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Health behavior patterns of sugar-sweetened beverage consumption among Brazilian adolescents in a nationally representative school-based study.
Rocha, LL, Pessoa, MC, Gratão, LHA, Carmo, ASD, Cunha, CF, Oliveira, TRPR, Mendes, LL
PloS one. 2021;16(1):e0245203
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Sugar sweetened beverages (SSB) are ultra-processed foods containing several man-made chemicals, which heavily feature in the diets of adolescents in many developing countries. This cross-sectional study of 74,589 adolescents aimed to determine health behaviour patterns that affect SSB consumption to focus education and policy efforts to reduce consumption. The results showed that most adolescents who consumed SSB’s had higher consumption of processed foods, more screen time, more days of alcoholic beverage consumption, were more likely to purchase food from the school canteen, and a smoking habit. Those who had a higher consumption of water, minimally processed foods and frequent physical activity were less likely to consume SSB’s. It was concluded that healthy habits can aid implementation of other beneficial health behaviours. This study could be used by healthcare professionals to understand the importance of adopting healthy habits to decrease SSB and ultra-processed food consumption.
Abstract
Studies on sugar-sweetened beverage consumption patterns can help in the individual and population level management of chronic non-communicable diseases and other conditions. This study aimed to identify the association between health behavior patterns and the consumption of sugar-sweetened beverages among Brazilian adolescents from a nationally representative school-based study. A cross-sectional study analyzed data from 71,553 adolescents aged 12-17 years who attended public and private schools in Brazilian cities, from the Study of Cardiovascular Risk in Adolescents. Principal component analysis was performed to identify health behavior patterns, and ordered logistic regression was performed to identify the association between health behavior patterns and sugar-sweetened beverage consumption. Sugar-sweetened beverage consumption (mL/day) was used as the dependent variable. The analyses were performed using Stata software version 14.0 with a significance level of 0.05. Patterns 2 (alcoholic beverage and smoking habit) and 3 (ultra-processed food and screen time) of health behaviors and regularly purchasing snacks in the school cafeteria increased the odds of sugar-sweetened beverage consumption, while pattern 1 (water, unprocessed and minimally processed food and physical activity) decreased these odds. The adoption of healthy habits can indirectly stimulate the adoption of other habits beneficial to health. These results indicate the importance of adopting a set of regulatory measures to reduce sugar-sweetened beverage consumption.
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Type 2 Diabetes Mellitus in Class II and III Obesity: Prevalence, Associated Factors, and Correlation between Glycemic Parameters and Body Mass Index.
Silveira, EA, de Souza Rosa, LP, de Carvalho Santos, ASEA, de Souza Cardoso, CK, Noll, M
International journal of environmental research and public health. 2020;17(11)
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Type 2 diabetes mellitus (T2DM) and obesity are independently known to cause serious health complications, with risks of cardiovascular diseases, higher mortality, low quality of life, and increased public health spending. However, when these diseases occur concurrently, their negative effects on health, health systems, and mortality are even greater. The main aim this study was to investigate the prevalence of T2DM and its associated factors, with an emphasis on biochemical parameters and eating habits, in class II and III obese individuals. The study included 150 class II and III obese individuals from the primary healthcare system of the Brazilian Unified Health System. Results indicate a high prevalence of T2DM (40%) in the studied population, with the associated risks being lower educational level, non-consumption of whole grains, and high insulin resistance. Furthermore, there was no correlation between BMI and glycaemic parameters, that is, an increased BMI did not directly affect a decline in the metabolic condition of T2DM individuals. Authors conclude by emphasising the need to perform further research on T2DM in class II and III obese population.
Abstract
Despite the worldwide growth of class II and III obesity, the factors associated with type 2 diabetes mellitus (T2DM) in these obese individuals are not widely understood. Moreover, no study has investigated these associations in South America. Our study aimed to investigate the prevalence of T2DM and its associated factors, with an emphasis on biochemical parameters and eating habits, in class II and III obese individuals. We also aimed to analyze the correlation between glycemic parameters and body mass index (BMI). Baseline data from a randomized clinical trial (DieTBra Trial) of 150 class II and III obese individuals (BMI > 35 kg/m2) was used. An accelerometer, Food Frequency Questionnaire, and bioimpedance analysis were used to assess physical activity levels, eating habits, and body composition, respectively. Blood was collected after 12 h of fasting. Hierarchical multivariate Poisson regression was performed, and prevalence ratios (PRs) were calculated. Correlations between glycemic parameters (fasting blood glucose, glycosylated hemoglobin, homeostasis model assessment of insulin resistance (HOMA-IR), and insulin) and BMI were also analyzed. The prevalence of T2DM was 40.0% (95% CI, 32.1-48.3), high fasting blood glucose level was 19.33% (95% CI, 13.3-26.6), and high glycosylated hemoglobin was 32.67% (95% CI, 25.2-40.8). Age ≥ 50 years (PR = 3.17, 95% CI, 1.26-7.98) was significantly associated with T2DM; there was a positive linear trend between age and T2DM (p = 0.011). Multivariate analysis showed an association with educational level (PR = 1.49, 1.07-2.09, p = 0.018), nonconsumption of whole grains daily (PR = 1.67, 1.00-2.80, p = 0.049), and high HOMA-IR (PR = 1.54, 1.08-2.18, p = 0.016). We found a high prevalence of T2DM and no significant correlations between BMI and glycemic parameters.