Variation in heat-related mortality risks: a longitudinal global analysis
Bibliographic record
Abstract
Background/Aim: The analysis of temporal variation in heat and cold related mortality is important in understanding potential population adaptation to temperature effects. While studies have examined temporal changes in specific locations, no study has provided an assessment at a global scale. In this contribution, we used a two-stage longitudinal design to evaluate and describe the reduction of the heat-related mortality (HRM) in 37 countries. Methods: We collected daily time series of mortality and mean temperature between 1990 and 2016 in 725 locations nested in 37 countries . For each city, we fitted a quasi-Poisson model with distributed lag non-linear model for temperature (lag 3 days) in 3-year subsets of the data. At the second-stage we used multilevel-multivariate meta-regression models to evaluate the effects of time-periods and countries on the derived set of splines coefficients. The modelled splines coefficients were used to estimate country and period specific 99th percentile relative risk (RR) relative to country-specific median daily temperature and heat-related attributable fractions (AF%). Results: The multilevel-multivariate meta-regression indicated that heat-related mortality risk trend is heterogeneous across countries (p<0.001). A declining trend of heat-related AF% (yearly AF% change) was found for Switzerland (-0.17%), Netherlands (-0.09%), France (-0.06%), Spain (-0.05%), Portugal (-0.05%), Japan (-0.05%) and US (-0.014%), Australia (-0.07%), South Korea (-0.04%), Brazil (-0.04%), Norway (-0.02%), Canada (-0.03%), Mexico (-0.03%), Germany (-0.02%); while a tendency for an increasing trend was observed in UK (+0.02%), Finland (+0.10), Estonia (+0.05), Peru (+0.32%) Chile (+0.31%), Italy (+0.05%) and Greece (+0.22%). Conclusion: We found that while HRM reduced in some populations over time, other populations experienced little or no attenuation in heat related risk. Understanding this heterogeneity can give valuable insights into potential differences in adaptation, important for public health planning and policy in the context of climate change. On behalf of the MCC Collaborative Research Network
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".