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Objectives To determine the impact of individual and regional variables on the geographic distribution of RD across six Latin-American countries Methods This is a secondary multilevel analysis of cross-sectional data of COPCORD studies that investigated the prevalence of RD in Argentina, Colombia, Ecuador, Mexico, Peru, and Venezuela. Individual factors were sex, age, comorbidities, job status, and Health Assessment Questionnaire (HAQ) score. Contextual level variables were country and subject9s identification as indigenous. RD predictors, including individual and regional variables, particularly indigenous status were identified with logistic regression models. The effect of contextual variables was estimated with median odds ratio9s (OR) estimation. Results Most individuals included in this analysis came from urban areas (82.40%); their mean age was 43.12 years (95% CI 43.01–43.35); and 56.0% were women. Nearly all of them reported >1 comorbidity (94.70%) and 72.19% were economically active. The prevalence of any RD varied from 1.55% in Peru to 26.09% in Argentina. The mean prevalence of Rheumatoid Arthritis (RA) was 1.58 (range 0.64 to 2.47) (table 1). Aside comorbidities, individual level variables associated to any RD were sex (OR: 1.35; 95% CI 1.28–1.43), age (OR: 1.02; 95% CI 1.01 -1.03), and HAQ score (OR: 3.71; 95% CI 3.22–4.28). Crude comparisons showed significant variations among countries (p Conclusions There common factors associated to the prevalence of RD in the region, however, the estimation of its impact varies in significant way across countries and related to the fact of belong to an indigenous group indicating an increase in the estimated ORs. Acknowledgements National Council for Science and Technology (CONACYT);Colegio Mexicano de Reumatologia (Mexico). EsSalud (Peru). Universidad de Cuenca (Ecuador).ASOREUMA (Colombia). Federico Wilhelm Agricola Foundation (Argentina). PDVSA East, SUELOPETROL and Bristol-Myers Laboratory (Venezuela) Disclosure of Interest None declared |
