Book contents
- Frontmatter
- Contents
- List of tables and figures
- Foreword
- Acknowledgements
- Glossary
- Dedication
- 1 Introduction
- 2 The health gap
- 3 Explaining the gap
- 4 The widening gap
- 5 Narrowing the gap – the policy debate
- References
- Appendix A Premature mortality, poverty and avoidable deaths for each Parliamentary Constituency in Britain by Member of Parliament and their Party 1991-95
- Appendix B Technical details for estimating numbers living in poverty
- Appendix C Does the spatial distribution of social class explain geographical inequalities in health?
- Index
Appendix C - Does the spatial distribution of social class explain geographical inequalities in health?
Published online by Cambridge University Press: 05 July 2022
- Frontmatter
- Contents
- List of tables and figures
- Foreword
- Acknowledgements
- Glossary
- Dedication
- 1 Introduction
- 2 The health gap
- 3 Explaining the gap
- 4 The widening gap
- 5 Narrowing the gap – the policy debate
- References
- Appendix A Premature mortality, poverty and avoidable deaths for each Parliamentary Constituency in Britain by Member of Parliament and their Party 1991-95
- Appendix B Technical details for estimating numbers living in poverty
- Appendix C Does the spatial distribution of social class explain geographical inequalities in health?
- Index
Summary
It would be easy to assume that the compositional effect of differential social class distributions between areas explains a large part of the geographical inequality in mortality between areas. Unfortunately a breakdown of class by age is only available from Sample of Anonymised Records (SAR) areas (see Dale and Marsh, 1993) and age/class specific mortality ratios are only available from the Longitudinal Study of England and Wales. Nevertheless we can use these sources to test the importance of class distribution by applying the age-class specific mortality rates by social class to the numbers of people living in each SAR area to determine the expected mortality in an area having allowed for both age and social class structure. Here we do this for men only as mortality rates by both age and class have not recently been published for women.
Table C1 gives age-class specific mortality rates for men in Britain calculated from the 1% Longitudinal Study sample. The 2% Sample of Anonymised Areas from the 1991 Census provides an estimate of the numbers of men of these ages and classes for 253 areas in England and Wales. Given these two data sources and an estimate of what fraction of the actual population are represented by the SAR it is simple to calculate how many men of these ages we would expect to have died in any of the 253 SAR areas. These age-class standardised mortality ratios can then be compared to simple age standardised ratios to estimate the extent to which variations in the spatial distribution of social classes can explain the spatial variations in mortality in Britain.
To illustrate our method, the total numbers of men by class in the SAR are shown in Table C2 for the SAR area of the 1991 Manchester district. Excluding Scotland, Manchester contains the greatest concentration of people living in the worst off areas in Britain referred to in this book. The total population figures are taken from the ‘Estimating with Confidence Project’, which adjusts the census to allow for people who were not included in the 1991 Census (Simpson and Dorling, 1994). The SAR undersamples men due to its sampling strategy as a representative household (rather than individual) sample and due to Census underenumeration.
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- Chapter
- Information
- The Widening GapHealth Inequalities and Policy in Britain, pp. 257 - 260Publisher: Bristol University PressPrint publication year: 1999