Geostatistical analysis, web-based mapping, and environmental determinants of under-5 stunting: evidence from the 2014 Ghana Demographic and Health Survey

Geostatistical modelling of child undernutrition in developing countries using remote-sensed data: evidence from Bangladesh and Ghana demographic and health surveys

Childhood chronic undernutrition, known as stunting, remains a critical public health problem globally. Unfortunately while the global stunting prevalence has been declining over time, as a result of concerted public health efforts, there are areas (notably in sub-Saharan Africa and South Asia) where progress has stagnated. These regions are also resource-poor, and monitoring progress in the fight against chronic undernutrition can be problematic. We propose geostatistical modelling using data from existing demographic surveys supplemented by remote-sensed information to provide improved estimates of childhood stunting, accounting for spatial and non-spatial differences across regions. We use two study areas-Bangladesh and Ghana-and our results, in the form of prevalence maps, identify communities for targeted intervention. For Bangladesh, the maps show that all districts in the south-eastern region are identified to have greater risk of stunting, while in Ghana the greater northern region had the highest prevalence of stunting. In countries like Bangladesh and Ghana with limited resources, these maps can be useful diagnostic tools for health planning, decision making and implementation.

Early-life air pollution and green space exposures as determinants of stunting among children under age five in Sub-Saharan Africa

BACKGROUND

Childhood malnutrition is a major public health issue in Sub-Saharan Africa (SSA) and 61.4 million children under the age of five years in the region are stunted. Although insight from existing studies suggests plausible pathways between ambient air pollution exposure and stunting, there are limited studies on the effect of different ambient air pollutants on stunting among children.

OBJECTIVE

Explore the effect of early-life environmental exposures on stunting among children under the age of five years.

METHODS

In this study, we used pooled health and population data from 33 countries in SSA between 2006 and 2019 and environmental data from the Atmospheric Composition Analysis Group and NASA's GIOVANNI platform. We estimated the association between early-life environmental exposures and stunting in three exposure periods - in-utero (during pregnancy), post-utero (after pregnancy to current age) and cumulative (from pregnancy to current age), using Bayesian hierarchical modelling. We also visualise the likelihood of stunting among children based on their region of residence using Bayesian hierarchical modelling.

RESULTS

The findings show that 33.6% of sampled children were stunted. In-utero PM2.5 was associated with a higher likelihood of stunting (OR = 1.038, CrI = 1.002-1.075). Early-life exposures to nitrogen dioxide and sulphate were robustly associated with stunting among children. The findings also show spatial variation in a high and low likelihood of stunting based on a region of residence.

IMPACT STATEMENT

This study explores the effect of early-life environmental exposures on child growth or stunting among sub-Saharan African children. The study focuses on three exposure windows - pregnancy, after birth and cumulative exposure during pregnancy and after birth. The study also employs spatial analysis to assess the spatial burden of stunted growth in relation to environmental exposures and socioeconomic factors. The findings suggest major air pollutants are associated with stunted growth among children in sub-Saharan Africa.

Mapping under-five child malaria risk that accounts for environmental and climatic factors to aid malaria preventive and control efforts in Ghana: Bayesian geospatial and interactive web-based mapping methods

BACKGROUND

Under-five child malaria is one of the leading causes of morbidity and mortality globally, especially among sub-Saharan African countries like Ghana. In Ghana, malaria is responsible for about 20,000 deaths in children annually of which 25% are those aged < 5 years. To provide opportunities for efficient malaria surveillance and targeted control efforts amidst limited public health resources, the study produced high resolution interactive web-based spatial maps that characterized geographical differences in malaria risk and identified high burden communities.

METHODS

This modelling and web-based mapping study utilized data from the 2019 Malaria Indicators Survey (MIS) of the Demographic and Health Survey Program. A novel and advanced Bayesian geospatial modelling and mapping approaches were utilized to examine predictors and geographical differences in under-five malaria. The model was validated via a cross-validation approach. The study produced an interactive web-based visualization map of the malaria risk by mapping the predicted malaria prevalence at both sampled and unsampled locations.

RESULTS

In 2019, 718 (25%) of 2867 under-five children surveyed had malaria. Substantial geographical differences in under-five malaria risk were observed. ITN coverage (log-odds 4.5643, 95% credible interval = 2.4086-6.8874), travel time (log-odds 0.0057, 95% credible interval = 0.0017-0.0099) and aridity (log-odds = 0.0600, credible interval = 0.0079-0.1167) were predictive of under-five malaria in the spatial model. The overall predicted national malaria prevalence was 16.3% (standard error (SE) 8.9%) with a range of 0.7% to 51.4% in the spatial model with covariates and prevalence of 28.0% (SE 13.9%) with a range of 2.4 to 67.2% in the spatial model without covariates. Residing in parts of Central and Bono East regions was associated with the highest risk of under-five malaria after adjusting for the selected covariates.

CONCLUSION

The high-resolution interactive web-based predictive maps can be used as an effective tool in the identification of communities that require urgent and targeted interventions by programme managers and implementers. This is key as part of an overall strategy in reducing the under-five malaria burden and its associated morbidity and mortality in a country with limited public health resources where universal intervention is practically impossible.

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

Introduction

Undernutrition is a serious global health issue, and stunting is a key indicator of children's nutritional status which results from long-term deprivation of basic needs. Ethiopia, the largest and most populous country in Sub-Saharan Africa, has the greatest rate of stunting among children under the age of five, yet the problem is unevenly distributed across the country. Thus, we investigate spatial heterogeneity and explore spatial projection of stunting among under-five children. Further, spatial predictors of stunting were assessed using geospatial regression models.

Methods

The Ethiopia Demographic and Health Surveys (EDHS) data from 2011, 2016, and 2019 were examined using a geostatistical technique that took into account spatial autocorrelation. Ordinary kriging was used to interpolate stunting data, and Kulldorff spatial scan statistics were used to identify spatial clusters with high and low stunting prevalence. In spatial regression modeling, the ordinary least square (OLS) model was employed to investigate spatial predictors of stunting and to examine local spatial variations geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) models were employed.

Results

Overall, stunting prevalence was decreased from 44.42% [95%, CI: 0.425–0.444] in 2011 to 36.77% [95%, CI: 0.349–0.375] in 2019. Across three waves of EDHS, clusters with a high prevalence of stunting in children under 5 years were consistently observed in northern Ethiopia stretching in Tigray, Amhara, Afar, and Benishangul-Gumuz. Another area of very high stunting incidence was observed in the Southern parts of Ethiopia and the Somali region of Ethiopia. Our spatial regression analysis revealed that the observed geographical variation of under-five stunting significantly correlated with poor sanitation, poor wealth index, inadequate diet, residency, and mothers' education.

Conclusions

In Ethiopia, substantial progress has been made in decreasing stunting among children under the age of 5 years; although disparities varied in some areas and districts between surveys, the pattern generally remained constant over time. These findings suggest a need for region and district-specific policies where priority should be given to children in areas where most likely to exhibit high-risk stunting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41043-022-00309-7.

Prevalence and determinants of wasting of under-5 children in Bangladesh: Quantile regression approach

BACKGROUND

Wasting is perhaps one of the signs of malnutrition that has been linked to the deaths of children suffering from malnutrition. As a result, understanding its correlations and drivers is critical. Using quantile regression analysis, this research aims to contribute to the discussion on under-5 malnutrition by analyzing the predictors of wasting in Bangladesh.

METHODS AND MATERIALS

The dataset was extracted from the 2017-18 Bangladesh demographic and health survey (BDHS) data. The weight-for-height (WHZ) z-score based anthropometric indicator was used in the study as the target variable. The weighted sample constitutes 8,334 children of under-5 years. However, after cleaning the missing values, the analysis is based on 8,321 children. Sequential quantile regression was used for finding the contributing factors.

RESULTS

The findings of this study depict that the prevalence of wasting in children is about 8 percent and only approximately one percent of children are severely wasted in Bangladesh. Age, mother's BMI, and parental educational qualification, are all major factors of the WHZ score of a child. The coefficient of the female child increased from 0.1 to 0.2 quantiles before dropping to 0.75 quantile. For a child aged up to three years, the coefficients have a declining tendency up to the 0.5 quantile, then an increasing trend. Children who come from the richest households had 16.3%, 3.6%, and 15.7% higher WHZ scores respectively than children come from the poorest households suggesting that the risk of severe wasting in children under the age of five was lower in children from the wealthiest families than in children from the poorest families. The long-term malnutrition indicator (wasting) will be influenced by the presence of various childhood infections and vaccinations. Furthermore, a family's economic position is a key determinant in influencing a child's WHZ score.

CONCLUSIONS

It is concluded that socioeconomic characteristics are correlated with the wasting status of a child. Maternal characteristics also played an important role to reduce the burden of malnutrition. Thus, maternal nutritional awareness might reduce the risk of malnutrition in children. Moreover, the findings disclose that to enrich the nutritional status of children along with achieving Sustainable Development Goal (SDG)-3 by 2030, a collaborative approach should necessarily be taken by the government of Bangladesh, and non-governmental organizations (NGOs) at the community level in Bangladesh.

Then and Now: Investigating Anthropometrics and Child Mortality among Females in Malawi

Information on the concentration of body mass index and child death among females in Malawi, where the epidemics of weight gain have been disconcerting and preventable deaths among children linger, is limited. Therefore, the study examined the polarity of body mass index and the death of children among females. Using data from the Malawian Demographic and Health Survey from 2000 to 2015–2016, the study applied for the first time the index of concentration at the extremes and indirect demographic techniques to estimate the polarity of body mass index and child mortality among 65,499 females aged 15 to 49 years. The preponderance of obesity more than doubled from 2000 to 2015–2016 and was highest among females who were older (35–49 years), urban dwellers, rich, and located in districts within the central and southern regions. In addition, child survival was low among underweight, overweight, and obese females. While national-, regional-, and individual-level statistics are in development, these findings provide helpful information for health experts and other stakeholders to initiate appropriate age-region specific programs and interventions in Malawi, including targeting females in the high socio-economic bracket.