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:
https://lup.lub.lu.se/record/96f15cd2-b0ce-47da-ad2d-d5235b1cec20
- author
- Wemrell, Maria
LU
; Mulinari, Shai
LU
and Merlo, Juan
LU
- organization
- publishing date
- 2017-01-24
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Social Science and Medicine
- volume
- 177
- pages
- 213 - 222
- publisher
- Elsevier
- external identifiers
-
- scopus:85011835164
- pmid:28189024
- wos:000397552900024
- ISSN
- 1873-5347
- DOI
- 10.1016/j.socscimed.2017.01.050
- project
- Swedish genes?
- Multilevel analysis of individual heterogeneity
- language
- English
- LU publication?
- yes
- id
- 96f15cd2-b0ce-47da-ad2d-d5235b1cec20
- date added to LUP
- 2017-01-26 09:35:38
- date last changed
- 2022-04-24 21:01:41
@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}},
doi = {{10.1016/j.socscimed.2017.01.050}},
volume = {{177}},
year = {{2017}},
}