Bayesian geostatistical modelling of stunting in Rwanda: risk factors and spatially explicit residual stunting burden

Prevalence and determinants of stunting and anaemia in children aged 6-23 months: A multilevel analysis from rural Ethiopia

Low- and middle-income countries shoulder the greatest burden of stunting and anaemia in children. This calls for prompt and effective intervention measures, while the contributing factors are not fully understood. This study evaluates determinants spanning from individual-, household- and community levels including agroecology and antinutrients as unique sets of predictors. Primary data were collected from 660 rural households representing the midland (ML), highland, and upper highland (UHL) agroecological zones from northern Ethiopia. The study relates several predictors to stunting and anaemia in children aged 6-23 months. We found 49.1% and 49.7% of children were stunted and anaemic, respectively. Children living in the ML are approximately twice more likely to be stunted adjusted odds ratio (AOR: 1.869; 95% CI: 1.147-3.043) than in the UHL. The risk of stunting increases by 16.3% and 41.9% for every unit increase in phytate-to-zinc and phytate-to-iron molar ratios, respectively. A 10% increase in mean aggregated crop yield was observed to reduce the likelihood of stunting occurrence by 13.6%. Households lacking non-farm income-generating opportunities, travel longer time to access the marketplace and poor health service utilisation were associated with increased risk of stunting. Low diversity of child's diet, age of the child (18-23 months) and mothers at a younger age are significantly associated with stunting. Risk of anaemia in children is high amongst households with unimproved water, sanitation, and hygiene practices, younger age (6-11 months) and mostly occurs amongst boys. Children in the ML had a 55% reduced risk of being anaemic (AOR: 0.446; 95% CI: 0.273-0.728) as compared to the UHL. Therefore, the influence of these factors should be considered to tailor strategies for reducing undernutrition in children of 6-23 months in rural Ethiopia. Interventions should go beyond the administrative boundaries into targeting agroecological variation.

Childhood stunting in Indonesia: assessing the performance of Bayesian spatial conditional autoregressive models

Stunting continues to be a significant health issue, particularly in developing nations, with Indonesia ranking third in prevalence in Southeast Asia. This research examined the risk of stunting and influencing factors in Indonesia by implementing various Bayesian spatial conditional autoregressive (CAR) models that include covariates. A total of 750 models were run, including five different Bayesian spatial CAR models (Besag-York-Mollie (BYM), CAR Leroux and three forms of localised CAR), with 30 covariate combinations and five different hyperprior combinations for each model. The Poisson distribution was employed to model the counts of stunting cases. After a comprehensive evaluation of all model selection criteria utilized, the Bayesian localised CAR model with three covariates were preferred, either allowing up to 2 clusters with a variance hyperprior of inverse-gamma (1, 0.1) or allowing 3 clusters with a variance hyperprior of inverse-gamma (1, 0.01). Poverty and recent low birth weight (LBW) births are significantly associated with an increased risk of stunting, whereas child diet diversity is inversely related to the risk of stunting. Model results indicated that Sulawesi Barat Province has the highest risk of stunting, with DKI Jakarta Province the lowest. These areas with high stunting require interventions to reduce poverty, LBW births and increase child diet diversity.

Childhood stunting is highly clustered in Northern Province of Rwanda: A spatial analysis of a population-based study

Background

In Northern Province, Rwanda, stunting is common among children aged under 5 years. However, previous studies on spatial analysis of childhood stunting in Rwanda did not assess its randomness and clustering, and none were conducted in Northern Province. We conducted a spatial-pattern analysis of childhood undernutrition to identify stunting clusters and hotspots for targeted interventions in Northern Province.

Methods

Using a household population-based questionnaire survey of the characteristics and causes of undernutrition in households with biological mothers of children aged 1-36 months, we collected anthropometric measurements of the children and their mothers and captured the coordinates of the households. Descriptive statistics were computed for the sociodemographic characteristics and anthropometric measurements. Spatial patterns of childhood stunting were determined using global and local Moran's I and Getis-Ord Gi* statistics, and the corresponding maps were produced.

Results

The z-scores of the three anthropometric measurements were normally distributed, but the z-scores of height-for-age were generally lower than those of weight-for-age and weight-for-height, prompting us to focus on height-for-age for the spatial analysis. The estimated incidence of stunting among 601 children aged 1-36 months was 27.1 %. The sample points were interpolated to the administrative level of the sector. The global Moran's I was positive and significant (Moran's I = 0.403, p < 0.001, z-score = 7.813), indicating clustering of childhood stunting across different sectors of Northern Province. The local Moran's I and hotspot analysis based on the Getis-Ord Gi* statistic showed statistically significant hotspots, which were strongest within Musanze district, followed by Gakenke and Gicumbi districts.

Conclusion

Childhood stunting in Northern Province showed statistically significant hotspots in Musanze, Gakenke, and Gicumbi districts. Factors associated with such clusters and hotspots should be assessed to identify possible geographically targeted interventions.

Socio-economic, demographic, and contextual predictors of malnutrition among children aged 6-59 months in Nigeria

Malnutrition has remained a global public health issue, particularly in low- and middle-income countries (LMICs). Researchers have committed to studying malnutrition (especially in children under the age of five) to address the nine malnutrition targets, set by the WHO to be achieved by 2025. This study seeks to evaluate the prevalence, the individual and contextual predictors of malnutrition among children aged 6-59 months across Nigeria and its states. Two separates, independently collected, nationally representative cross-sectional surveys, the National Human Development Report (NHDR 2018) and the 2018 Nigeria Demographic and Health Survey (2018 NDHS) were linked for this study. Spatial map was used to describe the prevalence of malnutrition, a 3-level multivariate multilevel logistic regression models were fitted where children/individuals (at level 1) were nested in communities/clusters (at level 2) and nested in states (at level 3). A weighted sample of 7,770 children 6-59 months were considered in this study. The results showed that an estimated 43.6% of children aged 6-59 months are poorly nourished in Nigeria. The proportions of poorly nourished children were generally highest in the Northern Nigeria. Child's gender, age, birth size, preceding birth order, anaemia status, maternal education, work status, body weight, household wealth status, number of bedrooms were among individual/household predictors of malnutrition. On the community level, being from community with high wealth index, distance to nearest health facilities is no big problem. Regional variations and gender inequality index were the state level predictors of malnutrition among children in Nigeria. This study has shown that two-third of children aged 6-59 months in Nigeria were poorly nourished, an indication of a growing concern of double burden of malnutrition in Nigeria.

Geospatial Overlap of Undernutrition and Tuberculosis in Ethiopia

Undernutrition is a key driver of the global tuberculosis (TB) epidemic, yet there is limited understanding regarding the spatial overlap of both diseases. This study aimed to determine the geographical co-distribution and socio-climatic factors of undernutrition and TB in Ethiopia. Data on undernutrition were found from the Ethiopian Demographic and Health Survey (EDHS). Data on TB were obtained from the Ethiopia national TB prevalence survey. We applied a geostatistical model using a Bayesian framework to predict the prevalence of undernutrition and TB. Spatial overlap of undernutrition and TB prevalence was detected in the Afar and Somali regions. Population density was associated with the spatial distribution of TB [β: 0.008; 95% CrI: 0.001, 0.014], wasting [β: -0.017; 95% CrI: -0.032, -0.004], underweight [β: -0.02; 95% CrI: -0.031, -0.011], stunting [β: -0.012; 95% CrI: -0.017, -0.006], and adult undernutrition [β: -0.007; 95% CrI: -0.01, -0.005]. Distance to a health facility was associated with the spatial distribution of stunting [β: 0.269; 95% CrI: 0.08, 0.46] and adult undernutrition [β: 0.176; 95% CrI: 0.044, 0.308]. Healthcare access and demographic factors were associated with the spatial distribution of TB and undernutrition. Therefore, geographically targeted service integration may be more effective than nationwide service integration.

Mapping Local Variations and the Determinants of Childhood Stunting in Nigeria

INTRODUCTION

Understanding the specific geospatial variations in childhood stunting is essential for aligning appropriate health services to where new and/or additional nutritional interventions are required to achieve the Sustainable Development Goals (SDGs) and national targets.

OBJECTIVES

We described local variations in the prevalence of childhood stunting at the second administrative level and its determinants in Nigeria after accounting for the influence of geospatial dependencies.

METHODS

This study used the 2018 national Nigeria Demographic and Health Survey datasets (NDHS; N = 12,627). We used a Bayesian geostatistical modelling approach to investigate the prevalence of stunting at the second administrative level and its proximal and contextual determinants among children under five years of age in Nigeria.

RESULTS

In 2018, the overall prevalence of childhood stunting in Nigeria was 41.5% (95% credible interval (CrI) from 26.4% to 55.7%). There were striking variations in the prevalence of stunting that ranged from 2.0% in Shomolu in Lagos State, Southern Nigeria to 66.4% in Biriniwa in Jigawa State, Northern Nigeria. Factors positively associated with stunting included being perceived as small at the time of birth and experience of three or more episodes of diarrhoea in the two weeks before the survey. Children whose mothers received a formal education and/or were overweight or obese were less likely to be stunted compared to their counterparts. Children who were from rich households, resided in households with improved cooking fuel, resided in urban centres, and lived in medium-rainfall geographic locations were also less likely to be stunted.

CONCLUSION

The study findings showed wide variations in childhood stunting in Nigeria, suggesting the need for a realignment of health services to the poorest regions of Northern Nigeria.

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.

Lack of Associations between Environmental Exposures and Environmental Enteric Dysfunction among 18-Month-Old Children in Rural Malawi

Environmental enteric dysfunction (EED) is common and contributes to linear growth faltering (stunting) and mortality among children in low-resource settings. A few studies on the environmental causes of EED have been conducted but the exact exposures that cause or predispose children to EED are context-specific and not clear. This study aimed to assess associations between selected environmental exposures and EED markers among 620 18-month-old children. This was a secondary analysis of data from Malawian children who participated in a randomized controlled trial (iLiNS-DYAD, registered at clinicaltrials.gov as NCT01239693) from birth to 18 months of age. Data on environmental exposures, including drinking water source, sanitation, exposure to animals, housing materials, season, residential area, and food insecurity were collected at enrolment. Biomarkers of EED included concentrations of calprotectin, regenerating 1B protein (REG1B), and alpha-1-antitrypsin from stool samples to assess intestinal inflammation, repair, and permeability, respectively. We performed bivariate and multivariable analyses to assess associations between environmental exposures and EED biomarkers. Adjusting for possible confounders, we did not find associations between the selected environmental exposures and the three biomarkers. These results do not provide support for our hypothesis that the studied adverse environmental exposures are associated with increased concentrations of children's EED markers in rural Malawi.