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Modeling the predictors of stunting in Ethiopia: analysis of 2016 Ethiopian demographic health survey data (EDHS).

ABSTRACT: Background:Despite 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. Methods:This 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. Results:The 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. Conclusion:The 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.

SUBMITTER: Mengesha HG

PROVIDER: S-EPMC7507682 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Modeling the predictors of stunting in Ethiopia: analysis of 2016 Ethiopian demographic health survey data (EDHS).

Mengesha Hayelom Gebrekirstos HG Vatanparast Hassan H Feng Cindy C Petrucka Pammla P

BMC nutrition 20200922

<h4>Background</h4>Despite 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.<h4>Methods</h4>T ...[more]

PMID: 32974038

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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: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:IntroductionLack of sanitation is a major global problem mainly for the poor and disadvantaged. According to the 2016 Ethiopian Demographic and Health Surveys (EDHS) report, one out of every three households lack a toilet in Ethiopia and about 56% of rural households use unimproved toilet facilities. We aimed to determine the magnitude of improved household latrine utilization and its determinants in Ethiopia using the mini-Ethiopian Demographic Health Survey (EDHS) 2019 data set.MethodA secondary data analysis was conducted based on the mini 2019 EDHS data set. A total weighted sample of 8663 households were involved in analysis. After selecting the relevant variables for the outcome variable, we have fitted four different models. The null (empty) model with no independent variables and the second model contained the effects of the individual-level factors on the outcome variable. The third model included the influence of the community-level factors on the response variable, and the final multilevel multivariable logistic regression model examined the effects of individual-level and community-level variables on the outcome variable. The measure of variation was quantified using Intra-Class Correlation (ICC), Median Odds Ratio, and Proportional Change in Variance (PCV). The Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) was used to show the strength of association and statistical significance was declared at p value < 0.05.ResultsThe magnitude of improved latrine utilization in Ethiopia was 19.5% with 95% CI (18.6%, 20.3%). The factors: educational status (AOR = 1.67; 95% CI: (1.10, 2.55), highest wealth index (AOR = 3.73; 95% CI: (2.73, 5.12), urban residence (AOR = 3.09; 95% CI: (1.68, 5.67), living in Addis Ababa (AOR = 4.08; 95% CI: (1.03, 16.2) and Dire Dawa (AOR = 8.22; 95% CI: (2.46, 27.42) and Somali regions (AOR = 3.11; 95% CI: (1.15, 8.42) were significantly associated to improved latrine utilization in Ethiopia.ConclusionThe magnitude of improved latrine utilization was quite low in Ethiopia. Higher wealth index, living in more urbanized areas, and the household head's educational status were all significant predictors of improved latrine utilization. The finding implies a need to increase household's access to latrine facilities and improve latrine utilization, particularly for rural households in the country.

Project description:BackgroundThough the consequences of teenage pregnancy and early motherhood has been studied very well, little is known about the magnitude as well as the determinants of adolescent fatherhood. Unlike adolescent motherhood, limited public health programs are working on adolescent fatherhood. Currently, in developed countries, there is an increased work to acknowledge teen fathers in clinical practice and in the research forum, but still, there are more issues that need to be addressed in developing countries including Ethiopia. Therefore, this study aimed to investigate the prevalence and associated factors of adolescent fatherhood in Ethiopia based on the nationally representative survey.MethodsThis study used the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 4455 adolescent men was included for the final analysis. For the associated factors, multilevel logistic regression analysis was conducted to consider the hierarchical nature of the EDHS data. Intra-class Correlation Coefficient (ICC), and deviance (-2LLR) were used for model comparison and for assessing model fitness. The model with the largest adjusted R2, lowest Bayesian Information Criteria (BIC) and the smallest cross-validation prediction error were considered as the best-fitted model. In the multivariable analysis, the Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) were reported to declare the presence of statistically significant factors associated with adolescent fatherhood, and variables with p-value <0.05 were considered as a significant variable.ResultsThe prevalence of adolescent fatherhood in Ethiopia was 6.79% [95%CI; 6.08%, 7.56%]. Adolescent men with contraceptive knowledge [AOR = 4.25; 95%CI = 1.23, 14.69], age in 20 to 24 years [AOR = 7.93; 95%CI = 3.66, 17.27] and being Muslim [AOR = 1.84; 95%CI = 1.02, 3.39] were significantly associated with Higher odds of adolescent fatherhood. Individuals who initiate sex lately [AOR = 0.35; 95%CI = 0.22, 0.54], being in female-headed family [AOR = 0.46; 95%CI; 0.26, 0.82] and being from Amhara region [AOR = 0.35; 95%CI = 0.14, 0.84] were significantly associated with lower odds of adolescent fatherhood.ConclusionIn this study, adolescent fatherhood was a common public health problem in Ethiopia as it is closely linked with poor quality of life and premature death (year of potential life lost). Age of respondent, knowledge of respondent about contraceptive methods, early initiation of sex, religion, sex of household head, and region were significantly associated with adolescent fatherhood. Therefore, program planners and decision-makers should give special attention to adolescent men through enhancing reproductive health services utilization and their knowledge towards it to decrease the incidence of adolescent fatherhood.

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: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: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.

Dataset Information

Modeling the predictors of stunting in Ethiopia: analysis of 2016 Ethiopian demographic health survey data (EDHS).

Publications

Modeling the predictors of stunting in Ethiopia: analysis of 2016 Ethiopian demographic health survey data (EDHS).

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