Metabolic health measurements of shift workers in a national cross‐sectional study: Results from the Canadian Health Measures Survey
Bibliographic record
Abstract
BACKGROUND: Shift work exposure may be a concern for a range of health effects, including metabolic health outcomes such as insulin resistance, high body weight, and abdominal obesity. METHODS: We analyzed shift work and indicators of metabolic health (overweight/obesity defined by body mass index, self-reported changes in body mass index (BMI) in previous 1 and 10 years, waist circumference, waist-to-hip ratio, and insulin resistance assessed by the homeostasis model assessment 2 (HOMA-2-IR)) in the cross-sectional Canadian Health Measures Survey (CHMS). We analyzed descriptive characteristics of shift workers (regular night, evening, and rotating shift) and used multivariable linear regression to examine the association between two definitions of shift work exposure and measures of metabolic health, adjusted for age, sex, daily energy expenditure, sleep, and poor dietary quality. RESULTS: 5470 anthropometry (2637 fasting) participants in CHMS Cycles 1 and 2 were included, of whom 16.5% worked regular evening, night, or rotating shifts. Shift workers were younger and slept longer hours than non-shift workers. Bivariate associations showed inverse relationships between shift work and BMI, waist circumference, waist-to-hip ratio, and HOMA-2-IR. In adjusted analyses, BMI was inversely related to shift work, and other metabolic health outcomes showed no significant associations. CONCLUSIONS: Healthy worker effects (including self-selection of exposure) could explain inverse relationships, particularly as the cross-sectional design only allowed assessment of current exposure. Key strengths include the population-based design and measurement of metabolic health indicators. Results underscore the importance of consideration of the health of shift workers following departure from the exposed population.
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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 | 0.013 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".