The Consequences of Sedentary Behaviors: Keeping Interpretations Anchored in Evidence
Notice bibliographique
Résumé
Research on the health consequences of certain sedentary behaviors and excessive sedentary time has increased in recent years and is commanding increased attention in public health and exercise science-related research (1,2). The Sedentary Behavior Research Network recently published an article reporting the findings from a global terminology consensus project where standardized definitions of key terms used in sedentary behavior research were presented, with the hope of further advancing research in this new field (3). There is clear evidence of enthusiasm in this area of research, and the sensibility of both a temporal trend toward increased sedentary time in contemporary lifestyles and the presumed negative health consequence of such a trend are intuitive and seemingly opportunistic. But are these sensibilities supported by robust scientific evidence? Or has the field of study gotten ahead of itself? Are we overinterpreting the existing evidence base? Are the relations more complex than previously conceptualized? In this issue of Exercise and Sport Sciences Reviews (ESSR), Professor Stuart Biddle and colleagues provide a brief review critically examining the evidence that sedentary behavior is causally related to adiposity in young people (4). They argue that despite some consistency of the evidence supporting the observation that increased sedentary behavior/screen/TV time is associated with undesirable adiposity measures in young people, the magnitude of the relations is usually small, based predominantly on associational research, and inconsistent between reported and direct measure methods and often fails to control or account for important factors (e.g., physical activity, diet, sleep) that could mediate or moderate the relations observed. The authors conclude that the current evidence does not support a causal association between sedentary behaviors and adiposity in young people, and they propose a conceptual model illustrating the complexity of this relation. Although the authors restrict their discussion to childhood obesity and adiposity, they remind us of the need to ensure that our research rhetoric does not supersede the underlying evidence. Sedentary behavior research is in its infancy, or at best childhood, and although seems to be a plausible, prominent, and pervasive public health threat, there is some concern that related guidelines, recommendations, and messages may be ahead of the evidence supporting them. In addition to the caution conveyed by Biddle et al. (4), a recent American Heart Association Advisory (1) concluded that “further evidence is required to better inform public health interventions and future quantitative guidelines on sedentary behavior and cardiovascular health outcomes.” A comprehensive review by Prince et al. (5) “identifies the need for longitudinal studies, as well as further research on factors in the physical, social, and policy environments” and “recognizes the need to standardize methodology for collecting, defining, and reporting sedentary behavior and correlates.” Ekelund et al. (6) concluded that 60–75 min·d−1 of moderate-intensity physical activity may eliminate the increased risk of death associated with excessive sitting in adults but does not eliminate the elevated risk associated with high TV-viewing time specifically. The collective evidence is structurally weak if not equivocal. Balancing the demand for public health guidance in relation to sedentary behaviors with the current state of the evidence is a challenge, and much more experimental research, with measures of the fidelity of interventions, is required. Nevertheless, as Biddle et al. (4) agree, the current approach of discouraging excessive sedentary behaviors, especially TV time, is sensible and the likelihood of benefit exceeds the risk of harm. Mark S. Tremblay Healthy Active Living and Obesity (HALO) Research Group Children’s Hospital of Eastern Ontario Research Institute Ottawa, ON, Canada
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 | 0,156 | 0,371 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,003 |
| Bibliométrie | 0,014 | 0,010 |
| Études des sciences et des technologies | 0,003 | 0,026 |
| Communication savante | 0,024 | 0,040 |
| Science ouverte | 0,010 | 0,014 |
| Intégrité de la recherche | 0,016 | 0,033 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
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.
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 ».