1.1 Estimates of health inequalities for the 23 proposed indicators are shown in the Summary Table in Annex C Appendix 1. More detailed information along with a graphical representation of these results is contained in Annex C Appendix 2. A summary description of the trends is provided in section 5.2 and a fuller description for each indicator is provided in section 5.3 5.1.2 The health inequality is calculated as the ratio between the health status of the population living in the most deprived quintile of postcode sectors and the population living in the most affluent quintile of postcode sectors.

• a ratio greater than 1 implies that the health of the population in the most deprived quintile is worse than that of the population in the most affluent quintile;

• an increase (or reduction) in this ratio over time implies that the degree of

inequality between the health of the populations living in the most deprived and affluent postcode sectors is widening (or narrowing).

5.1.3 In interpreting the trends shown in Annex C it is particularly important to bear in mind the confidence limits around the ratio estimates. The 95% confidence limits for each indicator is illustrated the in charts in Annex C Appendix 2. It is also important to recognise that these indicators measure trends in the relative health status of the populations living in affluent and deprived areas, not their absolute health status. For some indicators, the absolute health of all population groups may have improved over time. However, inequalities will widen if the rate of improvement in the most affluent population group is greater than the rate of improvement in the most deprived group. 5.1.4 Table 4 contains estimates of mortality rates from coronary heart disease among Males under 75 which illustrate these points. Table 4 : Mortality Rates From Coronary Heart Disease in Males Under 75 (Rate per 100,000 Population Standardised to the European Population) Quintile 1991 1998 2001 Most Affluent 161.36 98.04 79.54 Most Deprived 295.81 223.30 186.19 Ratio 1.83 2.28 2.34 Ratio Confidence Limits 1.68 - 2.00 2.05 - 2.53 2.09 - 2.63 Mortality rates per 100,000 people living in the most deprived and affluent quintiles have fallen substantially during the 1990s.

• The mortality rate in the most affluent quintile has fallen from 161.36 in 1991 to 79.54 in 2001 - a fall of 51%

• Over the same period, the mortality rate in the most deprived quintile fell from

295.81 in 1991 to 186.19 in 2001 - a fall of 37%.

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Therefore, despite a substantial fall in mortality rates in the most deprived areas, the ratio of the mortality rates in deprived and affluent areas suggests that inequality widened between 1991 and 2001.

However, the data on confidence limits suggests some caution is required in interpreting the changes in the ratio of mortality rates. The ratio confidence limits between 1991 and 2001 only narrowly avoid overlap. If they had overlapped then this would have suggested that the increase in the ratio may not be statistically significant. 5.2 Trends - Summary 5.2.1 The data contained in Annex C covers a wide range of health indicators and population groups and it is not easy to identify any general patterns in recent trends. A broad summary for the main population groups of trends in the health inequality ratios might be: Children

• no significant change in inequalities related to dental caries in five year olds, low birthweight babies, breastfeeding, hospital accident admissions and infant mortality;

• a significant narrowing of inequalities in relation to mothers smoking during pregnancy.

Young People

• no significant change in inequalities in the suicide rates, hospital accident admissions and teenage pregnancies, for both those aged 13-15 and those aged 13-19 year olds.

Adults

• lifestyle – a significant widening of inequalities between 1995 and 1998 in fresh fruit consumption for males but not for females. No significant change in inequalities in green vegetable consumption, smoking or obesity.

• self-reported health and long-standing illness – a significant increase in inequalities in females reporting a long-standing illness between 1999 and 2001. No other significant changes between 1999 and 2001.

• mental health (GHQ12 scores) – no significant change in inequalities; • mortality rates – there has been a significant widening of inequalities in coronary

heart disease mortality rates for males between 1991 and 2001, the increase for females was not quite significant. There have been no significant changes in inequalities in cancer mortality rates. For all-cause mortality, the increases in inequalities between 1991 and 2001 have been significant for males but not for females.

• life expectancy – the inequality ratio has widened for males between 1991-93 and 2000-02 and remained fairly constant for females.

Older People

• mortality rates - no significant changes in inequalities during the 1990s

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5.3 Results & Trends – By Indicator Children 1. Percentage of mothers smoking during pregnancy 5.3.1 In 1994, 42% of mothers from deprived areas smoked during pregnancy compared to 14% from affluent areas - by 2002, the corresponding results were 37% and 14%. This means that there has been a significant decrease in mothers smoking from deprived areas, causing a significant narrowing in the inequality ratio. By 2002, mothers from deprived areas were 2.58 times more likely to smoke during pregnancy than mothers from affluent areas, compared to an inequality ratio of 2.95 in 1994. Results for 1993, the first year shown in Annex C Appendix 1, do not seem to fit in with all the other years and should be treated with caution. 2. Percentage of mothers not breastfeeding at 6-8 weeks 5.3.2 In 1995, 85% of mothers from deprived areas were not breastfeeding compared to 51% from affluent areas – by 2002, the corresponding results were 76% and 44%. As there have been significant improvements for mothers living in both deprived and affluent areas, this has resulted in no significant change in the inequality ratio. By 2002, mothers from deprived areas were 1.71 times less likely to breastfeed than mothers from affluent areas, compared to an inequality ratio of 1.65 in 1995. 3. Percentage of 5-year olds with dental caries 5.3.3 Girls – In 1993, 75% of girls from deprived areas had dental caries compared to 41% from affluent areas – by 1999, the corresponding results were 72% and 39%. These improvements are not significant and have resulted in no change to the inequality ratio. In 1999, girls from deprived areas were 1.83 times more likely to have dental caries than girls from affluent areas, which is the same inequality ratio as in 1993. 5.3.4 Boys – have a similar rate of dental caries as girls. In 1993, 78% of boys from deprived areas had dental caries compared to 45% from affluent areas – by 1999, the corresponding results were 73% and 41%. Although these improvements are greater than for girls, they are still not significant. This has resulted in no significant change in the inequality ratio. In 1999, boys from deprived areas were 1.78 times more likely to have dental caries than boys from affluent areas, compared to an inequality ratio of 1.71 in 1993. 4. The percentage of low birthweight babies 5.3.5 Females – During 1991 to 1993, 4.4% of female babies born in deprived areas had a low birthweight compared to 2.0% from affluent areas – by 2000 to 2002, the corresponding results were 4.1% and 1.8%. These improvements are not significant. During 2000 to 2002, female babies from deprived areas were 2.30 times more likely to have a low birthweight than those from affluent areas, compared to an inequality ratio of 2.17 from 1991 to 1993. 5.3.6 Males – male babies are less likely to have a low birthweight than female babies, particularly in deprived areas. During 1991 to 1993, 2.7% of male babies born in deprived areas had a low birthweight compared to 1.4% from affluent areas – by 2000 to 2002, the corresponding results were 2.7% and 1.2%. These improvements are not significant. During 2000 to 2002, male babies from deprived areas were 2.31 times more likely to have a low birthweight than those from affluent areas, compared to an inequality ratio of 2.00 from 1991 to 1993.

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5. Accidents: hospital admissions of children aged 0-9 years 5.3.7 Females – In 1991, the hospital accident admission rate per 100 females aged 0-9 was 1.48 in deprived areas and 1.01 in affluent areas – by 2001, the corresponding results were 1.17 and 0.75. These improvements are significant for both deprived and affluent areas and result in no significant change to the inequality ratio. In 2001, females aged 0-9 from deprived areas were 1.55 times more likely to have a hospital accident admission than those from affluent areas, compared to an inequality ratio of 1.46 in 1991. 5.3.8 Males – aged 0-9 have a higher rate of hospital accident admissions than females. In 1991, the hospital accident admission rate per 100 males aged 0-9 was 2.69 in deprived areas and 1.42 in affluent areas – by 2001, the corresponding results were 1.77 and 1.02. These improvements are significant for both deprived and affluent areas and result in no significant change to the inequality ratio. In 2001, males aged 0-9 from deprived areas were 1.74 times more likely to have a hospital accident admission than those form affluent areas, compared to an inequality ratio of 1.89 in 1991. 6. Infant mortality 5.3.9 Females – During 1991 to 1993, the female infant mortality rate per 100,000 births was 708 in deprived areas and 480 in affluent areas – by 1999 to 2001, the corresponding results were 556 and 351. These improvements are not significant. During 1999 to 2001, the female infant mortality rate in deprived areas was 1.58 times higher than in affluent areas, compared to an inequality ratio of 1.48 during 1991 to 1993. However, these inequality ratios are not significantly different from 1.0, which means that we can not be certain than the inequalities which exist for female infant mortalities are significant. 5.3.10 Males – have a higher rate of infant mortality than females for most years in both deprived and affluent areas. However these higher rates are not significantly different, so we can not be certain that any significant gender inequalities exist. During 1991 to 1993, the male infant mortality rate per 100,000 births was 1042 in deprived areas and 616 in affluent areas – by 1999 to 2001, the corresponding results were 784 and 427. These improvements are not significant. During 1999 to 2001, the male infant mortality rate in deprived areas was 1.84 higher than in affluent areas, compared to an inequality ratio of 1.69 during 1991 to 1993. Although this change is not significant, both of these inequality ratios are significantly different from 1.0, which means that we can be fairly certain that there are significant inequalities for male infant mortalities. Young People 7. Accidents: hospital admissions of children aged 10-14 years 5.3.11 Females - In 1991, the hospital accident admission rate per 100 females aged 10-14 was 1.04 in deprived areas and 0.88 in affluent areas – by 2001, the corresponding results were 0.79 and 0.51. These improvements are significant for both deprived and affluent areas and result in no significant change to the inequality ratio. In 2001, females aged 10-14 from deprived areas were 1.56 times more likely to have a hospital accident admission than those from affluent areas, compared to an inequality ratio of 1.18 in 1991. Although the 2001 inequality ratio was significantly different from 1.0, this was not the case for all the years since 1991. This means that the inequality for hospital admission rates for females aged 10-14 is not significant in all years.

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5.3.12 Males - aged 10-14 have a higher rate of hospital accident admissions than females. In 1991, the hospital accident admission rate per 100 males aged 10-14 was 2.64 in deprived areas and 1.70 in affluent areas – by 2001, the corresponding results were 1.84 and 1.15. These improvements are significant for both deprived and affluent areas and result in no significant change to the inequality ratio. In 2001, males aged 10-14 from deprived areas were 1.60 times more likely to have a hospital accident admission than those form affluent areas, compared to an inequality ratio of 1.56 in 1991. The inequality ratio for all years since 1991 was significantly different from 1.0, which means that we can be fairly certain that significant inequalities exist in male 10-14 hospital accident admissions.

8. Teenage Pregnancies aged 13-15 5.3.13 During 1991 to 1993, the teenage pregnancy rate per 1,000 girls aged 13 to 15 was 13.1 in deprived areas and 4.4 in affluent areas – by 2000 to 2002, the corresponding results were 12.6 and 4.2. These improvements are not significant. During 2000 to 2002, girls from deprived areas were 3.00 more times likely to fall pregnant than girls from affluent areas, compared to an inequality ratio of 2.94 during 1991 to 1993. 5.3.14 The trend for this indicator also shows that the pregnancy rate increased significantly during the mid 1990s before falling back down, although this increase was only significant for girls in deprived areas. 9. Teenage Pregnancies aged 13-19 5.3.15 During 1991 to 1993, the teenage pregnancy rate per 1,000 girls aged 13 to 19 was 75.5 in deprived areas and 23.4 in affluent areas – by 2000 to 2002, the corresponding results were 63.0 and 20.4. These improvements are significant for both deprived and affluent areas and result in no significant change to the inequality ratio. During 2000 to 2002, girls from deprived areas were 3.09 more times likely to fall pregnant than girls from affluent areas, compared to an inequality ratio of 3.23 during 1991 to 1993. 5.3.16 There was no significant increase in the pregnancy rate for this age group in the mid 1990s, as there was for younger girls aged 13-15. 10. Suicides among young people aged 10-24 5.3.17 Females – During 1991 to 1993, the suicide rate per 100,000 females aged 10-24 was 3.0 in deprived areas and 1.7 in affluent areas – by 1999 to 2001, the corresponding results were 4.4 and 1.1. These changes are not significant. During 1999 to 2001, females aged 10-14 from deprived areas were 3.87 times more likely to commit suicide than those from affluent areas, compared to an inequality ratio of 1.77 during 1991 to 1993. The inequality ratio from 1991 to 1993 is not significantly different from 1.0, whereas the 1999 to 2001 inequality ratio is significantly different from 1.0, but only just. Over the 10 year period the inequality ratio for this indicator has fluctuated between showing a significant difference and not between deprive and affluent areas. Given the wide confidence limits, caution is advised when interpreting results for this indicator. 5.3.18 Males – aged 10-24 have a higher rate of suicide than females for both deprived and affluent areas. During 1991 to 1993, the suicide rate per 100,000 males aged 10-24 was 18.2 in deprived areas and 10.9 in affluent areas – by 1999 to 2001, the corresponding results were 25.8 and 6.7. These changes are not significant. During 1999 to 2001, males aged 10-14 from deprived areas were 3.86 times more likely to commit suicide than those from affluent areas, compared to an inequality ratio of 1.67 during 1991 to 1993. Although this change in the

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inequality ratio is not significant, the higher ratios in more recent years differ significantly from 1.0, which means we can be more certain that significant inequalities exist for this indicator. Given the wide confidence limits, caution is advised when interpreting results for this indicator. Adults (aged 16-64) 11a. Consumption of fresh fruit (adults aged 16-64) 5.3.19 Females – In 1995, 60% of females in deprived areas did not consume fresh fruit once a day or more compared to 38% in affluent areas – by 1998, the corresponding results were 55% and 31%. The improvement in affluent areas is significant but not in deprived areas. These changes have resulted in an increase in the inequality ratio, but the increase is not significant. In 1998, females in deprived areas were 1.79 times less likely to consume fresh fruit once a day or more than those in affluent areas, compared to an inequality ratio of 1.57 in 1995. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 5.3.20 Males – have a lower rate of fresh fruit consumption once a day or more than females. In 1995, 69% of males in deprived areas did not consume fresh fruit once a day or more compared to 54% in affluent areas – by 1998, the corresponding results were 68% and 45%. There has been little change in deprived areas and a significant improvement in affluent areas. This has resulted in a significant increase in the inequality ratio. In 1998, males in deprived areas were 1.53 times less likely to consume fresh fruit once a day or more than those in affluent areas, compared to an inequality ratio of 1.28 in 1995. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 11b. Consumption of cooked green vegetables (adults aged 16-64) 5.3.21 Females - In 1995, 62% of females in deprived areas did not consume cooked green vegetables 5 times a week or more compared to 49% in affluent areas – by 1998, the corresponding results were 65% and 48%. These changes are not significant. In 1998, females in deprived areas were 1.36 times less likely to consume cooked green vegetables 5 times a week or more than those in affluent areas, compared to an inequality ratio of 1.27 in 1995. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 5.3.22 Males – have a lower rate of cooked green vegetable consumption 5 times a week or more than females. In 1995, 68% of males in deprived areas did not consume fresh fruit once a day or more compared to 51% in affluent areas – by 1998, the corresponding results were 75% and 54%. There has been little change in affluent areas and a significant reduction in cooked green vegetable consumption in deprived areas. However, this has not resulted in a significant increase in the inequality ratio. In 1998, males in deprived areas were 1.38 times less likely to consume cooked green vegetables 5 times a week or more than those in affluent areas, compared to an inequality ratio of 1.32 in 1995. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey.

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12. Smoking (adults aged 16-64) 5.3.23 Females – In 1999, 44% of females in deprived areas were smokers compared to 19% from affluent areas – by 2001, the corresponding results were 42% and 16%. These improvements are not significant. In 2001, females from deprived areas were 2.55 times more likely to be smokers than those from affluent areas, compared to an inequality ratio of 2.27 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 5.3.24 Males – The percentage of male smokers is similar to female smokers. In 1999, 48% of males in deprived areas were smokers compared to 21% from affluent areas – by 2001, the corresponding results were 39% and 21%. There was little change in affluent areas but the improvement in male smokers in deprived areas is significant. However, this has not resulted in a significant decrease in the inequality ratio. In 2001, males from deprived areas were 1.89 times more likely to be smokers than those from affluent areas, compared to an inequality ratio of 2.32 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 13a. Self-reported general health in people aged 16-44 5.3.25 Females – In 1999, 16% of females aged 16-44 from deprived areas reported their general health as not good/very good compared to 7% from affluent areas – by 2001, the corresponding results were 11% and 5%. The improvement in deprived areas is significant but not in affluent areas. This has resulted in a small but non significant decrease in the inequality ratio. In 2001, females aged 16-44 from deprived areas were 2.11 times more likely to report their general health as not good/very good than those from affluent areas, compared to an inequality ratio of 2.21 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 5.3.26 Males – aged 16-44 are less likely to report their general health as not good/very good than females. In 1999, 10% of males aged 16-44 from deprived areas reported their general health as not good/very good compared to 4% from affluent areas – by 2001, the corresponding results were 7% and 4%. There has been little change in affluent areas and the improvement in deprived areas is not significant. This has resulted in a decrease in the inequality ratio, which is not significant. In 2001, males aged 16-44 from deprived areas were 1.64 times more likely to report their general health as not good/very good than those from affluent areas, compared to an inequality ratio of 2.23 in 1999. Although this change in the inequality ratio is not significant, the 2001 ratio is only just significantly different from 1.0, which means that any further reduction would remove the certainty that inequalities exit for this indicator. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 13b. Self-reported general health in people aged 45-64 5.3.27 Females – In 1999, 28% of females aged 45-64 from deprived areas reported their general health as not good/very good compared to 13% from affluent areas – by 2001, the corresponding results were 25% and 11%. These improvements are not significant. In 2001, females aged 45-64 from deprived areas were 2.41 times more likely to report their general health as not good/very good than those from affluent areas, compared to an inequality ratio

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of 2.13 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 5.3.28 Males – a similar proportion of males aged 45-64 report their general health as not good/very good as females. In 1999, 31% of males aged 45-64 from deprived areas reported their general health as not good/very good compared to 10% from affluent areas – by 2001, the corresponding results were 26% and 9%. These improvements are not significant. In 2001, males aged 45-64 from deprived areas were 2.82 times more likely to report their general health as not good/very good than those from affluent areas, compared to an inequality ratio of 2.94 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 14. Self-reported long-standing illness (adults aged 16-64) 5.3.29 Females – In 1999, 27% of females from deprived areas reported they had a limiting longstanding illness or disability compared to 17% from affluent areas – by 2001, the corresponding results were 21% and 8%. These improvements in both deprived and affluent areas are significant. This has resulted in a significant increase in the inequality ratio, as the rate of improvement in affluent areas has been greater than in deprived areas. In 2001, females from deprived areas were 2.54 times more likely to report they had a limiting longstanding illness or disability than those from affluent areas, compared to an inequality ratio of 1.53 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 5.3.30 Males – A similar proportion of males report they have a limiting longstanding illness or disability as females. In 1999, 28% of males from deprived areas reported they had a limiting longstanding illness or disability compared to 13% from affluent areas – by 2001, the corresponding results were 21% and 9%. These improvements in both deprived and affluent areas are significant. However, this has not resulted in a significant change in the inequality ratio. In 2001, males from deprived areas were 2.28 times more likely to report they had a limiting longstanding illness or disability than those from affluent areas, compared to an inequality ratio of 2.05 in 1999. It should be noted that information for this indicator is only available for a recent 3 year period. An update on trends will be available from the annual Scottish Household Survey. 15. Obesity (adults aged 16-64) 5.3.31 Females - In 1995, 21% of females in deprived areas were obese compared to 15% in affluent areas – by 1998, the corresponding results were 25% and 15%. These changes are not significant. In 1998, females in deprived areas were 1.70 times more likely to be obese than those in affluent areas, compared to an inequality ratio of 1.40 in 1995. This increase in the inequality ratio is not significant. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 5.3.32 Males – have a similar rate of obesity as females. In 1995, 19% of males in deprived areas were obese compared to 14% in affluent areas – by 1998, the corresponding results were 23% and 19%. These changes are not significant. In 1998, males in deprived areas were 1.23 times more likely to be obese than those in affluent areas, compared to an inequality

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ratio of 1.36 in 1995. This decrease in the inequality ratio is not significant. However, the 1998 ratio is not significantly different from 1.0, which means that we can not be certain that any significant inequalities exist in male obesity. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 16. Mental Health (GHQ12 scores) (adults aged 16-64) 5.3.33 Females - In 1995, 25% of females in deprived areas had a GHQ12 score of 4 or more, denoting poor mental health, compared to 18% in affluent areas – by 1998, the corresponding results were 25% and 18%. There has been no change. In 1998, females in deprived areas were 1.37 times more likely to suffer from poor mental health than those in affluent areas, which has remained unchanged since 1995. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 5.3.34 Males – are less likely than females to suffer from poor mental health. In 1995, 19% of males in deprived areas had a GHQ12 score of 4 or more, denoting poor mental health, compared to 11% in affluent areas – by 1998, the corresponding results were 16% and 11%. There has been no change in affluent areas and the improvement in deprived areas is not significant. In 1998, males in deprived areas were 1.44 times more likely to suffer from poor mental health than those in affluent areas, compared to the inequality ratio of 1.69 in 1995. This decrease in the inequality ratio is not significant. It should be noted that the latest information available for this indicator is now 5 years old. An update on trends will be available from the 2003 Scottish Health Survey. 17. All cause mortality rate among people under 75 5.3.35 Females – In 1991, the all cause mortality rate per 100,000 females aged under 75 in deprived areas was 530, compared to 308 in affluent areas – by 2001, the corresponding results were 452 and 245. These improvements in both deprived and affluent areas are significant. This has resulted in an increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas, however this increase is not significant. In 2001, the all cause mortality rate for females aged under 75 in deprived areas was 1.84 times higher than in affluent areas, compared to an inequality ratio of 1.72 in 1991. 5.3.36 Males – aged under 75 have a much higher all cause mortality rate than females in both affluent and deprived areas. In 1991, the all cause mortality rate per 100,000 males aged under 75 in deprived areas was 918, compared to 526 in affluent areas – by 2001, the corresponding results were 844 and 376. These improvements in both deprived and affluent areas are significant. This has resulted in a significant increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas. In 2001, the all cause mortality rate for males aged under 75 in deprived areas was 2.25 times higher than in affluent areas, compared to an inequality ratio of 1.75 in 1991. 18. Coronary heart disease mortality rate among people under 75 5.3.37 Females – In 1991, the coronary heart disease mortality rate per 100,000 females aged under 75 in deprived areas was 128, compared to 57 in affluent areas – by 2001, the corresponding results were 71 and 24. These improvements in both deprived and affluent areas are significant. This has resulted in an increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas, however this increase

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is not quite significant. In 2001, the coronary heart disease mortality rate for females aged under 75 in deprived areas was 2.95 times higher than in affluent areas, compared to an inequality ratio of 2.23 in 1991. 5.3.38 Males – aged under 75 have a much higher coronary heart disease mortality rate than females in both affluent and deprived areas. In 1991, the coronary heart disease mortality rate per 100,000 males aged under 75 in deprived areas was 296, compared to 161 in affluent areas – by 2001, the corresponding results were 186 and 80. These improvements in both deprived and affluent areas are significant. This has resulted in a significant increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas. In 2001, the coronary heart disease mortality rate for males aged under 75 in deprived areas was 2.34 times higher than in affluent areas, compared to an inequality ratio of 1.83 in 1991. 19. Cancer mortality rate among people under 75 5.3.39 Females – In 1991, the cancer mortality rate per 100,000 females aged under 75 in deprived areas was 175, compared to 129 in affluent areas – by 2001, the corresponding results were 159 and 114. There have been improvements in both deprived and affluent areas, although these changes are not quite significant. This has resulted in an increase in the inequality ratio, however this increase is not significant. In 2001, the cancer mortality rate for females aged under 75 in deprived areas was 1.40 times higher than in affluent areas, compared to an inequality ratio of 1.35 in 1991. 5.3.40 Males – aged under 75 have a much higher cancer mortality rate than females in deprived areas and a slightly higher rate in affluent areas. In 1991, the cancer mortality rate per 100,000 males aged under 75 in deprived areas was 271, compared to 162 in affluent areas – by 2001, the corresponding results were 231 and 135. These improvements in both deprived and affluent areas are significant. This has resulted in a slight increase in the inequality ratio, which is not significant. In 2001, the cancer mortality rate for males aged under 75 in deprived areas was 1.71 times higher than in affluent areas, compared to an inequality ratio of 1.68 in 1991. 20. Life Expectancy (at birth) 5.3.41 Females – During 1991 to 1993, the life expectancy of females in deprived areas was 74.8 years, compared to 79.2 years in affluent areas – by 2000 to 2002, the corresponding results were 76.3 and 80.9. These improvements are significant for both deprived and affluent areas. As the relative rate of improvement was the same in deprived and affluent areas, there has been no change in the inequality ratio. During 2000 to 2002, the life expectancy for females in affluent areas was 1.06 times higher than in deprived areas, the same as during 1991 to 1993. Note that although this inequality ratio of 1.06 may appear small, it corresponds to females in deprived areas having a life expectancy 6% lower than in affluent areas, which corresponds to 4.5 years of life. 5.3.42 Males – have a lower life expectancy than females in both deprived and affluent areas. During 1991 to 1993, the life expectancy of males in deprived areas was 68.3 years, compared to 74.6 years in affluent areas – by 2000 to 2002, the corresponding results were 69.1 and 77.0. These improvements are significant for both deprived and affluent areas. As the relative rate of improvement was higher in affluent areas there has been an increase in the inequality ratio. During 2000 to 2002, the life expectancy for males in affluent areas was 1.12 times higher than in deprived areas, compared to an inequality ratio of 1.09 during 1991

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to 1993. Note that although this inequality ratio of 1.12 may appear small, it corresponds to males in deprived areas having a life expectancy 12% lower than in affluent areas, which corresponds to 8 years of life. Older People (aged 75 and over) 21. All cause mortality rate among people aged 75 and over. 5.3.43 Females – In 1991, the all cause mortality rate per 100,000 females aged 75 and over in deprived areas was 9246, compared to 8466 in affluent areas – by 2001, the corresponding results were 8605 and 7734. These improvements in both deprived and affluent areas are significant, although these results should be treated with caution as the rates have fluctuated over this period. This has resulted in an increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas, however this increase is not significant. In 2001, the all cause mortality rate for females aged 75 and over in deprived areas was 1.11 times higher than in affluent areas, compared to an inequality ratio of 1.09 in 1991. Note also that the inequality ratio is only just significantly different from 1.0, which means that inequalities in all cause mortality for females aged 75 and over is only just significant. 5.3.44 Males – aged 75 and over have a higher all cause mortality than females in both deprived and affluent areas. In 1991, the all cause mortality rate per 100,000 males aged 75 and over in deprived areas was 13713, compared to 11611 in affluent areas – by 2001, the corresponding results were 11878 and 10189. These improvements in both deprived and affluent areas are significant, although these results should be treated with caution as the rates have fluctuated over this period. This has resulted in little change to the inequality ratio as the relative rate of improvement in affluent areas was similar to that in deprived areas. In 2001, the all cause mortality rate for males aged 75 and over in deprived areas was 1.17 times higher than in affluent areas, compared to an inequality ratio of 1.18 in 1991. Note that the inequality ratio for males is higher than for females. 22. Mortality rates from coronary heart disease among people 75 and over 5.3.45 Females – In 1991, the coronary heart disease mortality rate per 100,000 females aged 75 and over in deprived areas was 2365, compared to 2028 in affluent areas – by 2001, the corresponding results were 1774 and 1449. These improvements in both deprived and affluent areas are significant. This has resulted in an increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas, however this increase is not significant. In 2001, the coronary heart disease mortality rate for females aged 75 and over in deprived areas was 1.22 times higher than in affluent areas, compared to an inequality ratio of 1.17 in 1991. 5.3.46 Males – aged 75 and over have a higher coronary heart disease mortality rate than females in both affluent and deprived areas. In 1991, the coronary heart disease mortality rate per 100,000 males aged 75 and over in deprived areas was 3391, compared to 3259 in affluent areas – by 2001, the corresponding results were 2841 and 2291. These improvements in both deprived and affluent areas are significant. This has resulted in an increase in the inequality ratio as the relative rate of improvement in affluent areas has been better than in deprived areas, although this increase is not significant. In 2001, the coronary heart disease mortality rate for males aged 75 and over in deprived areas was 1.24 times higher than in affluent areas, compared to an inequality ratio of 1.04 in 1991. Note that the 1991 inequality ratio is not significantly different to 1.0, which means that there were no significant

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inequalities in coronary heart disease mortality rates for males aged 75 and over in that year. Since 1991, not all years show significant inequalities, so these results should be treated with some caution. 23. Mortality rates from cancer among people 75 and over 5.3.47 Females – In 1991, the cancer mortality rate per 100,000 females aged 75 and over in deprived areas was 1580, compared to 1262 in affluent areas – by 2001, the corresponding results were 1733 and 1409. These increases in mortality rates are not significant. This has resulted in little change to inequality ratio, as the relative rate of increase in mortality rates was similar in deprived and affluent areas. In 2001, the cancer mortality rate for females aged 75 and over in deprived areas was 1.23 times higher than in affluent areas, compared to an inequality ratio of 1.25 in 1991. 5.3.48 Males – aged 75 and over have a much higher cancer mortality rate than females in both deprived and affluent areas. In 1991, the cancer mortality rate per 100,000 males aged 75 and over in deprived areas was 2929, compared to 2349 in affluent areas – by 2001, the corresponding results were 2939 and 2416. These increases in mortality rates are not significant. This has resulted in a slight decrease in the inequality ratio, which is not significant. In 2001, the cancer mortality rate for males aged 75 and over in deprived areas was 1.22 times higher than in affluent areas, compared to an inequality ratio of 1.25 in 1991.

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6 TARGETS FOR REDUCING HEALTH INEQUALITIES 6.1 The Group has considered whether there would be advantages in setting explicit targets for reducing inequalities in health between affluent and deprived areas. 6.2 The Department of Health in England has adopted two targets for reducing health inequalities.

1. Infant Mortality - starting with children under one year, by 2010 to reduce by at least 10% the gap in mortality between manual groups and the population as a whole;

2. Life Expectancy - Starting with Health Authorities to reduce by at least 10% the

gap between the quintile of areas with the lowest life expectancy at birth and the population as a whole.

The Department of Health has emphasised that progress towards these targets will not be assessed simply in terms of the targets as formulated. A basket of indicators is being developed to ensure that all key aspects of the inequality agenda are kept under review. 6.3 The Working Group has considered whether it would be appropriate to set explicit targets for reducing inequalities in health in Scotland. It was felt that there are two advantages in adopting explicit targets.

• First, explicit targets would serve to raise the profile of health inequalities - in the same way that adopting explicit targets for reducing mortality rates from coronary heart disease and cancer has raised the profile of these health issues.

• Second, explicit targets also provides measurable goals to influence management

and to provide clear objectives against which progress can be assessed. 6.4 These are important arguments in favour of explicit target setting. However, the Group felt that there were a number of difficulties in setting targets in this area.

• First, it is not clear which indicators should be used as the basis for target setting. For example, selecting an indicator such as breastfeeding or coronary heart disease mortality might encourage effort to be focused on reducing inequalities in these areas. But as is clear from the analysis in this report there are many other areas of health where there are significant inequalities, and there is no obvious basis on which to select one or two areas for target setting.

• Second, setting explicit targets for a small number of health areas might distort

priorities by encouraging NHS Boards to focus on those areas at the expense of other areas where there are significant health inequalities.

• Third, the choice of a particular target reduction and timescale for achieving this

reduction would be quite arbitrary. Many of the indicators do not show trends that would point clearly to any likely future trend in inequalities.

6.5 The Group concluded that there was no clear evidence-base on which to recommend specific targets.

29

7 FUTURE WORK 7.1 The work of this Group has largely focused on developing a set of indicators that can be applied at national level to monitor progress in tackling health inequalities that are linked to socio-economic circumstances, and identifying a small set of indicators that can be used in the Performance Assessment Framework to monitor trends at NHS Board level. 7.2 Concerns have also been raised about other aspects of inequalities in health including: (a) inequalities between urban and rural areas; (b) inequalities in health among ethnic minorities; (c) inequalities by gender; (d) inequalities by age; (e) inequalities in access to and use of services; (f) inequalities in clinical outcomes. This report has not addressed these areas of potential inequality, but the Group is conscious of the concerns that exist about inequalities in these areas, and considers that further work should be done to examine the scope for identifying relevant measures of inequalities. 7.3 The work of this group has also focused on developing socio-economic indictors of inequality based on existing information rather than indicators that would require the collection of new information. It is clear that existing information sources have a number of limitations. Social Class measures of inequalities in health have serious limitations. While the Carstairs area-based measures has advantages over Social Class, it is clear that the Carstairs measure also has significant limitations. The Group considers that further consideration should now be given to developing alternative measures of socio-economic circumstances that would provide a more effective basis for monitoring trends in health inequalities in future. 7.4. Consideration should also be given to ensuring that a more comprehensive range of indicators is available for different population groups. It has proved especially difficult to identify appropriate indicators of inequalities in health in younger people and in older people. It is important that a wider range of indicators is developed to cover these age groups, though this may require the collection of new information.

**********

30

ANNEX A – APPENDIX 1

Appendix 1 : MEMBERSHIP OF WORKING GROUP Chairman Alasdair Munro Head of Analytical Services Division Scottish Executive Health Department Members Dr Sally Macintyre Director of MRC Social and Public Health Sciences Unit University of Glasgow Matthew Sutton Senior Research Fellow University of Glasgow Dr Gordon McLaren Consultant in Public Health Medicine Fife Health Board Dr Marion Bain Consultant in Public Health Medicine Information and Statistics Division of the Common Services Agency Paul Boyle Medical Geographer St Andrew's University Paul Allen Health Improvement Strategy Division Scottish Executive Health Department Dr Peter Craig Research Manager Chief Scientist Office Scottish Executive Health Department Robin Haynes Economic Adviser Office of the Chief Economic Adviser Finance and Central Services Department Fiona Montgomery Social Inclusion Division Scottish Executive Development Department

31


Scottish Executive Health Department Analytical Team Laura Beahan Statistician Jack Vize Senior Assistant Statistician David Notman Economic Adviser Andrew Walker Economist

32


Appendix 2: Potential Indicators of Health Inequalities Population Group Indicator of Inequalities Reason for consideration Children 1. Smoking during pregnancy

2. Breastfeeding 3. Dental health of children 4. Low birthweight babies 5. Accidents in children aged 0-9 (emergency hospital admissions) 6. Infant mortality 7. Mortality from accidents

Reducing the proportion of women smoking during pregnancy is a headline target in Towards a Healthier Scotland and a milestone in Social Justice Increasing the proportion of women breastfeeding is one of the Social Justice milestones Improving the dental health of children is one of the headline targets in Towards a Healthier Scotland and a milestone in Social Justice Reducing the percentage of low birth-weight babies is a Social Justice milestone. This is not a health target or Social Justice milestone. However, it is known that there are significant inequalities in accident rates in young children. This is not a health target or Social Justice milestone. However, there are significant inequalities between socio-economic groups and it may provide a useful indicator of progress in tackling inequalities generally. This is not a health target or Social Justice milestone. However, differences in mortality rates from accidents may provide a useful indicator.

Young People 8. Accidents in children aged 10-14 (emergency hospital admissions)

This is not a health target or Social Justice milestone. However, there are significant inequalities in admissions for accidents between older children from different socio-economic groups.

33


9. Teenage pregnancies (females aged 13-15) 10. Teenage pregnancies (females aged 13-19) 11. Suicides among young people aged 10-24

This is a headline target in Towards a Healthier Scotland and a Social Justice milestone. This is not a health target or Social Justice milestone. Although public health concern focuses on 13-15 year olds, there is still concern for those aged 13-19. It provides a broad indicator of health inequalities between different socio-economic groups for all teenage females This is a Social Justice milestone. The Group considered that it may provide a useful indicator of mental health in young people.

Adults 12. Diet - consumption of fresh fruit 13. Diet - consumption of green vegetables ------------------------------------------ 14. Adult smoking 15. Excess alcohol consumption ------------------------------------------ 16. Self-reported general health 17. Self-reported long-standing illness ------------------------------------------

Improvements in diet is one of the Second Rank targets in Towards a Healthier Scotland and a milestone in Social Justice. Consumption of fresh fruit and green vegetables are an important aspect of people’s diet. --------------------------------------------------------------------------------------- This is a second rank target in Towards a Healthier Scotland and a Social Justice milestone. Smoking is a key influence on health and is know to be a major influence on health inequalities. This is a second rank target in Towards a Healthier Scotland and a Social Justice milestone. -------------------------------------------------------------------------------------- These are not a health targets or Social Justice milestones. However, information on self-reported general health and self-reported long-standing illness is collected in the Scottish Health Survey and may provide a general measure of the relative health of different socio-economic groups. ---------------------------------------------------------------------------------------

34


18. Obesity 19. Mental health (GHQ12 scores) 20. All cause mortality rate among people under 75 ------------------------------------------ 21. Mortality rates from coronary heart disease among people under 75 22. Mortality rates from cancer among people under 75 ------------------------------------------ 23. Mortality rates from stroke among people under 75

This is not a health target or Social Justice milestone. However, the obesity rates in the population has been increasing and is seen as an increasingly important health issue. It may, therefore, provide a useful indicator of health inequalities. This is not a health target or Social Justice milestone. However, it is important to monitor trends in inequalities in mental as well as physical health. The Scottish Health Survey collects information on GHQ12 scores and this may provide a useful measure of socio-economic inequalities in mental health. This is not a health target or Social Justice milestone. However, differences in mortality rates from all causes among people under 75 may provide a useful indicator of overall inequalities in health. --------------------------------------------------------------------------------------- Reducing mortality rates from coronary heart disease and cancer among people under 75 are both headline health targets in Towards a Healthier Scotland. There are known to be wide socio-economic inequalities in mortality rates from these diseases they should be key indicators of progress in reducing health inequalities. Mortality from coronary heart disease (for people aged 16-64) is also a Social Justice milestone. --------------------------------------------------------------------------------------- This is a second rank target in Towards a Healthier Scotland.

35


24. Life expectancy 25. Admissions to hospital for drugs misuse

This is not a health target or Social Justice milestone. However, it provides a broad indicator of health inequalities between different socio-economic groups This is not a health target or Social Justice milestone, although Social Justice does include incidence of drug misuse in general. Admissions to hospital may provide a useful measure of health inequalities between different socio-economic groups.

Older People 26. Exercise in older people 27. Chronic respiratory disease ------------------------------------------ 28. All cause mortality rate among people over 75. 29. Mortality rates from coronary heart disease among people 75 and over. 30. Mortality rates from cancer among people 75 and over.

This is a Social Justice milestone. Exercise is seen as an important aspect of healthy lifestyle in all age groups. This is a Social Justice milestone. --------------------------------------------------------------------------------------- These are not health targets or Social Justice milestones. However, it is important to monitor inequalities in health among older people, and the all cause mortality rate along with mortality rates from coronary heart disease and cancer may provide useful indicators of inequalities in this age group.

36


Appendix 3 : Proposed Indicators of Health Inequalities – Definition and Data Sources Indicator Age

Group Age Standardisation

Source Definition

CHILDREN

1 2 3 4 5

Smoking during pregnancy Breastfeeding Dental health of children Low birthweight babies Accidents in children aged 0-9 (hospital admissions)

- - 5 year olds - 0-9 year olds

Not age standardised (e.g. by age of mother) Not age standardised (e.g. by age of mother) N/A Not age standardised (e.g. by age of mother) Not age standardised

ISD Scotland SMR02 ISD Scotland Child Health Surveillance Programme Dental Health Services Research Unit, Dundee ISD Scotland SMR02 ISD Scotland SMR01

The percentage of mothers at their first ante-natal visit to hospital who self-reported smoking. Home births & births at non-NHS hospitals are excluded. The percentage of women not breastfeeding as self-reported at the 6-8 week review. Currently 10 out of the 15 Health Boards provide information. The percentage of 5 year olds who have dental caries. This information is available from a survey every 2 years. Due to problems with the data collection in 2001-02, it is likely that there will be a gap in the data series. The percentage of births that are low weight (less than 2,500 grams). To smooth the annual fluctuations, a three year rolling average is shown. Home births are excluded, as are multiple births and preterm babies (36 or less weeks gestation) The number of admissions to hospital as emergencies per 100,000 population aged 0-9 years.

37


6

Infant mortality

less than 1 year old

Not age standardised

GRO(S)

Rate of mortality aged less than one per 100,000 births. Due to small numbers, a 3 year average is shown.

YOUNG PEOPLE

7 8 9 10

Accidents in children aged 10-14 (hospital admissions) Teenage pregnancies (females aged 13-15) Teenage pregnancies (females aged 13-19) Suicides among young people aged 10-24

10-14 years 13-15 years 13-19 years 10-24 years

Not age standardised Not age standardised Not age standardised Not age standardised

ISD Scotland SMR01 ISD Scotland SMR01 & SMR02 ISD Scotland SMR01 & SMR02 GROS

The number of admissions to hospital as emergencies per 100,000 population aged 10-14 years. The number of pregnancies amongst 13 to 15 year olds (at time of conception) per 1,000 population aged 13 to 15. Due to the small numbers, 3 year rolling averages are shown The number of pregnancies amongst 13 to 19 year olds (at time of conception) per 1,000 population aged 13 to 19. Three year rolling averages are shown. The number of suicides of 10 to 24 year olds per 100,000 population aged 10 to 24 years. Due to the small numbers, 3 year rolling averages are shown.

ADULTS

11a 11b

Diet - consumption of fresh fruit Diet - consumption of green vegetables

16-64 years 16-64 years

See note 1

See note 1

Scottish Health Survey 1995 & 1998 Scottish Health Survey 1995 & 1998

The percentage of 16-64 year olds who do not eat fresh fruit once a day or more.

The percentage of 16-64 year olds who do not eat green vegetables once a day or more.

38


12 13 14 15 16 17 18 19

Adult smoking Self –reported general health Self-reported long-standing illness Obesity Mental health (GHQ12 scores) All cause mortality rate among people under 75 Mortality rates from coronary heart disease among people under 75 Cancer mortality rate per 100,000

16-64 years 16-44 & 45-64 16-64 years 16-64 years 16-64 years 0-74 years 0-74 years 0-74 years

Not standardised. See note 2

See note 1 See note 1

See note 1

See note 1

Standardised to the European population Standardised to the European population Standardised to the European population

Scottish Household Survey Scottish Health Survey 1995 & 1998 Scottish Health Survey 1995 & 1998 Scottish Health Survey 1995 & 1998 Scottish Health Survey 1995 & 1998 GRO(S) GRO(S) GRO(S)

The percentage of 16 to 64 year olds who are current cigarette smokers. The percentage of 16-44 and 45-64 year olds whose self reported general health is not good or not very good. The percentage of 16-64 year olds who reported a longstanding illness. The percentage of 16 to 64 year olds who are obese (BMI greater than 30 kg/m2). The percentage of 16 to 64 year olds with a GHQ12 score of 4 or more. The age/sex standardised rate for all causes of death, persons aged less than 75 years. The age/sex standardised rate for coronary heart disease, persons aged less than 75. The age/sex standardised rate for cancer, persons aged less than 75.

39


20 Life expectancy

At birth SEHD/ASD Currently available for 1980-82 and 1990-92 through to 1999-2001.

OLDER PEOPLE

21 22 23

All cause mortality rate among people over 75 Mortality rates from coronary heart disease among people 75 and over Mortality rates from cancer among people over 75

75+ years 75+ years 75+ years

Standardised to the European population Standardised to the European population Standardised to the European population

GRO(S) GRO(S) GRO(S)

The age/sex standardised rate for all causes of death, persons aged 75 or more years. The age/sex standardised rate for coronary heart disease, persons aged 75 or more years. The age/sex standardised rate for cancer, persons aged 75 or more years.

Notes: 1. The Scottish Health Survey data has been weighted to represent the age and sex distribution within Scotland in mid-1995 and 1998. 2. The Scottish Household Survey data has been weighted for geographical factors and also household size.

40

ANNEX B – APPENDIX 1

Appendix 1 : Concentration Index 1. This method has been used to measure inequalities in the distribution of income. Figure 3 illustrates how this method can be used to measure inequalities in health. Figure 3: Measurement of Health Inequalities Cumulative proportion of ill health A 60% B 25% 25% Cumulative proportion of population ranked by socio-economic status 2. The horizontal axis measures the population ranked by socio-economic status beginning with the most deprived. The vertical axis measures the proportion of ill health accounted for by the relevant population. If ill health was uniformly distributed in the population then any given proportion of the population would account for the same proportion of ill health - for example, 25% of the population would account for 25% of ill health. This would be the position shown by the diagonal line B. 3. If, however, health is distributed unequally and is concentrated disproportionately among the most deprived, then the relationship will be close to that shown by the curved line A. In this illustrative example, the most deprived 25% of the population account for 60% of ill health. The further the line A is above the diagonal, the greater the degree of inequality in health. The degree of inequality can be measured statistically by the size of the area between the line A and the diagonal B relative to half the area of the square. This ratio must take a

41

ANNEX B – APPENDIX 1

value between 0 and 1. A value of zero implies complete equality; a value of +1 implies that poor health is concentrated entirely in the most deprived population. 4. The advantage of the concentration index is that estimates of the value of this index over time will take in account changes at any point in the distribution of health. For example, any improvement in the relative health of the population living in Quintile 4 would be reflected in the index, as well as any improvement in Quintile 5.

**********

42

ANNEX C APPENDIX 1

Appendix 1: Ratios in Health Inequalities Between Carstairs Quintile 5 (Most Deprived) and Quintile 1 (Most Affluent)

Indicator 1981 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002Children 1. Percentage of mothers smoking

during pregnancy 3.52 2.95 2.92 2.94 2.83 2.86 2.80 2.65 2.63 2.58

2. Percentage of mother not breastfeeding at 6-8 weeks

1.65 1.77 1.73 1.84 1.77 1.75 1.72 1.71

3. Percentage of 5 year olds with dental caries

M F

1.711.83

1.721.57

1.921.79

1.781.83

4. Percentage of low birthweight babies*

M F

2.002.17

2.10 2.49

2.21 2.49

2.25 2.31

2.26 2.11

2.27 2.24

2.32 2.39

2.26 2.50

2.33 2.41

2.31 2.30

5. Admissions to hospital for accidents in children (aged 0-9)

M F

1.891.46

1.71 1.60

1.80 1.68

1.59 1.54

1.61 1.50

1.55 1.61

1.75 1.52

1.65 1.30

1.47 1.43

1.72 1.40

1.74 1.55

6. Infant mortality* M F

1.691.48

1.65 1.58

1.67 1.71

2.03 1.52

2.07 1.68

2.05 1.66

1.60 1.67

1.95 1.70

1.84 1.58

Young People 7. Admissions to hospital for

accidents (children aged 10-14) M F

1.561.18

1.44 1.16

1.51 1.31

1.75 1.43

1.64 1.67

1.48 1.43

1.61 1.43

1.57 1.28

1.53 1.27

1.49 1.23

1.60 1.56

8. Teenage pregnancies (females aged 13-15)*

2.94 2.89 3.28 3.52 3.55 3.22 3.28 3.25 3.23 3.00

9. Teenage pregnancies (females aged 13-19)*

3.23 3.20 3.20 3.24 3.31 3.13 3.06 2.99 3.01 3.09

10. Suicides among young people (aged 10-24)*

M F

1.671.77

1.89 2.82

1.30 4.66

1.40 5.22

1.67 3.44

2.30 3.97

2.99 5.90

3.45 5.04

3.86 3.87

Adults 11a. Diet - percentage of population

who do not eat fresh fruit once a day or more

M F

1.281.57

1.531.79

11b. Diet - percentage of population who not eat green vegetables once a day or more

M F

1.321.27

1.381.36

12. Adult smoking

M F

2.32 2.27

1.86 1.92

1.89 2.55

43

ANNEX C APPENDIX 1

Indicator 1981 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002Adults ...ctd 13a. Self-reported general health (‘not

good or very good’) in people aged 16-44

M F

2.23 2.21

3.13 1.80

1.64 2.11

13b. Self-reported general health (‘not good or very good’) in people aged 45-64

M F

2.94 2.13

5.60 2.51

2.82 2.41

14. Self-reported limiting long-standing illness

M F

2.05 1.53

2.46 1.79

2.28 2.54

15. Obesity

M F

1.361.40

1.231.70

16. Mental health (GHQ12 scores)

M F

1.691.38

1.441.37

17. All cause mortality rate among people under 75

M F

1.751.72

1.85 1.70

1.91 1.83

1.93 1.73

2.00 1.81

2.10 1.88

2.09 1.88

2.17 1.97

2.13 1.91

2.14 1.90

2.25 1.84

18. Mortality rates from coronary heart disease among people under 75

M F

1.832.23

1.80 2.14

1.99 2.21

1.91 2.00

2.15 2.07

2.09 2.19

2.17 2.39

2.28 2.37

2.18 2.73

2.08 2.52

2.34 2.95

19. Mortality rates from cancer among people under 75

M F

1.681.35

1.77 1.38

1.73 1.39

1.70 1.46

1.66 1.54

1.78 1.39

1.71 1.52

1.73 1.56

1.71 1.43

1.62 1.48

1.71 1.40

20. Life expectancy at birth M F

Older People 21. All cause mortality among people

over 75 M F

1.181.09

1.18 1.06

1.15 1.11

1.22 1.08

1.18 1.06

1.16 1.08

1.18 1.06

1.22 1.17

1.29 1.10

1.21 1.15

1.17 1.11

22. Mortality rates from coronary heart disease among people over 75

M F

1.041.17

1.16 1.08

1.04 1.31

1.15 1.23

1.12 1.16

1.21 1.27

1.19 1.31

1.17 1.35

1.30 1.25

1.17 1.19

1.24 1.22

23. Mortality rates from cancer among people over 75

M F

1.251.25

1.28 1.16

1.29 1.16

1.46 1.24

1.45 1.27

1.16 1.29

1.32 1.13

1.21 1.18

1.29 1.10

1.33 1.38

1.22 1.23

* 3-year average centred on the year shown.

44

ANNEX C APPENDIX 2

APPENDIX 2: SCOTLAND CHARTS 1. Percentage of mothers smoking during pregnancy

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002Most affluent quintile 11.87 14.29 14.61 14.66 15.14 14.37 14.28 14.42 14.39 14.43Most deprived quintile 41.76 42.23 42.67 43.07 42.90 41.16 39.95 38.20 37.86 37.18Ratio 3.52 2.95 2.92 2.94 2.83 2.86 2.80 2.65 2.63 2.58

Percentage smoking during pregnancy

05

101520253035404550

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Year

Perc

enta

ge

Most affluent quintile Most deprived quintile

Percentage smoking during pregnancy Ratio: most deprived to most affluent

0

1

2

3

4

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

Year

Rat

io

45

ANNEX C APPENDIX 2

2. Percentage of mothers not breastfeeding at 6-8 weeks 1995 1996 1997 1998 1999 2000 2001 2002

Most affluent quintile 51.38 46.55 46.54 43.91 44.63 44.58 45.27 44.31Most deprived quintile 84.66 82.55 80.67 80.59 79.20 78.17 77.85 75.99Ratio 1.65 1.77 1.73 1.84 1.77 1.75 1.72 1.71

Percentage of mothers not breastfeeding at 6-8 weeks

0102030405060708090

1995

1996

1997

1998

1999

2000

2001

2002

Year

Perc

enta

ge


Percentage of mothers not breastfeeding at 6-8 weeks

Ratio: most deprived to most affluent

1

2

3

4

1995

1996

1997

1998

1999

2000

2001

2002

Year

Rat

io

46

ANNEX C APPENDIX 2

3. Percentage of 5 year olds with dental caries - Females

1993 1995 1997 1999Most affluent quintile 40.73 46.45 40.03 39.22Most deprived quintile 74.53 72.96 71.73 71.74Ratio 1.83 1.57 1.79 1.83

Percentage of 5 year olds with dental caries : Females

0

10

20

30

40

50

60

70

80

90

1993 1995 1997 1999Year

Perc

enta

ge


Percentage of 5 year olds with dental caries Ratio: most deprived to most affluent : Females

1

2

3

4

1993 1995 1997 1999

Year

Rat

io

47

ANNEX C APPENDIX 2

3. Percentage of 5 year olds with dental caries - Males

1993 1995 1997 1999Most affluent quintile 45.33 42.93 38.49 40.72Most deprived quintile 77.66 73.81 73.80 72.56Ratio 1.71 1.72 1.92 1.78

Percentage of 5 year olds with dental caries : Males

0

10

20

30

40

50

60

70

80

90

1993 1995 1997 1999Years

Perc

enta

ge


Percentage of 5 year olds with dental caries Ratio: most deprived to most affluent : Males

1

2

3

4

1993 1995 1997 1999Year

Rat

io

48

ANNEX C APPENDIX 2

4. Percentage of low birthweight babies (3 year average) – Females

1991-93 1992-94 1993-95 1994-96 1995-97 1996-98 1997-99 1998-00 1999-01 2000-02Most affluent quintile 2.01 1.78 1.71 1.85 1.96 1.84 1.76 1.74 1.79 1.80Most deprived quintile 4.36 4.43 4.26 4.29 4.14 4.12 4.19 4.34 4.32 4.15Ratio 2.17 2.49 2.49 2.31 2.11 2.24 2.39 2.50 2.41 2.30

Percentage of low birthweight babies - Females

1

2

3

4

5

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Perc

enta

ge


Percentage of low birthweight babiesRatio: most deprived to most affluent : Females

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

io

49

ANNEX C APPENDIX 2

4. Percentage of low birthweight babies (3 year average) – Males


Percentage of low birthweight babies - Males

0

1

2

3

4

5

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Perc

enta

ge


Percentage of low birthweight babies Ratio: most deprived to most affluent : Males

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

io

50

ANNEX C APPENDIX 2

5. Accidents in children hospital admissions rate per 100 population aged 0 to 9 years - Females

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001Most affluent quintile 1.01 0.98 0.93 0.99 0.98 0.99 0.89 0.88 0.88 0.88 0.75Most deprived quintile 1.48 1.56 1.56 1.52 1.47 1.60 1.35 1.15 1.26 1.22 1.17Ratio 1.46 1.60 1.68 1.54 1.50 1.61 1.52 1.30 1.43 1.40 1.55

Accidents in children hospital admissions rate per 100 population aged 0 to 9 years : Females

0.0

0.5

1.0

1.5

2.0

2.5

3.0

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

e pe

r 10

0


Accidents in children hospital admission rate per 100 population aged 0 to 9 years

Ratio: most deprived to most affluent : Females

1

2

3

4

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

io

51

ANNEX C APPENDIX 2

5. Accidents in children hospital admission rate per 100 population aged 0 to 9 years - Males


Accidents in children hospital admission rate per 100 population aged 0 to 9 years : Males

0.0

0.5

1.0

1.5

2.0

2.5

3.0

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

e pe

r 10

0



Ratio: most deprived to most affluent : Males

1

2

3

4

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

io

52

ANNEX C APPENDIX 2

6. Infant mortality – rate per 100,000 births - Females

1991-93 1992-94 1993-95 1994-96 1995-97 1996-98 1997-99 1998-00 1999-01Most affluent quintile 479.59 450.99 447.47 507.39 442.19 395.88 336.00 327.65 351.00Most deprived quintile 707.86 713.04 764.80 771.71 741.01 658.76 560.71 555.46 555.65Ratio 1.48 1.58 1.71 1.52 1.68 1.66 1.67 1.70 1.58

Infant mortality - Females

0

200

400

600

800

1000

1200

1400

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

e pe

r 10

0,00

0 bi

rths


Infant mortality Ratio: most deprived to most affluent : Females

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

io

53

ANNEX C APPENDIX 2

6. Infant mortality – rate per 100,000 births - Males


Infant mortality - Males

0

200

400

600

800

1000

1200

1400

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

e pe

r 10

0,00

0 bi

rths


Infant mortality Ratio: most deprived to most affluent : Males

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

io

54

ANNEX C APPENDIX 2

7. Accidents in children hospital admission rate per 100 population aged 10-14 years - Females


Accidents in children hospital admission rate per 100 population aged 10 to 14 years : Females

0.0

0.5

1.0

1.5

2.0

2.5

3.0

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

e pe

r 10

0




1

2

3

4

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

io

55

ANNEX C APPENDIX 2

7. Accidents in children hospital admission rate per 100 population aged 10-14 years - Males


Accidents in children hospital admission rate per 100 population aged 10 to 14 years : Males

0.0

0.5

1.0

1.5

2.0

2.5

3.0

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

e pe

r 10

0




1

2

3

4

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Year

Rat

io

56

ANNEX C APPENDIX 2

8. Rate of teenage pregnancies per 1,000 13 to 15 year olds


Rate of teenage pregnancies per 1,000 13 to 15 year olds

02468

101214161820

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

e pe

r 1,

000




1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

io

57

ANNEX C APPENDIX 2

9. Rate of teenage pregnancies per 1,000 13 to 19 year olds



0102030405060708090

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

e pe

r 1,

000




0

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

io

58

ANNEX C APPENDIX 2

10. Suicides among 10-24 year olds – Females


Suicides aged 10-24 years : Females

0

5

10

15

20

25

30

35

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

e pe

r 10

0,00

0


Suicides aged 10-24 years Ratio: most deprived to most affluent : Females

1

2

3

4

5

6

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

io

59

ANNEX C APPENDIX 2

10. Suicides among 10-24 year olds – Males


Suicides aged 10-24 years : Males

0

5

10

15

20

25

30

35

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

e pe

r 10

0,00

0


Suicides aged 10-24 years Ratio: most deprived to most affluent : Males

1

2

3

4

5

6

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

Year

Rat

io

60

ANNEX C APPENDIX 2

11a. Percentage of 16-64 year olds who do not eat fresh fruit once a day or more - Females

1995 1998Most affluent quintile 38.28 30.86Most deprived quintile 60.05 55.14Ratio 1.57 1.79

Percentage of 16-64 year olds who do not eat fresh fruit once a day or more : Females

01020304050607080

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds who do not eat fresh fruit once a day or more


1

2

3

4

1995

1998

Year

Rat

io

61

ANNEX C APPENDIX 2

11a. Percentage of 16-64 year olds who do not eat fresh fruit once a day or more - Males


Percentage of 16-64 year olds who do not eat fresh fruit once a day or more : Males

01020304050607080

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds who do not eat fresh fruit once a day or more


1

2

3

4

1995

1998

Year

Rat

io

62

ANNEX C APPENDIX 2

11b. Percentage of 16-64 year olds who do not eat cooked green vegetables 5 times a week or more - Females


Percentage of 16-64 year olds who do not eat cooked green vegetables 5 times a week or more :

Females

0102030405060708090

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds who do not eat cooked green vegetables 5 times a week or more


1

2

3

4

1995

1998

Year

Rat

io

63

ANNEX C APPENDIX 2

11b. Percentage of 16-64 year olds who do not eat cooked green vegetables 5 times a week or more - Males


Percentage of 16-64 year olds who do not eat cooked green vegetables 5 times a week or more : Males

0102030405060708090

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds who do not eat fresh cooked green vegetables 5 times a week or more


1

2

3

4

1995

1998

Year

Rat

io

64

ANNEX C APPENDIX 2

12. Percentage of 16-64 year olds who are current smokers - Females 1999 2000 2001

Most affluent quintile 19.42 22.48 16.35Most deprived quintile 44.15 43.18 41.74Ratio 2.27 1.92 2.55

Percentage of 16-64 year olds who are current smokers : Females

0

10

20

30

40

50

60

1999

2000

2001

Year

Perc

enta

ge


Percentage of 16-64 year olds who are current smokers


1

2

3

4

1999

2000

2001

Year

Rat

io

65

ANNEX C APPENDIX 2

12. Percentage of 16-64 year olds who are current smokers - Males 1999 2000 2001


Percentage of 16-64 year olds who are current smokers : Males

0

10

20

30

40

50

60

1999

2000

2001

Year

Perc

enta

ge


Percentage of 16-64 year olds who are current smokers


0

1

2

3

4

1999

2000

2001

Year

Rat

io

66

ANNEX C APPENDIX 2

13a. Percentage of 16-44 year olds whose self reported general health is not good - Females 1999 2000 2001


Percentage of 16-44 year olds whose self reported general health is not good : Females

0

5

10

15

20

1999

2000

2001

Year

Perc

enta

ge


Percentage of 16-44 year olds whose self reported general health is not good


1

2

3

4

1999

2000

2001

Year

Rat

io

67

ANNEX C APPENDIX 2

13a. Percentage of 16-44 year olds whose self reported general health is not good - Males 1999 2000 2001


Percentage of 16-44 year olds whose self reported health is not good : Males

0

5

10

15

20

1999

2000

2001

Year

Perc

enta

ge


Percentage of 16-44 year olds whose self reported health is not good


1

2

3

4

1999

2000

2001

Year

Rat

io

68

ANNEX C APPENDIX 2

13b. Percentage of 45-64 year olds whose self reported general health is not good - Females 1999 2000 2001


Percentage of 45-64 year olds whose self reported general health is not good : Females

05

10152025303540

1999

2000

2001

Year

Perc

enta

ge


Percentage of 45-64 year olds whose self reported general health is not good


1

2

3

4

5

6

1999

2000

2001

Year

Rat

io

69

ANNEX C APPENDIX 2

13b. Percentage of 45-64 year olds whose self reported general health is not good - Males 1999 2000 2001


Percentage of 45-64 year olds whose self reported health is not good : Males

05

10152025303540

1999

2000

2001

Year

Perc

enta

ge


Percentage of 45-64 year olds whose self reported health is not good


1

2

3

4

5

6

1999

2000

2001

Year

Rat

io

70

ANNEX C APPENDIX 2

14. Percentage of 16-64 year olds who reported a limiting longstanding illness or disability - Females

1999 2000 2001Most affluent quintile 17.4 12.3 8.3Most deprived quintile 26.6 21.9 21.1Ratio 1.53 1.79 2.54

Percentage of 16-64 year olds who reported a limiting longstanding illness or disability : Females

0

5

10

15

20

25

30

35

1999

2000

2001

Year

Perc

enta

ge


Percentage of 16-64 year olds who reported a limiting longstanding illness or disability


1

2

3

4

1999

2000

2001

Year

Rat

io

71

ANNEX C APPENDIX 2

14. Percentage of 16-64 year olds who reported a limiting longstanding illness or disability - Males

1999 2000 2001Most affluent quintile 13.4 10.1 9.1Most deprived quintile 27.6 24.9 20.7Ratio 2.05 2.46 2.28

Percentage of 16-64 year olds who reported a limiting longstanding illness or disability : Males

0

5

10

15

20

25

30

35

1999

2000

2001

Year

Perc

enta

ge


Percentage of 16-64 year olds who reported a limiting longstanding illness or disability


1

2

3

4

1999

2000

2001

Year

Rat

io

72

ANNEX C APPENDIX 2

15. Percentage of 16-64 year olds who are obese (BMI greater than 30 kg/m2) - Females 1995 1998

Most affluent quintile 14.7 14.8Most deprived quintile 20.6 25.1Ratio 1.40 1.70

Percentage of 16-64 year olds who are obese : Females

05

10152025303540

1995

1998

Year

Pere

ntag

e


Percentage of 16-64 year old who are obeseRatio: most deprived to most affluent : Females

1

2

3

4

1995

1998

Year

Rat

io

73

ANNEX C APPENDIX 2

15. Percentage of 16-64 year olds who are obese (BMI greater than 30 kg/m2) - Males 1995 1998


Percentage of 16-64 year olds who are obese : Males

0

5

10

15

20

25

30

35

40

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds who are obese Ratio: most deprived to most affluent : Males

1

2

3

4

1995

1998

Year

Rat

io

74

ANNEX C APPENDIX 2

16. Percentage of 16-64 year olds with a GHQ12 score of 4 or more - Females 1995 1998


Percentage of 16-64 year olds with a GHQ12 score of 4 or more : Females

0

5

10

15

20

25

30

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds with a GHQ12 score of 4 or more


1

2

3

4

1995

1998

Year

Rat

io

75

ANNEX C APPENDIX 2

16. Percentage of 16-64 year olds with a GHQ12 score of 4 or more - Males 1995 1998


Percentage of 16-64 year olds with a GHQ12 score of 4 or more : Males

0

5

10

15

20

25

30

1995

1998

Year

Perc

enta

ge


Percentage of 16-64 year olds with a GHQ12 score of 4 or more


1

2

3

4

1995

1998

Year

Rat

io

76

ANNEX C APPENDIX 2

17. All cause mortality under 75 years – (rate per 100,000 standardised to the European standard population) - Females


All cause mortality rate under 75 years : Females

0100200300400500600700800900

10001100

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


All cause mortality rate under 75 yearsRatio of most deprived to most affluent : Females

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

77

ANNEX C APPENDIX 2

17. All cause mortality under 75 years – (rate per 100,000 standardised to the European standard population) - Males


All cause mortality rate under 75 years : Males

0100200300400500600700800900

10001100

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


All cause mortality rate under 75 yearsRatio of most deprived to most affluent : Males

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

78

ANNEX C APPENDIX 2

18. Coronary heart disease mortality under 75 years – (rate per 100,000 standardised to the European standard population) - Females


Coronary Heart Disease mortality rate under 75 years : Females

0

50

100

150

200

250

300

350

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Coronary Heart Disease mortality rate under 75 yearsRatio of most deprived to most affluent : Females

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

79

ANNEX C APPENDIX 2

18. Coronary heart disease mortality under 75 years – (rate per 100,000 standardised to the European standard population) - Males


Coronary Heart Disease mortality rate under 75 years : Males

0

50

100

150

200

250

300

350

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Coronary Heart Disease mortality rate under 75 yearsRatio of most deprived to most affluent : Males

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

80

ANNEX C APPENDIX 2

19. Cancer mortality under 75 years – (rate per 100,000 standardised to the European standard population) - Females


Cancer mortality rate under 75 years : Females

0

50

100

150

200

250

300

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Cancer mortality rate under 75 yearsRatio of most deprived to most affluent : Females

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

81

ANNEX C APPENDIX 2

19. Cancer mortality under 75 years – (rate per 100,000 standardised to the European standard population) - Males


Cancer mortality rate under 75 years : Males

0

50

100

150

200

250

300

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Cancer mortality rate under 75 yearsRatio of most deprived to most affluent : Males

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

82

ANNEX C APPENDIX 2

20. Life expectancy at birth (3 year aggregate figures) – Females 1991-93 1992-94 1993-95 1994-96 1995-97 1996-98 1997-99 1998-00 1999-01 2000-02

Most affluent quintile 79.20 79.48 79.65 79.87 80.00 80.29 80.45 80.67 80.77 80.86Most deprived quintile 74.78 74.98 75.04 75.28 75.31 75.37 75.55 75.67 76.04 76.34Ratio 1.06 1.06 1.06 1.06 1.06 1.07 1.06 1.07 1.06 1.06

Life expectancy at birth - Females

65676971737577798183

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Life

exp

ecta

ncy


Life expectancy at birthRatio: most affluent to most deprived - Females

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

io

83

ANNEX C APPENDIX 2

20. Life expectancy at birth (3 year aggregate figures) – Males 1991-93 1992-94 1993-95 1994-96 1995-97 1996-98 1997-99 1998-00 1999-01 2000-02

Most affluent quintile 74.59 74.98 75.17 75.55 75.73 76.03 76.20 76.53 76.80 77.03Most deprived quintile 68.31 68.36 68.31 68.26 68.35 68.47 68.57 68.68 68.92 69.08Ratio 1.09 1.10 1.10 1.11 1.11 1.11 1.11 1.11 1.11 1.12

Life expectancy at birth - Males

65676971737577798183

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Life

exp

ecta

ncy


Life expectancy at birth Ratio: most affluent to most deprived - Males

1

2

3

4

1991-9

3

1992-9

4

1993-9

5

1994-9

6

1995-9

7

1996-9

8

1997-9

9

1998-0

0

1999-0

1

2000-0

2

Year

Rat

io

84

ANNEX C APPENDIX 2

21. All cause mortality 75 or more years – (rate per 100,000 standardised to the European standard population) - Females


All cause mortality rate 75 years and over : Females

0

2000

4000

6000

8000

10000

12000

14000

16000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


All cause mortality rate 75 years and overRatio of most deprived to most affluent : Females

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

85

ANNEX C APPENDIX 2

21. All cause mortality 75 or more years – (rate per 100,000 standardised to the European standard population) - Males


All cause mortality rate 75 years and over : Males

0

2000

4000

6000

8000

10000

12000

14000

16000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


All cause mortality rate 75 years and overRatio of most deprived to most affluent : Males

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

86

ANNEX C APPENDIX 2

22. Coronary heart disease mortality 75 or more years – (rate per 100,000 standardised to the European standard population) – Females


Coronary Heart Disease mortality rate 75 years and over : Females

0

500

1000

1500

2000

2500

3000

3500

4000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Coronary Heart Disease mortality rate 75 years and overRatio of most deprived to most affluent : Females

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

87

ANNEX C APPENDIX 2

22. Coronary heart disease mortality 75 or more years – (rate per 100,000 standardised to the European standard population) - Males


Coronary Heart Disease mortality rate 75 years and over : Males

0

500

1000

1500

2000

2500

3000

3500

4000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Coronary Heart Disease mortality rate 75 years and overRatio of most deprived to most affluent : Males

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

88

ANNEX C APPENDIX 2

23. Cancer mortality 75 or more years – (rate per 100,000 standardised to the European standard population) - Females


Cancer mortality rate 75 years and over : Females

0

500

1000

1500

2000

2500

3000

3500

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Cancer mortality rate 75 years and overRatio of most deprived to most affluent : Females

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

89

ANNEX C APPENDIX 2

90

23. Cancer mortality 75 or more years – (rate per 100,000 standardised to the European standard population) - Males


Cancer mortality rate 75 years and over : Males

0

500

1000

1500

2000

2500

3000

3500

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

e pe

r 10

0,00

0 st

anda

rdis

ed to

the

Eur

opea

n po

pula

tioin


Cancer mortality rate 75 years and over : MalesRatio of most deprived to most affluent

1

2

3

4

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Year

Rat

io d

epri

ved

to a

fflue

n

INEQUALITIES IN HEALTH - Social Care Onlinedocs.scie-socialcareonline.org.uk/fulltext/health... ·...

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