The Other Asian Enigma: Explaining the Rapid Reduction of Undernutrition in Bangladesh

We analysed socio-economic inequalities in stunting in South Asia and investigated disparities associated with factors at the individual, caregiver, and household levels (poor dietary diversity, low maternal education, and household poverty). We used time-series analysis of data from 55,459 children ages 6-23 months from Demographic and Health Surveys in Bangladesh, India, Nepal, and Pakistan (1991-2014). Logistic regression models, adjusted for age, sex, birth order, and place of residency, examined associations between stunting and multiple types of socio-economic disadvantage. All countries had high stunting rates. Bangladesh and Nepal recorded the largest reductions-2.9 and 4.1 percentage points per year, respectively-compared to 1.3 and 0.6 percentage points in India and Pakistan, respectively. Socio-economic adversity was associated with increased risk of stunting, regardless of disadvantage type. Poor children with inadequate diets and with poorly educated mothers experienced greater risk of stunting. Although stunting rates declined in the most deprived groups, socio-economic differences were largely preserved over time and in some cases worsened, namely, between wealth quintiles. The disproportionate burden of stunting experienced by the most disadvantaged children and the worsening inequalities between socio-economic groups are of concern in countries with substantial stunting burdens. Closing the gap between best and worst performing countries, and between most and least disadvantaged groups within countries, would yield substantial improvements in stunting rates in South Asia. To do so, greater attention needs to be paid to addressing the social, economic, and political drivers of stunting with targeted efforts towards the populations experiencing the greatest disadvantage and child growth faltering.

Section: Discussionmentioning

confidence: 99%

Trends in inequalities in child stunting in South Asia

Krishna¹,

Mejía‐Guevara

McGovern

et al. 2017

“…In the last step of our analysis, we applied a regression‐decomposition to assess the ability of the various determinants described above to predict spatial patterns in stunting and differences between very high‐burden and low‐burden districts. This approach has been used widely in literature to study mean outcome differences between groups (Jann, ), including differences in child malnutrition between geographical areas (Sharaf & Rashad, ; Spears et al, ; Srinivasan et al, ) and between populations measured at different points of time (Headey, Hoddinott, Ali, Tesfaye, & Dereje, ). This analysis effectively combines the analysis of differences in means of the explanatory variables ( X ) and regression estimates of the coefficients associated with these variables (β X ).…”

Section: Methodsmentioning

confidence: 99%

Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16

Menon

Headey

Avula

et al. 2018

India accounts for approximately one third of the world's total population of stunted preschoolers. Addressing global undernutrition, therefore, requires an understanding of the determinants of stunting across India's diverse states and districts. We created a district‐level aggregate data set from the recently released 2015–2016 National and Family Health Survey, which covered 601,509 households in 640 districts. We used mapping and descriptive analyses to understand spatial differences in distribution of stunting. We then used population‐weighted regressions to identify stunting determinants and regression‐based decompositions to explain differences between high‐ and low‐stunting districts across India. Stunting prevalence is high (38.4%) and varies considerably across districts (range: 12.4% to 65.1%), with 239 of the 640 districts have stunting levels above 40% and 202 have prevalence of 30–40%. High‐stunting districts are heavily clustered in the north and centre of the country. Differences in stunting prevalence between low and high burden districts were explained by differences in women's low body mass index (19% of the difference), education (12%), children's adequate diet (9%), assets (7%), open defecation (7%), age at marriage (7%), antenatal care (6%), and household size (5%). The decomposition models explained 71% of the observed difference in stunting prevalence. Our findings emphasize the variability in stunting across India, reinforce the multifactorial determinants of stunting, and highlight that interdistrict differences in stunting are strongly explained by a multitude of economic, health, hygiene, and demographic factors. A nationwide focus for stunting prevention is required, while addressing critical determinants district‐by‐district to reduce inequalities and prevalence of childhood stunting.

“…Stunting remains a chronic public health and development problem in South Asia, where 40%, or 58.7 million, of the world's stunted preschool‐aged children reside (United Nations Children's Fund [UNICEF], World Health Organization [WHO], & World Bank Group, ). Notwithstanding, there has been a decline in prevalence of stunting from 49.6% in 2000 to 33.3% in 2017 (UNICEF et al, ), attributed to many factors, including, poverty reduction, women's education, access to improved sanitation and health and nutrition programs (Headey & Hoddinott, ; Headey, Hoddinott, & Park, ; Headey, Hoddinotta, Ali, Tesfaye, & Dereje, ), although socio‐economic inequalities that may underlie stunting persist in many countries (Krishna, Mejía‐Guevara, McGovern, Aguayo, & Subramanian, ; Restrepo‐Mendez, Barros, Black, & Victora, ).…”

Section: Introductionmentioning

confidence: 99%

Nutritional status and risk factors for stunting in preschool children in Bhutan

Kang

Aguayo

Campbell

et al. 2018

Childhood malnutrition remains endemic in South Asia, although the burden varies by country. We examined the anthropometric status and risk factors for malnutrition among children aged 0–59 months through the 2015 National Nutrition Survey in Bhutan. We assessed in 1,506 children nutritional status (by z ‐scores of height‐for‐age [HAZ], weight‐for‐height [WHZ], and weight‐for‐age [WAZ]), estimating prevalence, adjusted for survey design, of stunting, wasting, underweight, and overweight (<−2 for HAZ, WHZ, and WAZ and >2 for WHZ). Children were also assessed for pedal oedema. We conducted multivariable linear/logistic regression analysis to identify child, maternal, and household risk factors for childhood undernutrition and overweight, excluding children with oedema (1.7%). Mean (SE) HAZ, WHZ, and WAZ were −0.82 (0.13), 0.10 (0.04), and −0.42 (0.05), respectively. Prevalence of stunting, wasting, underweight, and overweight were 21.2%, 2.6%, 7.4%, and 2.6%, respectively. In multivariable regressions, risk of stunting significantly increased by age: 5.3% at <6 months (reference), 16.8% at 6–23 months (OR = 3.06, 95% CI [0.63, 14.8]), and 25.0% at 24–59 months (OR = 5.07, [1.16, 22.2]). Risk of stunting also decreased in a dose–response manner with improved maternal education. None of the examined variables were significantly associated with wasting or overweight. Despite a WHZ distribution comparable with the World Health Organization reference (with ~2.6% vs. an expected 2.5% of children beyond 2 z in each tail), stunting persists in one fifth of preschool Bhutanese children, suggesting that other nutrient deficits or nonnutritional factors may be constraining linear growth for a substantial proportion of children.