An Intersectional Approach to Understanding Barriers to Healthcare for Women

• Published in: Journal of community health Vol. 48; no. 1; pp. 89 - 98
• Main Authors: Vohra-Gupta, Shetal, Petruzzi, Liana, Jones, Casey, Cubbin, Catherine
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2023; Springer Nature B.V
• Subjects: Access to Health Care; Adolescent; Adult; Aged; Barriers; Black or African American; Community and Environmental Psychology; Education; Ethics; Ethnic factors; Ethnicity; Female; Females; Health care; Health care access; Health Promotion and Disease Prevention; Health services; Health Services Accessibility; Healthcare Disparities; Hispanic or Latino; Humans; Identities; Income; Insurance; Intersectional Framework; Marital status; Medical electronics; Medical Services; Medicine; Medicine & Public Health; Middle Aged; Minority & ethnic groups; Original Paper; Predictor Variables; Race; Regression analysis; Regression models; Social factors; Socioeconomics; United States; White; Womens health; Young Adult; United States; Racial/ethnic differences in health and healthcare; Healthcare disparities; Gender/sex differences in health and health care; Intersectionality
• ISSN: 0094-5145; 1573-3610
• DOI: 10.1007/s10900-022-01147-8

Access to health care depends on multiple sociodemographic factors such as race/ethnicity, marital status, education, income, and insurance status. However, a paucity of research has examined access to healthcare disparities as they uniquely affect women, specifically women of color. National data were analyzed from the Medical Expenditure Panel Survey (MEPS) utilizing an 11-year sample (2005–2015) of women ages 18–74 (N = 128,355). More recent data were not included due to changes in how sampling was conducted after 2015. Predictor variables included race/ethnicity cross-classified with marital status, education, income, or insurance status, controlling for age. A dichotomous outcome variable called “any barriers to healthcare” was created based on usual source of care, delayed medical care, delayed dental care and delayed prescription care. Multivariate logistic regression models were used to identify associations with barriers to care. The foundation of this methodology is intersectionality and how it impacts access to care for women across social identities. Hispanic women (OR 1.08, 95% CI 1.02–1.14) had higher odds of having a barrier to care compared to White women. However, Black women (OR 0.92, 95% CI 0.87–0.97) had lower odds of having a barrier to care compared to White women. Race/ethnicity also significantly moderated the relationship between socioeconomic variables (marital status, income, education and insurance status) and having a barrier to care. To achieve a healthy community, addressing these racial/ethnic and socioeconomic inequalities helps to support the people who live and work within these communities.