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Sociodemographic and geographical inequalities in under- and overnutrition among children and mothers in Bangladesh: a spatial modelling approach to a nationally representative survey
Authors: Mia MN, Rahman MS, and Roy PK
Source: Public Health Nutrition, 2:1-11; DOI: 10.1017/S1368980018000988
Topic(s): Inequality
Country: Asia
Published: MAY 2018
Abstract: OBJECTIVE: To investigate the sociodemographic and geographical variation in under- and overnutrition prevalence among children and mothers. DESIGN: Data from the 2014 Bangladesh Demographic and Health Survey were analysed. Stunting and wasting for children and BMI<18·5 kg/m2 for mothers were considered as undernutrition; overweight was considered as overnutrition for both children and mothers. We estimated the prevalence and performed simple logistic regression analyses to assess the associations between outcome variables and predictors. Bayesian spatial models were applied to estimate region-level prevalence to identify the regions (districts) prone to under- and overnutrition.Settings/SubjectsChildren aged<5 years and their mothers aged 15-49 years in Bangladesh. RESULTS: A significant difference (P<0·001) was observed in both under- and overnutrition prevalence between poor and rich. A notable regional variation was also observed in under- and overnutrition prevalence. Stunting prevalence ranged from 20·3 % in Jessore to 56·2 % in Sunamgonj, wasting from 10·6 % in Dhaka to 19·2 % in Bhola, and overweight from 0·8 % in Shariatpur to 2·6 % in Dhaka. Of the sixty-four districts, twelve had prevalence of stunting and thirty-two districts had prevalence of wasting higher than the WHO critical threshold levels. Similarly, fifty-three districts had prevalence of maternal underweight higher than the national level. In contrast, the prevalence of overweight was comparatively high in the industrially equipped metropolitan districts. CONCLUSIONS: Observed sociodemographic and geographical inequalities imply slow progress in the overall improvement of both under- and overnutrition. Therefore, effective intervention programmes and policies need to be designed urgently targeting the grass-roots level of such regions. KEYWORDS: Bangladesh; Bayesian spatial model; Mapping; Under- and overnutrition