Lifestyle factors and high body mass index are associated with different multimorbidity clusters in the Brazilian population
Multimorbidity patterns of a population can be influenced by socioeconomic and lifestylerelated factors. Some of these factors are preventable when healthy habits are promoted to the population. This study analyzed the main grouping patterns of chronic diseases and the relationship with socioeconomi...
| Autores: | , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | Brasil |
| Recursos: | Universidade Federal do Rio Grande do Norte (UFRN) |
| Repositorio: | Repositório Institucional da UFRN |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.ufrn.br:123456789/54975 |
| Acesso em linha: | https://repositorio.ufrn.br/handle/123456789/54975 https://doi.org/10.1371/journal.pone.0207649 |
| Access Level: | acceso abierto |
| Palavra-chave: | multimorbidity body mass index healthy habits sedentary habits |
| Resumo: | Multimorbidity patterns of a population can be influenced by socioeconomic and lifestylerelated factors. Some of these factors are preventable when healthy habits are promoted to the population. This study analyzed the main grouping patterns of chronic diseases and the relationship with socioeconomic and lifestyle-related factors of the Brazilian population (over the age of 18), based on a population-based survey (2013 National Health Survey). A total of 60,202 participants were included. Cluster analysis was carried out to identify the combinations of chronic diseases. Bivariate and multivariate analyses were carried out to verify the relationship between disease clusters and independent variables, utilizing Poisson’s regression with robust variance, considering a 95% confidence interval. Cluster analysis revealed four disease clusters:cardiometabolic diseases/cancer, mental/occupational diseases, musculoskeletal diseases and respiratory diseases, all significantly associated with the female gender, current/past smoking habits and overweight/obesity in multivariate analyses. These aspects must be considered when planning health services and developing strategies and guidelines for the prevention and treatment of multiple chronic conditions |
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