Syndemics are a framework that documents health inequities and vulnerabilities in populations with rheumatic diseases. Compared with other approaches, syndemics are able to conjunctly consider epidemiological, biological, sociodemographic and economic factors, and their interactions.
Objective: To estimate health inequity and vulnerability among Indigenous and non-Indigenous populations with rheumatic and musculoskeletal diseases (RMD) in Latin America using the syndemic approach.
Design: This is a secondary analysis of a previously published large-scale study on the prevalence of RMD.
Setting: Studies carried out in five Latin American countries (Argentina, Colombia, Ecuador, Mexico and Venezuela). Health inequity and vulnerability in RMD were identified through a syndemic approach using network and cluster analysis.
Participants: A total of 44 560 individuals were studied: 29.78% self-identified as Indigenous, 60.92% were female, the mean age was 43.25 years. Twenty clusters were identified in the Indigenous population and 17 in the non-Indigenous population.
Results: The variables associated with RMD among Indigenous populations were rurality, public health system, high joint biomechanical stress, greater pain, disability and alcoholism; and among non-Indigenous people they were being a woman, urban origin, older age, private health system, joint biomechanical stress, greater pain and disability. We identified different health inequities among patients with RMD (ie, lower educational attainment, more comorbidities), associated with factors such as Indigenous self-identification and rural residence.
Conclusions: A syndemic approach enables us to identify health inequities in RMD, as shown by higher prevalence of comorbidities, disability and socioeconomic factors like lower educational attainment. These inequities exist for the overall population of patients with RMD, although it is more evident in Indigenous groups with added layers of vulnerability.
Keywords: epidemiology; public health; rheumatology; statistics & research methods.
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