Dataset Information

Spatial distribution and associated factors of underweight in Ethiopia: An analysis of Ethiopian demographic and health survey, 2016.

ABSTRACT: Background: Underweight 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.

Methods: Secondary 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.

Result: In Ethiopia, the spatial distribution of underweight was clustered with Global Moran's I? = ?0.79 at p-value?
Conclusions: There 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.

SUBMITTER: Tusa BS

PROVIDER: S-EPMC7707465 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Spatial distribution and associated factors of underweight in Ethiopia: An analysis of Ethiopian demographic and health survey, 2016.

Tusa Biruk Shalmeno BS Weldesenbet Adisu Birhanu AB Kebede Sewnet Adem SA

PloS one 20201201 12

<h4>Background</h4>Underweight 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 indi ...[more]

PMID: 33259562

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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.

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:Underweight is defined as being below the healthy weight range. Underweight in reproductive age group women not only affects women but also increases the risk of an intergenerational cycle of malnutrition and child mortality. Various factors are linked with underweight among women. However, studies on the prevalence of underweight and its associated factors among women are limited in Ethiopia. Hence, this study aimed to assess the prevalence of underweight and its associated factors among reproductive age group women in Ethiopia. Methods:For this study, data were drawn from the 2016 Ethiopian demographic and health survey (EDHS). From the total, 15,683 women participants of the 2016 EDHS; a subsample of 2,848 participants aged 15-49 years who had a complete response to all variables of interest were selected and utilized for analysis. Data were analyzed using SPSS version 20 software program. Pearson's chi-squared test was used to assess the frequency distribution of underweight and is presented with different sociodemographic characteristics. Logistic regression models were applied for analysis. A two-sided p value of less than 0.05 was used to declare a statistically significant association between the independent variables and underweight among women. Results:The prevalence of underweight among reproductive age group women in Ethiopia was 17.6%. The majority, 78.3% of underweight women, were rural dwellers. The odds of being underweight was higher among the young aged women, among those residing in rural areas, in those with higher educational status, and in those who have one or more children. On the other hand, the odds of underweight among respondents living in Benishangul, SNNPR, and Addis Ababa were less compared to those living in Dire Dawa. Similarly, the odds of underweight among participants with a higher level of husband or partner educational status and among those who chew Khat were less compared to their counterparts. Conclusion:Underweight among reproductive age group women in Ethiopia is still a major public health problem, particularly among rural dwellers. Underweight was significantly associated with different sociodemographic variables. Hence, context-based awareness creation programs need to be designed on the prevention methods of underweight in Ethiopia, giving especial emphasis to those residing in rural areas.

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: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:BackgroundChildhood under-nutrition is a major global health problem. Although the rate of under-nutrition in Ethiopia has declined in the last decade, but it still remains being the major causes of morbidity and mortality of children under-five years. The problem is even worse in rural areas. The prevalence of underweight among rural children was 25% compared with 13% among urban children. To alleviate this problem, it is necessary to determine the magnitude and determinants of underweight. The study models non-Gaussian data analysis to identify risk factors associated with underweight among under-five children in rural Ethiopia.MethodologyThe data source for this study was secondary data, which was retrieved from EDHS 2016 database. It was analyzed using two model families; one with marginal models (GEE and ALR) in which responses are modeled and marginalized overall other responses, and the other is random effects model (GLMM) which is useful when the interest of the analyst lies in the individual's response profiles as well as to evaluate within and between regional variations of underweight.ResultFrom fitting non-Gaussian data analysis to identify risk factors associated with underweight among under five children in rural Ethiopia, the independent variable which have significant effect on underweight were:-Age of child, birth interval, mothers education, fathers education, wealth index, diarrhea in last two weeks, fever in last two weeks are significant and also father's work status shows that difference in significance among the category.ConclusionChild age, preceding birth interval, mother's education, household's wealth index, fever, diarrhea, father's education and father's work status were associated with child underweight. Furthermore, there is both within and between regional heterogeneity of underweight among children in rural Ethiopia. Therefore, rigorous community-based interventions (such as uplifting mother's education by providing formal education and preventing infectious diseases that cause diarrhea and fever) should be developed and executed throughout the country to improve this grave situation of underweight prevalence in rural areas of Ethiopia.

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:BACKGROUND:Iodine deficiency disorder is a significant public health problem, affecting both developed and developing nations worldwide. It is associated with poor body growth and irreversible mental retardation. However, little is known about the spatial distribution and determinants of household iodized salt utilization in Ethiopia. Therefore, this study aimed to explore the spatial distribution and determinants of iodized salt utilization at national level. METHODS:Ethiopian Demographic and Health Survey 2016 data was used to investigate the spatial distribution and determinants of household iodized salt utilization in Ethiopia. ArcGIS 10.6 and SaTScan™ version 9.6 software were used to explore the spatial distribution and detect significant clusters, respectively. The odds ratio with its 95% confidence interval (CI) was determined for potential determinants included in the multivariable multilevel logistic regression model. RESULTS:Household iodized salt utilization was spatially clustered in Ethiopia (Moran's Index?=?0.076, p-value?=?0.01). The significant hotspot areas with high iodized salt utilization were located in Benishangul, Amhara, Gambella, Tigray and Northwest Oromia regions. Significant cold spot areas (areas with low iodized salt utilization) were found in Somali, and East Afar regions. Those households with higher education level ((Adjusted Odds Ratio [AOR] =1.49, 95% CI =1.14-1.93), high community level education (AOR?=?1.51, 95% CI?=?1.03-2.20), middle wealth index (AOR?=?1.31, 95% CI?=?1.04-1.65) and high community media exposure (AOR?=?1.52, 95% CI?=?1.07-2.17) had higher odds of iodized salt utilization. CONCLUSIONS:Household iodized salt utilization had significant spatial variation across the country. Both household and community level variables were found to be associated with household iodized salt utilization in Ethiopia. Therefore, increasing the education level, wealth status and community media exposure is recommended to improve iodized salt utilization in a country. A targeted intervention is also needed for those regions with low household iodized salt utilization.

Project description:BACKGROUND:Contraceptive discontinuations for reasons other than the desire for pregnancy are a public health concern because of their negative effect on reproductive health outcomes. In Ethiopia, the contraceptive discontinuation rate is increasing; however the factors associated are poorly understood. So this study was aimed at assessing reasons and multilevel factors for unscheduled contraceptive use discontinuation. METHODS:This is a cross-sectional study of Ethiopian women who participated in the Ethiopian demographic health survey from January 18, 2016, to June 27, 2016. Ever using any contraceptive with in the calendar of the survey were an inclusion criteria for which 3835 women were found eligible. The data were analyzed using multilevel binary logistic regression in STATA version 14. Variables with p-value less than 0.05 were considered as statistically significant, and reported using adjusted odds ratio and 95% confidence interval. Median odds ratio and interval odds ratio, to quantify the magnitude of the general and specific contextual effect respectively, were used. Receiver operating characteristics curve and akaike's information criterion were used for model comparison. RESULT:The prevalence of unscheduled contraceptive use discontinuation was 46.18% for the principal reason of method related problems (Side effects-45.3%, needing better method-33.6%, and inconvenience-21.1%,). Women heading a household (AOR?=?1.281, 95%CI 1.079-1.520), women who had no work (AOR?=?0.812, 95%CI 0.673, 0.979) compared to professionals, living in poorest house hold income (AOR?=?0.753, 95%CI 0.567, 0.997) compared to middle, residing in community with low contraceptive utilization rate (AOR?=?1.945, 95%CI 1.618, 2.339), residing in poor community (AOR?=?0.763, 95%CI 0.596-0.997), and having more children, and region were found to be significant predictors of unscheduled contraceptive use discontinuation. CONCLUSION:Method related problems were found to contribute for more than half of the contraceptive use discontinuation. Both individual and community level factors were found to significantly influence the Unscheduled contraceptive use discontinuation. The outcome was common in groups who could have more social interactions and knowledge on which myths and rumors are common. So strengthening the efforts to reduce contraceptive use discontinuation and quality of contraceptive service provision could be important.

Dataset Information

Spatial distribution and associated factors of underweight in Ethiopia: An analysis of Ethiopian demographic and health survey, 2016.

Publications

Spatial distribution and associated factors of underweight in Ethiopia: An analysis of Ethiopian demographic and health survey, 2016.

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