This map contains the 2020 Vulnerable Population Index along with the component demographic layers. The following seven populations were determined to be vulnerable based on an understanding of both federal requirements and regional demographics: 1) Low-Income Population (below 200% of poverty level) 2) Non-Hispanic Minority Population 3) Hispanic or Latino Population (all races) 4) Population with Limited English Proficiency (LEP) 5) Population with Disabilities 6) Elderly Population (age 75 and up) 7) Households with No CarFor each of these populations, Census tracts with concentrations above the regional mean concentration are divided into two categories above the regional mean. These categories are calculated by dividing the range of values between the regional mean and the regional maximum into two equal-sized intervals. Tracts in the lower interval are given a score of 1 and tracts in the upper interval are given a score of 2 for that demographic variable. The scores are totaled from the seven individual demographic variables to yield the Vulnerable Population Index (VPI). The VPI can range from zero to fourteen (0 to 14). A lower VPI indicates a less vulnerable area, while a higher VPI indicates a more vulnerable area.FIELDSP_PovL100: Percent Below 100% of the Poverty Level, P_PovL200: Percent Below 200% of the Poverty Level, P_Minrty: Percent Minority (non-White, non-Hispanic), P_Hisp: Percent Hispanic, P_LEP: Percent Limited English Proficiency (speak English "not well" or "not at all"), P_Disabld: Percent with Disabilities, P_Elderly: Percent Elderly (age 75 and over), P_NoCarHH: Percent Households with No Vehicle, RG_PovL100: Regional Average (Mean) of Percent Below 100% of the Poverty Level, RG_PovL200: Regional Average (Mean) of Percent Below 200% of the Poverty Level, RG_Minrty: Regional Average (Mean) of Percent Minority (non-White, non-Hispanic), RG_Hisp: Regional Average (Mean) of Percent Hispanic, RG_LEP: Regional Average (Mean) of Percent Limited English Proficiency (speak English "not well" or "not at all"), RG_Disabld: Regional Average (Mean) of Percent with Disabilities, RG_Elderly: Regional Average (Mean) of Percent Elderly (age 75 and over), RG_NoCarHH: Regional Average (Mean) of Percent Households with No Vehicle, [NO SC_PovL100: Note: Percent Below 100% of the Poverty Level not used in VPI 2020 calculation],SC_PovL200: VPI Score for Below 200% of the Poverty Level (Values: 0, 1, or 2),SC_Minrty: VPI Score for Minority (non-White, non-Hispanic) (Values: 0, 1, or 2),SC_Hisp: VPI Score for Hispanic (Values: 0, 1, or 2),SC_LEP: VPI Score for Limited English Proficiency (speak English "not well" or "not at all") (Values: 0, 1, or 2),SC_Disabld: VPI Score for Disabilities (Values: 0, 1, or 2),SC_Elderly: VPI Score for Elderly (age 75 and over) (Values: 0, 1, or 2),SC_NoCarHH: VPI Score for Households with No Vehicle (Values: 0, 1, or 2),VPI_2020: Total VPI Score (0 minimum to 14 maximum).Additional information on equity planning at BMC can be found here.Sources: Baltimore Metropolitan Council, U.S. Census Bureau 2016–2020 American Community Survey 5-Year Estimates. Margins of error are not shown.Updated: April 2022
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.
Financial overview and grant giving statistics of Hispanic-Latino Minority Health Coalition of Greater Indianapolis
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United States MDI: IC: Minority Board & Serving Hispanic data was reported at 8.000 Number in Dec 2019. This records a decrease from the previous number of 9.000 Number for Sep 2019. United States MDI: IC: Minority Board & Serving Hispanic data is updated quarterly, averaging 9.000 Number from Mar 2019 (Median) to Dec 2019, with 4 observations. The data reached an all-time high of 9.000 Number in Sep 2019 and a record low of 8.000 Number in Dec 2019. United States MDI: IC: Minority Board & Serving Hispanic data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB069: Minority Depository Institutions.
Majority minority districts are widely viewed as opportunities for racial minority groups to expand their representation in elected office. Do these districts facilitate the same opportunities for descriptive representation for women and men? I argue that majority minority districts have served as important, but distinct opportunities for Latinas and Latinos to get on the ballot. Analyzing pooled data from 57,812 state legislative general elections from the mid 1990’s to 2015, and during the first rounds of elections following 2000 and 2010 Census-based redistricting, I find support for this view. Key factors often associated with majority minority districts’ capacity as vehicles for minority representation, such as increasingly large Latina/o proportions of district populations and incumbent networks, are more robustly related to the presence of Latinos than Latinas on the ballot. These findings bear directly on our understanding of how majority minority districts fit into a portfolio of institutions for expanding descriptive representation.
The statistic shows the share of U.S. population, by race and Hispanic origin, in 2016 and a projection for 2060. As of 2016, about 17.79 percent of the U.S. population was of Hispanic origin. Race and ethnicity in the U.S. For decades, America was a melting pot of the racial and ethnical diversity of its population. The number of people of different ethnic groups in the United States has been growing steadily over the last decade, as has the population in total. For example, 35.81 million Black or African Americans were counted in the U.S. in 2000, while 43.5 million Black or African Americans were counted in 2017.
The median annual family income in the United States in 2017 earned by Black families was about 50,870 U.S. dollars, while the average family income earned by the Asian population was about 92,784 U.S. dollars. This is more than 15,000 U.S. dollars higher than the U.S. average family income, which was 75,938 U.S. dollars.
The unemployment rate varies by ethnicity as well. In 2018, about 6.5 percent of the Black or African American population in the United States were unemployed. In contrast to that, only three percent of the population with Asian origin was unemployed.
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This is the replication file for 'Cause or Effect', containing code to replicate all figures and tables in the manuscript. The abstract for the article is: Legislative redistricting alters the political and electoral context for some voters but not others, thus offering a potentially promising research design to study many questions of interest in political science. We apply this design to study the effect that descriptive representation has on co-ethnic political engagement, focusing on Hispanic participation following California’s 2000 redistricting cycle. We show that when redistrictors draw legislative boundaries in California’s 1990, 2000 and 2010 apportionment cycles, they systematically sort higher participating Hispanic voters into majority-Hispanic (MH) jurisdictions represented by co-ethnic candidates, biasing subsequent comparisons of Hispanic participation across districts. Similar sorting occurs during redistricting in Florida and Texas, though here the pattern is reversed, with less participating Hispanic voters redistricted to MH districts. Our study highlights important heterogeneity in redistricting largely unknown or under-appreciated in previous research. Ignoring this selection problem could significantly bias estimates of the effect of Hispanic representation, either positively or negatively. After we correct for these biases using a hierarchical genetic matching algorithm, we find that, in California, being moved to a district with an Hispanic incumbent has little impact on Hispanic participation in our data.
A dataset of a longitudinal study of over 3,000 Mexican-Americans aged 65 or over living in five southwestern states. The objective is to describe the physical and mental health of the study group and link them to key social variables (e.g., social support, health behavior, acculturation, migration). To the extent possible, the study was modeled after the existing EPESE studies, especially the Duke EPESE, which included a large sample if African-Americans. Unlike the other EPESE studies that were restricted to small geographic areas, the Hispanic EPESE aimed at obtaining a representative sample of community-dwelling Mexican-American elderly residing in Texas, New Mexico, Arizona, Colorado, and California. Approximately 85% of Mexican-American elderly reside in these states and data were obtained that are generalizable to roughly 500,000 older people. The final sample of 3,050 subjects at baseline is comparable to those of the other EPESE studies. Data Availability: Waves I to IV are available through the National Archive of Computerized Data on Aging (NACDA), ICPSR. Also available through NACDA is the ����??Resource Book of the Hispanic Established Populations for the Epidemiologic Studies of the Elderly����?? which offers a thorough review of the data and its applications. All subjects aged 75 or older were interviewed for Wave V and 902 new subjects were added. Hemoglobin A1c test kits were provided to subjects who self-reported diabetes. Approximately 270 of the kits were returned for analyses. Wave V data are being validated and reviewed. A tentative timeline for the archiving of Wave V data is November 2006. Wave VI interviewing and data collection is scheduled to begin in Fall 2006. * Dates of Study: 1993-2006 * Study Features: Longitudinal, Minority oversamples, Anthropometric Measures * Sample Size: ** 1993-4: 3,050 (Wave I) ** 1995-6: 2,438 (Wave II) ** 1998-9: 1,980 (Wave III) ** 2000-1: 1,682 (Wave IV) ** 2004-5: 2,073 (Wave V) ** 2006-7: (Wave VI) Links: * ICPSR Wave 1: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/2851 * ICPSR Wave 2: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/3385 * ICPSR Wave 3: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/4102 * ICPSR Wave 4: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/4314 * ICPSR Wave 5: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/25041 * ICPSR Wave 6: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/29654
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United States MDI: Assets: Minority Board & Serving Hispanic data was reported at 81,588,087.000 USD th in Dec 2019. This records a decrease from the previous number of 82,639,750.000 USD th for Sep 2019. United States MDI: Assets: Minority Board & Serving Hispanic data is updated quarterly, averaging 81,307,378.000 USD th from Mar 2019 (Median) to Dec 2019, with 4 observations. The data reached an all-time high of 82,639,750.000 USD th in Sep 2019 and a record low of 78,496,491.000 USD th in Mar 2019. United States MDI: Assets: Minority Board & Serving Hispanic data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB069: Minority Depository Institutions.
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Supplementary Material 1: Appendix 1 : World Health Organization Trial Registration Data Set. Appendix 2: SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents*.
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United States MDI: Assets: Hispanic American data was reported at 104,188,565.000 USD th in 2018. This records an increase from the previous number of 102,424,217.000 USD th for 2017. United States MDI: Assets: Hispanic American data is updated yearly, averaging 101,483,656.500 USD th from Dec 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 135,089,330.000 USD th in 2007 and a record low of 57,403,864.000 USD th in 2001. United States MDI: Assets: Hispanic American data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB070: Minority Depository Institutions: Annual.
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Relative concentration of the Northern California region's Hispanic and/or Black, Indigenous or person of color (HSPBIPOC) population. The variable HSPBIPOC is equivalent to all individuals who select a combination of racial and ethnic identity in response to the Census questionnaire EXCEPT those who select "not Hispanic" for the ethnic identity question, and "white race alone" for the racial identity question. This is the most encompassing possible definition of racial and ethnic identities that may be associated with historic underservice by agencies, or be more likely to express environmental justice concerns (as compared to predominantly non-Hispanic white communities). Until 2021, federal agency guidance for considering environmental justice impacts of proposed actions focused on how the actions affected "racial or ethnic minorities." "Racial minority" is an increasingly meaningless concept in the USA, and particularly so in California, where only about 3/8 of the state's population identifies as non-Hispanic and white race alone - a clear majority of Californians identify as Hispanic and/or not white. Because many federal and state map screening tools continue to rely on "minority population" as an indicator for flagging potentially vulnerable / disadvantaged/ underserved populations, our analysis includes the variable HSPBIPOC which is effectively "all minority" population according to the now outdated federal environmental justice direction. A more meaningful analysis for the potential impact of forest management actions on specific populations considers racial or ethnic populations individually: e.g., all people identifying as Hispanic regardless of race; all people identifying as American Indian, regardless of Hispanic ethnicity; etc.
"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as HSPBIPOC alone to the proportion of all people that live within the 1,207 block groups in the Northern California RRK region that identify as HSPBIPOC alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of HSPBIPOC individuals compared to the Northern California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then HSPBIPOC individuals are highly concentrated locally.
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BackgroundLatinx communities are disproportionately affected by COVID-19 compared with non-Latinx White communities in Oregon and much of the United States. The COVID-19 pandemic presents a critical and urgent need to reach Latinx communities with innovative, culturally tailored outreach and health promotion interventions to reduce viral transmission and address disparities. The aims of this case study are to (1) outline the collaborative development of a culturally and trauma-informed COVID-19 preventive intervention for Latinx communities; (2) describe essential intervention elements; and (3) summarize strengths and lessons learned for future applications.MethodsBetween June 2020 and January 2021, a multidisciplinary team of researchers and Latinx-serving partners engaged in the following intervention development activities: a scientific literature review, a survey of 67 Latinx residents attending public testing events, interviews with 13 leaders of community-based organizations serving Latinx residents, and bi-weekly consultations with the project's Public Health and Community Services Team and a regional Community and Scientific Advisory Board. After launching the intervention in the field in February 2021, bi-weekly meetings with interventionists continuously informed minor iterative refinements through present day.ResultsThe resulting intervention, Promotores de Salud, includes outreach and brief health education. Bilingual, trauma-informed trainings and materials reflect the lived experiences, cultural values, needs, and concerns of Latinx communities. Interventionists (21 Promotores) were Latinx residents from nine Oregon counties where the intervention was delivered.ConclusionsSharing development and intervention details with public health researchers and practitioners facilitates intervention uptake and replication to optimize the public health effect in Oregon's Latinx communities and beyond.
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Relative concentration of the Sierra Nevada region's Hispanic and/or Black, Indigenous or person of color (HSPBIPOC) population. The variable HSPBIPOC is equivalent to all individuals who select a combination of racial and ethnic identity in response to the Census questionnaire EXCEPT those who select "not Hispanic" for the ethnic identity question, and "white race alone" for the racial identity question. This is the most encompassing possible definition of racial and ethnic identities that may be associated with historic underservice by agencies, or be more likely to express environmental justice concerns (as compared to predominantly non-Hispanic white communities). Until 2021, federal agency guidance for considering environmental justice impacts of proposed actions focused on how the actions affected "racial or ethnic minorities." "Racial minority" is an increasingly meaningless concept in the USA, and particularly so in California, where only about 3/8 of the state's population identifies as non-Hispanic and white race alone - a clear majority of Californians identify as Hispanic and/or not white. Because many federal and state map screening tools continue to rely on "minority population" as an indicator for flagging potentially vulnerable / disadvantaged/ underserved populations, our analysis includes the variable HSPBIPOC which is effectively "all minority" population according to the now outdated federal environmental justice direction. A more meaningful analysis for the potential impact of forest management actions on specific populations considers racial or ethnic populations individually: e.g., all people identifying as Hispanic regardless of race; all people identifying as American Indian, regardless of Hispanic ethnicity; etc.
"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as HSPBIPOC alone to the proportion of all people that live within the 775 block groups in the Sierra Nevada RRK region that identify as HSPBIPOC alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of HSPBIPOC individuals compared to the Sierra Nevada RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then HSPBIPOC individuals are highly concentrated locally.
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Context
The dataset tabulates the Minnesota Hispanic or Latino population. It includes the distribution of the Hispanic or Latino population, of Minnesota, by their ancestries, as identified by the Census Bureau. The dataset can be utilized to understand the origin of the Hispanic or Latino population of Minnesota.
Key observations
Among the Hispanic population in Minnesota, regardless of the race, the largest group is of Mexican origin, with a population of 222,290 (62.86% of the total Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Origin for Hispanic or Latino population include:
Variables / Data Columns
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.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Minnesota Population by Race & Ethnicity. You can refer the same here
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The current study explored various factors affecting affirmative action attitudes. Undergraduate students completed an online survey with measures assessing support for Black-targeted and Hispanic-targeted affirmative action, perceived discrimination against Blacks and Hispanics, social dominance orientation, and racial group esteem. Prior to completing these measures, some participants were randomly assigned to read a set of 10 facts about current racial inequities. Analyses revealed that affirmative action support was greater for outreach and training policies versus preference and quota policies, greater among participants who read the inequity facts versus the control group, greater among Black and Hispanic participants versus White participants, greater among White participants with low versus high White esteem, and greater among participants with low versus high social dominance orientation. Regarding demographics, support was also greater among Democrat and liberal participants versus Republican and conservative participants, greater among female participants versus male participants, and greater among sexual minority participants versus straight participants. Additionally, whereas Black participants did not differ in their support for Black-targeted versus Hispanic-targeted affirmative action, Hispanic participants supported Hispanic-targeted affirmative action more than Black-targeted affirmative action, even though they also gave higher ratings of perceived discrimination faced by Black individuals in comparison to Hispanic individuals. These findings are consistent with past research, social dominance theory (whereby Hispanic affirmative action support may be influenced by group status threat), and the altruism-born-of-suffering theory (whereby adverse discriminatory experiences of Black and sexual minorities may have led to greater empathic concern and support for affirmative action).
In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.
Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.
The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.
The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.
The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.
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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:.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. Employment reflects the number of paid employees during the pay period in the reference year that included March 12...Data Items and Other Identifying Records:.Data include estimates on:.Number of employer firms (firms with paid employees). Sales and receipts of employer firms (reported in $1,000s of dollars). Number of employees (during the March 12 pay period). Annual payroll (reported in $1,000s of dollars)...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. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. 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."...Industry and Geography Coverage:..The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3- and 4-digit NAICS code for:..United States. States and the District of Columbia...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...Footnotes:.Footnote 660 - Agriculture, forestry, fishing and hunting (Sector 11): Crop and Animal Production (NAICS 111 and 112) are out of scope..Footnote 661 - Transportation and warehousing...
Financial overview and grant giving statistics of Hispanic Urban Minority Alcoholism and Drug Abuse Outreach Program
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United States MDI: IC: Hispanic American data was reported at 35.000 Number in 2018. This records a decrease from the previous number of 38.000 Number for 2017. United States MDI: IC: Hispanic American data is updated yearly, averaging 40.500 Number from Dec 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 53.000 Number in 2008 and a record low of 31.000 Number in 2002. United States MDI: IC: Hispanic American data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB070: Minority Depository Institutions: Annual.
This map contains the 2020 Vulnerable Population Index along with the component demographic layers. The following seven populations were determined to be vulnerable based on an understanding of both federal requirements and regional demographics: 1) Low-Income Population (below 200% of poverty level) 2) Non-Hispanic Minority Population 3) Hispanic or Latino Population (all races) 4) Population with Limited English Proficiency (LEP) 5) Population with Disabilities 6) Elderly Population (age 75 and up) 7) Households with No CarFor each of these populations, Census tracts with concentrations above the regional mean concentration are divided into two categories above the regional mean. These categories are calculated by dividing the range of values between the regional mean and the regional maximum into two equal-sized intervals. Tracts in the lower interval are given a score of 1 and tracts in the upper interval are given a score of 2 for that demographic variable. The scores are totaled from the seven individual demographic variables to yield the Vulnerable Population Index (VPI). The VPI can range from zero to fourteen (0 to 14). A lower VPI indicates a less vulnerable area, while a higher VPI indicates a more vulnerable area.FIELDSP_PovL100: Percent Below 100% of the Poverty Level, P_PovL200: Percent Below 200% of the Poverty Level, P_Minrty: Percent Minority (non-White, non-Hispanic), P_Hisp: Percent Hispanic, P_LEP: Percent Limited English Proficiency (speak English "not well" or "not at all"), P_Disabld: Percent with Disabilities, P_Elderly: Percent Elderly (age 75 and over), P_NoCarHH: Percent Households with No Vehicle, RG_PovL100: Regional Average (Mean) of Percent Below 100% of the Poverty Level, RG_PovL200: Regional Average (Mean) of Percent Below 200% of the Poverty Level, RG_Minrty: Regional Average (Mean) of Percent Minority (non-White, non-Hispanic), RG_Hisp: Regional Average (Mean) of Percent Hispanic, RG_LEP: Regional Average (Mean) of Percent Limited English Proficiency (speak English "not well" or "not at all"), RG_Disabld: Regional Average (Mean) of Percent with Disabilities, RG_Elderly: Regional Average (Mean) of Percent Elderly (age 75 and over), RG_NoCarHH: Regional Average (Mean) of Percent Households with No Vehicle, [NO SC_PovL100: Note: Percent Below 100% of the Poverty Level not used in VPI 2020 calculation],SC_PovL200: VPI Score for Below 200% of the Poverty Level (Values: 0, 1, or 2),SC_Minrty: VPI Score for Minority (non-White, non-Hispanic) (Values: 0, 1, or 2),SC_Hisp: VPI Score for Hispanic (Values: 0, 1, or 2),SC_LEP: VPI Score for Limited English Proficiency (speak English "not well" or "not at all") (Values: 0, 1, or 2),SC_Disabld: VPI Score for Disabilities (Values: 0, 1, or 2),SC_Elderly: VPI Score for Elderly (age 75 and over) (Values: 0, 1, or 2),SC_NoCarHH: VPI Score for Households with No Vehicle (Values: 0, 1, or 2),VPI_2020: Total VPI Score (0 minimum to 14 maximum).Additional information on equity planning at BMC can be found here.Sources: Baltimore Metropolitan Council, U.S. Census Bureau 2016–2020 American Community Survey 5-Year Estimates. Margins of error are not shown.Updated: April 2022