PLOS ONE RESEARCH ARTICLE Identifying hotspots of cardiometabolic outcomes based on a Bayesian approach: The example of Chile 1 2 1 3 Gloria A. AguayoID *, Anna Schritz , Maria Ruiz-Castell , Luis Villarroel , 3 1 4,5 6 Gonzalo Valdivia , Guy FagherazziID , Daniel R. WitteID , Andrew Lawson 1 Population Health Department, Luxembourg Institute of Health, Strassen, Luxembourg, 2 Competence Center for Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg, 3 Department of Public Health, School of Medicine, Pontificia Universidad CatoÂlica de Chile, Santiago, Chile, 4 Department of Public Health, Aarhus University, Aarhus, Denmark, 5 Danish Diabetes Academy, Odense, Denmark, a1111111111 6 Department of Public Health Sciences, Medical University of South Carolina, South Carolina, Charleston, a1111111111 United States of America a1111111111 *
[email protected] a1111111111 a1111111111 Abstract OPEN ACCESS Background Citation: Aguayo GA, Schritz A, Ruiz-Castell M, There is a need to identify priority zones for cardiometabolic prevention. Disease mapping in Villarroel L, Valdivia G, Fagherazzi G, et al. (2020) countries with high heterogeneity in the geographic distribution of the population is challeng- Identifying hotspots of cardiometabolic outcomes based on a Bayesian approach: The example of ing. Our goal was to map the cardiometabolic health and identify hotspots of disease using Chile. PLoS ONE 15(6): e0235009. https://doi.org/ data from a national health survey. 10.1371/journal.pone.0235009 Editor: Nayu Ikeda, National Institute of Health and Methods Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, JAPAN Using Chile as a case study, we applied a Bayesian hierarchical modelling. We performed a Received: December 10, 2019 cross-sectional analysis of the 2009±2010 Chilean Health Survey.