Ethiopia ET: Death Rate: Crude: per 1000 People data was reported at 6.825 Ratio in 2016. This records a decrease from the previous number of 6.997 Ratio for 2015. Ethiopia ET: Death Rate: Crude: per 1000 People data is updated yearly, averaging 18.966 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 25.000 Ratio in 1960 and a record low of 6.825 Ratio in 2016. Ethiopia ET: Death Rate: Crude: per 1000 People 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: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Ethiopia ET: Mortality Rate: Infant: per 1000 Live Births data was reported at 41.000 Ratio in 2016. This records a decrease from the previous number of 42.600 Ratio for 2015. Ethiopia ET: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 118.300 Ratio from Dec 1966 (Median) to 2016, with 51 observations. The data reached an all-time high of 144.300 Ratio in 1966 and a record low of 41.000 Ratio in 2016. Ethiopia ET: Mortality Rate: Infant: per 1000 Live Births 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. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given 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; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

Ethiopia ET: Mortality Rate: Under-5: Male: per 1000 Live Births data was reported at 63.700 Ratio in 2016. This records a decrease from the previous number of 66.700 Ratio for 2015. Ethiopia ET: Mortality Rate: Under-5: Male: per 1000 Live Births data is updated yearly, averaging 87.200 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 215.300 Ratio in 1990 and a record low of 63.700 Ratio in 2016. Ethiopia ET: Mortality Rate: Under-5: Male: per 1000 Live Births 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. Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

Ethiopia ET: Suicide Mortality Rate: Male data was reported at 11.200 NA in 2016. This stayed constant from the previous number of 11.200 NA for 2015. Ethiopia ET: Suicide Mortality Rate: Male data is updated yearly, averaging 11.300 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 12.200 NA in 2000 and a record low of 11.200 NA in 2016. Ethiopia ET: Suicide Mortality Rate: Male 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. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

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

Perinatal mortality rate by socio demographic characteristics of mothers who were pregnant and give birth during 5 years preceding the 2016 EDHS survey.

Ethiopia ET: Mortality Rate: Adult: Male: per 1000 Male Adults data was reported at 245.285 Ratio in 2016. This records a decrease from the previous number of 250.154 Ratio for 2015. Ethiopia ET: Mortality Rate: Adult: Male: per 1000 Male Adults data is updated yearly, averaging 415.954 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 499.054 Ratio in 1960 and a record low of 245.285 Ratio in 2016. Ethiopia ET: Mortality Rate: Adult: Male: per 1000 Male Adults 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. Adult mortality rate, male, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old male dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) University of California, Berkeley, and Max Planck Institute for Demographic Research. The Human Mortality Database.; Weighted average;

Variability at community-level and model comparison for perinatal mortality among women’s in the 5 years preceding the survey in Ethiopia, EDHS, 2016.

Multilevel mixed effect logistic regression for perinatal mortality and associated factor in EDHS 2016.

Ethiopia ET: Mortality Rate: Adult: Female: per 1000 Female Adults data was reported at 193.616 Ratio in 2016. This records a decrease from the previous number of 198.692 Ratio for 2015. Ethiopia ET: Mortality Rate: Adult: Female: per 1000 Female Adults data is updated yearly, averaging 365.610 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 438.492 Ratio in 1960 and a record low of 193.616 Ratio in 2016. Ethiopia ET: Mortality Rate: Adult: Female: per 1000 Female Adults 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. Adult mortality rate, female, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old female dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) University of California, Berkeley, and Max Planck Institute for Demographic Research. The Human Mortality Database.; Weighted average;

Operational definition and category of independent variables used in the study.

The perinatal mortality among pregnant women by reproductive health characteristics of study participants in emerging regions, Ethiopia, 2016.

Ethiopia ET: Mortality Rate Attributed to Unintentional Poisoning: Male: per 100,000 Male Population data was reported at 3.600 Ratio in 2016. This records a decrease from the previous number of 3.700 Ratio for 2015. Ethiopia ET: Mortality Rate Attributed to Unintentional Poisoning: Male: per 100,000 Male Population data is updated yearly, averaging 4.300 Ratio from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 6.900 Ratio in 2000 and a record low of 3.600 Ratio in 2016. Ethiopia ET: Mortality Rate Attributed to Unintentional Poisoning: Male: per 100,000 Male Population 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. Mortality rate attributed to unintentional poisonings is the number of male deaths from unintentional poisonings in a year per 100,000 male population. Unintentional poisoning can be caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

The bi-variable and multivariable binary logistic regression analysis of predictor factors associated with neonatal mortality among neonates in the Tigray regional state, 2016 (n = 716).

Ethiopia ET: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 43.700 Ratio in 2016. Ethiopia ET: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 43.700 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Ethiopia ET: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population 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. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

The multivariable multilevel logistic regression analysis of factors associated with perinatal mortality in emerging regions, Ethiopia, 2016.

エチオピアの安全でない水・衛生設備・衛生状態の悪さに起因する死亡率の統計データです。最新の2016年の数値「43.7(人口10万人当たり)」を含む2016～2016年までの推移表や他国との比較情報を無料で公開しています。csv形式でのダウンロードも可能でEXCELでも開けますので、研究や分析レポートにお役立て下さい。

Ethiopia ET: Suicide Mortality Rate: Female data was reported at 3.100 NA in 2016. This records a decrease from the previous number of 3.200 NA for 2015. Ethiopia ET: Suicide Mortality Rate: Female data is updated yearly, averaging 3.300 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 3.900 NA in 2000 and a record low of 3.100 NA in 2016. Ethiopia ET: Suicide Mortality Rate: Female 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. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

National and regional under-five mortality rate per 1000 live births in Ethiopia (2000, 2005, 2011, 2016, and 2019).

Ethiopia ET: Suicide Mortality Rate: per 100,000 Population data was reported at 7.200 Number in 2016. This stayed constant from the previous number of 7.200 Number for 2015. Ethiopia ET: Suicide Mortality Rate: per 100,000 Population data is updated yearly, averaging 7.300 Number from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 8.000 Number in 2000 and a record low of 7.200 Number in 2016. Ethiopia ET: Suicide Mortality Rate: per 100,000 Population 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. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;