In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

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.

As of 2023, around 37.99 million people of Mexican descent were living in the United States - the largest of any Hispanic group. Puerto Ricans, Salvadorans, Cubans, and Dominicans rounded out the top five Hispanic groups living in the U.S. in that year.

About this dataset

Context

This list ranks the 50 states in the United States by Non-Hispanic White population, as estimated by the United States Census Bureau. It also highlights population changes in each states 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 Non-Hispanic White Population: This column displays the rank of states in the United States by their Non-Hispanic White population, using the most recent ACS data available.
• states: The states for which the rank is shown in the previous column.
• Non-Hispanic White Population: The Non-Hispanic White population of the states is shown in this column.
• % of Total states Population: This shows what percentage of the total states population identifies as Non-Hispanic White. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total U.S. Non-Hispanic White Population: This tells us how much of the entire United States Non-Hispanic White population lives in that states. 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/.

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.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of South Carolina by race. It includes the distribution of the Non-Hispanic population of South Carolina across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of South Carolina across relevant racial categories.

Key observations

Of the Non-Hispanic population in South Carolina, the largest racial group is White alone with a population of 3.24 million (66.97% of the total Non-Hispanic population).

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the South Carolina
• Population: The population of the racial category (for Non-Hispanic) in the South Carolina is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of South Carolina total Non-Hispanic 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 South Carolina Population by Race & Ethnicity. You can refer the same here

The graph shows the Hispanic population in the United States in 2022 and offers a forecast until 2060. According to this projection, there will be almost 98 million people of Hispanic descent in the United States in 2060.

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

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Atlanta by race. It includes the distribution of the Non-Hispanic population of Atlanta across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Atlanta across relevant racial categories.

Key observations

Of the Non-Hispanic population in Atlanta, the largest racial group is Black or African American alone with a population of 231,361 (49.43% of the total Non-Hispanic population).

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Atlanta
• Population: The population of the racial category (for Non-Hispanic) in the Atlanta is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Atlanta total Non-Hispanic 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 Atlanta Population by Race & Ethnicity. You can refer the same here

This layer contains a Vermont-only subset of census tract level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, BLOCK, BLKGRP, and TBLKGRP.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual tract level, since this data has been protected using differential privacy.*VCGI exported a Vermont-only subset of the nation-wide layer to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLON: Internal Point (Longitude) INTPTLAT: Internal Point (Latitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual tracts will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

This layer contains a Vermont-only subset of county subdivision level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name derived from the technical documentation provided by the Census. The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderIn addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added: PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual tract level, since this data has been protected using differential privacy.*VCGI exported a subset of the TIGER geodatabase fields and tabular data fields to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier (from TIGER) NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLON: Internal Point (Longitude) INTPTLAT: Internal Point (Latitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual tracts will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Phoenix by race. It includes the distribution of the Non-Hispanic population of Phoenix across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Phoenix across relevant racial categories.

Key observations

Of the Non-Hispanic population in Phoenix, the largest racial group is White alone with a population of 671,373 (70.97% of the total Non-Hispanic population).

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Phoenix
• Population: The population of the racial category (for Non-Hispanic) in the Phoenix is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Phoenix total Non-Hispanic 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 Phoenix Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Gay Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Gay, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Gay.

Key observations

Among the Hispanic population in Gay, regardless of the race, the largest group is of Mexican origin, with a population of 48 (100% of the total Hispanic population).

Content

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

Origin for Hispanic or Latino population include:

• Mexican
• Puerto Rican
• Cuban
• Other Hispanic or Latino

Variables / Data Columns

• Origin: This column displays the origin for Hispanic or Latino population for the Gay
• Population: The population of the specific origin for Hispanic or Latino population in the Gay is shown in this column.
• % of Total Hispanic Population: This column displays the percentage distribution of each Hispanic origin as a proportion of Gay total Hispanic or Latino 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 Gay Population by Race & Ethnicity. You can refer the same here

The Housing Discrimination Study 2000 (HDS 2000) represents the most ambitious effort to date to measure the extent of housing discrimination in the United States against persons because of their race or color. It is the third nationwide effort sponsored by HUD to measure the amount of discrimination faced by minority home seekers. The previous studies were conducted in 1977 and 1989.The report noted below provides national estimates of discrimination faced by African Americans and Hispanics in 2000/2001 as they searched for housing in the sales and rental markets. It also provides an accurate measure of how housing discrimination has changed for these groups since 1989.Discrimination in Metropolitan Housing Markets: Phase 1The results in this report are based on 4,600 paired tests in 23 metropolitan areas nationwide. The report shows large decreases between 1989 and 2000 in the level of discrimination experienced by Hispanics and African Americans seeking to a buy a home. There has also been a modest decrease in discrimination toward African Americans seeking to rent a unit. This downward trend, however, has not been seen for Hispanic renters. Hispanic renters now are more likely to experience discrimination in their housing search than do African American renters.While generally down since 1989, housing discrimination still exists at unacceptable levels. The greatest share of discrimination for Hispanic and African American home seekers can still be attributed to being told units are unavailable when they are available to non-Hispanic whites and being shown and told about less units than a comparable non-minority. Although discrimination is down on most measures for African American and Hispanic homebuyers, there are worrisome upward trends of discrimination in the areas of geographic steering for African Americans and, relative to non-Hispanic whites, the amount of help agents provide to Hispanics with obtaining financing. On the rental side, Hispanics are more likely in 2000 than in 1989 to be quoted a higher rent than their white counterpart for the same unit.There are three volumes to this report, the main report, an annex, and a supplement. The main report provides the key findings; the annex provides more details on the data collection, analysis methods and metropolitan estimates; and the supplement uses 1,507 additional tests conducted in Phase 2 to provide state estimates for Alabama, California, Georgia, and New York, metropolitan estimates for the Baltimore MSA and the Miami MSA, and updated national estimates of discrimination for blacks and Hispanics.Discrimination in Metropolitan Housing Markets: Phase 2 - Asians and Pacific IslandersThis study provides the first ever estimate of the level of discrimination experienced by Asians and Pacific Islanders. The results are based on 889-paired tests conducted in eleven metropolitan areas nationwide in 2000 and 2001. The key findings are that:Asian and Pacific Islander prospective renters experienced consistent adverse treatment relative to comparable whites in 21.5 percent of tests, about the same as the level for African American and Hispanic renters.Asian and Pacific Islander prospective homebuyers experienced consistent adverse treatment relative to comparable whites 20.4 percent of the time, with systematic discrimination occurring in housing availability, inspections, financing assistance, and agent encouragement.In addition to the national estimate for Asians and Pacific Islanders, the report also provides a national estimate for Asians alone, an estimate for the continental U.S., statewide estimate of discrimination against Asians and Pacific Islanders in California, estimates of discrimination faced by Chinese and Koreans in the Los Angeles metropolitan area, and an estimate of discrimination faced by Southeast Asians in the Minneapolis metropolitan area.Discrimination in Metropolitan Housing Markets: Phase 3 - Native AmericansThis study provides estimates of the level of housing discrimination experienced by Native Americans when they search for housing in the metropolitan areas of Minnesota, Montana, and New Mexico. Across all three states, Native Americans receive consistently unfavorable treatment relative to whites in 28.5 percent of rental tests. Systematic discrimination is most observable on measures of availability. That is,

The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

BackgroundCancer is the leading cause of death among Latinos, the largest minority population in the United States (US). To address cancer challenges experienced by Latinos, we conducted a catchment area population assessment (CAPA) using validated questions from the National Cancer Institute (NCI) population health assessment supplement at our NCI-designated cancer center in California.MethodsA mixed-methods CAPA was administered by bilingual-bicultural staff, with a focus on understanding the differences between foreign-born and US-born Latinos.Results255 Latinos responded to the survey conducted between August 2019 and May 2020. Most respondents were foreign-born (63.9%), female (78.2%), and monolingual Spanish speakers (63.2%). Results showed that compared to US-born Latinos, foreign-born individuals were older, had lower educational attainment, were most likely to be monolingual Spanish speakers, were low-income, and were more likely to be uninsured. Foreign-born Latinos had lower levels of alcohol consumption and higher consumption of fruits and vegetables. The rate of preventive cancer screenings for breast, cervical and colorectal cancer did not differ by birthplace, although a low fraction (35.3%) of foreign-born Latinas who were up-to-date compared to US-born Latinas (83.3%) with colorectal cancer screening was observed. Time since the last routine check-up for all preventable cancers (cervical p=0.0002, breast p=0.0039, and colorectal p=0.0196) is significantly associated with being up to date with cancer screening. Individuals who had a check-up of two or more years ago are 84% less likely to be up to date with pap smears than those who had a check-up within the year (p=0.0060). Individuals without health insurance are 94% less likely to be up to date with mammograms and colonoscopy/FIT tests (p=0.0016 and p=0.0133, respectively) than those who are insured. There is no significant association between screening and nativity.ConclusionsConsiderable differences in socio-economic and environmental determinants of health and colorectal cancer screening rates were observed between US-born and foreign-born Latinos. The present study represents the foundation for future targeted intervention among immigrant populations at our cancer center’s catchment area.

Hispanic Foods Market size was valued at USD 50.1 Billion in 2023 and is projected to reach USD 80.1 Billion by 2030, growing at a CAGR of 6.93% during the forecast period 2024-2030.

Global Hispanic Foods Market Drivers The market drivers for the Hispanic Foods Market can be influenced by various factors. These may include:

Changing Demographics: As the number of Hispanic people increases across the country, the desire for real Hispanic food is rising.

Cultural Diversity and Awareness: As customers become more aware of and appreciative of other cultures, so does their desire for and appreciation of Hispanic cuisine.

Health & Wellness Trends: As consumer demands for better options expand, Hispanic foods are generally seen as tasty, fresh, and combining nutritious components.

Growing Disposable Income: Spending on specialized and ethnic foods has increased as a result of better economic conditions and growing disposable incomes among Hispanic and non-Hispanic customers.

Social Media and Digital Influence: Digital media and social media platforms are important for raising consumer interest and encouraging innovation in Hispanic food as well as for raising awareness of the cuisine.

Globalization and Trends in International Cuisine: Globalization has raised awareness of a variety of cuisines, including Hispanic cuisine, which has stimulated interest and uptake outside of traditional Hispanic populations.

Product Development and Innovation: Continual innovation in product offerings, such as ready-to-eat Hispanic food options that are convenient, responds to the shifting tastes and lives of consumers.

Retail and Foodservice Expansion: Increasing the selection of Hispanic meals in eateries, retail stores, and foodservice venues promotes accessibility and increases customer spending.

Travel and Culinary Tourism: By introducing customers to real Hispanic food, these travel and culinary experiences stimulate interest and demand in their home markets.

Events that highlight Hispanic cuisine include cultural events and festivals, which provide customers a chance to sample and enjoy the variety of Hispanic cuisine.

US Language Learner Market size was estimated at USD 74.06 Billion in 2024 and is projected to reach USD 234.55 Billion by 2031, growing at a CAGR of 15.50% from 2024 to 2031.

Key Market Drivers • Increase in Globalized Communication: Heightened demand for multilingual communication skills is observed due to the growing interconnectedness of the world, fostered by international trade and travel. This demand is particularly true in the US, where businesses are increasingly operated on a global scale. As a result, the need to learn new languages to effectively collaborate with international partners is driven by globalization. • Evolving Educational Landscape: A shift towards incorporating language learning at a younger age is being observed in the educational system in the US. This shift is driven by a recognition of the cognitive benefits of multilingualism and the growing importance of foreign languages in the job market. As a result, language learning at a foundational level is exposed to a larger segment of the US population, creating a more fertile ground for continued language acquisition later in life. • Technological Advancements in Learning Methods: The rise of mobile technology and online learning platforms has significantly impacted the US language learner market. Language learning has been made more accessible and convenient than ever before by these advancements. A vast array of interactive and personalized language courses can now be accessed by learners on their own time and schedule. This surge in language learning participation within the US is fueled by this ease of access. • Growing Hispanic Population: A significant and rapidly growing Hispanic population is observed in the US. This demographic shift has led to a heightened demand for Spanish language learning within the country. Spanish language skills are increasingly seen as valuable not only for personal communication but also for professional opportunities in a diverse workforce. The growth of the Spanish language learning segment within the US market is propelled by this demand.

Release Date: 2022-11-10.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY22-308)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2021 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2021 ABS collection year produces statistics for the 2020 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.The data include U.S. firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Employer firms with more than one domestic establishment are counted in each geographic area and industry in which they operate, but only once in the U.S. and state totals for all sectors. Employment reflects the number of paid employees during the pay period in the reference year that included March 12...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Sales and receipts of employer firms (reported in $1,000s of dollars). Number of employees (during the March 12 pay period). Annual payroll (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown for the number of years the firm has been in operation:.Years in Business:. Firms with less than 2 years in business. Firms with 2 to 3 years in business. Firms with 4 to 5 years in business. Firms with 6 to 10 years in business. Firms with 11 to 15 years in business. Firms with 16 or more years in business. ...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for businesses owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subgroup total because a Hispanic or Latino firm may be of any race, and because a firm could be tabulated in more than one racial group. For example, if a firm responded as both Chinese and Black majority owned, the firm would be included in the detailed Asian and Black estimates but would only be counted once toward the higher level all firms' estimates.. References such as "Hispanic- or Latino-owned" businesses refer only to businesses operating in the 50 states and the District of Columbia that self-identified 51 percent or more of their ownership in 2020 to be by individuals of Mexican, Puerto Rican, Cuban or other Hispanic or Latino origin. The ABS does not distinguish between U.S. residents and nonresidents. Companies owned by foreign governments or owned by other companies, foreign or domestic, are included in the category "Unclassifiable."...Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3- and 4-digit NAICS code for:..United States...For more information about NAICS, see NAICS Codes & Understanding Industry Class...

IntroductionThe population of older adults with Alzheimer’s disease and Related Dementias (ADRD) is growing larger and more diverse. Prevalence of ADRD is higher in African American (AA) and Hispanic populations relative to non-Hispanic whites (nHW), with larger differences for women compared to men of the same race. Given the public health importance of this issue, we sought to determine if AA and Hispanic women exhibit worse ADRD pathology compared to men of the same race and nHW women. We hypothesized that such differences may explain the discrepancy in ADRD prevalence.MethodsWe evaluated 932 articles that measured at least one of the following biomarkers of ADRD pathology in vivo and/or post-mortem: beta-amyloid (Aß), tau, neurodegeneration, and cerebral small vessel disease (cSVD). Criteria for inclusion were: (1) mean age of participants >65 years; (2) inclusion of nHW participants and either AA or Hispanics or both; (3) direct comparison of ADRD pathology between racial groups.ResultsWe included 26 articles (Aß = 9, tau = 6, neurodegeneration = 16, cSVD = 18), with seven including sex-by-race comparisons. Studies differed by sampling source (e.g., clinic or population), multivariable analytical approach (e.g., adjusted for risk factors for AD), and cognitive status of participants. Aß burden did not differ by race or sex. Tau differed by race (AA < nHW), and by sex (women > men). Both severity of neurodegeneration and cSVD differed by race (AA > nHW; Hispanics < nHW) and sex (women < men). Among the studies that tested sex-by-race interactions, results were not significant.ConclusionFew studies have examined the burden of ADRD pathology by both race and sex. The higher prevalence of ADRD in women compared to men of the same race may be due to both higher tau load and more vulnerability to cognitive decline in the presence of similar Aß and cSVD burden. AA women may also exhibit more neurodegeneration and cSVD relative to nHW populations. Studies suggest that between-group differences in ADRD pathology are complex, but they are too sparse to completely explain why minority women have the highest ADRD prevalence. Future work should recruit diverse cohorts, compare ADRD biomarkers by both race and sex, and collect relevant risk factor and cognitive data.