Racial discrimination and telomere shortening among African Americans: The Coronary Artery Risk Development in Young Adults (CARDIA) Study.
Bibliographic record
Abstract
OBJECTIVE: Telomeres are protective sequences of DNA capping the ends of chromosomes that shorten over time. Leukocyte telomere length (LTL) is posited to reflect the replicative history of cells and general systemic aging of the organism. Chronic stress exposure leads to accelerated LTL shortening, which has been linked to increased susceptibility to and faster progression of aging-related diseases. This study examined longitudinal associations between LTL and experiences of racial discrimination, a qualitatively unique source of minority psychosocial stress, among African Americans. METHOD: Data are from 391 African Americans in the Coronary Artery Risk Development in Young Adults (CARDIA) Telomere Ancillary Study. We examined the number of domains in which racial discrimination was experienced in relation to LTL collected in Years 15 and 25 (Y15: 2000/2001; Y25: 2010/2011). Multivariable linear regression examined if racial discrimination was associated with LTL. Latent change score analysis (LCS) examined changes in racial discrimination and LTL in relation to one another. RESULTS: = .015). CONCLUSIONS: This study adds to evidence that racial discrimination contributes to accelerated physiologic weathering and health declines among African Americans through its impact on biological systems, including via its effects on telomere attrition. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".