Predictive Model for the Risk of Severe Acute Malnutrition in Children
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...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Journal of Nutrition and Metabolism |
| Online Access: | http://dx.doi.org/10.1155/2019/4740825 |
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| author | Olivier Mukuku Augustin Mulangu Mutombo Lewis Kipili Kamona Toni Kasole Lubala Paul Makan Mawaw Michel Ntetani Aloni Stanislas Okitotsho Wembonyama Oscar Numbi Luboya |
| author_facet | Olivier Mukuku Augustin Mulangu Mutombo Lewis Kipili Kamona Toni Kasole Lubala Paul Makan Mawaw Michel Ntetani Aloni Stanislas Okitotsho Wembonyama Oscar Numbi Luboya |
| author_sort | Olivier Mukuku |
| collection | DOAJ |
| description | 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 < −3 SD or presence of edema of malnutrition. We performed a univariate and multivariate analysis. Discrimination score was assessed using the ROC curve and the calibration of the score by Hosmer–Lemeshow test. 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. |
| format | Article |
| id | doaj-art-66b3e26ce30d464ca07a32f8b2ebd5f1 |
| institution | Kabale University |
| issn | 2090-0724 2090-0732 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Nutrition and Metabolism |
| spelling | doaj-art-66b3e26ce30d464ca07a32f8b2ebd5f12025-02-03T01:10:07ZengWileyJournal of Nutrition and Metabolism2090-07242090-07322019-01-01201910.1155/2019/47408254740825Predictive Model for the Risk of Severe Acute Malnutrition in ChildrenOlivier Mukuku0Augustin Mulangu Mutombo1Lewis Kipili Kamona2Toni Kasole Lubala3Paul Makan Mawaw4Michel Ntetani Aloni5Stanislas Okitotsho Wembonyama6Oscar Numbi Luboya7Department of Research, Institut Supérieur des Techniques Médicales, Lubumbashi, Democratic Republic of the CongoDepartment of Pediatrics, University Hospital of Lubumbashi, University of Lubumbashi, Lubumbashi, Democratic Republic of the CongoDepartment of Pediatrics, University Hospital of Lubumbashi, University of Lubumbashi, Lubumbashi, Democratic Republic of the CongoDepartment of Pediatrics, University Hospital of Lubumbashi, University of Lubumbashi, Lubumbashi, Democratic Republic of the CongoSchool of Public Health, University of Lubumbashi, Lubumbashi, Democratic Republic of the CongoDivision of Hemato-oncology and Nephrology, Department of Pediatrics, University Hospital of Kinshasa, School of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the CongoDepartment of Pediatrics, University Hospital of Lubumbashi, University of Lubumbashi, Lubumbashi, Democratic Republic of the CongoDepartment of Research, Institut Supérieur des Techniques Médicales, Lubumbashi, Democratic Republic of the CongoBackground. 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 < −3 SD or presence of edema of malnutrition. We performed a univariate and multivariate analysis. Discrimination score was assessed using the ROC curve and the calibration of the score by Hosmer–Lemeshow test. 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.http://dx.doi.org/10.1155/2019/4740825 |
| spellingShingle | Olivier Mukuku Augustin Mulangu Mutombo Lewis Kipili Kamona Toni Kasole Lubala Paul Makan Mawaw Michel Ntetani Aloni Stanislas Okitotsho Wembonyama Oscar Numbi Luboya Predictive Model for the Risk of Severe Acute Malnutrition in Children Journal of Nutrition and Metabolism |
| title | Predictive Model for the Risk of Severe Acute Malnutrition in Children |
| title_full | Predictive Model for the Risk of Severe Acute Malnutrition in Children |
| title_fullStr | Predictive Model for the Risk of Severe Acute Malnutrition in Children |
| title_full_unstemmed | Predictive Model for the Risk of Severe Acute Malnutrition in Children |
| title_short | Predictive Model for the Risk of Severe Acute Malnutrition in Children |
| title_sort | predictive model for the risk of severe acute malnutrition in children |
| url | http://dx.doi.org/10.1155/2019/4740825 |
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