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Enregistrement W4238712761 · doi:10.1093/aje/kwx357

THE AUTHORS REPLY

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

Notice bibliographique

RevueAmerican Journal of Epidemiology · 2017
Typeletter
Langueen
DomaineMedicine
ThématiquePhysical Activity and Health
Établissements canadiensHôpital du Saint-SacrementSt. Michael's HospitalInstitute for Clinical Evaluative SciencesInstitute for Work & HealthPublic Health OntarioUniversity of Toronto
Organismes subventionnairesDepartment of Family and Community Medicine, University of TorontoCanadian Institutes of Health Research
Mots-clésMedicine

Résumé

récupéré en direct d'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.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,063
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,125
Score d'incertitude au seuil0,046

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,063
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0020,001
Études des sciences et des technologies0,0080,006
Communication savante0,0090,005
Science ouverte0,0040,005
Intégrité de la recherche0,1250,099
Charge utile insuffisante (le modèle a refusé de juger)0,0110,013

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.

Tête enseignante Opus0,109
Tête enseignante GPT0,423
Écart entre enseignants0,314 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission2
Résumé présentnon

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