Spatial heterogeneity and predictors of stunting among under five children in Mozambique: a geographically weighted regression.

INTRODUCTION

Childhood stunting, a major public health concern in many developing countries, is associated with impaired physical and cognitive development, increased risk of infectious diseases, and long-term adverse health and economic consequences. Mozambique is among the countries with the highest stunting rates in sub-Saharan Africa. This study aims to examine the spatial variation and identify the predictors of stunting among children under the age of five years in Mozambique.

METHODS

We utilized children's recode data and geographic coordinates extracted from the 2022-23 Mozambique Demographic and Health Survey dataset. A stratified two-stage cluster sampling approach was employed. The study included a total weighted sample of 3,910 children under the age of five years. A geographically weighted regression was used to identify predictors of stunting.

RESULTS

The prevalence of stunting among children under the age of five in Mozambique was 31.26% (95% CI: 29.88 to 32.65%). The Nampula (46.00%), Cabo Delgado (43.79%), Manica (40.88%), Zambezia (38.27%), Niassa (35.52%), and Tete (34.85%) regions of Mozambique were identified as hotspot areas of stunting. Several factors were significantly associated with the spatial heterogeneity in stunting, where household wealth index (poor and middle categories) and Mother's age (15-19 years) were positively associated with higher occurrence of stunting, while having an employed mother and being a child under 2 years of age were negatively associated with stunting occurrence.

CONCLUSION

The spatial heterogeneity in stunting patterns highlighted by this analysis suggests that a one-size-fits-all approach to address child undernutrition in Mozambique may not be effective. Instead, tailored, location-specific strategies that account for the predictors of stunting are necessary to effectively combat this persistent public health challenge. Policymakers and program implementers should prioritize the hotspot regions for targeted interventions, while also maintaining and strengthening the factors contributing to the lower stunting prevalence in the cold spot areas.