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Mukuku O, Mutombo AM, Kamona LK, et al. Predictive Model for the Risk of Severe Acute Malnutrition in Children. J Nutr Metab. 2019;2019:4740825doi: 10.1155/2019/4740825.
Mukuku, O., Mutombo, A. M., Kamona, L. K., Lubala, T. K., Mawaw, P. M., Aloni, M. N., Wembonyama, S. O., & Luboya, O. N. (2019). Predictive Model for the Risk of Severe Acute Malnutrition in Children. Journal of nutrition and metabolism, 20194740825. https://doi.org/10.1155/2019/4740825
Mukuku, Olivier, et al. "Predictive Model for the Risk of Severe Acute Malnutrition in Children." Journal of nutrition and metabolism vol. 2019 (2019): 4740825. doi: https://doi.org/10.1155/2019/4740825
Mukuku O, Mutombo AM, Kamona LK, Lubala TK, Mawaw PM, Aloni MN, Wembonyama SO, Luboya ON. Predictive Model for the Risk of Severe Acute Malnutrition in Children. J Nutr Metab. 2019 Jul 01;2019:4740825. doi: 10.1155/2019/4740825. eCollection 2019. PMID: 31354989; PMCID: PMC6636463.
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J Nutr Metab. 2019 Jul 01;2019:4740825. doi: 10.1155/2019/4740825. eCollection 2019.

Predictive Model for the Risk of Severe Acute Malnutrition in Children.

Journal of nutrition and metabolism

Olivier Mukuku, Augustin Mulangu Mutombo, Lewis Kipili Kamona, Toni Kasole Lubala, Paul Makan Mawaw, Michel Ntetani Aloni, Stanislas Okitotsho Wembonyama, Oscar Numbi Luboya

Affiliations

  1. Department of Research, Institut Supérieur des Techniques Médicales, Lubumbashi, Democratic Republic of the Congo.
  2. Department of Pediatrics, University Hospital of Lubumbashi, University of Lubumbashi, Lubumbashi, Democratic Republic of the Congo.
  3. School of Public Health, University of Lubumbashi, Lubumbashi, Democratic Republic of the Congo.
  4. Division of Hemato-oncology and Nephrology, Department of Pediatrics, University Hospital of Kinshasa, School of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.

PMID: 31354989 PMCID: PMC6636463 DOI: 10.1155/2019/4740825

Abstract

BACKGROUND: The nutritional status is the best indicator of the well-being of the child. Inadequate feeding practices are the main factors that affect physical growth and mental development. The aim of this study was to develop a predictive score of severe acute malnutrition (SAM) in children under 5 years of age.

METHODS: It was a case-control study. The case group (

RESULTS: Low birth weight, history of recurrent or chronic diarrhea, daily meal's number less than 3, age of breastfeeding's cessation less than 6 months, age of introduction of complementary diets less than 6 months, maternal age below 25 years, parity less than 5, family history of malnutrition, and number of children under 5 over 2 were predictive factors of SAM. Presence of these nine criteria affects a certain number of points; a score <6 points defines children at low risk of SAM, a score between 6 and 8 points defines a moderate risk of SAM, and a score >8 points presents a high risk of SAM. The area under ROC curve of this score was 0.9685, its sensitivity was 93.5%, and its specificity was 93.1%.

CONCLUSION: We propose a simple and efficient prediction model for the risk of occurrence of SAM in children under 5 years of age in developing countries. This predictive model of SAM would be a useful and simple clinical tool to identify people at risk, limit high rates of malnutrition, and reduce disease and child mortality registered in developing countries.

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