A cross-sectional study of different patterns of oral contraceptive use among premenopausal women and circulating IGF-1: implications for disease risk
Bibliographic record
Abstract
BACKGROUND: Insulin-like growth factor-1 (IGF-1) is important in normal growth, development, and homeostasis. Current use of oral contraceptives (OC) decreases IGF-1 concentrations; however, the effect of past use, age/timing of use, and type of OC used on IGF-1 levels is unknown. OC are the most commonly used form of birth control worldwide. Both IGF-1 and OC use have been linked to premenopausal breast and colorectal cancers, osteoporosis and cardiovascular disease (CVD). Understanding the effects of different patterns of OC use on IGF-1 levels may offer insight into its influence on disease risk in young women. METHODS: In a cross-sectional study of 328 premenopausal women ages 18 to 21 and 31 to 40 we examined the relationship between different patterns of OC use and circulating IGF-1 using adjusted linear regression analysis. Information on OC use was obtained through an interviewer administered questionnaire. Plasma IGF-1 was assessed with enzyme linked immunosorbent assay (ELISA). RESULTS: Among women aged 18 to 21, ever OC use was significantly associated with decreased IGF-1 levels compared to never use (β = -57.2 ng/ml, 95% confidence interval (CI): -88.7, -25.8). Among women aged 31 to 40, past users who first used OC at 25 years of age or older (β = 43.8 ng/ml, 95% CI: 8.8, 78.8), in the last 15 years (β = 35.1 ng/ml, 95% CI: 9.3, 61.0) or after 1995 (β = 46.6 ng/ml, 95% CI: 13.4, 79.8) had significantly higher IGF-1 levels compared to never users. CONCLUSION: This is the first study to highlight the long term effects of OC use after cessation on IGF-1 levels among premenopausal women, which previously were thought to be transitory. Future studies of past use and IGF-1 levels are required and must consider age/timing of use and type/generation of OC used. Additional studies are needed to confirm the potential mediation of IGF-1 levels in the links between OC use and health outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".