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Enregistrement W4408029621 · doi:10.1016/j.obpill.2025.100171

Management and impact of obesity in Canada: A real-world survey of people with obesity and their physicians

2025· article· en· W4408029621 sur OpenAlexaffabout
Jennifer M. Glass, Sophie Carter, Esther Artime, Victoria Higgins, Lewis Harrison, Andrea Leith, David C.W. Lau, Ian Patton, Jennifer L. Kuk

Notice bibliographique

RevueObesity Pillars · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueBariatric Surgery and Outcomes
Établissements canadiensYork UniversityCanadian Obesity NetworkUniversity of CalgaryEli Lilly (Canada)
Organismes subventionnairesEli Lilly and Company
Mots-clésObesityManagement of obesityMedicineEnvironmental healthGerontologyFamily medicineInternal medicineWeight loss

Résumé

récupéré en direct d'OpenAlex

Obesity is a chronic relapsing disease associated with multiple complications. This study described real-world demographic/clinical characteristics, including obesity-related complications (ORCs), prescribing rationale, and patient-reported outcome measures (PROMs) for adults living with obesity in Canada accessing treatment. This was a cross-sectional survey of physicians and consulting people with obesity (PwO) in Canada with retrospective data capture in a real-world setting. Canadian data were drawn between July and November 2022 from the multinational Adelphi Real World Obesity Disease Specific Programme™. Consulting PwO were required to be on a weight management program and/or have a current body mass index of ≥30 kg/m 2 . Physicians completed questionnaires for the next 3–5 consecutive PwO seen in their routine clinical practice. A quota was applied for obesity management medication (OMM). PROMs including Work Productivity and Activity Impairment (WPAI) questionnaire were provided voluntarily by PwO. Analyses were descriptive. Overall, 50 physicians (35 general practitioners, 15 endocrinologists) and 199 PwO were analyzed. More than 85 % of PwO had ≥1 ORC. The most common ORCs were hypertension, dyslipidemia, depression, and type 2 diabetes, and one-quarter to one-half of ORCs were not optimally controlled. Approximately two-thirds of the cohort were employed full-time, almost half had private insurance, and almost 70 % were classified as high socio-economic status. Mean number of weight-reduction attempts over the past 3 years was 2.9. Pharmacological treatment for obesity was common among those with ORCs. A general trend towards greater work impairment among people with ORCs than for PwO without ORCs was observed. Among PwO participating in our study, ORCs were common, often uncontrolled, and their presence impacted the likelihood of obesity treatment and possibly impaired work productivity. Medical treatment for obesity was often delayed until ORCs developed, suggesting that preventative healthcare measures are not the norm for PwO in Canada. A large proportion of PwO had high socioeconomic status, suggesting that PwO who access treatment may not be representative of the overall population of PwO in Canada. • Obesity is a chronic, relapsing and burdensome disease that is often not treated appropriately in Canada due to socioeconomic, healthcare system and payer barriers. • >85 % of people with obesity (PwO) in the study had obesity-related complications (ORCs), and obesity management medication (OMM) was prescribed primarily for those with ORCs, suggesting that treatment is mostly initiated after ORCs occur rather than preventatively. • WPAI questionnaire results suggest that there was a general trend towards greater activity/work impairment among PwO who had ORCs than for those without ORCs, although statistical analysis was not conducted. • Effective treatment should be accessible for all PwO in Canada to help reduce obesity and ORCs, but further work is needed to achieve this goal, including educating physicians and improving equitable access to OMM, particularly for the prevention of ORCs.

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 enseignants0,046
Score d'incertitude au seuil0,528

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
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 Opus0,009
Tête enseignante GPT0,239
Écart entre enseignants0,230 · 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

Citations3
Publié2025
Routes d'admission2
Résumé présentoui

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