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Abstract:
Undernutrition and child food poverty constitute a critical public health problem, particularly in the context of climate change. However, evidence on the links between climate and nutrition outcomes is not sufficiently available. The objectives of this study were to (1) examine the impacts of climate change on undernutrition and child food poverty and (2) apply geostatistical models to produce maps of undernutrition and child food poverty prevalences in Burkina Faso to identify hotspots more accurately.
The study utilized geostatistical modeling through data from the 2021 Burkina Faso Demographic and Health Survey, supplemented by remote-sensed information (covariates), to improve estimates of stunting, wasting, and child food poverty prevalences. Geostatistical models were developed at the cluster level considering all spatial and nonspatial covariates. Additionally, two models were developed for each individual covariate—one model assuming and the other not assuming the spatial locations of the clusters.
Results showed that the enhanced vegetation index (EVI), which takes several climate variables into account, was very strongly associated with wasting and stunting but was not associated with child food poverty. Positive associations were found between stunting prevalence and both low maternal education and open defecation. Wasting prevalence was associated with open defecation, and child food poverty was associated with maternal education and richer wealth quintiles. The maps showed that certain locations in Sahel, Centre Nord, and Est regions were at greater risk of stunting and wasting than other locations, as the maps made it possible to visualize intercluster disparities. We also validated the model, showing correlations between observed and predicted prevalences.
Through this study, we demonstrated the relationship between climate and undernutrition. This calls for the integration of climate considerations into nutrition commitments. We also demonstrated the value of applying geostatistical analyses to identify pockets of concentrated undernutrition and child food poverty to better guide intervention strategies. These methodologies present an opportunity for predicting the prevalences of stunting, wasting, and child food poverty in areas where access to traditional nutrition surveys is problematic.
Impact of Climate on Undernutrition and Child Food Poverty: Geostatistical Modeling Using Data From the 2021 Burkina Faso Demographic and Health Survey (PDF, 2151K)