In 2023, almost nine million people lived in Greater London, making it the most populated ceremonial county in England. The West Midlands Metropolitan County, which contains the large city of Birmingham, was the second-largest county at 2.98 million inhabitants, followed by Greater Manchester and then West Yorkshire with populations of 2.95 million and 2.4 million, respectively. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with around 1.89 million people. A patchwork of regions England is just one of the four countries that compose the United Kingdom of Great Britain and Northern Ireland, with England, Scotland and Wales making up Great Britain. England is therefore not to be confused with Great Britain or the United Kingdom as a whole. Within England, the next subdivisions are the nine regions of England, containing various smaller units such as unitary authorities, metropolitan counties and non-metropolitan districts. The counties in this statistic, however, are based on the ceremonial counties of England as defined by the Lieutenancies Act of 1997. Regions of Scotland, Wales, and Northern Ireland Like England, the other countries of the United Kingdom have their own regional subdivisions, although with some different terminology. Scotland’s subdivisions are council areas, while Wales has unitary authorities, and Northern Ireland has local government districts. As of 2022, the most-populated Scottish council area was Glasgow City, with over 622,000 inhabitants. In Wales, Cardiff had the largest population among its unitary authorities, and in Northern Ireland, Belfast was the local government area with the most people living there.

About this dataset

Context

The dataset tabulates the San Diego County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of San Diego County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of San Diego County was 3.27 million, a 0.22% decrease year-by-year from 2022. Previously, in 2022, San Diego County population was 3.28 million, an increase of 0.08% compared to a population of 3.27 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of San Diego County increased by 443,659. In this period, the peak population was 3.33 million in the year 2018. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the San Diego County is shown in this column.
• Year on Year Change: This column displays the change in San Diego County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 San Diego County Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Fairfield County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Fairfield County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2021, the population of Fairfield County was 959,768, a 0.41% increase year-by-year from 2020. Previously, in 2020, Fairfield County population was 955,895, an increase of 1.22% compared to a population of 944,388 in 2019. Over the last 20 plus years, between 2000 and 2021, population of Fairfield County increased by 75,436. In this period, the peak population was 959,768 in the year 2021. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

https://i.neilsberg.com/ch/population-of-fairfield-county-ct-population-by-year-2000-2021.jpeg" alt="Fairfield County population by year">

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2021

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2021)
• Population: The population for the specific year for the Fairfield County is shown in this column.
• Year on Year Change: This column displays the change in Fairfield County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Fairfield County Population by Year. You can refer the same here

This statistic shows the 25 largest counties in the United States in 2022, by population. In 2022, about 9.72 million people were estimated to be living in Los Angeles County, California.

Additional information on urbanization in the United States

Urbanization is defined as the process by which cities grow or by which societies become more urban. Rural to urban migration in the United States, and around the world, is often undertaken in the search for employment or to enjoy greater access to services such as healthcare. The largest cities in the United States are steadily growing. Given their size, incremental increases yield considerable numerical gains as seen by New York increasing by 69,777 people in 2011, the most of any city. However in terms of percentage growth, smaller cities outside the main centers are growing the fastest, such as Georgetown city and Leander city in Texas.

Urbanization has increased slowly in the United States, rising from 80.77 percent of the population living in urban areas in 2010 to 82.66 percent in 2020. In 2018, the United States ranked 14th in a ranking of countries based on their degree of urbanization. Unlike fully urbanized countries such as Singapore and Hong Kong, the United States maintains a sizeable agricultural industry. Although technological developments have reduced demands for rural labor, labor in the industry and supporting services are still required.

This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

Graph and download economic data for Resident Population in Orange County, CA (CAORAN7POP) from 1970 to 2024 about Orange County, CA; Los Angeles; residents; CA; population; and USA.

Graph and download economic data for Resident Population in Cuyahoga County, OH (OHCUYA5POP) from 1970 to 2024 about Cuyahoga County, OH; Cleveland; OH; residents; population; and USA.

Of the total population in Sweden of 10.55 million people, around half resided in the counties Stockholm, Västra Götaland or Skåne. This is also the three counties where the three largest cities in Sweden, Stockholm, Göteborg, and Malmö, are located. In the capital region Stockholm county, there lived nearly 2.5 million inhabitants in 2023. Västra Götaland county had close to 1.8 million inhabitants, while Skåne county, the southernmost region, had roughly 1.4 million inhabitants. The island Gotland had the lowest number of inhabitants with only 60,000.

The highest population density

Stockholm, Skåne and Västra Götaland were also the three counties in Sweden with the highest population density. In 2022, 374.6 inhabitants per square kilometer lived in Stockholm county, while the corresponding figures for Skåne and Västra Götaland were 129 and 73.9, respectively.

The highest rents

Unsurprisingly. Stockholm county is the county in Sweden with the highest rents for rented dwellings, with average prices for one square meter amounting to over 1,400 Swedish kronor in 2022. The lowest average renting prices were in the northwestern region Jämtland, one square meter costing 1,000 Swedish kronor.

About this dataset

Context

The dataset tabulates the Wake County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Wake County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Wake County was 1.19 million, a 1.67% increase year-by-year from 2022. Previously, in 2022, Wake County population was 1.17 million, an increase of 1.60% compared to a population of 1.15 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of Wake County increased by 556,746. In this period, the peak population was 1.19 million in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Wake County is shown in this column.
• Year on Year Change: This column displays the change in Wake County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Wake County Population by Year. You can refer the same here

Graph and download economic data for Resident Population in Clark County, WA (WACLAR1POP) from 1970 to 2024 about Clark County, WA; Portland; WA; residents; population; and USA.

Graph and download economic data for Resident Population in Fulton County, GA (GAFULT1POP) from 1970 to 2024 about Fulton County, GA; Atlanta; GA; residents; population; and USA.

About this dataset

Context

The dataset tabulates the data for the Orange County, VA population pyramid, which represents the Orange County population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Orange County, VA, is 28.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Orange County, VA, is 32.2.
• Total dependency ratio for Orange County, VA is 61.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Orange County, VA is 3.1.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Orange County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Orange County for the selected age group is shown in the following column.
• Population (Female): The female population in the Orange County for the selected age group is shown in the following column.
• Total Population: The total population of the Orange County for the selected age group 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 Orange County Population by Age. You can refer the same here

This Census Bureau Tile Layer displays Low Response Scores (LRS) by census tracts, utilized in the Response Outreach Area Mapper application. Per USCB, "The LRS is a metric developed by the Census Bureau to predict the percentage of households who will not self-respond to the Decennial Census. Support layers include State (or state equivalent) Boundary and County (or county equivalent) Boundary.Census Tract 36.01 Low Response ScoreData currency: Current Census service (ROAM/ROAM_Cache)Data modification(s): noneFor more information: Response Outreach Area Mapper; Response Outreach Area Mapper (ROAM)For feedback please contact: ArcGIScomNationalMaps@esri.comThumbnail image courtesy of: U.S. Department of AgricultureU.S. Census BureauPer USCB, "the Census Bureau is the federal government’s largest statistical agency. We are dedicated to providing current facts and figures about America’s people, places, and economy. Federal law protects the confidentiality of all the information the Census Bureau collects."

This statistic depicts the largest Puerto Rican-American population groups in different counties across the United States as of 2010. At this time there were 298,921 people of Puerto Rican origin living in Bronx County in New York.

In the United States in 2023, 89.2 percent of the homeless population living in El Dorado County, California were unsheltered.

Graph and download economic data for Resident Population in Fairfax County, VA (VAFAIR5POP) from 1970 to 2024 about Fairfax County, VA; Washington; VA; residents; population; and USA.

Estimated population count per county for 2019. Statistics from the Kenya National Bureau of Statistics.

Graph and download economic data for Resident Population in DuPage County, IL (ILDUPA0POP) from 1970 to 2023 about Du Page County, IL; Chicago; IL; residents; population; and USA.

About this dataset

Context

The dataset tabulates the population of Ohio County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Ohio County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.34% of total population being female. 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.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Ohio County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Ohio County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Ohio County Population by Race & Ethnicity. You can refer the same here

Graph and download economic data for Resident Population in Piscataquis County, ME (MEPISC1POP) from 1970 to 2023 about Piscataquis County, ME; ME; residents; population; and USA.