title: Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model.
abstract: 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.
authors.affiliation: Department of Statistics, Jahangirnagar University, Savar, Dhaka -1342, Bangladesh.
authors.forename: Mohammad Mafijul
authors.initials: MM
authors.lastname: Islam
authors.forename: Morshed
authors.initials: M
authors.lastname: Alam
authors.forename: Md
authors.initials: M
authors.lastname: Tariquzaman
authors.forename: Mohammad Alamgir
authors.initials: MA
authors.lastname: Kabir
authors.forename: Rokhsona
authors.initials: R
authors.lastname: Pervin
authors.forename: Munni
authors.initials: M
authors.lastname: Begum
authors.forename: Md Mobarak Hossain
authors.initials: MM
authors.lastname: Khan
mesh_terms: D001459:Bangladesh / Q000453:epidemiology; D015362:Child Nutrition Disorders / Q000453:epidemiology*; D002675:Child, Preschool; D006306:Health Surveys; D006801:Humans; D007223:Infant; D015233:Models, Statistical; D016012:Poisson Distribution; D012044:Regression Analysis; D015203:Reproducibility of Results