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Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009

Author

Listed:
  • Shireen Assaf

    (Department of Statistical Sciences, University Of Padua)

  • Stefano Campostrini

    (Department of Economics, University Of Venice C� Foscari)

  • Cinzia Di Novi

    (Department of Economics, University Of Venice C� Foscari)

  • Fang Xu

    (Northrop Grumman Information Systems)

  • Carol Gotway Crawford

    (Department of Biostatistics and Bioinformatics Rollins School of Public Health Emory University)

Abstract
Access to health care in the United States remains greatly disproportionate across socioeconomic groups. It is not known, however, whether the disparities between the socioeconomic categories are increasing or decreasing. This analysis used a well-established non-parametric technique, employing time-varying coefficient models applied to data from the 1993 to 2009 US Behavioral Risk Factor Surveillance System (BRFSS). The analysis was able to show the changes in the odds ratios of having no health insurance plan for variables of interest over time, therefore highlighting the changes in the disparities between the categories of a variable over time. While other studies have attempted to show the changes in health insurance coverage by socioeconomic groups in different time periods, there is no study to date that has shown these changes as a smooth function with time, therefore providing a clearer picture of the changes in these disparities. The results of this analysis show, for instance, that when compared with individuals with a college education or greater, those with less than a high school education showed a steady increase in the odds ratios for having no health insurance. The same trend seems applicable although in a less-clear way to Hispanics and Non-Hispanic black race-ethnicities, compared with non-Hispanic whites (the reference race category). As measures of the Affordable Care Act are being gradually implemented, studies are needed to provide baseline information about health care access disparity, in order to gauge any changes in health care access over time; BRFSS can be a useful data source in accomplishing this task.

Suggested Citation

  • Shireen Assaf & Stefano Campostrini & Cinzia Di Novi & Fang Xu & Carol Gotway Crawford, 2014. "Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009," Working Papers 2014: 14, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2014:14
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    References listed on IDEAS

    as
    1. Light, Donald W., 2011. "Historical and comparative reflections on the U.S. national health insurance reforms," Social Science & Medicine, Elsevier, vol. 72(2), pages 129-132, January.
    2. Sudano, Joseph J. & Baker, David W., 2006. "Explaining US racial/ethnic disparities in health declines and mortality in late middle age: The roles of socioeconomic status, health behaviors, and health insurance," Social Science & Medicine, Elsevier, vol. 62(4), pages 909-922, February.
    3. Jianhua Z. Huang, 2002. "Varying-coefficient models and basis function approximations for the analysis of repeated measurements," Biometrika, Biometrika Trust, vol. 89(1), pages 111-128, March.
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    Cited by:

    1. Scott R Sanders & Michael R Cope & Paige N Park & Wesley Jeffery & Jorden E Jackson, 2020. "Infants without health insurance: Racial/ethnic and rural/urban disparities in infant households’ insurance coverage," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-13, January.
    2. Di Novi, Cinzia & Marenzi, Anna, 2019. "The smoking epidemic across generations, genders, and educational groups: A matter of diffusion of innovations," Economics & Human Biology, Elsevier, vol. 33(C), pages 155-168.

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    More about this item

    Keywords

    USA; big data; disparities; health plan; health surveillance data; P-splines; temporal trends; varying coefficient model.;
    All these keywords.

    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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