The percent chance that two people picked at random within an area will be of a different race/ethnicity. This number does not reflect which race/ethnicity is predominant within an area. The higher the value, the more racially and ethnically diverse an area. Source: U.S. Bureau of the Census, American Community Survey Years Available: 2010, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2017-2021, 2018-2022, 2019-2023Please note: We do not recommend comparing overlapping years of data due to the nature of this dataset. For more information, please visit: https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data.html

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study examined differences in youth's mental health and substance abuse needs in seven different racial/ethnic groups of justice-involved youth. Using de-identified data from the Survey of Youth in Residential Placement (SYRP), it was assessed whether differences in mental health and substance abuse needs and services existed in a racially/ethnically diverse sample of youth in custody. Data came from a nationally representative sample of 7,073 youth in residential placements across 36 states, representing five program types. An examination of the extent to which there were racial/ethnic disparities in the delivery of services in relation to need was also conducted. This examination included assessing the differences in substance-related problems, availability of substance services, and receipt of substance-specific counseling. One SAS data file (syrp2017.sas7bdat) is included as part of this collection and has 138 variables for 7073 cases, with demographic variables on youth age, sex, race and ethnicity. Also included as part of the data collection are two SAS Program (syntax) files for use in secondary analysis of youth mental health and substance use.

This record contains the underlying research data for the publication "People in more racially diverse neighborhoods are more prosocial" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5359Five studies tested the hypothesis that people living in more diverse neighborhoods would have more inclusive identities, and would thus be more prosocial. Study 1 found that people residing in more racially diverse metropolitan areas were more likely to tweet prosocial concepts in their everyday lives. Study 2 found that following the 2013 Boston Marathon bombings, people in more racially diverse neighborhoods were more likely to spontaneously offer help to individuals stranded by the bombings. Study 3 found that people living in more ethnically diverse countries were more likely to report having helped a stranger in the past month. Providing evidence of the underlying mechanism, Study 4 found that people living in more racially diverse neighborhoods were more likely to identify with all of humanity, which explained their greater likelihood of having helped a stranger in the past month. Finally, providing causal evidence for the relationship between neighborhood diversity and prosociality, Study 5 found that people asked to imagine that they were living in a more racially diverse neighborhood were more willing to help others in need, and this effect was mediated by a broader identity. The studies identify a novel mechanism through which exposure to diversity can influence people, and document a novel consequence of this mechanism.

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 2024, as in 2023, approximately 12 percent of Fortune 500 companies' chief marketing officers (CMOs) in the United States belonged to historically underrepresented racial or ethnic groups. In 2022, the share stood at 14 percent. Meanwhile, the percentage of women among Fortune 500 CMOs in the U.S. increased.

This national, tract-level experienced racial segregation dataset uses data for over 66 million anonymized and opted-in devices in Cuebiq’s Spectus Clean Room data to estimate 15 minute time overlaps of device stays in 38.2m x 19.1m grids across the United States in 2022. We infer a probability distribution of racial backgrounds for each device given their home Census block groups at the time of data collection, and calculate the probability of a diverse social contact during that space and time. These measures are then aggregated to the Census tract and across the whole time period in order to preserve privacy and develop a generalizable measure of the diversity of a place. We propose that this dataset is a better measurement of the segregation and diversity as it is experienced, which we show diverges from standard measurements of segregation. The data can be used by researchers to better understand the determinants of experienced segregation; beyond research, we suggest this data can be used by policy makers to understand the impacts of policies designed to encourage social mixing and access to opportunities such as affordable housing and mixed-income housing, and more.

For the purposes of enhanced privacy, home census block groups were pre-calculated by the data provider, and all calculations are done at the Census tract, with tracts that have more than 20 unique devices over the period of analysis.

The U.S. has more immigrants than at any time since the 1920s and immigration rates remain high. Past research unequivocally predicts that the resulting increase in ethnic and racial diversity will reduce local investments in public goods. By analyzing a new, comprehensive data set on U.S. cities from 1950 to 2002, this paper challenges those predictions. In the 1950s and early 1960s, the percent black had no strong impacts on local public goods. Since the 1970s, the impact of diversity has been limited chiefly to criminal justice, an issue that has remained racially coded, nationally salient, and relevant to localities. Contrary to past work, diversity’s influence on local public goods is neither pervasive nor consistent. These findings challenge static conceptions of local ethnic and racial divisions, and they suggest a connection between diversity’s local impacts and trends in national politics.

In 2023, half of Generation Z in the United States were white. In comparison, 48 percent of Gen Alpha were white in that year, making it the first generation that does not have a majority white population in the United States.

The statistic shows public opinion on TV shows being more or less racially diverse compared to five years ago in the United States as of August 2017, sorted by ethnicity. During the survey, 40 percent of white respondents believed that TV shows are somewhat more racially diverse compared to five years ago.

IntroductionDementia is characterized by significant declines in cognitive, physical, social, and behavioral functioning, and includes multiple subtypes that differ in etiology. There is limited evidence of the influence of psychiatric and substance use history on the risk of dementia subtypes among older underrepresented racial/ethnic minorities in the United States. Our study explored the role of psychiatric and substance use history on the risk of etiology-specific dementias: Alzheimer’s disease (AD) and vascular dementia (VaD), in the context of a racially and ethnically diverse sample based on national data.MethodsWe conducted secondary data analyses based on the National Alzheimer’s Coordinating Center Uniform Data Set (N = 17,592) which is comprised a large, racially, and ethnically diverse cohort of adult research participants in the network of US Alzheimer Disease Research Centers (ADRCs). From 2005 to 2019, participants were assessed for history of five psychiatric and substance use disorders (depression, traumatic brain injury, other psychiatric disorders, alcohol use, and other substance use). Cox proportional hazard models were used to examine the influence of psychiatric and substance use history on the risk of AD and VaD subtypes, and the interactions between psychiatric and substance use history and race/ethnicity with adjustment for demographic and health-related factors.ResultsIn addition to other substance use, having any one type of psychiatric and substance use history increased the risk of developing AD by 22–51% and VaD by 22–53%. The risk of other psychiatric disorders on AD and VaD risk varied by race/ethnicity. For non-Hispanic White people, history of other psychiatric disorders increased AD risk by 27%, and VaD risk by 116%. For African Americans, AD risk increased by 28% and VaD risk increased by 108% when other psychiatric disorder history was present.ConclusionThe findings indicate that having psychiatric and substance use history increases the risk of developing AD and VaD in later life. Preventing the onset and recurrence of such disorders may prevent or delay the onset of AD and VaD dementia subtypes. Prevention efforts should pay particular attention to non-Hispanic White and African American older adults who have history of other psychiatric disorders.Future research should address diagnostic shortcomings in the measurement of such disorders in ADRCs, especially with regard to diverse racial and ethnic groups.

The diversity index measures the likelihood of two randomly selected people belonging to different racial and ethnic groups. A score of 0 represents that everyone in that area shares the same racial and ethnic background. A score nearing 100 represents that almost everyone of the population in that area has different racial and ethnic backgrounds.1The following racial and ethnic groups were used to calculate the diversity index:2American Indian and Alaska Native (AIAN)Asian/Asian AmericanBlack/African AmericanHispanic/Latina/o/xNative Hawaiian and Other Pacific Islander (NHPI)WhiteMultiracialOf Another Race

According to recent research, racial and ethnic diversity reduces U.S. localities' investment in public goods. Yet we remain unsure about the mechanisms behind that relationship, and uncertain that the relationship is causal. This essay addresses these challenges by studying the impact of racial and ethnic demographics on property tax votes in Massachusetts and Texas. Employing novel time-series cross-sectional data, it departs from the emerging consensus by showing that diversity does not always influence local tax votes. Instead, diversity reduces localities' willingness to raise taxes only when localities are undergoing sudden demographic changes. Theoretically, this finding points us away from the dominant understanding of diversity as divergent preferences, and towards approaches that emphasize how sudden demographic changes can destabilize residents' expectations and influence local elites. To understand how diversity influences public good provision, we should look to those towns that are diversifying, not those towns that are diverse.

This memo documents the data files and analysis files used to generate the estimates found in “Understanding Racial/Ethnic Diversity Gaps Among Early Career Teachers.” The abstract for the paper is found below:The growing evidence on the importance of teacher representation points to the need to better understand the factors shaping the lack of racial/ethnic diversity in the teacher workforce. In this study, we examine the extent to which college major choice explains racial/ethnic gaps in teaching. Drawing on data from the Baccalaureate and Beyond Longitudinal Study, we find that White college graduates are close to twice as likely to major in education compared to Black, Latinx, and other graduates of color. Even among college graduates, respondents who identify as White are 5 percentage points more likely to enter teaching than respondents who identify as Black and 2 percentage points more likely to enter teaching than graduates who identify as Latinx. Regression and decomposition analyses demonstrate that the observed racial/ethnic gaps in entry to teaching can largely be explained by whether a graduate studied education in college.

About this dataset

Context

The dataset presents the median household income across different racial categories in Salt Lake City. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Salt Lake City population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 72.47% of the total residents in Salt Lake City. Notably, the median household income for White households is $79,512. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $79,512.

https://i.neilsberg.com/ch/salt-lake-city-ut-median-household-income-by-race.jpeg" alt="Salt Lake City median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

Racial categories include:

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

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Salt Lake City.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Salt Lake City median household income by race. You can refer the same here

Background: There is an incomplete understanding of disparities in emergency care for children across racial and ethnic groups in the United States. In this project, we sought to investigate patterns in emergency care utilization, disposition, and resource use in children by race and ethnicity after adjusting for demographic, socioeconomic, and clinical factors.Methods: In this cross-sectional study of emergency department (ED) data from the nationally representative National Hospital Ambulatory Medical Survey (NHAMCS), we examined multiple dimensions of ED care and treatment from 2005 to 2016 among children in the United States. The main outcomes include ED disposition (hospital admission, ICU admission, and in hospital death), resources utilization (medical imaging use, blood tests, and procedure use) and patient ED waiting times and total length of ED stay. The main exposure variable is race/ethnicity, categorized as non-Hispanic white (white), non-Hispanic black (Black), Hispanic, Asian, and Other. Analyses were stratified by race/ethnicity and adjusted for demographic, socioeconomic, and clinical factors.Results: There were 78,471 pediatric (≤18 years old) ED encounters, providing a weighted sample of 333,169,620 ED visits eligible for analysis. Black and Hispanic pediatric patients were 8% less likely (aOR 0.92, 95% CI 0.91–0.92) and 14% less likely (aOR 0.86, CI 0.86–0.86), respectively, than whites to have their care needs classified as immediate/emergent. Blacks and Hispanics were also 28 and 3% less likely, respectively, than whites to be admitted to the hospital following an ED visit (aOR 0.72, CI 0.72–0.72; aOR 0.97, CI 0.97–0.97). Blacks and Hispanics also experienced significantly longer wait times and overall visits as compared to whites.Conclusions: Black and Hispanic children faced disparities in emergency care across multiple dimensions of emergency care when compared to non-Hispanic white children, while Asian children did not demonstrate such patterns. Further research is needed to understand the underlying causes and long-term health consequences of these divergent patterns of racial disparities in ED care within an increasingly racially diverse cohort of younger Americans.

This map shows the diversity index of the population in the USA in 2010 by block group. "The diversity index summarizes racial and ethnic diversity. The index shows the likelihood that two people, chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity). For example, a diversity index of 59 means there is a 59 percent probability that two people randomly chosen would belong to different race or ethnic groups." -Esri DemographicsIt calls to the 2010 Census service with attributes related to race and ethnicity. The field PctNonWhite calculates the total percentage of non-white population by subtracting the Total white population from the reported population total. This yields the total non-white population (Field "TotNonWhite"). This number was then divided by the total reported population and multipled by 100 to yield a percetage of the population that is non-white (Field "PctNonWhite"). Original data sourced from: https://tpc.maps.arcgis.com/home/item.html?id=04a8fbbf59aa48ebbc646ba2bc8d9b1c

This map service summarizes racial and ethnic diversity in the United States in 2012.

The Diversity Index shows the likelihood that two persons chosen at random from the same area, belong to different race or ethnic groups. The index ranges from 0 (no diversity) to 100 (complete diversity). Diversity in the U.S. population is increasing. The diversity score for the entire United States in 2012 is 61.

The data shown is from Esri's 2012 Updated Demographics. The map adds increasing level of detail as you zoom in, from state, to county, to ZIP Code, to tract, to block group data. This map shows Esri's 2012 estimates using Census 2010 geographies.

About this dataset

Context

The dataset tabulates the Bath population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Bath.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Bath, ME Population Breakdown by Race
• Bath, ME Non-Hispanic Population Breakdown by Race
• Bath, ME Hispanic or Latino Population Distribution by Their Ancestries

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/.

In 2021, the distribution by race and ethnicity reveals how diverse family caregivers are in the United States. That year, nearly two-thirds of family caregivers in the United States were white. However, with a 17 percent share in 2021, the second-most common race and ethnicity of family caregivers was Hispanic, followed by Black/African American.

About this dataset

Context

The dataset presents the median household income across different racial categories in Savannah. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Savannah population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 52.35% of the total residents in Savannah. Notably, the median household income for Black or African American households is $43,499. Interestingly, despite the Black or African American population being the most populous, it is worth noting that White households actually reports the highest median household income, with a median income of $71,602. This reveals that, while Black or African Americans may be the most numerous in Savannah, White households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/savannah-ga-median-household-income-by-race.jpeg" alt="Savannah median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates.

Racial categories include:

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

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Savannah.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Savannah median household income by race. You can refer the same here