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Hotspots of unimproved sources of drinking water in Ethiopia: mapping and spatial analysis of Ethiopia demographic and health survey Data 2016.

ABSTRACT: BACKGROUND:More than 35% of the Ethiopian population are using drinking water from unimproved sources. As per the United Nations' Sustainable Development Goals, Ethiopia is aspiring to achieve universal and equitable access to safe and affordable drinking water for all by 2030. For these goals to be accomplished, it is important to map the country's hotspot areas of unimproved source of drinking-water so that resource allocation and disease control can be optimized there. Therefore, the objective of this study is to map and identify hotspot areas of unimproved sources of drinking water in Ethiopia. METHODS:A population based cross-sectional study was conducted in Ethiopia from January 18 to June 27, 2016. Data were collected from 10,064 households using a pretested and structured questionnaire. A stratified two-stage cluster sampling was employed where the enumeration areas were primary sampling units and households were secondary sampling units. Systematic sampling with probability proportional to size was employed to select samples. Datasets were cleaned and entered into SaTScan and ArcGIS software for mapping and analysis. The Global Moran's I and spatial scan statistical tests (Bernoulli model) were done to explore the presence of clustering in the study area and local spatial clusters (hotspots) of unimproved sources of drinking water using ArcGIS version 10.3 and Kuldorff's SaTScan version 9.4 software, respectively. RESULTS:Unimproved sources of drinking water were spatially clustered in the study area (Moran's I: 0.35, p

SUBMITTER: Bogale GG

PROVIDER: S-EPMC7278129 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Hotspots of unimproved sources of drinking water in Ethiopia: mapping and spatial analysis of Ethiopia demographic and health survey Data 2016.

Bogale Getahun Gebre GG

BMC public health 20200608 1

<h4>Background</h4>More than 35% of the Ethiopian population are using drinking water from unimproved sources. As per the United Nations' Sustainable Development Goals, Ethiopia is aspiring to achieve universal and equitable access to safe and affordable drinking water for all by 2030. For these goals to be accomplished, it is important to map the country's hotspot areas of unimproved source of drinking-water so that resource allocation and disease control can be optimized there. Therefore, the ...[more]

PMID: 32513128

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Project description:ObjectiveThis study aimed to assess households access to improved drinking water sources and sanitation facilities and their associated factors in Ethiopia.DesignCross-sectional study.SettingEthiopia.ParticipantsHousehold heads.Primary outcomesAccess to improved drinking water sources and toilet facilities.MethodsWe conducted an in-depth secondary data analysis of 2016 Ethiopian Demographic and Health Survey. Data from a total of 16 650 households and 645 clusters were included in the analysis. The households were selected using a stratified two-stage cluster sampling technique. Multilevel binary logistic regression analyses were performed to identify factors associated with access to an improved drinking water source and toilet facilities. Adjusted OR with a 95% CI was reported with p value <0.05 was used to declare a significant association between the covariates and the outcome variables.ResultsThe proportions of households' access to improved sources of drinking water and toilet facilities were 69.94% (95% CI: 69.23% to 70.63%) and 25.36% (95% CI: 24.69% to 26.03%), respectively. Households headed by women and households with a better wealth index were positively associated with access to improved drinking water sources. Whereas rural households, ≥30 min round trip to obtain drinking water and region were factors negatively associated with households access to improved drinking water sources. A higher probability of having access to improved toilet facilities: households with heads who had attained higher education, households having better access to improved sources of drinking water and households with better wealth index. While the following households were less likely to have access to improved toilet facilities: households with heads were widowed, households with four to six members, rural households and region.ConclusionThe study found that the proportions of households' access to improved drinking water sources and toilet facilities in Ethiopia were relatively low, which demands the need to tailor strategies to increase the coverage of access to improved drinking water sources and toilet facilities.

Project description:ObjectiveThe government of Ghana has targeted universal access to safe drinking water by 2025 and elimination of open defecation by year 2030. This study explored the use of unimproved drinking water and unimproved sanitation and assessed their association with demographic factors.DesignThis was a secondary data analysis of the 2017 Ghana Maternal Health Survey, a nationally representative cross-sectional survey. Open defecation households were mapped to show regional differences. Weighted logistic regression was used to assess the association of demographic variables with use of unimproved drinking water and unimproved toilet facilities.SettingGhana.ParticipantsA total of 26 324 households were included in the analysis.Primary and secondary outcome measuresUse of unimproved drinking water and unimproved toilet facilities.ResultsOut of the 26 324 households, 8.9% used unimproved drinking water while 81.6% used unimproved sanitation. Open defecation was practised by 15.2% of Ghanaian households, with a prevalence of 58.8%, 6.7% and 12.5% in the Northern, Middle and Coastal zones, respectively. In the multivariate analysis, rural households (p<0.001), households with more than five members (p<0.001), households with heads less than 25 years (p=0.018), male-headed households (p<0.001) and household heads with no/low level of education (p<0.001) were significantly associated with drinking unimproved water. Also, rural households (p=0.002), households in the Northern zone (p<0.001), single-member households (p<0.001), households with heads less than 25 years (p<0.001) and household heads with no/low level of education (p<0.001) were significantly associated with using unimproved toilet facilities.ConclusionThe target of universal access to safe drinking water by 2025 and elimination of open defecation by 2030 seems impossible to be achieved if appropriate measures are not implemented. We recommend that state authorities, health partners and non-governmental organisations support local-level sanitation plans and strategies.

Project description:Background:Health insurance is one of the instruments to achieve universal health coverage. However, in Ethiopia, the coverage of health insurance is very low and varies from place to place as well. Therefore, exploring the spatial distribution of health insurance is important to prioritize and design targeted intervention programs in the country. Methods:A total of 16,583 reproductive age group women (15-49?years) were included in this study. The Bernoulli model was used by applying Kulldorff methods using the SaTScan software to analyse the purely spatial clusters of health insurance coverage. ArcGIS version 10.3 was used to visualize the distribution of health insurance coverage across the country. Mixed-effect logistic regression analysis was also used to identify predictors of health insurance coverage. Results:Health insurance coverage among women aged 15-49?years had spatial variations across the country (Moran's I: 0.115, p?<?0.001). Health insurance coverage in Amhara (p?<?0.001) and Tigray (p?<?0.001) National Regional States clustered spatially. Reading newspapers at least once a week (Adjusted Odds Ratio (AOR)?=?1.78, 95% CI: (1.18-2.68))), 40-44?years of age (AOR?=?2.14, 95% CI: (1.37-3.35)), clerical working mothers (AOR?=?4.33, 95% CI: (2.50-7.49)), mothers' with secondary school education (AOR?=?1.77; 95% CI: (1.21-2.58)), mothers' with higher school education (AOR?=?2.62; 95% CI: (1.63-4.23)), having more than 5 family members (AOR?=?1.25; 95% CI: (1.01-1.55)) and richest wealth quantile (AOR?=?3.43, 95% CI: (1.96-6.01)) were predictors of health insurance coverage among reproductive age group women in Ethiopia. Conclusion:Health insurance coverage was very low in Ethiopia and had spatial variations across the country. The hot spot areas with low health insurance coverage need more coherent and harmonized action such as strengthening financial protection through national health packages, sharing experience from regions which have better health insurance coverage and using mass media to increase awareness and confidence of potentials in the systems, which may encourage them to enrol.

Project description:BackgroundUnderweight is one form of indicators of under-nutrition, which results from the poor nutrient intake and underlying health problems. Its impact is beyond an individual and extends to a country level. It has been known from the literature that underweight has a negative effect on income and development of a country. In the context of Ethiopia, factors predicting underweight remain unknown and there is a paucity of evidence on geographical distribution of underweight among individuals aged 15-49 years. Therefore, the aim of this study was to examine the geographic distribution of underweight and its associated factors among individuals aged 15-49 years in Ethiopia.MethodsSecondary data analysis was done on a data set consisting of 28,450 individuals and obtained from the Ethiopian Demography and Health Survey (EDHS) 2016. The spatial distribution of underweight across the country was identified by ArcGIS software. Hotspots analysis was done using Getis-Ord Gi* statistic within ArcGIS. In SaTScan software, the Bernoulli model was fitted by Kulldorff's methods to identify the purely spatial clusters of underweight. A binary logistic regression was applied to determine factors associated with being underweight.ResultIn Ethiopia, the spatial distribution of underweight was clustered with Global Moran's I = 0.79 at p-value < 0.0001. The highest underweight clusters were observed in Tigray, Gambella, eastern part of Amhara, and western and central part of Afar regions. Male individuals [AOR = 1.21; 95% CI: (1.15 1.28)], never married [AOR = 1.14; 95% CI: (1.05, 1.24)], rural residents [AOR = 1.32; 95% CI: (1.18, 1.47)], rich [AOR = 0.85; 95% CI: (0.76, 0.94)], cigarette smoking [AOR = 1.25; 95% CI: (1.07, 1.46)], drinking treated water [AOR = 0.91; 95% CI: (0.83, 0.99)] and open filed defecation [AOR = 1.17; 95% CI: (1.08, 1.26)] were found to have a significant association with being underweight.ConclusionsThere was a significant clustering of underweight among individuals aged 15-49 years. Gender, age, marital status, place of residence, wealth index, cigarette smoking, using untreated water and types of toilet were the significant factors of being underweight. Therefore, effective public health interventions like building safe and supportive environments for nutrition, providing socio-economic protection and nutrition-related education for poor and rural resident would be better to mitigate these situations and associated risk factors in hot spot areas. In addition, policymakers should strengthen and promote nutrition sensitive policies and activities in order to alleviate the underlying and basic causes of underweight.

Project description:BackgroundThe perinatal mortality rate in Ethiopia is among the highest in Sub Saharan Africa. The aim of this study was to identify the spatial patterns and determinants of perinatal mortality in the country using a national representative 2016 Ethiopia Demographic and Health Survey (EDHS) data.MethodsThe analysis was completed utilizing data from 2016 Ethiopian Demographic and Health Survey. This data captured the information of 5 years preceding the survey period. A total of 7230 women who at delivered at seven or more months gestational age nested within 622 enumeration areas (EAs) were used. Statistical analysis was performed by using STATA version 14.1, by considering the hierarchical nature of the data. Multilevel logistic regression models were fitted to identify community and individual-level factors associated with perinatal mortality. ArcGIS version 10.1 was used for spatial analysis. Moran's, I statistics fitted to identify global autocorrelation and local autocorrelation was identified using SatSCan version 9.6.ResultsThe spatial distribution of perinatal mortality in Ethiopia revealed a clustering pattern. The global Moran's I value was 0.047 with p-value <0.001. Perinatal mortality was positively associated with the maternal age, being from rural residence, history of terminating a pregnancy, and place of delivery, while negatively associated with partners' educational level, higher wealth index, longer birth interval, female being head of household and the number of antenatal care (ANC) follow up.ConclusionsIn Ethiopia, the perinatal mortality is high and had spatial variations across the country. Strengthening partner's education, family planning for longer birth interval, ANC, and delivery services are essential to reduce perinatal mortality and achieve sustainable development goals in Ethiopia. Disparities in perinatal mortality rates should be addressed alongside efforts to address inequities in maternal and neonatal healthcare services all over the country.

Project description:ObjectiveTuberculosis is a major public health problem and is the second leading cause of death worldwide. BCG vaccination is a life-saving and important part of standard tuberculosis control measures, particularly in Ethiopia where tuberculosis is endemic. The End Tuberculosis Strategy targets of 2020 have not been achieved. Exploring spatial variations in BCG vaccination among children is vital to designing and monitoring effective intervention programmes. Therefore, this study aimed to explore the spatial variation in BCG vaccination among children in Ethiopia.DesignCross-sectional study design.SettingEthiopia.ParticipantsChildren aged 0-35 months.Primary outcomeBCG vaccination coverage.MethodsData from the 2016 Ethiopian Demographic and Health Survey were used and a total of 4453 children aged 0-35 months were included. Spatial autocorrelation analysis, cluster and outlier analysis, hotspot analysis, spatial interpolation, and spatial scan statistics were carried out to identify geographical risk areas for BCG vaccine utilisation. ArcGIS V.10.6 and SaTScan V.9.6 statistical software were employed to explore spatial pattern and significant hotspot areas for BCG vaccination among children.ResultsBCG vaccination was spatially clustered in Ethiopia at the regional level (Global Moran's I=0.516, p<0.001). A total of 51 most likely clusters of low BCG vaccination were identified in the Somali and Afar regions (log-likelihood ratio=136.58, p<0.001). Significant secondary clusters were also identified in North West Gambela, South Amhara, South West Addis Ababa, North East Southern Nations, Nationalities, and People's Region, and South West Oromia.ConclusionA low probability of receiving BCG vaccination was found among children in the Somali and Afar regions. Therefore, these areas should be given attention when designing effective immunisation strategies to improve BCG vaccination among children in order to reduce the burden of tuberculosis in Ethiopia.

Project description:Sustainable Development Goal (SDG) 6 aims to achieve universal access to safe drinking water sources. However, the health benefits of meeting this goal will only be fully realized if improved sources are used to the exclusion of unimproved sources. Very little is known about how rural African households balance the use of improved and unimproved water sources when multiple options are present. We assessed parallel use of untreated surface water and unimproved hand-dug wells (HDWs) in the presence of boreholes (BHs) using a semi-quantitative water use survey among 750 residents of 15 rural Ghanaian communities, distributed across three BH water quality clusters: control, high salinity, and high iron. Multivariate mixed effects logistic regression models were used to assess the impact of water quality cluster on the use of BHs, HDWs, and surface water, controlling for distance to the nearest source of each type. Reported surface water use was significantly higher in the high salinity and high iron clusters than in the control cluster, especially for water-intensive activities. Respondents in the non-control clusters had approximately eight times higher odds of clothes washing with surface water (p < 0.01) than in the control. Respondents in the high salinity cluster also had 4.3 times higher odds of drinking surface water (p < 0.05). BH use was high in all clusters, but decreased substantially when distance to the nearest BH exceeded 300 m (OR = 0.17-0.25, p < 0.001). Water use from all sources was inversely correlated with distance, with the largest effect observed on HDW use in multivariate models (OR = 0.02, p < 0.001). Surface water and HDW use will likely continue despite the presence of BHs when perceived groundwater quality is poor and other water sources are in close proximity. It is essential to account for naturally-occurring but undesirable groundwater quality parameters in rural water planning to ensure that SDG 6 is met and health benefits are realized.

Project description:BackgroundUnemployment is a major problem in both developed and developing countries. In Ethiopia, women unemployment is particularly high, and this makes it a grave socio-economic concern. The aim of this study is to assess the spatial distribution and identify the determinant factors of women unemployment in Ethiopia.MethodsThe data used for the study is the Ethiopian Demographic and Health Surveys of 2016. A total of 15683 women are involved in the study. Global Moran's I statistic and Poisson-based purely spatial scan statistics are employed to explore spatial patterns and detect spatial clusters of women unemployment, respectively. To identify factors associated with women unemployment, multilevel logistic regression model is used.ResultsA spatial analysis showed that there was a major spatial difference in women unemployment in Ethiopia with Global Moran's index value of 0.3 (p<0.001). The spatial distribution of women's unemployment varied significantly across the country. The major areas of unemployment were Afar and Somalia; southwest Tigray; North and west Oromia, and Eastern and southern parts of Amhara. Women with primary level of education(AOR = 0.88, 95%CI: 0.80, 0.98), secondary and above level of education (AOR = 0.71, 95%CI: 0.62, 0.82), women with rich wealth index (AOR = 0.79, 95% CI: 0.70, 0.90), pregnant women (AOR = 1.24, 95% CI: 1.06, 1.5), women with a male household head(AOR = 1.4, 95% CI: 1.28, 1.50), and urban women(AOR = 0.60, 95% CI: 0.50, 0.70) statistically associated with women unemployment.ConclusionThe unemployment rate of women in Ethiopia showed variation across different clusters. Improving entrepreneurship and women's education, sharing business experiences, supporting entrepreneurs are potential tools for reducing the unemployment women. Moreover, creating community-based programs that prioritize participation of poor households and rural women as well as improving their access to mass media and the labor market is crucial.

Project description:BackgroundBesides their benefits, heavy metals are toxic, persistent, and hazardous to human health, even at their lower concentrations. Consumption of unsafe concentrations of food contaminated with heavy metals may lead to the disruption of numerous biological and biochemical processes in the human body. In developing country including Ethiopia, where untreated or partially treated wastewater is used for agricultural purposes, the problems related to the consumption foods contaminated with heavy metals may poses highest risk to human health. Therefore, this review was aimed to determine the public health implications of heavy metals in foods and drinking water in Ethiopia.MethodsThe articles published from 2016 to 2020 were identified through systematic searches of electronic databases that include MEDLINE/PubMed, EMBASE, CINAH, Google Scholar, WHO, and FAO Libraries. The data was extracted using a predetermined data extraction form using Microsoft Excel, 2016. The methodological quality of the included studies was assessed using mixed methods appraisal tool (MMAT) version 2018 and Joanna Briggs Institute Critical Appraisal tools to determine the relevance of the studies. Finally, the results were evaluated based on the FAO/WHO guidelines for foods and drinking water.ResultsA total of 1019 articles published from 2016 to 2020 were searched from various electronic databases and by manual searching on Google. Following the initial screening, 317 articles were retrieved for evaluation and 49 articles were assessed for eligibility, of which 21 studies were included in the systematic review. The mean concentration of Cr, Cd, Pb, As, Hg, Zn, Cu, Ni, Co, Fe and Mn in fruits and vegetables ranged from 2.068-4.29, 0.86-1.37, 1.90-4.70, 1.01-3.56, 3.43-4.23, 19.18-98.15, 4.39-9.42, 1.037-5.27, 0.19-1.0, 199.5-370.4, 0.26-869 mg/kg, respectively. The mean concentration Cr, Cd, Pb, As, Zn, and Fe in meat and milk ranged from 1.032-2.72, 0.233-0.72, 1.32-3.15, 0.79-2.96, 78.37-467.7, and 505.61-3549.9 mg/kg, respectively. The mean concentration of Cr, Cd, Pb, Zn, and Cu in drinking water ranged 0.0089-0.054, 0.02-0.0237, 0.005-0.369, 0.625-2.137, and 0.176-1.176 ml/L, respectively. The mean concentration of Cr, Cd, Pb, Zn, Cu, Ni, Co, Fe, and Mn in other edible cereals ranged from 0.973-2.165, 0.424-0.55, 0.65-1.70, 70.51-81.58, 14.123-15.98, 1.89-13.8, 1.06-1.59, 67.866-110.3, and 13.686-15.4 mg/kg, respectively.ConclusionThis systematic review identified heavy metals in foods and drinking water and determined their public health implications. The results of this finding imply that the majority of the studies reported high concentrations of toxic heavy metals in foods and drinking water that are hazardous to human health. Therefore, effective food safety and risk-based food quality assessment are essential to protect the public health.

Dataset Information

Hotspots of unimproved sources of drinking water in Ethiopia: mapping and spatial analysis of Ethiopia demographic and health survey Data 2016.

Publications

Hotspots of unimproved sources of drinking water in Ethiopia: mapping and spatial analysis of Ethiopia demographic and health survey Data 2016.

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