THE AUTHORS REPLY
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,063 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,006 |
| Communication savante | 0,009 | 0,005 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,125 | 0,099 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,013 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».