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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVES, METHODS, RESULTS. Meshes: Data Collection, Geography, Health Status Indicators, Humans, Research Design, Selection Bias, Social Class, United States.
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Using aggregate geographic data to proxy individual socioeconomic status: does size matter? Context: This study assessed whether aggregate-level measures of socioeconomic status (SES) are less biased as proxies for individual-level measures if the unit of geographic aggregation is small in size and population. National Health Interview Survey and census data were used to replicate analyses that identified the degree to which aggregate proxies of individual SES bias interpretations of the effects of SES on health. Ordinary least squares regressions on self-perceived health showed that the coefficients for income and education measured at the tract and block group levels were larger than those at the individual level but smaller than those estimated by Geronimus et al. at the zip code level.
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Researchers should be cautious about use of proxy measurement of individual SES even if proxies are calculated from small geographic units.