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Am J Hum Biol. 2019 Jun 24:e23278. doi: 10.1002/ajhb.23278. [Epub ahead of print]

Obesity, genomic ancestry, and socioeconomic variables in Latin American mestizos.

Author information

Instituto Patagónico de Ciencias Sociales y Humanas-CONICET, Puerto Madryn, Chubut, Argentina.
School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, UK.
Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, UK.
Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru.
Grupo de Genética Molecular (GENMOL), Universidad de Antioquia, Medellín, Colombia.
Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Escuela Nacional de Antropología e Historia, Ciudad de México, Mexico.
Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, Mexico.
Instituto de Alta Investigación Universidad de Tarapacá, Programa de Genética Humana, ICBM Facultad de Medicina, Universidad de Chile, Santiago, Chile.
Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China.
Laboratory of Biocultural Anthropology, Law, Ethics, and Health (Centre National de la Recherche Scientifique and Etablissement Français du Sang, UMR-7268), Aix-Marseille University, Marseille, France.



This article aims to assess the contribution of genomic ancestry and socioeconomic status to obesity in a sample of admixed Latin Americans.


The study comprised 6776 adult volunteers from Brazil, Chile, Colombia, Mexico, and Peru. Each volunteer completed a questionnaire about socioeconomic variables. Anthropometric variables such as weight, height, waist, and hip circumference were measured to calculate body indices: body mass index, waist-to-hip ratio and waist-to-height ratio (WHtR). Genetic data were extracted from blood samples, and ancestry was estimated using chip genotypes. Multiple linear regression was used to evaluate the relationship between the indices and ancestry, educational level, and economic well-being. The body indices were dichotomized to obesity indices by using appropriate thresholds. Odds ratios were calculated for each obesity index.


The sample showed high percentages of obesity by all measurements. However, indices did not overlap consistently when classifying obesity. WHtR resulted in the highest prevalence of obesity. Overall, women with low education level and men with high economic wellness were more likely to be obese. American ancestry was statistically associated with obesity indices, although to a lesser extent than socioeconomic variables.


The proportion of obesity was heavily dependent on the index and the population. Genomic ancestry has a significant influence on the anthropometric measurements, especially on central adiposity. As a whole, we detected a large interpopulation variation that suggests that better approaches to overweight and obesity phenotypes are needed in order to obtain more precise reference values.


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