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.

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.

The estimated median age gives an idea of the age distribution of the population in a given area. A greater median age would suggest that the area of interest has a relatively large number of older residents, while a lower median age suggests that the area has a relatively large number of younger residents.

Champaign County’s estimated median age has risen for over a decade, but has always stayed between 28 and 31. Year-to-year changes from 2017 to 2019 were statistically significant, but not from 2019 to 2023. The Champaign County estimated median age has been consistently younger than the estimated median ages of the United States and State of Illinois. Champaign County’s figure is likely impacted to some degree by the large student population associated with the University of Illinois.

The estimated median age does not provide a significant amount of detail, and it does not provide any information on why the estimated median age is what it is. However, when placed in the context of other pieces of data and other indicators, it is a valuable starting point in understanding county demographics.

Estimated median age data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Median Age by Sex.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using data.census.gov; (8 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using data.census.gov; (6 October 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using data.census.gov; (13 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using data.census.gov; (7 April 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using data.census.gov; (7 April 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S0101; generated by CCRPC staff; using American FactFinder; (16 March 2016).

Graph and download economic data for Civilian Labor Force in Young County, TX (LAUCN485030000000006A) from 1990 to 2024 about Young County, TX; civilian; labor force; labor; household survey; TX; and USA.

Estimate, Median Age by Sex, Total Population (5-year estimate) in Young County, TX was 40.70000 Years of Age in January of 2023, according to the United States Federal Reserve. Historically, Estimate, Median Age by Sex, Total Population (5-year estimate) in Young County, TX reached a record high of 42.60000 in January of 2013 and a record low of 40.30000 in January of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for Estimate, Median Age by Sex, Total Population (5-year estimate) in Young County, TX - last updated from the United States Federal Reserve on June of 2025.

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.

About this dataset

Context

This list ranks the 3 cities in the Young County, TX by Multi-Racial Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Multi-Racial Black Population: This column displays the rank of cities in the Young County, TX by their Multi-Racial Black or African American population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Black Population: The Multi-Racial Black population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Young County Multi-Racial Black Population: This tells us how much of the entire Young County, TX Multi-Racial Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

The ranking of countries by average age of the population shows at one end of the spectrum the countries with the highest average age of the population. At the other end are the countries with the youngest populations: they usually have high birth rates and not very long life expectancy.

In 2024, the median age in Africa was **** years, meaning that half of the population was older and half was younger than that age. The median age on the continent increased compared to 2000 when it was around ** years. Africa is the youngest continent in the world and presents the highest share of inhabitants aged 14 years and younger, that is, ** percent of the total population. Niger, Uganda, and Angola were the countries with the youngest population in Africa as of 2023.

About this dataset

Context

The dataset tabulates the Young County population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Young County. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 9,919 (55.22% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Young County population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Young County is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Young County is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Young County Population by Age. You can refer the same here

Monaco is the country with the highest median age in the world. The population has a median age of around 57 years, which is around six years more than in Japan and Saint Pierre and Miquelon – the other countries that make up the top three. Southern European countries make up a large part of the top 20, with Italy, Slovenia, Greece, San Marino, Andorra, and Croatia all making the list. Low infant mortality means higher life expectancy Monaco and Japan also have the lowest infant mortality rates in the world, which contributes to the calculation of a higher life expectancy because fewer people are dying in the first years of life. Indeed, many of the nations with a high median age also feature on the list of countries with the highest average life expectancy, such as San Marino, Japan, Italy, and Lichtenstein. Demographics of islands and small countries Many smaller countries and island nations have populations with a high median age, such as Guernsey and the Isle of Man, which are both island territories within the British Isles. An explanation for this could be that younger people leave to seek work or education opportunities, while others choose to relocate there for retirement.

About this dataset

Context

This list ranks the 3 cities in the Young County, TX by Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Hispanic Other Race Population: This column displays the rank of cities in the Young County, TX by their Hispanic Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Hispanic Other Race Population: The Hispanic Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Young County Hispanic Other Race Population: This tells us how much of the entire Young County, TX Hispanic Other Race population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Families by age of youngest child by Local Authorities. (Census 2022 Theme 4 Table 4 )Census 2022 table 4.4 is families by age of youngest child. Details include family units by age of youngest child, number of families and number of persons. Census 2022 theme 4 is Families. The country is divided into 31 administrative counties/cities. Outside Dublin, there are 23 administrative counties and four cities: Cork, Limerick, Waterford and Galway. There are four local authority areas in Dublin: Dublin City and the three administrative counties of Dún Laoghaire-Rathdown, Fingal and South Dublin. The Local Government Reform Act 2014 Section 9 provided for the amalgamation of the city and county councils in Limerick, Waterford, and North Tipperary and South Tipperary County Councils.Coordinate reference system: Irish Transverse Mercator (EPSG 2157). These boundaries are based on 20m generalised boundaries sourced from Tailte Éireann Open Data Portal. This dataset is provided by Tailte Éireann, Administrative Counties 2019

Graph and download economic data for Population Estimate, Total, Hispanic or Latino, American Indian and Alaska Native Alone (5-year estimate) in Young County, TX (B03002015E048503) from 2009 to 2023 about Young County, TX; AK; American Indian; latino; hispanic; TX; estimate; persons; 5-year; population; and USA.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Relationship File (ADDR.dbf) contains the attributes of each address range. Each address range applies to a single edge and has a unique address range identifier (ARID) value. The edge to which an address range applies can be determined by linking the address range to the All Lines Shapefile (EDGES.shp) using the permanent topological edge identifier (TLID) attribute. Multiple address ranges can apply to the same edge since an edge can have multiple address ranges. Note that the most inclusive address range associated with each side of a street edge already appears in the All Lines Shapefile (EDGES.shp). The TIGER/Line Files contain potential address ranges, not individual addresses. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

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.

Families by age of youngest child by Province. (Census 2022 Theme 4 Table 4 )Census 2022 table 4.4 is families by age of youngest child. Details include family units by age of youngest child, number of families and number of persons. Census 2022 theme 4 is Families. Ireland is divided into four provinces - Leinster, Ulster, Munster and Connacht. They do not have any administrative functions and they are relevant for a number of historical, cultural and sporting reasons. The borders of the provinces coincide with the boundaries of counties. Three of the nine counties in Ulster are within the jurisdiction of the State.Coordinate reference system: Irish Transverse Mercator (EPSG 2157). These boundaries are based on 20m generalised boundaries sourced from Tailte Éireann Open Data Portal. Provinces - National Statutory Boundaries - 2019This dataset is provided by Tailte Éireann

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Feature Names Relationship File (FEATNAMES.dbf) contains a record for each feature name and any attributes associated with it. Each feature name can be linked to the corresponding edges that make up that feature in the All Lines Shapefile (EDGES.shp), where applicable to the corresponding address range or ranges in the Address Ranges Relationship File (ADDR.dbf), or to both files. Although this file includes feature names for all linear features, not just road features, the primary purpose of this relationship file is to identify all street names associated with each address range. An edge can have several feature names; an address range located on an edge can be associated with one or any combination of the available feature names (an address range can be linked to multiple feature names). The address range is identified by the address range identifier (ARID) attribute, which can be used to link to the Address Ranges Relationship File (ADDR.dbf). The linear feature is identified by the linear feature identifier (LINEARID) attribute, which can be used to relate the address range back to the name attributes of the feature in the Feature Names Relationship File or to the feature record in the Primary Roads, Primary and Secondary Roads, or All Roads Shapefiles. The edge to which a feature name applies can be determined by linking the feature name record to the All Lines Shapefile (EDGES.shp) using the permanent edge identifier (TLID) attribute. The address range identifier(s) (ARID) for a specific linear feature can be found by using the linear feature identifier (LINEARID) from the Feature Names Relationship File (FEATNAMES.dbf) through the Address Range / Feature Name Relationship File (ADDRFN.dbf).

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.