Modelling chronic malnutrition in Zambia: A Bayesian distributional regression approach

Abstract

Background The burden of child under-nutrition still remains a global challenge, with greater severity being faced by low- and middle-income countries, despite the strategies in the Sustainable Development Goals (SDGs). Globally, malnutrition is the one of the most important risk factors associated with illness and death, affecting hundreds of millions of pregnant women and young children. Sub-Saharan Africa is one of the regions in the world struggling with the burden of chronic malnutrition. The 2018 Zambia Demographic and Health Survey (ZDHS) report estimated that 35% of the children under five years of age are stunted. The objective of this study was to analyse the distribution, and associated factors of stunting in Zambia. Methods We analysed the relationships between socio-economic, and remote sensed characteristics and anthropometric outcomes in under five children, using Bayesian distributional regression. Georeferenced data was available for 25,852 children from two waves of the ZDHS, 31% observation were from the 2007 and 69% were from the 2013/14. We assessed the linear, non-linear and spatial effects of covariates on the height-for-age z-score. Results Stunting decreased between 2007 and 2013/14 from a mean z-score of 1.59 (credible interval (CI): -1.63; -1.55) to -1.47 (CI: -1.49; -1.44). We found a strong non-linear relationship for the education of the mother and the wealth of the household on the height-for-age z-score. Moreover, increasing levels of maternal education above the eighth grade were associated with a reduced variation of stunting. Our study finds that remote sensed covariates alone explain little of the variation of the height-for-age z-score, which highlights the importance to collect socio-economic characteristics, and to control for socio-economic characteristics of the individual and the household. Conclusions While stunting still remains unacceptably high in Zambia with remarkable regional inequalities, the decline is lagging behind goal two of the SDGs. This emphasises the need for policies that help to reduce the share of chronic malnourished children within Zambia.

Spatial trends and projections of chronic malnutrition among children under 5 years of age in Ethiopia from 2011 to 2019: a geographically weighted regression analysis

“…Findings indicated poor household sanitation and poor household wealth index exhibited a predominantly positive influence on under-five children to be stunted. This is also evidenced in some literature [ 19 , 22 , 44 ]. Similarly, when analyzing potential factors that may affect the clustering of under-five stunting, stunting among children in Ethiopia was positively associated with children who had uneducated mothers.…”

“…This is supported by previous spatial analysis of under-five stunting conducted previously in Ethiopia [ 24 , 25 , 27 – 30 ]. Furthermore, in the other settings, various pieces of evidence revealed the presence of geographical variation of under-five stunting such as studies conducted in Rwanda [ 44 ], Ghana [ 18 ], Zambia [ 19 ], Nigeria [ 20 , 21 ].…”

“…Similarly, when analyzing potential factors that may affect the clustering of under-five stunting, stunting among children in Ethiopia was positively associated with children who had uneducated mothers. Within the literature, previous evidence also recognizes that there is a higher chance of educated women in terms of reducing child malnutrition [ 19 , 22 , 31 ]; it is often that these women who are more educated had improved access to media and health-seeking practices, which further promotes the better dietary practice. Our GWR analysis revealed a positive relationship (both strong and weak positive relationships) between residences of participants, with being a rural resident being a strong predictor of disparity in under-five stunting.…”

Navigating the nutritional paradox: The impact of sustainable development targets on childhood wasting and overweight prevalence

“…This finding has been echoed by Johri et al 2019 who also called into question the relationship between improved water sources and wasting and stunting [36]. Furthermore, the influence of maternal education on children's nutrition appears to hinge on reaching a certain level of educational attainment [37][38][39]. Investigators in a case-control study have also found that maternal employment does not affect a child's nutritional status [40].…”