Investigating Cortisol Production, Pattern, and Variability as Mediators in the Relationship Between Shift Work and Cardiometabolic Risk
Bibliographic record
Abstract
Background: Shift work has emerged as a risk factor for many diseases, particularly cardiovascular disease (CVD). While the pathway by which shift work increases CVD risk is still not fully understood, it is hypothesized that disruption of cortisol during night work is an intermediate. Objective: To determine whether quantity of cortisol production, diurnal pattern, and cortisol variability mediate the relationship between current shift work status and cardiometabolic risk among female hospital employees. Methods: A cross-sectional study was conducted with 326 female employees (166 rotating shift workers and 160 day workers) at Kingston General Hospital in Ontario, Canada. Participants completed a baseline interview, questionnaire, and clinical exam, and provided urine samples over two 24-hour cycles (included one-night shift for the shift workers). Diurnal quantity of cortisol production (AUCG), cortisol pattern (AUCI), and the magnitude of variation for both AUCG and AUCI was determined across the two cycles using creatinine-adjusted urinary cortisol. Two measures of cardiometabolic risk (CMR) were used: metabolic syndrome (MetS) based on the 2009 Joint Interim Studies consensus statement, and a continuous CMR score created by Hillier and colleagues (2006). Results: Current shift workers are more likely to have MetS than dayworkers (21% vs. 12%, respectively, OR: 2.41, 95% CI: 1.25-4.64) and have a higher CMR score (β: 0.45, 95% CI: 0.12-0.78). Shift work is also associated with a lower average AUCG and a higher magnitude of variation in AUCI, but not with average AUCI or magnitude of variation in AUCG. Average AUCG is a partial mediator in the relationship between shift work and CMR, as measured with the CMR score. There is no evidence that AUCI or either magnitude of variation are intermediates between shift work and CMR. Conclusions: Current rotating shift workers have a lower quantity of cortisol production, a higher magnitude of variation in pattern, a higher CMR score, and a higher odds of MetS in comparison to day workers. Quantity of cortisol production is a partial mediator in the relationship between current shift work and CMR. Future studies warrant the consideration of other potential mediators in the causal pathway between shift work and CVD risk.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".