Lifestyle factors and high body mass index are associated with different multimorbidity clusters in the Brazilian population

• Published in: PloS one Vol. 13; no. 11; p. e0207649
• Main Authors: de Carvalho, Januse Nogueira, de Camargo Cancela, Marianna, de Souza, Dyego Leandro Bezerra
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 20.11.2018; Public Library of Science (PLoS)
• Subjects: Alcohol; Biology and Life Sciences; Bivariate analysis; Body mass; Body mass index; Body size; Body weight; Cancer; Chronic conditions; Chronic illnesses; Chronic obstructive pulmonary disease; Cluster analysis; Comorbidity; Confidence intervals; Diabetes; Epidemiology; Exercise; Health care; Health surveys; Independent variables; Lifestyles; Medical research; Medicine and Health Sciences; Multimorbidity; Musculoskeletal diseases; Obesity; Occupational diseases; Overweight; People and places; Population; Population studies; Public health; Regression analysis; Respiratory diseases; Robustness (mathematics); Smoking; Social Sciences; Socioeconomics; Statistical analysis; Studies; Variables; Brazil
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0207649

Multimorbidity patterns of a population can be influenced by socioeconomic and lifestyle-related 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.