Ethiopia ET: Probability of Dying at Age 15-19 Years: per 1000 data was reported at 8.000 Ratio in 2019. This records a decrease from the previous number of 8.300 Ratio for 2018. Ethiopia ET: Probability of Dying at Age 15-19 Years: per 1000 data is updated yearly, averaging 16.700 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 38.600 Ratio in 1990 and a record low of 8.000 Ratio in 2019. Ethiopia ET: Probability of Dying at Age 15-19 Years: per 1000 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.WDI: Health Statistics. Probability of dying between age 15-19 years of age expressed per 1,000 adolescents age 15, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Historical chart and dataset showing Ethiopia maternal mortality rate by year from 1985 to 2023.

Ethiopia ET: Number of Deaths Ages 20-24 Years data was reported at 19,663.000 Person in 2019. This records an increase from the previous number of 19,390.000 Person for 2018. Ethiopia ET: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 25,173.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 44,858.000 Person in 1990 and a record low of 18,879.000 Person in 2016. Ethiopia ET: Number of Deaths Ages 20-24 Years 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.WDI: Health Statistics. Number of deaths of youths ages 20-24 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Log rank estimate of variables among TB/HIV co-infected children at public hospitals in Southern Ethiopia, 2020.

Ethiopia ET: Number of Deaths Ages 10-14 Years data was reported at 13,204.000 Person in 2019. This records a decrease from the previous number of 13,579.000 Person for 2018. Ethiopia ET: Number of Deaths Ages 10-14 Years data is updated yearly, averaging 21,142.000 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 28,549.000 Person in 1990 and a record low of 13,204.000 Person in 2019. Ethiopia ET: Number of Deaths Ages 10-14 Years 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.WDI: Health Statistics. Number of deaths of adolescents ages 10-14 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Ethiopia ET: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 4.800 Ratio in 2019. This records a decrease from the previous number of 5.000 Ratio for 2018. Ethiopia ET: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 10.850 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 23.900 Ratio in 1990 and a record low of 4.800 Ratio in 2019. Ethiopia ET: Probability of Dying at Age 10-14 Years: per 1000 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.WDI: Health Statistics. Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Predictors of mortality among TB/HIV Co-infected children at public hospitals in Southern Ethiopia, 2020.

Ethiopia ET: Probability of Dying at Age 5-9 Years: per 1000 data was reported at 5.900 Ratio in 2019. This records a decrease from the previous number of 6.200 Ratio for 2018. Ethiopia ET: Probability of Dying at Age 5-9 Years: per 1000 data is updated yearly, averaging 20.900 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 56.800 Ratio in 1990 and a record low of 5.900 Ratio in 2019. Ethiopia ET: Probability of Dying at Age 5-9 Years: per 1000 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.WDI: Health Statistics. Probability of dying between age 5-9 years of age expressed per 1,000 children aged 5, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

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). 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.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-59
• Health facility

Universe

The survey covered all de jure household members (usual residents), women age 15-49 years and men age 15-59 years resident in the household.

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.

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

Mode of data collection

Face-to-face [f2f]

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.

Cleaning operations

All electronic data files for the 2016 EDHS were transferred via IFSS to the CSA 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 openended questions; it also required generating a file for the list of children for whom a vaccination card was not seen by the interviewers and whose vaccination records had to be checked at health facilities. The data were processed by two individuals who took part in the main fieldwork training; they were supervised by two senior staff from CSA. Data editing was accomplished using CSPro software. During the duration of fieldwork, tables were generated to check various data quality parameters and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in January 2016 and completed in August 2016.

Response rate

A total of 18,008 households were selected for the sample, of which 17,067 were occupied. Of the occupied households, 16,650 were successfully interviewed, yielding a response rate of 98%.

In the interviewed households, 16,583 eligible women were identified for individual interviews. Interviews were completed with 15,683 women, yielding a response rate of 95%. A total of 14,795 eligible men were identified in the sampled households and 12,688 were successfully interviewed, yielding a response rate of 86%. Although overall there was little variation in response rates according to residence, response rates among men were higher in rural than in urban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling 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 the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2016 Ethiopia DHS (EDHS) to minimise this type of error, non-sampling errors are impossible to avoid and are difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2016 EDHS is only one of many samples that could have been selected from the same population, by using the same design and the expected size. Each of those samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between 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 (such as mean or percentage), 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 2016 EDHS sample is the result of a multi-stage stratified design and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, with programs developed by ICF International. These programs use the Taylor linearisation method of variance estimation 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.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar

Africa has the youngest population in the world. Among the 35 countries with the lowest median age worldwide, only three fall outside the continent. In 2023, the median age in Niger was 15.1 years, the youngest country. This means that at this age point, half of the population was younger and half older. A young population reflects several demographic characteristics of a country. For instance, together with a high population growth, life expectancy in Western Africa is low: this reached 57 years for men and 59 for women. Overall, Africa has the lowest life expectancy in the world.

Africa’s population is still growing Africa’s population growth can be linked to a high fertility rate along with a drop in death rates. Despite the fertility rate on the continent, following a constant declining trend, it remains far higher compared to all other regions worldwide. It was forecast to reach 4.12 children per woman, compared to a worldwide average of 2.31 children per woman in 2024. Furthermore, the crude death rate in Africa overall dropped, only increasing slightly during the coronavirus (COVID-19) pandemic. The largest populations on the continent Nigeria, Ethiopia, Egypt, and the Democratic Republic of Congo are the most populous African countries. In 2023, people living in Nigeria amounted to around 224 million, while the number for the three other countries exceeded 100 million each. Of those, the Democratic Republic of Congo sustained the fourth-highest fertility rate in Africa. Nigeria and Ethiopia also had high rates, with 5.24 and 4.16 births per woman, respectively. Although such a high fertility rate is expected to slow down, it will still impact the population structure, growing younger nations.

Ethiopia ET: Number of Deaths Ages 5-9 Years data was reported at 17,613.000 Person in 2019. This records a decrease from the previous number of 18,226.000 Person for 2018. Ethiopia ET: Number of Deaths Ages 5-9 Years data is updated yearly, averaging 49,889.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 84,307.000 Person in 1990 and a record low of 17,613.000 Person in 2019. Ethiopia ET: Number of Deaths Ages 5-9 Years 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.WDI: Health Statistics. Number of deaths of children ages 5-9 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Life table showing the cumulative survival probability among TB/HIV co-infected children at public hospitals in Southern Ethiopia, 2020.

Prevalence and intrapartum conditions of the participants, northeast Ethiopia, 2018.

Sociodemographic characteristics of the study participants, northeast Ethiopia, 2018.

Maternal and antepartum related conditions of participants, northeast Ethiopia, 2018.

Expected and additional child, neonatal, and maternal deaths, March 2020 to June 2021.

Mortality rate stratified by baseline and follow up clinical and immunological characteristics of adults on ART at Debre-Markos Referral Hospital from January 1, 2014 to December 31, 2018 (n = 494).

Multivariable Cox regression analysis model for survival of female breast cancer patients in southern Ethiopia, 2013–2018 (n = 302).

Correlates of monthly disruption magnitude in service volume.

Log-rank test for equality of survival function of female breast cancer patients in southern Ethiopia, 2013–2018 (n = 302).