Dietary Fiber Estimate of DialBetesPlus App Users: Secondary Analysis of Data From a Randomized Controlled Trial
Notice bibliographique
Résumé
Background: Despite the importance of dietary fiber in regulating glycemic control, the reported intake among patients with type 2 diabetes (T2D) in Japan was around 12-16 g, well below the local official recommended intake of 20 g and above. Recent data is lacking, with the most recent available estimates collected between 2014 and 2019. Most mHealth dietary intervention apps for T2D focus on calorie and carbohydrate outcomes, with limited evidence on fiber intake. Fiber data was collected in a recent 12-month trial of DialBetesPlus, a multimodal diabetes mHealth self-management system that supports dietary behavior change by allowing users to record their meals and provides timely and detailed information on users' nutrient intake. Objective: This study aimed to assess the pattern of dietary fiber intake among DialBetesPlus intervention users to provide recent data. As a secondary objective, the study explored factors that may influence dietary fiber intake among participants. Methods: Meal records were extracted using the DialBetesPlus app developer dashboard. Dietary fiber intake was measured for all intervention participants. The analysis included only data from participants with complete (breakfast, lunch, and dinner) meal records for at least 7 days. We calculated the average dietary fiber intake and fiber density per day by first averaging across all participants for each day, then averaging these daily values over 1 year. We averaged fiber intake per meal type across all days with available data for each participant, without excluding incomplete meal record days. Results: Out of 66 participants from the intervention group who were assigned to the DialBetesPlus intervention, 47 (71.2%) had at least 7 days of complete meal records and were included in the analysis. A 1-year trend analysis revealed a slight upward trend of daily fiber intake with the rolling average consistently below 18 g. The average fiber intake was 17.1 g/day, with a corresponding mean fiber density of 10.5 g/1000 kcal. The overall mean fiber intake was 17.1 g/day. Separate analysis by meal types revealed that the highest fiber intake was during dinner (6.7 g), followed by lunch (4.8 g), breakfast (4.4 g), and snacks (1.5 g), while fiber density was lowest for snacks (7.8 g/1000 kcal), followed by dinner (10.2 g/1000 kcal), lunch (10.5 g/1000 kcal), and breakfast (10.8 g/1000 kcal). No significant correlations were observed between average fiber intake and participant characteristics such as age, sex, BMI, hemoglobin A1c, blood pressure, and frequency of meal logging. Conclusions: Despite using a general diabetes self-management mHealth app (DiabetesPlus) that included dietary self-monitoring and basic nutritional feedback, users consumed less than the recommended 20 g/day of dietary fiber on average over a 1-year period. This study highlights the need to explore alternative mHealth strategies to further enhance dietary fiber intake among patients with T2D.
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 | 0,024 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,010 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».