Analyzing disparity trends for health care insurance coverage among non-elderly adults in the US: evidence from the Behavioral Risk Factor Surveillance System, 1993–2009

Shireen Assaf (), Stefano Campostrini (), Cinzia Di Novi (), Fang Xu () and Carol Gotway Crawford ()
Additional contact information
Shireen Assaf: ICF International
Stefano Campostrini: Ca’ Foscari University of Venice
Cinzia Di Novi: University of Pavia
Fang Xu: Northrop Grumman Corporation
Carol Gotway Crawford: Rollins School of Public Health Emory University

The European Journal of Health Economics, 2017, vol. 18, issue 3, No 10, 387-398

Abstract: Abstract Objective To explore the changing disparities in access to health care insurance in the United States using time-varying coefficient models. Data Secondary data from the Behavioral Risk Factor Surveillance System (BRFSS) from 1993 to 2009 was used. Study design A time-varying coefficient model was constructed using a binary outcome of no enrollment in health insurance plan versus enrolled. The independent variables included age, sex, education, income, work status, race, and number of health conditions. Smooth functions of odds ratios and time were used to produce odds ratio plots. Results Significant time-varying coefficients were found for all the independent variables with the odds ratio plots showing changing trends except for a constant line for the categories of male, student, and having three health conditions. Some categories showed decreasing disparities, such as the income categories. However, some categories had increasing disparities in health insurance enrollment such as the education and race categories. Conclusions As the Affordable Care Act is being gradually implemented, studies are needed to provide baseline information about disparities in access to health insurance, in order to gauge any changes in health insurance access. The use of time-varying coefficient models with BRFSS data can be useful in accomplishing this task.

Keywords: Health insurance; Disparities; Health surveillance data; Temporal trends; P-splines; Varying coefficient model (search for similar items in EconPapers)
JEL-codes: I14 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10198-016-0806-1

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