Academic Journal
Predictive Model for the Risk of Severe Acute Malnutrition in Children
العنوان: | Predictive Model for the Risk of Severe Acute Malnutrition in Children |
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المؤلفون: | Olivier Mukuku, Augustin Mulangu Mutombo, Lewis Kipili Kamona, Toni Kasole Lubala, Paul Makan Mawaw, Michel Ntetani Aloni, Stanislas Okitotsho Wembonyama, Oscar Numbi Luboya |
المصدر: | Journal of Nutrition and Metabolism, Vol 2019 (2019) |
بيانات النشر: | Hindawi Limited, 2019. |
سنة النشر: | 2019 |
المجموعة: | LCC:Nutritional diseases. Deficiency diseases |
مصطلحات موضوعية: | Nutritional diseases. Deficiency diseases, RC620-627 |
الوصف: | 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 (n = 263) consisted of children aged 6 to 59 months admitted to hospital for SAM that was defined by a z-score weight/height 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. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 2090-0724 2090-0732 |
Relation: | https://doaj.org/toc/2090-0724; https://doaj.org/toc/2090-0732 |
DOI: | 10.1155/2019/4740825 |
URL الوصول: | https://doaj.org/article/66b3e26ce30d464ca07a32f8b2ebd5f1 |
رقم الانضمام: | edsdoj.66b3e26ce30d464ca07a32f8b2ebd5f1 |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 20900724 20900732 |
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DOI: | 10.1155/2019/4740825 |