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Record W4238712761 · doi:10.1093/aje/kwx357

THE AUTHORS REPLY

2017· letter· en· W4238712761 on OpenAlexafffund
Peter Smith, Huiting Ma, Richard H. Glazier, Mahée Gilbert‐Ouimet, Cameron Mustard

Bibliographic record

VenueAmerican Journal of Epidemiology · 2017
Typeletter
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsHôpital du Saint-SacrementSt. Michael's HospitalInstitute for Clinical Evaluative SciencesInstitute for Work & HealthPublic Health OntarioUniversity of Toronto
FundersDepartment of Family and Community Medicine, University of TorontoCanadian Institutes of Health Research
KeywordsMedicine

Abstract

fetched live from OpenAlex

We thank Drs. LeBlanc and Chaput for their letter (1) regarding our recent study on prolonged standing at work and heart disease in Canada (2). Their letter suggests that our finding that prolonged occupational standing is associated with an increased risk of heart disease is simply spurious, and that further adjustment for dietary patterns and occupation would explain our results. Of course, unobserved confounding is always a threat in observational epidemiology. It is also an easy explanation for any finding that goes against someone’s preconceived understanding of a field of research. However, we do not believe that further accounting for dietary patterns and some additional measure of occupation would appreciably change the hazard ratios presented in our paper. For dietary patterns to be a confounder of importance, this variable would need to not only be a risk factor for heart disease but also be associated with prolonged standing (and this not be because diet is a consequence of prolonged standing). While it is unlikely that dietary patterns result in the types of jobs people hold, it is possible that other upstream factors (such as opportunities to engage in healthy behaviors) might lead to an association between employment in occupations requiring prolonged standing and dietary patterns associated with worse health. However, this same mechanism also links prolonged standing to leisure-time physical activity, smoking, and obesity. We note that while adjustment for these factors reduced the hazard ratio for prolonged standing, it did not explain the relationship observed. It is unlikely that additional adjustment for dietary patterns would offer any meaningful further attenuation. It is also true that people engaged in prolonged-standing occupations and those engaged in prolonged-sitting occupations might differ in other ways inside and outside of work. LeBlanc and Chaput are incorrect when they assert that we did not adjust for occupational demands and education in the same model (1). As we clearly explained in the footnotes of Table 2 (2), all adjustments in the models were in addition to the adjustments made in previous models. Further, as we explained in the paper (2), initial regression models also included other occupational exposures (e.g., exposure to dangerous chemical substances, noise, etc.), which are also associated with blue-collar occupations. Because these variables were not associated with our main predictor or outcome, we removed them from the model to reduce bias due to unnecessary adjustment (3). In addition, contrary to the assertion of LeBlanc and Chaput (1), low-skilled occupations were also fairly evenly distributed across all occupational exposure groups in our study (i.e., not all sitting occupations are high-skilled occupations). LeBlanc and Chaput are also incorrect when they assert that our paper promotes sedentary behavior at work (1). It does not. In fact, the extra energy expended while standing is not much greater than that associated with sitting (4). This might explain the modest effects that even potentially unfeasible sit-stand routines have on cardiovascular markers (5). Rather, our paper is trying to shine a light on the health effects of prolonged standing at work, without opportunities to sit. That prolonged standing may be a health risk need not be counterintuitive, as it is biologically plausible (6) and has been demonstrated in other studies (see our original paper (2) for additional citations). Further, the risks of prolonged standing were recognized in the original recommendations about prolonged sitting at work (7) but unfortunately have been largely overlooked to date. Continuing to overlook these risks in an effort to make messages simpler than they should be is a disservice to those workers who have to endure prolonged standing, which is often unnecessary (8), as part of their job. P.S. was supported through a Research Chair in Gender, Work & Health from the Canadian Institutes of Health Research. R.H.G. was supported as a Clinician Scientist in the Department of Family and Community Medicine at the University of Toronto and at St. Michael’s Hospital. M.G.-O. was supported through a postdoctoral fellowship from the Canadian Institutes of Health Research. Conflict of interest: none declared.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.125
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.063
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0080.006
Scholarly communication0.0090.005
Open science0.0040.005
Research integrity0.1250.099
Insufficient payload (model declined to judge)0.0110.013

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.

Opus teacher head0.109
GPT teacher head0.423
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2017
Admission routes2
Has abstractno

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