This statistic shows the age structure in Ethiopia from 2013 to 2023. In 2023, about 39.37 percent of Ethiopia's total population were aged 0 to 14 years.

This statistic shows the total population of Ethiopia from 2013 to 2023 by gender. In 2023, Ethiopia's female population amounted to approximately 64.21 million, while the male population amounted to approximately 64.49 million inhabitants.

Age dependency ratio (% of working-age population) in Ethiopia was reported at 73.28 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Age dependency ratio (% of working-age population) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

As of 2020, the median age stood at **** years in Ethiopia, which is an increase of nearly a year compared to the previous four years. Despite the increment, the median age remained low, indicating a high fertility rate among Ethiopian population. Looking at the population from a different perspective, the human development index scored countries based on health and living standards, in which Ethiopia registered a steady but low level of development in 2019. The country experienced a slight increase in the HDI score since the previous year, which was ****. Other measures such as the gender gap index and the economic freedom give further insights into Ethiopia’s population.

Gender gap index score

The overall gender gap index score of Ethiopia amounted to ****, ranking **** out of 156 listed countries globally in 2021. It indicates the discrepancy between genders in four different areas: economic participation and opportunity, educational attainment, health and survival, and political empowerment. Categorizing the index score by industry, Ethiopia scored low (****) in political empowerment in 2021, indicating a low share of women in politics. Health and survival, on the other hand, had a more equal score of ****.

Economic freedom in Ethiopia

 Concerning the economic freedom of Ethiopia, which is an index based on ** categories ranging from property rights to financial possibilities, the country scored **** in 2021. This was slightly lower compared to Africa’s average (****). However, Ethiopia registered a steady increase from 2013 onwards, indicating slight improvements in the economic freedom of the people living there.

SP.POP.GROW. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. This database presents population and other demographic estimates and projections from 1960 to 2050, covering more than 200 economies. It includes population data by various age groups, sex, urban/rural; fertility data; mortality data; and migration data.

Population ages 65 and above (% of total population) in Ethiopia was reported at 3.23 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 65 and above (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Ethiopia administrative level 0-3 sex and age disaggregated projected 2022 population statistics.

REFERENCE YEAR: 2022

These tables are suitable for database or GIS linkage to the Ethiopia - Subnational Administrative Boundaries.

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

SH.DYN.1019. Probability of dying between age 10-19 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year. This database presents population and other demographic estimates and projections from 1960 to 2050, covering more than 200 economies. It includes population data by various age groups, sex, urban/rural; fertility data; mortality data; and migration data.

Ethiopia ET: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data was reported at 86.019 % in 2015. This records a decrease from the previous number of 86.317 % for 2014. Ethiopia ET: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children data is updated yearly, averaging 47.353 % from Dec 1987 (Median) to 2015, with 23 observations. The data reached an all-time high of 86.317 % in 2014 and a record low of 19.105 % in 1994. Ethiopia ET: Adjusted Net Enrollment Rate: Primary: % of Primary School Age Children 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: Education Statistics. Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Analysis unit

Persons, households, and dwellings Short-questionnaire recipients lack many variables

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: A housing unit is a separate and independent part of the whole of a building or a group of buildings used or intended to be used for habitation by a household, or if not so, used or intended to be used for a combination of habitation and commercial activity, or commercial activity only. - Households: A group of persons who live in the same housing unit or in connected premises and have common arrangements for cooking and eating their food. A household could consist of a single person, but usually, it consists of a husband, his wife, his children, relatives and non-relatives. The non-relatives could be friends, servants, employees, etc. As long as household members have the same arrangement for food it includes servants and guards, too. - Group quarters: Premises (housing units, buildings, or compounds) in which a number of unrelated or related persons reside together, and share common facilities. It includes, hotels, hostels, boarding schools, home for the aged , children’s home, prisons, military barracks, monasteries, work camps, rehabilitation centers, children’s home, etc. It is important to note that in the premises of some collective quarters there may be private households.

Universe

All housing units and households; all individuals who passed the night of the census date in the dwelling

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Central Statistical Agency

SAMPLE SIZE (person records): 7434086.

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the country.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two census questionnaires, a short form and a long form, collected information in five sections: 1) Area identification, 2) Type of residence and housing identification, 3) Details of persons in the household, 4) Deaths in the household during the last 12 month, and 5) Information on housing unit. The long questionnaire was administerd to 1 in 5 households in each enumeration area. The short questionnaire with a subset of the long questionnaire items corresponding to basic demographic and social characteristics (population size, sex, age, religion, mother tongue, ethnic group, disability and orphanage) was administered to the remaining (non-sample) households.

Geographic coverage

National coverage

Analysis unit

Household Person Housing unit

Universe

The census has counted people on dejure and defacto basis. The dejure population comprises all the persons who belong to a given area at a given time by virtue of usual residence, while under defacto approach people were counted as the residents of the place where they found. In the census, a person is said to be a usual resident of a household (and hence an area) if he/she has been residing in the household continuously for at least six months before the census day or intends to reside in the household for six months or longer. Thus, visitors are not included with the usual (dejure) population. Homeless persons were enumerated in the place where they spent the night on the enumeration day. The 2007 census counted foreign nationals who were residing in the city administration. On the other hand all Ethiopians living abroad were not counted.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

Two type sof questionnaires were used to collect census data: i) Short questionnaire ii) Long questionnaire

Unlike the previous censuses, the contents of the short and long questionnaires were similar both for the urban and rural areas as well as for the entire city. But the short and the long questionnaires differ by the number of variables they contained. That is, the short questionnaire was used to collect basic data on population characteristics, such as population size, sex, age, language, ethnic group, religion, orphanhood and disability. Whereas the long questionnaire includes information on marital status, education, economic activity, migration, fertility, mortality, as well as housing stocks and conditions in addition to those questions contained in a short questionnaire.

The geodatabase contains boundaries for the national and first-, second-, and third-order administrative divisions, aligned to the Large Scale International Boundaries dataset from the U.S. Department of State. The feature classes are suitable for linking to the attribute data provided.

The tabular data contain total population for 2007 (census), as well as five-year age group and sex, and information relating to religion, the economy, disability, households, housing, ethnicity, language, health, and agriculture.

Population ages 0-14 (% of total population) in Ethiopia was reported at 39.06 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 0-14 (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Abstract

The principal objective of the Ethiopia Demographic and Health Survey (DHS) is to provide current and reliable data on fertility and family planning behavior, child mortality, children’s nutritional status, the utilization of maternal and child health services, and knowledge of HIV/AIDS. This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Authority to plan, conduct, process, and analyze data from complex national population and health surveys. Moreover, the 2000 Ethiopia DHS is the first survey of its kind in the country to provide national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. As part of the worldwide DHS project, the Ethiopia DHS data add to the vast and growing international database on demographic and health variables. The Ethiopia DHS collected demographic and health information from a nationally representative sample of women and men in the reproductive age groups 15-49 and 15-59, respectively.

The Ethiopia DHS was carried out under the aegis of the Ministry of Health and was implemented by the Central Statistical Authority. ORC Macro provided technical assistance through its MEASURE DHS+ project. The survey was principally funded by the Essential Services for Health in Ethiopia (ESHE) project through a bilateral agreement between the United States Agency for International Development (USAID) and the Federal Democratic Republic of Ethiopia. Funding was also provided by the United Nations Population Fund (UNFPA).

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The Ethiopia DHS used the sampling frame provided by the list of census enumeration areas (EAs) with population and household information from the 1994 Population and Housing Census. A proportional sample allocation was discarded because this procedure yielded a distribution in which 80 percent of the sample came from three regions, 16 percent from four regions and 4 percent from five regions. To avoid such an uneven sample allocation among regions, it was decided that the sample should be allocated by region in proportion to the square root of the region's population size. Additional adjustments were made to ensure that the sample size for each region included at least 700 households, in order to yield estimates with reasonable statistical precision.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

The Ethiopia DHS used three questionnaires: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire, which were based on model survey instruments developed for the international MEASURE DHS+ project. The questionnaires were specifically geared toward obtaining the kind of information needed by health and family planning program managers and policymakers. The model questionnaires were then adapted to local conditions and a number of additional questions specific to on-going health and family planning programs in Ethiopia were added. These questionnaires were developed in the English language and translated into the five principal languages in use in the country: Amarigna, Oromigna, Tigrigna, Somaligna, and Afarigna. They were then independently translated back to English and appropriate changes were made in the translation of questions in which the back-translated version did not compare well with the original English version. A pretest of all three questionnaires was conducted in the five local languages in November 1999.

All usual members in a selected household and visitors who stayed there the previous night were enumerated using the Household Questionnaire. Specifically, the Household Questionnaire obtained information on the relationship to the head of the household, residence, sex, age, marital status, parental survivorship, and education of each usual resident or visitor. This information was used to identify women and men who were eligible for the individual interview. Women age 15-49 in all selected households and all men age 15-59 in every fifth selected household, whether usual residents or visitors, were deemed eligible, and were interviewed. The Household Questionnaire also obtained information on some basic socioeconomic indicators such as the number of rooms, the flooring material, the source of water, the type of toilet facilities, and the ownership of a variety of durable items. Information was also obtained on the use of impregnated bednets, and the salt used in each household was tested for its iodine content. All eligible women and all children born since Meskerem 1987 in the Ethiopian Calendar, which roughly corresponds to September 1994 in the Gregorian Calendar, were weighed and measured.

The Women’s Questionnaire collected information on female respondent’s background characteristics, reproductive history, contraceptive knowledge and use, antenatal, delivery and postnatal care, infant feeding practices, child immunization and health, marriage, fertility preferences, and attitudes about family planning, husband’s background characteristics and women’s work, knowledge of HIV/AIDS and other sexually transmitted infections (STIs).

The Men’s Questionnaire collected information on the male respondent’s background characteristics, reproduction, contraceptive knowledge and use, marriage, fertility preferences and attitudes about family planning, and knowledge of HIV/AIDS and STIs.

Response rate

A total of 14,642 households were selected for the Ethiopia DHS, of which 14,167 were found to be occupied. Household interviews were completed for 99 percent of the occupied households. A total of 15,716 eligible women from these households and 2,771 eligible men from every fifth household were identified for the individual interviews. The response rate for eligible women is slightly higher than for eligible men (98 percent compared with 94 percent, respectively). Interviews were successfully completed for 15,367 women and 2,607 men.

There is no difference by urban-rural residence in the overall response rate for eligible women; however, rural men are slightly more likely than urban men to have completed an interview (94 percent and 92 percent, respectively). The overall response rate among women by region is relatively high and ranges from 93 percent in the Affar Region to 99 percent in the Oromiya Region. The response rate among men ranges from 83 percent in the Affar Region to 98 percent in the Tigray and Benishangul-Gumuz regions.

Note: See summarized response rates by place of residence in Table A.1.1 and Table A.1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) 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 Ethiopia DHS to minimise 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 Ethiopia DHS 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A 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 percent 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 Ethiopia DHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the Ethiopia DHS is the ISSA Sampling Error Module (SAMPERR). This module used the Taylor linearisation method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age

VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Nigeria: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Methodology

These high-resolution maps are created using machine learning techniques to identify buildings from commercially available satellite images. This is then overlayed with general population estimates based on publicly available census data and other population statistics at Columbia University. The resulting maps are the most detailed and actionable tools available for aid and research organizations. For more information about the methodology used to create our high resolution population density maps and the demographic distributions, click [here](https://dataforgood.fb.com/docs/methodology-high-resolution-population-density-maps-demographic-estimates/

For information about how to use HDX to access these datasets, please visit: https://dataforgood.fb.com/docs/high-resolution-population-density-maps-demographic-estimates-documentation/

Adjustments to match the census population with the UN estimates are applied at the national level. The UN estimate for a given country (or state/territory) is divided by the total census estimate of population for the given country. The resulting adjustment factor is multiplied by each administrative unit census value for the target year. This preserves the relative population totals across administrative units while matching the UN total. More information can be found here

Ethiopia ET: Primary Completion Rate: Total: % of Relevant Age Group data was reported at 54.282 % in 2015. This records an increase from the previous number of 53.544 % for 2014. Ethiopia ET: Primary Completion Rate: Total: % of Relevant Age Group data is updated yearly, averaging 33.008 % from Dec 1982 (Median) to 2015, with 24 observations. The data reached an all-time high of 57.743 % in 2010 and a record low of 13.909 % in 1995. Ethiopia ET: Primary Completion Rate: Total: % of Relevant Age Group 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: Education Statistics. Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map population age and sex counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076).

Gridded, spatial datasets for Africa providing version 1.0 estimates for dependency ratios at sub-national level. Ratios are based on sub-national estimates for 5-year age group proportions. The series is comprised of raster dataset: 1) The ratio of dependents (both young, 0 to 14, and old, 65 ) upon the working age population; 2) The ratio of young dependents upon the working age population; 3) The ratio of older dependents upon the working age population. DATA RESOLUTION: Sub-national administrative areas SPATIAL RESOLUTION: 0.05 decimal degrees (approx 5kkm at the equator) PROJECTION: Geographic, WGS84 UNITS: Sub-national dependency ratios FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) DATASET CONSTRUCTION DETAILS: This dataset is derived from the WorldPop Whole Continent Age Structures data series, described here: http://www.worldpop.org.uk/data/data_sources/.

Socio-demographic characteristics of selected mothers in Ethiopia.