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Published on: January 11, 2016
Risk Factors for Malnutrition Among Children With Cerebral Palsy in Botswana
Allison Johnson1, Claudia Gambrah-Sampaney1, Esha Khurana1
1University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
Insights
Malnutrition affects 43% of children with cerebral palsy in Botswana. Nonambulatory status and socioeconomic factors are key risks, identified by a new Malnutrition Risk Score.
Area of Science:
- Pediatric Nutrition
- Cerebral Palsy Research
- Global Health Disparities
Background:
- Children with cerebral palsy (CP) in low-resource settings face high malnutrition risk.
- Malnutrition exacerbates poor health outcomes in pediatric CP populations.
- Limited data exist on CP malnutrition risk factors in developing countries.
Purpose of the Study:
- To identify specific risk factors for malnutrition in children with CP in Botswana.
- To develop and validate a Malnutrition Risk Score for early identification of at-risk children.
Main Methods:
- A case-control study was conducted with 61 children with CP in Gaborone, Botswana.
- Malnutrition was defined using World Health Organization (WHO) growth curves.
- Multivariable logistic regression identified risk factors; a Malnutrition Risk Score was developed and validated using Receiver Operating Characteristic (ROC) curves.
Main Results:
- 43% of children with CP (26/61) were malnourished.
- Nonambulatory status (OR 13.8) and socioeconomic status (OR 1.6) were significant risk factors.
- The Malnutrition Risk Score demonstrated excellent performance (AUC 0.92).
Conclusions:
- Malnutrition is prevalent in children with CP in Botswana.
- A simple Malnutrition Risk Score can effectively identify high-risk individuals.
- Further validation and intervention studies are recommended.
Background:
Children with cerebral palsy in low-resource settings are at high risk of malnutrition, which further increases their risk of poor health outcomes. However, there are few available data on specific risk factors for malnutrition among children with cerebral palsy in the developing world.
Methods:
We performed a case-control study among children with cerebral palsy receiving care at a tertiary care hospital in Gaborone, Botswana. Children with cerebral palsy and malnutrition were identified according to World Health Organization growth curves and compared with subjects with cerebral palsy without malnutrition. Risk factors for malnutrition were identified using multivariable logistic regression models. These risk factors were then used to generate a Malnutrition Risk Score, and Receiver Operating Characteristic curves were used to identify optimal cutoffs to identify subjects at high risk of malnutrition.
Results:
We identified 61 children with cerebral palsy, 26 of whom (43%) met criteria for malnutrition. Nonambulatory status (odds ratio 13.8, 95% confidence interval [CI] 3.8-50.1, P < 0.001) and a composite measure of socioeconomic status (odds ratio 1.6, 95% CI 1.0-2.5, P = 0.03) were the strongest risk factors for malnutrition. A Malnutrition Risk Score was constructed based on these risk factors, and receiver operating characteristic curve analysis demonstrated excellent performance characteristics of this score (area under the curve 0.92, 95% CI 0.89-0.94).
Conclusions:
Malnutrition is common among children with cerebral palsy in Botswana, and a simple risk score may help identify children with the highest risk. Further studies are needed to validate this screening tool and to determine optimal nutritional interventions in this population.
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