Weight Change and the Risk of Late-Onset Breast Cancer in the Original Framingham Cohort
Bibliographic record
Abstract
OBJECTIVE: Adult weight gain has been associated with a twofold risk of postmenopausal breast cancer. Data are limited regarding whether weight gain at specific periods of marked changes in estrogen- and insulin-related hormones have different risk associations. This study assesses the relation of adult weight change overall and at specific, hormonally relevant times with diagnosis of a first breast cancer after age 55 (late onset). METHODS: Framingham study data were used to assess premenopausal (25-44 yr), perimenopausal (45-55 yr), postmenopausal (after 55 yr), and adult lifetime (from 25 yr) weight change in relation to late-onset breast cancer in 2,873 women followed for up to 48 yr, with 206 late-onset breast cancers. RESULTS: Adult lifetime weight gain was associated with an increased risk of late-onset breast cancer (P trend = 0.046). Weight gain during specific time periods was not associated with breast cancer. Data suggested a possible decreased risk of breast cancer with weight loss from ages 25 to 44 and 45 to 55 yr (relative risk = 0.4 [0.2-1.2] and 0.5 [0.3-0.9], respectively). CONCLUSION: These data confirm prior reports of an association between adult lifetime weight gain and increased risk of late-onset breast cancer and support current recommendations to avoid adult weight gain.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".