On exploring and ranking risk factors of child malnutrition in Bangladesh using multiple classification analysis

Abstract

Background: Logistic regression analysis is widely used to explore the determinants of child malnutrition status mainly for nominal response variable and non-linear relationship of interval-scale anthropometric measure with nominal-scale predictors. Multiple classification analysis relaxes the linearity assumption and additionally prioritizes the predictors. Main objective of the study is to show how does multiple classification analysis perform like linear and logistic regression analyses for exploring and ranking the determinants of child malnutrition. Methods: Anthropometric data of under-5 children are extracted from the 2011 Bangladesh Demographic and Health Survey. The analysis is carried out considering several socio-economic, demographic and environmental explanatory variables. The Height-for-age Z-score is used as the anthropometric measure from which malnutrition status (stunting: below −2.0 Z-score) is identified.

On selection of an appropriate logistic model to determine the risk factors of childhood stunting in Bangladesh

“…One of such influential predictors may be selecting more slums in urban areas especially in the capital city Dhaka, where bulk share of population is living. The same scenario has also been experienced in a recent study using 2011 BDHS child nutrition data (Bhowmik & Das, ).…”

“…The considered logistic‐type regression models have been developed in many studies for identifying the risk factors of child malnutrition. In a number of studies, child's age and birth interval, mother's education and nutrition, household wealth status, child feeding index, and incidence of child fever, acute respiratory infection, and diarrhoea are identified as the significant predictors of child malnutrition using ordinary LR (Bhowmik & Das, ; Das, Hossain, & Islam, ; Das & Rahman, ). Habyarimana () and Makoka () developed SLR model of child malnutrition and found child's sex and birth order and mother's education and body mass index (BMI) as potential factors of child malnutrition.…”

Bacteriophages Isolated from Stunted Children Can Regulate Gut Bacterial Communities in an Age-Specific Manner

“…Nutritional status related to height-for-age Z (HAZ), weight-for-age Z (WAZ) and weight-for-height Z (WHZ) scores were assessed using the WHO growth reference for the same age and sex (WHO Anthro software, version 3.2.2, WHO, Geneva, Switzerland). The WHOrecommended HAZ cut-off point of <-2 SD for low height-for-age status was used to define stunting (i.e., when HAZ is below -2 SD of the reference value) in this study (Bhowmik and Das, 2017;Sanin et al, 2018). Children selected for this study had not taken any nutritional supplements, did not receive any antibiotics treatment, nor had a diarrheal episode at least one month prior to sampling.…”

Non-Linear Effects of Continuous Predictors on Malnutrition Status of Children in Bangladesh

“…Many socio-economic, demographic and health related factors are found to be influential for the growth of this problem in several studies [8][9][10][11][12][13][14][15][16][17]. Das and Gulshan [8] used logistic regression model to examine the extent of malnutrition status among children in Bangladesh in a recent study.…”

“…Talukder [16] assessed the covariates that influence malnutrition status of children through proportional odds model. Bhowmik and Das [17] applied linear regression, logistic regression and multiple classification analysis to rank the significant covariates that affect nutrition status of children. Takele [14] identified some factors that influence nutrition status of children in Ethiopia through…”