Epidemiologists and other population health researchers have made considerable developments in bridging intersectionality theory with epidemiological methods over the past decade. The following list attempts to reflect the dynamic and non-linear nature of this endeavor and is organized as follows. The first set of articles are conceptual, reviewing the why and how of incorporating an intersectional lens into epidemiological research. The second set of articles are methodological, presenting new or novel applications of existing analytic approaches to studying the distribution and determinants of health and disease. When possible, I mention published commentaries and responses to these articles to highlight the ongoing challenges involved in “quantifying” intersectionality and to emphasize the fact that no single method is inherently intersectional. Finally, because intersectionality theory is first and foremost a critical theory with the goal of enacting transformative social change, the third set of articles are focused on examining the process of epidemiological knowledge production itself as a means of reinforcing or challenging systems of power, as well as how epidemiological knowledge can be used to promote intersectional health equity. Of course, this list is nowhere near exhaustive, and is influenced by both extant interpretations of intersectionality theory in the field of epidemiology and my own social location, academic training, and worldview… read more »

Praxis Articles

Shim JK. Understanding the routinised inclusion of race, socioeconomic status and sex in epidemiology: The utility of concepts from technoscience studies. Sociol Heal Illn. 2002;24(2):129 – 150. 

In this sociological article, Shim reviews the use and conceptualization of social identities within epidemiological research and argues that the conflation of social identity with individual-level biology and/or behavior in mainstream epidemiology (re)produces hegemonic (and problematic) notions regarding differences between social groups. She offers a critique of the multifactorial model of disease causation, positing that the model ignores both the intersectional nature of social identities and the social and historical contexts in which disease occurs, and raises important questions about the process of epidemiological knowledge production (e.g., “To what extent are epidemiologists deliberately conscious of and concerned about the meanings that specific measures of race, class and sex/gender embody?” (p. 143)). Overall, Shim’s article is an important read as it encourages epidemiologists to view our work as both a scientific and social product. 

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Wemrell M, Merlo J, Mulinari S, Hornborg AC. Contemporary epidemiology: A review of critical discussions within the discipline and a call for further dialogue with social theory. Sociol Compass. 2016;10(2):153–171. 

Wemrell and colleagues offer a critical review of historical debates within epidemiology, with a focus on critiquing the hegemony of “risk factor epidemiology”. In particular, risk factor epidemiology is argued to erase within-group heterogeneity, ignore social and historical contexts, and prioritize scientific objectivity and neutrality over public health-promoting social change. They conclude by arguing for a greater incorporation of social theory (including intersectionality theory) into epidemiological research, particularly with respect to studying the social determinants of health and health disparities, in order to produce epidemiological knowledge that better promotes health equity. 

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Breilh J. Latin American critical (‘Social’) epidemiology: New settings for an old dream. Int J Epidemiol. 2008;37:745–750. 

Breilh’s article provides an important critique of the “scientific discrimination” in mainstream epidemiological and public health research, whereby the scientific contributions from Latin America are under-appreciated and under-acknowledged relative to contributions from Western countries. As a means of challenging this form of structural academic bias, he outlines the objectives and major contributions of “Latin American critical epidemiology”, illustrating how the field has “constructed a sound institutional and academic platform from which to exercise a democratic projection of science and mold an alternative public health movement” (p. 749). Breilh’s article is an essential read for epidemiologists looking to engage in intersectional scholarship as it encourages us to ask who is “at the table” of epidemiological knowledge production (and why), and what the implications are with respect to producing knowledge to promote intersectional health equity.

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Ng E, Muntaner C. A critical approach to macrosocial determinants of population health: Engaging scientific realism and incorporating social conflict. Curr Epidemiol Reports. 2014;1:27–37. 

Ng and Muntaner argue for the advancement of macrosocial epidemiology, defined as the study of macro-level factors, processes, and institutions (e.g., globalization, macroeconomics) on the population patterning and determinants of health and disease. Although they do not explicitly discuss intersectionality theory, macrosocial epidemiology’s emphasis on structural power and social justice is directly in-line with the theory’s core tenets and critical bent, making this read helpful for thinking about how intersectionality and social epidemiological theories can inform and build upon one another. 

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Inhorn MC, Whittle KL. Feminism meets the “new” epidemiologies: toward an appraisal of antifeminist biases in epidemiological research on women’s health. Soc Sci Med. 2001;53(5):553–67. 

Similar to Ng and Muntaner’s argument for macrosocial epidemiology, Inhorn and Whittle put forth their vision of a “feminist epidemiology”, characterized by a strong engagement with critical social theory (including intersectionality theory), an examination of the researcher’s positionality, a focus on structural power, and a grass-roots, participatory approach. 

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Cho S, Crenshaw KW, McCall L. Toward a field of intersectionality studies: Theory, applications, and praxis. Signs (Chic). 2013;38(4):785–810. 

Last but certainly not least, this article from Cho and colleagues provides a comprehensive overview of extant intersectional scholarship in an effort to define and distinguish a field of “intersectionality studies”. Although not specific to epidemiology, the authors “Template for a Collaborative Intersectionality” can provide epidemiologists with important guidelines for incorporating intersectionality into their work and foster a more critical, interdisciplinary, and social justice-oriented epidemiology.

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Epidemiologists and other population health researchers have made considerable developments in bridging intersectionality theory with epidemiological methods over the past decade. The following list attempts to reflect the dynamic and non-linear nature of this endeavor and is organized as follows. The first set of articles are conceptual, reviewing the why and how of incorporating an intersectional lens into epidemiological research. The second set of articles are methodological, presenting new or novel applications of existing analytic approaches to studying the distribution and determinants of health and disease. When possible, I mention published commentaries and responses to these articles to highlight the ongoing challenges involved in “quantifying” intersectionality and to emphasize the fact that no single method is inherently intersectional… read more »

Methodological Articles

Veenstra G. Race, gender, class, and sexual orientation: Intersecting axes of inequality and self-rated health in Canada. Int J Equity Health. 2011;10(3):1–11. 

Veenstra’s article is one of the first to explicitly present a quantitative analytic approach for incorporating intersectionality theory into epidemiological research. He uses statistical interaction (i.e., two- and three-way cross-product terms between social identity variables in multivariable models) to assess whether multiply marginalized groups are more likely to report poor self-rated health relative to singly- or non-marginalized groups, drawing on intersectionality core tenets of directionality, simultaneity, multiplicativity, and multiple jeopardy. Although the use of statistical interaction to assess intersectionality is increasingly critiqued by social epidemiologists, this article and those informed by it helped motivate the development of the methods introduced in the following articles. 

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Jackson JW, Williams DR, VanderWeele TJ. Disparities at the intersection of marginalized groups. Soc Psychiatry Psychiatr Epidemiol. 2016;51(10):1349–1359. 

Building off the aforementioned critiques of using statistical interaction to assess intersectionality, this article from Jackson, Williams, and VanderWeele argues in favor of evaluating additive-scale interaction (i.e., a situation in which the combined effect of two factors differ from the sum of each factor’s individual effect) as an alternative quantitative analytic approach. They present a novel additive-scale interaction method that is specific to intersectionality, the joint disparity and its decomposition, and illustrate how it and related measures can be used to quantify excess (i.e., intersectional) risk of disease among groups at the nexus of two marginalized social identities. Technical appendices provide equations for applying the methods to continuous and binary outcomes. 

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Commentaries:

Schwartz S. Commentary: on the application of potential outcomes-based methods to questions in social psychiatry and psychiatric epidemiology. Soc Psychiatry Psychiatr Epidemiol. 2017;52(2):139–42. 

Jackson JW. Explaining intersectionality through description, counterfactual thinking, and mediation analysis. Soc Psychiatry Psychiatr Epidemiol. 2017;52(7):785–93.

Wemrell M, Mulinari S, Merlo J. Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches. Soc Sci Med. 2017;177:213–22. 

The majority of intersectionality-informed epidemiological research adopts an intracategorical or intercategorical orientation; much less attention has been directed to developing quantitative methods consistent with anticategorical intersectionality (see McCall, 2005 listed above). Wemrell and colleagues help to fill this gap by introducing an innovative method for conducting quantitative anticategorical intersectionality-informed research based on the epidemiological concept of discriminatory accuracy (DA). Specifically, the authors contend that quantifying the ability of social identity-based categories to distinguish between those with and without a health outcome of interest (as is typically done in epidemiological research) can demonstrate the large degree of heterogeneity within these categories, and thus what anticategorical intersectionality describes as the “simplifying social fictions” (McCall, 2005, p. 1773) of social identities. They outline their analytic approach (using area under the receiver-operating characteristic curves) and provide guidance for intersectionality theory-consistent interpretations.

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Evans CR, Williams DR, Onnela JP, Subramanian SV. A multilevel approach to modeling health inequalities at the intersection of multiple social identities. Soc Sci Med. 2018;203:64–73. 

In this pioneering article, Evans and colleagues introduce a novel modeling approach for intercategorical intersectionality-informed epidemiological research that is referred to in subsequent articles as Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). Briefly, Intersectional MAIHDA models are multilevel models in which individuals are nested within groups defined by intersecting social identities, which enables investigations of within- and between-group heterogeneity and the ability to identify and quantify interaction (i.e., intersectional) effects for all groups. The authors outline methodological and theoretical advantages of the method over “conventional” intersectional models (i.e., fixed effects models with cross-product terms between social identity variables) and provide an illustrative example. 

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Commentaries: 

Merlo J. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) within an intersectional framework. Soc Sci Med. 2018; 

Evans CR. Adding interactions to models of intersectional health inequalities: Comparing multilevel and conventional methods. Soc Sci Med. 2019;221:95–105. 

Evans further develops the Intersectional MAIHDA method by investigating whether adding additional dimensions of identity into the models reveals or explains away intersectional effects. She also compares findings from Intersectional MAIHDA models to those obtained from conventional intersectional models and discusses plausible statistically-based reasons for the observed differences. Stata code for all analyses are provided in the supplementary materials. 

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Commentaries:

Bauer GR. Math versus meaning in MAIHDA: A commentary on multilevel statistical models for quantitative intersectionality. Soc Sci Med. 2019; 112500. 

Evans CR, Leckie G, Merlo J. Multilevel versus single-level regression for the analysis of multilevel information: The case of quantitative intersectional analysis. Soc Sci Med. 2019;245:112499. 

Evans CR. Reintegrating contexts into quantitative intersectional analyses of health inequalities. Heal Place. 2019;60:102214. 

Another Intersectional MAIHDA methods article, Evans outlines how to incorporate social contexts (e.g., schools and neighborhoods) into the models. She also suggests alternative conceptualizations of contexts for quantitative intersectionality-informed research, with the goal of motivating epidemiologists to better attend to socio-structural processes in their analyses.

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Scheim AI, Bauer GR. The Intersectional Discrimination Index: Development and validation of measures of self-reported enacted and anticipated discrimination for intercategorical analysis. Soc Sci Med. 2019;226:236–45. 

In the only measurement-specific article on this list, Scheim and Bauer develop and validate the Intersectional Discrimination Index (InDI), a measure of attribution-free anticipated and enacted discrimination to be used in intercategorical intersectionality-informed epidemiological research. The authors include the final version of the index within the paper, provide guidance regarding its scoring, and outline an analytic approach for using the index to assess discrimination as social determinant of intersectional health inequities in a companion article (listed below). 

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Commentaries:

Harnois CE, Bastos JL. The promise and pitfalls of intersectional scale development. Soc Sci Med. 2019;223:73–6. 

Bauer GR, Scheim AI. Methods for analytic intercategorical intersectionality in quantitative research: Discrimination as a mediator of health inequalities. Soc Sci Med. 2019;226:236–45. 

In the companion article to that listed above, Bauer and Scheim illustrate a novel method for analytic (i.e., process-oriented) intersectionality-informed epidemiological research. They start with a helpful overview of extant analytic approaches for incorporating intersectionality theory into epidemiological research and highlight persisting methodological challenges, with an emphasis on research aiming to conduct causal analyses. They then introduce their method, a causal mediation analysis (adapted from VanderWeele’s three-way decomposition method and informed by the potential outcomes framework) that allows for heterogeneity of the mediated effect across groups defined by intersecting social identities, and provide an illustrative demonstration complete with equations and SAS code. 

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Commentaries:

Evans CR. Modeling the intersectionality of processes in the social production of health inequalities. Soc Sci Med. 2019;226:249–53.

Jackson JW, VanderWeele TJ. Intersectional decomposition analysis with differential exposure, effects, and construct. Soc Sci Med. 2019;226:254–9. 

Richman LS, Zucker AN. Quantifying intersectionality: An important advancement for health inequality research. Soc Sci Med. 2019;226:246–8. 

Bauer GR, Scheim AI. Advancing quantitative intersectionality research methods: Intracategorical and intercategorical approaches to shared and differential constructs. Soc Sci Med. 2019;226:260–2.

Social identities (i.e., gender, race, ethnicity, class, sexual orientation, age, etc.) are a key construct within epidemiological research, used to define populations and study the patterning of health and disease. And yet, epidemiologists have conceptualized identity in varied, shifting, and oftentimes problematic ways. There have been numerous calls to shift from a discrete and individualized framing of identity to a more nuanced and contextualized one, reflecting broader debates in epidemiology between theories of disease distribution that locate risk within the biology and behaviors of individuals and those that locate risk further upstream (Krieger, 2001). 

Perhaps because of its potential to improve upon extant conceptualizations of identity as well as other core population health constructs, there has been a growing interest in intersectionality theory among epidemiologists. Originating in Black feminist activism and scholarship as a way to explain the unique forms of discrimination experienced by Black women (Collins, 1990; Crenshaw, 1989), intersectionality is a theoretical framework primarily concerned with the multidimensional, interlocking nature of social inequities. Within this framework, social identities are conceptualized as mutually constitutive, jointly shaping lived experience through their historical and ongoing relationships with systems of power. This has several implications for epidemiology: adopting an intersectional perspective could lead to a more nuanced (and valid) understanding of the population patterning of disease, a heightened focus on social determinants, and more structurally oriented interventions. However, there are well-articulated challenges involved in translating a theory aimed at describing complex realities (versus generating hypotheses or predictions) into a quantitative science such as epidemiology, as well as important questions over epistemological consistency.  

Thankfully, epidemiologists and other population health researchers have made considerable developments in bridging intersectionality theory with epidemiological methods over the past decade. The following list attempts to reflect the dynamic and non-linear nature of this endeavor and is organized as follows. The first set of articles are conceptual, reviewing the why and how of incorporating an intersectional lens into epidemiological research. The second set of articles are methodological, presenting new or novel applications of existing analytic approaches to studying the distribution and determinants of health and disease. When possible, I mention published commentaries and responses to these articles to highlight the ongoing challenges involved in “quantifying” intersectionality and to emphasize the fact that no single method is inherently intersectional. Finally, because intersectionality theory is first and foremost a critical theory with the goal of enacting transformative social change, the third set of articles are focused on examining the process of epidemiological knowledge production itself as a means of reinforcing or challenging systems of power, as well as how epidemiological knowledge can be used to promote intersectional health equity. Of course, this list is nowhere near exhaustive, and is influenced by both extant interpretations of intersectionality theory in the field of epidemiology and my own social location, academic training, and worldview. 

Conceptual articles

Bowleg L. The problem with the phrase women and minorities: Intersectionality-an important theoretical framework for public health. Am J Public Health. 2012;102(7):1267–73. 

In one of the first articles to explicitly advocate for an intersectional approach to epidemiological-related research, Bowleg provides a compelling case for adopting intersectionality theory as a critical public health framework, focusing on its potential to “[reframe] how public health scholars conceptualize, investigate, analyze, and address disparities and social inequality in health” (p. 1267). After providing a brief history of intersectionality and outlining its core tenets, she reviews the major theoretical and methodological challenges associated with incorporating the theory into public health research; however, she stresses that having an “intersectionality-informed stance” is more important than methodological refinement. Bowleg concludes by outlining five ways in which this intersectionality-informed stance will benefit public health, ranging from increased understanding of how intersecting social identities influence the patterning and determinants of health disparities to improved interventions and surveillance efforts.     

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Bauer GR. Incorporating intersectionality theory into population health research methodology: Challenges and the potential to advance health equity. Soc Sci Med. 2014;110(10–17). 

Another formative article, Bauer starts similarly by articulating the potential benefits of incorporating intersectionality theory into the broader field of population health sciences. She provides a detailed and nuanced description of the associated methodological challenges, with a focus on measurement- and analytic-related concerns, and offers guidelines for addressing them. The most useful aspect is Bauer’s discussion of how tensions within intersectional scholarship may be understood in the context of population health research. For example, questions such as “who” is intersectional (e.g., all social locations or only those with multiple marginalized identities) and whether all identities are relevant/intersectional in all contexts are addressed in terms of their significance for understanding the distribution and determinants of health and disease. She also considers how intersectionality meshes with epidemiologic theories, particularly Nancy Krieger’s ecosocial theory, with implications for the validity and social value of epidemiological research. 

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Gkiouleka A, Huijts T, Beckfield J, Bambra C. Understanding the micro and macro politics of health: Inequalities, intersectionality & institutions – A research agenda. Soc Sci Med. 2018;200:92–8. 

Gkiouleka and colleagues review the theoretical and methodological underpinnings of using intersectionality as an analytic tool for studying health inequities and offer two research approaches relevant to epidemiology: “situational intersectionality” (i.e., focusing on the specific social identities relevant to a given research question, while exploring potential heterogeneity in such relevance across groups) and “institutional imbrication” (i.e., operationalizing institutions and other macro-level factors typically studied discreetly in epidemiology (e.g., neighborhoods and laws/policies) as intersectional). The article concludes with recommendations for measurement and analysis when using these research approaches and outlines seven actions that researchers can take to make their work more intersectional. 

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Bowleg L. When Black + lesbian + woman ≠ Black lesbian woman: The methodological challenges of qualitative and quantitative intersectionality research. Sex Roles. 2008;59:312–25. 

While not specific to epidemiology or even to population or public health, this earlier article by Bowleg nonetheless provides an excellent overview of measurement-, analytic-, and interpretation-related challenges to conducting intersectionality-informed research. For each of these domains, she provides specific guidelines for addressing the noted challenges, although she emphasizes that contextualization is paramount to defining intersectional scholarship. 

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McCall L. The complexity of intersectionality. Signs (Chic). 2005;30:1771–800. 

This seminal article in intersectional scholarship laid the groundwork for how epidemiologists began to operationalize the theory for quantitative research. McCall presents three orientations for intersectionality-informed research, which represent a continuum of approaches to managing the complexity of multiple intersecting identities: “anticategorical intersectionality” (critique and deconstruct social identities), “intracategorical intersectionality” (reveal nuance within a particular social location), and “intercategorical intersectionality” (document inequalities across many social locations). After reviewing the underlying assumptions and analytic guidelines for each orientation, she calls for an expansion of methodologies used to answer intersectionality-informed research questions so as to “fully engage with the topics and issues of intersectionality” (p. 1774); on a personal note, I find this a strong argument for the incorporation of intersectionality theory into epidemiology! 

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Evans CR. Modeling the intersectionality of processes in the social production of health inequalities. Soc Sci Med. 2019;226:249–53. 

This article is a comprehensive overview of the types of intersectionality-informed epidemiological and population health studies. Evans provides a useful classification system for this growing body of research, distinguishing specific/intracategorical from comprehensive/intercategorical and descriptive from analytic studies, providing researchers with a common language to describe their objectives and analyses. She also suggests specific epidemiologic theories that are particularly well-aligned with intersectionality theory (and could thus be used in conjunction, advancing both fields) and outlines future research directions.  

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