19 datasets found
  1. Distribution of blood types in the U.S. as of 2024, by ethnicity

    • statista.com
    Updated Mar 18, 2025
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    Statista (2025). Distribution of blood types in the U.S. as of 2024, by ethnicity [Dataset]. https://www.statista.com/statistics/1203831/blood-type-distribution-us-by-ethnicity/
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    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The most common blood type among the population in the United States is O-positive. Around 53 percent of the Latino-American population in the U.S. has blood type O-positive, while only around 37 percent of the Caucasian population has this blood type. The second most common blood type in the United States is A-positive. Around 33 percent of the Caucasian population in the United States has A-positive blood type. Blood type O-negative Those with blood type O-negative are universal donors as this type of blood can be used in transfusions for any blood type. O-negative blood type is most common in the U.S. among Caucasian adults. Around eight percent of the Caucasian population has type O-negative blood, while only around one percent of the Asian population has this blood type. Only around seven percent of all adults in the United States have O-negative blood type. Blood Donations The American Red Cross estimates that someone in the United States needs blood every two seconds. However, only around three percent of age-eligible people donate blood yearly. The percentage of adults who donated blood in the United States has not fluctuated much for the past two decades. In 2021, around 15 percent of U.S. adults donated blood, the same share reported in the year 2003.

  2. Distribution of blood types in the U.S. as of 2023

    • statista.com
    Updated Mar 18, 2025
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    Statista (2025). Distribution of blood types in the U.S. as of 2023 [Dataset]. https://www.statista.com/statistics/1112664/blood-type-distribution-us/
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    Dataset updated
    Mar 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The eight main blood types are A+, A-, B+, B-, O+, O-, AB+, and AB-. The most common blood type in the United States is O-positive, with around 38 percent of the population having this type of blood. However, blood type O-positive is more common in Latino-Americans than other ethnicities, with around 53 percent of Latino-Americans with this blood type, compared to 47 percent of African Americans and 37 percent of Caucasians. Blood donation The American Red Cross estimates that every two seconds someone in the United States needs blood or platelets, highlighting the importance of blood donation. It was estimated that in 2021, around 6.5 million people in the U.S. donated blood, with around 1.7 million of these people donating for the first time. Those with blood type O-negative are universal blood donors, meaning their blood can be transfused for any blood type. Therefore, this blood type is the most requested by hospitals. However, only about seven percent of the U.S. population has this blood type. Blood transfusion Blood transfusion is a routine procedure that involves adding donated blood to a patient’s body. There are many reasons why a patient may need a blood transfusion, including surgery, cancer treatment, severe injury, or chronic illness. In 2021, there were around 10.76 million blood transfusions in the United States. Most blood transfusions in the United States occur in an inpatient medicine setting, while critical care accounts for the second highest number of transfusions.

  3. Blood groups of the French, according to the Rh system

    • statista.com
    Updated Jul 14, 2025
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    Statista (2025). Blood groups of the French, according to the Rh system [Dataset]. https://www.statista.com/statistics/764507/groups-blood-division-rh-la-france/
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    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    France
    Description

    This statistic illustrates the distribution of blood groups in the French population, according to the Rhesus system. It shows that less than *** percent of French people had the blood group AB negative.

  4. f

    Geometric Mean (95% CI) of FVIII/VWF Ratio in ABO Blood Groups*.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 3, 2023
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    Jaewoo Song; Fengju Chen; Marco Campos; Doug Bolgiano; Katie Houck; Lloyd E. Chambless; Kenneth K. Wu; Aaron R. Folsom; David Couper; Eric Boerwinkle; Jing-fei Dong (2023). Geometric Mean (95% CI) of FVIII/VWF Ratio in ABO Blood Groups*. [Dataset]. http://doi.org/10.1371/journal.pone.0132626.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jaewoo Song; Fengju Chen; Marco Campos; Doug Bolgiano; Katie Houck; Lloyd E. Chambless; Kenneth K. Wu; Aaron R. Folsom; David Couper; Eric Boerwinkle; Jing-fei Dong
    License

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

    Description

    Top row: unadjusted values; bottom row (shaded): values adjusted for age, smoking, BMI, diabetes, and hypertension (race and gender were also included for overall population; race in the gender-specific analyses and gender in the race-specific analyses)Geometric Mean (95% CI) of FVIII/VWF Ratio in ABO Blood Groups*.

  5. f

    Transplant center assessment of the inequity in the kidney transplant...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    pdf
    Updated May 31, 2023
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Transplant center assessment of the inequity in the kidney transplant process and outcomes for the Indigenous American patients [Dataset]. http://doi.org/10.1371/journal.pone.0207819
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    pdfAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    BackgroundThe goal is to determine the delays and reduced rates of kidney transplant (KTx) for the Indigenous Americans and variables predictive of these outcomes at a large single transplant center.Methods300 Indigenous Americans and 300 non-Hispanic white American patients presenting for KTx evaluation from 2012–2016 were studied.ResultsCompared to whites, the Indigenous Americans had the following: more diabetes, dialysis, physical limitation and worse socioeconomic characteristics(p

  6. e

    Differential DNA methylation in Latino population

    • ebi.ac.uk
    Updated Feb 28, 2016
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    Esteban Burchard (2016). Differential DNA methylation in Latino population [Dataset]. https://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-77716
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    Dataset updated
    Feb 28, 2016
    Authors
    Esteban Burchard
    Description

    (1) In clinical practice and biomedical research populations are often divided categorically into distinct racial and ethnic groups. In reality, these categories comprise diverse groups with highly heterogeneous histories, cultures, traditions, religions, as well as social and environmental exposures. While the factors captured by these categories contribute to clinical practice and biomedical research, the use of race/ethnicity is widely debated. As a response to this debate, genetic ancestry has been suggested as a complement or alternative to this categorization. However, few studies have examined the effect of genetic ancestry, racial/ethnic identity, and environmental exposures on biological processes. Herein, we examine the contribution of self-identification within ethnicity, genetic ancestry, and environmental exposures on epigenetic modification of DNA methylation, a phenomenon affected by both genetic and environmental factors. We typed over 450,000 variably methylated CpG sites in primary whole blood of 573 individuals of Mexican and Puerto Rican descent who also had high-density genotype data. We found that methylation levels at a large number of CpG sites were significantly associated with ethnicity even when adjusting for genetic ancestry. In addition, we found an enrichment of ethnicity-associated sites amongst loci previously associated with environmental and social exposures. Interestingly, one of the strongest associated sites is driven by the Duffy Null blood type variant, demonstrating a new function of the locus in lymphocytes. Overall, the methylation changes associated with race/ethnicity, driven by both genes and environment, highlight the importance of measuring and accounting for both self-identified race/ethnicity and genetic ancestry in clinical and biomedical studies and the benefits of studying diverse populations. (2) In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell-types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) for the correction of cell-type heterogeneity in EWAS. ReFACTor does not require knowledge of the cell counts, and it obtains improved estimates of the cell-type composition, resulting in improved power and control for false positives in EWAS. Bisulphite converted DNA from 573 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip and a complete blood count with automated white blood cell differential was performed by automated flow cytometry for 95 of the samples.

  7. f

    Demographics and clinical risk factors for the Indigenous and white...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 1, 2023
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Demographics and clinical risk factors for the Indigenous and white Americans. [Dataset]. http://doi.org/10.1371/journal.pone.0207819.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    Demographics and clinical risk factors for the Indigenous and white Americans.

  8. Effect Size (%) of Covariates for FVIII activity and FVIII/VWF ratio.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated May 31, 2023
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    Jaewoo Song; Fengju Chen; Marco Campos; Doug Bolgiano; Katie Houck; Lloyd E. Chambless; Kenneth K. Wu; Aaron R. Folsom; David Couper; Eric Boerwinkle; Jing-fei Dong (2023). Effect Size (%) of Covariates for FVIII activity and FVIII/VWF ratio. [Dataset]. http://doi.org/10.1371/journal.pone.0132626.t005
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jaewoo Song; Fengju Chen; Marco Campos; Doug Bolgiano; Katie Houck; Lloyd E. Chambless; Kenneth K. Wu; Aaron R. Folsom; David Couper; Eric Boerwinkle; Jing-fei Dong
    License

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

    Description
    • Semipartial ω2 is the proportion of variability explained by each factor.a Model was defined as log FVIII = log VWF + ABO + environmental covariates (age, BMI, hypertension, diabetes, ever smoking status, and combination of race and gender).b Model was defined as log FVIII/VWF ratio = ABO + environmental covariates (age, BMI, hypertension, diabetes, ever smoking status, and combination of race and gender).Effect Size (%) of Covariates for FVIII activity and FVIII/VWF ratio.
  9. f

    Socioeconomic and psychosocial factors for the Indigenous and white...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 4, 2023
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Socioeconomic and psychosocial factors for the Indigenous and white Americans. [Dataset]. http://doi.org/10.1371/journal.pone.0207819.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    Socioeconomic and psychosocial factors for the Indigenous and white Americans.

  10. f

    Kidney transplant process outcomes between the two groups.

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated May 31, 2023
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Kidney transplant process outcomes between the two groups. [Dataset]. http://doi.org/10.1371/journal.pone.0207819.t004
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    Kidney transplant process outcomes between the two groups.

  11. Univariate and multivariate time to event analysis for predicting the...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 2, 2023
    + more versions
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Univariate and multivariate time to event analysis for predicting the likelihood of placement on the UNOS waitlist after kidney transplant evaluationa. [Dataset]. http://doi.org/10.1371/journal.pone.0207819.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    Univariate and multivariate time to event analysis for predicting the likelihood of placement on the UNOS waitlist after kidney transplant evaluationa.

  12. Differences in delays in the kidney transplant process between the two...

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Differences in delays in the kidney transplant process between the two groups. [Dataset]. http://doi.org/10.1371/journal.pone.0207819.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    Differences in delays in the kidney transplant process between the two groups.

  13. Multivariate linear regression analysis showing determinants of delays at...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated May 31, 2023
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    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman (2023). Multivariate linear regression analysis showing determinants of delays at various steps in the kidney transplant process. [Dataset]. http://doi.org/10.1371/journal.pone.0207819.t005
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mira T. Keddis; Amit Sharma; Muneeb Ilyas; Nan Zhang; Hasan Khamash; Scott J. Leischow; Raymond L. Heilman
    License

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

    Description

    Multivariate linear regression analysis showing determinants of delays at various steps in the kidney transplant process.

  14. Univariate and multivariate analysis for phototherapy treatment, and TSB >...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Adrian Castillo; Tristan R. Grogan; Grace H. Wegrzyn; Karrie V. Ly; Valencia P. Walker; Kara L. Calkins (2023). Univariate and multivariate analysis for phototherapy treatment, and TSB > 95th and TSB > 75th percentile. [Dataset]. http://doi.org/10.1371/journal.pone.0197888.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Adrian Castillo; Tristan R. Grogan; Grace H. Wegrzyn; Karrie V. Ly; Valencia P. Walker; Kara L. Calkins
    License

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

    Description

    Univariate and multivariate analysis for phototherapy treatment, and TSB > 95th and TSB > 75th percentile.

  15. The estimated effect of age, location, race, and education on ln(TL) by...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 7, 2023
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    Arline T. Geronimus; John Bound; Colter Mitchell; Aresha Martinez-Cardoso; Linnea Evans; Landon Hughes; Lisa Schneper; Daniel A. Notterman (2023). The estimated effect of age, location, race, and education on ln(TL) by specimen type. [Dataset]. http://doi.org/10.1371/journal.pone.0255237.t005
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    xlsAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Arline T. Geronimus; John Bound; Colter Mitchell; Aresha Martinez-Cardoso; Linnea Evans; Landon Hughes; Lisa Schneper; Daniel A. Notterman
    License

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

    Description

    The estimated effect of age, location, race, and education on ln(TL) by specimen type.

  16. f

    Table1_Comparing Genetic and Socioenvironmental Contributions to Ethnic...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 9, 2023
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    Shashwat Deepali Nagar; Andrew B. Conley; Shivam Sharma; Lavanya Rishishwar; I. King Jordan; Leonardo Mariño-Ramírez (2023). Table1_Comparing Genetic and Socioenvironmental Contributions to Ethnic Differences in C-Reactive Protein.XLSX [Dataset]. http://doi.org/10.3389/fgene.2021.738485.s002
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    xlsxAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    Frontiers
    Authors
    Shashwat Deepali Nagar; Andrew B. Conley; Shivam Sharma; Lavanya Rishishwar; I. King Jordan; Leonardo Mariño-Ramírez
    License

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

    Description

    C-reactive protein (CRP) is a routinely measured blood biomarker for inflammation. Elevated levels of circulating CRP are associated with response to infection, risk for a number of complex common diseases, and psychosocial stress. The objective of this study was to compare the contributions of genetic ancestry, socioenvironmental factors, and inflammation-related health conditions to ethnic differences in C-reactive protein levels. We used multivariable regression to compare CRP blood serum levels between Black and White ethnic groups from the United Kingdom Biobank (UKBB) prospective cohort study. CRP serum levels are significantly associated with ethnicity in an age and sex adjusted model. Study participants who identify as Black have higher average CRP than those who identify as White, CRP increases with age, and females have higher average CRP than males. Ethnicity and sex show a significant interaction effect on CRP. Black females have higher average CRP levels than White females, whereas White males have higher average CRP than Black males. Significant associations between CRP, ethnicity, and genetic ancestry are almost completely attenuated in a fully adjusted model that includes socioenvironmental factors and inflammation-related health conditions. BMI, smoking, and socioeconomic deprivation all have high relative effects on CRP. These results indicate that socioenvironmental factors contribute more to CRP ethnic differences than genetics. Differences in CRP are associated with ethnic disparities for a number of chronic diseases, including type 2 diabetes, essential hypertension, sarcoidosis, and lupus erythematosus. Our results indicate that ethnic differences in CRP are linked to both socioenvironmental factors and numerous ethnic health disparities.

  17. f

    Incidence of stroke typesa and ischemic stroke sub-types by race/ethnicity.

    • plos.figshare.com
    xls
    Updated Jun 6, 2023
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    Tefera Gezmu; Dona Schneider; Kitaw Demissie; Yong Lin; Martin S. Gizzi (2023). Incidence of stroke typesa and ischemic stroke sub-types by race/ethnicity. [Dataset]. http://doi.org/10.1371/journal.pone.0108901.t005
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    Dataset updated
    Jun 6, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tefera Gezmu; Dona Schneider; Kitaw Demissie; Yong Lin; Martin S. Gizzi
    License

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

    Description

    aOn average less than 3% of data was missing. Missing data was largely among Hispanics and ranged from 1.2 to 2.9%.bP-values from chi-square tests for overall race/ethnicity effect followed by pairwise comparison between race/ethnicities. A significant level of 0.05 was used for the overall race/ethnicity comparisons. Bonferroni adjustments created a significance level of 0.05/2 = 0.025 (since South Asians were to each race/ethnicity at a time).cIschemic stroke classification scheme from the Trial of ORG 10172 in Acute Stroke Treatment (TOAST).Incidence of stroke typesa and ischemic stroke sub-types by race/ethnicity.

  18. f

    Influence of socioeconomic status on the whole blood transcriptome in...

    • figshare.com
    docx
    Updated Jun 1, 2023
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    Amadou Gaye; Gary H. Gibbons; Charles Barry; Rakale Quarells; Sharon K. Davis (2023). Influence of socioeconomic status on the whole blood transcriptome in African Americans [Dataset]. http://doi.org/10.1371/journal.pone.0187290
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Amadou Gaye; Gary H. Gibbons; Charles Barry; Rakale Quarells; Sharon K. Davis
    License

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

    Description

    BackgroundThe correlation between low socioeconomic status (SES) and poor health outcome or higher risk of disease has been consistently reported by many epidemiological studies across various race/ancestry groups. However, the biological mechanisms linking low SES to disease and/or disease risk factors are not well understood and remain relatively under-studied. The analysis of the blood transcriptome is a promising window for elucidating how social and environmental factors influence the molecular networks governing health and disease. To further define the mechanistic pathways between social determinants and health, this study examined the impact of SES on the blood transcriptome in a sample of African-Americans.MethodsAn integrative approach leveraging three complementary methods (Weighted Gene Co-expression Network Analysis, Random Forest and Differential Expression) was adopted to identify the most predictive and robust transcriptome pathways associated with SES. We analyzed the expression of 15079 genes (RNA-seq) from whole blood across 36 samples.ResultsThe results revealed a cluster of 141 co-expressed genes over-expressed in the low SES group. Three pro-inflammatory pathways (IL-8 Signaling, NF-κB Signaling and Dendritic Cell Maturation) are activated in this module and over-expressed in low SES. Random Forest analysis revealed 55 of the 141 genes that, collectively, predict SES with an area under the curve of 0.85. One third of the 141 genes are significantly over-expressed in the low SES group.ConclusionLower SES has consistently been linked to many social and environmental conditions acting as stressors and known to be correlated with vulnerability to chronic illnesses (e.g. asthma, diabetes) associated with a chronic inflammatory state. Our unbiased analysis of the blood transcriptome in African-Americans revealed evidence of a robust molecular signature of increased inflammation associated with low SES. The results provide a plausible link between the social factors and chronic inflammation.

  19. f

    Descriptive statistics for blood pressure.

    • plos.figshare.com
    xls
    Updated Jun 14, 2023
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    Ben Carey; Colleen Anne Dell; James Stempien; Susan Tupper; Betty Rohr; Eloise Carr; Maria Cruz; Sharon Acoose; Peter Butt; Lindsey Broberg; Lisa Collard; Logan Fele-Slaferek; Cathie Fornssler; Donna Goodridge; Janet Gunderson; Holly McKenzie; Joe Rubin; Jason Shand; Jane Smith; Jason Trask; Kerry Ukrainetz; Simona Meier (2023). Descriptive statistics for blood pressure. [Dataset]. http://doi.org/10.1371/journal.pone.0262599.t016
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    xlsAvailable download formats
    Dataset updated
    Jun 14, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ben Carey; Colleen Anne Dell; James Stempien; Susan Tupper; Betty Rohr; Eloise Carr; Maria Cruz; Sharon Acoose; Peter Butt; Lindsey Broberg; Lisa Collard; Logan Fele-Slaferek; Cathie Fornssler; Donna Goodridge; Janet Gunderson; Holly McKenzie; Joe Rubin; Jason Shand; Jane Smith; Jason Trask; Kerry Ukrainetz; Simona Meier
    License

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

    Description

    Descriptive statistics for blood pressure.

  20. Not seeing a result you expected?
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Statista (2025). Distribution of blood types in the U.S. as of 2024, by ethnicity [Dataset]. https://www.statista.com/statistics/1203831/blood-type-distribution-us-by-ethnicity/
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Distribution of blood types in the U.S. as of 2024, by ethnicity

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Dataset updated
Mar 18, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

The most common blood type among the population in the United States is O-positive. Around 53 percent of the Latino-American population in the U.S. has blood type O-positive, while only around 37 percent of the Caucasian population has this blood type. The second most common blood type in the United States is A-positive. Around 33 percent of the Caucasian population in the United States has A-positive blood type. Blood type O-negative Those with blood type O-negative are universal donors as this type of blood can be used in transfusions for any blood type. O-negative blood type is most common in the U.S. among Caucasian adults. Around eight percent of the Caucasian population has type O-negative blood, while only around one percent of the Asian population has this blood type. Only around seven percent of all adults in the United States have O-negative blood type. Blood Donations The American Red Cross estimates that someone in the United States needs blood every two seconds. However, only around three percent of age-eligible people donate blood yearly. The percentage of adults who donated blood in the United States has not fluctuated much for the past two decades. In 2021, around 15 percent of U.S. adults donated blood, the same share reported in the year 2003.

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