Literature DB >> 2066230

Area variations in health outcomes: artefact or ecology.

K Humphreys1, R Carr-Hill.   

Abstract

It is a long-standing belief that the size of the difference between the poor (lower social groups) and the rich (higher social groups) in health outcomes will vary according to the characteristics of the area. However typical approaches to analyses of this kind of question violate standard statistical assumption. The basic problem is how to estimate the size of a 'ward effect' (the disadvantage of living in a 'poor' ward over and above effects associated with individual or household circumstances). This is complicated by the hypothesized existence of intra-ward correlated errors; the only way to avoid this bias is to explicitly model the different variance components using multi-level modelling techniques. The purpose of this paper is to illustrate this technique. Analysis using several of the health outcomes in the Health and Lifestyle Survey data, suggests that the ward effect is quite substantial, and remains after 'controlling for' age, gender and several other socio-demographic variables. This 'ward effect' appears to be best represented by the proportions without access to a car and the preponderance of working class members (RGSC IV and V) in the population. Whilst the verdict on the original hypothesis remains 'not proven', the hypothesis has been shown to be more complex than its simplistic statement suggests. The analyses have shown how to unpack these complexities and, more generally, have illustrated the power of the multi-level modelling technique.

Mesh:

Year:  1991        PMID: 2066230     DOI: 10.1093/ije/20.1.251

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  20 in total

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2.  The relation of residential segregation to all-cause mortality: a study in black and white.

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3.  Health conditions and residential concentration of poverty: a study in Rio de Janeiro, Brazil.

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4.  Multilevel ecoepidemiology and parsimony.

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5.  The loss of the population approach puts epidemiology at risk.

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Review 6.  Investigating neighborhood and area effects on health.

Authors:  A V Diez Roux
Journal:  Am J Public Health       Date:  2001-11       Impact factor: 9.308

7.  Life table analysis for areas using vital register data.

Authors:  P Congdon
Journal:  Eur J Popul       Date:  1995-12

8.  Modelling inequality in reported long term illness in the UK: combining individual and area characteristics.

Authors:  S Shouls; P Congdon; S Curtis
Journal:  J Epidemiol Community Health       Date:  1996-06       Impact factor: 3.710

9.  Higher prevalence of mental disorders in socioeconomically deprived urban areas in The Netherlands: community or personal disadvantage?

Authors:  S A Reijneveld; A H Schene
Journal:  J Epidemiol Community Health       Date:  1998-01       Impact factor: 3.710

Review 10.  Studying environmental influences and breast cancer risk: suggestions for an integrated population-based approach.

Authors:  R Millikan; E DeVoto; B Newman; D Savitz
Journal:  Breast Cancer Res Treat       Date:  1995-07       Impact factor: 4.872

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