Abstract

The 2016 Ethiopia Demographic and Health Survey (EDHS) is the fourth Demographic and Health Survey conducted in Ethiopia. It was implemented by the Central Statistical Agency (CSA) at the request of the Federal Ministry of Health (FMoH). Data collection took place from January 18, 2016, to June 27, 2016.

SURVEY OBJECTIVES The primary objective of the 2016 EDHS is to provide up-to-date estimates of key demographic and health indicators. The EDHS provides a comprehensive overview of population, maternal, and child health issues in Ethiopia. More specifically, the 2016 EDHS: - Collected data at the national level that allowed calculation of key demographic indicators, particularly fertility and under-5 and adult mortality rates - Explored the direct and indirect factors that determine levels and trends of fertility and child mortality - Measured levels of contraceptive knowledge and practice - Collected data on key aspects of family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery - Obtained data on child feeding practices, including breastfeeding - Collected anthropometric measures to assess the nutritional status of children under age 5, women age 15-49, and men age 15-59 - Conducted haemoglobin testing on eligible children age 6-59 months, women age 15-49, and men age 15-59 to provide information on the prevalence of anaemia in these groups - Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviours and condom use - Conducted HIV testing of dried blood spot (DBS) samples collected from women age 15-49 and men age 15-59 to provide information on the prevalence of HIV among adults of reproductive age - Collected data on the prevalence of injuries and accidents among all household members - Collected data on knowledge and prevalence of fistula and female genital mutilation or cutting (FGM/C) among women age 15-49 and their daughters age 0-14 - Obtained data on women’s experience of emotional, physical, and sexual violence.

As the fourth DHS conducted in Ethiopia, following the 2000, 2005, and 2011 EDHS surveys, the 2016 EDHS provides valuable information on trends in key demographic and health indicators over time. The information collected through the 2016 EDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Additionally, the 2016 EDHS included a health facility component that recorded data on children’s vaccinations, which were then combined with the household data on vaccinations.

Geographic coverage

National coverage

Analysis unit

• Households
• Men
• Women
• Children

Universe

Household members women age 15-49 men age 15-59 children under age 5

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2016 EDHS is the Ethiopia Population and Housing Census (PHC), which was conducted in 2007 by the Ethiopia Central Statistical Agency. The census frame is a complete list of 84,915 enumeration areas (EAs) created for the 2007 PHC. An EA is a geographic area covering on average 181 households. The sampling frame contains information about the EA location, type of residence (urban or rural), and estimated number of residential households. With the exception of EAs in six zones of the Somali region, each EA has accompanying cartographic materials. These materials delineate geographic locations, boundaries, main access, and landmarks in or outside the EA that help identify the EA. In Somali, a cartographic frame was used in three zones where sketch maps delineating the EA geographic boundaries were available for each EA; in the remaining six zones, satellite image maps were used to provide a map for each EA.

Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2016 EDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the nine regions and the two administrative cities.

The 2016 EDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling.

In the first stage, a total of 645 EAs (202 in urban areas and 443 in rural areas) were selected with probability proportional to EA size (based on the 2007 PHC) and with independent selection in each sampling stratum. A household listing operation was carried out in all of the selected EAs from September to December 2015. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs were large, consisting of more than 300 households. To minimise the task of household listing, each large EA selected for the 2016 EDHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2016 EDHS cluster is either an EA or a segment of an EA.

In the second stage of selection, a fixed number of 28 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 and all men age 15-59 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the selected households, all women age 15-49 were eligible for the FGM/C module, and only one woman per household was selected for the domestic violence module. In all of the selected households, height and weight measurements were collected from children age 0-59 months, women age 15-49, and men age 15-59. Anaemia testing was performed on consenting women age 15-49 and men age 15-59 and on children age 6-59 months whose parent/guardian consented to the testing. In addition, DBS samples were collected for HIV testing in the laboratory from women age 15-49 and men age 15-59 who consented to testing.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2016 EDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Health Facility Questionnaire. These questionnaires, based on the DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After all questionnaires were finalised in English, they were translated into Amarigna, Tigrigna, and Oromiffa.

The Household Questionnaire was used to list all members of and visitors to selected households. Basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, marital status, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, and flooring materials, as well as on ownership of various durable goods. The Household Questionnaire included an additional module developed by the DHS Program to estimate the prevalence of injuries/accidents among all household members.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics: - Background characteristics (including age, education, and media exposure) - Birth history and childhood mortality - Family planning, including knowledge, use, and sources of contraceptive methods - Fertility preferences - Antenatal, delivery, and postnatal care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Women’s work and husbands’ background characteristics - Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted diseases (STDs) - Knowledge, attitudes, and behaviours related to other health issues (e.g., injections, smoking, use of chat) - Adult and maternal mortality - Female genital mutilation or cutting - Fistula - Violence against women The Man’s Questionnaire was administered to all eligible men age 15-59. This questionnaire collected much of the same information elicited from the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history, questions on maternal and child health, or questions on domestic violence. The Biomarker Questionnaire was used to record biomarker data

Abstract

The 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) is a nationwide survey with a nationally representative sample of 9,150 selected households. All women age 15-49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In the selected households, all children under age 5 were eligible for height and weight measurements. The survey was designed to produce reliable estimates of key indicators at the national level as well as for urban and rural areas and each of the 11 regions in Ethiopia.

The primary objective of the 2019 EMDHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the main objectives of the survey are: ▪ To collect high-quality data on contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; child nutrition; and other health issues relevant to achievement of the Sustainable Development Goals (SDGs) ▪ To collect information on health-related matters such as breastfeeding, maternal and child care (antenatal, delivery, and postnatal), children’s immunizations, and childhood diseases ▪ To assess the nutritional status of children under age 5 by measuring weight and height

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Health facility

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019 EMDHS is a frame of all census enumeration areas (EAs) created for the 2019 Ethiopia Population and Housing Census (EPHC) and conducted by the Central Statistical Agency (CSA). The census frame is a complete list of the 149,093 EAs created for the 2019 EPHC. An EA is a geographic area covering an average of 131 households. The sampling frame contains information about EA location, type of residence (urban or rural), and estimated number of residential households.

Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2019 EMDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the nine regions and the two administrative cities.

The 2019 EMDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling.

To ensure that survey precision was comparable across regions, sample allocation was done through an equal allocation wherein 25 EAs were selected from eight regions. However, 35 EAs were selected from each of the three larger regions: Amhara, Oromia, and the Southern Nations, Nationalities, and Peoples’ Region (SNNPR).

In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size (based on the 2019 EPHC frame) and with independent selection in each sampling stratum. A household listing operation was carried out in all selected EAs from January through April 2019. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs for the 2019 EMDHS were large, with more than 300 households. To minimise the task of household listing, each large EA selected for the 2019 EMDHS was segmented. Only one segment was selected for the survey, with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2019 EMDHS cluster is either an EA or a segment of an EA.

In the second stage of selection, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 who were either permanent residents of the selected households or visitors who slept in the household the night before the survey were eligible to be interviewed. In all selected households, height and weight measurements were collected from children age 0-59 months, and women age 15-49 were interviewed using the Woman’s Questionnaire.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019 EMDHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Anthropometry Questionnaire, (4) the Health Facility Questionnaire, and (5) the Fieldworker’s Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. They were shortened substantially to collect data on indicators of particular relevance to Ethiopia and donors to child health programmes.

Cleaning operations

All electronic data files were transferred via the secure internet file streaming system (IFSS) to the EPHI central office in Addis Ababa, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by EPHI staff members and an ICF consultant who took part in the main fieldwork training. They were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro System software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing, double data entry from both the anthropometry and health facility questionnaires, and data processing were initiated in April 2019 and completed in July 2019.

Response rate

A total of 9,150 households were selected for the sample, of which 8,794 were occupied. Of the occupied households, 8,663 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 9,012 eligible women were identified for individual interviews; interviews were completed with 8,885 women, yielding a response rate of 99%. Overall, there was little variation in response rates according to residence; however, rates were slightly higher in rural than in urban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 EMDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 EMDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution

- Age distribution of eligible and interviewed women

Child and maternal, characteristics and health service usage finding from 2000 to 2016 DHS.

Analysis unit

Woman, Birth, Child, Birth, Man, Household Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-59, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: Central Statistical Agency [Ethiopia] and ICF.

SAMPLE UNIT: Woman SAMPLE SIZE: 15683

SAMPLE UNIT: Birth SAMPLE SIZE: 41392

SAMPLE UNIT: Child SAMPLE SIZE: 10641

SAMPLE UNIT: Man SAMPLE SIZE: 12688

SAMPLE UNIT: Member SAMPLE SIZE: 75224

Mode of data collection

Face-to-face [f2f]

The magnitude of cesarean section rate across the various characteristics of the respondents in Ethiopia, finding from 2000 to 2016.

Ethiopia ET: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data was reported at 70.600 % in 2016. This records an increase from the previous number of 54.400 % for 2011. Ethiopia ET: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data is updated yearly, averaging 54.400 % from Dec 2005 (Median) to 2016, with 3 observations. The data reached an all-time high of 70.600 % in 2016 and a record low of 45.400 % in 2005. Ethiopia ET: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).; ; Demographic and Health Surveys (DHS); ;

Number (percent) of SPA facilities linked to DHS clusters by linking method.

This poverty assessment focuses on the evolution of poverty and other social indicators in Ethiopia between 2010-11 and 2015-2016 (henceforth referred to as 2011 and 2016). Using data from a variety of sources, mainly the twinned household living standards surveys (HCES and WMS), the Ethiopia Socioeconomic Survey (ESS) and the Demographic and Health Surveys (DHS), the poverty assessment documents trends in monetary and non-monetary dimensions of living standards and examines the drivers of observed trends, with a special focus on government programs. The aim of the poverty assessment is to provide policy makers and development partners with information and analysis that can be used to improve the effectiveness of their poverty reduction and social programs.

Characteristics of HIV tested, sexually active, young women in Ethiopia, EDHS 2016 (N = 1003).

The poverty headcount in Ethiopia is falling. The share of the population below the national poverty line decreased from 30 percent in 2011 to 24 percent in 2016. This decrease was achieved in spite of the fact that the 2015-16 survey was conducted during the severe El-Nino drought. The observed reduction in poverty is robust to the use of alternative deflators. The fall in the poverty headcount was driven mainly by Ethiopia’s strong economic growth over that period. This poverty assessment focuses on the evolution of poverty and other social indicators in Ethiopia between 2011 and 2016. It uses data from a variety of sources, mainly the Household Consumption and Expenditure Survey (HCES), the Welfare Monitoring Surveys (WMS), the Ethiopia Socioeconomic Survey (ESS) and the Demographic and Health Surveys (DHS), to observe trends in monetary and non-monetary dimensions of living standards and to examine the drivers of these trends, with a special focus on government programs. The aim of the poverty assessment is to provide policymakers and development partners with information and analysis that can be used to improve the effectiveness of their poverty reduction and social programs.

Low birth weight is a significant risk factor associated with high rates of neonatal and infant mortality, particularly in developing countries. However, most studies conducted on this topic in Ethiopia have small sample sizes, often focusing on specific areas and using standard models employing maximum likelihood estimation, leading to potential bias and inaccurate coverage probability. This study used a novel approach, the Bayesian rank likelihood method, within a latent traits model, to estimate parameters and provide a nationwide estimate of low birth weight and its risk factors in Ethiopia. Data from the Ethiopian Demographic and Health Survey (EDHS) of 2016 were used as a data source for the study. Data stratified all regions into urban and rural areas. Among 15, 680 representative selected households, the analysis included complete cases from 10, 641 children. The evaluation of model performance considered metrics such as the root mean square error, the mean absolute error, and t..., , , # Rank likelihood-based estimation of low birth weight in Ethiopia

Low birth weight data was obtained from the Ethiopian Demographic and Health Survey (EDHS).

Raw data: Lowbirthweight.sav

Description of the data and file structure

Lowbirthweightdata_data

childweight: categorical weight of the child at birth motherage: age of the mothers ancvisti: number of antenatal care visits that the mothers attended birthorder: order of birth for the child birthinterval: time between successive births (months) bmi: body mass index of the mothers Regions: the region where the child born CLID: cluster-level ID that indicates from which cluster the information is obtained

Sharing or accessing information

Our data is taken from the DHS website (http://dhsprogram.com. Low birth weight data was extracted from the 2016 EDHS. EDHS 2016 was conducted using standardized survey design and data collection procedures.

Multivariate multilevel logistic regression analysis for determinants of AAP from Ethiopian DHS 2016 in Ethiopia.

This interactive map of Ethiopia identifies the woredas (districts) where the AGP is active. GAFSP contributes about 23% of the total AGP financing, which is also supported by other development partners, including the Canadian International Development Agency (CIDA), the Spanish Agency for International Development Cooperation (AECID), the Kingdom of the Netherlands, the United Nations Development Program (UNDP), and the United States Agency for International Development (USAID). GAFSP funds are being channeled into a pooled AGP fund to increase donor coordination and to decrease project administrative costs. The map is broken down into 11 regions, 81 zones, and 550 woredas (districts). The 83 AGP project areas (at the woreda level) are spread across the four regions of Amhara, Oromiya, Tigray, and Southern Nations, Nationalities, and Peoples Region (SNNPR). AGP activities are primarily in the highlands temperate mixed zones, where the climatic conditions are relatively temperate and that, with AGP support, have considerable potential for agricultural growth. In these areas, small-scale farmers crop an average area of less than 1 hectare (ranging between 0.25 and 2.3 hectares). The interactive map shows sub-national poverty and population density data, as well as information on the predominant farming systems in the various regions. Data Sources: AGP Project LocationsSource: Project Appraisal Document (PAD). Africa Juice Project LocationSource: IFC - GAFSP Documents. Poverty (Proportion of population below the poverty line) (2005): Proportion of the population living on less than US$1.25 a day, measured at 2005 international prices, adjusted for purchasing power parity (PPP).Source: Harvest Choice / Multiple national household surveys; PovcalNet; The World Bank; and Centro Internacional de Agricultura Tropical (CIAT). 2011. Sub-national poverty headcount ratios derived from 23 nationally representative household surveys and population census information conducted in various years. Rates are for the $1.25/day (extreme poverty) expressed in 2005 international equivalent purchasing power parity (PPP) dollars. Rates are in percentages of total population. (Aggregation type: WGHTD). Poverty (Proportion of population below the poverty line) (2011): Proportion of the population living on less than 3,781 Birr per adult per year.Source: Ministry of Finance and Economic Development. “Ethiopia’s Progress Towards Eradicating Poverty: An Interim Report on Poverty Analysis Study (2010/11).” Malnutrition (Proportion of underweight children under 5 years) (2011): Prevalence of severely underweight children is the percentage of children aged 0-59 months whose weight-for-age is less than minus 3 standard deviations below the median weight for age of the international reference population.Source: “Demographic and Health Survey 2011.” Measure DHS.MEASURE DHS (Demographic and Health Surveys) Project is responsible for collecting and disseminating accurate, nationally representative data on health and population in developing countries. The project is implemented by Macro International, Inc. and is funded by the United States Agency for International Development (USAID) with contributions from other donors such as UNICEF, UNFPA, WHO, UNAIDS. Malnutrition (Proportion of underweight children under 5 years) (2016): Prevalence of severely underweight children is the percentage of children aged 0-59 months whose weight for age is less than minus 3 standard deviations below the median weight for age of the international reference population.Source: Central Statistical Agency CAS. “Demographic and Health Survey 2016.” Measure DHS. Population Density (Persons per 1 square kilometer) (2007): Population divided by land area in square kilometers.Total population (2015): Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship, except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin.Source: Central Statistical Agency CAS. Projections based on the results of the May 2007 National Population and Housing Census of Ethiopia. Population Density (2015): Population divided by land area in square kilometers.Source: Central Statistical Agency CAS. Projections based on the results of the May 2007 National Population and Housing Census of Ethiopia. Market Centers: Key market centers for retail, assembly and/ or wholesale of agricultural products. FEWS NET reference markets.Source: FEWS Net. The Famine Early Warning Systems Network (FEWS NET) is a USAID-funded activity that collaborates with international, regional and national partners to provide timely and rigorous early warning and vulnerability information on emerging and evolving food security issues. Farming Systems (2001): Farming systems according to FAO methodology: Agro-pastoral land, millet-sorghum, highland perennial, maize mixed, irrigated land, pastoral land and sparse arid Land.Source: Harvest Choice / Dixon, J. and A. Gulliver with David Gibbon, Principal Editor: Malcolm Hall. Improving Farmers' Livelihoods in a Changing World. FAO/World Bank. 2001. (Aggregation type: NONE) Land cover (2009): Land cover defined as the physical material at the surface or earth, vegetation planted or man-made constructions (water, ice, bare rock, sand, grass, asphalt, trees, etc.). Land cover can be determined by analyzing satellite and aerial imagery.Source: 3R Initiative (RAIN, Acacia Water, MetaMeta, Aqua for all, BGR and IGRAC). “Global Land Cover.” www.hoefsloot.com/horn/ Sorghum Area (2015-16): Area in hectares of agriculture land used for sorghum.Source: Central Statistical Agency CAS. “Agricultural Sample Survey (AgSS) 2015/2016 (2008 E.C.) Report on Area and Production of Major Crops.” Sorghum Production (2015-16): Sorghum harvested expressed in tons.Source: Central Statistical Agency CAS. “Agricultural Sample Survey (AgSS) 2015/2016 (2008 E.C.). Report on Area and Production of Major Crops.” Maize Area (2015-16): Area in hectares of agriculture land used for Maize.Source: Central Statistical Agency CAS. “Agricultural Sample Survey (AgSS) 2015/2016 (2008 E.C.). Report on Area and Production of Major Crops.” Maize Production (2015-16): Maize harvested expressed in tons.

Source: Central Statistical Agency CAS. “Agricultural Sample Survey (AgSS) 2015/2016 (2008 E.C.). Report on Area and Production of Major Crops.”The maps displayed on this website are for reference only. The boundaries, colors, denominations and any other information shown on these maps do not imply, on the part of GAFSP (and the World Bank Group), any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.

Socio-demographic characteristic of young, sexually active women in Ethiopia, EDHS 2016 (N = 2661).

Individual and household level characteristics of pregnant women in Ethiopian 2016 DHS (Na = 3,292).

Ethiopia ET: Women Who were First Married by Age 18: % of Women Aged 20-24 data was reported at 40.300 % in 2016. This records a decrease from the previous number of 41.200 % for 2011. Ethiopia ET: Women Who were First Married by Age 18: % of Women Aged 20-24 data is updated yearly, averaging 45.150 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 49.200 % in 2005 and a record low of 40.300 % in 2016. Ethiopia ET: Women Who were First Married by Age 18: % of Women Aged 20-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Population and Urbanization Statistics. Women who were first married by age 18 refers to the percentage of women ages 20-24 who were first married by age 18.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), AIDS Indicator Surveys(AIS), Reproductive Health Survey(RHS), and other household surveys.; ;

Sociodemographic characteristics of men who were sexual-active, Ethiopia; 2016 DHS.

Individual-and community-level characteristics of participants, pooled data from Ethiopia DHS 2016 & 2019 (n = 4,423).

The prevalence of undernourished children under five by household wealth status, educational status of mothers, place of residence, and regions in Ethiopia (DHS 2005 to 2016).

Multilevel mixed-effects logistic regression modeling of individual- and community-level factors associated with no ASF consumption among children aged 6–23 months in Ethiopia, based on pooled data from Ethiopia DHS 2016 & 2019 (n = 4,423).