BackgroundThis pragmatic evaluation investigated the effectiveness of the Children’s Health, Activity and Nutrition: Get Educated! (CHANGE!) Project, a cluster randomised intervention to promote healthy weight using an educational focus on physical activity and healthy eating.MethodsParticipants (n = 318, aged 10–11 years) from 6 Intervention and 6 Comparison schools took part in the 20 weeks intervention between November 2010 and March/April 2011. This consisted of a teacher-led curriculum, learning resources, and homework tasks. Primary outcome measures were waist circumference, body mass index (BMI), and BMI z-scores. Secondary outcomes were objectively-assessed physical activity and sedentary time, and food intake. Outcomes were assessed at baseline, at post-intervention (20 weeks), and at follow-up (30 weeks). Data were analysed using 2-level multi-level modelling (levels: school, student) and adjusted for baseline values of the outcomes and potential confounders. Differences in intervention effect by subgroup (sex, weight status, socio-economic status) were explored using statistical interaction.ResultsSignificant between-group effects were observed for waist circumference at post-intervention (β for intervention effect =−1.63 (95% CI = −2.20, -1.07) cm, p<0.001) and for BMI z-score at follow-up (β=−0.24 (95% CI = −0.48, -0.003), p=0.04). At follow-up there was also a significant intervention effect for light intensity physical activity (β=25.97 (95% CI = 8.04, 43.89) min, p=0.01). Interaction analyses revealed that the intervention was most effective for overweight/obese participants (waist circumference: β=−2.82 (95% CI = −4.06, -1.58) cm, p<0.001), girls (BMI: β=−0.39 (95% CI = −0.81, 0.03) kg/m2, p=0.07), and participants with higher family socioeconomic status (breakfast consumption: β=8.82 (95% CI = 6.47, 11.16), p=0.07).ConclusionsThe CHANGE! intervention positively influenced body size outcomes and light physical activity, and most effectively influenced body size outcomes among overweight and obese children and girls. The findings add support for the effectiveness of combined school-based physical activity and nutrition interventions. Additional work is required to test intervention fidelity and the sustained effectiveness of this intervention in the medium and long term.Trial registrationCurrent Controlled Trials ISRCTN03863885.

Additionally, CHO intake in U18s was lower (P<0.05) at breakfast, dinner and snacks 56 when compared with both squads but no differences were apparent at lunch. 57Furthermore, the U15/16s reported lower relative daily protein intake than the 58 U13/14s and U18s (1.6±0.3 vs. 2.2±0.5, 2.0±0.3 g·kg -1 ). A skewed distribution 59 (P<0.05) of daily protein intake was observed in all squads, with a hierarchical order 60 of dinner (~0.6 g·kg -1 ) > lunch (~0.5 g·kg -1 ) > breakfast (~0.3 g·kg -1 ). We conclude 61 elite youth soccer players do not meet current CHO guidelines. Although daily protein 62 targets are achieved, we report a skewed daily distribution in all ages such that 63 dinner>lunch>breakfast. Our data suggest that dietary advice for elite youth players 64 should focus on both total daily macronutrient intake and optimal daily distribution 65 patterns. al., 2015). These studies have typically been limited to reports of total daily energy 80and macronutrient intake, often concluding that elite youth soccer players habitually 81 don't meet their energy requirements (Boisseau et al. 2002; LeBlanc et al., 2002; Ruiz 82 et al., 2005;Russell and Pennock, 2011; Briggs et al., 2015). 83In addition to the quantification of daily energy and macronutrient intake, it is 84 important to consider timing of intake in relation to training sessions (Burke, 2010; 85 Mori, 2014), main meals (Garaulet and Gomez-Abellan, 2014; Johnston, 2014) and 86 sleep (Lane et al., 2015). Whilst this is most well documented for carbohydrate 87 (CHO) intake in order to fuel training and matches (Goedecke et al., 2013; 88 Jeukendrup, 2014) and promote glycogen re-synthesis (Zehnder et al., 2001; 89 Gunnarsson et al., 2013), recent data suggests that the daily distribution of protein 90 intake is critical for optimizing components of training adaptations such as muscle 91 protein synthesis (MPS) (Areta et al., 2013; Mamerow et al., 2014). Recent data has 92 highlighted the importance of quantity and timing of protein intake in elite youth 93 soccer players. Milsom et al. (2015) demonstrated that such populations typically 94 Therefore, the aims of the present study were two-fold: 1) to quantify the total daily 101 energy and macronutrient intakes of elite youth UK academy players of different ages 102 (U13/14, U15/16 and U18 playing squads) and 2) to quantify the daily distribution of 103 energy and macronutrient intake. In accordance with the higher absolute body masses 104 and training loads of the U18 squads (Wrigley et al., 2012), we hypothesised that this 105 squad would report higher absolute daily energy and macronutrient intakes in 106 comparison to the U13/14s and U15/16s. Furthermore, based on the habitual eating 107 patterns of both athletic and non-athletic populations (Mamerow et al., 2014), we 108 hypothesised that all squads would report an uneven daily distribution of 109 macronutrient intakes, particularly for daily protein intake. 110 Methodology 111 Participants 112Elite youth soccer players were recruited ...

The reduction in fasting TG concentration (but not waist circumference) was the only significant predictor of MTS change. Fasting TG may be the most important metabolic syndrome component to best characterize the metabolic heterogeneity in obese cohorts and the changes in metabolic risk in clinically obese youth.

Worldwide type 2 diabetes (T2D) prevalence is increasing dramatically. The present study aimed to evaluate the association between dietary habits and T2D in an Iranian adult population using a cross-sectional analysis of the Shahedieh cohort study. Participants were adults aged 35–70 years (n 9261) from Zarch and Shahedieh, Yazd, Iran, who attended the baseline phase of the Shahedieh cohort study. Dietary habits including meal frequency, fried-food consumption, adding salt to prepared meals and grilled-food consumption were assessed by a standard questionnaire. T2D was defined as fasting plasma glucose (FPG) ≥126 mg/dl according to the American Diabetes Association. Multiple logistic regression assessed the association between dietary habits and T2D. Individuals who consumed a meal more than six times per day compared to three times per day had greater odds for T2D (OR 2⋅503, 95 % CI 1⋅651, 3⋅793). These associations remained significant in a fully adjusted model. There was a significant association between greater intakes of fried foods and prevalence of T2D (OR 1⋅294, 95 % CI 1⋅004, 1⋅668) in the adjusted model. No significant associations were observed between other dietary habits (adding salt to prepared meals and grilled-food consumption) and odds of T2D in all crude and adjusted models. In conclusion, we have highlighted the association between meal and fried-food consumption frequencies with risk of T2D. Large longitudinal studies in different ethnicities are needed to confirm these associations.

Background Psychological disorders including depression, anxiety, and stress comprise a huge public health problem. The aim of this cross-sectional study is to assess the relationship between dietary glycemic index (DGI) and glycemic load (DGL) and mental disorders. Method Participants (n = 10,000) aged 20–69 were randomly selected from 200 clusters in Yazd from the recruitment phase of Yazd Health Study. The dietary intake of study participants was collected by a reliable and validated food frequency questionnaire consisting of 178 food items. DGI and DGL were calculated from the FFQ data using previously published reference values. To assess psychological disorders an Iranian validated short version of a self-reported questionnaire Depression Anxiety Stress Scales 21 was used. Results There were no significant associations between DGI and DGL with odds of depression or anxiety in crude and adjusted models. However, individuals in the highest quartiles of DGL had the lowest odds of stress (OR: 0.69; 95% CI 0.47–1, P-trend = 0.023). This association remained significant after adjustment for potential confounding variables in model I (OR: 0.45; 95% CI 0.22–0.9, P-trend = 0.023), model II (OR: 0.46; 95% CI 0.22–0.96, P-trend = 0.039) and model III (OR: 0.46; 95% CI 0.22–0.96, P-trend = 0.042). Conclusion In conclusion, consumption of foods with higher GL was associated with lower odds of stress; however, no significant association was found between DGI or DGL and risk of depression and anxiety. Performing further studies with longitudinal design is suggested to confirm these results.