Early-life famine exposure may modify the association between long-term temperature variability and cardio-cerebrovascular diseases: a nationwide study
Bibliographic record
Abstract
Abstract We aimed to evaluate whether the association between long-term temperature variability (TV) and cardio-cerebrovascular diseases (CCVDs) was affected by famine exposure in different age stages. We used data from the fourth national urban and rural elderly population survey (2015). Participants were categorized into six groups based on their age at famine exposure (famine exposure under age 5, between ages 5 and 18, and during adulthood) and the severity (severely affected areas versus mildly affected areas) of the Great Chinese Famine (1959–1961) in their province of residence. Mixed-effects logistic regression model was used to quantify the association between long-term TV and the prevalence of CCVDs across six famine-exposed groups. A total of 222 179 participants were included. In severely affected areas, the odds ratio (OR) of CCVDs associated with per 1 °C increase in 5 year average TV were 1.07 (95% confidence interval [CI]: 1.02, 1.13) for those exposed to famine during adulthood, 1.28 (95% CI: 1.17, 1.40) under the age of 5 years. Urban residence, higher education, increased household income, and more frequent physical activity could mitigate the association between TV and CCVDs, particularly among those exposed to severe famine before the age of 5. Individuals exposed to famine before the age of 5 are more susceptible to TV-related CCVDs compared to those exposed during adulthood. Our findings highlight the importance of early-life nutrition in lowering susceptibility to CCVDs later in life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".