Combining information from multiple surveys for assessing health disparities |
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Authors: | Trivellore E Raghunathan |
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Institution: | (1) School of Public Health, Institute for Social Research, University of Michigan, 48109 Ann Arbor, MI, USA |
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Abstract: | Despite advances in public health practice and medical technology, the disparities in health among
the various racial/ethnic and socioeconomic groups remain a concern which has prompted the Department
of Human and Health Services to designate the elimination of disparities in health as an overarching goal
of Healthy People 2010. To assess the progress towards this goal, suitable measures are needed at the population
level that can be tracked over time; Statistical inferential procedures have to be developed for these population
level measures; and the data sources have to be identified to allow for such inferences to be conducted.
Popular data sources for health disparities research are large surveys such the National Health and Interview
Survey (NHIS) or the Behavior Risk Factor Surveillance System (BRFSS). The self-report disease status collected
in these surveys may be inaccurate and the errors may be correlated with variables used in defining the
groups. This article uses the National Health and Nutritional Examination Survey (NHANES) 99-00 to assess
the extent of error in the self-report disease status; uses a Bayesian framework develop corrections
for the self-report disease status in the National Health Interview Survey (NHIS) 99-00; and compares inferences
about various measures of health disparities, with and without correcting for measurement error. The methodology
is illustrated using the disease outcome hypertension, a common risk factor for cardiovascular disease.
JEL classification C1 (C11, C13, C15), C4 (C42) and I3 (I31, I38) |
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Keywords: | Bayesian analysis Complex surveys Monte Carlo simulation Measurement error |
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