Dataset Information

Spatial patterns and determinants of postnatal care use in Ethiopia: findings from the 2016 demographic and health survey.

ABSTRACT:

Objective

Postnatal 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.

Methods

A 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.

Results

The 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.

Conclusion

PNC 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.

SUBMITTER: Sisay MM

PROVIDER: S-EPMC6577400 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Spatial patterns and determinants of postnatal care use in Ethiopia: findings from the 2016 demographic and health survey.

Sisay Malede Mequanent MM Geremew Tesfahun Taddege TT Demlie Yeshambel Worku YW Alem Asaye Tariku AT Beyene Desalew Kassahun DK Melak Melkitu Fentie MF Gelaye Kassahun Alemu KA Ayele Tadesse Awoke TA Andargie Asrat Atsedeweyn AA

BMJ open 20190611 6

<h4>Objective</h4>Postnatal 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.<h4>Methods</h4>A 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 em ...[more]

PMID: 31189672

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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: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:BACKGROUND:The first 2 days after childbirth present the highest risk of dying for a mother. Providing postnatal care within the first 2 days after childbirth can help avert maternal mortality because it allows early detection of problems that could result in adverse maternal health outcomes. Unfortunately, knowledge of the uptake of early postnatal care (EPNC), which is imperative for informing policies aimed at reducing maternal mortality, remains low in Uganda. Therefore, the purpose of this study is to investigate the determinants of early postnatal care attendance among Ugandan women. METHODS:This study was based on nationally representative data from the 2016 Uganda Demographic and Health Survey. The study sample comprised 5471 women (age 15-49) who delivered a child in the 2?years preceding the survey. We used logistic regression to identify factors associated with use of early postnatal care. RESULTS:Our findings showed that 50% of mothers used EPNC services for their most recent delivery in the 2?years preceding the survey. Women's residence, education level, religion, wealth status, marital status, occupation, antenatal care attendance, place of delivery, birth order, perceived accessibility of health facilities, and access to mass media messages were associated with greater use of EPNC. The percentage of women receiving EPNC was much higher among women who delivered at a health facility, either a public facility (63%) or private facility (65%), versus only 9% among women who delivered at home. Multivariate analysis showed that delivery at a health facility was the most important determinant of early postnatal care attendance. CONCLUSIONS:To increase mothers' use of EPNC services and improve maternal survival in Uganda, programs could promote and strengthen health facility delivery and ensure that EPNC services are provided to all women before discharge. Even so, the fact that only about two-thirds of women who delivered at a health facility received early postpartum care shows substantial room for improvement. Interventions should target women who deliver at home, women who attend fewer than four antenatal care visits, and women with a primary education.

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.

Project description:BACKGROUND:All pregnancies are at risk and have to be attended by skilled professionals. In Ethiopia however nearly half (45.7%) of the women were giving birth at home after antenatal care (ANC) visits in which skilled professionals were not available. Therefore, the aim of this study was to assess spatial clustering and the determinant factors of home delivery after antenatal care visits in Ethiopia. METHODS:A case control study was conducted on 2110 mothers who gave birth at home after ANC (cases), and 2510 mothers who gave birth at health institutions after attending ANC (controls), based on EDHS 2016 data. As per the recommendations of the DHS program, we weighed the data before analysis. ArcGIS 10.3 was used to show spatial pattern and SaTScan™ 9.4 to identify significant clusters. Stata 14 was used for data cleaning, weighing, and the analysis of the determinant factors. Bi variable and multi variable multilevel mixed effect logistic regression was fitted. Finally, the Log-likelihood ratio (LLR) and Relative risk with p-value of spatial scan statistics and AOR with 95% CI for significant determinant factors were reported. RESULTS:Home delivery after ANC was spatially clustered in Ethiopia (Moran's Index?=?0.91, p-value<?0.01). Attending, 1-3 ANC visits (AOR?=?1.41, 95%CI: 1.17-1.71), no information about birth preparedness plan (AOR?=?2.21, 95%CI: 1.83-2.69), pregnancies wanted later (AOR?=?1.55, 95%CI: 1.20, 2.06), not having health insurance (AOR?=?2.16, 95% CI: 1.29, 3.62), Muslim (AOR?=?1.57, 95% CI: 1.13, 2.19) and protestant (AOR?=?1.72, 95%CI: 1.16, 2.42) religions were positively associated with home delivery; While being rich (AOR?=?0.42, 95%CI: 0.32-0.54), middle wealth index (AOR?=?O.66, 95%CI: 0.51, 0.86), primary education (AOR?=?0.45, 95%CI: 0.36-0.55), secondary education (AOR?=?0.11, 95%CI: 0.07-0.16), above secondary education (AOR?=?0.06, 95%CI: 0.03-0.11) were negatively associated. CONCLUSIONS:Home delivery after ANC follow ups was spatially clustered. Socio-demographic, health service and pregnancy related factors determined the prevalence of home delivery after antenatal care visits. Strengthening women's education, ANC visit, giving more information about birth preparedness plan, and improving family wealth are vital to reduce home delivery after antenatal care visits.

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: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 <?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). CONCLUSIONS:This 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.

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: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.

Dataset Information

Spatial patterns and determinants of postnatal care use in Ethiopia: findings from the 2016 demographic and health survey.

Objective

Methods

Results

Conclusion

Publications

Spatial patterns and determinants of postnatal care use in Ethiopia: findings from the 2016 demographic and health survey.

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