Influence of environmental temperature on risk of gestational diabetes
Bibliographic record
Abstract
BACKGROUND: Cold-induced thermogenesis is known to improve insulin sensitivity, which may become increasingly relevant in the face of global warming. The aim of this study was to examine the relation between outdoor air temperature and the risk of gestational diabetes mellitus. METHODS: We identified all births in the Greater Toronto Area from 2002 to 2014 using administrative health databases. Generalized estimating equations were used to examine the relation between the mean 30-day outdoor air temperature before the time of gestational diabetes mellitus screening and the likelihood of diagnosis of gestational diabetes mellitus based on a validated algorithm using hospital records and physician service claims. RESULTS: Over the 12-year period, there were 555 911 births among 396 828 women. Prevalence of gestational diabetes mellitus was 4.6% among women exposed to extremely cold mean outdoor air temperatures (≤ -10°C) in the 30-day period before screening and increased to 7.7% among those exposed to hot mean 30-day temperatures (≥ 24°C). Each 10°C increase in mean 30-day temperature was associated with a 1.06 (95% confidence interval [CI] 1.04-1.07) times higher odds of gestational diabetes mellitus, after adjusting for maternal age, parity, neighbourhood income quintile, world region and year. A similar effect was seen for each 10°C rise in outdoor air temperature difference between 2 consecutive pregnancies for the same woman (adjusted odds ratio 1.06, 95% CI 1.03-1.08). INTERPRETATION: In our setting, there was a direct relation between outdoor air temperature and the likelihood of gestational diabetes mellitus. Future climate patterns may substantially affect global variations in the prevalence of diabetes, which also has important implications for the prevention and treatment of gestational diabetes mellitus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".