利用贝叶斯半参数回归对幼儿营养不良患病率进行建模

Q4 Mathematics
Rosa Rosmanah, Y. Andriyana, Anindya Apriliyanti Pravitasari
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引用次数: 0

摘要

幼儿营养不良是由于能量和蛋白质消耗不足以及其他社会经济变量造成的。本研究的分析单位为印尼各省。本研究使用了五个解释变量,表明对幼儿体重的增加或减少有影响。在对数据进行初步探索的基础上,考虑了贝叶斯半参数模型。结果表明,完整的基础免疫和教育变量对营养不良有负向影响。因此,接受完整基本免疫接种的幼儿越多,一个地区的人口受教育程度越高,营养不良的发生率就可以降低。这项研究的结果还发现,出生体重和纯母乳喂养对营养不良没有影响。这种情况之所以会发生,是因为可以通过改善幼儿的营养来预防营养不良,即使在出生时,他们的体重很低,反之亦然,即使在6个月以下的幼儿接受纯母乳喂养,也可能发生营养不良。贫困变量对营养不良的增加有积极的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling the prevalence of malnutrition toddlers using Bayesian semiparametric regression
: 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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