This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

This map shows the percentage of people who identify as something other than non-Hispanic white throughout the US according to the most current American Community Survey. The pattern is shown by states, counties, and Census tracts. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The Arcade expression used was: 100 - B03002_calc_pctNHWhiteE, which is simply 100 minus the percent of population who identifies as non-Hispanic white. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map update automatically annually when the newest estimates are released by ACS. For more detailed metadata, visit the ArcGIS Living Atlas Layer: ACS Race and Hispanic Origin Variables - Boundaries.The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.Other maps of interest:American Indian or Alaska Native Population in the US (Current ACS)Asian Population in the US (Current ACS)Black or African American Population in the US (Current ACS)Hawaiian or Other Pacific Islander Population in the US (Current ACS)Hispanic or Latino Population in the US (Current ACS) (some people prefer Latinx)Population who are Some Other Race in the US (Current ACS)Population who are Two or More Races in the US (Current ACS) (some people prefer mixed race or multiracial)White Population in the US (Current ACS)Race in the US by Dot DensityWhat is the most common race/ethnicity?

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.

How racially diverse are residents in Massachusetts? This topic shows the demographic breakdown of residents by race/ethnicity and the increases in the Non-white population since 2010.

In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

Note. Demographic data were not collected in Study 3.Participant Demographics.

The 2006 Census estimated 5.1 million individuals who belonged to a visible minority. The Employment Equity Act defines visible minorities as 'persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour’. The visible minority population has grown steadily over the last 25 years. In 1981, when data for the four Employment Equity designated groups were first derived, the estimated 1.1 million visible minorities represented 4.7% of Canada's total population. In 1991, 2.5 million people were members of the visible minority population, 9.4% of the total population. The visible minority population further increased to 3.2 million in 1996, or 11.2% of the total population. By 2001, their numbers had reached an estimated 3.9 million or 13.4% of the total population. In 2006, the visible minorities accounted for 16.2% of Canada’s total population. This map shows the percentage of visible minorities (South Asian population) by census subdivisions.

Four focus groups of 15 individuals each were conducted in greater London and Birmingham in adjacent locales, one diverse, one more homogeneous. Locations were Croydon and Bromley in Greater London, and Lozells and Sutton Coldfield in Greater Birmingham. Participants were paid £30 apiece for their time and recruited by a Recruitment company.

Respondents were asked about perceptions of immigration and residential choice. We explored the 'halo' effect among those in whiter areas living in proximity to diversity, and the 'contact' effect of whites living with minorities in diverse areas. The former is theorised to increase threat perceptions of diversity, the latter to mitigate them.

Questions also explored ethnically motivated 'white flight' or whether social ties and amenities account for ethnic sorting. The link between immigration and issues of fairness, housing, services and employment was also broached.

Locations and dates:

3rd April, East Croydon United Reform Church, 6-7.30pm (diverse area) 8th April, Hayes Village Hall, Bromley, 6-7.30pm (White area)

9th April, Trinity Centre, Sutton Coldfield. 6-7.30pm (White area) 10th April, Lozells Methodist Community Centre, Birmingham, 6-7.30pm (diverse area)

This project advances the hypothesis that ethnic change in England and Wales is associated with white working-class ‘exit,’ ‘voice’, or ‘accommodation’. ‘Voice’ is manifested as a rise in ethnic nationalist voting and anti-immigration sentiment and ‘exit’ as outmigration from, or avoidance of, diverse locales. Once areas reach a threshold of minority population share, however, these initial responses may give way to ‘accommodation’ in the form of decreased ethno-nationalist voting, reduced anti-immigration sentiment and lower white outmigration. In the course of our investigation, we ask the policy-relevant question: do residential integration and minority acculturation calm or fuel white working-class exit and voice? In other words, does contact improve ethnic relations or do ‘good fences make good neighbours’? This research adds to existing scholarship by integrating individual data with a more complex array of contextual variables, blending quantitative methods with focus-group qualitative research.

Relative concentration of the Southern California region's Black/African American population. The variable HSPBIPOC is equivalent to all individuals who select a combination of racial and ethnic identity in response to the Census questionnaire EXCEPT those who select "not Hispanic" for the ethnic identity question, and "white race alone" for the racial identity question. This is the most encompassing possible definition of racial and ethnic identities that may be associated with historic underservice by agencies, or be more likely to express environmental justice concerns (as compared to predominantly non-Hispanic white communities). Until 2021, federal agency guidance for considering environmental justice impacts of proposed actions focused on how the actions affected "racial or ethnic minorities." "Racial minority" is an increasingly meaningless concept in the USA, and particularly so in California, where only about 3/8 of the state's population identifies as non-Hispanic and white race alone - a clear majority of Californians identify as Hispanic and/or not white. Because many federal and state map screening tools continue to rely on "minority population" as an indicator for flagging potentially vulnerable / disadvantaged/ underserved populations, our analysis includes the variable HSPBIPOC which is effectively "all minority" population according to the now outdated federal environmental justice direction. A more meaningful analysis for the potential impact of forest management actions on specific populations considers racial or ethnic populations individually: e.g., all people identifying as Hispanic regardless of race; all people identifying as American Indian, regardless of Hispanic ethnicity; etc.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as HSPBIPOC alone to the proportion of all people that live within the 13,312 block groups in the Southern California RRK region that identify as HSPBIPOC alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of HSPBIPOC individuals compared to the Southern California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then HSPBIPOC individuals are highly concentrated locally.

Abstract copyright UK Data Service and data collection copyright owner.

The purpose of this survey was to study non-white people aged 15 and over, whose families originate from India, Pakistan and Bangladesh, or the East Indies, with reference to their housing, employment and educational characteristics, their awareness and experience of racial discrimination. Comparative data were also collected for white men aged 16 and over, using the same questionnaire but with questions omitted when not applicable.
Main Topics:
Attitudinal/Behavioural Questions
Immigration: reasons; advantages of Britain/previous country; whether definite job arranged prior to arrival. Residence: number of rooms occupied; whether house was multi-occupied; amenities (whether shared); number of addresses in past five years. Tenure:
1. If owned: whether singly or jointly; mortgage/loan details; leasehold/freehold (date of expiry).
2. If rented: rent and rates details; council/private ownership; race of landlord. Council house tenants were asked how they obtained their housing.
Reasons for leaving previous residence:
A. Personal experience of mortgage/loan refusal, type of organisation which refused, year of application.
B. Personal experience of refusal of rented accommodation, number of refusals, details of last refusal.
In both A and B, respondents were asked to give the organisation's reasons for refusal and their personal opinion of reasons, with an explanation. Details of housing and financial facilities provided by the Council, entitlement/receipt of rent rebates and/or allowances, whether respondent has made an application to the council (length of time on waiting list). Occupation: hours worked per week, position, responsibility, qualifications, nature of firm, number of employees, source of information about job, promotion prospects, job satisfaction. In addition, respondents were asked whether they had visited the employment exchange or were receiving/had received benefits since 1964. Respondents were asked to relate experiences of unfair treatment with regard to promotion or application for jobs, and whether they thought there were firms giving equal opportunities to Asians and whites. Whether respondent believed employers discriminated against them - reasons. Details of previous refusals. Trade union membership and existence of unions at workplace.
Whether unemployed women had ever considered working (reasons). Working women with children were asked about child care facilities (hours, cost, satisfaction, etc.) Asian women were asked whether religion or family custom restricted their lives in terms of work, going out, company. Desired change was explored.
All respondents asked whether situation in Britain had improved for Asians over past five years - reasons. Knowledge of government bodies on race relations/Race Relations Board and its functions/Community Relations Commission and its functions was tested.
Whether voted at previous general election. Whether on voting list.
Background Variables
Age, sex, place of birth, previous countries of residence, date of arrival in Britain, age on arrival in Britain. Number of persons in household, household status. Age finished full-time education, examination and qualification details, further study, school attended by children.
Employment status, income, ownership of consumer durables. Residence: type, age, external conditions. Fluency in English, language of interview. Sampling area. Religion, church/mosque/temple attendance.

Among the 81 largest metropolitan areas (by population) in the United States, Knoxville, Tennessee was ranked first with **** percent of residents reporting as white, non-Hispanic in 2023.

To assess differences in psychological outcomes as well as risk and protective factors for these outcomes among several USA ethnic groups and identify correlates of these psychological outcomes among adults with diabetes in the second Diabetes Attitudes, Wishes and Needs (DAWN2) study. The core USA DAWN2 sample was supplemented by independent samples of specific ethnic minority groups, yielding a total of 447 White non-Hispanics, 241 African Americans, 194 Hispanics, and 173 Chinese Americans (n = 1055). Multivariate analysis examined ethnic differences in psychological outcomes and risk/protective factors (disease, demographic and socioeconomic factors, health status and healthcare access/utilization, subjective burden of diabetes and social support/burden). Separate analyses were performed on each group to determine whether risk/protective factors differed across ethnic groups. Psychological outcomes include well-being, quality of life, impact of diabetes on life domains, diabetes distress, and diabetes empowerment. NCT01507116. Ethnic minorities tended to have better psychological outcomes than White non-Hispanics, although their diabetes distress was higher. Levels of most risk and protective factors differed significantly across ethnic groups; adjustment for these factors reduced ethnic group differences in psychological outcomes. Health status and modifiable diabetes-specific risk/protective factors (healthcare access/utilization, subjective diabetes burden, social support/burden) had strong associations with psychological outcomes, especially diabetes distress and empowerment. Numerous interactions between ethnicity and other correlates of psychological outcomes suggest that ethnic groups are differentially sensitive to various risk/protective factors. Potential limitations are the sample sizes and representativeness. Ethnic groups differ in their psychological outcomes. The risk/protective factors for psychological outcomes differ across ethnic groups and different ethnic groups are more/less sensitive to their influence. These findings can aid the development of strategies to overcome the most prominent and influential psychosocial barriers to optimal diabetes care within each ethnic group.

Relative concentration of the Sierra Nevada region's Hispanic and/or Black, Indigenous or person of color (HSPBIPOC) population. The variable HSPBIPOC is equivalent to all individuals who select a combination of racial and ethnic identity in response to the Census questionnaire EXCEPT those who select "not Hispanic" for the ethnic identity question, and "white race alone" for the racial identity question. This is the most encompassing possible definition of racial and ethnic identities that may be associated with historic underservice by agencies, or be more likely to express environmental justice concerns (as compared to predominantly non-Hispanic white communities). Until 2021, federal agency guidance for considering environmental justice impacts of proposed actions focused on how the actions affected "racial or ethnic minorities." "Racial minority" is an increasingly meaningless concept in the USA, and particularly so in California, where only about 3/8 of the state's population identifies as non-Hispanic and white race alone - a clear majority of Californians identify as Hispanic and/or not white. Because many federal and state map screening tools continue to rely on "minority population" as an indicator for flagging potentially vulnerable / disadvantaged/ underserved populations, our analysis includes the variable HSPBIPOC which is effectively "all minority" population according to the now outdated federal environmental justice direction. A more meaningful analysis for the potential impact of forest management actions on specific populations considers racial or ethnic populations individually: e.g., all people identifying as Hispanic regardless of race; all people identifying as American Indian, regardless of Hispanic ethnicity; etc.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as HSPBIPOC alone to the proportion of all people that live within the 775 block groups in the Sierra Nevada RRK region that identify as HSPBIPOC alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of HSPBIPOC individuals compared to the Sierra Nevada RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then HSPBIPOC individuals are highly concentrated locally.

In 2019, people from most ethnic minority groups were more likely than White British people to live in the most deprived neighbourhoods.

Relative concentration of the Central California region's Hispanic and/or Black, Indigenous or person of color (HSPBIPOC) American population. The variable HSPBIPOC is equivalent to all individuals who select a combination of racial and ethnic identity in response to the Census questionnaire EXCEPT those who select "not Hispanic" for the ethnic identity question, and "white race alone" for the racial identity question. This is the most encompassing possible definition of racial and ethnic identities that may be associated with historic underservice by agencies, or be more likely to express environmental justice concerns (as compared to predominantly non-Hispanic white communities). Until 2021, federal agency guidance for considering environmental justice impacts of proposed actions focused on how the actions affected "racial or ethnic minorities." "Racial minority" is an increasingly meaningless concept in the USA, and particularly so in California, where only about 3/8 of the state's population identifies as non-Hispanic and white race alone - a clear majority of Californians identify as Hispanic and/or not white. Because many federal and state map screening tools continue to rely on "minority population" as an indicator for flagging potentially vulnerable / disadvantaged/ underserved populations, our analysis includes the variable HSPBIPOC which is effectively "all minority" population according to the now outdated federal environmental justice direction. A more meaningful analysis for the potential impact of forest management actions on specific populations considers racial or ethnic populations individually: e.g., all people identifying as Hispanic regardless of race; all people identifying as American Indian, regardless of Hispanic ethnicity; etc.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as HSPBIPOC alone to the proportion of all people that live within the 4,961 block groups in the Central California RRK region that identify as HSPBIPOC alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of HSPBIPOC individuals compared to the Central California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then HSPBIPOC individuals are highly concentrated locally.

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

This map contains the 2020 Vulnerable Population Index along with the component demographic layers. The following seven populations were determined to be vulnerable based on an understanding of both federal requirements and regional demographics: 1) Low-Income Population (below 200% of poverty level) 2) Non-Hispanic Minority Population 3) Hispanic or Latino Population (all races) 4) Population with Limited English Proficiency (LEP) 5) Population with Disabilities 6) Elderly Population (age 75 and up) 7) Households with No CarFor each of these populations, Census tracts with concentrations above the regional mean concentration are divided into two categories above the regional mean. These categories are calculated by dividing the range of values between the regional mean and the regional maximum into two equal-sized intervals. Tracts in the lower interval are given a score of 1 and tracts in the upper interval are given a score of 2 for that demographic variable. The scores are totaled from the seven individual demographic variables to yield the Vulnerable Population Index (VPI). The VPI can range from zero to fourteen (0 to 14). A lower VPI indicates a less vulnerable area, while a higher VPI indicates a more vulnerable area.FIELDSP_PovL100: Percent Below 100% of the Poverty Level, P_PovL200: Percent Below 200% of the Poverty Level, P_Minrty: Percent Minority (non-White, non-Hispanic), P_Hisp: Percent Hispanic, P_LEP: Percent Limited English Proficiency (speak English "not well" or "not at all"), P_Disabld: Percent with Disabilities, P_Elderly: Percent Elderly (age 75 and over), P_NoCarHH: Percent Households with No Vehicle, RG_PovL100: Regional Average (Mean) of Percent Below 100% of the Poverty Level, RG_PovL200: Regional Average (Mean) of Percent Below 200% of the Poverty Level, RG_Minrty: Regional Average (Mean) of Percent Minority (non-White, non-Hispanic), RG_Hisp: Regional Average (Mean) of Percent Hispanic, RG_LEP: Regional Average (Mean) of Percent Limited English Proficiency (speak English "not well" or "not at all"), RG_Disabld: Regional Average (Mean) of Percent with Disabilities, RG_Elderly: Regional Average (Mean) of Percent Elderly (age 75 and over), RG_NoCarHH: Regional Average (Mean) of Percent Households with No Vehicle, [NO SC_PovL100: Note: Percent Below 100% of the Poverty Level not used in VPI 2020 calculation],SC_PovL200: VPI Score for Below 200% of the Poverty Level (Values: 0, 1, or 2),SC_Minrty: VPI Score for Minority (non-White, non-Hispanic) (Values: 0, 1, or 2),SC_Hisp: VPI Score for Hispanic (Values: 0, 1, or 2),SC_LEP: VPI Score for Limited English Proficiency (speak English "not well" or "not at all") (Values: 0, 1, or 2),SC_Disabld: VPI Score for Disabilities (Values: 0, 1, or 2),SC_Elderly: VPI Score for Elderly (age 75 and over) (Values: 0, 1, or 2),SC_NoCarHH: VPI Score for Households with No Vehicle (Values: 0, 1, or 2),VPI_2020: Total VPI Score (0 minimum to 14 maximum).Additional information on equity planning at BMC can be found here.Sources: Baltimore Metropolitan Council, U.S. Census Bureau 2016–2020 American Community Survey 5-Year Estimates. Margins of error are not shown.Updated: April 2022

Number of people belonging to a visible minority group as defined by the Employment Equity Act and, if so, the visible minority group to which the person belongs. The Employment Equity Act defines visible minorities as 'persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour.' The visible minority population consists mainly of the following groups: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese.