Department of Statistics, Jahangirnagar University, Savar, Dhaka -1342, Bangladesh.
BMC Public Health. 2013 Jan 8;13:11. doi: 10.1186/1471-2458-13-11.
Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable.
The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model.
The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother's education, father's education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman.
Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh.
在包括孟加拉国在内的发展中国家，营养不良是导致儿童死亡的主要原因之一。据我们所知，大多数针对五岁以下儿童营养不良问题的现有研究都考虑了分类（二项式/多项式）结果变量，并应用逻辑回归（二项式/多项式）来寻找其预测因素。在这项研究中，营养不良变量（即结果）被定义为一个家庭中五岁以下营养不良儿童的数量，这是一个非负计数变量。本研究的目的是：（i）展示广义泊松回归（GPR）模型作为替代其他统计方法的适用性；（ii）寻找该结果变量的一些预测因素。
该数据取自 2007 年孟加拉国人口与健康调查（BDHS）。简而言之，该调查采用了基于家庭两阶段分层抽样的全国代表性样本。使用各种统计技术，包括卡方检验和 GPR 模型，对 4460 名五岁以下儿童进行了分析。
与标准泊松回归和负二项回归相比，GPR 模型（由于其过离散（方差<均值）特性）被发现是研究上述结果变量的合理选择。我们的研究还确定了几个结果变量的显著预测因素，包括母亲的教育程度、父亲的教育程度、财富指数、卫生状况、饮用水来源和妇女的总生育数。
鉴于许多其他研究的结果一致性，GPR 模型是分析家庭中五岁以下营养不良儿童数量的其他统计模型的理想替代方案。基于显著预测因素的策略可能会改善孟加拉国儿童的营养状况。
