Advanced

Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches

Wemrell, Maria LU ; Mulinari, Shai LU and Merlo, Juan LU (2017) In Social Science and Medicine 177. p.213-222
Abstract
Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while... (More)
Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while estimating odds ratios through logistic regressions. The anti-categorical approach is operationalized through measurement of discriminatory accuracy (DA), i.e., capacity to accurately categorize individuals with or without a certain outcome, through computation of the area under the curve (AUC). Our results show substantial differences in average risk between intersectional groupings. The DA of social categorizations is found to be low, however, due to outcome variability within and overlap between categories. We argue that measures of DA should be used for proper interpretation of differences in average risk between social (or any other) categories. Tension between average between-group risk and the DA of categorizations, which can be related to categorical and anti-categorical intersectional analyses, should be made explicit and discussed to a larger degree in epidemiology and public health. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Social Science and Medicine
volume
177
pages
213 - 222
publisher
Elsevier
external identifiers
  • scopus:85011835164
  • wos:000397552900024
ISSN
1873-5347
DOI
10.1016/j.socscimed.2017.01.050
language
English
LU publication?
yes
id
96f15cd2-b0ce-47da-ad2d-d5235b1cec20
date added to LUP
2017-01-26 09:35:38
date last changed
2018-07-08 04:20:55
@article{96f15cd2-b0ce-47da-ad2d-d5235b1cec20,
  abstract     = {Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while estimating odds ratios through logistic regressions. The anti-categorical approach is operationalized through measurement of discriminatory accuracy (DA), i.e., capacity to accurately categorize individuals with or without a certain outcome, through computation of the area under the curve (AUC). Our results show substantial differences in average risk between intersectional groupings. The DA of social categorizations is found to be low, however, due to outcome variability within and overlap between categories. We argue that measures of DA should be used for proper interpretation of differences in average risk between social (or any other) categories. Tension between average between-group risk and the DA of categorizations, which can be related to categorical and anti-categorical intersectional analyses, should be made explicit and discussed to a larger degree in epidemiology and public health.},
  author       = {Wemrell, Maria and Mulinari, Shai and Merlo, Juan},
  issn         = {1873-5347},
  language     = {eng},
  month        = {01},
  pages        = {213--222},
  publisher    = {Elsevier},
  series       = {Social Science and Medicine},
  title        = {Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches},
  url          = {http://dx.doi.org/10.1016/j.socscimed.2017.01.050},
  volume       = {177},
  year         = {2017},
}