Tracking Our Physical Inactivity and Progression to Death: Is This Evolutionary Stagnation?
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Résumé
Editorials3 October 2017Tracking Our Physical Inactivity and Progression to Death: Is This Evolutionary Stagnation?David A. Alter, MD, PhDDavid A. Alter, MD, PhDFrom University of Toronto, Toronto, Ontario, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M17-2181 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Progression is rarely linear. Once highly mobile hunters and gatherers, we have evolved into a technologically advanced but kinetically stagnant species. Sedentary societies define today's cultural norms (1). The adverse health outcomes associated with sedentary behavior have led many to conclude that sedentary behavior is a novel risk factor whose population-attributable risk may even surpass that of smoking (2). Others have interpreted such associations more cautiously, given inconsistencies in evidence across studies, measurement biases, residual confounding, ambiguity in explanatory intercausal pathway mechanisms, and the absence of clinical trials that are adequately powered to detect differences in mortality from sedentary interventions ...References1. Dumith SC, Hallal PC, Reis RS, Kohl HW. Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Prev Med. 2011;53:24-8. [PMID: 21371494] doi:10.1016/j.ypmed.2011.02.017 CrossrefMedlineGoogle Scholar2. Ding D, Rogers K, van der Ploeg H, Stamatakis E, Bauman AE. Traditional and emerging lifestyle risk behaviors and all-cause mortality in middle-aged and older adults: evidence from a large population-based Australian cohort. PLoS Med. 2015;12:e1001917. [PMID: 26645683] doi:10.1371/journal.pmed.1001917 CrossrefMedlineGoogle Scholar3. Young DR, Hivert MF, Alhassan S, Camhi SM, Ferguson JF, Katzmarzyk PT, et al; Endorsed by The Obesity Society. Sedentary behavior and cardiovascular morbidity and mortality: a science advisory from the American Heart Association. Circulation. 2016;134:e262-79. [PMID: 27528691] doi:10.1161/CIR.0000000000000440 CrossrefMedlineGoogle Scholar4. Diaz KM, Howard VJ, Hutto B, Colabianchi N, Vena JE, Safford MM, et al. Patterns of sedentary behavior and mortality in U.S. middle-aged and older adults. A national cohort study. Ann Intern Med. 2017;167:465-75. doi:10.7326/M17-0212 LinkGoogle Scholar5. Booth FW, Laye MJ, Lees SJ, Rector RS, Thyfault JP. Reduced physical activity and risk of chronic disease: the biology behind the consequences. Eur J Appl Physiol. 2008;102:381-90. [PMID: 17987311] CrossrefMedlineGoogle Scholar6. Hamilton MT, Etienne J, McClure WC, Pavey BS, Holloway AK. Role of local contractile activity and muscle fiber type on LPL regulation during exercise. Am J Physiol. 1998;275:E1016-22. [PMID: 9843744] MedlineGoogle Scholar7. Barnett DW, Barnett A, Nathan A, Van Cauwenberg J, Cerin E; Council on Environment and Physical Activity (CEPA)—Older Adults working group. Built environmental correlates of older adults' total physical activity and walking: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017;14:103. [PMID: 28784183] doi:10.1186/s12966-017-0558-z CrossrefMedlineGoogle Scholar8. Prince SA, Saunders TJ, Gresty K, Reid RD. A comparison of the effectiveness of physical activity and sedentary behaviour interventions in reducing sedentary time in adults: a systematic review and meta-analysis of controlled trials. Obes Rev. 2014;15:905-19. [PMID: 25112481] doi:10.1111/obr.12215 CrossrefMedlineGoogle Scholar9. Harber MP, Kaminsky LA, Arena R, Blair SN, Franklin BA, Myers J, et al. Impact of cardiorespiratory fitness on all-cause and disease-specific mortality: advances since 2009. Prog Cardiovasc Dis. 2017;60:11-20. [PMID: 28286137] doi:10.1016/j.pcad.2017.03.001 CrossrefMedlineGoogle Scholar10. Gardner B, Smith L, Lorencatto F, Hamer M, Biddle SJ. How to reduce sitting time? A review of behaviour change strategies used in sedentary behaviour reduction interventions among adults. Health Psychol Rev. 2016;10:89-112. [PMID: 26315814] doi:10.1080/17437199.2015.1082146 CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From University of Toronto, Toronto, Ontario, Canada.Disclaimer: The opinions reported in this article are those of the author and are independent from the Institute for Clinical Evaluative Sciences and the University Health Network–Toronto Rehabilitation Institute. No endorsement by Institute for Clinical Evaluative Sciences, Ontario Ministry of Health and Long-Term Care, or University Health Network–Toronto Rehabilitation Institute is intended or should be inferred.Financial Support: Dr. Alter is funded by a Chair in Cardiovascular and Metabolic Rehabilitation, University Health Network–Toronto Rehabilitation Institute, University of Toronto. The Institute for Clinical Evaluative Sciences is supported by a grant from the Ontario Ministry of Health and Long-Term Care.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M17-2181.Corresponding Author: David Alter, MD, PhD, University Health Network—Toronto Rehabilitation Institute, 347 Rumsey Road, Toronto, Ontario M4G 1R7, Canada; e-mail, [email protected]on.ca.This article was published at Annals.org on 12 September 2017. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPatterns of Sedentary Behavior and Mortality in U.S. Middle-Aged and Older Adults Keith M. Diaz , Virginia J. Howard , Brent Hutto , Natalie Colabianchi , John E. Vena , Monika M. Safford , Steven N. Blair , and Steven P. Hooker Metrics Cited bySedentary behaviour at work—an underappreciated occupational hazard? 3 October 2017Volume 167, Issue 7Page: 513-514KeywordsCohort studiesDisclosureExerciseHealth careLong-term careMedical risk factorsMortalitySedentary behaviorSkeletal musclesStroke ePublished: 12 September 2017 Issue Published: 3 October 2017 Copyright & PermissionsCopyright © 2017 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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 | 0,008 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,007 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,009 |
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 ».