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 58 years for men and 60 for women in 2024. 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 4.02 children per woman, compared to a worldwide average of 2.25 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 2025, people living in Nigeria amounted to over 237 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 in 2023. Nigeria and Ethiopia also had high rates, with 4.48 and 3.99 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.

List of African countries by median age. Niger average age is 14.8, the youngest African country and the youngest country in the world. The African islands of Seychelles is the oldest African country with an average age of 36.8.

*********************, who became prime minister of ******* in December 2024, is the youngest state leader worldwide, aged **. Ibrahim Traore of Burkina Faso and Daniel Noboa of Ecuador are aged **, too. Conversely, the oldest state leader in the world is ********* of ********, aged **.

List of African countries by median age of the total population and male and female median ages. Niger with an average age of 14.8 years old is the youngest country in Africa and the youngest country in the world.

This statistic shows the countries with the lowest projected median age in 2050. By 2050, Niger is projected to have the population with the lowest median age at 19 years old.

Kosovo, one of the youngest countries in an aging Europe, took its first steps on the road to greater prosperity a quarter of a century ago. Kosovo’s economy has experienced significant growth in recent years. The Coronavirus disease 2019 (COVID-19) pandemic has triggered Kosovo’s first ever recession in 2020. While spending on education has more than doubled, the quality of human capital needs to improve. And barriers to women’s economic empowerment need to be lifted. Proximity to major markets in Europe and a youthful population provide an opportunity for growth. Kosovo is one of the youngest countries in an aging Europe. Trade facilitation and logistics connectivity are getting better. Proximity to a large and affluent market, low taxes and labor costs, a resilient and liquid financial sector, and strong ties with its diaspora will help support growth.

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

In 2024, Italy was the European country with the oldest population, recording a median age of 48.7 years, closely ahead of Bulgaria and Portugal, with 47 years. In general, almost all European countries have a median age above 40 years old. Only Azerbaijan, Turkey, Armenia, and Kosovo had a median age below 35 years old. Kosovo was the youngest territory of the continent in terms of median age.

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Data Source: This dataset was compiled from multiple data sources

If this was helpful, a vote is appreciated ❤️ Thank you 🙂

license: apache-2.0 tags: - africa - sustainable-development-goals - world-health-organization - development

  Children and young people achieving a minimum proficiency level in reading (%) - Primary education





  Dataset Description

This dataset provides country-level data for the indicator "4.1.1 Children and young people achieving a minimum proficiency level in reading (%) - Primary education" across African nations, sourced from the World Health Organization's… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/children-and-young-people-achieving-a-minimum-proficiency-le-for-african-countries.

The average for 2023 based on 177 countries was 15.77 percent. The highest value was in Djibouti: 76.27 percent and the lowest value was in Niger: 0.42 percent. The indicator is available from 1991 to 2024. Below is a chart for all countries where data are available.

Burkina Faso BF: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 77.124 % in 2023. This records a decrease from the previous number of 78.932 % for 2022. Burkina Faso BF: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 87.529 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 95.822 % in 1993 and a record low of 69.305 % in 1960. Burkina Faso BF: Age Dependency Ratio: % of Working-Age Population: Young data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burkina Faso – Table BF.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.;World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2024 Revision.;Weighted average;

The Netherlands was the country in the world with the highest labor force participation rate among young men in 2022, reaching over ** percent. Iceland, Uganda, and Honduras followed behind.

Introduction

This data contains percentage of part-time employment of adults by sex, age groups, number of children and age of youngest child.

Details

• Created: 15.02.2023
• Updated: 12.06.2025
• Landing Page: https://ec.europa.eu/eurostat/databrowser/product/page/lfst_hhptechi
• Publisher:
  • Name: Eurostat
  • Homepage: https://commission.europa.eu/about/departments-and-executive-agencies/euros...
• Contact Points:
  • Telephone: tel:+352430136789
  • Address: Joseph Bech building, 5 Rue Alphonse Weicker, L-2721 Luxembourg
• Url: http://ec.europa.eu/eurostat/help/support
• Catalogue Record:
• Added to data.europa.eu: 29 April 2022
• Updated on data.europa.eu: 28 August 2025

Spatial Resource:
Link: http://publications.europa.eu/resource/authority/country/MKD Link: http://publications.europa.eu/resource/authority/country/ROU Link: http://publications.europa.eu/resource/authority/country/SRB Link: http://publications.europa.eu/resource/authority/country/PRT Link: http://publications.europa.eu/resource/authority/country/AUT Link: http://publications.europa.eu/resource/authority/country/IRL Link: http://publications.europa.eu/resource/authority/country/POL Link: http://publications.europa.eu/resource/authority/country/ITA Link: http://publications.europa.eu/resource/authority/country/LTU Link: http://publications.europa.eu/resource/authority/country/SVN Link: http://publications.europa.eu/resource/authority/country/DNK Link: http://publications.europa.eu/resource/authority/country/CZE Link: http://publications.europa.eu/resource/authority/country/BIH Link: http://publications.europa.eu/resource/authority/country/MLT Link: http://publications.europa.eu/resource/authority/country/NOR Link: http://publications.europa.eu/resource/authority/country/EST Link: http://publications.europa.eu/resource/authority/country/HRV Link: http://publications.europa.eu/resource/authority/country/FIN Link: http://publications.europa.eu/resource/authority/country/LUX Link: http://publications.europa.eu/resource/authority/country/BGR Link: http://publications.europa.eu/resource/authority/country/DEU Link: http://publications.europa.eu/resource/authority/country/GBR Link: http://publications.europa.eu/resource/authority/country/HUN Link: http://publications.europa.eu/resource/authority/country/FRA Link: http://publications.europa.eu/resource/authority/country/NLD Link: http://publications.europa.eu/resource/authority/country/MNE Link: http://publications.europa.eu/resource/authority/country/ESP Link: http://publications.europa.eu/resource/authority/country/SWE Link: http://publications.europa.eu/resource/authority/country/GRC Link: http://publications.europa.eu/resource/authority/country/SVK Link: http://publications.europa.eu/resource/authority/country/BEL Link: http://publications.europa.eu/resource/authority/country/LVA Link: http://publications.europa.eu/resource/authority/country/TUR Link: http://publications.europa.eu/resource/authority/country/CYP Link: http://publications.europa.eu/resource/authority/country/EUR

Tunisia TN: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 35.314 % in 2017. This records an increase from the previous number of 34.999 % for 2016. Tunisia TN: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 66.027 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 92.534 % in 1966 and a record low of 33.566 % in 2011. Tunisia TN: Age Dependency Ratio: % of Working-Age Population: Young data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tunisia – Table TN.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

Uzbekistan UZ: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 41.430 % in 2017. This records an increase from the previous number of 41.332 % for 2016. Uzbekistan UZ: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 73.540 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 93.209 % in 1968 and a record low of 41.332 % in 2016. Uzbekistan UZ: Age Dependency Ratio: % of Working-Age Population: Young data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uzbekistan – Table UZ.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

This dataset provides values for RETIREMENT AGE WOMEN reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Abstract

Young Lives: An International Study of Childhood Poverty is a collaborative project investigating the changing nature of childhood poverty in selected developing countries. The UK’s Department for International Development (DFID) is funding the first three-year phase of the project.

Young Lives involves collaboration between Non Governmental Organisations (NGOs) and the academic sector. In the UK, the project is being run by Save the Children-UK together with an academic consortium that comprises the University of Reading, London School of Hygiene and Tropical Medicine, South Bank University, the Institute of Development Studies at Sussex University and the South African Medical Research Council.

The study is being conducted in Ethiopia, India (in Andhra Pradesh), Peru and Vietnam. These countries were selected because they reflect a range of cultural, geographical and social contexts and experience differing issues facing the developing world; high debt burden, emergence from conflict, and vulnerability to environmental conditions such as drought and flood.

Objectives of the study The Young Lives study has three broad objectives: • producing good quality panel data about the changing nature of the lives of children in poverty. • trace linkages between key policy changes and child poverty • informing and responding to the needs of policy makers, planners and other stakeholders There will also be a strong education and media element, both in the countries where the project takes place, and in the UK.

The study takes a broad approach to child poverty, exploring not only household economic indicators such as assets and wealth, but also child centred poverty measures such as the child’s physical and mental health, growth, development and education. These child centred measures are age specific so the information collected by the study will change as the children get older.

Further information about the survey, including publications, can be downloaded from the Young Lives website.

Geographic coverage

Young Lives is an international study of childhood poverty, involving 12,000 children in 4 countries. - Ethiopia (20 communities in Addis Ababa, Amhara, Oromia, and Southern National, Nationalities and People's Regions) - India (20 sites across Andhra Pradesh and Telangana) - Peru (74 communities across Peru) - Vietnam (20 communities in the communes of Lao Cai in the north-west, Hung Yen province in the Red River Delta, the city of Danang on the coast, Phu Yen province from the South Central Coast and Ben Tre province on the Mekong River Delta)

Analysis unit

Individuals; Families/households

Universe

Location of Units of Observation: Cross-national; Subnational Population: Children aged approximately 1 year old and their households, and children aged 8 years old and their households, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam, in 2002. See documentation for details of the exact regions covered in each country.

Kind of data

Sample survey data [ssd]

Sampling procedure

Purposive selection/case studies

A key need for the study's objectives was to obtain data at different levels - the children, their households, the community in which they resided, as well as at regional and national levels. This need thus determined that children should be selected in geographic clusters rather than randomly selected across the country. There was, however, a much more important reason for recruiting children in clusters - the sites are also intended to provide suitable settings for a range of complementary thematic studies. For example, one or a few sites may be used for a qualitative study designed to achieve a deeper level of understanding of some social issues, either because they are important in that particular place, or because the sites are appropriate locales to investigate a more general concern. The quantitative panel study is seen as the foundation upon which a coherent and interesting range of linked studies can be set up.

Thus the design was decided, in each country, comprising 20 geographic clusters with 100 children sampled in each cluster.

For details on sample design, see the methodological document which is available in the documentation.

Sampling deviation

Ethiopia: 1,999 (1-year-olds), 1,000 (8-year-olds); India: 2,011 (1-year-olds), 1,008 (8-year-olds); Peru: 2,052 (1-year-olds), 714 (8-year-olds); Vietnam: 2,000 (1-year-olds), 1,000 (8-year-olds).

Mode of data collection

Face-to-face interview

Research instrument

Every questionnaire used in the study consists of a 'core' element and a country-specific element, which focuses on issues important for that country.

The core element of the questionnaires consists of the following sections: Core 6-17.9 month old household questionnaire • Section 1: Locating information • Section 2: Household composition • Section 3: Pregnancy, delivery and breastfeeding • Section 4: Child care • Section 5: Child health • Section 6: Caregiver background • Section 7: Livelihoods and time allocation • Section 8: Economic changes • Section 9: Socio-economic status • Section 10: Caregiver psychosocial well-being • Section 11: Social capital • Section 12: Tracking details • Section 13: Anthropometry

Core 7.5-8.5 year old household questionnaire • Section 1: Locating information • Section 2: Household composition • Section 3: Births and deaths • Section 4: Child school • Section 5: Child health • Section 6: Caregiver background • Section 7: Livelihoods and time allocation • Section 8: Economic changes • Section 9: Socio-economic status • Section 10: Child mental health • Section 11: Social capital • Section 12: Tracking details • Section 13: Anthropometry

The communnity questionnaire consists of the following sections: • Section 1: Physical environment • Section 2: Social environment • Section 3: Infrastructure and access • Section 4: Economy • Section 5: Health and education

Young immigrants by sex, age and country of birth