This statistics shows the leading metropolitan areas in the United States in 2023 with the highest percentage of Asian population. Among the 81 largest metropolitan areas, Urban Honolulu, Hawaii was ranked first with **** percent of residents reporting as Asian in 2023.

About this dataset

Context

This list ranks the 269 cities in the South Carolina by Non-Hispanic Asian 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 Non-Hispanic Asian Population: This column displays the rank of cities in the South Carolina by their Non-Hispanic Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Non-Hispanic Asian Population: The Non-Hispanic Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total South Carolina Non-Hispanic Asian Population: This tells us how much of the entire South Carolina Non-Hispanic Asian 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/.

The U.S. Census defines Asian Americans as individuals having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent (U.S. Office of Management and Budget, 1997). As a broad racial category, Asian Americans are the fastest-growing minority group in the United States (U.S. Census Bureau, 2012). The growth rate of 42.9% in Asian Americans between 2000 and 2010 is phenomenal given that the corresponding figure for the U.S. total population is only 9.3% (see Figure 1). Currently, Asian Americans make up 5.6% of the total U.S. population and are projected to reach 10% by 2050. It is particularly notable that Asians have recently overtaken Hispanics as the largest group of new immigrants to the U.S. (Pew Research Center, 2015). The rapid growth rate and unique challenges as a new immigrant group call for a better understanding of the social and health needs of the Asian American population.

About this dataset

Context

This list ranks the 64 counties in the South Dakota by Non-Hispanic Asian 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 Non-Hispanic Asian Population: This column displays the rank of counties in the South Dakota by their Non-Hispanic Asian population, using the most recent ACS data available.
• counties: The counties for which the rank is shown in the previous column.
• Non-Hispanic Asian Population: The Non-Hispanic Asian population of the counties is shown in this column.
• % of Total counties Population: This shows what percentage of the total counties population identifies as Non-Hispanic Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total South Dakota Non-Hispanic Asian Population: This tells us how much of the entire South Dakota Non-Hispanic Asian 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/.

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

This list ranks the 46 counties in the South Carolina by Hispanic Asian 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 Asian Population: This column displays the rank of counties in the South Carolina by their Hispanic Asian population, using the most recent ACS data available.
• counties: The counties for which the rank is shown in the previous column.
• Hispanic Asian Population: The Hispanic Asian 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 Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total South Carolina Hispanic Asian Population: This tells us how much of the entire South Carolina Hispanic Asian 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/.

The US Census Bureau defines Asian as "A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. This includes people who reported detailed Asian responses such as: Indian, Bangladeshi, Bhutanese, Burmese, Cambodian, Chinese, Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian specified, Other Asian not specified.". 2020 Census block groups for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted from the 2020 State of Kansas Census Block Group shapefile provided by the State of Kansas GIS Data Access and Support Center (https://www.kansasgis.org/index.cfm).Change in Population and Housing for the Sedgwick County area from 2010 - 2020 based upon US Census. Census Blocks from 2010 were spatially joined to Census Block Groups from 2020 to compare the population and housing figures. This is not a product of the US Census Bureau and is only available through City of Wichita GIS. Please refer to Census Block Groups for 2010 and 2020 for verification of all data Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number. For example, blocks 3001, 3002, 3003… 3999 in census tract 1210.02 belong to Block Group 3. Due to boundary and feature changes that occur throughout the decade, current block groups do not always maintain these same block number to block group relationships. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the identification string (GEOID20) for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block identification strings are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain between 600 and 3,000 people. Local participants delineated most block groups as part of the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains at least one block group and block groups are uniquely numbered within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.Block groups have a valid range of 0 through 9. Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

Asian Indians were the first South Asians to immigrate to the United States in the late 1800s and are currently the largest ethnic group of South Asians living in the United States. Despite this the literature on perceived ethnic and racial discrimination experiences among this group is relatively understudied. The documented experiences of Asian Indians who either recently immigrated from India or were born and raised in America pose an important question: what are the experiences of perceived discrimination among Asian Indians living in America, particularly among younger populations who are continuing to develop their racial and ethnic identities? The current study utilized phenomenological methodology to explore the experiences of nine Asian Indian American adolescents' (ages 12–17 years). Data were collected via semi-structured interviews to assess participants' experiences of ethnic and racial discrimination and identity development. Thematic analysis was used to identify themes and subthemes among the participants' responses. Asian Indian adolescents living in the United States report experiencing discrimination at a young age. It is also evident that Asian Indian youth experience significant challenges when developing their sense of ethnic and racial identity while living within the United States. Findings document the racial and ethnic discrimination that Asian Indian adolescents living in the United States may experience from a young age. Importantly, these discrimination experiences are occurring as Asian Indian adolescents are developing their racial and ethnic identities. This study provides insight for future research, which is necessary to fully understand the experiences of Asian Indian adolescents.

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

About this dataset

Context

This list ranks the 307 cities in the South Dakota by Hispanic Asian 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 Hispanic Asian Population: This column displays the rank of cities in the South Dakota by their Hispanic Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Hispanic Asian Population: The Hispanic Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total South Dakota Hispanic Asian Population: This tells us how much of the entire South Dakota Hispanic Asian 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/.

South Asian Americans are part of the fastest growing racial/ethnic group in the United States and make up a substantial portion of the U.S. immigrant population. Research on this group has often focused on acculturation, the adoption of different values and behaviors in a new sociocultural environment. While there is evidence to suggest that acculturation (and the stress associated with this process) has a negative effect on the health and well-being of Asian Americans, more recent research has emphasized the need to examine the role of broader social forces—including everyday racism—in impacting mental health. Drawing on the stress process model, this study uses an original survey instrument to investigate the relationships between acculturative stress, anti-Asian racism, and mental health among a community sample of 200 South Asians in Texas. Results from hierarchical multiple regression models indicate that both acculturative stress and everyday racism are strongly linked to higher levels of anxiety-related symptoms and more frequent depressive symptoms. Everyday racism, however, explained variance in these outcomes, well beyond the effect of acculturative stress and other sociodemographic factors. These results underscore the potential benefit and importance of including questions about racism in community health surveys that aim to study health disparities among Asian Americans and highlight the persistence of social issues that U.S. South Asians face.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

The footnotes in the table are represented in brackets. The first footnote does not appear in the table.Footnotes: 1 For the 2011 National Household Survey (NHS) estimates, the global non-response rate (GNR) is used as an indicator of data quality. This indicator combines complete non-response (household) and partial non-response (question) into a single rate. The value of the GNR is presented to users. A smaller GNR indicates a lower risk of non-response bias and as a result, lower risk of inaccuracy. The threshold used for estimates' suppression is a GNR of 50% or more. For more information, please refer to the National Household Survey User Guide, 2011.2 The category 'Total - Single and multiple ethnic origin responses' indicates the number of respondents who reported a specified ethnic origin, either as their only ethnic origin or in addition to one or more other ethnic origins. The sum of all total responses for all ethnic origins is greater than the total population estimate due to the reporting of multiple origins.3 A single ethnic origin response occurs when a respondent provides one ethnic origin only.4 A multiple ethnic origin response occurs when a respondent provides two or more ethnic origins.5 This is a total population estimate. The sum of the ethnic groups in this table is greater than the total population estimate because a person may report more than one ethnic origin in the NHS.6 Includes general responses indicating North American origins (e.g., 'North American') as well as more specific responses indicating North American origins that have not been included elsewhere (e.g., 'Maritimer,' 'Manitoban').7 Includes general responses indicating British Isles origins (e.g., 'British,' 'United Kingdom') as well as more specific responses indicating British Isles origins that have not been included elsewhere (e.g., 'Celtic').8 Includes general responses indicating Western European origins (e.g., 'Western European') as well as more specific responses indicating Western European origins that have not been included elsewhere (e.g., 'Liechtensteiner').9 Includes general responses indicating Northern European origins (e.g., 'Northern European') as well as more specific responses indicating Northern European origins that have not been included elsewhere (e.g., 'Faroese,' 'Scandinavian').10 Includes general responses indicating Eastern European origins (e.g., 'Eastern European') as well as more specific responses indicating Eastern European origins that have not been included elsewhere (e.g., 'Baltic').11 Includes general responses indicating Southern European origins (e.g., 'Southern European') as well as more specific responses indicating Southern European origins that have not been included elsewhere (e.g., 'Gibraltarian').12 Includes general responses indicating Other European origins (e.g., 'European') as well as more specific responses indicating European origins that have not been included elsewhere (e.g., 'Central European').13 Includes general responses indicating Caribbean origins (e.g., 'Caribbean') as well as more specific responses indicating Caribbean origins that have not been included elsewhere (e.g., 'Guadelupian,' 'Aruban').14 Includes general responses indicating Latin, Central or South American origins (e.g., 'South American') as well as more specific responses indicating Latin, Central or South American origins that have not been included elsewhere (e.g., 'Surinamese').15 Includes general responses indicating Central or West African origins (e.g., 'West African') as well as more specific responses indicating Central or West African origins that have not been included elsewhere (e.g., 'Ewe,' 'Wolof').16 Includes general responses indicating North African origins (e.g., 'North African') as well as more specific responses indicating North African origins that have not been included elsewhere (e.g., 'Maghreb').17 Includes general responses indicating Southern or East African origins (e.g., 'East African') as well as more specific responses indicating Southern or East African origins that have not been included elsewhere (e.g., 'Hutu,' 'Shona').18 Some respondents may choose to provide very specific ethnic origins in the National Household Survey (NHS), while other respondents may choose to give more general responses. This means that two respondents with the same ethnic ancestry could have different response patterns and thus could be counted as having different ethnic origins. For example, one respondent may report 'East Indian' ethnic origin while another respondent, with a similar ancestral background, may report 'Punjabi' or 'South Asian' origins; one respondent may report 'Black' while another, similar respondent, may report 'Ghanaian' or 'African.' As a result, ethnic origin data are very fluid, and counts for certain origins, such as 'East Indian' and 'Black,' may seem lower than initially expected. Users who wish to obtain broader response counts may wish to combine data for one or more ethnic origins together or use counts for ethnic categories such as 'South Asian origins' or 'African origins.' (Please note, however, that 'African origins' should not be considered equivalent to the 'Black' population group or visible minority status, as there are persons reporting African origins who report a population group or visible minority status other than 'Black.' Conversely, many people report a population group or visible minority status of 'Black' and do not report having 'African' origins. For information on population group and visible minority population in the 2011 NHS, refer to the appropriate definitions in this publication).19 Includes general responses indicating Other African origins (e.g., 'African') as well as more specific responses indicating Other African origins that have not been included elsewhere (e.g., 'Saharan').20 Includes general responses indicating West Asian, Central Asian and Middle Eastern origins (e.g., 'West Asian,' 'Middle Eastern') as well as more specific responses indicating West Asian, Central Asian and Middle Eastern origins that have not been included elsewhere (e.g., 'Baloch,' 'Circassian').21 Some respondents may choose to provide very specific ethnic origins in the National Household Survey (NHS), while other respondents may choose to give more general responses. This means that two respondents with the same ethnic ancestry could have different response patterns and thus could be counted as having different ethnic origins. For example, one respondent may report 'East Indian' ethnic origin while another respondent, with a similar ancestral background, may report 'Punjabi' or 'South Asian' origins; one respondent may report 'Black' while another, similar respondent, may report 'Ghanaian' or 'African.' As a result, ethnic origin data are very fluid, and counts for certain origins, such as 'East Indian' and 'Black,' may seem lower than initially expected. Users who wish to obtain broader response counts may wish to combine data for one or more ethnic origins together or use counts for ethnic categories such as 'South Asian origins' or 'African origins.' (Please note, however, that 'African origins' should not be considered equivalent to the 'Black' population group or visible minority status, as there are persons reporting African origins who report a population group or visible minority status other than 'Black.' Conversely, many people report a population group or visible minority status of 'Black' and do not report having 'African' origins. For information on population group and visible minority population in the 2011 NHS, refer to the appropriate definitions in this publication).22 Includes general responses indicating South Asian origins (e.g., 'South Asian') as well as more specific responses indicating South Asian origins that have not been included elsewhere (e.g., 'Bhutanese').23 Includes general responses indicating East and Southeast Asian origins (e.g., 'Southeast Asian') as well as more specific responses indicating East and Southeast Asian origins that have not been included elsewhere (e.g., 'Bruneian,' 'Karen').24 Includes general responses indicating Other Asian origins (e.g., 'Asian') as well as more specific responses indicating Other Asian origins that have not been included elsewhere (e.g., 'Eurasian').25 Includes general responses indicating Pacific Islands origins (e.g., 'Pacific Islander') as well as more specific responses indicating Pacific Islands origins that have not been included elsewhere (e.g., 'Tahitian').

This dataset includes six tables which were custom ordered from Statistics Canada. All tables include commuting characteristics (mode of commuting, duration/distance), labour characteristics (employment income groups in 2015, Industry by the North American Industry Classification System 2012), and visible minority groups. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Place of Work (POW), Census Tract (CT) within CMA Vancouver. The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. However, it will be provided upon request. GNR values for POR and POW are different for each geography. Universe: The Employed Labour Force having a usual place of work for the population aged 15 years and over in private households that are rented (Tenure rented), full year-full time workers (40-52weeks) Variables: Visible minority (15) 1. Total - Visible minority 2. Total visible minority population 3. South Asian 4. Chinese 5. Black 6. Filipino 7. Latin American 8. Arab 9. Southeast Asian 10. West Asian 11. Korean 12. Japanese 13. Visible minority, n.i.e. 14. Multiple visible minorities 15. Not a visible minority Commuting duration and distance (18) 1. Total - Commuting duration 2. Less than 15 minutes 3. 15 to 29 minutes 4. 30 to 44 minutes 5. 45 to 59 minutes 6. 60 minutes and over 7. Total - Commuting distance 8. Less than 1 km 9. 1 to 2.9 km 10. 3 to 4.9 km 11. 5 to 6.9 km 12. 7 to 9.9 km 13. 10 to 14.9 km 14. 15 to 19.9 km 15. 20 to 24.9 Km 16. 25 to 29.9 km 17. 30 to 34.9 km 18. 35 km or more Main mode of commuting (7) 1. Total - Main mode of commuting 2. Driver, alone 3. 2 or more persons shared the ride to work 4. Public transit 5. Walked 6. Bicycle 7. Other method Employment income groups in 2015 (39) 1. Total – Total Employment income groups in 2015 2. Without employment income 3. With employment income 4. Less than $30,000 (including loss) 5. $30,000 to $79,999 6. $30,000 to $39,999 7. $40,000 to $49,999 8. $50,000 to $59,999 9. $60,000 to $69,999 10. $70,000 to $79,999 11. $80,000 and above 12. Median employment income ($) 13. Average employment income ($) 14. Total – Male Employment income groups in 2015 15. Without employment income 16. With employment income 17. Less than $30,000 (including loss) 18. $30,000 to $79,999 19. $30,000 to $39,999 20. $40,000 to $49,999 21. $50,000 to $59,999 22. $60,000 to $69,999 23. $70,000 to $79,999 24. $80,000 and above 25. Median employment income ($) 26. Average employment income ($) 27. Total – Female Employment income groups in 2015 28. Without employment income 29. With employment income 30. Less than $30,000 (including loss) 31. $30,000 to $79,999 32. $30,000 to $39,999 33. $40,000 to $49,999 34. $50,000 to $59,999 35. $60,000 to $69,999 36. $70,000 to $79,999 37. $80,000 and above 38. Median employment income ($) 39. Average employment income ($) Industry - North American Industry Classification System (NAICS) 2012 (54) 1. Total - Industry - North American Industry Classification System (NAICS) 2012 2. 11 Agriculture, forestry, fishing and hunting 3. 21 Mining, quarrying, and oil and gas extraction 4. 22 Utilities 5. 23 Construction 6. 236 Construction of buildings 7. 237 Heavy and civil engineering construction 8. 238 Specialty trade contractors 9. 31-33 Manufacturing 10. 311 Food manufacturing 11. 41 Wholesale trade 12. 44-45 Retail trade 13. 441 Motor vehicle and parts dealers 14. 442 Furniture and home furnishings stores 15. 443 Electronics and appliance stores 16. 444 Building material and garden equipment and supplies dealers 17. 445 Food and beverage stores 18. 446 Health and personal care stores 19. 447 Gasoline stations 20. 448 Clothing and clothing accessories stores 21. 451 Sporting goods, hobby, book and music stores 22. 452 General merchandise stores 23. 453 Miscellaneous store retailers 24. 454 Non-store retailers 25. 48-49 Transportation and warehousing 26. 481 Air transportation 27. 482 Rail transportation 28. 483 Water...

Whereas the population is expected to decrease somewhat until 2100 in Asia, Europe, and South America, it is predicted to grow significantly in Africa. While there were 1.5 billion inhabitants on the continent at the beginning of 2024, the number of inhabitants is expected to reach 3.8 billion by 2100. In total, the global population is expected to reach nearly 10.4 billion by 2100. Worldwide population In the United States, the total population is expected to steadily increase over the next couple of years. In 2024, Asia held over half of the global population and is expected to have the highest number of people living in urban areas in 2050. Asia is home to the two most populous countries, India and China, both with a population of over one billion people. However, the small country of Monaco had the highest population density worldwide in 2021. Effects of overpopulation Alongside the growing worldwide population, there are negative effects of overpopulation. The increasing population puts a higher pressure on existing resources and contributes to pollution. As the population grows, the demand for food grows, which requires more water, which in turn takes away from the freshwater available. Concurrently, food needs to be transported through different mechanisms, which contributes to air pollution. Not every resource is renewable, meaning the world is using up limited resources that will eventually run out. Furthermore, more species will become extinct which harms the ecosystem and food chain. Overpopulation was considered to be one of the most important environmental issues worldwide in 2020.

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 statistic illustrates the share of people in the United States who traveled to South East Asia (e.g. Thailand, Malaysia) in the last 12 months as of 2018. The results were sorted by age. In 2018, **** percent of American respondents aged 18 to 29 years stated they made a trip to South East Asia in the last 12 months. The Statista Global Consumer Survey offers a global perspective on consumption and media usage, covering the offline und online world of the consumer.

The world's population first reached one billion people in 1805, and reached eight billion in 2022, and will peak at almost 10.2 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two-thirds of the world's population lives in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a few years later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

The issue of race and slavery was arguably the largest cause of the American Civil War, with the southern states seceding from the Union as the practice of slavery became increasingly threatened. From the graph we can see that roughly 16.5 percent of the entire US population at this time was black, and the vast majority of these were slaves. In 1860 there were almost 27 million white people, four and a half million black people, and less than one hundred thousand non-black or white people (mostly of Native/Latin American or East-Asian origin).

About this dataset

Context

This list ranks the 2 cities in the Southeast Fairbanks Census Area, AK by Hispanic Asian 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 Hispanic Asian Population: This column displays the rank of cities in the Southeast Fairbanks Census Area, AK by their Hispanic Asian population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Hispanic Asian Population: The Hispanic Asian population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Asian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Southeast Fairbanks Census Area Hispanic Asian Population: This tells us how much of the entire Southeast Fairbanks Census Area, AK Hispanic Asian 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/.