Geographical variation of common childhood illness and its associated factors among under-five children in Ethiopia: spatial and multilevel analysis.

Although substantial progress has been made in reducing child mortality over the last three decades, the magnitude of the problem remains immense. Ethiopia is one of the countries with a high under-five mortality rate due to childhood illnesses including acute respiratory infections, diarrhea, and fever that varies from place to place. It is vital to have evidence of the factors associated with childhood illnesses and the spatial distribution across the country to prioritize and design targeted interventions. Thus, this study aimed to investigate the spatial cluster distribution and associated factors with common childhood illnesses. Secondary data analysis based on the 2016 Ethiopian Demographic and Health Survey data was carried out. A total weighted sample of 10,417 children was included. The study used ArcGIS and SaTScan software to explore spatial distribution. For associated factors, a multilevel binary logistic regression model was fitted using STATA V.14 software. Adjusted Odds Ratios (AOR) with a 95% Confidence Interval (CI) and p-value ≤ 0.05 in the multivariable model were used to declare significant factors associated with the problem. ICC, MOR, PCV, and deviance (-2LLR) were used to check model fitness and model comparison. In this study, the prevalence of common childhood illnesses among under-five children was 22.5% (95% CI: 21.6-23.3%). The spatial analysis depicted that common childhood illnesses have significant spatial variation across Ethiopia. The SaTScan analysis identified significant primary clusters in Tigray and Northern Amhara regions (log-likelihood ratio (LLR) = 60.19, p < 0.001). In the multilevel analysis, being rural residence [AOR = 1.39, 95% CI (1.01-1.98)], small child size at birth [AOR = 1.36, 95% CI (1.21-1.55)], high community poverty [AOR = 1.26, 95% CI (1.06-1.52)], mothers aged 35-49 [AOR = 0.81, 95% CI (0.69-0.94)], the household had electricity [AOR = 0.77, 95% CI (0.61-0.98)], the household had a refrigerator [AOR = 0.60, 95% CI (0.42-0.87)], improved drinking water [AOR = 0.82, 95% CI (0.70-0.95)], improved toilet [AOR = 0.72, 95% CI (0.54-0.94)], average child size at birth [AOR = 0.83, 95% CI (0.75-0.94)] were significantly associated with common childhood illnesses. Common childhood illnesses had spatial variations across Ethiopia. Hotspot areas of the problem were found in the Tigray, Northern Amhara, and Northeast SNNPR. Both individual and community-level factors affected common childhood illnesses distribution and prevalence in Ethiopia. Therefore, public health intervention should target the hotspot areas of common childhood illnesses to reduce their incidence in the country.

Chilot D ，Diress M ，Yismaw Gela Y ，Sinamaw D ，Simegn W ，Andualem AA ，Seid AM ，Bitew DA ，Seid MA ，Eshetu HB ，Kibret AA ，Belay DG ... -  《Scientific Reports》

Individual and community-level determinants, and spatial distribution of institutional delivery in Ethiopia, 2016: Spatial and multilevel analysis.

Tesema GA ，Mekonnen TH ，Teshale AB 《PLoS One》

Spatial distribution of stillbirth and associated factors in Ethiopia: a spatial and multilevel analysis.

Although the rate of stillbirth has decreased globally, it remains unacceptably high in developing countries. Today, only 10 countries share the burden of more than 65% of the global rate of stillbirth and these include Ethiopia. Ethiopia ranks seventh in terms of high rate of stillbirths. Exploring the spatial distribution of stillbirth is critical to developing successful interventions and monitoring public health programmes. However, there is no study on the spatial distribution and the associated factors of stillbirth in Ethiopia. Therefore, this study aimed to explore the spatial distribution and the associated factors of stillbirth. Secondary data analysis was conducted based on the 2016 Ethiopian Demographic and Health Survey data. A total weighted sample of 11 375 women were included in the analysis. The Bernoulli model was fitted using SaTScan V.9.6 to identify hotspot areas and ArcGIS V.10.6 to explore the spatial distribution of stillbirth. For associated factors, a multilevel binary logistic regression model was fitted using STATA V.14 software. Variables with a p value of less than 0.2 were considered for the multivariable multilevel analysis. In the multivariable multilevel analysis, adjusted OR (AOR) with 95% CI was reported to reveal significantly associated factors of stillbirth. The spatial analysis showed that stillbirth has significant spatial variation across the country. The SaTScan analysis identified significant primary clusters of stillbirth in the Northeast Somali region (log likelihood ratio (LLR)=13.4, p<0.001) and secondary clusters in the border area of Oromia and Amhara regions (LLR=8.8, p<0.05). In the multilevel analysis, rural residence (AOR=4.83, 95% CI 1.44 to 16.19), primary education (AOR=0.39, 95% CI 0.20 to 0.74), no antenatal care (ANC) visit (AOR=2.77, 95% CI 1.70 to 4.51), caesarean delivery (AOR=5.07, 95% CI 1.65 to 15.58), birth interval <24 months (AOR=1.95, 95% CI 1.20 to 3.10) and height <150 cm (AOR=2.73, 95% CI 1.45 to 4.97) were significantly associated with stillbirth. In Ethiopia, stillbirth had significant spatial variations across the country. Residence, maternal stature, preceding birth interval, caesarean delivery, education and ANC visit were significantly associated with stillbirth. Therefore, public health interventions that enhance maternal healthcare service utilisation and maternal education in hotspot areas of stillbirth are crucial to reducing stillbirth in Ethiopia.

Tesema GA ，Gezie LD ，Nigatu SG 《BMJ Open》

Complete basic childhood vaccination and associated factors among children aged 12-23 months in East Africa: a multilevel analysis of recent demographic and health surveys.

Tesema GA ，Tessema ZT ，Tamirat KS ，Teshale AB ... -  《BMC PUBLIC HEALTH》

Spatial Distribution and Determinants of Early Marriage among Married Women in Ethiopia: A spatial and Multilevel Analysis.

Alem AZ ，Yeshaw Y ，Kebede SA ，Liyew AM ，Tesema GA ，Agegnehu CD ，Teshale AB ... -  《BMC Womens Health》