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Natalia Tumas, Pompeu Fabra University
Cecilia Anza Ramírez, CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Peru.
Mariana Carvalho de Menezes, Universidade Federal de Ouro Preto, Brazil.
Mónica Mazariegos, Instituto de Nutrición de Centro América y Panamá (INCAP), Guatemala.
Kari Moore, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
Ana Ortigoza, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
Carolina Pérez Ferrer, Instituto Nacional de Salud Pública, Mexico.
Santiago Rodríguez López, CIECS, CONICET and Universidad Nacional de Córdoba, Argentina.
Olga Sarmiento, Universidad de los Andes
Joan Benach, Pompeu Fabra University
Mariana Lazo, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
Obesity is a major public health issue, interrelated to urbanization, social, and gender inequalities. A comprehensive understanding on this intersection in Latin America is yet to be accomplished. Our aim is to analyze the association between city-level income inequality, women empowerment indicators and obesity by gender in Latin America; and how these associations vary by individual- or subcity-socioeconomic conditions (SEC). Using census and health surveys information compiled by the SALURBAL (Urban Health in Latin America) project, we will analyze data of 187 cities from Argentina, Brazil, Chile, Colombia, El Salvador, Guatemala, Mexico and Peru (2002-2016). Obesity will be used as the outcome while the income-based Gini and a women´s labor force participation (WLFP) score -as proxy of women empowerment- will be considered as exposure variables. We will estimate gender-stratified three-level logistic mixed-models. We expect that individuals living in cities with greater income inequality will have higher probability of obesity, and this association will be stronger among individuals from lower subcity- and individual-SEC. Individuals living in cities with greater WLFP will have lower probability of obesity, and this association will be stronger among individuals from higher subcity and individual-SEC. All the associations are expected to be stronger among women than men.
Keywords: Health and morbidity, Urbanization and urban populations, Multi-level modeling, Inequality