ArticleNature communications2026
Decoding health disparities by gender, ethnicity and chronic diseases across three Latin American countries.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Chronic diseases disproportionately affect certain ethnic and gender groups, but the social determinants driving these disparities in Latin America are not fully understood. In this study, we analyzed data from national health surveys in Brazil, Mexico, and Ecuador (2018-2019), representing a total weighted population of 96,726,891 adults. We used random forest models to predict chronic disease diagnoses based on education, occupation, and access to essential services such as sanitation, drinking water, and garbage collection. Our models performed better for indigenous and afro-descendant people, highlighting significant inequalities. While occupation and education were strong predictors for women, decreasing model performance by 8.57% and 7.36% respectively, occupation was the critical variable for men, decreasing model performance by 19.6% when neutralized. This work highlights the need for public policies adapted to the specific needs of different ethnic and gender groups.
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