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Enregistrement W2309239137 · doi:10.1093/eurpub/ckw030

The association between long working hours and metabolic syndrome remains elusive

2016· letter· en· W2309239137 sur OpenAlexaboutno aff
Adriano Marçal Pimenta, Miguel Ángel Martínez‐González

Notice bibliographique

RevueEuropean Journal of Public Health · 2016
Typeletter
Langueen
DomaineHealth Professions
ThématiqueWorkplace Health and Well-being
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAssociation (psychology)Metabolic syndromeMedicinePediatricsInternal medicinePsychologyObesity

Résumé

récupéré en direct d'OpenAlex

In the SUN longitudinal study with 6845 university graduates followed-up for 8.3 years, we found that long working hours did not exhibit any association with an increased risk of MetS. 1 Recently, a cross-sectional study including 466 female employees from two hospitals in Ontario, Canada, reported that full-time work status, extended shift length, and working ≥ 35 paid overtime hours/year were associated with higher risk of MetS. 2 Another cross-sectional study with 4,456 employees in Korea reported no significant differences in the prevalence of MetS according to weekly working hours. 3 These studies had a cross-sectional design, which does not guarantee the temporal sequence for this association. We appreciate the comments on our article by Dr. Kawada. However, it should be consider that (1) Though MetS increases the risk for cardiovascular disease (CVD), not all subjects with MetS will eventually develop cardiovascular events; they are two different entities; (2) No study evaluating the association between long working hours and MetS was quoted by Kawada. Indeed, an important meta-analysis concluded that employees who work for long hours (≥ 55 h/week) have a higher risk of stroke than those working standard hours (< 35 h/week), but the association with coronary heart disease (CHD) was weaker. 4 Moreover, when the analysis was stratified by the occupational socioeconomic status, long working hours increased the risk of CHD only in participants in the low socioeconomic status group; (3) Other labour exposure factors were used to justify the association between long working hours and CVD such as job strain, shift work and sleep restriction. We believe that, beyond the quantification of working hours, further characteristics of the work should also be considered because some of these conditions might be strongly associated with MetS or CVD. As previously cited, Kivimäki et al.4 reported that workers in low socioeconomic status had a higher risk of CHD. Canuto et al.5 reported that higher educational level was protective against MetS in 902 fixed-shift Brazilian workers. It has been proposed that ‘blue collar workers’ have a greater risk of negative health events than ‘white collar workers’. Occupations which require more challenging and mentally active work may have a protective effect against negative health events, because the professional is less affected by job strain. Thus, the lack of association between long working hours and MetS in our study could be explained because the SUN cohort included only highly educated individuals that, generally, are white collar workers; (4) It was suggested that our results could be explained by lack of the adjustment for sleep parameters and other potential confounders. Additionally, we adjusted our results for sleep duration. Long working hours were not significantly associated with MetS; (5) Finally, we used the same cut-off points proposed by Kiwimäki et al.4 in their study to categorize working hours. Once again, long working hours were not related to MetS after multivariate adjustment. Thus, we reinforce our conclusion that long working hours did not increase the risk of MetS development in highly educated subjects with white collar jobs. Spanish Government (Grants PI01/0619, PI030678, PI040233, PI042241, PI050976, PI070240, PI070312, PI081943, PI080819, PI1002658, PI1002293, PND2010/87, RD06/0045and G03/140), the Navarra Regional Government (36/2001, 43/2002, 41/2005, 36/2008 and 45/2011) and the University of Navarra. Conflicts of interest : None declared. Key point Long working hours did not increase the risk of MetS development in highly educated subjects with white collar jobs.

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)0,003
score de la tête « metaresearch » (Gemma)0,019
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 enseignants0,009
Score d'incertitude au seuil0,016

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,019
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0090,010
Charge utile insuffisante (le modèle a refusé de juger)0,0040,002

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 Opus0,065
Tête enseignante GPT0,355
Écart entre enseignants0,289 · 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

Citations3
Publié2016
Routes d'admission1
Résumé présentoui

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