A cohort study of reproductive risk factors, weight and weight change and the development of diabetes mellitus
Bibliographic record
Abstract
AIMS: Reproductive factors (parity, miscarriages, terminations), oral contraceptive use, hormone replacement therapy, body weight at first pregnancy and weight gain following pregnancy may be associated with a long-term risk of diabetes. The aim of this study is to investigate the independent risks of reproductive factors and body weight for diabetes in later life. METHODS: This is a retrospective cohort study of 1257 parous women who had a first pregnancy between 1951 and 1970. Reproductive history, weight and height were measured at the time of first pregnancy, then assessed by questionnaire in 1997 for all women. A clinical examination and an analysis of blood samples were undertaken for 992 women. The main outcome was incidence of diabetes based on medical history, medication and random glucose measurement. RESULTS: Sixty of the 1257 (4.8%) women developed diabetes. Body mass index at index pregnancy and after 28-48 years follow-up were both significantly associated with risk of diabetes, this increased with greater weight gain. There was a non-significant increased risk of diabetes associated with stillbirths and miscarriages after age and BMI adjustment. CONCLUSIONS: In parous women, higher BMI at index pregnancy, weight gain during follow-up and BMI in later life strongly predict diabetes risk.
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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 | 0.001 |
| 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 | 0.001 |
| 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".