比例优势模型在确定孟加拉国五岁以下儿童营养不良影响因素中的应用:以坦盖尔地区为例

Gowranga Kumar Paul, Mossamet Kamrun Nesa, S. K. Mondal, Sifat Ar Salan, F. Mim
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引用次数: 4

摘要

背景:儿童营养不良是全世界主要的公共卫生问题之一,特别是在孟加拉国等发展中国家。造成这种情况的几个社会经济和人口因素。目的:本研究的目的是利用从坦盖尔农村收集的原始数据,确定坦盖尔地区营养不良的影响因素。材料与方法:采用整群抽样技术采集样本。将村庄视为一个聚类,采用概率比例法从聚类中选取样本。在我们的研究中,我们根据年龄体重z-score将儿童营养状况分为“严重营养不良”、“中度营养不良”和“营养不良”。通过对有序变量的伽马测量进行双变量分析,并检查儿童营养状况与选定个体变量之间的关联;我们使用了列联表和卡方检验。统计分析:进行单因素、双因素和多因素分析以达到研究目的。选择比例优势模型来了解影响儿童营养不良的协变量的稳定效应。结果:双因素分析显示,几乎所有选定的协变量都有显著(P < 0.01)的相关性,多因素分析显示,教育程度与职业、母亲体重指数和儿童营养不良之间的关系具有高度统计学意义(P < 0.01)。结论:提高母亲的受教育程度、营养状况和工作条件是实现5岁以下儿童最佳营养的必要条件。
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Application of proportional odds model in identifying contributing factor of under-five child malnutrition in Bangladesh: A case study in Tangail district
Background: Children malnutrition is one of the major public health-related concerns in all over the world, especially in developing countries like Bangladesh. Several socioeconomic and demographic factors are responsible for this situation. Aims: The purpose of this research was to identify the contributing factors of malnutrition in Tangail district using primary data collected from rural Tangail. Materials and Methods: The sample was collected using the cluster sampling techniques. Villages were considered as a cluster, and the sample from cluster are selected using probability proportional to size method. In our study, we have categorized the child nutritional status as, “severely malnourished,” “moderately malnourished,” and “nourished” based on Weight-for-age z-score. Bivariate analysis was conducted by examining the gamma measurement for ordinal variables and to check the association between child nutrition status and selected individual variables; we have used the contingency table and Chi-square test. Statistical Analysis: Both univariate, bivariate, and multivariate analysis was conducted to meet the objectives of the study. The proportional odds model was selected to understand the stable effects of covariates influencing the child malnutrition. Results: Bivariate analysis shows significant (P < 0.01) associations for almost all of the selected covariates and the multivariate analysis describes the relationship between education and occupation, mother's (body mass index were found highly statistically significant (P < 0.01) and for child malnutrition. Conclusions: The findings of this study suggest the necessity of improving the mother's education level, nutritional status, and the job facilities for women to achieve the optimum nutrition for children under 5 years of age.
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