Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases : An intersectional multilevel analysis
Kiadaliri, Ali LU
and Englund, Martin
LU
(2021)
In Arthritis care and research : the official journal of the Arthritis Health Professions Association
73(2).
p.296-304
- Abstract
OBJECTIVE: To examine how intersections of multiple sociodemographic variables explain the individual heterogeneity in risk of being diagnosed with any of following chronic rheumatic diseases (CRDs): osteoarthritis (OA), gout, rheumatoid arthritis (RA), or spondyloarthritis (SpA).
METHODS: We identified people aged 40-65 years residing in Skåne, Sweden, by 31st December 2013 and having done so from 1st January 2000 (N=342,542). We used Skåne healthcare register to identify those with a diagnosis of the CRD of interest between 1st January 2014 and 31st December 2015 with no previous such diagnosis during 2000-2013. We created 144 intersectional social strata (ISS) using categories of age, gender, education, income, civil status,... (More)
OBJECTIVE: To examine how intersections of multiple sociodemographic variables explain the individual heterogeneity in risk of being diagnosed with any of following chronic rheumatic diseases (CRDs): osteoarthritis (OA), gout, rheumatoid arthritis (RA), or spondyloarthritis (SpA).
METHODS: We identified people aged 40-65 years residing in Skåne, Sweden, by 31st December 2013 and having done so from 1st January 2000 (N=342,542). We used Skåne healthcare register to identify those with a diagnosis of the CRD of interest between 1st January 2014 and 31st December 2015 with no previous such diagnosis during 2000-2013. We created 144 intersectional social strata (ISS) using categories of age, gender, education, income, civil status, and immigration. With individuals nested within ISS, we applied multilevel logistic regression models to estimate: 1) variance partition coefficient (VPC) as a measure of discriminatory accuracy of the ISS and 2) predicted absolute risks and 95% credible intervals for each stratum.
RESULTS: In overall, 3.5%, 0.5%, 0.2%, and 0.2% of the study population were diagnosed with OA, gout, RA, and SpA, respectively. The VPC ranged from 16.2% for gout to 0.5% for SpA. Gender explained the largest proportion of between-strata variation in risk of RA, gout, and SpA while age was the most important factor for OA. The most between-strata differences in risk of these CRDs were due to the additive main effects.
CONCLUSION: Despite meaningful between-strata inequalities in the risk of being diagnosed with CRDs (except SpA), there were substantial within-strata heterogeneities that remains unexplained. There were limited evidence of intersectional interaction effects.
(Less)
- author
- Kiadaliri, Ali
LU
and Englund, Martin
LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Arthritis care and research : the official journal of the Arthritis Health Professions Association
- volume
- 73
- issue
- 2
- pages
- 296 - 304
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- scopus:85100071492
- pmid:31733042
- ISSN
- 2151-4658
- DOI
- 10.1002/acr.24109
- project
- Intersectionality and incidence of musculoskeletal disorders
- language
- English
- LU publication?
- yes
- additional info
- © 2019, American College of Rheumatology.
- id
- 456c02cd-ada5-41fa-b5f0-02c25b62d109
- date added to LUP
- 2019-11-17 15:37:33
- date last changed
- 2024-04-16 22:45:50
@article{456c02cd-ada5-41fa-b5f0-02c25b62d109,
abstract = {{<p>OBJECTIVE: To examine how intersections of multiple sociodemographic variables explain the individual heterogeneity in risk of being diagnosed with any of following chronic rheumatic diseases (CRDs): osteoarthritis (OA), gout, rheumatoid arthritis (RA), or spondyloarthritis (SpA).</p><p>METHODS: We identified people aged 40-65 years residing in Skåne, Sweden, by 31st December 2013 and having done so from 1st January 2000 (N=342,542). We used Skåne healthcare register to identify those with a diagnosis of the CRD of interest between 1st January 2014 and 31st December 2015 with no previous such diagnosis during 2000-2013. We created 144 intersectional social strata (ISS) using categories of age, gender, education, income, civil status, and immigration. With individuals nested within ISS, we applied multilevel logistic regression models to estimate: 1) variance partition coefficient (VPC) as a measure of discriminatory accuracy of the ISS and 2) predicted absolute risks and 95% credible intervals for each stratum.</p><p>RESULTS: In overall, 3.5%, 0.5%, 0.2%, and 0.2% of the study population were diagnosed with OA, gout, RA, and SpA, respectively. The VPC ranged from 16.2% for gout to 0.5% for SpA. Gender explained the largest proportion of between-strata variation in risk of RA, gout, and SpA while age was the most important factor for OA. The most between-strata differences in risk of these CRDs were due to the additive main effects.</p><p>CONCLUSION: Despite meaningful between-strata inequalities in the risk of being diagnosed with CRDs (except SpA), there were substantial within-strata heterogeneities that remains unexplained. There were limited evidence of intersectional interaction effects.</p>}},
author = {{Kiadaliri, Ali and Englund, Martin}},
issn = {{2151-4658}},
language = {{eng}},
number = {{2}},
pages = {{296--304}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Arthritis care and research : the official journal of the Arthritis Health Professions Association}},
title = {{Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases : An intersectional multilevel analysis}},
url = {{http://dx.doi.org/10.1002/acr.24109}},
doi = {{10.1002/acr.24109}},
volume = {{73}},
year = {{2021}},
}