100+ datasets found
  1. a

    Predominant Non White or Hispanic Adult Citizen Population

    • gis-for-racialequity.hub.arcgis.com
    Updated Jul 20, 2017
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    ArcGIS Living Atlas Team (2017). Predominant Non White or Hispanic Adult Citizen Population [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/6cec02b9243b4ad2af4f4e6fc2057b69
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    Dataset updated
    Jul 20, 2017
    Dataset authored and provided by
    ArcGIS Living Atlas Team
    Area covered
    Description

    This map shows the predominant non white or Hispanic population of citizens age 18+ in the United States and Puerto Rico. The map is available for states, counties, tracts, and block groups increasing in detail as you zoom in.The color of the features represent the different ethnicities African American, American Indian or Alaska Native, American Indian and White, Asian, African American and White, Asian and White, Native Hawaiian, American Indian and African American, and Remainder of Two or More Race Responses. The size represents the amount of people who reported their race to the census.The data source is the US Census Bureau Voting Age Population by Citizenship and Race (CVAP) tabulation from the 2012-2016 American Community Survey 5 year estimates. More information can be found here.

  2. Racial and ethnic distribution of users in adult day care in the U.S. in...

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Racial and ethnic distribution of users in adult day care in the U.S. in 2022 [Dataset]. https://www.statista.com/statistics/1554197/adult-day-care-users-by-race-and-ethnicity/
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    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    In 2022, of the estimated ******* participants enrolled in adult day services centers in the United States, just ** percent were white, non-Hispanic adults. Racial and ethnic minorities accounted for ** percent of adult day care users at that time.

  3. F

    Consumer Unit Characteristics: Adults 65 and Older by Hispanic or Latino...

    • fred.stlouisfed.org
    json
    Updated Sep 14, 2023
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    (2023). Consumer Unit Characteristics: Adults 65 and Older by Hispanic or Latino Origin: Not Hispanic or Latino: White and All Other Races, Not Including Black or African American [Dataset]. https://fred.stlouisfed.org/series/CXU980060LB1004M
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    jsonAvailable download formats
    Dataset updated
    Sep 14, 2023
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Consumer Unit Characteristics: Adults 65 and Older by Hispanic or Latino Origin: Not Hispanic or Latino: White and All Other Races, Not Including Black or African American (CXU980060LB1004M) from 2003 to 2022 about 65-years +, adult, consumer unit, white, hispanic, latino, and USA.

  4. Uninsured adult U.S. workers in 2022, by ethnicity

    • statista.com
    Updated Jan 4, 2024
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    Statista (2024). Uninsured adult U.S. workers in 2022, by ethnicity [Dataset]. https://www.statista.com/statistics/985589/us-workers-without-health-insurance-by-ethnicity/
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    Dataset updated
    Jan 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    This statistic shows the number of nonelderly adult workers without health insurance in the U.S. in 2022, sorted by race/ethnicity. Almost six million non-Hispanic white adult workers in the United States were uninsured.

  5. f

    Data_Sheet_1_Decomposing interaction and mediating effects of race/ethnicity...

    • frontiersin.figshare.com
    pdf
    Updated Jun 1, 2023
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    César Higgins Tejera; Erin B. Ware; Lindsay C. Kobayashi; Mingzhou Fu; Margaret Hicken; Matthew Zawistowski; Bhramar Mukherjee; Kelly M. Bakulski (2023). Data_Sheet_1_Decomposing interaction and mediating effects of race/ethnicity and circulating blood levels of cystatin C on cognitive status in the United States health and retirement study.PDF [Dataset]. http://doi.org/10.3389/fnhum.2023.1052435.s001
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    César Higgins Tejera; Erin B. Ware; Lindsay C. Kobayashi; Mingzhou Fu; Margaret Hicken; Matthew Zawistowski; Bhramar Mukherjee; Kelly M. Bakulski
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Background and objectivesElevated circulating cystatin C is associated with cognitive impairment in non-Hispanic Whites, but its role in racial disparities in dementia is understudied. In a nationally representative sample of older non-Hispanic White, non-Hispanic Black, and Hispanic adults in the United States, we use mediation-interaction analysis to understand how racial disparities in the cystatin C physiological pathway may contribute to racial disparities in prevalent dementia.MethodsIn a pooled cross-sectional sample of the Health and Retirement Study (n = 9,923), we employed Poisson regression to estimate prevalence ratios and to test the relationship between elevated cystatin C (>1.24 vs. ≤1.24 mg/L) and impaired cognition, adjusted for demographics, behavioral risk factors, other biomarkers, and chronic conditions. Self-reported racialized social categories were a proxy measure for exposure to racism. We calculated additive interaction measures and conducted four-way mediation-interaction decomposition analysis to test the moderating effect of race/ethnicity and mediating effect of cystatin C on the racial disparity.ResultsOverall, elevated cystatin C was associated with dementia (prevalence ratio [PR] = 1.2; 95% CI: 1.0, 1.5). Among non-Hispanic Black relative to non-Hispanic White participants, the relative excess risk due to interaction was 0.7 (95% CI: −0.1, 2.4), the attributable proportion was 0.1 (95% CI: −0.2, 0.4), and the synergy index was 1.1 (95% CI: 0.8, 1.8) in a fully adjusted model. Elevated cystatin C was estimated to account for 2% (95% CI: −0, 4%) for the racial disparity in prevalent dementia, and the interaction accounted for 8% (95% CI: −5, 22%). Analyses for Hispanic relative to non-white participants suggested moderation by race/ethnicity, but not mediation.DiscussionElevated cystatin C was associated with dementia prevalence. Our mediation-interaction decomposition analysis suggested that the effect of elevated cystatin C on the racial disparity might be moderated by race/ethnicity, which indicates that the racialization process affects not only the distribution of circulating cystatin C across minoritized racial groups, but also the strength of association between the biomarker and dementia prevalence. These results provide evidence that cystatin C is associated with adverse brain health and this effect is larger than expected for individuals racialized as minorities had they been racialized and treated as non-Hispanic White.

  6. Data from: Hispanic Established Populations for the Epidemiologic Study of...

    • search.datacite.org
    • icpsr.umich.edu
    Updated 2016
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    Kyriakos S. Markides; Nai-Wei Chen; Ronald Angel; Raymond Palmer (2016). Hispanic Established Populations for the Epidemiologic Study of the Elderly (HEPESE) Wave 8, 2012-2013 [Arizona, California, Colorado, New Mexico, and Texas] [Dataset]. http://doi.org/10.3886/icpsr36578
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    Dataset updated
    2016
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    DataCitehttps://www.datacite.org/
    Authors
    Kyriakos S. Markides; Nai-Wei Chen; Ronald Angel; Raymond Palmer
    Dataset funded by
    United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging
    Description

    The Hispanic EPESE provides data on risk factors for mortality and morbidity in Mexican Americans in order to contrast how these factors operate differently in non-Hispanic White Americans, African Americans, and other major ethnic groups. The Wave 8 dataset comprises the seventh follow-up of the baseline Hispanic EPESE (HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: [ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS] [ICPSR 2851]). The baseline Hispanic EPESE collected data on a representative sample of community-dwelling Mexican Americans, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The public-use data cover demographic characteristics (age, sex, marital status), height, weight, BMI, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of hospital and nursing home services, and depression. Subsequent follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization, and other changes in living arrangements, as well as changes in life situations and quality of life issues. During this 8th Wave, 2012-2013, re-interviews were conducted either in person or by proxy, with 452 of the original respondents. This Wave also includes 292 re-interviews from the additional sample of Mexican Americans aged 75 years and over with higher average-levels of education than those of the surviving cohort who were added in Wave 5, increasing the total number of respondents to 744.

  7. o

    Data from: It’s Complicated: Everyday Discrimination Across the Transition...

    • openicpsr.org
    Updated Oct 24, 2022
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    Ashley N Palmer (2022). It’s Complicated: Everyday Discrimination Across the Transition into Adulthood [Dataset]. http://doi.org/10.3886/E183323V1
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    Dataset updated
    Oct 24, 2022
    Dataset provided by
    TCU
    Authors
    Ashley N Palmer
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2005 - 2017
    Area covered
    United States
    Description

    Experiences during emerging adulthood hold particular importance for future health and economic well-being. This study uses Panel Study of Income Dynamics Transition into Adulthood Supplement data to explore growth trajectories of perceived discrimination across the transition into adulthood and to examine how gendered racialized group status might shape perceived discrimination among U.S. emerging adult men and women racialized as white, non-Hispanic, Black, non-Hispanic, or Hispanic (n=2,532) using multilevel models. Results showed that as emerging adults age there is a decreasing pattern of perceived everyday discrimination, though there were individual differences in the rate and direction of change. Women racialized as Black, non-Hispanic had significantly lower perceived discrimination than all other groups except Hispanic women. Each of the six gendered racialized subgroups had similar patterns of perceived discrimination over time. More research is needed to better understand differences in the rate and direction of change in perceived discrimination over time.

  8. Data from: Hispanic Established Populations for Epidemiologic Studies of the...

    • search.datacite.org
    • icpsr.umich.edu
    Updated 2005
    + more versions
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    Kyriakos S. Markides; Laura A. Ray (2005). Hispanic Established Populations for Epidemiologic Studies of the Elderly, Wave IV, 2000-2001 [Arizona, California, Colorado, New Mexico, and Texas] [Dataset]. http://doi.org/10.3886/icpsr04314
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    Dataset updated
    2005
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    DataCitehttps://www.datacite.org/
    Authors
    Kyriakos S. Markides; Laura A. Ray
    Dataset funded by
    United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging
    Description

    This dataset comprises the third follow-up of the baseline Hispanic EPESE, HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS, and provides information on 1,682 of the original respondents. The Hispanic EPESE collected data on a representative sample of community-dwelling Mexican-American elderly, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The primary purpose of the series was to provide estimates of the prevalence of key physical health conditions, mental health conditions, and functional impairments in older Mexican Americans and to compare these estimates with those for other populations. The Hispanic EPESE attempted to determine whether certain risk factors for mortality and morbidity operate differently in Mexican Americans than in non-Hispanic White Americans, African Americans, and other major ethnic groups. The public-use data cover background characteristics (age, sex, type of Hispanic race, income, education, marital status, number of children, employment, and religion), height, weight, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of dental, hospital, and nursing home services, and depression. The follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization and other changes in living arrangements, as well as changes in life situations and quality of life issues. The vital status of respondents from baseline to this round of the survey may be determined using the Vital Status file (Part 2). This file contains interview dates from the baseline as well as vital status at Wave IV (respondent survived, date of death if deceased, proxy-assisted, proxy-reported cause of death, proxy-true). The first follow-up of the baseline data (Hispanic EPESE Wave II, 1995-1996 [ICPSR 3385]) followed 2,438 of the original 3,050 respondents, and the second follow-up (Hispanic EPESE Wave III, 1998-1999 [ICPSR 4102]) followed 1,980 of these respondents. Hispanic EPESE, 1993-1994 (ICPSR 2851), was modeled after the design of ESTABLISHED POPULATIONS FOR EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1981-1993: EAST BOSTON, MASSACHUSETTS, IOWA AND WASHINGTON COUNTIES, IOWA, NEW HAVEN, CONNECTICUT, AND NORTH CENTRAL NORTH CAROLINA and ESTABLISHED POPULATIONS FOR EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1996-1997: PIEDMONT HEALTH SURVEY OF THE ELDERLY, FOURTH IN-PERSON SURVEY DURHAM, WARREN, VANCE, GRANVILLE, AND FRANKLIN COUNTIES, NORTH CAROLINA.

  9. f

    Data_Sheet_1_Factors that protect against poor sleep quality in an adult...

    • frontiersin.figshare.com
    docx
    Updated Jun 21, 2023
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    Emily Hokett; Aditi Arunmozhi; Jessica Campbell; Audrey Duarte (2023). Data_Sheet_1_Factors that protect against poor sleep quality in an adult lifespan sample of non-Hispanic Black and non-Hispanic White adults during COVID-19: A cross-sectional study.docx [Dataset]. http://doi.org/10.3389/fpsyg.2022.949364.s001
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    docxAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    Frontiers
    Authors
    Emily Hokett; Aditi Arunmozhi; Jessica Campbell; Audrey Duarte
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionStress in relation to the Coronavirus disease 19 pandemic (i.e., COVID-19, COVID stress) may be linked with poor sleep quality. The association between stress that is specific to the COVID-19 pandemic and sleep quality has been understudied, particularly in racially diverse people across the adult lifespan. Here, we investigated self-reported sleep quality in relation to COVID stress and factors that may protect against experiencing poor sleep quality from high COVID stress, including social support and religiosity.MethodWe recruited non-Hispanic Black (n = 73) and non-Hispanic White (n = 178) participants across the adult lifespan (18–76 years) using an online, cross-sectional design during the COVID-19 pandemic (March 2021–June 2021). We asked participants to report information regarding demographics (age, race/ethnicity, years of education), sleep (sleep quality, sleep habits), and positive (social support, religious activities) and negative (events of discrimination, depression, general stress, COVID stress) psychosocial factors.ResultsAcross age and racial groups, better sleep habits were associated with better sleep quality, and higher COVID stress was linked to poorer sleep quality. Black participants reported higher quality sleep than White participants (p = 0.006). They also endorsed greater private and internal religiosity (p’s < 0.001). Across racial groups, moderation analyses revealed a protective effect of religiosity against poor sleep (p’s < 0.006). Specifically, individuals with high religious activity and high COVID stress did not experience poor sleep quality, but individuals with low religious activity and high COVID stress demonstrated poor sleep quality. These results remained significant when controlling for general stress.DiscussionProtective factors, such as religiosity, may mitigate the negative associations between high COVID stress and poor sleep quality.

  10. a

    SBLA Income & Employment Indicators

    • hub.arcgis.com
    • equity-lacounty.hub.arcgis.com
    Updated Sep 27, 2022
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    County of Los Angeles (2022). SBLA Income & Employment Indicators [Dataset]. https://hub.arcgis.com/datasets/bda5109ae480420287d6ec3f8770f3f4
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    Dataset updated
    Sep 27, 2022
    Dataset authored and provided by
    County of Los Angeles
    Description

    Created for the 2023-2025 State of Black Los Angeles County (SBLA) interactive report. To learn more about this effort, please visit the report home page at https://ceo.lacounty.gov/ardi/sbla/. For more information about the purpose of this data, please contact CEO-ARDI. For more information about the configuration of this data, please contact ISD-Enterprise GIS. table name indicator name Universe timeframe source race notes source url

    below_fpl_perc below 100% federal poverty level percent (%) Population for whom poverty status is determined 2016-2020 American Community Survey - S1703 Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S1703

    below_200fpl_perc below 200% federal poverty level percent (%) Total population 2021 Population and Poverty Estimates of Los Angeles County Tract-City Splits by Age, Sex and Race-Ethnicity for July 1, 2021, Los Angeles, CA, April 2022 All races are Non-Hispanic LA County eGIS-Demography

    median_income Median income (household) Households 2016-2020 American Community Survey - S1903 All races are Non-Hispanic; Race is that of householder https://data.census.gov/cedsci/table?q=S1903&g=0500000US06037

    percapita_income Mean Per Capita Income Total population 2016-2020 American Community Survey - S1902 Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S1902

    college_degree_any College degree AA, BA, or Higher % Population 25 years and over 2021 American Community Survey - B15002B-I Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?q=b15002b&g=0500000US06037

    graduate_professional_degree Graduate or professional degree % Population 25 years and over 2021 American Community Survey - B15002B-I Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?q=b15002b&g=0500000US06037

    unemployment_rate Unemployment Rate Population 16 years and over 2016-2020 American Community Survey - S2301 Race alone; White is Non-Hispanic White https://data.census.gov/cedsci/table?q=S2301%3A%20EMPLOYMENT%20STATUS&g=0500000US06037&tid=ACSST5Y2020.S2301

    below_300fpl_food_insecure Percent of Households with Incomes <300% Federal Poverty Level That Are Food Insecure Percent of Households with Incomes <300% Federal Poverty Level 2018 Los Angeles County Health Survey

    https://publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

    below_185fpl_snap Percent of Adults (Ages 18 Years and Older) with Household Incomes <185% Federal Poverty Level Who Are Currently Receiving Supplemental Nutrition Assistance Program (SNAP), Also Known as Calfresh Adults (Ages 18 Years and Older) with Household Incomes <185% Federal Poverty Level Los Angeles County Health Survey 20182018 https://publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

    B24010 Sex by Occupation for the Civilian Employed Population 16 Years and Over Civilian employed population 16 years and over

  11. Uninsured adult U.S. men in 2017, by ethnicity

    • statista.com
    Updated Jun 20, 2022
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    Statista (2022). Uninsured adult U.S. men in 2017, by ethnicity [Dataset]. https://www.statista.com/statistics/985518/us-men-without-health-insurance-by-ethnicity/
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    Dataset updated
    Jun 20, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    United States
    Description

    This statistic shows the number of nonelderly adult men without health insurance in the U.S. in 2017, sorted by race/ethnicity. Some 5.5 million non-Hispanic white adult men in the United States were uninsured.

  12. Rates and Trends in Heart Disease and Stroke Mortality Among US Adults (35+)...

    • catalog.data.gov
    • healthdata.gov
    • +4more
    Updated Jun 28, 2025
    + more versions
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    Centers for Disease Control and Prevention (2025). Rates and Trends in Heart Disease and Stroke Mortality Among US Adults (35+) by County, Age Group, Race/Ethnicity, and Sex – 2000-2019 [Dataset]. https://catalog.data.gov/dataset/rates-and-trends-in-heart-disease-and-stroke-mortality-among-us-adults-35-by-county-a-2000-45659
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset documents rates and trends in heart disease and stroke mortality. Specifically, this report presents county (or county equivalent) estimates of heart disease and stroke death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (women, men). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.

  13. Rates and Trends in Hypertension-related Cardiovascular Disease Mortality...

    • data.virginia.gov
    • healthdata.gov
    • +5more
    csv, json, rdf, xsl
    Updated Aug 24, 2023
    + more versions
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    Centers for Disease Control and Prevention (2023). Rates and Trends in Hypertension-related Cardiovascular Disease Mortality Among US Adults (35+) by County, Age Group, Race/Ethnicity, and Sex – 2000-2019 [Dataset]. https://data.virginia.gov/dataset/rates-and-trends-in-hypertension-related-cardiovascular-disease-mortality-among-us-ad-2000-2019
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    csv, rdf, json, xslAvailable download formats
    Dataset updated
    Aug 24, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset documents rates and trends in local hypertension-related cardiovascular disease (CVD) death rates. Specifically, this report presents county (or county equivalent) estimates of hypertension-related CVD death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (female, male). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.

  14. f

    Mortality and complications among Black, white, Hispanic, and non-Hispanic...

    • figshare.com
    xls
    Updated Jun 9, 2023
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    Ann M. Navar; Stacey N. Purinton; Qingjiang Hou; Robert J. Taylor; Eric D. Peterson (2023). Mortality and complications among Black, white, Hispanic, and non-Hispanic adults hospitalized for COVID-19. [Dataset]. http://doi.org/10.1371/journal.pone.0254809.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ann M. Navar; Stacey N. Purinton; Qingjiang Hou; Robert J. Taylor; Eric D. Peterson
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Mortality and complications among Black, white, Hispanic, and non-Hispanic adults hospitalized for COVID-19.

  15. Data from: Race/Ethnicity Influences Outcomes in Young Adults with...

    • zenodo.org
    • search.dataone.org
    • +1more
    Updated Jun 1, 2022
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    Laura C Miyares; Guido J Falcone; Audrey Leasure; Opeolu Adeoye; Fu-Dong Shi; Steven J Kittner; Carl Langefeld; Achala Vagal; Kevin N Sheth; Daniel Woo; Laura C Miyares; Guido J Falcone; Audrey Leasure; Opeolu Adeoye; Fu-Dong Shi; Steven J Kittner; Carl Langefeld; Achala Vagal; Kevin N Sheth; Daniel Woo (2022). Data from: Race/Ethnicity Influences Outcomes in Young Adults with Intracerebral Hemorrhage [Dataset]. http://doi.org/10.5061/dryad.6kb10h4
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    Dataset updated
    Jun 1, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Laura C Miyares; Guido J Falcone; Audrey Leasure; Opeolu Adeoye; Fu-Dong Shi; Steven J Kittner; Carl Langefeld; Achala Vagal; Kevin N Sheth; Daniel Woo; Laura C Miyares; Guido J Falcone; Audrey Leasure; Opeolu Adeoye; Fu-Dong Shi; Steven J Kittner; Carl Langefeld; Achala Vagal; Kevin N Sheth; Daniel Woo
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Objectives: We investigated the predictors of functional outcome in young patients enrolled in a multi-ethnic study of intracerebral hemorrhage (ICH). Methods: The Ethnic/Racial Variations in Intracerebral Hemorrhage (ERICH) study is a prospective multi-center study of ICH among adult (age ≥18 years) non-Hispanic whites, non-Hispanic blacks, and Hispanics. The study recruited 1000 participants per racial/ethnic group. The present study utilized the subset of ERICH cases aged <50 years with supratentorial ICH. Functional outcome was ascertained using the modified Rankin Scale (mRS) at 3 months. Logistic regression was used to identify factors associated with poor outcome (mRS 4–6), and analyses were compared by race/ethnicity to identify differences across these groups. Results: Of the 3000 ICH cases enrolled in ERICH, 418 were studied (mean age 43 years, 69% male), of which 48 (12%) were white, 173 (41%) were black, and 197 (47%) were Hispanic. For supratentorial ICH, blacks (odds ratio [OR] 0.42, p=0.046) and Hispanics (OR 0.34, p=0.01) had better outcomes than whites after adjustment for other factors associated with poor outcome: age, baseline disability, admission blood pressure, admission Glasgow Coma Scale score, ICH volume, deep ICH location, and intraventricular extension. Conclusions: In young patients with supratentorial ICH, black and Hispanic race/ethnicity is associated with better functional outcomes, compared with white race. Additional studies are needed to identify the biological and social mediators of this association.

  16. f

    Characteristics of white, Black, Hispanic, and non-Hispanic patients...

    • figshare.com
    xls
    Updated Jun 9, 2023
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    Ann M. Navar; Stacey N. Purinton; Qingjiang Hou; Robert J. Taylor; Eric D. Peterson (2023). Characteristics of white, Black, Hispanic, and non-Hispanic patients hospitalized with COVID-19. [Dataset]. http://doi.org/10.1371/journal.pone.0254809.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ann M. Navar; Stacey N. Purinton; Qingjiang Hou; Robert J. Taylor; Eric D. Peterson
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Characteristics of white, Black, Hispanic, and non-Hispanic patients hospitalized with COVID-19.

  17. Deaths from falls among seniors

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 7, 2018
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    Santa Clara County Public Health (2018). Deaths from falls among seniors [Dataset]. https://hub.arcgis.com/maps/sccphd::deaths-from-falls-among-seniors
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    Dataset updated
    Feb 7, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Age-adjusted rate of deaths from unintentional falls among adults ages 65 and older by sex, race/ethnicity, age; trends if available. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau; 2010 Census, Tables PCT12, PCT12H, PCT12I, PCT12J, PCT12K, PCT12L, PCT12M; generated by Baath M.; using American FactFinder; Accessed June 20, 2017. METADATA:Notes (String): Lists table title, notes and sourcesYear (String): Year of data; presented as single year or pooled years (2012-2016)Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); age categories as follows: 65 to 74, 75 to 84, 85+; Healthy People 2020 targetRate per 100,000 people (Numeric): Rate of deaths from falls among adults ages 65+. Rates for age groups are reported as age-specific rates per 100,000 people. All other rates are age-adjusted rates per 100,000 people.

  18. d

    Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA)

    • datasetcatalog.nlm.nih.gov
    Updated Oct 23, 2013
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    Rowell MPH, Sarah; Blackburn PhD, Elizabeth; Walter MA, Larry; Risch PhD, Neil; Somkin PhD, Carol; Iribarren MD, PhD, Carlos; Banda PhD, Yambazi; Kvale PhD, Mark; Quesenberry PhD, Charles; Whitmer PhD, Rachel; Schaefer PhD, Catherine; Hoffmann PhD, Thomas; Kwok MD, PhD, Pui-Yan; Van den Eeden PhD, Stephen (2013). Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA) [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000000454
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    Dataset updated
    Oct 23, 2013
    Authors
    Rowell MPH, Sarah; Blackburn PhD, Elizabeth; Walter MA, Larry; Risch PhD, Neil; Somkin PhD, Carol; Iribarren MD, PhD, Carlos; Banda PhD, Yambazi; Kvale PhD, Mark; Quesenberry PhD, Charles; Whitmer PhD, Rachel; Schaefer PhD, Catherine; Hoffmann PhD, Thomas; Kwok MD, PhD, Pui-Yan; Van den Eeden PhD, Stephen
    Description

    The Resource for Genetic Epidemiology Research on Aging (GERA) Cohort was created by a RC2 "Grand Opportunity" grant that was awarded to the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) and the UCSF Institute for Human Genetics (AG036607; Schaefer/Risch, PIs). The RC2 project enabled genome-wide SNP genotyping (GWAS) to be conducted on a cohort of over 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its RPGEH. The purpose of the RPGEH is to facilitate research on the genetic and environmental factors that affect health and disease by linking together clinical data from electronic health records, survey data on demographic and behavioral factors, and environmental data from various sources, with genetic data derived from biospecimens collected from participants. At the time of the award of the RC2 project in late 2009, the RPGEH had established a cohort of about 140,000 individuals who had answered a detailed survey, provided saliva samples for extraction of DNA, and given broad consent for the use of their data in studies of health and disease. To maximize the diversity of the resulting sample, the GERA cohort was formed by including all racial and ethnic minority participants with saliva samples (N = 20,925; 19%); the remaining participants were drawn sequentially and randomly from white non-Hispanic participants (89,341; 81%). A total of 110,266 participant samples were included to ensure that at least 100,000 were successfully assayed. The resulting GERA cohort is 42% male, 58% female, and ranges in age from 18 to over 100 years old with an average age of 63 years at the time of the RPGEH survey (2007). The sample is ethnically diverse, generally well-educated with above average income. Approximately 69% of the participants are married or living with a partner. Length of membership in KPNC averages 23.5 years. UCSF and RPGEH investigators worked with the genomics company Affymetrix to design four custom microarrays for genotyping each of the four major race-ethnicity groups included in the GERA Cohort, described in detail in Hoffmann et al., 2011a and 2011b. Following genotyping and quality control procedures, and after removal of invalid, discordant, or withdrawn samples, about 103,000 participants were successfully genotyped. The resulting genotypic data were linked to survey data and data abstracted from the electronic medical records. As described below, all RPGEH participants were mailed new consent forms with explicit discussion of the placement of data in the NIH-maintained dbGaP. About 77% of participants returned completed consent forms, resulting in a final sample size of 78,486 participants in the GERA Cohort with data for deposit into dbGaP. Origins of the RPGEH GERA Cohort The goal in creating the RPGEH GERA cohort was to create a large, multiethnic, and comprehensive population-based resource for research into the genetic and environmental basis of common age-related diseases and their treatment, and factors influencing healthy aging and longevity. The GERA Cohort consists of a diverse cohort of more than 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its Research Program on Genes, Environment and Health (RPGEH). KPNC is an integrated health care delivery system with a population of about 3.3 million people in northern California. The membership of KPNC is representative of the general population in the 14 county area in which facilities are located, although the membership is underrepresented for the extremes of income at both ends of the spectrum. The RPGEH utilizes the longitudinal electronic health records (EHR) of KPNC to obtain clinical, laboratory, imaging and pharmacy information on all cohort members, to which personal demographic, behavioral and health characteristics have been added through member surveys. The GERA Cohort comprises a subsample of the RPGEH participant cohort, and was created through the RC2 award from the NIA, NIMH, and NIH Common Fund as described above. GERA Study Design The GERA Cohort is a subsample, as described above, of the longitudinal cohort enrolled in the Kaiser Permanente RPGEH. The RPGEH cohort includes about 400,000 survey participants of whom about 200,000 have provided broad consent and a sample of saliva or blood for use in studies of genetic and environmental factors in health and disease. The GERA Cohort was developed from a mailed survey sent to all adult members of KPNC who had been members for two years or more in 2007. All survey respondents were contacted and asked to complete a consent form; those who completed consent forms were asked to provide a saliva sample. Additional male participants were added to the RPGEH through inclusion of the Northern California sample of the California Men's Health Study (CMHS) cohort of about 40,000 men from KPNC, ages 45-69 years old at the time of the CMHS survey in 2002-2003. The CMHS participants contributed about 15,400 saliva samples to the RPGEH and were eligible for inclusion in the GERA Cohort. CMHS participants were included according to the same sampling design as for the RPGEH cohort as a whole. Specifically, all minority participants were selected for inclusion in order to maximize representation of minorities in the GERA Cohort, and Non-Hispanic White participants were selected at random to complete the sample of 110,266 GERA Cohort participants. GERA Genotypic Data High-density genotyping was conducted at UCSF using custom designed Affymetrix Axiom arrays, as described in Hoffmann et al. (2011a; 2011b). To maximize genome-wide coverage of common and less common variants, four specific arrays were designed for individuals of Non-Hispanic White (EUR), East Asian (EAS), African-American (AFR), and Latino (LAT) race/ethnicity. There was broad overlap among the SNPs on the arrays, which were designed using a hybrid greedy imputation algorithm (Hoffmann et al., 2011b) applied to genotype information validated by Affymetrix from the 1000 Genomes Project. However, in order to capture low frequency variants specific to particular race-ethnicity groups, SNP content varies between arrays. A more detailed description of the process of genotyping and results is included in Genotyping of DNA Samples. Description of the analyses of population structure and development of principal components for adjustment of population structure is included in Population Structure Analysis. GERA Phenotypic Data RPGEH and CMHS Survey Data. The sources of data on demographic and behavioral factors deposited in dbGaP for the GERA Cohort are the RPGEH and CMHS surveys. Data on common demographic factors such as gender, race/ethnicity, marital status, and education and on behavioral factors such as smoking, alcohol consumption, and body mass index, have been cleaned, edited, reconciled between the two surveys, and compiled into summary indices, where appropriate, for deposition into dbGaP. A more complete description of the survey variables is included in Survey Variables Documentation. Please note that the terms of use of the GERA Cohort Data, as specified in the Data Use Certification (DUC), prohibit the use of survey variables as outcomes in analyses. For example, a genome-wide association study (GWAS) of education or smoking is not permitted as specified by the DUC. Only health conditions can be used as outcome variables in analyses. Health Conditions derived from Kaiser Permanente Electronic Medical Records. Data on the occurrence of health conditions in participants in the GERA Cohort have been derived from summarizing ICD-9 coded diagnoses in Kaiser Permanente's electronic medical records. An algorithm that aggregates specific ICD-9 codes into appropriate diagnostic groups for selected conditions is applied to outpatient and inpatient databases; see Disease and Conditions Definitions Documentation for details. The criterion for including a condition as "present" for a participant is the occurrence of two or more diagnoses within a diagnostic category occurring on separate days. Two or more is used as the criterion in order to reduce false positives due to mistakes or rule-out diagnoses. When compared with validated disease registries, the criterion of 2+ diagnoses yields high specificity and good sensitivity. ICD-9 codes in the electronic records are specified in several ways. For outpatient visits occurring during the period 1995 to 2006, diagnoses were assigned by the treating physician who endorsed specific diagnoses on an optically scanned list that varied by specialty. Beginning in 2006 with the advent of an integrated, fully electronic medical record, outpatient diagnoses are made by physicians/ providers using a pull down menu. Discharge diagnoses from inpatient stays are specified by physicians and coded by specially trained coders. Databases of ICD-9 codes for diagnoses assigned at outpatient visits, or as one of the discharge diagnoses following inpatient stays, are complete and available for all KPNC members dating back to 1995. Although the average length of KPNC membership among GERA cohort members is 23.5 years in 2007, not all have been members since 1995, so the history for some conditions, such as those that are not chronic or recurrent, may not be complete for all cohort members. The year of first membership in KPNC is included as a variable in the list of survey variables, enabling investigators to estimate the number of years of observation of each Cohort member. RPGEH Access and Collaborations Website and Procedures The RPGEH maintains a web portal for inquiries and applications for collaboration and access to data. The url is: https://rpgehportal.kaiser.org/. RPGEH has an application process and an Access Review Committee that reviews applications for collaboration and use. For more details, please

  19. f

    Data from: Prevalence of health conditions associated with higher risk for...

    • tandf.figshare.com
    xlsx
    Updated Aug 8, 2025
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    Abby Hitchens; Sean D. Candrilli; Justin Carrico; Katherine A. Hicks; Eleanor Wilson; Darshan Mehta; Catherine A. Panozzo; Parinaz Ghaswalla (2025). Prevalence of health conditions associated with higher risk for severe respiratory syncytial virus, influenza, or COVID-19 [Dataset]. http://doi.org/10.6084/m9.figshare.29608467.v3
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    xlsxAvailable download formats
    Dataset updated
    Aug 8, 2025
    Dataset provided by
    Taylor & Francis
    Authors
    Abby Hitchens; Sean D. Candrilli; Justin Carrico; Katherine A. Hicks; Eleanor Wilson; Darshan Mehta; Catherine A. Panozzo; Parinaz Ghaswalla
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Respiratory syncytial virus (RSV), influenza virus, and SARS-CoV-2 cause significant morbidity and mortality. Understanding the prevalence of underlying conditions associated with higher risk for severe RSV, influenza, or COVID-19, and demographic trends in multi-morbidity prevalence, may help inform effective interventional strategies against these respiratory infections in high-risk populations. This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) database (2017–2018) from a representative sample of US adults (≥20 years). Of 239 million surveyed adults, 44.5% had ≥1 underlying condition associated with higher risk of severe RSV, influenza, or COVID-19; this proportion increased to 72.2% of adults if 2 additional underlying conditions were also considered (hypertension and smoking; both associated risk factors for severe COVID-19). Among older adults (≥60 years), the majority had ≥1 underlying condition associated with higher risk for severe RSV, influenza, or COVID-19. Across different racial/ethnic groups, overall prevalence of ≥2 conditions was highest among individuals of Other Race (including multiracial) at 19.5%, followed by non-Hispanic Black (18.9%), non-Hispanic White (18.5%), Mexican-American/Other Hispanic (10.3%), and non-Hispanic Asian individuals (7.7%). Notably, non-Hispanic Black individuals had a higher prevalence of ≥1 underlying condition compared with other race/ethnicity groups across all age groups

  20. f

    Table_2_The relationship of history of psychiatric and substance use...

    • frontiersin.figshare.com
    docx
    Updated Jun 8, 2023
    + more versions
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    María P. Aranda; Jiaming Liang; Xinhui Wang; Lon S. Schneider; Helena C. Chui (2023). Table_2_The relationship of history of psychiatric and substance use disorders on risk of dementia among racial and ethnic groups in the United States.DOCX [Dataset]. http://doi.org/10.3389/fpsyt.2023.1165262.s002
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    docxAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Frontiers
    Authors
    María P. Aranda; Jiaming Liang; Xinhui Wang; Lon S. Schneider; Helena C. Chui
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

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ArcGIS Living Atlas Team (2017). Predominant Non White or Hispanic Adult Citizen Population [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/6cec02b9243b4ad2af4f4e6fc2057b69

Predominant Non White or Hispanic Adult Citizen Population

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Dataset updated
Jul 20, 2017
Dataset authored and provided by
ArcGIS Living Atlas Team
Area covered
Description

This map shows the predominant non white or Hispanic population of citizens age 18+ in the United States and Puerto Rico. The map is available for states, counties, tracts, and block groups increasing in detail as you zoom in.The color of the features represent the different ethnicities African American, American Indian or Alaska Native, American Indian and White, Asian, African American and White, Asian and White, Native Hawaiian, American Indian and African American, and Remainder of Two or More Race Responses. The size represents the amount of people who reported their race to the census.The data source is the US Census Bureau Voting Age Population by Citizenship and Race (CVAP) tabulation from the 2012-2016 American Community Survey 5 year estimates. More information can be found here.

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