Prevalence and Determinants of Stunting Among Preschool Children and Its Urban-Rural Disparities in Bangladesh

Food Nutr Bull. 2018 Dec;39(4):521-535. doi: 10.1177/0379572118794770. Epub 2018 Aug 29.

Abstract

Background: Despite improvements in the reduction of child stunting rates over the last decade, poor nutritional status still remains a public health concern in Bangladesh, where young children are the most vulnerable.

Objective: The objective of this study is to capture the prevalence and determinants of childhood stunting and document its urban-rural disparities in the context of Bangladesh.

Methods: The study used data from the Bangladesh Demographic and Health Survey of 2014. A bivariate analysis was performed to find out the differentials in prevalence of stunting, and multivariate logistic regression was performed to also assess the association of stunting with potential risk factors.

Results: The overall prevalence of stunting was 36.3% and was significantly higher in rural (38.1%) areas than urban (31.2%) areas. In all 3 regression models, significantly higher odds were found among children aged 36 to 47 months compared to 6 to 12 months and among the children from the poorest households. In rural areas, male children were significantly more likely to be stunted (odds ratio = 1.31; 95% confidence interval: 1.12-1.53). Other significant risk factors for childhood stunting were maternal education and body mass index, children suffering from diarrhea, initial breast-feeding, and administrative divisions.

Conclusions: Disparities exist among urban and rural areas regarding stunting among the children younger than 5 in Bangladesh, which need to be reduced. Public health policies and interventions need to consider the risk factors in urban and rural areas separately.

Keywords: Bangladesh; disparities; nutrition; preschool children; stunting.

MeSH terms

  • Bangladesh / epidemiology
  • Child, Preschool
  • Cross-Sectional Studies
  • Female
  • Growth Disorders / epidemiology*
  • Humans
  • Male
  • Nutritional Status
  • Prevalence
  • Risk Factors
  • Rural Population / statistics & numerical data*
  • Socioeconomic Factors
  • Urban Population / statistics & numerical data*