Physical Activity during Adolescence and Early Adulthood and Breast Cancer Risk before Age 40 Years
Bibliographic record
Abstract
BACKGROUND: Breast cancer incidence is increasing in women under age 40, underscoring the need for research on breast cancer risk factors for younger women. METHODS: We used data from an international family cohort (n = 26,348) to examine whether recreational physical activity (RPA) during adolescence and early adulthood is associated with breast cancer risk before age 40. The cohort includes 2,502 women diagnosed with breast cancer before age 40, including 2,408 diagnosed before study enrollment (68% within 5 years of enrollment). Women reported their average hours per week of moderate and strenuous RPA during adolescence (12-17 years) and early adulthood (25-34 years), which were converted to total age-adjusted metabolic equivalents per week and categorized into quartiles. We conducted attained age analyses until age 40 (follow-up time began at age 18) using Cox proportional hazards regression models adjusted for study center, race and ethnicity, and education. RESULTS: Being in the highest versus lowest quartile of RPA during adolescence and early adulthood were respectively associated with 12% [HR (95% confidence interval, or CI), 0.88 (0.78-0.98)] and 16% [HR (95% CI), 0.84 (0.74-0.95) lower breast cancer risks before age 40. Being in the highest quartile of RPA during both adolescence and early adulthood (Pearson correlation = 0.52) versus neither time point was associated with a 22% lower risk [HR (95% CI), 0.78 (0.68-0.89)]. CONCLUSIONS: Findings suggest that RPA during adolescence and early adulthood may lower breast cancer risk before age 40. IMPACT: Policies promoting physical activity during adolescence and early adulthood may be important for reducing the growing burden of breast cancer in younger women.
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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 | 0.000 | 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 | 0.000 | 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".