We are complex beings: comparison of statistical methods to capture and account for intersectionality

Area of Science:

• Sociology
• Public Health
• Health Disparities Research

Background:

• Intersectionality theory explains how overlapping social identities (race, disability, sexual orientation, income) create unique experiences of oppression and marginalization.
• Understanding these compounded effects is crucial for addressing health disparities.

Purpose of the Study:

• To compare quantitative analytical methods for measuring the impact of intersecting sociodemographic variables on self-reported health.
• To interpret the relative influence of marginalized social positions on health outcomes.

Main Methods:

• Secondary analysis of the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III), a large US cross-sectional study.
• Assessment of interactions among race/ethnicity, disability, sexual orientation, and income using three regression approaches: non-intersectional, single multicategorical predictor, and two-way interactions.

Main Results:

• Multivariate regression with a single multicategorical predictor showed no significant difference in excellent/very good health odds for white, non-disabled, heterosexual individuals compared to gay/lesbian/bisexual/unsure individuals.
• Multivariate regression with two-way interactions revealed that the relationship between sexual orientation and health varied by race/ethnicity.
• Specifically, LGBQ+ individuals had lower odds of reporting better health among white populations but higher odds among Black, Indigenous, and People of Color (BIPOC) populations.

Conclusions:

• Quantitative approaches can illuminate complex intersectional experiences in healthcare.
• Findings underscore the need for interventions and policies that simultaneously address multiple, compounding needs to improve health equity.