Knowing the racial and ethnic composition of a community is often one of the first steps in understanding, serving, and advocating for various groups. This information can help enforce laws, policies, and regulations against discrimination based on race and ethnicity. These statistics can also help tailor services to accommodate cultural differences.This multi-scale map shows the most common race/ethnicity living within an area. Map opens at tract-level in Los Angeles, CA but has national coverage. Zoom out to see counties and states.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available. The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.

ABSTRACTIn March 2024, the Office of Management and Budget updated guidelines for measuring race/ethnicity on federal forms in the United States (US). By March 2029, Middle Eastern and North African (MENA) Americans will have a new category. This population was previously included in the definition for the White race. It is unknown how this change will alter health estimates for other racial/ethnic groups, particularly among the aging population that has become increasingly diverse. Using cognitive difficulty as the health outcome of interest, our objectives were to 1) compare the prevalence of cognitive difficulty using 2020 and 2030 US Census racial/ethnic categories and 2) determine whether the odds of cognitive difficulty differs with and without a MENA checkbox. We used 2018-2022 American Community Survey data (ages >=65 years; n=3,351,611). We categorized race/ethnicity based on 2020 US Census categories (White, Black, AI/AN, Asian, NH/OPI, Some Other Race, Two or More Races, Hispanic/Latino) then created a separate category for older adults of MENA descent using questions on ancestry and place of birth to align with 2030 categories. Bivariate statistics and multivariable logistic regression models were calculated. Using 2020 categories, the odds of cognitive difficulty were higher among all racial/ethnic groups compared to Whites. Using 2030 categories, the odds of cognitive difficulty were 1.53 times greater (95%CI=1.43-1.62) among MENA compared to Whites. The odds of cognitive difficulty using 2020 and 2030 US Census racial/ethnic categories for other groups were not significantly different. Our results highlight the disparity in cognitive health among MENA and White older adults. Including a separate MENA checkbox on the ACS starting in 2027 is critical to provide baseline data and move forward discussions on health disparities among older adults.

A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco. The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person. The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons: • The person was not asked about their race and ethnicity. • The person was asked, but refused to answer. • The person answered, but the testing provider did not include the person's answers in the reports. • The testing provider reported the person's answers in a format that could not be used by the health department. For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.” B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown." The Race/Ethnicity categorization increases data clarity by emulating the methodology used by the U.S. Census in the American Community Survey. Specifically, persons who identify as "Asian," "Black or African American," "American Indian or Alaska Native," "Native Hawaiian or Other Pacific Islander," "White," "Multi-racial," or "Other" do NOT include any person who identified as Hispanic/Latino at any time in their testing reports that either (1) identified them as SF residents or (2) as someone who tested without a locating address by an SF provider. All persons across all races who identify as Hispanic/Latino are recorded as “"Hispanic or Latino/a, all races." This categorization increases data accuracy by correcting the way “Other” persons were counted. Previously, when a person reported “Other” for Race/Ethnicity, they would be recorded “Unknown.” Under the new categorization, they are counted as “Other” and are distinct from “Unknown.” If a person records their race/ethnicity as “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other” for their first COVID-19 test, then this data will not change—even if a different race/ethnicity is reported for this person for any future COVID-19 test. There are two exceptions to this rule. The first exception is if a person’s race/ethnicity value i

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of the 2017 Discrimination in the United States Survey, a survey from Harvard T.H. Chan School of Public Health/Robert Wood Johnson Foundation/National Public Radio conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include:Belief in discrimination against racial/ethnic minoritiesDiscrimination against men/womenDiscrimination against lesbian/gay/bisexual peopleDiscrimination against transgender peopleBiggest problem with discrimination against lesbian/gay/bisexual/transgender/queer (LGBTQ) peopleLive on tribal landsLocal/tribal government Discrimination based on raceDiscrimination based on genderDiscrimination based on being part of the LGBTQ communityReasons for avoiding seeking health careExperiences with discriminationDiscrimination resulting in fewer employment opportunitiesDiscrimination resulting in unequal payDiscrimination resulting in fewer chances for quality educationEncouraged to/discouraged from applying to collegePredominant groups living in respondent's areaNot feeling/being welcomed in neighborhood due to raceNot feeling/being welcomed in neighborhood due to being part of LGBTQ communityConsidered moving to another area because of discriminationComparing respondent's area to othersPolice using unnecessary force based on race/ethnicityAvoiding activities to avoid discrimination from policeExperiences caused by racial discriminationExperiences caused by gender discriminationExperiences caused by discrimination against LGBTQ communityLocal police force does/does not reflect racial/ethnic background of communityContacted by political representatives about voting/supporting causeRegistered to voteVote in 2016 presidential electionPhysical health statusMental health statusDisabilityChronic illnessVeterans AdministrationIndian Health ServicesSeeking health careInsurance coverageThe data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31114655]. Frequencies and summary statistics for the 235 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

About this dataset

Context

This list ranks the 4 cities in the Brown County, IL by Multi-Racial Some Other Race (SOR) 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 Multi-Racial Other Race Population: This column displays the rank of cities in the Brown County, IL by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Brown County Multi-Racial Other Race Population: This tells us how much of the entire Brown County, IL Multi-Racial Other Race 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/.

Written questionnaire completed by each subject prior to participating in the study. (0.03 MB PDF)

Note: As of March 2022, the race/ethnicity label changed from Native American to American Indian or Alaska Native to align with the Census.

Note: As of April 16, 2021, this dataset will update daily with a five-day data lag.

Note: As of February 2022, the way race/ethnicity is categorized has been changed. See Section B for additional information.

A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco.

The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person.

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. Each positive test result is investigated by the health department. While the city tries to only report on tests for San Francisco residents (or tests in San Francisco for those with no locating address listed), some test results purported to be for San Francisco residents are actually for people living outside the city. This can be discovered during a case investigation or data quality assurance. In such an instance, the test would be counted as a positive test in the SF data but would not be counted as a COVID-19 case in San Francisco. If a person tests positive for COVID-19 on different dates, they would be included each of those times in the testing data but only one case. To track the number of cases by race/ethnicity, see this dashboard: https://sf.gov/data/covid-19-population-characteristics#race-or-ethnicity-

When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons:

• The person was not asked about their race and ethnicity.
• The person was asked, but refused to answer.
• The person answered, but the testing provider did not include the person's answers in the reports.
• The testing provider reported the person's answers in a format that could not be used by the health department.

For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.”

B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown."

On February 10, 2022, the method for which race/ethnicity is categorized was updated for the sake of data accuracy, clarity, and stability. The new categorization increases data clarity by emulating the methodology used by the U.S. Census in the

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

IntroductionData on ethnic and racial differences in symptoms and health-related impacts following SARS-CoV-2 infection are limited. We aimed to estimate the ethnic and racial differences in symptoms and health-related impacts 3 and 6 months after the first SARS-CoV-2 infection.MethodsParticipants included adults with SARS-CoV-2 infection enrolled in a prospective multicenter US study between 12/11/2020 and 7/4/2022 as the primary cohort of interest, as well as a SARS-CoV-2-negative cohort to account for non-SARS-CoV-2-infection impacts, who completed enrollment and 3-month surveys (N = 3,161; 2,402 SARS-CoV-2-positive, 759 SARS-CoV-2-negative). Marginal odds ratios were estimated using GEE logistic regression for individual symptoms, health status, activity level, and missed work 3 and 6 months after COVID-19 illness, comparing each ethnicity or race to the referent group (non-Hispanic or white), adjusting for demographic factors, social determinants of health, substance use, pre-existing health conditions, SARS-CoV-2 infection status, COVID-19 vaccination status, and survey time point, with interactions between ethnicity or race and time point, ethnicity or race and SARS-CoV-2 infection status, and SARS-CoV-2 infection status and time point.ResultsFollowing SARS-CoV-2 infection, the majority of symptoms were similar over time between ethnic and racial groups. At 3 months, Hispanic participants were more likely than non-Hispanic participants to report fair/poor health (OR: 1.94; 95%CI: 1.36–2.78) and reduced activity (somewhat less, OR: 1.47; 95%CI: 1.06–2.02; much less, OR: 2.23; 95%CI: 1.38–3.61). At 6 months, differences by ethnicity were not present. At 3 months, Other/Multiple race participants were more likely than white participants to report fair/poor health (OR: 1.90; 95% CI: 1.25–2.88), reduced activity (somewhat less, OR: 1.72; 95%CI: 1.21–2.46; much less, OR: 2.08; 95%CI: 1.18–3.65). At 6 months, Asian participants were more likely than white participants to report fair/poor health (OR: 1.88; 95%CI: 1.13–3.12); Black participants reported more missed work (OR, 2.83; 95%CI: 1.60–5.00); and Other/Multiple race participants reported more fair/poor health (OR: 1.83; 95%CI: 1.10–3.05), reduced activity (somewhat less, OR: 1.60; 95%CI: 1.02–2.51; much less, OR: 2.49; 95%CI: 1.40–4.44), and more missed work (OR: 2.25; 95%CI: 1.27–3.98).DiscussionAwareness of ethnic and racial differences in outcomes following SARS-CoV-2 infection may inform clinical and public health efforts to advance health equity in long-term outcomes.

Survey completion by survey mode and self-reported race/ethnicity.

This layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B03002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Meta-analysis of surveys showing association between experience of racial discrimination (last 12 months) and health and wellbeing measures, stratified by ethnicity and adjusted for age, gender, nativity, NZDep, education qualification.

About this dataset

Context

This list ranks the 12 city in the Washita County, OK by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each city 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 Multi-Racial Other Race Population: This column displays the rank of city in the Washita County, OK by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• city: The city for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the city is shown in this column.
• % of Total city Population: This shows what percentage of the total city population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Washita County Multi-Racial Other Race Population: This tells us how much of the entire Washita County, OK Multi-Racial Other Race population lives in that city. 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/.

County-level race and ethnicity estimates for populations 25 years of age and over, cross-tabulated with educational attainment estimates for populations that have less than a high school diploma. Race and ethnicity estimates include the following categories: White alone, Black or African American alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, Some Other Race alone, Two or More Races, White alone and Not Hispanic or Latino, Hispanic or Latino, and people of color. Estimates are accompanied by margins of error, coefficients of variation, and percentages. Geometry source: 2020 Census. Attribute source: 2019-2023 American Community Survey 5-year estimates, tables B06009, C15002A, C15002B, C15002C, C15002D, C15002E, C15002F, C15002G, C15002H, and C15002I. Date of last data update: 2024-01-11 This is official RLIS data. Contact Person: Joe Gordon joe.gordon@oregonmetro.gov 503-797-1587 RLIS Metadata Viewer: https://gis.oregonmetro.gov/rlis-metadata/#/details/3846 RLIS Terms of Use: https://rlisdiscovery.oregonmetro.gov/pages/terms-of-use

About this dataset

Context

This list ranks the 6 cities in the Loudon County, TN by Multi-Racial Some Other Race (SOR) 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 Multi-Racial Other Race Population: This column displays the rank of cities in the Loudon County, TN by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Loudon County Multi-Racial Other Race Population: This tells us how much of the entire Loudon County, TN Multi-Racial Other Race 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 7 city in the Nuckolls County, NE by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each city 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 Multi-Racial Other Race Population: This column displays the rank of city in the Nuckolls County, NE by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• city: The city for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the city is shown in this column.
• % of Total city Population: This shows what percentage of the total city population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Nuckolls County Multi-Racial Other Race Population: This tells us how much of the entire Nuckolls County, NE Multi-Racial Other Race population lives in that city. 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 175 city in the Cook County, IL by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each city 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 Multi-Racial Other Race Population: This column displays the rank of city in the Cook County, IL by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• city: The city for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the city is shown in this column.
• % of Total city Population: This shows what percentage of the total city population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Cook County Multi-Racial Other Race Population: This tells us how much of the entire Cook County, IL Multi-Racial Other Race population lives in that city. 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 7 cities in the Hot Spring County, AR by Multi-Racial Some Other Race (SOR) 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 Multi-Racial Other Race Population: This column displays the rank of cities in the Hot Spring County, AR by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Hot Spring County Multi-Racial Other Race Population: This tells us how much of the entire Hot Spring County, AR Multi-Racial Other Race 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 9 city in the Knox County, OH by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each city 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 Multi-Racial Other Race Population: This column displays the rank of city in the Knox County, OH by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• city: The city for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the city is shown in this column.
• % of Total city Population: This shows what percentage of the total city population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Knox County Multi-Racial Other Race Population: This tells us how much of the entire Knox County, OH Multi-Racial Other Race population lives in that city. 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 31 city in the Pope County, MN by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each city 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 Multi-Racial Other Race Population: This column displays the rank of city in the Pope County, MN by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• city: The city for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the city is shown in this column.
• % of Total city Population: This shows what percentage of the total city population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Pope County Multi-Racial Other Race Population: This tells us how much of the entire Pope County, MN Multi-Racial Other Race population lives in that city. 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/.