OBJECTIVES : To evaluate the difference in health insurance coverage between citizens and non-citizens.

METHODS : The study utilized the US Census microdata and American Community Survey data compiled by the Integrated Public Use Microdata Series (IPUMS) for a sample of US population from 2010 to 2016. The study population included citizens (natural-born or naturalized) and legal immigrants, aged 18 years and older, with information on health insurance coverage. Univariate logistic regression was conducted to determine the association between health care coverage and the independent variables, including citizenship status, gender, age, marital status, race, ethnicity, education, income, employment status, language, and year. Multivariable logistic regression was used to compare health insurance coverage between citizens and non-citizens, adjusting for other covariates.

RESULTS : Among 17,170,869 respondents, 16,052,244 (93.5%) were citizens and 1,118,625 (6.5%) were non-citizens. The average age of the population was 49 years and 51.9% of the population was female. Among citizens, 89.2% had health insurance, whereas among non-citizens, only 61.0% had health insurance, (P-value<0.001). All variables were significant in the univariate logistic regression analysis with citizens having a higher likelihood of having health insurance, with an Odds Ratio (OR) of 5.26 (95% Confidence Interval (CI): 5.24, 5.28). In the multivariate logistic regression analysis, citizens were almost 3 times more likely to have health insurance compared to non-citizens (OR: 2.94, 95% CI: 2.93, 2.96). It was also found that being female, older, White, English-speaking, and having a college education is associated with higher chance of having insurance coverage (P-value < 0.001).

CONCLUSIONS : Citizens are more likely to have health insurance compared to non-citizens, even after adjusting for confounding variables that contribute to this disparity.