Arima forecasting of the prevalence of anemia in children in Myanmar
DOI:
https://doi.org/10.47494/mesb.2020.4.41Keywords:
arima, forecasting, prevalence, anemia, children, MyanmarAbstract
Using annual time series data on the prevalence of anemia in children under 5 years of age in Myanmar from 1990 – 2016, the study makes predictions for the period 2017 – 2025. The study applies the Box-Jenkins ARIMA methodology. The diagnostic ADF tests show that, AM, the series under consideration is an I (0) variable. Based on the AIC, the study presents an AR (4) model, which is also called the ARIMA (4, 0, 0) model. This has been found to be the parsimonious model. The diagnostic tests further reveal that the presented model is quite stable and its residuals are not serially correlated. The results of the research indicate that the prevalence of anemia in children in Myanmar will rise from approximately 54.5% in 2017 to almost 64.8% by 2025. This means that anemia is not yet under control in the country. This is a wake up call to both public health policy makers and nutrition specialists in the country.
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References
Kemmer, T. M., et al. (2003). Iron Deficiency is Unacceptably High in Refugee Children From Burma, Journal of Nutrition, 138: 2534 – 2536.
Nyoni, T (2018b). Modeling and Forecasting Inflation in Kenya: Recent Insights from ARIMA and GARCH analysis, Dimorian Review, 5 (6): 16 – 40.
Nyoni, T. (2018a). Modeling and Forecasting Naira/USD Exchange Rate in Nigeria: A Box-Jenkins ARIMA Approach, MPRA Paper No. 88622, University Library of Munich, Munich, Germany.
Aziza Tohirovna Ahmedova. (2020). System of innovative business strategic management of the enterprise. Middle European Scientific Bulletin, 4, 10-13. Retrieved from https://cejsr.academicjournal.io/index.php/journal/article/view/aziza
Nyoni, T. (2018c). Box – Jenkins ARIMA Approach to Predicting net FDI inflows in Zimbabwe, MPRA Paper No. 87737, University Library of Munich, Munich, Germany.
Sayed, N. E., et al. (1999). Assessment of the Prevalence and Potential Determinants of Nutritional Anemia in Upper Egypt, Food & Nutrition Bulletin, 20: 417 – 421.
WHO (2002). Reducing Risks, Promoting Healthy Life, WHO, Geneva.
Win, H. H., & Ko, M. K. (2018). Geographical Disparities and Determinants of Anemia Among Women of Reproductive Age in Myanmar: Analysis of the 2015 – 2016 Myanmar Demographic and Health Survey, WHO South-East Asia Journal of Public Health, 7 (2): 107 – 113.
Zhao, A., et al. (2012). Prevalence of Anemia and its Risk Factors Among Children 6-36 Months Old in Burma, American Journal of Tropical Medicine and Hygiene, 87: 306 – 311.
Zhao, A., et al. (2015). Potential Contribution of Iron Deficiency and Multiple Factors to Anemia Among 6 to 72 Month Old Children in the Kokang Area of Myanmar, American Journal of Tropical Medicine and Hygiene, 93 (4): 836 – 840.
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Copyright (c) 2020 Smartson. P. NYONI, Thabani NYONI
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