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Health care utilization for common childhood illnesses in rural parts of Ethiopia: evidence from the 2016 Ethiopian demographic and health survey.

ABSTRACT: BACKGROUND:Generally, health care utilization in developing countries is low particularly rural community have lower health care utilization. Despite this fact, little is known about the magnitude and determinants of health care utilization for common childhood illnesses in Ethiopia. Thus, this study was conducted to determine the magnitude and to identify determinants of health care utilization for common childhood illnesses in the rural parts of Ethiopia. METHODS:For this study, data were obtained from the 2016 Ethiopian demographic and health survey. A total of 1576 mothers of under-five children were included in the analysis. Data analysis was performed using R software. Both univariable and multivariable logistic regression analysis were fitted to identify the determinants of health care utilization. Variables with a 95% confidence interval for odds ratio excluding one were considered as significant determinants of the outcome. RESULTS:The findings of this study revealed that only half (49.7%) (95%CI: 46.1-53.4%), 40.9% (95%CI 37.6-44.2%), and 38.0% (95%CI: 34.7-41.4%) of the children utilized health care for diarrhea, fever, and cough, respectively. Children age between 12 and 23?months (AOR: 1.58, 95%CI: 1.08-2.31), maternal education (AOR: 1.96, 95%CI: 1.34-2.88), and giving birth at health facilities (AOR: 1.49, 95%CI: 1.04-2.13) were found to be the determinants of health care utilization for diarrhea. Marital status (AOR: 0.25, 95%CI: 0.06-0.81), husbands' education (AOR: 1.37, 95%CI: 1.01-1.86), and giving birth at health facilities (AOR: 1.51, 95%CI: 1.09-2.10) were factors significantly associated with health care utilization for fever. Children age between 12 and 23?months (AOR: 1.51, 95%CI: 1.03-2.22), maternal education (AOR: 1.70, 95%CI: 1.18-2.44), and giving birth at health facilities (AOR: 1.74, 95%CI: 1.23-2.46) were significantly associated with health care utilization for cough. CONCLUSIONS:Low health care utilization for childhood illnesses was noticed. The health care utilization for diarrhea and cough was lower for children of ages between 0 and 11?months, mothers without formal education and home-delivered children's. The health care utilization for fever was lower for separated parents, husbands without formal education, giving birth at home and from the poorest family. Programs to improve the educational status of a household are essential for better care utilization and children development.

SUBMITTER: Alene M

PROVIDER: S-EPMC6332529 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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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.

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.

Project description:BACKGROUND:Diarrhoea is one of the major contributors to death among under-five children in Ethiopia. Studies conducted in different countries showed that rural children are more severely affected by diarrhoea than urban children. Thus, this study was aimed to identify the socio-demographic, environmental and behavioural associated risk factors of the occurrence of diarrhoea among under-five children in rural Ethiopia. METHODS:Data for the study was drawn from the 2016 Ethiopian Demographic and Health Survey. A total of 8041 under-five children were included in the study. Binary logistic regression was used to assess the association of occurrence of diarrhoea with socio-demographic, environmental and behavioural factors among under-five children. RESULTS:Children aged 6-11?months (AOR:3.5; 95% CI: 2.58-4.87), 12-23?months (AOR: 3.1; 95% CI: 2.33-4.04) and 24-35?months (AOR: 1.7; 95% CI: 1.26-2.34) as compared to >?35?months were significantly associated with an increasing prevalence of diarrhoea. Children in Afar region (AOR: 1.92; 95% CI: 1.01-3.64) and Gambela region (AOR: 2.12; 95% CI: 1.18, 3.81) were significantly associated with an increasing prevalence of diarrhoea, but a decreasing prevalence in Somali region (AOR: .42; 95% CI: (.217-.80) as compared to Tigray region. Increasing prevalence of diarrhoea was also significantly associated with male children (AOR: 1.3; 95% CI: 1.05-1.58); households who shared toilet facilities with other households (AOR: 1.4; 95% CI: 1.09-1.77); fourth birth order (AOR: 1.81; 95% CI: 1.17-2.79), and fifth and above birth order (AOR: 1.85; 95% CI: 1.22, 2.81) as compared to first order; and mother's current age 35-49?years in a household with ?3 under-five children (AOR: 4.7; 95% CI: 1.64-13.45) as compared to those maternal ages of 15-24?years in a household with ?2 under-five children. CONCLUSION:The age of a child, sex of a child, region, birth order, toilet facilities shared with other households and the interaction effect of the number of under-five children with mother's current age are identified as associated risk factors for diarrhoea occurrence among under-five children in rural Ethiopia. The findings show the need for planning and implementing appropriate prevention strategies considering these risk factors for rural under-five children.

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:BackgroundDespite continued efforts to address malnutrition, there is minimal reduction in the prevalence rates of stunting in developing countries, including Ethiopia. The association between nutritional and socioeconomic factors collected from a national survey in Ethiopia and stunting have not been rigorously analyzed. Therefore, this study aims to model the effect of nutritional and socioeconomic predictors using 2016 Ethiopian Demographic Health Survey (EDHS) data.MethodsThis study is a secondary data analysis of the 2016 EDHS survey, which included 7909 children aged 6 to59 months. Descriptive statistics using frequency and percentage for categorical data and mean and standard deviation for metric data were conducted. Linearity, confounding, and multicollinearity were checked. Bivariable and multivariable logistic regression were carried out. The adjusted odds ratio (AOR) and 95% confidence interval (CI) were calculated. A receiver operative curve was built to estimate the sensitivity and specificity of the model.ResultsThe study identified that 39.2% of children included in this analysis were stunted. Furthermore, 76.47, 84.27, and 92.62% of the children did not consume fruits and vegetables, legumes and lentils, or meat and its products, respectively. Children aged 24 months to 59 months were found to be at 9.71 times higher risk of being stunted compared to their younger counterparts aged 6-24 months (AOR: 9.71; CI: 8.07, 11.6 children). Those children weighing below 9.1 kg were at 27.86 odds of being stunted compared to those weighing 23.3 kg and above. Moreover, mothers with a height below 150 cm (AOR: 2.01; CI: 1.76, 2.5), living in a rural area (AOR: 1.3, CI: 1.09, 1.54), and being male (AOR: 1.4; CI: 1.26, 1.56) were factors associated with stunting. The predictive ability of the model was 77%: if a pair of observations with stunted and non-stunted children were taken, the model correctly ranks 77% of such pair of observations.ConclusionThe model indicates that being born male, being from a mother of short stature, living in rural areas, small child size, mother with mild anemia, father having no formal education or primary education only, having low child weight, and being 24-59 months of age increases the likelihood of stunting. On the other hand, being born of an overweight or obese mother decreases the likelihood of stunting.

Project description:IntroductionChildhood vaccination is a cost-effective public health intervention to reduce child mortality and morbidity. But, vaccination coverage remains low, and previous similar studies have not focused on machine learning algorithms to predict childhood vaccination. Therefore, knowledge extraction, association rule formulation, and discovering insights from hidden patterns in vaccination data are limited. Therefore, this study aimed to predict childhood vaccination among children aged 12-23 months using the best machine learning algorithm.MethodsA cross-sectional study design with a two-stage sampling technique was used. A total of 1617 samples of living children aged 12-23 months were used from the 2016 Ethiopian Demographic and Health Survey dataset. The data was pre-processed, and 70% and 30% of the observations were used for training, and evaluating the model, respectively. Eight machine learning algorithms were included for consideration of model building and comparison. All the included algorithms were evaluated using confusion matrix elements. The synthetic minority oversampling technique was used for imbalanced data management. Informational gain value was used to select important attributes to predict childhood vaccination. The If/ then logical association was used to generate rules based on relationships among attributes, and Weka version 3.8.6 software was used to perform all the prediction analyses.ResultsPART was the first best machine learning algorithm to predict childhood vaccination with 95.53% accuracy. J48, multilayer perceptron, and random forest models were the consecutively best machine learning algorithms to predict childhood vaccination with 89.24%, 87.20%, and 82.37% accuracy, respectively. ANC visits, institutional delivery, health facility visits, higher education, and being rich were the top five attributes to predict childhood vaccination. A total of seven rules were generated that could jointly determine the magnitude of childhood vaccination. Of these, if wealth status = 3 (Rich), adequate ANC visits = 1 (yes), and residency = 2 (Urban), then the probability of childhood vaccination would be 86.73%.ConclusionsThe PART, J48, multilayer perceptron, and random forest algorithms were important algorithms for predicting childhood vaccination. The findings would provide insight into childhood vaccination and serve as a framework for further studies. Strengthening mothers' ANC visits, institutional delivery, improving maternal education, and creating income opportunities for mothers could be important interventions to enhance childhood vaccination.

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:ObjectiveThis study aimed to assess the trends and factors that had contributed to the change in home delivery in Ethiopia over the last decade.Design, setting and analysisA nationally representative repeated cross-sectional survey was conducted using 2005, 2011 and 2016 Ethiopian Demographic and Health Surveys. Multivariate decomposition logistic regression analysis was employed to identify significant factors that have been contributed to the change in home delivery. Level of statistical significance was declared at a two-sided p value <0.05.Outcome measureTrends of home delivery.ParticipantsA total of 33 482 women were included.ResultsHome delivery has been decreased by 21% over the last decade in Ethiopia. In the last decade, 39% of the decrements in home delivery attributed to change in women's compositional characteristics. Antenatal care visits, educational status of the women and husband, birth order, religion, wealth index and distance from a health facility were the main sources of compositional change factors for the change of home delivery. Behavioural changes towards health facility delivery contributed approximately two-thirds of the decline of home delivery in Ethiopia. Antenatal care visits, birth order and religion have significantly contributed to the change of home delivery resulted from behavioural changes towards healthcare facility utilisation over the last decade.ConclusionDespite the importance of health facility delivery, a significant number of women still deliver at home in Ethiopia. Women's compositional characteristics and behaviour changes were significantly associated with the change in home delivery. Multisectoral educational intervention is needed to change women's attitudes towards home delivery. Antenatal care coverage and healthcare facility coverage should increase thereby to improve healthcare facility based-delivery practice. Further research needs to be done to explore the potential barriers of health facility delivery from a religious perspective.

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Health care utilization for common childhood illnesses in rural parts of Ethiopia: evidence from the 2016 Ethiopian demographic and health survey.

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