The Physiology behind the Epidemiology of Heat-Related Health Impacts
Bibliographic record
Abstract
A direct consequence of climate change is the intensification of hot weather and extreme heat events that are epidemiologically associated with a greater risk of heat-related illnesses and other adverse health outcomes, often resulting in subsequent hospital admissions and mortality. The health risks associated with hot weather directly arise from the body's physiological responses (i.e., heat strain) to heat exposure. The magnitude of heat strain experienced and the extent of heat strain required to cause an adverse health outcome can be modulated by personal characteristics and the adoption of protective behaviors. This review presents the pathophysiological mechanisms responsible for the epidemiological association between heat exposure and a greater risk of heat illnesses (e.g., heat exhaustion, heatstroke), adverse cardiovascular events, and acute kidney injury or failure. These mechanisms are framed within the larger context that defines heat-related health risks, and we provide examples and perspectives of how physiologists are uniquely positioned to contribute to risk reduction and adaptation efforts to protect humans against the adverse health impacts of heat, while maintaining optimum well-being and performance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".