Intersecting social inequalities in health: An introduction

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Intersecting social inequalities in health: An introduction Aditi Iyer Ramalingaswami Centre on Equity & Social Determinants of Health Public Health Foundation of India, Bangalore Pre-Conference Workshop on Cutting Edge Research in Health Inequities: Concept and Method, 7 July 2016

Intersecting inequalities?

Intersections/Intersectionality Intersectionality promotes an understanding of human beings as shaped by the interaction of different social locations (e.g., ‘race’/ethnicity, Indigeneity, gender, class, sexuality, geography, age, disability/ability, migration status, religion). These interactions occur within a context of connected systems and structures of power (e.g., laws, policies, state governments and other political and economic unions, religious institutions, media). Through such processes, interdependent forms of privilege and oppression shaped by colonialism, imperialism, racism, homophobia, ableism and patriarchy are created. Hankivsky 2014, p.2

Principles Social relations of power are multi-dimensional, dynamic and simultaneous Specific configurations of power & the importance of one system of power relative to others is time-, situation- and context-dependent Intersectionality can overturn our assumptions about how each system of power operates. While differences between groups at the extreme ends of a multi-dimensional social spectrum are predictable, less is known about the “middle groups” who leverage their social advantages to overcome their disadvantages

Intersectionality in health Examples?

Measure, analyse, understand: HOW???

Questions drive research Types of research Questions Quantitative ? Qualitative Mixed methods

Determining the units of analyses Individuals, marginalised groups Categories of differences Systems and processes of power Importance of the research question & context

Is this intersectionality? Why? Independent variables Multinomial logit (continued treatment=1) Discontinued treatment=2 No treatment=3 Sex Male 1.00 Female 1.20 3.36 ** Economic class Non-poor Poor 1.31 1.45 Poorest 1.92 1.75 Sample size 1290

Pitfalls of treating multiple inequalities as parallel processes Studying only caste or class differences without reference to gender, or only gender differences without reference to caste or class hides important processes. The impact of any one axis of power is mediated the others. Gender relations may be class or caste dependent, or the experience of class or caste may differ by gender. As social position is multi-dimensional, the pathways to health inequalities cannot be predicted satisfactorily along a single dimension of power. The effects of socioeconomic class on health can vary in magnitude and direction by race/ethnicity and by gender. Moreover, changes in socioeconomic position over time can result in differential effects and changing patterns of inequalities in health. The relative importance of risk factors for health outcomes often differs for men and women in different socioeconomic and racial groups, and in different contexts. Indeed, gender (including norms, values, behavior and practices) across and within caste, race, class and ethnicity-based groups, is an important driver of differences in the patterning of risk factors and their consequent influence on health. Studies strongly suggest that economic class should not be analyzed by itself, and that apparent class differences can be misinterpreted without gender analysis. The burden of economic pressures on the household, and responses to disasters, can be disproportionately borne by girls and women. They are the ones more likely to be trapped by medical poverty.

Typical quantitative approaches Stratification of variables by one type of inequality (e.g., gender) to assess the impact of another type of inequality (e.g., economic class) This approach can become cumbersome when there are multiple variables and inexact if the regression coefficients are not tested.

Typical quantitative approaches Use of hierarchical regression models (logistic or OLS) with product terms. This approach cannot specifically distinguish between each intersecting category.

Typical quantitative approaches Neither of these approaches allow for analyses along the entire length of the multi-dimensional social spectrum. Simple and versatile methodology designed at IIMB to enable analysis of differences along the entire social spectrum, not just between the extremes.

Sen, Iyer, Mukherjee (2009) Methodology The method assigns unique identities to each intersecting category (e.g., poor men, non-poor women) vis-à-vis the reference group. It allows for testing the significance of differences between categories taken pair-wise using the chi- squared test on regressed variables It enables one to plot the odds ratios of all categories on a log scale and order them in ascending/descending order

Sen & Iyer (2012) application

Other methodologies Refer to: William Joe, Udaya S. Mishra and K. Navaneetham (2013), Inter-group inequalities in child undernutrition in India: Group analogue of the Gini Coefficient and Atkinson’s Index, Oxford Development Studies, 41:2, 239-257 William Joe (2014), Intersectional inequalities in immunization in India, 1992-93 to 2005-06: a progress assessment. Health Policy and Planning 30: 407–22.