Children at high risk for overweight: a classification and regression trees analysis approach.

OBJECTIVE: Early identification of children at high risk for childhood overweight is a major challenge in fighting the obesity epidemic. We tried to identify the most powerful set of combined predictors for childhood overweight at school entry. RESEARCH METHODS AND PROCEDURES: A classification and regression trees analysis on risk factors for childhood overweight in 4289 children 5 to 6 years of age participating in the obligatory school entry health examination 2001/2002 in Bavaria, Germany, was performed. Parental questionnaires asked for children's weight at birth and 2 years, breastfeeding history, maternal smoking in pregnancy, parental education, parental overweight/obesity, nationality, and number of older siblings. Overweight was defined according to sex- and age-specific BMI cut-points proposed by the International Obesity Task Force.
RESULTS: Prevalence of overweight was 11% among the entire study population. Although high early weight gain >10,000 grams was found in about one-half of the overweight children, its positive predictive value reached only 25%, indicating that one of four children with a high early weight gain is overweight at school entry. The best reliable set of predictors included high early weight gain and obese parents and accounted for a likelihood ratio of 3.6, with a corresponding positive predictive value of 40%, and was found in 4% of all children. DISCUSSION: A combination of predictors available at 2 years of age could improve predictability of overweight at school entry. However, corresponding low positive predictive values indicate a precision of the prediction that might be insufficient for targeting intervention programs for identified high-risk children.