ObjectivesThe study aims to evaluate the magnitude of multimorbidity in Brazilian adults, as well to measure their association with individual and contextual factors stratified by Brazilian states and regions.MethodsA national-based cross-sectional study was carried out in 2013 with Brazilian adults. Multimorbidity was evaluated by a list of 22 physical and mental morbidities (based on self-reported medical diagnosis and Patient Health Questionnaire-9 for depression). The outcome was analysed taking ≥2 and ≥3 diseases as cut-off points. Factor analysis (FA) was used to identify disease patterns and multilevel models were used to test association with individual and contextual variables.ResultsThe sample comprised 60 202 individuals. Multimorbidity frequency was 22.2% (95% CI 21.5 to 22.9) for ≥2 morbidities and 10.2% (95% CI 9.7 to 10.7) for ≥3 morbidities. In the multilevel adjusted models, females, older people, those living with a partner and having less schooling presented more multiple diseases. No linear association was found according to wealth index but greater outcome frequency was found in individuals with midrange wealth index. Living in states with higher levels of education and wealthier states was associated with greater multimorbidity. Two patterns of morbidities (cardiometabolic problems and respiratory/mental/muscle–skeletal disorders) explained 92% of total variance. The relationship of disease patterns with individual and contextual variables was similar to the overall multimorbidity, with differences among Brazilian regions.ConclusionsIn Brazil, at least 19 million adults had multimorbidity. Frequency is similar to that found in other Low and and Middle Income Countries. Contextual and individual social inequalities were observed.
Estudo transversal com o objetivo de investigar a associação entre comportamento sedentário e consumo de alimentos ultraprocessados (AUP) em adolescentes brasileiros. Foram utilizados dados da Pesquisa Nacional de Saúde do Escolar (PeNSE) realizada em 2015. O consumo diário de pelo menos um grupo de AUP representou o desfecho, e a exposição principal foi o tempo diário de comportamento sedentário (horas em atividades sentado, excluído o tempo dispendido na escola). Foram calculadas prevalências, razões de prevalências e intervalos de 95% de confiança (IC95%). As análises foram ajustadas para sexo, idade, cor da pele, escolaridade materna, índice de bens, região geográfica e dependência administrativa da escola. Cerca de 40% dos escolares reportaram consumo diário de pelo menos um grupo de AUP (39,7%; IC95%: 39,2-40,3) e 68,1% (IC95%: 67,7-68,7) referiram > 2 horas/dia de comportamento sedentário. Entre os escolares com comportamento sedentário > 2 horas/dia, a prevalência de consumo diário de AUP foi de 42,8% (IC95%: 42,1-43,6%), maior do que entre os sem comportamento sedentário (29,8%; IC95%: 29,0-30,5%). Quanto maior o tempo de comportamento sedentário, maior a prevalência de consumo de AUP (valor de p para tendência linear < 0,001). Estratégias que promovam a alimentação saudável e a diminuição de comportamentos sedentários, bem como regulamentações da publicidade de AUP, tornam-se necessárias a fim de evitar que estilos de vida não saudáveis perdurem à idade adulta.
Objective: to analyze the Family Health Strategy (FHS) coverage time trend in Brazil, its Regions and Federative Units (FUs) from 2006-2016. Methods: this was an ecological study with time series analysis of Ministry of Health Primary Care Department data; Prais-Winsten regression was used. Results: FHS coverage in Brazil in 2006 and 2016 was 45.3% and 64.0%, respectively, with an increasing trend of coverage (annual variation = 8.4%: 95%CI 7.4;9.3); all five regions showed an increasing trend in coverage, as did the majority of FUs, with the exception of Roraima, Amapá, Piauí, Rio Grande do Norte and Paraíba, which showed stability; in 2016, 14 FUs had coverage of between 75 and 100%, and 11 had coverage of between 50 and 74,9%; coverage in São Paulo and the Federal District was below 50%. Conclusion: although, overall, FHS coverage increased, 13 FUs had coverage below 75% in 2016; therefore, more efforts are needed to universalize FHS coverage.
Lower socioeconomic level is positively related to multimorbidity and it is possible that the clustering of health conditions carries the same association. The aim of this study was to identify prevalence of multimorbidity and clusters of health conditions among elderly, as well the underlying socioeconomic inequalities. This was a cross-sectional population-based study carried out with 60-year-old individuals. Multimorbidity was defined as the presence of 2+, 3+, 4+ or 5+ health conditions in the same individual. Schooling levels and the National Economic Index were used to investigate inequalities in the prevalence of multimorbidities among elderly. Slope and concentration indexes of inequality were used to evaluate absolute and relative differences. A factorial analysis was performed to identify disease clusters. In every ten older adults, about nine, eight, seven and six presented, respectvely, 2+, 3+, 4+ and 5+ health conditions. Three clusters of health conditions were found, involving musculoskeletal/mental/functional disorders, cardiometabolic, and respiratory factors. Higher inequalities were found the higher amount of health conditions (5+), when considering economic level, and for 3+, 4+ and 5+, when considering educational level. These findings show high multimorbidity prevalence among elderly, highlighting the persistence of health inequalities in Southern Brazil. Strategies by the health services need to focus on elderly at lower socioeconomic levels.
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