Ocorreu um erro. Detalhes Ocultar
Você tem páginas não gravadas. Restaurar Cancelar

Institute for Health Metrics and Evaluation

The Institute for Health Metrics and Evaluation (IHME) is an independent global health research center at the University of Washington that provides rigorous and comparable measurement of the world's most important health problems and evaluates the strategies used to address them. IHME makes this information freely available so that policymakers have the evidence they need to make informed decisions about how to allocate resources to best improve population health.

Todos os conjuntos de dados:  G
  • G
    • setembro 2017
      Fonte: Institute for Health Metrics and Evaluation
      Carregamento por: Knoema
      Acesso em 14 novembro, 2017
      Selecionar Conjunto de dados
      The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. As part of this study, estimates for obesity and overweight prevalence and the disease burden attributable to high body mass index (BMI) were produced by sex, age group, and year for 195 countries and territories. Estimates for high BMI-attributable deaths, DALYs, and other measures (1990-2015) are available from the GBD Results Tool. Files available in this record include obesity and overweight prevalence estimates for 1980-2015. Study results were published in The New England Journal of Medicine in June 2017 in "Health Effects of Overweight and Obesity in 195 Countries over 25 Years."
    • maio 2014
      Fonte: Institute for Health Metrics and Evaluation
      Carregamento por: Kirill Kosenkov
      Acesso em 27 agosto, 2015
      Selecionar Conjunto de dados
      Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013. Comparable estimates based on systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports, using mixed effects linear regression to correct for bias in self-reports. Data for prevalence of obesity and overweight by age, sex, country, and year (n=19 244) obtained with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Research by the staff of the Institute for Health Metrics and Evalutaion with co-authors. Published online 28 May 2014, "The Lancet" Volume 384, No. 9945, p766–781. DOI: http://dx.doi.org/10.1016/S0140-6736(14)60460-8

Nossa declaração de privacidade e política de cookies

O nosso website utiliza cookies para facilitar a sua experiência online. Eles foram salvos no seu computador quando você lançou este site. Você pode modificar suas configurações pessoais para cookies através das configurações do seu navegador de Internet.

Política de Privacidade