Screening for marasmus: a discriminant analysis as a guide to choose the anthropometric variables

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 measur...

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Veröffentlicht in:The American journal of clinical nutrition 1987-02, Vol.45 (2), p.488-493
Hauptverfasser: Van Loon, H, Saverys, V, Vuylsteke, J P, Vlietinck, R F, Van den Berghe, H
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container_issue 2
container_start_page 488
container_title The American journal of clinical nutrition
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creator Van Loon, H
Saverys, V
Vuylsteke, J P
Vlietinck, R F
Van den Berghe, H
description 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%. 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
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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%. 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. 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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. 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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%. 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.</abstract><cop>Bethesda, MD</cop><pub>Elsevier Inc</pub><pmid>3101482</pmid><doi>10.1093/ajcn/45.2.488</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record>
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subjects Africa
Age Factors
Anthropometry
Anthropometry - methods
Arm - anatomy & histology
Asia
Biological and medical sciences
Biology
Body Weight
Child
Child Development
Child, Preschool
Deficiency Diseases
Developing Countries
DIAGNOSTIC
DIAGNOSTICO
Diseases
ERGONOMIA
ERGONOMIE
Female
Growth
Health
Humans
Infant
Infant, Newborn
Male
MALNUTRICION
MALNUTRITION
Measurement
Medical sciences
Metabolic diseases
NORMAS
NORME
Nutrition
Nutrition Disorders
Nutrition Indexes
Other nutritional diseases (malnutrition, nutritional and vitamin deficiencies...)
Physiology
Population
Protein-Energy Malnutrition - diagnosis
Research Methodology
Research Report
Statistics as Topic
title Screening for marasmus: a discriminant analysis as a guide to choose the anthropometric variables
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