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.

The leading causes of death among the white population of the United States are cardiovascular diseases and cancer. Cardiovascular diseases and cancer accounted for a combined **** percent of all deaths among this population in 2022. In 2020 and 2021, COVID-19 was the third leading cause of death among white people. Disparities in causes of death In the United States, there exist disparities in the leading causes of death based on race and ethnicity. For example, chronic liver disease and cirrhosis is the ***** leading cause of death among the white population and the ****** among the Hispanic population, but is not among the ten leading causes for Black people. On the other hand, homicide is the ******* leading cause of death among the Black population, but is not among the 10 leading causes for whites or Hispanics. However, cardiovascular diseases and cancer by far account for the highest share of deaths for every race and ethnicity. Diseases of despair The American Indian and Alaska Native population in the United States has the highest rates of death from suicide, drug overdose, and alcohol. Together, these three behavior-related conditions are often referred to as diseases of despair. Asians have by far the lowest rates of death due to drug overdose and alcohol, as well as slightly lower rates of suicide.

About this dataset

Context

This list ranks the 1208 cities in the Texas by White population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

About this dataset

Context

This list ranks the 46 counties in the South Carolina by Hispanic White population, as estimated by the United States Census Bureau. It also highlights population changes in each counties over the past five years.

Content

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

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

Variables / Data Columns

• Rank by Hispanic White Population: This column displays the rank of counties in the South Carolina by their Hispanic White population, using the most recent ACS data available.
• counties: The counties for which the rank is shown in the previous column.
• Hispanic White Population: The Hispanic White population of the counties is shown in this column.
• % of Total counties Population: This shows what percentage of the total counties population identifies as Hispanic White. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total South Carolina Hispanic White Population: This tells us how much of the entire South Carolina Hispanic White population lives in that counties. 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/.

About this dataset

Context

This list ranks the 10 cities in the Mason County, IL by White population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

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

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

This dataset represents the popular last names in the United States for White.

New York was the most populous state in the union in the year 1900. It had the largest white population, for both native born and foreign born persons, and together these groups made up over 7.1 million of New York's 7.2 million inhabitants at this time. The United States' industrial centers to the north and northeast were one of the most important economic draws during this period, and states in these regions had the largest foreign born white populations. Ethnic minorities Immigration into the agricultural southern states was much lower than the north, and these states had the largest Black populations due to the legacy of slavery - this balance would begin to shift in the following decades as a large share of the Black population migrated to urban centers to the north during the Great Migration. The Japanese and Chinese populations at this time were more concentrated in the West, as these states were the most common point of entry for Asians into the country. The states with the largest Native American populations were to the west and southwest, due to the legacy of forced displacement - this included the Indian Territory, an unorganized and independent territory assigned to the Native American population in the early 1800s, although this was incorporated into Oklahoma when it was admitted into the union in 1907. Additionally, non-taxpaying Native Americans were historically omitted from the U.S. Census, as they usually lived in separate communities and could not vote or hold office - more of an effort was made to count all Native Americans from 1890 onward, although there are likely inaccuracies in the figures given here. Changing distribution Internal migration in the 20th century greatly changed population distribution across the country, with California and Florida now ranking among the three most populous states in the U.S. today, while they were outside the top 20 in 1900. The growth of Western states' populations was largely due to the wave of internal migration during the Great Depression, where unemployment in the east saw many emigrate to "newer" states in search of opportunity, as well as significant immigration from Latin America (especially Mexico) and Asia since the mid-1900s.

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 layer was developed by the Research & Analytics Division of the Atlanta Regional Commission to represent the United States Census Bureau's 2010 Decennial Census data at the block geography.Attributes:STATEFP10 = The Federal Information Processing Series (FIPS) state code. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.COUNTYFP10 = The Federal Information Processing Series (FIPS) county code. TRACTCE10 = Census Tract Codes and Numbers—Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.BLOCKCE10 = Census block number - Census blocks are numbered uniquely with a four-digit census block number from 0000 to 9999 within census tract, which nest within state and county. The first digit of the census block number identifies the block group. Block numbers beginning with a zero (in Block Group 0) are only associated with water-only areas.GEOID10 = A concatenation of STATEFP10, COUNTYFP10, TRACTCE10, and BLOCKCE10, which produces the entire FIPS code for this geography.NAME10 = Block nameMTFCC10 = MAF/TIGER feature class codeUR10 = Census urban/rural indicatorUACE10 = Census urban area typeFUNCSTAT10 = Functional statusALAND10 = Land area in square metersAWATER10 = Water area in square metersINTPTLAT10 = Latitude of the centroid (center of this geography)INTPLON10 = Longitude of the centroid (center of this geography)STFID = The entire FIPS code of this geographyCOUNTY_NM = County namePLNG_REGIO = Planning regionSUMLEV = Summary level of census geography (code)NAME = Block namePLACE = Census place codeSTATE = The state FIPS codeCOUNTY = The county FIPS codeTRACT = The tract FIPS codeBLOCK = The block FIPS codetotpop10 = Total populationoner_10 = One race populationwhite_or10 = White, one race populationbl_or10 = Black, one race populationaian_or10 = American Indian and Alaska Native, one race populationasia_or10 = Asian, one race populationnhpi_or10 = Native Hawaiian and Other Pacific Islander, one race populationsomoth_or1 = Some other, one race populationtwoplusr10 = Two-plus races populationtotpop101 = Total populationhisp_lat10 = Total Hispanic/Latino populationnonhisp10 = Total non-Hispanic/Latino populationnh_or10 = Non-Hispanic/Latino, one race populationnhw_or10 = Non-Hispanic/Latino White, one race populationnhbl_or10 = Non-Hispanic/Latino Black, one race populationnhai_or10 = Non-Hispanic/Latino American Indian and Alaskan Native, one race populationnhas_or10 = Non-Hispanic/Latino Asian, one race populationnhhp_or10 = Non-Hispanic/Latino Native Hawaiian and Other Pacific Islander, one race populationnhot_or10 = Non-Hispanic/Latino Other, one race populationnh_twor10 = Non-Hispanic/Latino, two or more races populationtothu10 = Total housing unitstotoccu_10 = Total occupied housing unitstotvach_10 = Total vacant housing unitsAcresLand = Land area in acresAcresWater = Water area in acresAcresTotal = Total area in acresCD = Congressional Districe (111th)SLDU = State Legislative District (Upper; Year 1)SLDL = State Legislative District (Lower; Year 1)VTD = Voting DistrictVTDI = Voting District Indicatortotpop10_1 = Total populationoner_10_11 = One race populationwhite_or10_11 = White, one race populationbl_or10_1 = Black, one race populationaian_or10_1 = American Indian and Alaska Native, one race populationasia_or10_1 = Asian, one race populationnhpi_or10_1 = Native Hawaiian and Other Pacific Islander, one race populationsomoth_or10 = Some other, one race populationtwoplusr10_1 = Two-plus races populationhisp_lat10_1 = Total Hispanic/Latino populationnonhisp10_1 = Total non-Hispanic/Latino populationnh_or10_1 = Non-Hispanic/Latino, one race populationnhw_or10_1 = Non-Hispanic/Latino White, one race populationnhbl_or10_1 = Non-Hispanic/Latino Black, one race populationnhai_or10_1 = Non-Hispanic/Latino American Indian and Alaskan Native, one race populationnhas_or10_1 = Non-Hispanic/Latino Asian, one race populationnhhp_or10_1 = Non-Hispanic/Latino Native Hawaiian and Other Pacific Islander, one race populationnhot_or10_1 = Non-Hispanic/Latino Other, one race populationnh_twor10_1 = Non-Hispanic/Latino, two or more races populationtotvpop10 = Total 18+ populationvoner_10 = 18+ One race populationvwhite_or10 = 18+ White, one race populationvbl_or10 = 18+ Black, one race populationvaian_or10 = 18+ American Indian and Alaska Native, one race populationvasia_or10 = 18+ Asian, one race populationvnhpi_or10 = 18+ Native Hawaiian and Other Pacific Islander, one race populationvsomoth_or1 = 18+ Some other, one race populationvtwoplusr10 = 18+ Two-plus races populationvhisp_lat10 = 18+ Total Hispanic/Latino population of any racevnonhisp10 = 18+ Total non-Hispanic/Latino population of any racevnh_or10 = 18+ Non-Hispanic/Latino, one race populationvnhw_or10 = 18+ Non-Hispanic/Latino White, one race populationvnhbl_or10 = 18+ Non-Hispanic/Latino Black, one race populationvnhai_or10 = 18+ Non-Hispanic/Latino American Indian and Alaskan Native, one race populationvnhas_or10 = 18+ Non-Hispanic/Latino Asian, one race populationvnhhp_or10 = 18+ Non-Hispanic/Latino Native Hawaiian and Other Pacific Islander, one race populationvnhot_or10 = 18+ Non-Hispanic/Latino Other, one race populationvnh_twor10 = 18+ Non-Hispanic/Latino, two or more races populationvhisp_or10 = 18+ Hispanic, one race populationvhsw_or10 = 18+ Hispanic white, one race populationvhsbl_or10 = 18+ Hispanic black, one race populationvhsai_or10 = 18+ Hispanic American Indian, one race populationvhsas_or10 = 18+ Hispanic Asian, one race populationvhshp_or10 = 18+ Hispanic Hawaiian/Pacific Islander, one race populationvhsot_or10 = 18+ Hispanic other, one race populationvhs_twor10 = 18+ Hispanic, two or more races populationtotu18pop10 = Total under 18 populationu18oner_10 = Under 18, one race populationu18white_or10 = Under 18 white, one race populationu18bl_or10 = Under 18 black, one race populationu18aian_or10 = Under 18 American Indian, one race populationu18asia_or10 = Under 18 Asian, one race populationu18nhpi_or10 = Under 18 Hawaiian/Pacific Islander, one race populationu18somoth_or10 = Under 18 some other, one race populationu18twoplusr10 = Under 18, two or more races populationu18hisp_lat10 = Under 18, Hispanic/Latino of any race populationu18nonhisp10 = Under 18, non-Hispanic/Latino of any race populationu18nh_or10 = Under 18 non-Hispanic , one race populationu18nhw_or10 = Under 18 non-Hispanic white, one race populationu18nhbl_or10 = Under 18 non-Hispanic black, one race populationu18nhai_or10 = Under 18 non-Hispanic American Indian, one race populationu18nhas_or10 = Under 18 non-Hispanic Asian, one race populationu18nhhp_or10 = Under 18 non-Hispanic Hawaiian/Pacific Islander, one race populationu18nhot_or10 = Under 18 non-Hispanic other, one race populationu18nh_twor10 = Under 18 non-Hispanic, two or more races populationu18hs_or10 = Under 18 Hispanic, one race populationu18hishw_or10 = Under 18 Hispanic white, one race populationu18hisbl_or10 = Under 18 Hispanic black, one race populationu18hisai_or10 = Under 18 Hispanic American Indian, one race populationu18hisas_or10 = Under 18 Hispanic Asian, one race populationu18hishp_or10 = Under 18 Hispanic Hawaiian/Pacific Islander, one race populationu18hisoth_or10 = Under 18 Hispanic other, one race populationu18his_twor10 = Under 18 Hispanic, two or more races populationShape.STArea() = Total area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2010For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

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

African American males in the United States are much more likely to die from homicide than white males. In 2016, the death rate by homicide for African American males was ** per 100,000 population, compared to a rate of just *** per 100,000 population for white males. African American males are twice as likely to die from firearm-related injuries than white males, with handguns involved in the largest share of homicides in the U.S. Homicide as a leading cause of death While the leading causes of death for black and white residents in the U.S. are similar in many ways, there are two distinct differences. Homicide is not in the leading 10 causes of death among whites, but it is the ******* leading cause of death for blacks, accounting for around ***** percent of all deaths in this group. However, suicide is the ***** leading cause of death among whites, while it is not included in the ** leading causes of death for blacks. Death rates Overall, the death rate in the United States is higher among non-Hispanic whites than any other ethnicity. Furthermore, males across all ethnicities in the U.S. have higher death rates than females. The *** leading causes of death for every ethnicity in the U.S. are cancer and heart disease.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission to represent the United States Census Bureau's 2010 Decennial Census data at the block group geography.Attributes:STATEFP10 = The Federal Information Processing Series (FIPS) state code. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.COUNTYFP10 = The Federal Information Processing Series (FIPS) county code. TRACTCE10 = Census Tract Codes and Numbers—Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.BLKGRPCE10 = Block Group Codes—Block Groups have a valid code range of 0 through 9. Block Groups beginning with a zero only contain water area and are generally in coastal and Great Lakes water and territorial seas, but also in larger inland water bodies.GEOID10 = A concatenation of STATEFP10, COUNTYFP10, TRACTCE10, and BLKGRPCE10, which produces the entire FIPS code for this geography.NAMELSAD10 = Block Group nameMTFCC10 = MAF/TIGER feature class codeFUNCSTAT10 = Functional statusALAND10 = Land area in square metersAWATER10 = Water area in square metersINTPTLAT10 = Latitude of the centroid (center of this geography)INTPLON10 = Longitude of the centroid (center of this geography)STFID = The entire FIPS code of this geographyCOUNTY_NM = County namePLNG_REGIO = Planning regionSUMLEV = Summary level of census geography (code)STATE = The state FIPS codeCOUNTY = The county FIPS codeTRACT = The tract FIPS codeBLKGRP = The block group FIPS codetotpop10 = Total populationoner_10 = One race populationwhite_or10 = White, one race populationbl_or10 = Black, one race populationaian_or10 = American Indian and Alaska Native, one race populationasia_or10 = Asian, one race populationnhpi_or10 = Native Hawaiian and Other Pacific Islander, one race populationsomoth_or1 = Some other, one race populationtwoplusr10 = Two-plus races populationtotpop101 = Total populationhisp_lat10 = Total Hispanic/Latino populationnonhisp10 = Total non-Hispanic/Latino populationnh_or10 = Non-Hispanic/Latino, one race populationnhw_or10 = Non-Hispanic/Latino White, one race populationnhbl_or10 = Non-Hispanic/Latino Black, one race populationnhai_or10 = Non-Hispanic/Latino American Indian and Alaskan Native, one race populationnhas_or10 = Non-Hispanic/Latino Asian, one race populationnhhp_or10 = Non-Hispanic/Latino Native Hawaiian and Other Pacific Islander, one race populationnhot_or10 = Non-Hispanic/Latino Other, one race populationnh_twor10 = Non-Hispanic/Latino, two or more races populationtothu10 = Total housing unitstotoccu_10 = Total occupied housing unitstotvach_10 = Total vacant housing unitsAcresLand = Land area in acresAcresWater = Water area in acresAcresTotal = Total area in acresSq_Miles = Total area in square milesShape.STArea() = Total area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2010For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

This statistic shows the states with the highest wheat production in the United States in 2023 and 2024. North Dakota was ranked as the first leading wheat production state with about 367.7 million bushels produced in 2024 and just under 307 million bushels in 2023. Wheat production Wheat is the second most important grain that is cultivated in the United States, following only corn. Wheat is a cereal crop that can be classified into five major classes. These five wheat classes include hard red winter, hard red spring, soft red winter, white, and durum wheat. Each class has a different end-use and the cultivation tends to be region-specific. Hard red winter wheat is mainly grown in the Great Plains area ranging from Montana to Texas. This type is primarily used for the production of bread flour. Hard red spring wheat is mostly cultivated in the Northern Plains area. Their wheat ears are mainly taken for protein blending purposes. Durum wheat, which is primarily grown in North Dakota and Montana, is known for their excellent qualities for producing pasta. The wheat class everyone knows from their breakfast cereal is named white wheat. Almost every U.S. state is involved in agricultural wheat production. The latest statistics show that North Dakota, Kansas and Montana were the leading wheat producing states among the United States.

Many sports are played in the United States, either as hobbies or professional careers. During a 2019 survey, 38 percent of white respondents stated that their favorite sport was American football, while 23 percent had no favorite sport at all.

Lynching in the United States is estimated to have claimed over 4.7 thousand lives between 1882 and 1968, and just under 3.5 thousand of these victims were black. Today, lynching is more commonly associated with racial oppression, particularly in the south, however, in early years, victims were more commonly white (specifically Mexican), and lynchings were more frequent in western territories and along the southern border. It was only after Reconstruction's end where the lynching of black people became more prevalent, and was arguably the most violent tool of oppression used by white supremacists. Nationwide, the share of the population who was black fluctuated between 10 and 13 percent in the years shown here, however the share of lynching victims who were black was almost 73 percent. North-south divide Of the 4.7 thousand victims of lynching between 1882 and 1968, over 3.5 thousand of these were killed in former-Confederate states. Of the fourteen states where the highest number of lynching victims were killed, eleven were former-Confederate states, and all saw the deaths of at least one hundred people due to lynching. Mississippi was the state where most people were lynched in these years, with an estimated 581 victims, 93 percent of whom were black. Georgia saw the second most lynchings, with 531 in total, and the share of black victims was also 93 percent. Compared to the nationwide average of 73 percent, the share of black victims in former-Confederate states was 86 percent. Texas was the only former-Confederate state where this share (71 percent) was below the national average, due to the large number of Mexicans who were lynched there. Outside of the south Of the non-Confederate state with the highest number of lynching victims, most either bordered the former-Confederate states, or were to the west. Generally speaking, the share of white victims in these states was often higher than in the south, meaning that the majority took place in the earlier years represented here; something often attributed to the lack of an established judiciary system in rural regions, and the demand for a speedy resolution. However, there are many reports of black people being lynched in the former border states in the early-20th century, as they made their way northward during the Great Migration. Between 1882 and 1968, lynchings were rare in the Northeast, although Connecticut, Massachusetts, New Hampshire and Rhode Island were the only states** without any recorded lynchings in these years.

In 2024, more than ** percent of people employed in the motion picture and video industries in the United States identified as white. About one out of ten employees identified as Black or African American. That same year, almost ********** of employees in the U.S. film industry were male.

Despite comprising of a smaller share of the U.S. population than African Americans or Hispanics, the most represented non-white U.S. CEOs were of an Asian background. They made up 55 percent of CEO positions at Fortune 500 and S&P 500 companies in 2024. By comparison, 11 percent of CEOs at the time were African American. The rise of environmental, social, and corporate governance (ESG) Investments in ESG have risen dramatically over last few years. In November 2023 there were approximately 480 billion U.S. dollars in ESG ETF assets worldwide, compared to 16 billion U.S. dollars in 2015. ESG measures were put in place to encourage companies to act responsibly, with the leading reason for ESG investing stated to be brand and reputation according to managers and asset owners. Gender diversity With the general acceptance of ESG in larger companies, there has still been a significant employment gap of women working in senior positions. For example, the share of women working as a partner or principal at EY, one of the largest accounting firms in the world, was just only 28 percent in 2023.

In 2023, about 26.9 percent of Asian private households in the U.S. had an annual income of 200,000 U.S. dollars and more. Comparatively, around 13.9 percent of Black households had an annual income under 15,000 U.S. dollars.

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 California in 2022, 20.5 percent of students enrolled in K-12 public schools were white, 11.9 percent were Asian, and 56.2 percent were Hispanic. In the United States overall, 44.7 percent of K-12 public school students were white, 5.5 percent were Asian, and 28.7 percent were Hispanic.