Prevalence and Recent Trends in Exposure to Night Shiftwork in Canada
Bibliographic record
Abstract
OBJECTIVES: Night shiftwork has been linked to various health outcomes. Knowing where and to what extent workers are exposed to this type of shiftwork can help prioritize areas for intervention and further study. This study describes recent estimates of exposure to night shiftwork in Canada for 2011, and temporal trends from 1997 to 2010. METHODS: Estimates by occupation, industry, province, and sex were calculated using data from the Survey of Labour and Income Dynamics (SLID) from 1996 to 2011. Workers who reported rotating or regular night shifts were classified as exposed to shiftwork involving nights, while those reporting other types of shiftwork, outside of regular daytime and evening shifts, were classified as possibly exposed. Results, with 97.5% confidence intervals (CIs), were summarized for three exposure categories: exposed workers, possibly exposed workers, and evening shift workers. Trends in 3-year rolling averages were described. RESULTS: In 2011, approximately 1.8 million Canadians (97.5% CI, 1.7-1.8 million), or 12% of the working population (97.5% CI, 11-12%), were exposed to night shiftwork; 45% were female. An additional 2.6 million were possibly exposed (97.5% CI, 2.5-2.7 million workers), and 745 000 worked evening shifts (97.5% CI, 701 000-792 000). This amounts to 17% (97.5% CI, 17-18%) and 4.9% (97.5% CI, 4.6-5.2%) of the labour force, respectively. Industries with the highest prevalence were accommodation and food services (20%; 97.5% CI, 18-22%), forestry, fishing, mining, oil, and gas (19%; 97.5% CI, 16-23%), and healthcare and social assistance (18%; 97.5% CI, 17-19%). By occupation, the highest prevalence of exposure was in occupations in protective services (37%; 97.5% CI, 32-42%), professional occupations in health (35%; 97.5% CI, 32-39%), and machine operators and assemblers in manufacturing (24%; 97.5% CI, 22-28%). The overall number of exposure workers increased by 29% from 1997 to 2010, but the overall proportion remained relatively the same (11% and 12%, respectively). The proportion of female workers exposed increased by 2%. CONCLUSIONS: These estimates characterize exposure to night shiftwork in Canada. Continued collection of shiftwork data, with greater detail on scheduling, workplace and personal factors, is needed for high-quality surveillance and investigations of shiftwork and health.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".