Dietary Fibre, Insulin and Breast Tissue Composition at Age 15-18: A Mediation Analysis.
Bibliographic record
Abstract
Abstract Background. Risk of breast cancer in adult life is influenced by body size and height in childhood. The mechanisms responsible for these associations are currently unknown. The present research was carried out to determine if, at age 15-18, measures of dietary intake were associated with body size, hormones and growth factors, and with variations in breast tissue composition that in adult life are strongly associated with risk of breast cancer.Methods. We carried out a cross-sectional study in 766 healthy young Caucasian women aged 15-18. Percent breast water (PBW), total breast water and fat were measured by magnetic resonance (MR). Dietary intake at age 15-18 was assessed using a validated food frequency questionnaire. We also measured height, weight, skin-fold thicknesses and waist-to-hip ratio, and obtained fasting blood to assay glucose and insulin, and calculated an estimate of insulin sensitivity (HOMA2-S). Results. After adjustment for age, measures of body size, and energy intake, dietary fiber (insoluble and total fiber) was associated positively with PBW with the HOMA2-S estimate of insulin sensitivity, and inversely with fasting serum insulin. Insulin sensitivity was also significantly and positively associated with PBW and inversely with total breast fat. The association of dietary fiber with breast tissue composition was no longer statistically significant after adjustment for fasting insulin or insulin sensitivity. Conclusions. These results show an association of dietary fiber with breast tissue measures and suggest that this association may be mediated, at least in part, by insulin or insulin sensitivity. These findings suggest a potential approach to breast cancer prevention in early life.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".