Model Generalized Poisson Regression (GPR) Pada Kasus Stunting Di Provinsi Nusa Tenggara Timur

Maria Febriana Lais, Astri Atti, Rapmaida M Pangaribuan, Robertus Dole Guntur
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Abstract

Stunting is a child development disorder due to chronic malnutrition and recurrent infections characterized by a height below average. The purpose of this study was to determine the Generalized Poisson Regression (GPR) model in stunting cases in East Nusa Tenggara Province and the factors that influence the incidence these events in 2022. The Generalized Poisson Regression method has been implemented to analyse the problem of overdispersion in the data. Data from the Central Bureau of Statistics (BPS) of East Nusa Tenggara Province is used. The data consits of the number of stunting cases in toddlers (Y), Percentage of Low Weight Infants (BBLR) (X1), Percentage of Toddlers Immunized with Complete Basis (X2), Percentage of Infants Exclusively Breastfed (X3), Number of Undernourished Toddlers (X4), Percentage of Poor People (X5) and Percentage of Access to Proper Sanitation (X6). Results showed that the Generalized Poisson Regression model is µ = exp(5.044 + 0.0005604X4 − 0.01173X6) with two predictor variables that significantly affectstunting cases, namely the number of under-five malnourished children (X4) and the percentage ofaccess to proper sanitation (X6).
东努沙登加拉省发育迟缓病例的广义泊松回归(GPR)模型
发育迟缓是由于慢性营养不良和反复感染造成的儿童发育障碍,其特征是身高低于平均水平。本研究的目的是确定2022年东努沙登加拉省发育迟缓病例的广义泊松回归(GPR)模型及其影响这些事件发生率的因素。应用广义泊松回归方法分析了数据的过分散问题。数据来自东努沙登加拉省中央统计局(BPS)。数据包括幼儿发育迟缓病例数(Y)、低体重婴儿百分比(X1)、获得完全基础免疫的幼儿百分比(X2)、纯母乳喂养的婴儿百分比(X3)、营养不良幼儿人数(X4)、贫困人口百分比(X5)和获得适当卫生设施的百分比(X6)。结果表明,广义泊松回归模型为μ = exp(5.044 + 0.0005604X4 - 0.01173X6),其中两个预测变量显著影响发育迟缓病例,即5岁以下营养不良儿童人数(X4)和获得适当卫生设施的百分比(X6)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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