In a cross-sectional study, children 0-6 yr of age from eight different population groups in Africa and Asia were examined. Clinical assessment defined 8750 children as being well nourished and 194 as having marasmus. Height, weight, arm circumference (AC), and triceps skinfold thickness were measured; the latter two measurements and the clinical assessment were done by the same observer. Based on data from normal children, local growth curves were computed for each group. Each child's growth was expressed in standard deviation scores (SDS) of his own group. On the basis of the results of a discriminant analysis, all variables were ranked by their decreasing power to discriminate between normal and marasmic children. For 83% of the children one measurement (AC/age) is sufficient to classify them definitely; for the others several variables are needed. This strategy yields an overall sensitivity of 80%, a specificity of 97%, and a positive predictive value of 38%.
PIP: The definition of a malnourished child is commonly based on anthropometric measurements. In order to define an optimal selection procedure, this study uses a discriminant analysis to choose the most appropriate anthropometric variables for distinguishing clinically defined marasmic children from clinically normal children. This selection procedure would be a better alternative for routine practice in health clinics than the commonly used procedures of weight for age or weight for height. In a cross-sectional study, children 0-6 years of age from 8 different population groups in Africa and Asia were examined. Clinical assessment defined 8750 children as being well nourished and 194 as having marasmus. Height, weight, arm circumference, and triceps skinfold thickness were measured; the latter 2 measurements and the clinical assessment were done by the same observer. Based on data from normal children, local growth curves were computed for each group. Each child's growth expressed in standard deviation scores of his own group. On the basis of the results of a discriminant analysis, all variables were ranked by their decreasing power to discriminate between normal and marasmic children. For 83% of the children 1 measurement (arm circumference/age) is sufficient to classify them definitely; for the others, several variables are needed. This strategy yields an overall sensitivity of 80%, a specificity of 97%, and a positive predictive value of 38%. Developing countries, where scarcity of resources is a daily reality, need uniformly efficient selection procedures in order to tackle their very common problem: marasmus. Using the clinical definition of marasmus as a substitute for morbidity and mortality, the proposed selection procedure is able to select children at risk with high sensitivity and a very low number of false positives.