stdClass Object
(
    [id] => 14922
    [paper_index] => 202501-09-019956
    [title] => MODELLING STUNTING (HEIGHT-FOR-AGE) IN CHILDREN UNDER 5 IN UGANDA
    [description] => 
    [author] => Nahabwe Patrick Kagambo John, Maniple Everd Bikaitwoha
    [googlescholar] => 
    [doi] => 
    [year] => 2025
    [month] => January
    [volume] => 12
    [issue] => 1
    [file] => fm/jpanel/upload/2025/January/202501-09-019956.pdf
    [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] => ARIMA modelling, Stunting (Height-for-Age)
    [doj] => 2025-01-25
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 5
    [journal_id] => 9
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Socio-Economic and Environmental Outlook(SEEO)
    [short_code] => IJSA
    [eissn] => 2348-4101
    [pissn] => 
    [home_page_wrapper] => images/products_image/5.SEEO.png
)
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