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Malnutrition: more than the eye can see
F C van Leth1, J M Koeleman, A S Manya
1Misikhu Mission Hospital, P.O. Box 129 Webuye, Kenya.
Insights
Hospital malnutrition is prevalent, with 44.3% of young children affected. Anthropometric measurements identified more cases than clinical diagnosis alone, highlighting the need for standardized assessments in pediatric care.
Area of Science:
- Pediatric Nutrition
- Clinical Diagnosis
- Public Health
Background:
- Malnutrition remains a significant health challenge in hospital settings, particularly affecting children under five.
- Accurate identification of malnutrition is crucial for timely intervention and improved patient outcomes.
Purpose of the Study:
- To determine the prevalence of malnutrition among hospitalized children under five.
- To compare the effectiveness of anthropometric measurements versus clinical diagnosis in identifying malnutrition.
Main Methods:
- A descriptive study was conducted at Misikhu Mission Hospital, Kenya.
- Anthropometric measures (length, weight) were collected from 1130 children under five.
- Data were analyzed using EPI-Info, calculating z-scores against NCHS growth curves.
Main Results:
- A high prevalence of malnutrition was found, affecting 44.3% of the study population.
- Only 14% of malnourished children received a clinical diagnosis of malnutrition.
- Anthropometric measurements identified a significantly larger number of malnourished children compared to clinical diagnosis.
Conclusions:
- Standardized anthropometric measurements are a valuable tool for identifying malnutrition in hospitalized children.
- Implementing routine anthropometry can improve the detection rates of malnutrition compared to clinical diagnosis alone.
- This approach can aid in better management and outcomes for malnourished children in healthcare facilities.
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.