Background: Malnutrition is one of the most critical health challenges confronting public health agencies in developing nations. This study aimed to determine the scope and underlying factors contributing to malnutrition in West African countries, specifically Gabon, Gambia, Liberia, Mauritania, and Nigeria.
Method: For this secondary data analysis, this study drew upon the demographic and health surveys (DHS) conducted within these West African nations. These surveys employed a complex sampling design involving a combination of stratification and cluster sampling in two stages, with varying probabilities of selection leading to weighted samples that effectively represented different components of the population. Given the intricacies of this sampling design, it is paramount to account for them when analyzing the survey data. To address this concern, this study applied a survey logistic regression model, which accommodates factors such as stratification, clustering, and sampling weights and departs from the assumption of independence inherent in the ordinary logistic regression model.
Results: The outcomes of this model revealed several variables that emerged as statistically significant (p < 0.05) determinants of malnutrition. These influential factors encompass the region of the respondent, the current age of the mother, the highest level of education attained by the mother, the source of drinking water, the type of toilet facility, the household's wealth status, the age and gender of the child, and whether the child experienced a fever in the preceding two weeks.
Conclusion: These findings demonstrate with poignant clarity the importance of primary health care interventions in the recognition and management of malnutrition. The countries of interest should invest in public health care interventions including community workshops and outreach programs. Workshops may occur at primary health care facilities during queue waits, or health workers may work with community leaders to perform workshops in areas of high foot traffic, such as places of worship, shopping hubs and collection points for financial aid or grants.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373175 | PMC |
http://dx.doi.org/10.1186/s13690-024-01374-6 | DOI Listing |
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