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Journal Article

Citation

Rehkopf DH, Buka SL. Psychol. Med. 2006; 36(2): 145-157.

Affiliation

Department of Society, Human Development and Health, Harvard School of Public Health, Boston, MA, USA.

Copyright

(Copyright © 2006, Cambridge University Press)

DOI

10.1017/S003329170500588X

PMID

16420711

Abstract

Background. Despite an extensive literature, there have been widely divergent findings regarding the direction of the association between area socio-economic characteristics and area suicide rates, with high-quality studies finding either a direct relation (higher rates of suicide in higher socio-economic areas), an inverse relation (lower rates of suicide in higher socio-economic areas) or no association. Method. We performed a systematic review of the literature dating from 1897 to 2004 and identified 86 publications with 221 separate analyses that met our inclusion criteria. We examined the percent of direct, inverse and null findings stratified by key study characteristics including size of aggregated area, socio-economic measure used, region of study, control variables and study design.Results. Analyses at the community level are significantly more likely to demonstrate lower rates of suicide among higher socio-economic areas than studies using larger areas of aggregation. Measures of area poverty and deprivation are most likely to be inversely associated with suicide rates and median income is least likely to be inversely associated with suicide rates. Analyses using measures of unemployment and education and occupation were equally likely to demonstrate inverse associations. Study results did not vary significantly by gender or by study design. Conclusions. The heterogeneity of associations is mostly accounted for by study design features that have largely been neglected in this literature. Enhanced attention to size of region and measurement strategies provide a clearer picture of how suicide rates vary by region. Resources for suicide prevention should be targeted to high poverty/deprivation and high unemployment areas.

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