Trends in age and red blood cell donation habits among several racial/ethnic minority groups in the United States
Bibliographic record
Abstract
BACKGROUND: To meet the needs of a diverse patient population, an adequate supply of red blood cells (RBCs) from ethnic/racial minority donors is essential. We previously described the 10-year changes in minority blood donation in the United States. This study describes donation patterns by donor status, age, and race/ethnicity. STUDY DESIGN AND METHODS: Data on the age and the number of unique black/African American, Hispanic/Latino, Asian, and white RBC donors were obtained from eight US blood collectors for 2006, 2009, 2012, and 2015. Donors self-identified their race/ethnicity. First-time (FT) and repeat (R) donors were analyzed separately. RESULTS: Overall, for both FT and R donor groups, whites constituted the majority of unique donors (FT 66.7% and R 82.7%) and also donated the greatest proportion of RBC units (FT 66.6% and R 83.8%). Donors less than 20 years old comprised the greatest proportion of FT donors for all racial/ethnic groups (39.2%) and had the highest mean number of RBC donations per donor (1.12) among FT donors. Conversely, R donors less than 20 years old had some of the lowest mean number of RBC donations per donor (1.55) among R donors, whereas R donors at least 60 years old had the highest mean (1.88). Year by year, the percentage of FT donors who were less than 20 years old increased for all race/ethnicities. For R donors, whites were more frequently older, while Hispanics/Latinos and Asians were younger. CONCLUSIONS: Greater efforts to convert FT donors less than 20 years into R donors should be undertaken to ensure the continued diversity of the blood supply.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".