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People and Places: Contrasting Perspectives on the Association between Social Class and Health

Kaplan, George A.·1996·International Journal of Health Services

Abstract

While a substantial body of evidence demonstrates a strong association between socioeconomic variables and health outcomes, most analyses conceptualize socioeconomic status as an individual characteristic. This article argues for an expanded view that focuses on the relationship between social class and characteristics of the neighborhood and communities in which people live, and illustrates how these characteristics can provide some new directions for research relating class and health. Using the Alameda County Study, the author presents three analyses that support this view. They indicate that socioenvironmental characteristics of areas are importantly related to the mortality experience of individuals, independent of characteristics of the individuals, and that personal and socioenvironmental risk factors cluster together in areas of low income and high mortality. Studying the balance of demands and resources in areas may help to unravel some of the pathways that link social class and health.

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Metadata

Authors
Kaplan, G. A.
Venue
International Journal of Health Services
Published
1996-07
Volume
26
Issue
3
Pages
507-519
ISSN
  • 0020-7314 (ISSN-L)
  • 1541-4469
OpenAlex
W1968636206
Cited by
213
References
0
FWCI
13.24
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: People and Places: Contrasting Perspectives on the Association between Social Class and Health. https://app.cochat.ai/papers/10.2190/4cuu-7b3g-g4xr-0k0b
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Kaplan, G. A. (1996). People and Places: Contrasting Perspectives on the Association between Social Class and Health. International Journal of Health Services. https://doi.org/10.2190/4cuu-7b3g-g4xr-0k0b

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.