Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases: An intersectional multilevel analysis. Kiadaliri, A. & Englund, M. Arthritis Care & Research, 73(2):296–304, 2021. Number: 2![Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases: An intersectional multilevel analysis [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{kiadaliri_intersectional_2021,
title = {Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases: {An} intersectional multilevel analysis},
volume = {73},
copyright = {© 2019, American College of Rheumatology},
issn = {2151-4658},
shorttitle = {Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/acr.24109},
doi = {10.1002/acr.24109},
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, 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.},
language = {en},
number = {2},
urldate = {2019-11-18},
journal = {Arthritis Care \& Research},
author = {Kiadaliri, Ali and Englund, Martin},
year = {2021},
note = {Number: 2},
keywords = {Replace full text},
pages = {296--304},
}
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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.","language":"en","number":"2","urldate":"2019-11-18","journal":"Arthritis Care & Research","author":[{"propositions":[],"lastnames":["Kiadaliri"],"firstnames":["Ali"],"suffixes":[]},{"propositions":[],"lastnames":["Englund"],"firstnames":["Martin"],"suffixes":[]}],"year":"2021","note":"Number: 2","keywords":"Replace full text","pages":"296–304","bibtex":"@article{kiadaliri_intersectional_2021,\n\ttitle = {Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases: {An} intersectional multilevel analysis},\n\tvolume = {73},\n\tcopyright = {© 2019, American College of Rheumatology},\n\tissn = {2151-4658},\n\tshorttitle = {Intersectional inequalities and individual heterogeneity in chronic rheumatic diseases},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1002/acr.24109},\n\tdoi = {10.1002/acr.24109},\n\tabstract = {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. 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