Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

Islam MM, Alam M, Tariquzaman M, Kabir MA, Pervin R, Begum M, Khan MH (2013)
BMC Public Health 13(1): 11.

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Abstract / Bemerkung
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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BMC Public Health
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13
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1
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11
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
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Islam MM, Alam M, Tariquzaman M, et al. Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC Public Health. 2013;13(1):11.
Islam, M. M., Alam, M., Tariquzaman, M., Kabir, M. A., Pervin, R., Begum, M., & Khan, M. H. (2013). Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC Public Health, 13(1), 11. doi:10.1186/1471-2458-13-11
Islam, M. M., Alam, M., Tariquzaman, M., Kabir, M. A., Pervin, R., Begum, M., and Khan, M. H. (2013). Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC Public Health 13, 11.
Islam, M.M., et al., 2013. Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC Public Health, 13(1), p 11.
M.M. Islam, et al., “Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model”, BMC Public Health, vol. 13, 2013, pp. 11.
Islam, M.M., Alam, M., Tariquzaman, M., Kabir, M.A., Pervin, R., Begum, M., Khan, M.H.: Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model. BMC Public Health. 13, 11 (2013).
Islam, Mohammad Mafijul, Alam, Morshed, Tariquzaman, Md, Kabir, Mohammad Alamgir, Pervin, Rokhsona, Begum, Munni, and Khan, Mobarak Hossain. “Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model”. BMC Public Health 13.1 (2013): 11.
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2013-03-28T09:00:22Z

9 Zitationen in Europe PMC

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