2009East African Medical JournalOpen access

Malnutrition: More that the eye can see

FCM Van Leth, JM Koeleman, AS Manya

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Abstract

OBJECTIVES: To assess the magnitude of malnutrition in a hospital setting and to relate anthropometric measures to the clinical diagnosis of malnutrition. DESIGN: A descriptive study whereby anthropometric measures (length and weight) were taken of every child under the age of five years who was admitted to the hospital. The anthropometric data were analysed using the EPI-Info statistical package, which calculates z-scores for weight-for-age, weight-for-height and height-for-age. As reference curve, the reference growth curves of the NCHS were used. Of all the children who were classified as being malnourished, it was recorded if the clinical diagnosis of malnutrition was made at the time of admission or during the hospital stay. SETTING: Misikhu Mission Hospital, western Kenya. SUBJECTS: Every child under the age of five years who was admitted to the hospital, was eligible to enter the study. The data of 1130 children were used. The data of 40 other children who were admitted in this period were not complete and could therefore not be used. RESULTS: An overall percentage for malnutrition of 44.3 was found. Only fourteen per cent of the malnourished children were clinically diagnosed as having malnutrition. CONCLUSION: Anthropometric measures are an easy, but time-consuming way of identifying children with malnutrition, it identifies more children with malnutrition than clinical diagnosis alone. Therefore it should be considered to implement standardised anthropometry in a hospital setting.

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OBJECTIVES: To assess the magnitude of malnutrition in a hospital setting and to relate anthropometric measures to the clinical diagnosis of malnutrition. DESIGN: A descriptive study whereby anthropometric measures (length and weight) were taken of every child under the age of five years who was admitted to the hospital. The anthropometric data were analysed using the EPI-Info statistical package, which calculates z-scores for weight-for-age, weight-for-height and height-for-age. As reference curve, the reference growth curves of the NCHS were used. Of all the children who were classified as being malnourished, it was recorded if the clinical diagnosis of malnutrition was made at the time of admission or during the hospital stay. SETTING: Misikhu Mission Hospital, western Kenya. SUBJECTS: Every child under the age of five years who was admitted to the hospital, was eligible to enter the study. The data of 1130 children were used. The data of 40 other children who were admitted in this period were not complete and could therefore not be used. RESULTS: An overall percentage for malnutrition of 44.3 was found. Only fourteen per cent of the malnourished children were clinically diagnosed as having malnutrition. CONCLUSION: Anthropometric measures are an easy, but time-consuming way of identifying children with malnutrition, it identifies more children with malnutrition than clinical diagnosis alone. Therefore it should be considered to implement standardised anthropometry in a hospital setting.

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Available abstract

OBJECTIVES: To assess the magnitude of malnutrition in a hospital setting and to relate anthropometric measures to the clinical diagnosis of malnutrition. DESIGN: A descriptive study whereby anthropometric measures (length and weight) were taken of every child under the age of five years who was admitted to the hospital. The anthropometric data were analysed using the EPI-Info statistical package, which calculates z-scores for weight-for-age, weight-for-height and height-for-age. As reference curve, the reference growth curves of the NCHS were used. Of all the children who were classified as being malnourished, it was recorded if the clinical diagnosis of malnutrition was made at the time of admission or during the hospital stay. SETTING: Misikhu Mission Hospital, western Kenya. SUBJECTS: Every child under the age of five years who was admitted to the hospital, was eligible to enter the study. The data of 1130 children were used. The data of 40 other children who were admitted in this period were not complete and could therefore not be used. RESULTS: An overall percentage for malnutrition of 44.3 was found. Only fourteen per cent of the malnourished children were clinically diagnosed as having malnutrition. CONCLUSION: Anthropometric measures are an easy, but time-consuming way of identifying children with malnutrition, it identifies more children with malnutrition than clinical diagnosis alone. Therefore it should be considered to implement standardised anthropometry in a hospital setting.

Key concepts: Malnutrition, Anthropometry, Medicine, Pediatrics, Weight for Age, Malnutrition in children, Internal medicine

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