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Enregistrement W2899661629 · doi:10.1161/circ.137.suppl_1.017

Abstract 017: Friends Make Children Less Sedentary but Neighborhoods Make Them More Active

2018· article· en· W2899661629 sur OpenAlexaffabout
Tracie A. Barnett, Mélanie Henderson

Notice bibliographique

RevueCirculation · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiovascular Health and Risk Factors
Établissements canadiensUniversité de MontréalInstitut National de la Recherche Scientifique
Organismes subventionnairesnon disponible
Mots-clésMedicineObesityDemographyLogistic regressionCohortChildhood obesityPhysical activityGerontologyPhysical therapyOverweight

Résumé

récupéré en direct d'OpenAlex

Background and Purpose: Sedentary behavior (SB) and physical inactivity are distinct constructs for which separate research and intervention paradigms may be warranted. To this end, we compared individual- and neighborhood-level risk factors of each among youth at risk of obesity. Methods: Data are from QUALITY, a cohort study of the natural history of obesity in Quebec, Canada. Baseline data were obtained in 2005-2008 when children were aged 8-10y (n=512 families). Activity level was measured using accelerometers at age 8-10y and again 2 years later at age 10-12y. At each time point, children were categorized as inactive if they did <60 min/day of moderate to vigorous physical activity (PA) and as excessively sedentary if they recorded <100 counts/min for > 50% of the day. Children were required to have worn the device for at least 4 days and for at least 10 hours/day. Child-level factors included sex, sleep duration, and weekly frequency seeing friends; neighborhood-level factors included density of fast food outlets, convenience stores, and parks; school proximity, street connectivity, land use mix, disorder, social and material deprivation, and parental perceived safety. Separate logistic regression models were estimated for each of inactivity and excessive SB. We tested models using the identical set of baseline risk factors at both time points. Analyses were restricted to 413 children with complete data at age 8-10y, and to 283 children with complete data at age 10-12y. Models controlled for child’s obesity status, father and mother’s obesity status, and parental education. Results: At both time points, girls were 75% to 85% more likely to be inactive than boys, but were equally likely to be excessively sedentary as were boys. Also at both time points, each additional weekly outing with friends reduced the likelihood of being sedentary by 20%, but did not reduce the likelihood of being inactive. Only area-level disorder was associated with being excessively sedentary, and only in 10-12y olds; in contrast, several factors increased the likelihood of being inactive, including area deprivation at age 8-10y (OR: 1.7; 1.0-3.0) and perceived lack of safety at age 10-12y (OR: 2.8: 1.1-6.3). Moreover, the likelihood of being inactive decreased by 24% for each quintile increase in land use mix. Although obesity status in children was strongly associated with outcomes in all models, other determinants were unaffected by its inclusion in the models. Conclusions: Our findings suggest that physical inactivity and sedentary behavior are driven by largely distinct paradigms. Each of these may be impacted through increases in light PA. Although interventions need to target all spheres of influence, reducing physical inactivity may be more effectively mediated by features of the built environment, while leveraging social and peer groups may be more effective to reduce sedentary behaviors.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,166
Score d'incertitude au seuil0,684

Scores Codex et Gemma par catégorie

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

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 Opus0,026
Tête enseignante GPT0,289
Écart entre enseignants0,263 · 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 tête enseignante, pas un consensus.

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

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
Publié2018
Routes d'admission2
Résumé présentoui

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