The statistic shows the share of U.S. population, by race and Hispanic origin, in 2016 and a projection for 2060. As of 2016, about 17.79 percent of the U.S. population was of Hispanic origin. Race and ethnicity in the U.S. For decades, America was a melting pot of the racial and ethnical diversity of its population. The number of people of different ethnic groups in the United States has been growing steadily over the last decade, as has the population in total. For example, 35.81 million Black or African Americans were counted in the U.S. in 2000, while 43.5 million Black or African Americans were counted in 2017.

The median annual family income in the United States in 2017 earned by Black families was about 50,870 U.S. dollars, while the average family income earned by the Asian population was about 92,784 U.S. dollars. This is more than 15,000 U.S. dollars higher than the U.S. average family income, which was 75,938 U.S. dollars.

The unemployment rate varies by ethnicity as well. In 2018, about 6.5 percent of the Black or African American population in the United States were unemployed. In contrast to that, only three percent of the population with Asian origin was unemployed.

Dataset population: Households

Multiple ethnic group households

Multiple ethnic groups classifies households by the diversity in ethnic group of household members in different relationships.

For example, different ethnic groups between generations or within partnerships.

For Northern Ireland only, 'Same ethnic group' means within the same ethnic group as defined by the 12-way ethnic classification (White, Chinese, Irish Traveller, Indian, Pakistani, Bangladeshi, Other Asian, Black Caribbean, Black African, Black Other, Mixed, Other).

'Different ethnic groups within partnerships' includes all households where there are different ethnic groups within partnerships whether or not there are also different ethnic groups between generations.

As of 2021, Akan was the largest ethnic group in Ghana, accounting for 45.7 percent of the country's population. Simultaneously, Akan, as a language, was the most widely spoken in Ghana. Mole-Dagbani and Ewe covered 18.5 percent and 12.8 percent of the groups of ethnicity, respectively. Other ethnic groups include Ga-Dangme, Gurma, Guan, and Grusi.

This map shows the diversity index of the population in the USA in 2010 by block group. "The diversity index summarizes racial and ethnic diversity. The index shows the likelihood that two people, chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity). For example, a diversity index of 59 means there is a 59 percent probability that two people randomly chosen would belong to different race or ethnic groups." -Esri DemographicsIt calls to the 2010 Census service with attributes related to race and ethnicity. The field PctNonWhite calculates the total percentage of non-white population by subtracting the Total white population from the reported population total. This yields the total non-white population (Field "TotNonWhite"). This number was then divided by the total reported population and multipled by 100 to yield a percetage of the population that is non-white (Field "PctNonWhite"). Original data sourced from: https://tpc.maps.arcgis.com/home/item.html?id=04a8fbbf59aa48ebbc646ba2bc8d9b1c

Background: Each year, the Virginia Department of Education collects statistics on the number of students enrolled in public school on September 30th. This report is submitted by each school in Virginia which officially enrolls students (i.e. student records are maintained on a Virginia Teacher's Register or automated system). Student counts are reported by grade assignment and ethnicity. Excluded from the September 30 count are Special education preschool pupils, pupils in hospitals, clinics or detention homes, and local programs such as vocational and alternative education centers (i.e. centers or schools which receive, but do not officially enroll students). Definitions: The five Federal racial/ethnic categories are as follows: American Indian or Alaskan native - a person having origins (ancestry) in any of the original peoples of North America, who maintains cultural identification through tribal affiliation or community recognition. Asian or Pacific Islander - a person having origins (ancestry) in any of the original peoples of the Far East, Southeast Asian, the Pacific Islands, or the Indian subcontinent. Included, for example, are peoples of China, Korea, the Philippine Islands, Samoa, and India.

Black, not of Hispanic origin - a person having origins (ancestry) in any of the black racial groups of Africa.

Hispanic- a person of Mexican, Puerto Rican, Cuban, Central or South American, or other Spanish culture or origin (ancestry), regardless of race.

White, not of Hispanic origin - a person have origins (ancestry) in any of the original peoples of Europe, North Africa, or the Middle East.

The following abbreviations are used in the 1998 Fall Membership reports: PK - Pre-Kindergarten, KG - Kindergarten, PG - Post Graduate, UG - Ungraded.

This dataset provides Census 2021 estimates that classify households in England and Wales by the diversity in ethnic group of household members in different relationships. The estimates are as at Census Day, 21 March 2021.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Multiple ethnic groups in household (6 categories)

Classifies households by whether members identify as having the same or different ethnic groups.

If multiple ethnic groups are present, this identifies whether they differ between generations or partnerships within the household.

This dataset provides Census 2022 estimates for the Multiple ethnic groups in household in Scotland.

Multiple ethnic groups in household

'Multiple ethnic groups' classifies households by the diversity in ethnic group of household members in different relationships - for example, different ethnic groups between generations or within partnerships. The ethnic group of each household member is coded according to the hierarchy document containing 19 categories for ethnic groups and then compared to obtain the classification below.

Details of classification can be found here

The quality assurance report can be found here

Dataset contains ethnic group census usually resident population counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the ethnic group population count between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by regional council.

The ethnic groups are:

• European
• Māori
• Pacific peoples
• Asian
• Middle Eastern/Latin American/African
• Other ethnicity.

Map shows percentage change in the census usually resident population count for ethnic groups between the 2018 and 2023 Censuses.

Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Ethnicity concept quality rating

Ethnicity is rated as high quality.

Ethnicity – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Symbol

-998 Not applicable

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for ‘Total stated’ where this applies.

In 2023, the gross median household income for Asian households in the United States stood at 112,800 U.S. dollars. Median household income in the United States, of all racial and ethnic groups, came out to 80,610 U.S. dollars in 2023. Asian and Caucasian (white not Hispanic) households had relatively high median incomes, while the median income of Hispanic, Black, American Indian, and Alaskan Native households all came in lower than the national median. A number of related statistics illustrate further the current state of racial inequality in the United States. Unemployment is highest among Black or African American individuals in the U.S. with 8.6 percent unemployed, according to the Bureau of Labor Statistics in 2021. Hispanic individuals (of any race) were most likely to go without health insurance as of 2021, with 22.8 percent uninsured.

This study describes how racial/ethnic group differences in self-neglect incidence varied across metropolitan and rural regions of Texas. The data included 134,538 cases of self-neglect validated by adult protective services among people 65+ years old from 2020 to 2023. We aggregated county population figures from US Census Bureau estimates and used negative binomial regression models to estimate the association of race/ethnicity, gender, and region type with self-neglect case counts. Self-neglect incidence among Black older adults was about twice that of White older adults, a difference that persisted across metropolitan regions. Black-White differences were more pronounced in Northwest rural regions but were absent in the El Paso region. Hispanic-White differences varied across both metropolitan and rural regions. In the Arlington region, for example, self-neglect incidence among Hispanic older adults was less than that of White older adults, whereas in San Antonio it was greater. Addressing self-neglect among Black and Hispanic older adults should anticipate that different communities may require distinct approaches. Future studies with more geographic units should build on this descriptive study to explain variation in racial/ethnic group differences in self-neglect incidence.

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

The survey examines the attitudes of second-generation immigrants in Finland toward democracy, their political participation, and how they discuss political and social issues with those close to them. The survey responses are used in a research project funded by the Prime Minister's Office on the social participation of Finns with foreign background and foreign-language speakers (UTViS). The data were collected through the Gen2 survey panel, which is part of the Finnish Research Infrastructure for Public Opinion (FIRIPO). The survey began by asking respondents about their views on democracy in Finland using various statements. They were also asked about their satisfaction with the functioning of democracy. Next, respondents were asked whether they voted in the 2023 parliamentary elections and which party they chose. The survey then examined their societal participation over the past four years, including, for example, whether they had taken part in peaceful demonstrations. The next section focused on how having a parent from outside Finland may have influenced political and societal discussions between respondents and their parents. Respondents were first asked about their parents' background and reasons for moving to Finland. They then evaluated a series of statements about their parents' political engagement, discussions, and voting behavior during their childhood and adolescence. Similar statements were then assessed in relation to the present day. Finally, the survey addressed experiences and perceptions of racism, including whether respondents believe racism is a problem in Finnish society. Background variables included the respondent's age, gender, region of residence, electoral district, statistical grouping of municipalities, level of education, occupational group, party affiliation, and the continent of birth of their parents.

In 2021, 20.1% of people from the Indian ethnic group were in higher managerial and professional occupations – the highest percentage out of all ethnic groups in this socioeconomic group.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by country of birth and by ethnic group. The estimates are as at Census Day, 21 March 2021.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Country of birth

The country in which a person was born.

For people not born in one of in the four parts of the UK, there was an option to select "elsewhere".

People who selected "elsewhere" were asked to write in the current name for their country of birth.

Ethnic group

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.

Respondents could choose one out of 19 tick-box response categories, including write-in response options.

The statistics of indigenous peoples in various districts of Taichung CityData for each year can be found at the web address with the parameter "Year" (in ROC year)Data for each year can be found at the web address with the parameter "Month" (month)https://demographics.taichung.gov.tw/Demographic/WebService/APIReport03.aspx?Year112&Month05For example: Year112&Month05, then check the data for May 112th year

This statistic shows the share of ethnic groups in Australia in the total population. 33 percent of the total population of Australia are english.

Australia’s population

Australia’s ethnic diversity can be attributed to their history and location. The country’s colonization from Europeans is a significant reason for the majority of its population being Caucasian. Additionally, being that Australia is one of the most developed countries closest to Eastern Asia; its Asian population comes as no surprise.

Australia is one of the world’s most developed countries, often earning recognition as one of the world’s economical leaders. With a more recent economic boom, Australia has become an attractive country for students and workers alike, who seek an opportunity to improve their lifestyle. Over the past decade, Australia’s population has slowly increased and is expected to continue to do so over the next several years. A beautiful landscape, many work opportunities and a high quality of life helped play a role in the country’s development. In 2011, Australia was considered to have one of the highest life expectancies in the world, with the average Australian living to approximately 82 years of age.

From an employment standpoint, Australia has maintained a rather low employment rate compared to many other developed countries. After experiencing a significant jump in unemployment in 2009, primarily due to the world economic crisis, Australia has been able to remain stable and slightly increase employment year-over-year.

Information about the ethnic affiliation(s) and characteristics of a human population. Includes, for example, information about: the ethnic groups located within a geographic region, their community social structures, their mutual associations and conflicts with other groups, their historic roles and influence, and the physical distribution of their members. Ethnic groups are human populations whose members identify with each other, usually on the basis of having a common cultural traditions and heritage (for example: as distinguished by customs, language, religious practices, or common history) or a presumed common genealogy or ancestry.

In 2019, the Indian and White ethnic groups had the lowest percentage of recent internet users (90.4% and 90.5%). The Chinese group had the highest (98.6%).

This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in employment the week before the census in England and Wales by industry and by ethnic group. The estimates are as at Census Day, 21 March 2021.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Lower tier local authorities

Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.

Coverage

Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Industry (current)

Classifies people aged 16 years and over who were in employment between 15 March and 21 March 2021 by the Standard Industrial Classification (SIC) code that represents their current industry or business.

The SIC code is assigned based on the information provided about a firm or organisation’s main activity.

Ethnic group

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance.

Respondents could choose one out of 19 tick-box response categories, including write-in response options.

This dataset provides Census 2021 estimates that classify usual residents in Birmingham by ethnic group, by religion, and by age.

Ethnic Group: The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance. Religion: The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it. Age: A person's age on Census Day, 21 March 2021 in England and Wales.CoverageThis dataset is focused on the data for Birmingham at city level. About the 2021 CensusThe Census takes place every 10 years and gives us a picture of all the people and households in England and Wales.Protecting personal dataThe ONS sometimes need to make changes to data if it is possible to identify individuals. This is known as statistical disclosure control. In Census 2021, they:Swapped records (targeted record swapping), for example, if a household was likely to be identified in datasets because it has unusual characteristics, they swapped the record with a similar one from a nearby small area. Very unusual households could be swapped with one in a nearby local authority.Added small changes to some counts (cell key perturbation), for example, we might change a count of four to a three or a five. This might make small differences between tables depending on how the data are broken down when they applied perturbation.For more geographies, aggregations or topics see the link in the Reference below. Or, to create a custom dataset with multiple variables use the ONS Create a custom dataset tool.