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Who is the child at risk?
A A Kielmann1, D Neuvians, F D Mtango
1Department of Food Technology and Nutrition, University of Nairobi, Kenya.
Insights
A nutrition survey in rural Tanzania found low malnutrition rates. Key factors influencing child nutrition included household size, parental care, and village of residence, highlighting areas for targeted intervention.
Area of Science:
- Child Nutrition
- Public Health
- Rural Development
Background:
- Baseline data collection for a nutrition intervention program in Bagamoyo, Tanzania.
- Assessing preschool child nutritional status and identifying at-risk individuals.
- Understanding socio-economic and community factors influencing child health.
Purpose of the Study:
- Establish a baseline for evaluating a nutrition intervention program.
- Identify children at risk of malnutrition.
- Analyze factors affecting preschool nutritional status in rural Tanzania.
Main Methods:
- Cross-sectional survey in eleven randomly selected villages.
- Collection of anthropometric measurements and socio-community variables.
- Multiple linear regression analysis to identify significant correlations.
Main Results:
- Relatively low prevalence of malnutrition compared to other developing regions.
- Significant negative correlations: child's age, household size, child mortality, paternal care, village of residence.
- Significant positive correlations: birth weight, breastfeeding, milk supplementation, sibling/nanny care.
Conclusions:
- Village of residence emerged as a critical factor influencing nutritional status.
- Further research is needed to pinpoint specific village-level variables for intervention optimization.
- Findings provide a foundation for targeted nutrition interventions in the region.
Abstract:
Prior to the establishment of a nutrition intervention programme in the Bagamoyo district of rural Tanzania, all children residing in eleven randomly selected villages were weighted and a number of social and community variables collected. The survey served the dual purpose of providing a baseline to subsequently measure programme impact and identifying the child at risk of becoming malnourished. Despite the survey being carried out during a season of relative scarcity of food, results suggest a relatively benign level of malnutrition in relation to other regions of Subsaharan Africa or other developing countries. Age, the total number of children per household, the proportion of child deaths in the family, paternal care, and residence in specific villages showed statistically significant negative correlations with preschool nutritional status. Apart from residence in specific villages, birth weight, breast-feeding status, supplementation with milk and care of the child in the absence of the mother by a sibling or "nanny" provided positive correlations. The fact that residence in certain villages was associated with highly significant positive or negative effects on preschool child nutrition, as revealed by multiple linear regression analyses, suggests that further research into identification of the precise nature of these variables is required before optimization of an intervention package may be achieved.