Research article

Identifying the insured and uninsured in rural America: an empirical discriminant analysis

  • Received: 05 February 2021 Accepted: 09 May 2021 Published: 17 May 2021
  • Purpose

    This present study sought to investigate whether there were factors that could discriminate insured from uninsured rural Americans.

    Methods

    Data for four groups were used: 34 uninsured, 102 government-insured (GP), 324 private- or employer-insured (PEP), and 96 both government- and private- or employer-insured (GPEP). A discriminant analysis was conducted on the four groups, using group membership as the dependent variable; age, education, income, attitude to insurance, emergency room visit, chronic disease prevalence were the independent variables.

    Findings

    The analysis yielded three discriminant functions, however the only significant function was the one that discriminated the PEP-insured individuals from the other groups. About 48% of the cases were classified correctly with the significant discriminant function.

    Conclusion

    The findings of this study can serve as a baseline for future research seeking to eradicate barriers to getting health insurance among the uninsured in rural America.

    Citation: Promise Tewogbola, Norah Aung. Identifying the insured and uninsured in rural America: an empirical discriminant analysis[J]. AIMS Public Health, 2021, 8(3): 421-427. doi: 10.3934/publichealth.2021032

    Related Papers:

  • Purpose

    This present study sought to investigate whether there were factors that could discriminate insured from uninsured rural Americans.

    Methods

    Data for four groups were used: 34 uninsured, 102 government-insured (GP), 324 private- or employer-insured (PEP), and 96 both government- and private- or employer-insured (GPEP). A discriminant analysis was conducted on the four groups, using group membership as the dependent variable; age, education, income, attitude to insurance, emergency room visit, chronic disease prevalence were the independent variables.

    Findings

    The analysis yielded three discriminant functions, however the only significant function was the one that discriminated the PEP-insured individuals from the other groups. About 48% of the cases were classified correctly with the significant discriminant function.

    Conclusion

    The findings of this study can serve as a baseline for future research seeking to eradicate barriers to getting health insurance among the uninsured in rural America.



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    Acknowledgments



    The authors would like to thank Dr. Tamara Kang for introducing us to the statistical approach used in this article.

    Conflicts of interest



    The author declares no conflicts of interest.

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    [9] Wippold GM, Nmezi N, Williams JL, et al. (2020) An Exploratory Study to Understand Factors Associated with Health-related Quality of Life Among Uninsured/Underinsured Patients as Identified by Clinic Providers and Staff. J Prim Care Community Health 11: 2150132720949412. doi: 10.1177/2150132720949412
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  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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