📄 Abstract
This study models the prevalence of stunting (height-for-age) among children under 5 years in Uganda using historical data from 2000 to 2022. Autoregressive integrated moving average (ARIMA) approach is applied for time-series analysis to forecast trends and assess patterns in stunting prevalence. Data sourced from the World Bank is utilized, with the prevalence of stunting (height-for-age) as the dependent variable, while autoregressive (AR) and moving average (MA) components serve as independent variables. Parameter estimation, conducted using conditional least squares (CLS), reveals a positive and statistically significant AR(1) coefficient (0.667780) and a negative MA(5) coefficient (-0.908297). These results imply that approximately 67% of past stunting trends persist into the present, while 91% of errors are corrected in subsequent periods. The estimated ARIMA (1, 2, 5) model is found to be covariance stationary and invertible, confirming its robustness for forecasting future trends. Projections indicate a slight increase in the prevalence of stunting from 23.5% in 2023 to 24.3% by 2032, suggesting a persistent public health challenge despite observed improvements over the study period. Given the implications of these findings, we recommend strengthening nutrition-sensitive interventions, scaling up maternal and child health programs, and implementing policies targeting poverty reduction and food security to mitigate stunting prevalence in Uganda.
🏷️ Keywords
📚 How to Cite:
Nahabwe Patrick Kagambo John, Maniple Everd Bikaitwoha , MODELLING STUNTING (HEIGHT-FOR-AGE) IN CHILDREN UNDER 5 IN UGANDA , Volume 12 , Issue 1, january 2025, EPRA International Journal of Socio-Economic and Environmental Outlook(SEEO) ,