Child stunting prevalence determination at sector level in Rwanda using small area estimation

Abstract

Abstract Background Stunting among children under 5 years of age remains a worldwide concern, with 148.1 million (22.3%) stunted in 2022. The recent 2019/2020 Rwanda Demographic Health Survey (RDHS) revealed that the prevalence of stunting in Rwanda among under five children was 33.5%. In Rwanda, there is no sufficient evidence on stunting status to guide prioritized interventions at the sector level, the lowest administrative unit for implementing development initiatives. This study aimed to provide reliable estimates of stunting prevalence in Rwanda at the sector level. Methods In this article, Small Area Estimation (SAE) techniques were used to provide sector level estimates of stunting prevalence in children under five in Rwanda. By plugging in relevant significant covariates in the generalized linear mixed model, model-based estimates are produced for all sectors with their corresponding Mean Square Error (MSE). Results The findings showed that, overall, 40 out of 416 sectors had met the national target of having a stunting rate less than or equal to 19%, while 194 sectors were far from meeting this target, having a stunting rate higher than the national prevalence of 33.5% in the year 2020. The majority of the sectors with stunting prevalence that were higher than the national average of 33.5% were found in the Northern Province with 68 sectors out of 89 and in Western Province with 64 sectors out of 96. In contrast, the prevalence of stunting was lower in the City of Kigali where 14 out of 35 sectors had a stunting rate between 0 and 19%, and all sectors were below the national average. This study showed a substantial connection between stunting and factors such as household size, place of residence, the gender of the household head, and access to improved toilet facilities and clean water. Conclusion The results of this study may guide and support informed policy decisions and promote localised and targeted interventions in Rwanda’s most severely affected sectors with a high stunting prevalence in Rwanda.

Keywords

• Generalized linear mixed model
• Small area estimation
• Stunting
• Undernutrition