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Susceptibility of a Multivariate Approach to the Measurement of Neighborhood-Level Socioeconomic Status in Neighborhoods and Health Research: Descriptive Findings with Analytical Reasoning

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  • Masayoshi Oka

    (Department of Management, Faculty of Management, Josai University, Sakado 350-0295, Japan)

Abstract

A fairly large number of area-based indices have been developed in the United States (US) and other countries to examine the contextual effect of neighborhood-level socioeconomic status (SES) on health. However, two conceptual and methodological review articles raised several concerns about a multivariate approach to the measurement of neighborhood-level SES. To untangle some of the conceptual and methodological concerns raised in those review articles, the purpose of this study was to illuminate a couple of common oversights masked by the lack of analytical transparency in neighborhoods and health research. Using the State of California and its seven Metropolitan Statistical Areas as the study areas, census-tract-level population estimates from the 2000 Census as well as the 2005–2009, 2010–2014, and 2015–2019 American Community Survey were obtained from the United States Census Bureau’s website for conducting a sequence of data analyses. The results of this study suggest that a multivariate approach to the measurement of neighborhood-level SES may be susceptible to the spatial size and spatial configuration of geographic areas and/or the population size and population structure of geographic areas. For these reasons, a few underlying sources of measurement uncertainty, which may undermine the generalizability of existing area-based indices and their measurement validity, are discussed in a general sense so as to be relevant for examining the contextual effect of neighborhood-level SES on health in the US and other countries.

Suggested Citation

  • Masayoshi Oka, 2024. "Susceptibility of a Multivariate Approach to the Measurement of Neighborhood-Level Socioeconomic Status in Neighborhoods and Health Research: Descriptive Findings with Analytical Reasoning," Social Sciences, MDPI, vol. 13(12), pages 1-33, December.
    • Handle: RePEc:gam:jscscx:v:13:y:2024:i:12:p:693-:d:1547706
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    References listed on IDEAS

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    2. Roger S. Bivand & David W. S. Wong, 2018. "Comparing implementations of global and local indicators of spatial association," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 716-748, September.
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