Understanding urban inequalities in children's linear growth outcomes: a trend and decomposition analysis of 39,049 children in Bangladesh (2000-2018)

Abstract Background Despite significant progress in reducing child undernutrition, Bangladesh remains among the top six countries globally with the largest burden of child stunting and has disproportionately high stunting prevalence among the urban poor. We use population representative data to iden...

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Main Authors: Hayman Win (Author), Jordyn Wallenborn (Author), Nicole Probst-Hensch (Author), Günther Fink (Author)
Format: Book
Published: BMC, 2021-11-01T00:00:00Z.
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001 doaj_7c2fe61a86b94e8f9b420fb0469d4625
042 |a dc 
100 1 0 |a Hayman Win  |e author 
700 1 0 |a Jordyn Wallenborn  |e author 
700 1 0 |a Nicole Probst-Hensch  |e author 
700 1 0 |a Günther Fink  |e author 
245 0 0 |a Understanding urban inequalities in children's linear growth outcomes: a trend and decomposition analysis of 39,049 children in Bangladesh (2000-2018) 
260 |b BMC,   |c 2021-11-01T00:00:00Z. 
500 |a 10.1186/s12889-021-12181-x 
500 |a 1471-2458 
520 |a Abstract Background Despite significant progress in reducing child undernutrition, Bangladesh remains among the top six countries globally with the largest burden of child stunting and has disproportionately high stunting prevalence among the urban poor. We use population representative data to identify key predictors of child stunting in Bangladesh and assess their contributions to linear growth differences observed between urban poor and non-poor children. Methods We combined six rounds of Demographic and Health Survey data spanning 2000-2018 and used official poverty rates to classify the urban population into poor and non-poor households. We identified key stunting determinants using stepwise selection method. Regression-decomposition was used to quantify contributions of these key determinants to poverty-based intra-urban differences in child linear growth status. Results Key stunting determinants identified in our study predicted 84% of the linear growth difference between urban poor and non-poor children. Child's place of birth (27%), household wealth (22%), maternal education (18%), and maternal body mass index (11%) were the largest contributors to the intra-urban child linear growth gap. Difference in average height-for-age z score between urban poor and non-poor children declined by 0.31 standard deviations between 2000 and 2018. About one quarter of this observed decrease was explained by reduced differentials between urban poor and non-poor in levels of maternal education and maternal underweight status. Conclusions Although the intra-urban disparity in child linear growth status declined over the 2000-2018 period, socioeconomic gaps remain significant. Increased nutrition-sensitive programs and investments targeting the urban poor to improve girls' education, household food security, and maternal and child health services could aid in further narrowing the remaining linear growth gap. 
546 |a EN 
690 |a Urban health 
690 |a Health equity 
690 |a Child nutrition 
690 |a Stunting 
690 |a Linear growth 
690 |a Bangladesh 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n BMC Public Health, Vol 21, Iss 1, Pp 1-18 (2021) 
787 0 |n https://doi.org/10.1186/s12889-021-12181-x 
787 0 |n https://doaj.org/toc/1471-2458 
856 4 1 |u https://doaj.org/article/7c2fe61a86b94e8f9b420fb0469d4625  |z Connect to this object online.