26 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. R

    Rhesus blood group biosynthesis

    • reactome.org
    biopax2, biopax3 +5
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    Bijay Jassal, Rhesus blood group biosynthesis [Dataset]. https://reactome.org/content/detail/R-HSA-9037628
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    owl, sbml, biopax2, sbgn, docx, biopax3, pdfAvailable download formats
    Dataset provided by
    Ontario Institute for Cancer Research
    Authors
    Bijay Jassal
    License

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

    Description

    The Rhesus (Rh) blood group system (including the Rh factor) is the second most important blood group system after the ABO blood group system. The Rh blood type was first discovered in 1937 by Karl Landsteiner and Alexander S. Wiener who named it after the rhesus macaque whose RBCs were used to generate the rabbit immune serum that first detected the human blood group system. Subsequent studies by them and Philip Levine and Rufus Stetson identified the antigen that induced this immunization as the "Rh factor" and also its association with hemolytic disease of the newborn (Levine & Stetson 1984, Landsteiner & Wiener 1941). Of the 50 defined Rh blood group antigens, five (D, C/c and E/e) are the major types expressed by the RHD and RHCE genes in the RH gene complex. Rh antigens are expressed on red cell (RBC) membranes in association with other membrane proteins and this whole complex interacts with the spectrin-based skeleton and contributes to the maintenance of the mechanical properties of the RBC membrane (Van Kim et al. 2006).

    The RHD gene produces the D antigen, the most immunogenic Rh antigen. The term "Rh factor" refers only to the D antigen; Rh positive (Rh+) individuals have the D antigen on their RBC membranes whereas Rh negative (Rh-) individuals don't. Humans are not born with antibodies towards the D antigen in their blood, they have to be exposed to it (through blood transfusion or placental exposure during pregnancy) at some point in their lives before antibodies are made against it. Once exposed, however, Rh+ individuals remain sensitive for the rest of their lives. Importantly, if individuals are Rh+ and are exposed to Rh- blood, no immune response is mounted. Anti-D antibodies are only seen if an individual is lacking the D antigen (Rh-) and is exposed to Rh+ blood. The RHCE gene produces polypeptides with C/c and E/e antigens.

    These polypeptides are the core components of their respective antigens but by themselves are devoid of the immunoreactivity which defines the Rh antigens. The remaining antigens are produced by partial deletion, recombination, mutation, or polymorphisms of one or both RHD and RHCE genes (Cartron 1999). Together, these antigens form the most complex and polymorphic blood group system based on the multitude of phenotypes that can be expressed on the RBC surface. The Fisher-Race system, the nomenclature used most commonly, uses the CDE system to depict the notation of Rh genotypes (Race 1948). The most common group of 3 genes inherited is CDe with ce (D negative) being the second most common. Rh genotyping is used in blood transfusion, paternity testing and to determine the risk of hemolytic disease of the newborn.

  5. f

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

    • plos.figshare.com
    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*.

  6. f

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

    • plos.figshare.com
    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.

  7. 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.

  8. d

    Health Survey for England

    • digital.nhs.uk
    pdf
    Updated Apr 21, 2006
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    (2006). Health Survey for England [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england
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    pdf(194.6 kB), pdf(2.2 MB), pdf(4.9 MB)Available download formats
    Dataset updated
    Apr 21, 2006
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Jan 1, 2004 - Dec 31, 2004
    Area covered
    England
    Description

    The Health Survey for England is an annual survey of the health of the population. It has an annually repeating core accompanied by different topic modules each year. The focus of the 2004 report is on the health of minority ethnic groups with an emphasis on cardiovascular disease (CVD). The report also covers the behavioural risk factors associated with CVD such as drinking, smoking and eating habits and health status risk factors such as diabetes, blood pressure, and cholesterol. For children the emphasis is on respiratory health.

  9. f

    Cardiometabolic Risk Factors by Matching Type-B Diet Scores and ABO...

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Jingzhou Wang; Bibiana García-Bailo; Daiva E. Nielsen; Ahmed El-Sohemy (2023). Cardiometabolic Risk Factors by Matching Type-B Diet Scores and ABO Genotypea. [Dataset]. http://doi.org/10.1371/journal.pone.0084749.t007
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jingzhou Wang; Bibiana García-Bailo; Daiva E. Nielsen; Ahmed El-Sohemy
    License

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

    Description

    a HDL, high density lipoprotein; LDL, low density lipoprotein; hs-CRP, high-sensitivity C-reactive protein; HOMA-IR, homeostasis model of insulin resistance; and HOMA-Beta, homeostasis model of beta-cell function. ANCOVA adjusted for age, sex, ethnicity and energy intake was used to examine the interaction effect between the ABO blood group and diet adherence on levels of cardiometabolic risk factors. The Tukey-Kramer procedure was used to adjust for multiple comparisons between groups within each ANCOVA.b Mean ± SE (all such values).

  10. f

    Risk Factors Associated with Colorectal Cancer in a Subset of Patients with...

    • plos.figshare.com
    docx
    Updated May 30, 2023
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    Abram Bunya Kamiza; Ling-Ling Hsieh; Reiping Tang; Huei-Tzu Chien; Chih-Hsiung Lai; Li-Ling Chiu; Tsai-Ping Lo; Kuan-Yi Hung; Chun-Yi Wang; Jeng-Fu You; Chao A. Hsiung; Chih-Ching Yeh (2023). Risk Factors Associated with Colorectal Cancer in a Subset of Patients with Mutations in MLH1 and MSH2 in Taiwan Fulfilling the Amsterdam II Criteria for Lynch Syndrome [Dataset]. http://doi.org/10.1371/journal.pone.0130018
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    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Abram Bunya Kamiza; Ling-Ling Hsieh; Reiping Tang; Huei-Tzu Chien; Chih-Hsiung Lai; Li-Ling Chiu; Tsai-Ping Lo; Kuan-Yi Hung; Chun-Yi Wang; Jeng-Fu You; Chao A. Hsiung; Chih-Ching Yeh
    License

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

    Area covered
    Taiwan
    Description

    Background and AimLynch syndrome, caused by germline mutations in mismatch repair genes, is a predisposing factor for colorectal cancer (CRC). This retrospective cohort study investigated the risk factors associated with the development of CRC in patients with MLH1 and MSH2 germline mutations.MethodsIn total, 301 MLH1 and MSH2 germline mutation carriers were identified from the Amsterdam criteria family registry provided by the Taiwan Hereditary Nonpolyposis Colorectal Cancer Consortium. A Cox proportional hazard model was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) to determine the association between the risk factors and CRC development. A robust sandwich covariance estimation model was used to evaluate family dependence.ResultsAmong the total cohort, subjects of the Hakka ethnicity exhibited an increased CRC risk (HR = 1.62, 95% CI = 1.09–2.34); however, those who performed regular physical activity exhibited a decreased CRC risk (HR = 0.62, 95% CI = 0.41–0.88). The CRC risk was enhanced in MLH1 germline mutation carriers, with corresponding HRs of 1.72 (95% CI = 1.16–2.55) and 0.54 (95% CI = 0.34–0.83) among subjects of the Hakka ethnicity and those who performed regular physical activity, respectively. In addition, the total cohort with a manual occupation had a 1.56 times higher CRC risk (95% CI = 1.07–2.27) than did that with a skilled occupation. Moreover, MSH2 germline mutation carriers with blood group type B exhibited an increased risk of CRC development (HR = 2.64, 95% CI = 1.06–6.58) compared with those with blood group type O.ConclusionThe present study revealed that Hakka ethnicity, manual occupation, and blood group type B were associated with an increased CRC risk, whereas regular physical activity was associated with a decreased CRC risk in MLH1 and MSH2 germline mutation carriers.

  11. f

    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
    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

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

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

    • plos.figshare.com
    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.

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

    • plos.figshare.com
    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. f

    ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors

    • plos.figshare.com
    docx
    Updated Jun 4, 2023
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    Jingzhou Wang; Bibiana García-Bailo; Daiva E. Nielsen; Ahmed El-Sohemy (2023). ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors [Dataset]. http://doi.org/10.1371/journal.pone.0084749
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    docxAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jingzhou Wang; Bibiana García-Bailo; Daiva E. Nielsen; Ahmed El-Sohemy
    License

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

    Description

    BackgroundThe ‘Blood-Type’ diet advises individuals to eat according to their ABO blood group to improve their health and decrease risk of chronic diseases such as cardiovascular disease. However, the association between blood type-based dietary patterns and health outcomes has not been examined. The objective of this study was to determine the association between ‘blood-type’ diets and biomarkers of cardiometabolic health and whether an individual's ABO genotype modifies any associations.MethodsSubjects (n = 1,455) were participants of the Toronto Nutrigenomics and Health study. Dietary intake was assessed using a one-month, 196-item food frequency questionnaire and a diet score was calculated to determine relative adherence to each of the four ‘Blood-Type’ diets. ABO blood group was determined by genotyping rs8176719 and rs8176746 in the ABO gene. ANCOVA, with age, sex, ethnicity, and energy intake as covariates, was used to compare cardiometabolic biomarkers across tertiles of each ‘Blood-Type’ diet score.ResultsAdherence to the Type-A diet was associated with lower BMI, waist circumference, blood pressure, serum cholesterol, triglycerides, insulin, HOMA-IR and HOMA-Beta (P

  15. f

    DataSheet_1_Differential Expression of HERV-W in Peripheral Blood in...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 3, 2023
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    Rachael Tarlinton; Belinda Wang; Elena Morandi; Bruno Gran; Timur Khaiboullin; Ekatarina Martynova; Albert Rizvanov; Svetlana Khaiboullina (2023). DataSheet_1_Differential Expression of HERV-W in Peripheral Blood in Multiple Sclerosis and Healthy Patients in Two Different Ethnic Groups.xlsx [Dataset]. http://doi.org/10.3389/fphar.2019.01645.s001
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    xlsxAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    Frontiers
    Authors
    Rachael Tarlinton; Belinda Wang; Elena Morandi; Bruno Gran; Timur Khaiboullin; Ekatarina Martynova; Albert Rizvanov; Svetlana Khaiboullina
    License

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

    Description

    Overexpression of the Human endogenous retrovirus W (HERV-W) group of inherited retroviruses has been consistently linked with Multiple Sclerosis (MS). However most of the studies on this link have focused on European genetic groups with a very high risk of MS and it is not clear that this relationship holds for all ethnic groups. This study examined via qPCR the RNA expression in peripheral blood of HERV-W (the multiple sclerosis associated retrovirus variant MSRV) of MS patients and healthy controls from two ethnic groups with very different risk rates of MS. Population one was derived from the UK with a Northern European genetic background and an MS risk rate of 108/100,000, population two was derived from the republic of Tatarstan, Russian Federation, with a mixed Russian (Eastern European) and Tartar (Turkic or Volga/Urals) population with an MS risk rate of 21-31/100,000. The Russian population displayed a significantly higher basal level of expression of MSRV in both healthy and MS individuals when compared to the British control population with a trend in the Russian population towards higher expression levels in MS patients than healthy patients.

  16. f

    Associations between age and SARS-CoV-2 antibodies (prevalence ratios),...

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    • +1more
    xls
    Updated Oct 8, 2024
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    Renee Bolijn; Annemieke M. W. Spijkerman; Henrike Galenkamp; Anneke Blokstra; Liza Coyer; Anders Boyd; Maria Prins; Karien Stronks (2024). Associations between age and SARS-CoV-2 antibodies (prevalence ratios), adjusted for exposure variables, by ethnicity. [Dataset]. http://doi.org/10.1371/journal.pone.0311196.t002
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    xlsAvailable download formats
    Dataset updated
    Oct 8, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Renee Bolijn; Annemieke M. W. Spijkerman; Henrike Galenkamp; Anneke Blokstra; Liza Coyer; Anders Boyd; Maria Prins; Karien Stronks
    License

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

    Description

    Associations between age and SARS-CoV-2 antibodies (prevalence ratios), adjusted for exposure variables, by ethnicity.

  17. f

    Demographic, systemic and ocular parameters among the three ethnic groups.

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Chen-Wei Pan; Jun Li; Hua Zhong; Wei Shen; Zhiqiang Niu; Yuansheng Yuan; Qin Chen (2023). Demographic, systemic and ocular parameters among the three ethnic groups. [Dataset]. http://doi.org/10.1371/journal.pone.0135913.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Chen-Wei Pan; Jun Li; Hua Zhong; Wei Shen; Zhiqiang Niu; Yuansheng Yuan; Qin Chen
    License

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

    Description

    Demographic, systemic and ocular parameters among the three ethnic groups.

  18. Linear regression of follow-up blood tests of adults from different ethnic...

    • plos.figshare.com
    xls
    Updated Oct 31, 2024
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    Sindhu Bhaarrati Naidu; Anita Saigal; Amar Jitu Shah; Chibueze Ogbonnaya; Shiuli Bhattacharyya; Karthig Thillaivasan; Songyuan Xiao; Camila Nagoda Niklewicz; George Seligmann; Heba Majed Bintalib; John Robert Hurst; Marc Caeroos Isaac Lipman; Swapna Mandal (2024). Linear regression of follow-up blood tests of adults from different ethnic groups. [Dataset]. http://doi.org/10.1371/journal.pone.0312719.t003
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    xlsAvailable download formats
    Dataset updated
    Oct 31, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Sindhu Bhaarrati Naidu; Anita Saigal; Amar Jitu Shah; Chibueze Ogbonnaya; Shiuli Bhattacharyya; Karthig Thillaivasan; Songyuan Xiao; Camila Nagoda Niklewicz; George Seligmann; Heba Majed Bintalib; John Robert Hurst; Marc Caeroos Isaac Lipman; Swapna Mandal
    License

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

    Description

    Linear regression of follow-up blood tests of adults from different ethnic groups.

  19. f

    Demographics, co-morbidities, admission and follow-up characteristics of...

    • plos.figshare.com
    xls
    Updated Oct 31, 2024
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    Sindhu Bhaarrati Naidu; Anita Saigal; Amar Jitu Shah; Chibueze Ogbonnaya; Shiuli Bhattacharyya; Karthig Thillaivasan; Songyuan Xiao; Camila Nagoda Niklewicz; George Seligmann; Heba Majed Bintalib; John Robert Hurst; Marc Caeroos Isaac Lipman; Swapna Mandal (2024). Demographics, co-morbidities, admission and follow-up characteristics of adults from different ethnic groups. [Dataset]. http://doi.org/10.1371/journal.pone.0312719.t001
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    xlsAvailable download formats
    Dataset updated
    Oct 31, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Sindhu Bhaarrati Naidu; Anita Saigal; Amar Jitu Shah; Chibueze Ogbonnaya; Shiuli Bhattacharyya; Karthig Thillaivasan; Songyuan Xiao; Camila Nagoda Niklewicz; George Seligmann; Heba Majed Bintalib; John Robert Hurst; Marc Caeroos Isaac Lipman; Swapna Mandal
    License

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

    Description

    Demographics, co-morbidities, admission and follow-up characteristics of adults from different ethnic groups.

  20. f

    Follow-up outcomes of adults from different ethnic groups.

    • plos.figshare.com
    xls
    Updated Oct 31, 2024
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    Sindhu Bhaarrati Naidu; Anita Saigal; Amar Jitu Shah; Chibueze Ogbonnaya; Shiuli Bhattacharyya; Karthig Thillaivasan; Songyuan Xiao; Camila Nagoda Niklewicz; George Seligmann; Heba Majed Bintalib; John Robert Hurst; Marc Caeroos Isaac Lipman; Swapna Mandal (2024). Follow-up outcomes of adults from different ethnic groups. [Dataset]. http://doi.org/10.1371/journal.pone.0312719.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Oct 31, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Sindhu Bhaarrati Naidu; Anita Saigal; Amar Jitu Shah; Chibueze Ogbonnaya; Shiuli Bhattacharyya; Karthig Thillaivasan; Songyuan Xiao; Camila Nagoda Niklewicz; George Seligmann; Heba Majed Bintalib; John Robert Hurst; Marc Caeroos Isaac Lipman; Swapna Mandal
    License

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

    Description

    Follow-up outcomes of adults from different ethnic groups.

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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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