The convergence of vulnerable characteristics and health insurance in the US.
This study defines vulnerability as a multi-dimensional construct, reflected in the convergence of predisposing, enabling, and need attributes of risk. Using race, income, and self-perceived health status as indicators and based on eight rounds of the US 1996 panel of the Medical Expenditure Panel Survey, the study examined how the interactions of these vulnerable characteristics affect insurance coverage, a critical measure of health care access. The results of the study demonstrate insurance coverage does vary with the extent of vulnerability. While race and income significantly influence insurance coverage, respectively, there was relatively little disparity in insurance due to health status. Between race and income, income was a more significant predictor of lack of insurance coverage since low-income people regardless of race and health were significantly more likely to be uninsured or partially insured. However, it is important to note that minorities were disproportionately over-represented in the low-income or bad health groups so that any adverse association between income, bad health, and insurance status would affect minorities significantly more than whites. Among those with insurance, the most vulnerable group, the minority-low-income-bad health group or those with all the three vulnerability indicators, were most likely to be publicly insured. A policy implication is to target limited resources on insurance coverage for the more vulnerable groups, those with a convergence or cluster of predisposing, enabling, and need attributes of risk.
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Department of Health Policy and Management, Primary Care Policy Center for the Underserved, Johns Hopkins School of Hygiene & Public Health, Baltimore, MD 21205-1996, USA. ishi@jhsph.edu
D006302:Health Services Research; D006305:Health Status Indicators; D006801:Humans; D007182:Income; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D007348:Insurance, Health / Q000706:statistics & numerical data*; D016015:Logistic Models; D008913:Minority Groups; D018570:Risk Assessment; D014481:United States