Assessment of the effect of cold and hot temperatures on mortality in Ontario, Canada: a population-based study
Bibliographic record
Abstract
BACKGROUND: Ambient high temperature is associated with death; however, heat-related risk of death has not been quantified systematically in Ontario, the most populous province in Canada. Less is known about cold-related risk in this population. Our objective was to quantify the health impact from cold and hot temperatures in Ontario. METHODS: The study population consisted of all residents of Ontario who died between Jan. 1, 1996, and Dec. 31, 2010, from any nonaccidental cause. A case-crossover analysis was applied to assess the relation between daily temperature fluctuation and deaths from nonaccidental and selected causes in cold (December-February) and warm (June-August) seasons, respectively, adjusting for various potential confounders. Risk estimates were obtained for each census division, then pooled across Ontario. We examined potential effect modification for selected comorbidities and sociodemographic characteristics. RESULTS: In warm seasons, each 5°C increase in daily mean temperature was associated with a 2.5% increase in nonaccidental deaths (95% confidence interval [CI] = 1.3% to 3.8%) on the day of exposure (lag 0). In cold seasons, each 5°C decrease in daily temperature was associated with a 3.0% (95% CI 1.8% to 4.2%) increase in nonaccidental deaths, which persisted over 7 days (lag 0-6). The cold-related effects (lag 0-6) were stronger for cardiovascular-related deaths (any cardiovascular death: 4.1%, 95% CI 2.3% to 5.9%; ischemic heart disease: 5.8%, 95% CI 3.6% to 8.1%), especially among people less than 65 years of age (8.0%, 95% CI 3.0% to 13.0%). Conversely, heat most strongly increased respiratory-related deaths during admission to hospital (26.0%, 95% CI 0% to 61.4%). Across Ontario, each 5°C change in daily temperature was estimated to induce 7 excess deaths per day in cold seasons and 4 excess deaths in warm seasons. INTERPRETATION: Heat contributed to excess deaths in Ontario, although the effect of cold weather appeared to be greater. Further work is required to better define high-risk subgroups, which might include the homeless and people with inadequately heated housing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".