District Effect Appraisal in East Sub-Saharan Africa: Combating Childhood Anaemia

Shared component modelling of early childhood anaemia and malaria in Kenya, Malawi, Tanzania and Uganda

Background

Malaria and anaemia contribute substantially to child morbidity and mortality. In this study, we sought to jointly model the residual spatial variation in the likelihood of these two correlated diseases, while controlling for individual-level, household-level and environmental characteristics.

Methods

A child-level shared component model was utilised to partition shared and disease-specific district-level spatial effects.

Results

The results indicated that the spatial variation in the likelihood of malaria was more prominent compared to that of anaemia, for both the shared and specific spatial components. In addition, approximately 30% of the districts were associated with an increased likelihood of anaemia but a decreased likelihood of malaria. This suggests that there are other drivers of anaemia in children in these districts, which warrants further investigation.

Conclusions

The maps of the shared and disease-specific spatial patterns provide a tool to allow for more targeted action in malaria and anaemia control and prevention, as well as for the targeted allocation of limited district health system resources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03694-4.

Prevalence Rate and Associated Risk Factors of Anaemia among under Five Years Children in Ethiopia

Background: Anaemia is a condition characterised by a decrease in the concentration of haemoglobin (Hb) in the blood. Anaemia suffers under five years children about 47.4% and 67.6% worldwide and developing countries including Ethiopia, respectively. The aim of this study was to assess the prevalence rate and the associated socio-economic, geographic and demographic factors of anaemia status of under five years children in Ethiopia. Methods: The data for this study were obtained from the 2011 Ethiopia National Malaria Indicator Survey (EMIS 2011). A sample of 4356 under five years age children was obtained from three regional states of Ethiopia. Based on haemoglobin level, child anaemia status was ordered and takes an ordinal value as no anaemia, mild anaemia, moderate anaemia and severe anaemia, respectively. Ordinal logistic regression model, specifically the proportional odds model was used by considering with and without survey design features. Results: Of the 4356 complete cases, 2190 (50.28%) were male and 1966 (49.72%) were female children under five years old. The children overall mean (SD) age was 2.68 (1.21) years. It was observed that both the mean ages and their variabilities in the regions are approximately equal to the overall mean and variability. It was also observed that in Amhara, Oromiya and SNNP regions 72.28%, 67.99% and 73.63% of the children, respectively had no anaemia; 15.93%, 13.47% and 13.56% of the children, respectively had mild anaemia; 10.99%, 15.61% and 11.33% of the children, respectively had moderate anaemia; and only 0.81%, 2.93% and 1.49% had severe anaemia, respectively. The prevalence of severe child anaemia status was higher in Oromiya region compared to Amhara and SNNP regions, respectively. Our result indicates that age, use of mosquito net, malaria RDT outcome, type of toilet facility, household wealth index, region and median altitude were significantly related to child anaemia status. However, it was observed that some covariates were model dependent, for example household wealth index and type of toilet facility were not significant when considering survey features. Conclusions: Anaemia burden remains high particularly in developing countries. Controlling the burden of anaemia necessitates the formulation of integrated interventions which prioritise the highest risk groups including children under five years. The statistical model used in this paper identified individual, household and cluster level risk factors of child anaemia. The identified risk factors for example not having improved toilet facility in the dwelling where a child lived as well as poorest household wealth index suggest the policymakers should target to focus more on children from poor community. Further, the strong association between malaria infection and anaemia suggests that malaria preventative methods such as vector control methods namely, long-lasting insecticidal nets (LLINs) and indoor residual spraying of households with insecticides and including case diagnostic testing and treatment may be the most effective ways to reduce infections associated with anaemia. Such collective assessment approach may lead to more effective public health strategies and could have important policy implications for health promotion and for the reduction of health disparities.

Relationship between distance of referring facilities and haemoglobin change in children in Malawi

BACKGROUND

Anaemia is a significant cause of mortality in children in sub-Saharan Africa where blood transfusion is often available only at referral hospitals. Understanding the pattern of referrals by health facilities is essential to identify the delays that affect child survival.

AIM

To determine if there was a correlation between change in haemoglobin (Hb) level and distance from referring facilities to Kamuzu Central Hospital (KCH) in Malawi, and whether distance affected mortality rates.

METHODS

This was a retrospective cohort study of 2259 children referred to KCH whose Hb was measured at the referring facility or at KCH. Maps were created using ArcGIS® software. The relationship between distance from KCH and change in Hb was assessed by χ2 analysis and multiple linear regression with SAS© software.

RESULTS

The majority of children were referred by health facilities in the Lilongwe District. When categorised as Hb <4, 4-6 or >6 g/dL, 87.0% of children remained in the same category during transfer. There was no significant relationship between Hb drop and distance from KCH. Distance from KCH was not a significant predictor of Hb level at KCH or Hb change. However, mortality rates were significantly higher in facilities that were 10-50 km from KCH than in those which were <10 km away.

CONCLUSIONS

Using distance as a proxy for time, this suggests that referring facilities are transferring children sufficiently quickly to avert significant reductions in Hb. Despite this, there is a need to identify the factors that influence the decision to transfer anaemic children.

Disparities in childhood composite index of anthropometric failure prevalence and determinants across Ethiopian administrative zones

BACKGROUND

The prevalence of under-five children's undernutrition in Ethiopia is among the highest in the world. This study aimed at exploring the prevalence and risk factors of the composite index for anthropometric failure (CIAF) of under-five children in Ethiopia by incorporating the zonal (district) effects.

METHODS

The data was drawn from Ethiopian Demographic and Health Surveys (EDHSs), a population-based cross-sectional study of 29,599 under-five year children from 72 Zones in the years 2000, 2005, 2011, and 2016. Fixed effect variables related to child and maternal-household were included in the model. We adopted a generalized mixed model with CIAF as outcome variable and Zones as random effects.

RESULTS

The prevalence of CIAF in Ethiopia was 53.78% with the highest prevalence of 61.30% in 2000 and the lowest prevalence of 46.58% in 2016. The model result revealed that being a female child, absence of comorbidity, singleton births, and the first order of birth showed significantly lower CIAF prevalence than their counterparts. Among the household characteristics, children from mothers of underweight body mass index, uneducated parents, poor household sanitation, and rural residents were more likely to be undernourished than their counterparts. Based on the best linear unbiased prediction for the zonal-level random effect, significant variations of CIAF among zones were observed.

CONCLUSION

The generalized linear mixed-effects model results identified gender of the child, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. Disparities of CIAF were observed between and within the Ethiopian administrative Zones over time.

Copula geoadditive modelling of anaemia and malaria in young children in Kenya, Malawi, Tanzania and Uganda

BACKGROUND

Anaemia and malaria are the leading causes of sub-Saharan African childhood morbidity and mortality. This study aimed to explore the complex relationship between anaemia and malaria in young children across the districts or counties of four contiguous sub-Saharan African countries, namely Kenya, Malawi, Tanzania and Uganda, while accounting for the effects of socio-economic, demographic and environmental factors. Geospatial maps were constructed to visualise the relationship between the two responses across the districts of the countries.

METHODS

A joint bivariate copula regression model was used, which estimates the correlation between the two responses conditional on the linear, non-linear and spatial effects of the explanatory variables considered. The copula framework allows the dependency structure between the responses to be isolated from their marginal distributions. The association between the two responses was set to vary according to the district of residence across the four countries.

RESULTS

The study revealed a positive association between anaemia and malaria throughout the districts, the strength of which varied across the districts of the four countries. Due to this heterogeneous association between anaemia and malaria, we further considered the joint probability of each combination of outcome of anaemia and malaria to further reveal more about the relationship between the responses. A considerable number of districts had a high joint probability of a child being anaemic but not having malaria. This might suggest the existence of other significant drivers of childhood anaemia in these districts.

CONCLUSIONS

This study presents an alternative technique to joint modelling of anaemia and malaria in young children which assists in understanding more about their relationship compared to techniques of multivariate modelling. The approach used in this study can aid in visualising the relationship through mapping of their correlation and joint probabilities. These maps produced can then help policy makers target the correct set of interventions, or prevent the use of incorrect interventions, particularly for childhood anaemia, the causes of which are multiple and complex.