Spatial Distribution of Infant Mortality in Ethiopia: Using Demographic Health Survey, the Ethiopia

Abstract Background Mortality is one of the demographic variables that affect population trends. Among mortality of children, Infant mortality contributed to more than 75% of all under-five deaths globally. It disproportionately affects those living in the different regions of countries and within the region. Exploring the spatial distribution and identifying associated factors is important to design effective intervention programs to reduce infant mortality. Thus, this study aimed to assess the spatial distribution and associated factors of infant mortality in Ethiopia using the 2016 Ethiopian Demographic and Health Survey (EDHS). Method The Data this study were used Ethiopian Demographic and Health Survey in 2016. A total of 11,023 live births from the EDHS data were included in the analysis. Spatial analysis was done to explore spatial distribution of infant mortality using ArcGIS version 10.4. Results This study revealed that the spatial distribution of infant mortality was non-random in the country with Moran’s index 0.1546 (P-value=0.0185). The Afar and Somali regions of Ethiopia were identified in this study on the hot spot of infant mortality. Conclusions The spatial distribution of infant mortality varies across the country. ANC usage, sex of a child, birth interval, birth size, birth type, birth order, wealth index, residence, region, and the spatial variable (Si) were significant predictors of infant mortality. Therefore, it needs interventions in the hot spot areas. Focusing on maternal health care services, rural residences, multiple births, infants having a smaller birth size, and male infants deserves special attention.

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

PLoS ONE ◽

10.1371/journal.pone.0242744 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0242744

Author(s):

Biruk Shalmeno Tusa ◽

Adisu Birhanu Weldesenbet ◽

Sewnet Adem Kebede

Keyword(s):

Spatial Distribution ◽

Cigarette Smoking ◽

Health Survey ◽

Associated Factors ◽

Hot Spot ◽

Secondary Data ◽

Binary Logistic Regression ◽

Wealth Index ◽

P Value ◽

Data Set

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 < 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. 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.

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Spatial distribution and associated factors’ of Early Marriage among Reproductive age women in Ethiopia: A Secondary Data Analysis of Ethiopian Demographic and Health Survey 2016.

10.21203/rs.2.23055/v3 ◽

2020 ◽

Author(s):

Zemenu Tessema Tadesse

Keyword(s):

Spatial Distribution ◽

Health Survey ◽

Associated Factors ◽

Demographic And Health Survey ◽

Reproductive Age ◽

Scan Statistics ◽

Early Marriage ◽

P Value ◽

Factors Associated ◽

Reproductive Age Women

Abstract Background Besides, the presence of national law, the country has to set up its own mid-term and long term goals to bring about a significant reduction in child marriages in Ethiopia. To achieve this, determining the spatial pattern of early marriage and factors associated is important for government, other concerned bodies, program implementers and policy developers to end up early childhood marriage. Thus, the aim of this study was to assess the spatial patterns and associated factors of Early marriage among reproductive-age women in Ethiopia. Methods This study analyzed retrospectively a cross-sectional data on a weighted sample of 11,646 women aged 15-49 years after requesting from Ethiopian Demographic and Health Survey 2016 via the link www.measuredhs.com . ArcGIS version 10.7 software was used to visualize spatial distribution for Early marriage. The Bernoulli model was applied using Kilduff SaTScan version 9.6 software to identify significant purely spatial clusters for Early marriage in Ethiopia multiple logistic regression analysis was used to identify factors associated with early marriage. Finally, variables with a p-value<0.05 were considered as statistically significant. Results In this analysis, about 62.8% (95%CI: 61.9, 63.74%) of the study participants were married before they reached 18 years. The overall median age at first marriage was 17.1 with IQR 5 years. The high clustering of early marriage was located in Amhara, Afar, and Gambella Regions. In spatial Scan statistics 87 clusters (RR = 1.28, P-value < 0.001) significant primary clusters were identified. The associated factors of early marriage were lesser among women’s attending primary (AOR=0.60; 95%CI: 0.51, 0.71), secondary (AOR=0.19; 95%CI: 0.13, 0.26) and tertiary education (AOR=0.11; 95%CI: 0.07, 0.18). Similarly, women found in Addis Ababa were at a lesser risk of early marriage compared to other regions of the country. Conclusion Marriage below age 18 was high in Ethiopia. High-risk area of early marriage was located in Amhara, Afar, and Gambella and special attention should be given for identified risk areas. Therefore, providing educational opportunities to young girls was important in addition to inhibiting the marriage of girls under 18 years.

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Households access to improved drinking water sources and toilet facilities in Ethiopia: a multilevel analysis based on 2016 Ethiopian Demographic and Health Survey

BMJ Open ◽

10.1136/bmjopen-2020-042071 ◽

2021 ◽

Vol 11 (3) ◽

pp. e042071

Author(s):

Zewudu Andualem ◽

Henok Dagne ◽

Zelalem Nigussie Azene ◽

Asefa Adimasu Taddese ◽

Baye Dagnew ◽

...

Keyword(s):

Drinking Water ◽

Health Survey ◽

Rural Households ◽

Wealth Index ◽

Water Sources ◽

Demographic And Health Survey ◽

P Value ◽

Cluster Sampling ◽

Drinking Water Source ◽

Drinking Water Sources

ObjectiveThis study aimed to assess households access to improved drinking water sources and sanitation facilities and their associated factors in Ethiopia.DesignCross-sectional study.SettingEthiopia.ParticipantsHousehold heads.Primary outcomesAccess to improved drinking water sources and toilet facilities.MethodsWe conducted an in-depth secondary data analysis of 2016 Ethiopian Demographic and Health Survey. Data from a total of 16 650 households and 645 clusters were included in the analysis. The households were selected using a stratified two-stage cluster sampling technique. Multilevel binary logistic regression analyses were performed to identify factors associated with access to an improved drinking water source and toilet facilities. Adjusted OR with a 95% CI was reported with p value <0.05 was used to declare a significant association between the covariates and the outcome variables.ResultsThe proportions of households’ access to improved sources of drinking water and toilet facilities were 69.94% (95% CI: 69.23% to 70.63%) and 25.36% (95% CI: 24.69% to 26.03%), respectively. Households headed by women and households with a better wealth index were positively associated with access to improved drinking water sources. Whereas rural households, ≥30 min round trip to obtain drinking water and region were factors negatively associated with households access to improved drinking water sources. A higher probability of having access to improved toilet facilities: households with heads who had attained higher education, households having better access to improved sources of drinking water and households with better wealth index. While the following households were less likely to have access to improved toilet facilities: households with heads were widowed, households with four to six members, rural households and region.ConclusionThe study found that the proportions of households’ access to improved drinking water sources and toilet facilities in Ethiopia were relatively low, which demands the need to tailor strategies to increase the coverage of access to improved drinking water sources and toilet facilities.

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Spatial distribution of iron rich foods consumption and its associated factors among children aged 6–23 months in Ethiopia: spatial and multilevel analysis of 2016 Ethiopian demographic and health survey

Nutrition Journal ◽

10.1186/s12937-020-00635-8 ◽

2020 ◽

Vol 19 (1) ◽

Author(s):

Sofonyas Abebaw Tiruneh ◽

Belete Achamyelew Ayele ◽

Getachew Yideg Yitbarek ◽

Desalegn Tesfa Asnakew ◽

Melaku Tadege Engidaw ◽

...

Keyword(s):

Spatial Distribution ◽

Health Survey ◽

Associated Factors ◽

Household Wealth ◽

Demographic And Health Survey ◽

Scan Statistics ◽

Nutritional Deficiencies ◽

Spatial Scan Statistics ◽

Developmental Problems ◽

Spatial Scan

Abstract Background Micronutrient deficiencies are the most prevalent nutritional deficiencies that cause serious developmental problems in the globe. The aim of this study was to assess the spatial distribution of iron rich foods consumption and its associated factors among children aged 6–23 months in Ethiopia. Methods The data retrieved from the standard Ethiopian Demographic and Health Survey 2016 dataset with a total sample size of 3055 children aged 6–23 months. Spatial scan statistics done using Kuldorff’s SaTScan version 9.6 software. ArcGIS version 10.7 software used to visualize spatial distribution for poor consumption of iron rich foods. Multilevel mixed-effects logistic regression analysis employed to identify the associated factors for good consumption of iron-rich foods. Level of statistical significance was declared at a two-sided P-value < 0.05. Results Overall, 21.41% (95% CI: 19.9–22.9) of children aged 6–23 months had good consumption of iron rich foods in Ethiopia. Poor consumption of iron rich foods highly clustered at Southern Afar, Southeastern Amhara and Tigray, and the Northern part of Somali Regional States of Ethiopia. In spatial scan statistics, children aged 6–23 months living in the most likely cluster were 21% more likely vulnerable to poor consumption of iron rich foods than those living outside the window (RR = 1.21, P-value < 0.001). Child aged 12–17 months (AOR = 1.90, 95% CI: 1.45–2.49) and 18–23 months (AOR = 2.05, 95% CI: 1.55–2.73), primary (AOR = 1.42, 95% CI:1.06–1.87) and secondary and above (AOR = 2.26, 95% CI: 1.47–3.46) mother’s education level, rich (AOR = 1.49, 95% CI: 1.04–2.13) and middle (AOR = 1.83, 95% CI: 1.31–2.57) household wealth status, Amhara (AOR = 0.24, 95% CI: 0.09–0.60), Afar (AOR = 0.38, 95% CI: 0.17–0.84), and Harari (AOR = 2.11, 95% CI: 1.02–4.39) regional states of Ethiopia were statistically significant factors for good consumption of iron rich foods. Conclusion Overall, the consumption of iron rich foods was low and spatially non-random in Ethiopia. Federal Ministry of Health and other stakeholders should give prior attention to the identified hot spot areas to enhance the consumption of iron rich foods among children aged 6–23 months.

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Spatial distribution and determinant factors of Female Genital Mutilation among reproductive age women in Ethiopia, 2016; Based on Ethiopian National Demographic and Health Survey

10.21203/rs.2.13810/v1 ◽

2019 ◽

Author(s):

Atalay Goshu Muluneh ◽

Getahun Molla Kassa ◽

Mehari Mariam Merid

Keyword(s):

Spatial Distribution ◽

Spatial Analysis ◽

Health Survey ◽

Female Genital Mutilation ◽

Data Cleaning ◽

Demographic And Health Survey ◽

P Value ◽

Genital Mutilation ◽

Female Genital ◽

Variable Analysis

Abstract Background : Though condemned and considered as a crime by the countries government, Female Genital Mutilation (FGM) remains a common public health problem in Africa and Ethiopia as well. Thus, this study was aimed to assess the spatial distribution and associated factors of female genital mutilation in Ethiopia based on the Ethiopian demographic and Health survey 2016 data. Method: This is a secondary data analysis of Ethiopian Demographic and Health Survey (EDHS) 2016 data based on 7,163 women who were included for FGM interview. The data was weighted using sampling weight as recommended by the program. The MS excel and ArcGIS 10.3 softwares were used for data cleaning and spatial analysis respectively. Global and local level clustering was assessed. For the none spatial data and the determinant factors, data cleaning and analysis was done using STATA 14. Multi-level mixed effect logistic regression model was fitted. Variables with P-value <0.25 in the bi-variable analysis were fitted in the multi-variable analysis. Finally, variables with p-value <0.05 with 95% CI of adjusted odds ratio were reported as a statistically significant determinants of FGM. Result : Female genital mutilation was spatially clustered (Global Moran’s I: 0.46, p<0.001). Significant hot spot clusters were found in Amhara, Oromia, Southern Nations Nationalities and Peoples (SNNP) regions. Mothers age >30 (AOR=2.41, 95% CI: 1.78,3.26) years, never in union (AOR=0.31, 95%CI: 0.22, 0.44), currently not working (AOR=0.71, 95%CI: 0.55, 0.92), women who considered FGM to be continued (AOR=2.86, 95%CI: 1.75, 4.68), not heard of FGM (AOR=0.22, 95%CI: 0.08,0.62), had no formal education (AOR=1.67, 95% CI: 1.03, 2.71), muslim (AOR=3.90, 95%CI:2.5, 6.09) and protestant (AOR=1.76, 95%CI: 1.25, 2.97), and those who thought of FGM as required by religion (AOR=1.99, 95%CI: 1.31,2.99) were found to be significant determinants of female genital mutilation. Conclusion: Female genital mutilation was spatially clustered with hotspot areas located. in Amhara, Oromia, and SNNP regions . Age of the mother, religion, occupation, educational level, marital status, information about Female genital mutilation, and intention about FGM to be stopped or continued were significant determinants of female genital mutilation Key words : Female Genital Mutilations, Spatial analysis

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Prevalence and Determinants of Pre-lacteal Feeding: Insights from the 2017 Indonesia Demographic and Health Survey

Kesmas National Public Health Journal ◽

10.21109/kesmas.v16i2.4283 ◽

2021 ◽

Vol 16 (2) ◽

Author(s):

Siti Nurokhmah ◽

Siti Masitoh ◽

Kusuma Estu Werdani

Keyword(s):

Health Survey ◽

Wealth Index ◽

Household Wealth ◽

Early Initiation ◽

Demographic And Health Survey ◽

Birth Size ◽

Feeding Practice ◽

Gender Role Attitude ◽

Early Initiation Of Breastfeeding ◽

Initiation Of Breastfeeding

Pre-lacteal feeding is a challenge to optimal breastfeeding practices in developing countries, and it directly or indirectly affects the health of infants. Furthermore, it is widely known as a distraction to exclusive breastfeeding, and the malpractice continues to be prevalent in Indonesia. Therefore, this study aimed to explore the potential determinants of pre-lacteal feeding among mothers of infants below aged 24 months. A sample of 6,455 mother-infant pairs from the 2017 Indonesia Demographic and Health Survey (IDHS) was used. Also, multivariate logistic regression was employed to identify factors associated with pre-lacteal feeding practice. In Indonesia, 44.0% of infants were introduced to solid/liquid feeds in their first three days of life. Infant formula was the most common pre-lacteal feed given, followed by any other milk, plain and sugar water, and honey. Early initiation of breastfeeding and living in an urban area were protective method against pre-lacteal feeding (AOR: 0.24; 95% CI: 0.21-0.28; AOR: 0.76; 95% CI: 0.65-0.90, respectively), while cesarean delivery acted as a risk factor (AOR: 1.36; 95% CI: 1.14-1.63). Meanwhile, gender role attitude, parity, perceived birth size, and household wealth index was also associated with pre-lacteal feeding. Overall, the percentage of mothers introducing pre-lacteal feeds was still high. The modifiable covariates associated with pre-lacteal feedings, such as early initiation of breastfeeding, parity, and birth size were the major factors discouraging this practice.

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Spatial patterns and associated factors’ of Early Marriage among Reproductive age women in Ethiopia: a Secondary Analysis of Ethiopian Demographic and Health Survey 2016

10.21203/rs.2.23055/v1 ◽

2020 ◽

Author(s):

Zemenu Tessema Tadesse

Keyword(s):

Spatial Patterns ◽

Health Survey ◽

Associated Factors ◽

Demographic And Health Survey ◽

Reproductive Age ◽

Scan Statistics ◽

Early Marriage ◽

P Value ◽

Factors Associated ◽

Reproductive Age Women

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Spatial distribution and associated factors of health insurance coverage in Ethiopia: further analysis of Ethiopia demographic and health survey, 2016

Archives of Public Health ◽

10.1186/s13690-020-00407-0 ◽

2020 ◽

Vol 78 (1) ◽

Author(s):

Sewnet Adem Kebede ◽

Alemneh Mekuriaw Liyew ◽

Getayeneh Antehunegn Tesema ◽

Chilot Desta Agegnehu ◽

Achamyeleh Birhanu Teshale ◽

...

Keyword(s):

Spatial Distribution ◽

Health Insurance ◽

Health Survey ◽

Associated Factors ◽

Insurance Coverage ◽

Health Insurance Coverage ◽

Demographic And Health Survey

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Time to death and its associated factors among infants in sub-Saharan Africa using the recent demographic and health surveys: shared frailty survival analysis

BMC Pediatrics ◽

10.1186/s12887-021-02895-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Sofonyas Abebaw Tiruneh ◽

Ejigu Gebeye Zeleke ◽

Yaregal Animut

Keyword(s):

Survival Analysis ◽

Infant Mortality ◽

Health Survey ◽

Associated Factors ◽

Demographic And Health Survey ◽

Sub Saharan Africa ◽

Time To Death ◽

Live Births ◽

Shared Frailty ◽

Sub Saharan

Abstract Background Globally, approximately 4.1 million infants died, accounting for 75% of all under-five deaths. In sub-Saharan Africa (SSA), infant mortality was 52.7/1000 live births in 2018 This study aimed to assess the pooled estimate of infant mortality rate (IMR), time to death, and its associated factors in SSA using the recent demographic and health survey dataset between 2010 and 2018. Methods Data were retrieved from the standard demographic and health survey datasets among 33 SSA countries. A total of 93,765 samples were included. The data were cleaned using Microsoft Excel and STATA software. Data analysis was done using R and STATA software. Parametric shared frailty survival analysis was employed. Statistical significance was declared as a two-side P-value < 0.05. Results The pooled estimate of IMR in SSA was 51 per 1000 live births (95% Confidence Interval (CI): 46.65–55.21). The pooled estimate of the IMR was 53 in Central, 44 in Eastern, 44 in Southern, and 57 in Western Africa per 1000 live births. The cumulative survival probability at the end of 1 year was 56%. Multiple births (Adjusted Hazard ratio (AHR) = 2.68, 95% CI: 2.54–2.82), low birth weight infants (AHR = 1.28, 95% CI: 1.22–1.34), teenage pregnancy (AHR = 1.19, 95 CI: 1.10–1.29), preceding birth interval < 18 months (AHR = 3.27, 95% CI: 3.10–3.45), birth order ≥ four (AHR = 1.14, 95% CI:1.10–1.19), home delivery (AHR = 1.08, 95% CI: 1.04–1.13), and unimproved water source (AHR = 1.07, 95% CI: 1.01–1.13), female sex (AHR = 0.86, 95% CI: 0.83–0.89), immediately breastfeed (AHR = 0.24, 95% CI: 0.23–0.25), and educated mother (AHR = 0.88, 95% CI: 0.82–0. 95) and educated father (AHR = 0.90, 95% CI: 0.85–0.96) were statistically significant factors for infant mortality. Conclusion Significant number of infants died in SSA. The most common cause of infant death is a preventable bio-demographic factor. To reduce infant mortality in the region, policymakers and other stakeholders should pay attention to preventable bio-demographic risk factors, enhance women education and improved water sources.

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Spatial distribution and associated factors’ of early marriage among reproductive age women in Ethiopia: a secondary data analysis of Ethiopian Demographic and Health Survey 2016

BMC Women s Health ◽

10.1186/s12905-020-01103-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Zemenu Tadesse Tessema

Keyword(s):

Spatial Distribution ◽

Health Survey ◽

Associated Factors ◽

Multiple Logistic Regression Analysis ◽

Demographic And Health Survey ◽

Reproductive Age ◽

Scan Statistics ◽

Early Marriage ◽

Factors Associated ◽

Reproductive Age Women

Abstract Background Besides, the presence of national law, the country has to set up its own mid-term and long term goals to bring about a significant reduction in child marriages in Ethiopia. As my search concerned, there is no study conducted on the spatial distribution of early marriage in Ethiopia. Determining the spatial distribution of early marriage and factors associated is important for government, other concerned bodies, program implementers, and policy developers to end up early childhood marriage. Thus, this study aimed to assess the spatial distribution and associated factors of Early marriage among reproductive-age women in Ethiopia. Methods This study analyzed retrospectively a cross-sectional data on a weighted sample of 11,646 reproductive age women after requesting from Ethiopian Demographic and Health Survey 2016. ArcGIS and SaTScan software were for spatial analysis. Multiple logistic regression analysis was used to identify factors associated with early marriage. Finally, variables with a p-value of less than or equal 0.05 were considered as statistically significant. Results In this analysis, about 62.8% (95% CI 61.9, 63.74%) of the study participants were married before they reached 18 years. The overall median age at first marriage was 17.1 with IQR 5 years. The high clustering of early marriage was located in Amhara, Afar, and Gambella Regions. In spatial Scan statistics, 87 clusters (RR = 1.28) significant primary clusters were identified. The associated factors of early marriage were lesser among women’s attending primary (AOR = 0.60; 95% CI 0.51, 0.71), secondary (AOR = 0.19; 95% CI 0.13, 0.26) and tertiary education (AOR = 0.11; 95% CI 0.07, 0.18). Similarly, women found in Addis Ababa were at a lesser risk of early marriage compared to other regions of the country. Conclusion Marriage below age 18 is high in Ethiopia. High-risk area of early marriage was located in Amhara, Afar, and Gambella. Governmental and non-governmental organizations should design an effective intervention in these regions to reduce Early marriage. Therefore, providing educational opportunities to young girls was important in addition to inhibiting the marriage of girls under 18 years.

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