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ORIGINAL ARTICLE
Year : 2018  |  Volume : 5  |  Issue : 3  |  Page : 128-134

Application of proportional odds model in identifying contributing factor of under-five child malnutrition in Bangladesh: A case study in Tangail district


1 Department of Statistics, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh
2 Department of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh

Correspondence Address:
Asst Prof. Gowranga Kumar Paul
Department of Statistics, Mawlana Bhashani Science and Technology University, Tangail
Bangladesh
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jhrr.jhrr_38_18

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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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