The effect of shift work on eating habits: a systematic review
Bibliographic record
Abstract
Objective This systematic review aimed to evaluate the association between shift work and eating habits. Methods The protocol was registered in PROSPERO (number 42015024680). PubMed, EMBASE, Scopus, and Web of Science were searched for published reports. Of 2432 identified articles, 33 observational studies met the inclusion criteria. Their methodological approaches were assessed using the Newcastle-Ottawa Scale. Data were extracted using a standardized form. Studies were considered to have a low or a high risk of bias according to a percentage score of quality. Results The majority of the studies presented a quality score of <70% and a high risk of bias for comparability, sample selection and non-respondents. Shift workers show changes in meal patterns, skipping more meals and consuming more food at unconventional times. They also show higher consumption of unhealthy foods, such as saturated fats and soft drinks. Conclusions This review suggests that shift work can affect the quality of workers' diets, but new studies, especially longitudinal studies, which examine the time of exposure to shift work, the duration of the workday and sleep patterns, are necessary to confirm this association.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".