Incorporating intersectionality into quantitative research methods in public health

Abstract

Abstract Introduction The use of intersectionality as an explicit theoretical framework in quantitative public health research is relatively recent, and has involved a wide array of study design and statistical methods. As best practices have not been identified, guidance for research design and analysis is needed. Methods We draw on a review of the literature and our own methods publications to present an overview of key considerations in approaching public health research from an intersectional perspective. Results Key considerations differ for descriptive studies of intersectional inequalities and analytic studies of potential causes of those inequalities, as research methodologies and their strengths and limitations differ. For descriptive studies, considerations include specification of intersectional groups, multiplicative vs. additive scale for analysis of effects and interactions, limitations of data sets, whether all intersectional groups are of equal interest, and choosing statistical methods. For analytic studies, considerations include whether potential causal factors are relevant and measurable for all intersections or are specific to some, variable measurement, different options in standardization or control of confounding, and statistical analysis methods. Discussion We present considerations in incorporating intersectionality frameworks, and provide tools for conceptualizing intersectionality-informed quantitative public health research.