Association between fetal famine exposure and risk of type 2 diabetes: a prospective cohort study
Bibliographic record
Abstract
The objective of this study was to explore the effects of fetal experience of famine on the onset of type 2 diabetes mellitus (T2DM) in adults. The analysis included 16 594 participants from the Kailuan Study who were free of diabetes at baseline (2006). According to the date of birth, the individuals born on October 1, 1962 – September 30, 1964, were divided into the non-exposed group (used as the reference group), individuals born on October 1, 1959 – September 30, 1961, were divided into the fetal exposure group, and the early childhood exposure group included those born on October 1, 1956 – September 30, 1958. The cumulative incidence of T2DM for each group was calculated and compared among the 3 groups, and the Cox regression model was used to analyze the effects of fetal famine experience on the risk of diabetes. During a median 10.27 years (170 358 person-years) (2006–2017), 3509 incident T2DM cases were identified, with a cumulative incidence rate of 19.46%. The cumulative incidences of T2DM in the non-exposed, fetal exposure, and early childhood exposure groups were 17.38%, 20.85%, and 20.65%, respectively (P < 0.01). After adjusting for confounding factors, the hazard ratio (HR) of T2DM in the fetal exposure group was 1.222 (95% confidence interval: 1.087–1.374, P < 0.01), compared with the reference group. The association was modified by sex and hypertension (both P interaction less than 0.05). Fetal famine exposure may increase the risk of developing T2DM in adults. This association was more pronounced among women and those with hypertension. Novelty: The association was modified by sex and hypertension. Long follow-up time.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".