Gender and national origin differences in healthcare utilization among U.S. Immigrants from Mexico, China, and India.

Journal Article (Journal Article)


To examine gender and national origin differences in the healthcare utilization of immigrants from the three largest populations in the U.S. today (Mexico, China, and India) and to determine if barriers to utilization operate similarly across groups.


The analysis uses nationally-representative data from the 2003 New Immigrant Survey (NIS) to compare utilization behaviors among legal permanent residents from Mexico, China, and India (n = 2244). Conceptually, the study draws on Andersen's Behavioral Model to hypothesize gender and national origin differences in utilization based on factors that might predispose, enable, or necessitate healthcare. Multivariate logistic regression models are used to predict the odds of having seen a doctor in the past year and to test whether obstacles to utilization differ across immigrant groups.


Chinese immigrants are less likely than Mexican and Indian immigrants to have seen a doctor in the past year, a finding that is largely driven by a lack of health insurance. Female immigrants are more likely than males to have done so, despite having fewer resources that enable access to care (e.g. income, English proficiency). Moreover, the relationship between gender and utilization is moderated by English language proficiency: among immigrants with low levels of proficiency, women are significantly more likely than men to have seen a doctor in the past year, while no difference exists between men and women who are proficient in English. This pattern is most evident among Mexican, and to a lesser extent, Indian immigrants.


Barriers to immigrant healthcare utilization vary by gender and national origin. Research will need to continue documenting such variation in order to better inform policy makers and health practitioners of potential solutions for improving health outcomes in increasingly diverse immigrant communities.

Full Text

Duke Authors

Cited Authors

  • Read, JG; Smith, PB

Published Date

  • November 2018

Published In

Volume / Issue

  • 23 / 8

Start / End Page

  • 867 - 883

PubMed ID

  • 28277018

Pubmed Central ID

  • PMC6563819

Electronic International Standard Serial Number (EISSN)

  • 1465-3419

International Standard Serial Number (ISSN)

  • 1355-7858

Digital Object Identifier (DOI)

  • 10.1080/13557858.2017.1297776


  • eng