A prevalência de diabetes mellitus está sendo considerada uma epidemia global, com 382 milhões de pessoas atualmente afetadas em todo o mundo e previsão de aumento para 592 milhões para o ano 2035. Atualmente, o Brasil é o quarto país no mundo em número de diabetes. O presente estudo teve como objetivo descrever as características epidemiológicas de indivíduos com diabetes mellitus atendidos no Centro Hiperdia da cidade de Viçosa-MG, considerando características sociodemográficos, fatores de risco modificáveis e não modificáveis. Trata-se de um estudo descritivo, quantitativo, documental e de corte transversal. Foram analisados 547 prontuários, sendo 218 inativos e 329 pacientes ativos. A análise dos pacientes ativos demonstrou que 51% do número total de pacientes apresentavam diabetes mellitus tipo 2 associada à hipertensão. Em relação aos pacientes ativos, 72% apresentavam baixa renda familiar, 74% apresentavam baixa escolaridade, 74%, 78% e 57% apresentavam hipertensão arterial, sobrepeso/obesidade, inatividade física, respectivamente. A presença de dois ou mais antecedentes familiares para doenças coronarianas e metabólicas foi encontrada em 79% dos pacientes. A análise da glicemia de jejum e pós-prandial demonstrou valores inadequados em mais de 50% dos pacientes ativos. Os pacientes com diabetes atendidos pelo Centro Hiperdia de Viçosa apresentaram tanto fatores de risco modificáveis quanto não modificáveis, sendo ambos complicadores para o controle do diabetes e de um bom estado de saúde. Palavras-chave: AbstractThe prevalence of diabetes mellitus is being considered a global epidemic, with 382 million people currently affected worldwide and increase forecast for 592 million for the year 2035. Currently, Brazil is the fourth country in the world in number of diabetes. This study aimed to describe the epidemiological characteristics of individuals with diabetes mellitus treated at Hiperdia Center of Viçosa-MG, considering socio demographic, modifiable risk factors and not modifiable. This is a descriptive study, quantitative, documentary and cross-sectional. 547 records were analyzed, 218 retirees and 329 active patients. The analysis of the active patients showed that 51% of the total number of patients had a higher prevalence of type 2 diabetes mellitus associated with hypertension. In relation to active patients, 72% had low family income, 74% had low education, 74%, 78 % and 57% had high prevalence of hypertension, overweight/obesity, physical inactivity, respectively. The presence of two or more family history of coronary and metabolic diseases was found in 79% of patients. The analysis of fasting and postprandial proved inadequate values by more than 50% of the active patients. Patients with diabetes attended by the Hiperdia Center of Viçosapresented in addition to the disease itself, modifiable and non-modifiable risk factors, both being complicating for diabetes control and a good health.
Background Latent class analysis (LCA) is an alternative and innovative approach to verify the relation of the various combinations of the constructed environment and movement behavior (levels of physical activity, sedentary behavior, and sleep) characteristics. This study aimed to identify latent classes based on the characteristics of the neighborhood environment perceived by adolescents and their association with gender, socioeconomic status (SS), body composition and movement behaviors. Methods This cross-sectional study includes 309 Brazilian adolescents (14 to 16 years old, 57% female). The characteristics of the neighborhood environment perceived were analyzed by the Neighborhood Walkability for Youth Scale. Accelerometers were used for a week to evaluate the movement behaviors. Questionnaires assessed the screen times, total sitting time (TST), and sociodemographic characteristics. LCA was used for modeling the “Perceived Enviroment” variable, having been conducted in the poLCA (Polychromous Variable Latent Class Analysis) package of the R statistical software. Results Three classes were recognized: class 1, “Best Perceived Environment” with 23.03% of adolescents; class 2, “Moderate Perceived Environment”, 63.33%; and class 3, “Worst Perceived Environment”, 13.67%. Light physical activity (LPA), TST, and SS were associated with class prevalence. The adolescents with medium and low SS were, respectively, 3.42 (95% CI 1.62–7.21) and 4.18 (95% CI 1.66–10.50) more likely to belong to class 2, and those with low SS were 5.21 (95% CI 1.35–20.13) more likely to belong to class 3. Class 1 adolescents were associated with a lower chance (OR: 0.09, 95% CI 0.02–0.55) of involvement in ‘adequate LPA time’ compared to class 3. Class 1 adolescents were associated with a lower chance (OR: 0.31, 95% CI 0.12–0.79) of involvement in ‘adequate TST’ compared to class 2. There was a difference between the LPA and TST classes; class 3 presented a longer time in LPA than class 1; class 1 had higher TST than the other classes. Conclusion The findings highlight the influence of neighborhood classes on adolescents’ LPA and TST.
The ecological model has been widely used to help researchers understand the multiple influences in the physical activity (PA) and in the sedentary behaviors in isolated forms. To date, few correlates concerning the behavioral groupings of PA and sedentary behaviors have been studied. In this context, this study aimed to identify movement behaviors’ latent classes related to the different adolescents’ PA and sedentary time expressions, as well as their associations with individual, sociodemographic, family, and environmental correlates. This is a cross-sectional study with 309 students aged between 14 and 16. Latent Class Analysis was used to identify movement behavior classes based on light PA, moderate to vigorous PA, number of steps, sedentary time, and screen time (ST). An accelerometer was used to evaluate movement behaviors. The individual, sociodemographic, family, and environmental correlates were assessed by questionnaires. Three classes were identified: Class 1, "Active and Non-Sedentary" (8.10% of the sample), Class 2, "Active and Sedentary" (28.5%), and Class 3, "Inactive and Sedentary" (63.4%). Those with low fruit intake, low aerobic fitness, stressed and whose head of the family obtained an ‘elementary school’ level education were, respectively, 7.17, 3.59, 3.56, and 4.40 times more likely to belong to class 3 than class 1. Those with medium and high socioeconomic status were 82% and 83% less likely to belong to class 1 than classes 2 and 3, respectively. Adolescents who perceived the neighborhoods with the best access to diversified land use, street connectivity, walking/pedaling ease, and traffic safety attributes, were 84%, 85%, 82%, and 82%, respectively less likely to belong to class 1 than class 2. It is concluded that distinct correlates can be associated with the movement behaviors classes.
Esta tese teve como objetivo geral verificar as características individuais, familiares, do ambiente escolar e da vizinhança que influenciam nos comportamentos de atividade física (AF) e sedentário de adolescentes da cidade de Viçosa-MG. Trata-se de um estudo transversal, com 309 adolescentes, com idade entre 14 e 16 anos. AF, comportamento sedentário e sono foram monitorados por acelerometria. As características individuais, familiares e do ambiente escolar foram obtidos por questionários. O ambiente da vizinhança foi avaliado por questionário e dados georreferenciados. Realizou-se avaliação antropométrica e da aptidão cardiorrespiratória. A Regressão Robusta mostrou que meninos, aqueles que trabalham e os de vizinhança sem calçamento apresentaram maior número de passos (NP) e tempo em AF leve (AFL) e AF moderada a vigorosa (AFMV); aqueles de vizinhanças com maior criminalidade realizaram maior NP e tempo em AFMV; aqueles de vizinhanças sem local adequado para caminhar realizaram maior NP; aqueles que se deslocam de forma ativa para escola apresentaram maior tempo em AFMV; enquanto os que se deslocam de forma passiva apresentaram maior tempo em AFL. Constatou-se que para cada hora a mais de sono, houve redução média de 5,0 minutos no tempo de AFL. A análise de classe latente (ACL) referente aos comportamentos de AF e sedentário identificou três classes: 1)“Ativa e Não Sedentária”, 2)“Ativa e Sedentária” e 3)“Inativa e Sedentária”. As associações entre as classes comportamentais mostraram que comparados aos adolescentes da classe 1, aqueles com tempo sentado elevado (TST), e aqueles com tempo de celular alto, baixo consumo de frutas, aptidão aeróbica baixa, estressado e chefe da família com Ensino Fundamental tiveram, respectivamente, mais chances de pertencerem as classes 2 e 3. Aqueles com status socioeconômico (SS) médio e alto tiveram menos chances de pertencerem a classe 1 que as classes 2 e 3, respectivamente. Adolescentes de vizinhanças com melhores atributos (uso diversificado do solo, conectividade de rua, facilidade para caminhar e segurança), tiveram menos chances de pertencerem a classe 1 que a classe 2. Os resultados da ACL do ambiente da vizinhança identificou três classes: 1)“Melhor Ambiente Percebido”; 2)“Moderado Ambiente Percebido” e 3)“Pior Ambiente Percebido”. As associações das classes de ambiente mostraram que aqueles com SS médio e baixo e aqueles com SS alto tiveram, respectivamente, mais chances de pertencer as classes 2 e 1. Adolescentes da classe 1 tiveram menor chance de envolvimento em ‘adequado tempo AFL’ e em ‘adequado TST’ em relação aos das classes 3 e 2, respectivamente. A Regressão Logística mostrou associações entre o nível de AF com as estimativas de densidade (KDE) dos locais de AF, raios de 1200m e 1600m, e com índice de caminhabilidade. Nos KDE 1200m e KDE 1600m, comparados aos adolescentes do quartil 1, aqueles dos quartis 3 e 4 tiveram maior chance de serem ativos. Para a caminhabilidade, constatou que aqueles do quartil 4 tiveram maior chance de serem ativos comparados aos do quartil 1. Esses achados poderão auxiliar na elaboração de estratégias envolvendo os vários domínios que o adolescente está inserido, com intuito de modificar seus comportamentos ativos e sedentários. Palavras-chave: Atividade Física. Comportamento Sedentário. Correlatos. Modelo Ecológico. Análise de Classe Latente. Adolescentes. Ambiente Construído. Geoprocessamento.
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