T H E U S E O F A P R E D I C T I O N M O D E L T O P R E V E N T A B N O R M A L W E I G H T I N C H I L D H O O D I N T H E Y O U T H H E A L T H C A R E P R A C T I C E Discussion The prediction model we describe assumes that the expected growth pattern of an individual child can already be used in the first year of life as an indication for fu-‐ ture trend in growth. In this early period, mainly genetic, nutritional and some be-‐ havioral factors (like crawling and walking) will determine the development of overweight. This study shows that the calculation of PI appears to be a better tool to detect and diagnose overweight than using the weight for length growth charts. To predict overweight at the age of 5 years, the best method appears to be the pre-‐ diction model, followed by the calculation of PI. Using the weight for length growth chart appears to be the poorest predictor for overweight by comparing these 3 methods. The sensitivity, specificity and the diagnostic odds ratios of these 3 meth-‐ ods (Tables 1-‐3) confirm this statement. The specificity of our prediction model is lower than the other methods, but the sensitivity is much higher. By using the pre-‐ diction model, in 16% of all cases a child may be wrongly appointed to become overweight and parents may receive redundant advices to prevent overweight. In 54% of all cases a child with an overweight risk will be missed. Compared to the weight for length growth chart and PI calculation (84% and 72% resp.), this is a much lower percentage. To avoid methodological complications, we calculated the diagnostic odds ratio, besides the sensitivity and specificity. The diagnostic odds ratio has the advantage to be less sensitive for changes in composition of the study population. It summarizes the diagnostic test performance. The diagnostic odds ratio is higher in our prediction model than in the other 2 methods. The higher the diagnostic odds ratio, the higher the discriminant power of the model. By applying the prediction model, more parents of children with an overweight risk will be warned. Several studies tried to find parameters to predict overweight in childhood. Steur et al found that there are several characteristics that are available at birth, which are predictors of overweight. These characteristics are: Paternal and maternal BMI, female gender, smoking in the parental house, birth weight and hospital delivery14. Reilly et al identified 8 risk factors in early life (up to 3 years of age) for obesity: Paternal obesity, very early (43 months) BMI or adiposity rebound, more than 8 hours watching television per week at the age of 3 years, catch-‐up growth, standard deviation scores (highest quarter) at 8 and 18 months, weight gain in the first year, birth weight and short (< 10.5 hours) sleep duration at the age of 3 years15. Also promoting breastfeeding is important in the prevention of overweight, as Arm-‐ strong found that breastfeeding is associated with a reduction in childhood obesity risk16. Tamayo stated that a low childhood socioeconomic status (SES) is a risk factor for overweight and obesity later in life17. All these predictors can be useful in the prevention of overweight by health care physicians. If these risk factors are taken into account at an early age and discussed with parents, it is possible to con-‐ 99
Proefschrift binnenwerk Manon Ernst_DEF.indd
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