This study aimed to conduct a systematic review of publications addressing the multidisciplinary treatment of obesity in Brazil and analyze their main results. A search was conducted in the databases SciELO, Lilacs, and Pubmed/Medline using the following search terms: 'obesidade', 'intervenção', 'tratamento', 'Brasil', for the search in Portuguese, and 'obesity', 'intervention', 'treatment', 'Brazil', for the search in English. Based on these terms, the following combination of words was used: 'Intervenção multiprofissional da obesidade', 'tratamento multidisciplinar da obesidade, tratamento multiprofissional da obesidade' and 'multidisciplinary obesity intervention', 'multidisciplinary obesity treatment', 'Multiprofessional obesity treatment'. Inclusion criteria were as follows: original studies carried out in Brazil involving human beings and that reported an intervention including two or more health care professionals. Articles published between January 2005 and July 2015 were analyzed independently by two reviewers. At the end of the analysis, out of 355 articles initially selected, 26 met all inclusion criteria. The following results were found: 23 studies involved children and adolescents and 03 involved adults 20-60 years of age. It was also found that the 26 studies analyzed had an impact on anthropometric parameters, 10 on physical fitness parameters, 16 on biochemical parameters, 10 on the reduction in comorbidities, 6 on nutritional parameters, and 4 on the psychological/social aspects. Based on evidence presented in the studies reviewed, it can be said that the multidisciplinary treatment for obesity greatly contributed to the reduction in the anthropometric indicators, especially BMI and the biochemical, social, and psychological parameters. Thus, these findings demonstrate that there is a need to expand the range of this type of treatment since it has proven to be effective in the fight against obesity and its comorbidities.

RINALDI, W. Associação entre o indíce de massa corporal, jornada de trabalho e nível de atividade física dos servidores do hemocentro do hospital universitário de maringá. Arq. Cienc. Saúde UNI-PAR, Umuarama, v. 20, n. 3, p, 165-170, set./dez. 2016. RESUMO:O profissional de saúde está sujeito a diversos comportamentos de risco que são determinantes para o desenvolvimento de doenças agudas e crônicas no decorrer da vida, sendo que o estilo de vida adotado influencia diretamente nesse contexto. O objetivo deste estudo foi associar o índice de massa corporal, a jornada de trabalho e nível de atividade física dos servidores do Hemocentro do Hospital Universitário de Maringá. Esta pesquisa caracteriza-se do tipo transversal, contando com a participação de 32 servidores. Os dados foram analisados por estatística descritiva de frequência absoluta e percentual, e o Teste Qui-Quadrado para associação das variáveis por meio do pacote estatístico SPSS, adotando um p< 0,05. Nos resultados encontrados, 56,2% dos servidores foram classificados como não ativos, e 28,1% foram classificados com sobrepeso. Diante deste estudo pode-se verificar a importância de programas de intervenção no ambiente de trabalho, como ginástica laboral durante a jornada de trabalho, ou atividades físicas após ou antes a jornada laboral, para prevenção de doenças e promoção da saúde. PALAVRAS-CHAVE: Atividade física. Jornada de trabalho. Saúde. ASSOCIATION AMONG BODY MASS INDEX, WORK DAY AND LEVEL OF PHYSICAL ACTIVITY OF WORKERS OF THE BLOOD CENTER AT THE UNIVERSITY HOSPITAL OF MARINGÁABSTRACT: Health professionals are subject to various risk behaviors that are determinants to the development of acute and chronic diseases later in life, with direct influence of the adopted lifestyle. The purpose of this study was to associate the body mass index, the working shift and the level of physical activity of health professionals working at the Blood Center of the University Hospital of Maringá. This is a cross-sectional study with 32 participants. Data were analyzed using descriptive statistics of absolute and percentage frequency, as well as the Chi-Square test for association of variables using the SPSS statistical package, adopting p <0.05. The results showed that 56.2% of workers were classified as sedentary, while 28.1% were classified as overweight. Therefore, the importance of intervention programs in the workplace is emphasized, such as occupational gymnastics during the working day, or physical activities after or before the work shift, in order to prevent diseases and promote the health of the workers.

Background: Studies have demonstrated the positive effects of physical activity on cardiovascular risk factors. Longitudinal studies using modeled trajectories are necessary to understand patterns of physical activity and association with cardiovascular risk factors.Objective: To analyze the association between sports practice in young people and current physical activity with the trajectory of cardiovascular risk factors in workers at a public hospital.Methods: Four hundred and seventeen workers was followed for four years reporting Physical Activity, health status, lifestyle behaviors and socio-demographic characteristics. Group-based trajectory modeling identified the trajectories of PA and associations with time-stable and time-varying covariates. We considered a range of sociodemographic and health and lifestyle factors as potential covariates.Results: The results shows the association between participation in sports activities in youth and current physical activity and trajectories of cardiovascular risk, adjusted for sex and age (p &lt; 0.05). Adults who reported having played sports in their youth and are currently active have a lower risk of having a history of obesity and low HDL-c than workers who did not play sports in their youth and are currently sedentary 0.690 (0.565–0.844) obesity, 0.647 (0.500–0.837) low HDL-c.Conclusion: The practice of sports in youth and current physical activity is a protective factor against the trajectory of obesity and low HDL-c, mainly in female workers. Programs to encourage the practice of physical activity should be carried out in order to reduce cardiovascular risk factors and prevent chronic diseases in workers.

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Este estudo teve o objetivo de analisar a associação das barreiras auto referidas para a prática de atividade física e estágio de mudança de comportamento em servidores de um Hospital Escola do Sul do Brasil. Estudo transversal, o qual investigou 485 servidores de um Hospital Escola do Sul do Brasil, sendo 313 mulheres e 172 homens. As variáveis analisadas foram: nível de atividade física, índice de massa corporal, circunferência abdominal, idade, tabagismo, consumo de álcool, horas despendidas de sono, estágio de mudança de comportamento e barreiras para a prática de atividade física. A estatística descritiva foi utilizada em valores de mediana, mínimo e máximo para caracterização da população, além da utilização do teste U de Mann-Whitney para comparação entre os sexos. Foi utilizado o teste Qui-quadrado (p<0,05) com correção de Fisher, quando necessário. No sexo masculino, as barreiras: não gostar de atividade física (p=0,018), medo de lesão (p=0,003) e falta de companhia (p=0,005) demonstraram diferença significativa entre comportamentos inativos e ativos. As barreiras; falta de tempo livre, medo de lesão e preguiça demonstraram uma diferença significativa entre as faixas etárias, não demonstrando progressão no decorrer do tempo. O baixo nível de atividade física pode ser considerado um fator associado a maiores queixas de limitações para a prática de atividade física.

Cardiometabolic diseases, developed throughout the worker’s life,such as hypertension, diabetes, dyslipidemia and obesity are amongthe main causes of death and are associated with modifiable andcontrollable risk factors. The general objective of this study wasto apply supervised Machine Learning techniques and to comparetheir performance to predict the risk of developing cardiometabolicdisease from servers working at the School Hospital of south inBrazil. We sought to map the characteristics of individuals who aremore likely to develop cardiometabolic diseases. The machine learningmodels evaluated were Naive Bayes, Decision Tree, RandomForest, KNN, Logistic Regression and SVM. The results obtained inthe experiments showed that some supervised machine learningmodels produce a good classification, depending on the attributesand hyperparameters used.

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