Drivers of change in weight-for-height among children under 5 years of age in Ethiopia: Risk factors and data gaps to identify risk factors.
Meron GirmaAlemayehu HusseinKaleab BayeAregash SamuelCornelia van ZylMasresha TessemaStanley ChitekweArnaud LaillouPublished in: Maternal & child nutrition (2022)
The prevention of wasting should be a public health priority as the global burden of acute malnutrition is still high. Gaps still exist in our understanding of context-specific risk factors and interventions that can be implemented to prevent acute malnutrition. We used data from the four rounds of the Ethiopia Demographic and Health Survey (2000-2016) to identify risk factors that have contributed to the change in weight-for-height z-score (WHZ) among children under 5 years of age. We performed a pooled linear regression analysis followed by a decomposition analysis to identify relevant risk factors and their relative contribution to the change in WHZ. Modest improvements in WHZ were seen between 2000 and 2016. The sharpest decrease in mean WHZ occurred from birth to 6 months of age. Perceived low weight at birth and recent diarrhoea predicted a decline in WHZ among children aged 0-5, 6-23 and 23-59 months. Less than 50% of the change in WHZ was accounted for by the change in risk factors included in our regression decomposition analysis. This finding highlights data gaps to identify context-specific wasting risk factors. The decline in the prevalence of recent diarrhoea (15% of the improvement), decline in low birth size (7%-9%), and an increase in wealth (15%-30%) were the main risk factors that accounted for the explained change in WHZ. Our findings emphasize the importance of interventions to reduce low birthweight, diarrhoea and interventions that address income inequities to prevent acute malnutrition.
Keyphrases
- risk factors
- physical activity
- public health
- body mass index
- liver failure
- mental health
- weight loss
- young adults
- randomized controlled trial
- gestational age
- clinical trial
- depressive symptoms
- machine learning
- drug induced
- deep learning
- aortic dissection
- neural network
- preterm birth
- global health
- extracorporeal membrane oxygenation