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(SECA861, Schinkel, Nieuwegein, the Netherlands). Weight and height were used to calculate BMI (kg/m2). For the calculation of BMI standard deviation scores (BMIsds) or z-scores, a reference database of Dutch children was used (www.growthanalyser.org; version 3.5). Waist circumference was measured and recorded with a flexible band to an accuracy of 0.1 cm. Body composition was assessed by Dual Energy X-ray Absorptiometry (DXA; Hologic QDR4500-Delphi, Tromp Medical, Castricum, The Netherlands). A standard oral glucose tolerance test was performed by a research nurse (3). Baseline samples were obtained for measurement of fasting glucose, fasting insulin and lipids. Glucose was given orally (1.75 g/kg body weight, up to a maximum of 75 g glucose). Blood samples were drawn after 30 and 120 minutes. Prediabetes was defined according the American Diabetes Association (ADA) guidelines as impaired fasting glucose (IFG 5.6–6.9 mmol/l) and/or impaired glucose tolerance (IGT 7.8–11.1 mmol/l) (15). Insulin resistance was estimated by the homeostatic model assessment (HOMA-IR=(fasting insulin in mU/l x fasting glucose in mmol/l)/22.5). Systolic and diastolic blood pressures were measured at the left arm after a 10-min rest in the supine position.
The metabolic syndrome was defined following IDF guidelines (16). For adolescents aged 10 years or older the metabolic syndrome is diagnosed when waist circumference is above the 90th percentile (17) in combination with the presence of 2 or more clinical features (fasting triglycerides >1.7 mmol/l; fasting HDL <1.03 mmol/l; blood pressure >130 mmHg systolic or >85 mmHg diastolic; fasting glucose >5.6 mmol/l). For adolescents aged 16 years and older, the adult IDF criteria were used. The adult definition is the same as for children, except for fasting HDL in females (fasting HDL <1.29).
Statistics
Baseline characteristics were analysed by t-test for continuous variables and Chi-square test for categorical variables. Group comparisons were performed according the intention-to-treat principle whereby all subjects were analyzed in the group to which they were randomly assigned. Linear mixed models were applied to assess the effect of the intervention over time. A random intercept and a random slope with time were assumed. Age-, sex- and, ethnicity adjusted analyses were performed with intervention as categorical variable and time as a continuous variable, with an interaction term for intervention and time. B coefficients, 95% confidence intervals, and p-values were calculated. This approach increases statistical power as it accounts for within-person correlations over time and includes all assessments, at baseline as well as at 6 and 18 months. A p-value of <0.05 was considered statistically significant. Effect modification by sex, age and ethnicity was checked by adding an interaction term between group allocation and the potential moderator. A p-value of <0.10 was considered statistically significant. In case effect modification was found,
Effectiveness of Go4it
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