AIMS Public Health (May 2021)
Identifying the insured and uninsured in rural America: an empirical discriminant analysis
Abstract
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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