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.

In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

The population of some areas in the United States is dominated heavily by one racial or ethnic group. These areas stand out on this map. In other areas, one group may be the majority, but the population is much more evenly balanced. Other areas have one group claiming a plurality, but not a majority.In each neighborhood, county, and state, this map shows which race or ethnicity is predominant, and by how much. It uses map colors to identify the predominant racial or ethnic group in specific areas by county and tract. The strength of the color indicates the extent to which one group is dominant over the next most populous.The data shown is from the U.S. Census Bureau's SF1 and TIGER data sets for 2010, and Esri. Concept and colors by Andrew Skinner.Original data sourced from: https://nation.maps.arcgis.com/apps/OnePane/splash/index.html?appid=602849530f5d4b6781ba37393144728c

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

This survey of minority groups was part of a larger project to investigate the patterns, predictors, and consequences of midlife development in the areas of physical health, psychological well-being, and social responsibility. Conducted in Chicago and New York City, the survey was designed to assess the well-being of middle-aged, urban, ethnic minority adults living in both hyper-segregated neighborhoods and in areas with lower concentrations of minorities. Respondents' views were sought on issues relevant to quality of life, including health, childhood and family background, religion, race and ethnicity, personal beliefs, work experiences, marital and close relationships, financial situation, children, community involvement, and neighborhood characteristics. Questions on health explored the respondents' physical and emotional well-being, past and future attitudes toward health, physical limitations, energy level and appetite, amount of time spent worrying about health, and physical reactions to those worries. Questions about childhood and family background elicited information on family structure, the role of the parents with regard to child rearing, parental education, employment status, and supervisory responsibilities at work, the family financial situation including experiences with the welfare system, relationships with siblings, and whether as a child the respondent slept in the same bed as a parent or adult relative. Questions on religion covered religious preference, whether it is good to explore different religious teachings, and the role of religion in daily decision-making. Questions about race and ethnicity investigated respondents' backgrounds and experiences as minorities, including whether respondents preferred to be with people of the same racial group, how important they thought it was to marry within one's racial or ethnic group, citizenship, reasons for moving to the United States and the challenges faced since their arrival, their native language, how they would rate the work ethic of certain ethnic groups, their views on race relations, and their experiences with discrimination. Questions on personal beliefs probed for respondents' satisfaction with life and confidence in their opinions. Respondents were asked whether they had control over changing their life or their personality, and what age they viewed as the ideal age. They also rated people in their late 20s in the areas of physical health, contribution to the welfare and well-being of others, marriage and close relationships, relationships with their children, work situation, and financial situation. Questions on work experiences covered respondents' employment status, employment history, future employment goals, number of hours worked weekly, number of nights away from home due to work, exposure to the risk of accident or injury, relationships with coworkers and supervisors, work-related stress, and experience with discrimination in the workplace. A series of questions was posed on marriage and close relationships, including marital status, quality and length of relationships, whether the respondent had control over his or her relationships, and spouse/partner's education, physical and mental health, employment status, and work schedule. Questions on finance explored respondents' financial situation, financial planning, household income, retirement plans, insurance coverage, and whether the household had enough money. Questions on children included the number of children in the household, quality of respondents' relationships with their children, prospects for their children's future, child care coverage, and whether respondents had changed their work schedules to accommodate a child's illness. Additional topics focused on children's identification with their culture, their relationships with friends of different backgrounds, and their experiences with racism. Community involvement was another area of investigation, with items on respondents' role in child-rearing, participation on a jury, voting behavior, involvement in charitable organizations, volunteer experiences, whether they made monetary or clothing donations, and experiences living in an institutional setting or being homeless. Respondents were also queried about their neighborhoods, with items on neighborhood problems including racism, vandalism, crime, drugs, poor schools, teenag

This multi-scale map shows the predominant (most numerous) race/ethnicity living within an area. Map opens at the state level, centered on the lower 48 states. Data is from U.S. Census Bureau's 2020 PL 94-171 data for state, county, tract, block group, and block.The map's colors indicate which of the eight race/ethnicity categories have the highest total count.Race and ethnicity highlights from the U.S. Census Bureau:White population remained the largest race or ethnicity group in the United States, with 204.3 million people identifying as White alone. Overall, 235.4 million people reported White alone or in combination with another group. However, the White alone population decreased by 8.6% since 2010.Two or More Races population (also referred to as the Multiracial population) has changed considerably since 2010. The Multiracial population was measured at 9 million people in 2010 and is now 33.8 million people in 2020, a 276% increase.“In combination” multiracial populations for all race groups accounted for most of the overall changes in each racial category.All of the race alone or in combination groups experienced increases. The Some Other Race alone or in combination group (49.9 million) increased 129%, surpassing the Black or African American population (46.9 million) as the second-largest race alone or in combination group.The next largest racial populations were the Asian alone or in combination group (24 million), the American Indian and Alaska Native alone or in combination group (9.7 million), and the Native Hawaiian and Other Pacific Islander alone or in combination group (1.6 million).Hispanic or Latino population, which includes people of any race, was 62.1 million in 2020. Hispanic or Latino population grew 23%, while the population that was not of Hispanic or Latino origin grew 4.3% since 2010.View more 2020 Census statistics highlights on race and ethnicity.

This data package consists of 26 datasets all containing statistical data relating to the population and particular groups within it belonging to different countries, mostly the United States.

About this dataset

Context

The dataset presents the median household income across different racial categories in Rich Square. 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 Rich Square population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 63.98% of the total residents in Rich Square. Notably, the median household income for Black or African American households is $34,031. Interestingly, Black or African American is both the largest group and the one with the highest median household income, which stands at $34,031.

https://i.neilsberg.com/ch/rich-square-nc-median-household-income-by-race.jpeg" alt="Rich Square 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) 2017-2021 5-Year Estimates.

Racial categories include:

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

Variables / Data Columns

• Race 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 Rich Square.
• 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 Rich Square median household income by race. You can refer the same here

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

This dataset contains information about the demographics of all US cities and census-designated places with a population greater or equal to 65,000. This data comes from the US Census Bureau's 2015 American Community Survey. This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.

Release Date: 2021-01-28.The Census Bureau has reviewed this data product for unauthorized disclosure of confidential information and has approved the disclosure avoidance practices applied (Approval ID: CBDRB-FY20-424)...Release Schedule:.Data in this file come from estimates of business ownership by sex, ethnicity, race, and veteran status from the 2019 Annual Business Survey (ABS) collection. Data are also obtained from administrative records, the 2017 Economic Census, and other economic surveys...Note: The collection year is the year in which the data are collected. A reference year is the year that is referenced in the questions on the survey and in which the statistics are tabulated. For example, the 2019 ABS collection year produces statistics for the 2018 reference year. The "Year" column in the table is the reference year...For more information about ABS planned data product releases, see Tentative ABS Schedule...Key Table Information:.This is the only table in the ABS series to provide information on select economic and demographic characteristics of business owners (CBO) for U.S. employer firms that reported the sex, ethnicity, race, and veteran status for up to four persons owning the largest percentage(s) of the business. The data include estimates for owners of U.S. respondent firms with paid employees operating during the reference year with receipts of $1,000 or more, which are classified in the North American Industry Classification System (NAICS), Sectors 11 through 99, except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered. Owners of employer firms with more than one domestic establishment are counted in each geographic area and industry in which the firm operates, but only once in the U.S. and state totals for all sectors. Firms are asked to report their employees as of the March 12 pay period...Data Items and Other Identifying Records:.Data include estimates on:.Number of owners of respondent employer firms. Percent of number of owners of respondent employer firms (%)...These data are aggregated at the owner level for up to four persons owning the largest percentages of the business by the following demographic classifications:.All owners of respondent firms. Sex. Female. Male. . . Ethnicity. Hispanic. Non-Hispanic. . . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Nonminority (Firms classified as non-Hispanic and White). . . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Nonveteran. . . ...Data Notes:.. Data are tabulated at the owner level.. Respondents are informed that Hispanic origins are not races and are instructed to answer both the Hispanic origin and race questions.. An owner can be tabulated in more than one racial group. This can result because:. The sole owner was reported to be of more than one race.. The majority owner was reported to be of more than one race.. A majority combination of owners was reported to be of more than one race.. . An owner cannot be tabulated with two mutually exclusive demographic classifications (e.g. both as a veteran and a nonveteran.). CBO data are not designed to produce estimates for all U.S. business owners as information was only collected for up to four owners per firm. Researchers analyzing data to create their own estimates are responsible for the validity of those estimates and should cite the Census Bureau as the source of the original data only....Owner Characteristics:.The ABS asked for information for up to four persons owning the largest percentage(s) of the business. Respondent firms include all firms that responded to the characteristics tabulated in this dataset and that reported sex, ethnicity, race, or veteran status for at least one business owner so that the classification of owners of respondent firms by sex, ethnicity, race, and veteran status could be determined. Furthermore, the ABS was designed to include select questions about owner characteristics from multiple reference periods and to incorporate new content each survey year based on topics of relevance. Percentages are for owners of respondent firms only and are not recalculated when the dataset is resorted. Percentages are always based on total reporting (defined above) within a sex, ethnicity, race, veteran status, and/or industry group for the characteristics tabulated in this dataset...To see the specific survey questions for which estimates are provided in this table, visit the following:... Owner Characteristics collected on the 2019 Annual Business Survey...Industry and Geography Cover...

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.

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

we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI).American Community Survey (ACS):Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themesEach tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively. In our utilization of these sources, we likely integrated data from both the ACS and the SVI to analyze and understand various socio-economic and demographic indicators at the state, county, and possibly tract levels. This integrated data would have been valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United StatesNote: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2015-2019 ACSEP_PCIEP_PCIPer capita income estimate, 2015-2019 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2015-2019 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2015-2019 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2015-2019 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2015-2019 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computerThis table provides a mapping between the CSV variable names and the shapefile variable names, along with a brief description of each variable.

Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at both the tract and county levels, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsPolicy Development: Helps policymakers develop targeted interventions to address the needs of vulnerable populations.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability.Research: Provides a robust foundation for academic and applied research in socio-economic and demographic studies.Community Planning: Aids in the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities.Note: Due to limitations in the ArcGIS Pro environment, the data variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2013-2017 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2013-2017 ACSEP_PCIEP_PCIPer capita income estimate, 2013-2017 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2013-2017 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2013-2017 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2013-2017 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2013-2017 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2013-2017 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

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

In 2024, the racial group with the largest representation in accounting services in the United States were Hispanic where almost ** percent of the total workforce was represented. African Americans represented ***** percent of those working in accounting services in the United States.

How racially diverse are residents in Massachusetts? This topic shows the demographic breakdown of residents by race/ethnicity and the increases in the Non-white population since 2010.

The coronavirus disease (COVID-19) has revealed existing health inequalities in racial and ethnic minority groups in the US. This work investigates and quantifies the non-uniform effects of geographical location and other known risk factors on various ethnic groups during the COVID-19 pandemic at a national level. To quantify the geographical impact on various ethnic groups, we grouped all the states of the US. into four different regions (Northeast, Midwest, South, and West) and considered Non-Hispanic White (NHW), Non-Hispanic Black (NHB), Hispanic, Non-Hispanic Asian (NHA) as ethnic groups of our interest. Our analysis showed that infection and mortality among NHB and Hispanics are considerably higher than NHW. In particular, the COVID-19 infection rate in the Hispanic community was significantly higher than their population share, a phenomenon we observed across all regions in the US but is most prominent in the West. To gauge the differential impact of comorbidities on different ethnicities, we performed cross-sectional regression analyses of statewide data for COVID-19 infection and mortality for each ethnic group using advanced age, poverty, obesity, hypertension, cardiovascular disease, and diabetes as risk factors. After removing the risk factors causing multicollinearity, poverty emerged as one of the independent risk factors in explaining mortality rates in NHW, NHB, and Hispanic communities. Moreover, for NHW and NHB groups, we found that obesity encapsulated the effect of several other comorbidities such as advanced age, hypertension, and cardiovascular disease. At the same time, advanced age was the most robust predictor of mortality in the Hispanic group. Our study quantifies the unique impact of various risk factors on different ethnic groups, explaining the ethnicity-specific differences observed in the COVID-19 pandemic. The findings could provide insight into focused public health strategies and interventions.