Modelling the prevalence of malnutrition toddlers using Bayesian semiparametric regression

Rosa Rosmanah, Yudhie Andriyana, Anindya Apriliyanti Pravitasari

Abstract


The malnutrition toddler is caused by low consumption of energy and protein and other socio-economic variables. The units of analysis in this study are all provinces in Indonesia. This study uses five explanatory variables which are indicated to have an effect on increasing or decreasing the weight of toddlers. Based on the preliminary exploration of data, the Bayesian Semiparametric model was considered. The results showed that complete basic immunization and education variables had a negative effect on the malnutrition. Therefore, the more toddlers who received complete basic immunization and the more educated the population in an area, the incidence of malnutrition could be reduced. The results of this study also found that birth weight and exclusive breastfeeding had no effect on malnutrition. This can happen because malnutrition can be prevented by improving the nutrition of toddlers even though, at birth, they have low body weight, and vice versa, malnutrition can occur in toddlers even though they are exclusively breastfed when they are under six months old. The variable of poverty has a positive effect on increasing the malnutrition.

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Published: 2022-05-26

How to Cite this Article:

Rosa Rosmanah, Yudhie Andriyana, Anindya Apriliyanti Pravitasari, Modelling the prevalence of malnutrition toddlers using Bayesian semiparametric regression, J. Math. Comput. Sci., 12 (2022), Article ID 159

Copyright © 2022 Rosa Rosmanah, Yudhie Andriyana, Anindya Apriliyanti Pravitasari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

 

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