RF-14 The Association between Shift Work, Mental Health and Cardiometabolic Health in the Atlantic PATH Cohort
Bibliographic record
Abstract
<h3>Introduction</h3> Contemporary work environments increasingly rely upon a 24-hour work cycle resulting in more employees exposed to shift work. Thirty percent of working age Canadians work evening, night and rotating shifts. Compared to regular daytime work, shift work has the potential for disturbing sleep patterns and disrupting circadian rhythms with adverse health effects. <h3>Methods</h3> A population health study was conducted with 4,155 shift workers and 8,258 non-shift workers from the Atlantic PATH cohort. Linear and logistic regression models were used to assess the differences in i) self-reported mental health measures between shift workers and non-shift workers and ii) anthropometric measures (body adiposity) and self-reported cardiometabolic disease outcomes (obesity, diabetes, and cardiovascular disease). <h3>Results</h3> Shift workers reported higher levels of each of the mental health domains. There was a significant increased risk of depression (OR=1.13, 95% CI, 1.00–1.27) and poor self-rated health (OR=1.13, 95% CI, 1.14–1.55) among shift workers compared to non-shift workers. There was a significant increased risk of cardiovascular disease, obesity, and diabetes among shift workers despite higher levels of physical activity and lower levels of sedentary behaviour compared to matched controls. Shift workers were 17% more likely to be obese (95% CI 7–27) and 27% more likely to have diabetes (95% CI 8–51). <h3>Conclusions</h3> Shift work is associated with cardiometabolic health and mental health, as well as depression. The association between shift work and cardiometabolic health was independent of body mass index for cardiovascular disease and diabetes, and independent of fat mass index for diabetes. Subsequently, shift workers have an increased risk of developing other chronic disease.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".