Effect of a Web-Based Nutritional and Physical Activity Intervention With Email Support (the EDDY Program) on Primary School Children’s BMI Z-Score During the COVID-19 Pandemic: Intervention Study
Notice bibliographique
Résumé
Background: COVID-19 mitigation measures enhanced increases in children's weight and BMI due to decreased physical activity and increased energy intake. Overweight and obesity were major worldwide problems before the pandemic, and COVID-19 increased their severity even more. High BMI directly correlates with health disadvantages including cardiovascular diseases, musculoskeletal disorders, and mental health diseases. Therefore, it is vitally important to develop counteracting interventions to maintain children's health during exceptional situations like pandemics. However, worldwide data from such interventions are limited, and to our knowledge, no suitable study has been carried out during the pandemic in Austria. Objective: This study was conducted to examine a 15-week web-based intervention with email support, the EDDY (Effect of Sports and Diet Trainings to Prevent Obesity and Secondary Diseases and to Influence Young Children's Lifestyle) program and the effect of nutritional education and physical activity on children's BMI z-score during the COVID-19 pandemic in Vienna, Austria. Methods: The intervention consisted of 3 weekly videos-2 physical activity and 1 nutritional education video, respectively-and a biweekly email newsletter for the parents. This study was conducted in a Viennese primary school from February to June 2021 by a team of physicians, nutritionists, and sports scientists, including both professionals and students. The study population included an intervention group (who received web-based nutritional and physical activity training) and a control group (who received no intervention), comprising in total 125 children aged 8 to 11 years. Due to COVID-19 mitigation measures, the control group was a comparative group observed during the prior school year (2019-2020). Anthropometric measurements were obtained before and after the intervention in both groups. Results: Due to a high dropout rate (n=57, 45.6%) because of the mitigation measures, there were 41 children in the intervention group and 27 in the control group. At baseline, the BMI z-score was 1.0 (SD 1.1) in the intervention group and 0.6 (SD 1.2) in the control group (P=.17). After the study period, the BMI z-score decreased by 0.06 (SD 0.21) in the intervention group, whereas it increased by 0.17 (SD 0.34) in the control group (P<.001). Comparing the change in BMI z-scores within BMI categories in the intervention group and control group revealed a statistically significant difference in the normal-weight children (P=.006). Further results showed that the decrease in BMI z-score was significant in the intervention group among both boys (P=.004) and girls (P=.01). Conclusions: A web-based intervention with combined nutritional education and physical activity training might be an adequate tool to lessen the enhanced increase in body weight during a pandemic. Therefore, additional studies with greater sample sizes and different locations are needed. As the implementation of such intervention programs is essential, further studies need to be established rapidly.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».