Objective: To evaluate energy balance and physical activity in obese preschool children attending day-care centres. Design: Cross-sectional study. Subjects: Twenty-four 3-5 years old obese children selected at random from four different day-care centres in Santiago City, Chile. Total energy expenditure (TEE) was measured by doubly labelled water and physical activity as recorded by TRITRAC R3D motion sensor. Energy intake was assessed by measuring food intake while at the centre, along with the recording of additional food intake in the home. Results: Obese children had a 5.4% higher weighed energy intake than their energy requirements 2001. Energy intake during the week was 771671092 kJ/day and 740171023 kJ/day in boys and girls, respectively. Minimal activity was higher in the daycare centres (62%) compared to 52% during the weekend at home. Light activity was higher during the weekend at home than during the week (25 versus 20%), but moderate-intense activity was similar (3-5%). Conclusions: Reduction in dietary energy provided at the day-care centres helps to balance energy requirements during the week. Obese children had marked sedentary characteristics with regards to physical activity, although children are more active at home in weekends. This situation suggests that educators and parents need to improve children's physical activity levels and nutrition habits.

Background: We aimed to determine the sensitivity and specificity of selected anthropometric indicators as predictors of cardiovascular risk in adolescents. Methods: Cross-sectional study in 678 adolescents (16.8y ± 0.3) from an infancy cohort. Weight, height, waist circumference (WC) and hip circumference were measured. Body-Mass Index (BMI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) were estimated. MetS was diagnosed with IDF/AHA/NHLBI. Optimal cutoffs of BMI, WC, WHR and WHtR for diagnosing MetS were determined using ROC analysis. Results: In males, WHtR (0.96) had the greatest area under the ROC curve, followed by WC (0.95) and BMI (0.93). In females, BMI (0.84) had the greatest area under the ROC curve (0.84), followed by WHtR (0.83) and WC (0.83). In both sexes, the optimal WHtR cutoff for MetS diagnosis was 0.54. A BMI of 26.9 in males and 26.3 in females were the optimal cutoffs for diagnosing MetS. Finally, WC values of 92 and 81.6 cm in males and females, respectively, were the optimal cutoffs for MetS diagnosis. Conclusions: In both sexes, a WHtR value of 0.54 was a good predictor of MetS. In males and females, the optimal cutoff of BMI for Mets diagnosis was below the values for diagnosing obesity.

Relationship between anthropometrical indicators of adiposity and cardiometabolic markers becomes stronger from 7 years onwards; BAZ, WC and WHtR perform similarly as markers of cardiometabolic risk at least until 10 years of age.

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Multivariate Adaptive Regression Splines (MARS) is a non-parametric modelling method that extends the linear model, incorporating nonlinearities and interactions between variables. It is a flexible tool that automates the construction of predictive models: selecting relevant variables, transforming the predictor variables, processing missing values and preventing overshooting using a self-test. It is also able to predict, taking into account structural factors that might influence the outcome variable, thereby generating hypothetical models. The end result could identify relevant cut-off points in data series. It is rarely used in health, so it is proposed as a tool for the evaluation of relevant public health indicators. For demonstrative purposes, data series regarding the mortality of children under 5 years of age in Costa Rica were used, comprising the period 1978-2008.