Sleep duration and quality in children: interactions with food choices, energy balance, and digital screen-time
Notice bibliographique
Résumé
Introduction Chronic obesity is a complex health problem that affects millions of people globally, including many children. Childhood obesity is a multifactorial condition affected by genetic and lifestyle factors that, if ignored, can cause serious health consequences such as insulin resistance, type 2 diabetes, and cardiovascular diseases. It is essential to identify modifiable lifestyle habits associated with childhood obesity, including sleep, dietary habits, physical activity (PA), and screen time (ST). The primary objective of this pilot and feasibility study was to evaluate the viability of implementing a larger-scale interventional trial in an identical cohort. This involved assessing recruitment rate, retention, attrition, data collection procedures, protocol adherence, data management, and potential obstacles or challenges to putting the intervention approach into practice. These preliminary findings establish the groundwork for future research while providing insights into the intervention's feasibility. Methods Participants (n=22) aged 9-12 years were recruited for this pilot and feasibility study. Anthropometric measurements were performed according to the WHO guidelines. Data on the demographic characteristics and ST were collected using different questionnaires. Sleep and PA data were obtained by using both actigraphy and questionnaires. The Automated Self-Administered 24-hour Dietary Assessment Tool (Canada-2018) was used to collect and analyze the dietary intake data from two dietary recalls. Linear regression analyses were adjusted for age, sex, parental education, and household income. Results In this pilot and feasibility study, the participant recruiting method demonstrated effective involvement, resulting in a 36.7% recruitment rate. With logistical obstacles, the study retained all 22 participants, obtaining a remarkable 100% retention rate. Participants followed study guidelines, thoroughly completing multiple parts such as questionnaires, dietary recalls, and actigraphy wear. The time required to collect data ranged from 5 to 35 minutes. Among the 22 participants (10.5 ±1.2 y, 59% girls, 68% Caucasian), 52% slept for less than eight hours based on the actigraphy report. Actigraphy measurements significantly differed from child- and parent-reported sleep durations (p < 0.001). Sleep duration had a positive correlation with sugar consumption (r = 0.647, p = 0.001), while other sleep parameters did not significantly correlate with intrinsic sugar, fruit, and vegetable intake. The relationship between sleep parameters, screen time, and physical activity level showed no significant associations. Conclusion In this pilot and feasibility study, participants engaged proactively, data was collected efficiently, and research procedures were implemented effectively, highlighting the study's practicality and success. Our data indicate that more than half of the participants slept less than the Canadian recommendation. It has been shown that sleep parameters may play a role in adolescents' choices of healthy and unhealthy foods. These data suggest that sleep patterns may be the target of intervention studies and obesity prevention programs.
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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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.
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 ».