A retrospective review of older adults who attended a medical fitness facility in Winnipeg, MB and the impact of the medical fitness model on long term health outcomes
Notice bibliographique
Résumé
Background: It is well established that being active helps prevent chronic diseases and reduce the risk of premature death. However, physical inactivity is common among older adults which may be associated with poor health outcomes. Furthermore, it is not clearly understood whether physical inactivity is related to increased health care utilization in older adults. As the proportion of older adults increases, it is important for this population to stay active and practice positive health behaviours to maintain functional independence, live longer and improve quality of life. The aim of this study was to determine the relationship between the medical fitness model (membership and attendance) and all-cause mortality, health care utilization and a major adverse cardiac event in older adults. Methods: We conducted a retrospective cohort study linking data from two medical fitness facilities in Winnipeg, MB to provincial health administrative databases between January 1st 2005 and December 31st, 2015. Our propensity model included age, sex, socioeconomic status, comorbidities and year of index date. We then applied stabilized inverse probability treatment weights to examine the association of all-cause mortality and a major adverse cardiac event in older adult members using time-dependent Cox regression models. Health care utilization (hospitalizations, outpatient primary care visits, emergency department visits) was assessed using negative binomial regression models. Results: We included 3,108 older adult members and 92,045 controls in our study. We had 1,765 members attend <1 weekly and 1,343 attend >1 weekly at the medical fitness facility. Compared to controls, older adult members had a 62% lower risk of all-cause mortality during the first 536 days (HR, 0.38 [95% CI, 0.29 – 0.48]) and 37% after 536 days (HR, 0.63 [95% CI, 0.56 – 0.70]). Older adult members were associated with a lower risk of hospitalizations (OR, 0.74 [95% CI, 0.70 – 0.80]), which strengthened the more frequently older adults attended (<1 weekly; OR, 0.80 [95% CI, 0.73 – 0.88], (>1 weekly; OR, 0.65 [95% CI, 0.59 – 0.73]). Less frequent users were more likely to visit a general practitioner (OR, 1.07 [95% CI, 1.03 – 1.11]). More frequent users were more likely to visit a general practitioner (OR, 1.06 [95% CI, 1.01 – 1.10]), less likely to visit the emergency department (OR, 0.79 [95% CI, 0.72 – 0.86]) and had a lower risk of a major adverse cardiac event after sustained exposure to the medical fitness facility (HR, 0.71 [95% CI, 0.57 – 0.89]). Conclusions: Our findings suggest that attending a medical fitness facility may be associated with survival benefits, as well as, decreased risk of hospitalizations, emergency department visits and cardiovascular events, for older adult members. The medical fitness model may be an alternative approach for public health efforts aimed at reducing physical inactivity and promoting positive health behaviours in older adult populations.
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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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».