Is Sitting Worse Than Static Standing? How a Gender Analysis Can Move Us Toward Understanding Determinants and Effects of Occupational Standing and Walking
Bibliographic record
Abstract
The Yant Award was established in 1964 to honor the contributions of William P. Yant, the first president of the American Industrial Hygiene Association. It is presented annually for outstanding contributions in industrial hygiene or allied fields to an individual residing outside the United States. The 2014 award recipient is Dr. Karen Messing, Professor emeritus, Department of Biological Sciences, Université du Québec à Montréal and Researcher, CINBIOSE Research Centre. Gender (socially determined) differences in occupations, employment, and working conditions, task assignments, and work methods that affect exposure to health risks are increasingly documented. Interactions of (biologically influenced) sex differences with workplace parameters may also influence exposure levels. During field studies, ergonomists learn a lot about gender and sex that can be important when generating and testing hypotheses about the mechanisms that link workplace exposures to health outcomes. Prolonged standing is common in North America; almost half (45%) of Québec workers spend more than three-quarters of their working time on their feet and 40% of these cannot sit at will. This posture has been linked to chronic back pain and musculoskeletal disorders (MSDs) in the lower limbs, but many health professionals suggest workers should stand rather than sit at work. We ask: (1) Given the fact that roughly the same proportion of men and women stand at work, what does a gender-sensitive analysis add to our ability to detect and thus prevent work-related MSDs?; (2) How does ergonomics research inform gender-sensitive analysis of occupational health data?; and (3) What do researchers need to know to orient interventions to improve general working postures? We have sought answers to these questions through collaborative research with specialists in epidemiology, occupational medicine, biomechanics, and physiology, carried out in partnership with public health organisations, community groups, and unions. We conclude that failure to characterize prolonged static standing and to apply gender-sensitive analysis can confuse assessment of musculoskeletal and circulatory effects of working postures. We suggest that prolonged static sitting and standing postures can and should be avoided by changes to workplace organization and environments. Research is needed to define optimal walking speeds and arrive at optimal ratios of sitting, standing, and walking in the workplace.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".