Long-term prognosis of cardiometabolic diseases among U.S. workers: The contribution of shift work to mortality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Shift work is a known risk factor for cardiometabolic diseases (CMD), including cardiovascular diseases (CVD) and diabetes. However, limited evidence exists on the long-term prognosis of individuals already diagnosed with CMD, particularly regarding mortality outcomes following continued exposure to shift work. This study aimed to investigate the prospective association between shift work and mortality outcomes, including all-cause, CMD, and CVD mortality, among U.S. workers with CMD. Methods: The data of 2010 and 2015 National Health Interview Survey (NHIS) were linked to mortality records from the National Death Index through December 31, 2019. A total of 9,622 workers with CMD were included. Shift work exposure was self-reported usual work schedules and categorized as shift versus regular daytime work. Cox proportional hazards models were performed, with adjustment for baseline demographic information, socioeconomic status, and occupational characteristics. Results: At baseline, 25.7 % (2,470) reported shift work. During follow-up period, 308 deaths in the non-shift work group (100 CMD deaths and 90 CVD deaths) and 129 deaths in the shift work group (50 CMD deaths and 43 CVD deaths) were documented. Shift work was associated with a higher risk of all-cause mortality (HR=1.28, 95 % CI=1.02, 1.62), CMD mortality (HR=1.57, 95 % CI=1.01, 2.42), and CVD mortality (HR=1.61, 95 % CI=1.02, 2.53), adjusting for baseline covariates. Conclusions: Among U.S. workers with CMD, shift work was associated with substantially higher risks of all-cause and cause-specific mortality, highlighting the need to consider occupational exposures in clinical care and workplace policies to support secondary prevention for workers with CMD.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it