Warmer summer nocturnal surface air temperatures and cardiovascular disease death risk: a population-based study
Bibliographic record
Abstract
BACKGROUND: In recent summers, some populous mid-latitude to high-latitude regions have experienced greater heat intensity, more at night than by day. Such warming has been associated with increased cause-specific adult mortality. Sex-specific and age-specific associations between summer nocturnal surface air temperatures (SAT) and cardiovascular disease (CVD) deaths have yet to be established. METHODS: A monthly time series analysis (June-July, 2001-2015) was performed on sex-specific CVD deaths in England and Wales of adults aged 60-64 and 65-69 years. Using negative binomial regression with autocorrelative residuals, associations between summer (June-July) nocturnal SAT anomalies (primary exposure) and CVD death rates (outcome) were computed, controlling for key covariates. To explore external validity, similar associations with respect to CVD death in King County, Washington, USA, also were calculated, but only for men aged 60-64 and 65-69 years. Results are reported as incidence rate ratios. RESULTS: From 2001 to 2015, within these specific cohorts, 39 912 CVD deaths (68.9% men) were recorded in England and Wales and 488 deaths in King County. In England and Wales, after controlling for covariates, a 1°C rise in anomalous summer nocturnal SAT associated significantly with a 3.1% (95% CI 0.3% to 5.9%) increased risk of CVD mortality among men aged 60-64, but not older men or either women age groups. In King County, after controlling for covariates, a 1°C rise associated significantly with a 4.8% (95% CI 1.7% to 8.1%) increased risk of CVD mortality among those <65 years but not older men. CONCLUSION: In two mid-latitude regions, warmer summer nights are accompanied by an increased risk of death from CVD among men aged 60-64 years.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".