Gravidity is not associated with telomere length in a biracial cohort of middle-aged women: The Coronary Artery Risk Development in Young Adults (CARDIA) study
Bibliographic record
Abstract
OBJECTIVE: Having experienced 2-3 births is associated with reduced mortality versus women with <2 or ≥4 births. The effect of 2-3 births on lifespan may be associated with delayed cellular aging. We hypothesized telomere length, a marker of cellular aging, would be longer in women who had 2-3 pregnancies. METHODS: Leukocyte telomere length was measured using quantitative real-time polymerase chain reaction in 620 women in CARDIA at the year 15 and 20 exams, expressed as the ratio of telomere repeat copy number to single-copy gene copy number (T/S). Number of pregnancies at the time of telomere length measurement was obtained (mean age = 41±0.1 years, average gravidity = 2.64±0.1 pregnancies). Participants were divided into 4 groups by number of pregnancies: 0, 1, 2-3, and ≥4, to test for differences in telomere length by gravidity group. RESULTS: The mean and SD for telomere length was 0.98 ± 0.20 T/S in the whole cohort. There were no differences in mean telomere length between groups; 0.98±0.02 T/S in women with 0 pregnancies, 1.01±0.02 T/S in women with 1 pregnancy, 0.97±0.01 T/S in women with 2-3 pregnancies, and 0.99±0.02 T/S in women with ≥4 pregnancies (p = 0.51). We defined high-risk (shorter) telomere length as ≤25th percentile, and low-risk (longer) telomere length as ≥75 percentile. There were no differences in the prevalence of high-risk or low-risk telomere length between gravidity groups. CONCLUSIONS: Gravidity was not associated with telomere length in early middle age; the protective association of 2-3 births may act through other mechanisms.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".