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Soc Sci Med. 2012 Apr;74(8):1204-12. doi: 10.1016/j.socscimed.2011.11.034. Epub 2012 Jan 28.

Do neighborhoods affect individual mortality? A systematic review and meta-analysis of multilevel studies.

Author information

1
Unit for Health Promotion Research, Institute of Public Health, University of Southern Denmark, Denmark. matm@niph.dk

Abstract

There has been increasing interest in investigating whether inhabitants in socially or physically deprived neighborhoods have higher mortality when individual socioeconomic status is adjusted for. Results so far appear ambiguous and the objective of this study was to conduct a systematic literature review of previous studies and to quantify the association between area-level socioeconomic status (ALSES) and all-cause mortality in a meta-analysis. Current guidelines for systematic reviews and meta-analyses were followed. Articles were retrieved from Medline, Embase, Social Sciences Citation Index and PsycInfo and individually evaluated by two researchers. Only peer-reviewed multilevel studies from high-income countries, which analyzed the influence of at least one area-level indicator and which controlled for individual SES, were included. The ALSES estimates in each study were first combined into a single estimate using weighted linear regression. In the meta-analysis we calculated combined estimates with random effects to account for heterogeneity between studies. Out of the 40 studies found eligible for the systematic review 18 studies were included in the meta-analysis. The systematic review suggests that there is an association between social cohesion and mortality but found no evidence for a clear association for area-level income inequality or for social capital. Studies including more than one area level suggest that characteristics on different area levels contribute to individual mortality. In the meta-analysis we found significantly higher mortality among inhabitants living in areas with low ALSES. Associations were stronger for men and younger age groups and in studies analyzing geographical units with fewer inhabitants.

PMID:
22365939
DOI:
10.1016/j.socscimed.2011.11.034
[Indexed for MEDLINE]

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