Spatio-temporal distribution and associated factors of anaemia among children aged 6-59 months in Ethiopia: a spatial and multilevel analysis based on the EDHS 2005-2016

Prevalence of and factors associated with childhood anaemia in remote villages of the Peruvian Amazon: a cross-sectional study and geospatial analysis

BACKGROUND

Anaemia is a public health problem in Peru. In the Loreto region of the Amazon, ≥50% of children may be anaemic, although insufficient information exists for rural villages.

METHODS

To generate more data about childhood anaemia in the Peruvian Amazon, haemoglobin was measured as part of a trachoma survey in 21 randomly selected villages. All children 1-9 y of age from 30 randomly selected households per village were recruited. Anaemia was classified according to the World Health Organization guidelines and a socio-economic status (SES) index was created for each household using principal component analysis. Spatial autocorrelation was determined using Moran's I and Ripley's K function.

RESULTS

Of 678 children with complete haemoglobin data, 25.4% (95% confidence interval [CI] 21.2 to 30.1) had mild-or-worse anaemia and 22.1% (95% CI 15.6 to 30.3) had moderate-or-worse anaemia. Mild-or-worse anaemia was more common among children whose primary source of drinking water was surface water (prevalence ratio [PR] 1.26 [95% CI 1.14 to 1.40], p<0.001) and who were in the lowest SES tercile (PR 1.16 [95% CI 1.02 to 1.32], p=0.021). Moderate-or-worse anaemia was more common among boys (PR 1.32 [95% CI 1.09 to 1.60], p=0.005). No evidence of geospatial clustering was found.

CONCLUSIONS

Remote villages of the Amazon would benefit from interventions for childhood anaemia and the poorest households would have the most to gain. Integrating anaemia screening into neglected tropical diseases surveys is an opportunity to use public health resources more efficiently.

Unimproved source of drinking water and its associated factors: a spatial and multilevel analysis of Ethiopian demographic and health survey

BACKGROUND

Drinking water quality has been a major public health concern in lower and middle income countries where access to improved water supplies is limited. Ethiopia is thought to have one of the worst drinking water infrastructures in the world. This study aimed to assess the spatial variation and determinants of using unimproved sources of drinking water in Ethiopia using recent nationally representative data.

METHODS

A population-based cross-sectional study was employed with the recent EDHS data of 2019. A total of 8663 households were sampled using a stratified two-stage cluster sampling method. Kuldorff's SaTScan version 9.6 software was used to generate spatial scan statistics. ArcGIS version 10.7 software was used to visualize the spatial patterns of unimproved drinking water sources. A multilevel multivariable mixed-effect logistic regression was used to identify factors associated with the use of an unimproved drinking water source. In the multivariable multilevel analysis, those variables with a p-value < 0.05 were considered to be significant predictors of using an unimproved source of drinking water.

RESULT

Around 31% (95% CI: 30%, 32%) of the population in Ethiopia uses unimproved sources of drinking water with significant spatial variation across the country. Households aged 41-60 [AOR = 0.69; 95%CI; 0.53, 0.89] as compared to the households aged 10-25, households having middle wealth index [AOR = 0.48; 95%CI; 0.40, 0.59], and households having a rich wealth index [AOR = 0.31; 95%CI; 0.25, 0.39] as compared to the poor households, living in high community literacy level [AOR = 0.36; 95%CI; 0.16, 0.80], living in high-level community poverty [AOR = 3.03; 95%CI; 1.32, 6.98], rural residence [AOR = 7.88; 95%CI; 2.74, 22.67] were significant predictors of use of unimproved source of drinking water. Hot spot areas of use of unimproved drinking water sources were observed in Amhara, Afar, and Somalia regions and some parts of SNNPR and Oromia regions in Ethiopia. The primary clusters were found in Ethiopia's Somalia and Oromia regions.

CONCLUSION

Around one third of the Ethiopian population utilizes unimproved source of drinking water and it was distributed non-randomly across regions of Ethiopia. The age of the household head, wealth status of the household, residence, community poverty level, and community literacy level were found to be significantly associated with utilizing unimproved drinking water source. State authorities, non-governmental organizations and local health administrators should work to improve the quality of drinking water particularly for high risk groups such as communities living in high poverty and low literacy, poor households, rural residents, and hot spot areas to decrease the adverse consequences of using unimproved drinking water source.

Spatial variation and attributable risk factors of anaemia among young children in Uganda: Evidence from a nationally representative survey

Anaemia continues to be a burden especially in developing countries that not only affects the physical growth and cognitive development of children but also increases their risk to death. Over the past decade, the prevalence of anaemia among Ugandan children has been unacceptably high. Despite this, spatial variation and attributable risk factors of anaemia are not well explored at national level. The study utilized the 2016 Uganda Demographic and Health Survey (UDHS) data with a weighted sample of 3805 children aged 6-59 months. Spatial analysis was performed using ArcGIS version 10.7 and SaTScan version 9.6. This was followed by a multilevel mixed-effects generalized linear model for the analysis of the risk factors. Estimates for population attributable risks (PAR) and fractions (PAF) were also provided using STATA version 17. In the results, intra-cluster correlation coefficient (ICC) indicates that 18% of the total variability of anaemia was due to communities within the different regions. Moran's index further confirmed this clustering (Global Moran's index = 0.17; p-value<0.001). The main hot spot areas of anaemia were Acholi, Teso, Busoga, West Nile, Lango and Karamoja sub-regions. Anaemia prevalence was highest among boy-child, the poor, mothers with no education as well as children who had fever. Results also showed that if all children were born to mothers with higher education or were staying in rich household, the prevalence would be reduced by 14% and 8% respectively. Also having no fever reduces anaemia by 8%. In conclusion, anaemia among young children is significantly clustered in the country with disparities noted across communities within different sub-regions. Policies targeting poverty alleviation, climate change or environment adaptation, food security as well interventions on malaria prevention will help to bridge a gap in the sub regional inequalities of anaemia prevalence.

Bayesian spatio-temporal modelling of child anemia in Ethiopia using conditional autoregressive model

Anemia is a common health problem for women and under five children in low income countries. According to the WHO, anemia is considered a serious public health problem when the prevalence is greater than 40%. The prevalence of anemia among children under five in Ethiopia changes over time, and is spatially correlated because it is influenced by environmental, socio-economic and other related factors. However, to our knowledge, there is no small area level estimates of anemia among children under five in Ethiopia. Therefore, this study aimed to assess zonal level estimates of anemia using a Bayesian spatio-temporal conditional autoregressive modeling approach. The data for the study was extracted from the Ethiopian Demographic and Health Surveys (EDHS) from 2005 to 2016. A sample of 18,939 children aged 6-59 months were considered for this study. A Bayesian spatio-temporal conditional autoregressive model was implemented to identify the risk of child anemia. Smoothed relative risks along with the 95% credible interval were reported. The queen's adjacency matrix method was used in spatial smoothing and in estimating the relative risk. The prevalence of anemia among children aged 6-59 months in Ethiopia was 54% in 2005, 44% in 2011 and 57% in 2016. This study showed that low maternal education, low socio-economic status of women, and maternal anemia at zone level were strongly associated with child anemia in Ethiopia. Therefore, enhancing education for women, improving women's socioeconomic status, and mitigating maternal anemia are crucial to reduce the prevalence of childhood anemia in Ethiopia.

Bayesian spatio-temporal modelling and mapping of malaria and anaemia among children between 0 and 59 months in Nigeria

BACKGROUND/M&M

A vital aspect of disease management and policy making lies in the understanding of the universal distribution of diseases. Nevertheless, due to differences all-over host groups and space-time outbreak activities, data are subject to intricacies. Herein, Bayesian spatio-temporal models were proposed to model and map malaria and anaemia risk ratio in space and time as well as to ascertain risk factors related to these diseases and the most endemic states in Nigeria. Parameter estimation was performed by employing the R-integrated nested Laplace approximation (INLA) package and Deviance Information Criteria were applied to select the best model.

RESULTS

In malaria, model 7 which basically suggests that previous trend of an event cannot account for future trend i.e., Interaction with one random time effect (random walk) has the least deviance. On the other hand, model 6 assumes that previous event can be used to predict future event i.e., (Interaction with one random time effect (ar1)) gave the least deviance in anaemia.

DISCUSSION

For malaria and anaemia, models 7 and 6 were selected to model and map these diseases in Nigeria, because these models have the capacity to receive strength from adjacent states, in a manner that neighbouring states have the same risk. Changes in risk and clustering with a high record of these diseases among states in Nigeria was observed. However, despite these changes, the total risk of malaria and anaemia for 2010 and 2015 was unaffected.

CONCLUSION

Notwithstanding the methods applied, this study will be valuable to the advancement of a spatio-temporal approach for analyzing malaria and anaemia risk in Nigeria.

Geographic weighted regression analysis of hot spots of anemia and its associated factors among children aged 6-59 months in Ethiopia: A geographic weighted regression analysis and multilevel robust Poisson regression analysis

INTRODUCTION

Anemia among children aged 6-59 months remains a major public health problem in low-and high-income countries including Ethiopia. Anemia is associated with significant consequences on the health of children such as under-five morbidity and mortality, increased risk of infection, and poor academic performance. The prevalence of anemia in Ethiopia has varied across areas. Therefore, this study aimed to investigate the geographic weighted regression analysis of anemia and its associated factors among children aged 6-59 months in Ethiopia.

METHODS

This study was based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 8482 children aged 6-59 months was included. For the spatial analysis, Arc-GIS version 10.7 and SaTScan version 9.6 statistical software were used. Spatial regression was done to identify factors associated with the hotspots of anemia and model comparison was based on adjusted R2 and Corrected Akaike Information Criteria (AICc). For the associated factors, the multilevel robust Poisson regression was fitted since the prevalence of anemia was greater than 10%. Variables with a p-value < 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable multilevel robust Poisson regression analysis, the adjusted prevalence ratio with the 95% confidence interval was reported to declare the statistical significance and strength of association.

RESULTS

The prevalence of anemia among children aged 6-59 months was 57.56% (95%CI: 56.50%, 58.61%) with significant spatial variation across regions in Ethiopia. The significant hot spot areas of anemia among children aged 6-59 months were detected in the central, west, and east Afar, Somali, Dire Dawa, Harari, and northwest Gambella regions. Mothers who had anemia, a child aged 23-59 months, mothers aged 15-19 years, and coming from a household with a poorer or poorest household were significant predictors of the spatial variations of anemia among children aged 6-59 months. In the multilevel robust Poisson analysis, born to mothers aged 30-39 (APR = 0.84, 95% CI: 0.76, 0.92) and 40-49 years (APR = 0.73, 95% CI: 0.65, 0.83), mothers who didn't have formal education (APR = 1.10, 95% CI: 1.00, 1.20), Children in the poorest household wealth index (APR = 1.17, 95% CI: 1.06, 1.29), being 4-6 (APR = 1.08, 95% CI: 1.02, 1.13) and above 6 order of birth (APR = 1.15, 95% CI: 1.07, 1.23), children born to anemic mothers (APR = 1.24, 95% CI: 1.19, 1.29), children aged 24-59 months (APR = 0.70, 95% CI: 0.68, 0.73), stunted children (APR = 1.09, 95% CI: 1.04, 1.13) and underweight children (APR = 1.07, 95% CI: 1.03, 1.13) were significantly associated with anemia among children aged 6-59 months.

CONCLUSION AND RECOMMENDATION

Anemia is still a public health problem for children in Ethiopia. Residing in a geographic area where a high proportion of children born to mothers aged 15-19 years, a child aged 6-23 months, coming from a household with poorer or poorest wealth index, and mothers with anemia increased the risk of experiencing anemia among children aged 6-59 months. Maternal education, maternal age, child age, household wealth, stunting, underweight, birth order, and maternal anemia were significant predictors of anemia among children. The detailed map of anemia hot spots among children aged 6-59 months and its predictors could assist program planners and decision-makers to design targeted public health interventions.