Abstract P518: Prospective Study of Skipping Meals to Lose Weight as a Predictor of Incident Type 2 Diabetes and Coronary Heart Disease: The Canadian 1995 Nova Scotia Health Survey
Notice bibliographique
Résumé
Introduction: Skipping meals is an increasingly common practice to lose weight among North American adults of all bodyweights. However, due to a lack of long-term studies, the long-term effect of skipping meals to lose weight on cardiometabolic health outcomes such as a diagnosis of type 2 diabetes mellitus (T2DM) or incident coronary heart disease (CHD) remains unknown, although previous short-term studies of skipping meals and risk factors for T2DM and CHD have suggested plausible biological pathways for a relationship to exist in either direction, protective or harmful. Hypothesis: We assessed the hypotheses that skipping meals to lose weight was associated with long-term risk of incident T2DM and CHD in the Canadian 1995 Nova Scotia Health Survey (NSHS95), and that these associations were influenced by cardiometabolic risk factors. Methods: Skipping meals to lose weight was assessed via questionnaire in a cohort of 2,898 adults in the NSHS95 and was linked to population-based health care administrative databases to determine incidence of T2DM and/or CHD in the following 23 years. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for T2DM and CHD. Results: During 23 years of follow-up, 430 incident cases of T2DM and 632 incident cases of CHD were diagnosed. Compared to participants who did not skip meals to lose weight, those who did skip meals to lose weight (2.7%) had an 87% higher risk of T2DM (multivariable-adjusted HR=1.87, 95% CI: 1.11-3.17). This association was no longer present after adjustment for baseline body mass index (BMI) (HR=1.42, 0.83-2.42). After stratification by BMI, skipping meals was associated with T2DM among participants who had BMI <25 kg/m 2 (n=1,030; HR=4.42, 1.01-19.30) but not among participants with BMIs of 25-29.9 kg/m 2 (n=1,123; HR=1.07, 0.39-2.96) or 30+ kg/m 2 (n=586; HR=1.21, 0.61-2.39). The multivariable-adjusted (including BMI) association was also present within participants with elevated cholesterol (n=1,450; HR=1.88, 1.00-3.53) and high blood pressure (n=1,363; HR=2.07, 1.11-3.85), but not among those without. No significant association was observed between skipping meals to lose weight and CHD risk before (HR=1.14, 0.67-1.96) or after adjustment for BMI (HR=1.05, 0.61-1.81), or within subgroups. Conclusion: These findings suggest that skipping meals to lose weight may be a predictive modifiable risk factor for developing T2DM over time, especially among people with a BMI <25 kg/m 2 , potentially working in connection or iteration with other T2DM risk factors. With the growing number of popular diets that include skipping meals, future studies are warranted to understand perturbations of potential metabolic consequences.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».