Résumé :
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[BDSP. Notice produite par INIST-CNRS j80R0xf4. Diffusion soumise à autorisation]. Objectives. To aid state and local policymakers, program planners, and community advocates, we created estimates of the percentage of the population lacking health insurance in small geographic areas of California. Methods. We modeled probabilities of uninsurance using state-level, multiyear data from the US Census Bureau's Current Population Survey. The models were applied to population projection data from a commercial vender (Claritas). We updated the population data using the most recently available census and survey data to reflect intercensual population changes. Legislative district boundary files were merged into the updated population projections. Finally, calibration ensured the consistency and stability of the estimates when they were aggregated. Results. Health insurance coverage among nonelderly persons varied widely across assembly districts, from 10% to 44%. The utility of local-level estimates was most apparent when the variations in subcounty uninsured rates in Los Angeles County (19% - 44%) were examined. Conclusions. Stable and useful estimates of health insurance rates for small areas such as legislative districts can be created through use of multiple sources of publicly available data.
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