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Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases : An intersectional multilevel analysis

Kiadaliri, Ali LU and Englund, Martin LU (2019) In Arthritis care and research : the official journal of the Arthritis Health Professions Association
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.

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author
organization
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type
Contribution to journal
publication status
epub
subject
in
Arthritis care and research : the official journal of the Arthritis Health Professions Association
publisher
John Wiley & Sons
external identifiers
  • pmid:31733042
ISSN
0893-7524
DOI
10.1002/acr.24109
language
English
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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
2019-11-18 10:19:31
@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         = {0893-7524},
  language     = {eng},
  month        = {11},
  publisher    = {John Wiley & Sons},
  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},
  year         = {2019},
}