Intersectional Inequalities and Individual Heterogeneity in Chronic Rheumatic Diseases: An Intersectional Multilevel Analysis

다국어 초록 (Multilingual Abstract)

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).
We identified individuals ages 40–65 years residing in Skåne, Sweden by December 31, 2013 and having done so from January 1, 2000 (n = 342,542). We used a Skåne health care register to identify those with a diagnosis of the CRD of interest between January 1, 2014 and December 31, 2015, with no previous such diagnosis during 2000–2013. We created 144 intersectional social strata (ISS) using categories of age, sex, education, income, civil status, and immigration. For individuals nested within ISS, we applied multilevel logistic regression models to estimate the variance partition coefficient (VPC) as a measure of discriminatory accuracy of the ISS and the predicted absolute risks and 95% credible intervals for each stratum.
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. Sex 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.
Despite meaningful between‐strata inequalities in the risk of being diagnosed with CRDs (except SpA), there were substantial within‐strata heterogeneities that remain unexplained. There was limited evidence of intersectional interaction effects.