Spatial distribution and associated factors of health insurance coverage in Ethiopia: further analysis of Ethiopia demographic and health survey, 2016.
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ABSTRACT:
SUBMITTER: Kebede SA
PROVIDER: S-EPMC7076975 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
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Spatial distribution and associated factors of health insurance coverage in Ethiopia: further analysis of Ethiopia demographic and health survey, 2016.
Kebede Sewnet Adem SA Liyew Alemneh Mekuriaw AM Tesema Getayeneh Antehunegn GA Agegnehu Chilot Desta CD Teshale Achamyeleh Birhanu AB Alem Adugnaw Zeleke AZ Yeshaw Yigizie Y
Archives of public health = Archives belges de sante publique 20200316
<h4>Background</h4>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.<h4>Methods</h4>A total of 16,583 reproductive age group women (15-49 years) were included in this study. The Bernoulli model was used by apply ...[more]
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Project description:BackgroundWomen's health and welfare, as well as the survival of their children, are adversely affected by high fertility rates in developing countries. The fertility rate in Ethiopia has been high for a long time, with some pockets still showing poor improvement. Thus, the current study is aimed to assess the spatial distribution and its predictors of high fertility status in Ethiopia.MethodsSecondary data analysis was used using the 2016 Ethiopian Demographic and Health Survey (EDHS). The Bernoulli model was used by applying Kulldorff methods using the SaTScan software to analyze the purely spatial clusters of high fertility status. ArcGIS version 10.8 was used to visualize the distribution of high fertility status across the country. Mixed-effect logistic regression analysis was also used to identify the predictors of high fertility.ResultHigh fertility among reproductive-age women had spatial variation across the country. In this study, a higher proportion of fertility occurred in Somali region, Southeastern part of Oromia region, and Northeastern part of SNNPR. About 45.33% (confidence interval: (44.32, 46.33) of reproductive-age women had high fertility. Education; no formal (aOR: 13.12, 95% CI: 9.27, 18.58) and primary (aOR: 5.51, 95% CI: 3.88, 7.79), religion; Muslim (aOR: 1.52, 95% CI: 1.28, 1.81) and Protestant (aOR: 1.48, 95% CI: 1.23, 1.78), age at first birth (aOR: 2.94, 95% CI: 2.61, 3.31), age at first sex (aOR: 1.70, 95% CI: 1.49, 1.93), rural resident (aOR: 3.76, 95% CI: 2.85, 4.94) were predictors of high fertility in Ethiopia.ConclusionThe spatial pattern of high fertility status in Ethiopia is clustered. Hotspot areas of a problem were located in Somali, Central Afar, Northeastern part of SNNPR, and Southeastern part of Oromia region. Therefore, designing a hotspot area-based interventional plan could help to reduce high fertility. Moreover, much is needed to be done among rural residents, reducing early sexual initiations and early age at first birth, and enhancing women's education. All the concerned bodies including the kebele administration, religious leaders, and community leaders should be in a position to ensure the practicability of the legal age of marriage.
| S-EPMC10490912 | biostudies-literature
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.
| S-EPMC7707465 | biostudies-literature
Project description:BackgroundEthiopia has made satisfactory progress in improving maternal and child health over the past two decades. The introduction of family planning through informed choice is one of the main strategies to improve maternal and child health. However, this positive progress may have masked the significant urban-rural disparities in informed choice for family planning.ObjectiveTo identify factor contributing to observed urban-rural disparities and to determine the spatial distribution of informed family planning choices in Ethiopia.MethodsThe study used information from 3,511 women currently using contraceptives (rural-2685 and urban-826) as per recent Ethiopian demographic health survey cross-sectional data. Spatial and descriptive, bivariable, and multivariable logit-based decomposition analysis methods were used.ResultsThe spatial configuration of uninformed choice was clustered. The primary cluster (LLR = 34.8, p-value<0.001) was located at the southern portion of Amhara region that covers east & west Gojjam, south Gondar and south Wollo administrative zones. The magnitude of informed choice was 12 percent higher in urban residents compared to rural residents. Urban-rural gap was attributed to variations in characteristics (74%). Place of family planning offer i.e., private health facility, being aged between 35 and 49 years, and having visited to health facility in the last 1 year are found decrease the urban-rural gap of informed family planning choice by 15%, 9% and 5% respectively. Conversely, being aged between 25 and 34 years, being a listener to radio has increased the gap by 9% and 12% respectively.ConclusionThe variables being private health facility visitors, being aged between 35 and 49 years and having visited health facilities in the last one year are found to increase the gap of informed family planning choices between urban and rural residents Besides, the spatial distribution of uninformed family planning choices is non-random.
| S-EPMC10443855 | biostudies-literature
Project description:IntroductionChildhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This study aimed to assess the geographical distribution and associated factors for common childhood illnesses and service utilisation across Ethiopia based on the 2016 Demographic and Health Survey.MethodsThe sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS.ResultsOverall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P<0.001, and Moran's index = 0.0804, Z-score 4.498, P< 0.001, respectively. Wealth and reported distance to health facilities were associated with service utilisation. Prevalence of common childhood illnesses was higher in the North, while service utilisation was more likely to be on a low level in the Eastern, South-western, and the Northern parts of the country.ConclusionOur study provided evidence of geographic clustering of common childhood illnesses and health service utilisation when the child was sick. Areas with low service utilisation for childhood illnesses need priority, including actions to counteract barriers such as poverty and long distances to services.
| S-EPMC10004611 | biostudies-literature
Project description:ObjectiveThis study aimed to assess the spatial distribution, individual and community-level factors associated with low birth weight in Ethiopia.MethodSecondary data analysis was conducted using the 2016 Ethiopian Demographic and Health Survey data. A total of 2110 neonates were included in this study. Spatial autocorrelation analysis was conducted to assess the spatial clustering of LBW. Besides, the spatial scan statistics and ordinary kriging interpolation were done to detect the local level clusters and to assess predicted risk areas, respectively. Furthermore, a multilevel logistic regression model was fitted to determine individual and community-level factors associated with LBW. Finally, most likely clusters with log-likelihood ratio (LLR), relative risk and p value from spatial scan statistics and adjusted OR (AOR) with 95% CI for multilevel logistic regression model were reported.ResultsLBW was spatially clustered in Ethiopia. Primary (LLR=11.57; p=0.002) clusters were detected in the Amhara region. Neonates within this spatial window had a 2.66 times higher risk of being LBW babies as compared with those outside the window. Besides, secondary (LLR=11.4; p=0.003; LLR=10.14, p=0.0075) clusters were identified at southwest Oromia, north Oromia, south Afar and southeast Amhara regions. Neonates who were born from severely anaemic (AOR=1.40, 95% CI (1.03 to 2.15)), and uneducated (AOR=1.90, 95% CI (1.23 to 2.93)) mothers, those who were born before 37 weeks of gestation (AOR=5.97, 95% CI (3.26 to 10.95)) and women (AOR=1.41, 95% CI (1.05 to 1.89)), had significantly higher odds of being LBW babies.ConclusionThe high-risk areas of LBW were detected in Afar, Amhara and Oromia regions. Therefore, targeting the policy interventions in those hotspot areas and focusing on the improvement of maternal education, strengthening anaemia control programmes and elimination of modifiable causes of prematurity could be vital for reducing the LBW disparity in Ethiopia.
| S-EPMC8103935 | biostudies-literature
Project description:BackgroundGlobally, divorce is a common phenomenon in couples' marital life. As a result, many divorced couples and their children face several social, economic, and health problems after dissolution. There is little information on the magnitude and determinants of divorce in developing countries including Ethiopia. Therefore, this study aimed to estimate the prevalence of divorce from the first union and its predictors among reproductive-age women in Ethiopia.MethodsWe used the 2016 Ethiopia demographic and health survey data for this analysis. The survey was a community-based cross-sectional study conducted from January 18 to June 27, 2016. The survey employed a two-stage stratified cluster sampling technique. A total of 11,646 ever-married women were included in the analysis. Bivariate and multivariable logistics regression was done to identify the determinants of divorce from the first marriage. A p-value < 0.05 was used to declare statistical significance.ResultsAbout 25% (95%CI: 23.4% - 26.6%) ever-married women were divorced from their first marital relationship. Women who were married at age < 15 years (AOR = 1.34; 95%CI: 1.07-1.68), urban women (AOR = 1.69; 95%CI: 1.22-2.35), women who did not attend formal education (AOR = 4.36; 95%CI: 3.14-6.05), women who were employed (AOR = 1.51; 95%CI: 1.31-1.73), and being childless (AOR = 1.34; 95%CI: 1.07-1.69) had higher odds of experiencing a divorce. Similarly, women who experienced partner violence, women with no house ownership, and women in the Amhara region had higher odds of divorce from their first marital union. Conversely, women in Oromia, SNNPR, the metropolis, and the pastoral regions had lower odds of divorce from their first marital union.ConclusionDivorce from the first marriage is high in Ethiopia. Preventing early marriage and partner violence and promoting girls' education would reduce the divorce rate in Ethiopia.
| S-EPMC7737979 | biostudies-literature
Project description:BACKGROUND:Unsafe abortion remains a global public health concern and it is the leading cause of maternal mortality and morbidity. Despite the efforts made to improve maternal health care service utilization, unsafe abortion yet constitutes the highest maternal mortality in Sub-Saharan Africa (SSA) including Ethiopia. Although abortion among reproductive-age women is a common problem in Ethiopia, there is limited evidence about the spatial distribution and determinants of abortion. Therefore, this study aimed to investigate the spatial distribution and determinants of abortion among reproductive-age women in Ethiopia. METHODS:A secondary data analysis was conducted using the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total of 12378 reproductive-age women were included in this study. The Bernoulli model was fitted using SaTScan version 9.6 statistical software to identify significant hotspot areas of abortion and ArcGIS version 10.6 statistical software was used to explore the spatial distributions of abortion. For the determinant factors, a mixed effect logistic regression model was fitted to take into account the hierarchical nature of the EDHS data. Deviance (-2LL), AIC, BIC, and ICC were used for model comparison. The AOR with a 95% CI was estimated for the potential determinants of abortion. RESULTS:The overall prevalence of abortion in Ethiopia was 8.9% ranging from 4.5% in Benishangul to 11.3% in Tigray regions. The spatial analysis revealed that abortion was significantly varied across the country. The SaTScan analysis identified a total of 60 significant clusters, of these 19 clusters were primary clusters. The primary clusters were located in the northern part of the Tigray region (LLR = 26.6, p<0.01; RR = 2.63). In the multivariable mixed-effect logistic regression analysis; primary education [AOR = 1.36; 95% CI: 1.13, 1.64], rural residence [AOR = 4.96; 95% CI: 3.42, 7.18], protestant religion follower [AOR = 0.56; 95% CI: 0.42, 0.75], richest wealth status [AOR = 1.72; 95% CI: 1.24, 2.40], maternal age 45-49 years [AOR = 3.12; 95% CI: 1.52, 6.44], listening radio [AOR = 1.27; 1.01, 1.60], and watching television [AOR = 1.45; 1.04, 2.01] were significant determinants of abortion. CONCLUSIONS:The prevalence of abortion remains unacceptably high in Ethiopia. The spatial distribution of abortion has been significantly varied across regions in Ethiopia. Having primary education, being rural, having media exposure, and being from the richest household were significantly associated with higher odds of abortion whereas being protestant religious followers were associated with lower odds of abortion. Therefore, the government should design public health programs targeting the identified hotspot areas of abortion and should scale up maternal health programs in rural areas, to reduce maternal morbidity and mortality.
| S-EPMC7323954 | biostudies-literature
Project description:BackgroundMore 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.MethodsA 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.ResultsUnimproved sources of drinking water were spatially clustered in the study area (Moran's I: 0.35, p < 0.05). A total of 143 significant clusters was identified. Of which, eight were most likely (primary) clusters and the other 135 were secondary clusters. The first spatial window which contains primary clusters was located in Amhara and Afar regions (LLR: 78.89, at p < 0.001). The other 33 spatial windows which contain secondary clusters were found in all regions, except Gambela region and Addis Abeba city administration (with a range of LLR: 10.09-78.89, p < 0.001).ConclusionsThis study allowed the identification of important non-random clusters and hotspots of unimproved sources of drinking water. Therefore, these results will be determinant to help decision makers in their geographical interventions to combat problems related to drinking water quality.
| S-EPMC7278129 | biostudies-literature
Project description:ObjectivePostnatal care (PNC) is essential for preventing maternal and newborn deaths; however, it still remains less well recognised in low-income and middle-income countries. This study was aimed to explore geographical patterns and identify the determinants of PNC usage among women aged 15-49 years in Ethiopia.MethodsA secondary data analysis was conducted using the 2016 Ethiopian demographic and health survey data. A total of 7193 women were included in this analysis. We employed spatial scan statistics to detect spatial inequalities of PNC usage among women. A multilevel binary logistic regression model was fitted to identify factors associated with women's PNC.ResultsThe prevalence of PNC usage among women was 6.9% (95%?CI 6.3% to 7.5%). The SaTScan spatial analysis identified three most likely clusters with low rates of PNC use namely southwestern Ethiopia (log likelihood ratio (LLR)=18.07, p<0.0001), southeast Ethiopia (LLR=14.29, p<0.001) and eastern Ethiopia (LLR=10.18, p=0.024). Women with no education (Adjusted Odd Ratio (AOR)=0.55, 95%?CI 0.37 to 0.84) and in the poorest wealth quantile (AOR=0.55, 95%?CI 0.39 to 0.78) were less likely to use PNC, while women aged 35-49 years (AOR: 1.75, 95%?CI 1.01 to 3.04) and with at least four antenatal care (ANC) visits (AOR=2.37, 95%?CI 1.71 to 3.29) were more likely to use PNC.ConclusionPNC usage remains a public health problem and has spatial variations at regional levels in the country. Low prevalence of PNC was detected in the Somali, Oromia, Gambella and Southern Nations, Nationalities, and People's Region (SNNPR) regions. Women with low educational status, old age, being in poorest wealth quantile and history of ANC visits were significantly associated with PNC usage. Hence, it is better to strengthen maternal health programmes that give special emphasis on health promotion with a continuum of care during pregnancy.
| S-EPMC6577400 | biostudies-literature
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.
| S-EPMC7682862 | biostudies-literature