Quantitative intersectionality research: Past, present, and future directions

Area of Science:

• Public Health
• Epidemiology
• Social Justice Research

Background:

• Intersectionality, originating from Black feminist scholarship, provides a framework to analyze how interconnected systems of oppression affect health.
• Current quantitative intersectionality research in public health and epidemiology encounters significant measurement and analysis hurdles.
• Existing studies often use simplistic, individual-level identity measures, failing to capture complex, structural oppression dynamics.

Purpose of the Study:

• To highlight the critical measurement and analysis challenges in quantitative intersectionality research.
• To advocate for the development of lifecourse-informed, multidimensional, and structurally-focused measures.
• To emphasize the need for addressing epidemiologic biases in intersectionality research for actionable evidence.

Main Methods:

• Discusses the limitations of current static, unidimensional measures of social identities.
• Introduces advanced analytic methods like Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA).
• Highlights the scarcity of causal inference methods for quantifying intervention impacts in this field.

Main Results:

• Researchers face substantial measurement and analysis challenges in quantitative intersectionality.
• Existing methods often rely on inadequate proxies for exposure to systems of oppression.
• There's a recognized need for lifecourse-informed, multidimensional, and structurally-focused measurement approaches.

Conclusions:

• Addressing measurement and analysis challenges is vital for valid evidence in intersectionality research.
• Developing sophisticated, lifecourse-oriented, and structural measures is essential.
• Thorough examination of epidemiologic biases is necessary to advance health equity.