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 BMI = weight푘푘푘푘 height푚푚! Of each child the PI and BMI were plotted against age and a regression line (y = αt + c) was drawn representing the individual change of growth in time (Figure 1). The slope of the regression line, expressed as the individual alpha PI (αPI ind) or alpha BMI (αBMI ind), estimates the growth velocity of the child while the constant value of c indicates the PI or BMI at t0. Thus αPI ind represents the growth velocity from birth until the age of 1 year, αBMI ind represents the growth velocity from the age of 1 year until the age of 4 years. Figure 1: Example of an individual child; the individual BMI is plotted against age. The value of αPI ind or αBMI ind depends on the PI or BMI at t0, this means that a high value of PI or BMI at t0 will result in a lower α and a low value of PI or BMI at t0 in a higher α. This phenomenon is known as the regression to the mean17. Next, all αPI ind and all αBMI ind values were plotted against all individual values of PI at birth and BMI at the age of 1 year respectively. Regression lines were calculated, based on the corresponding α values, representing the total child population (α tot). The expected value of the PI (PIe) and BMI (BMIe) at a certain age can be estimated according to the formulas: 79
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