A systematic review of ambient heat and sleep in a warming climate
Bibliographic record
Abstract
Abstract Background Earlier reviews documented the effects of a broad range of climate change outcomes on sleep but have not yet evaluated the effect of ambient temperature. This systematic review aims to identify and summarize the literature on ambient temperature and sleep outcomes in a warming world. Methods For this systematic review, we searched online databases (PubMed, Scopus, JSTOR, GreenFILE, GeoRef and PsycARTICLES) together with relevant journals for studies published before February 2023. We included articles reporting associations between objective indicators of ambient temperature and valid sleep outcomes measured in real-life environments. We included studies conducted among adults, adolescents, and children. A narrative synthesis of the literature was then performed. Findings The present systematic review shows that higher outdoor or indoor ambient temperatures, expressed either as daily mean or night-time temperature, are negatively associated with sleep quality and quantity worldwide. The negative effect of higher ambient temperatures on sleep is stronger in the warmest months of the year, among vulnerable populations and in the warmest areas of the world. This result appears consistent across several sleep indicators and measures. Interpretation Although this work identified several methodological limitations of the extant literature, a strong body of evidence from both this systematic review and previous experimental studies converge on the negative impact of elevated temperatures on sleep quality and quantity. In absence of solid evidence on fast adaptation to the effects of heat on sleep, rising temperatures induced by climate change pose a planetary threat to human sleep and therefore human health, performance and wellbeing.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".