P3‐214: Longitudinal relations among walking activity, gait speed, and cognitive functioning over a 10‐year period: Findings from the health, aging, and body composition study
Notice bibliographique
Résumé
Previous studies have linked both physical activity and functional mobility to future changes in cognition among older adults. However, few studies have assessed all three constructs longitudinally in order to determine their interrelations over time and whether physical activity and functional mobility have independent associations with cognition. This study examined self-reported time spent walking, gait speed, and general cognition as measured by the Modified Mini Mental State Test (3MS) over a ten-year period. 2527 older adults (mean age = 73.5 years at year 1) with complete data at year 1 from the Health ABC study, a biracial cohort were included. Self-reported time spent walking (mins/week), 3MS, and gait speed over a 20-meter walk were assessed at several time points from year 1 to 10. Joint longitudinal models were constructed using Mplus 7.3 and maximum likelihood estimation with robust standard errors. Covariates included clinical site, age, education, race, BMI, sex, smoking and drinking status, and prevalent diabetes, cerebrovascular and cardiovascular disease. A covariate-adjusted latent growth curve model examined the longitudinal relationships among walking activity, gait speed, and cognition (Figure 1). Higher initial gait speed predicted slower decline in cognition and walking activity from year 1 to 10 (ps<.001). Initial cognition and walking activity were not significant cross-domain predictors. After accounting for the predictive effects of the baseline scores, decline in walking, cognition and gait speed were interrelated (ps<.01). In follow-up analyses, the correlation between change in walking and cognition became non-significant after accounting for changes in gait speed; however, the correlation between change in cognition and change in gait speed was unmitigated after controlling for changes in walking. In a follow-up piecewise model (Figure 2), early decline in gait speed predicted later decline in cognition (p<.05), but early decline in cognition did not predict later decline in gait speed. Standardized results of latent growth curve model assessing longitudinal relations among routine walking, gait speed, and general cognitive functioning. To reduce model complexity, observed variables and covariates are not shown. Covariates include education, year 1 age, clinical site, race, gender, smoking and drinking status, and prevalent cerebrovascular disease, cardiovascular disease, and diabetes. All latent variables are regressed on the covariates. Standardized estimates are shown. Predictive associations are shown in red and correlations are shown in purple. To be considered significant, the p value must be less than .05 in both unadjusted and adjusted models. 3MS = Modified mini mental state test. ∗p < .05 ∗∗ p < .01 ∗∗∗ p < .001 Model fit indices: RMSEA = .024 (.022, .026); CFI = .976; TLI = .969. Standardized results from piece-wise latent change regression model. To reduce model complexity, covariates are not shown. Covariates include education, year 1 age, clinical site, race, gender, smoking and drinking status, and prevalent cerebrovascular disease, cardiovascular disease, and diabetes. All latent variables are regressed on the covariates. Standardized estimates are shown. Predictive associations are shown in red and correlations are shown in purple. To be considered significant, the p value must be less than .OS in both unadjusted and adjusted models. 3MS = Modified mini mental state test. ∗p < .05; ∗∗ p < .01; ∗∗∗ p < .001 These results suggest that gait speed is more closely related to changes in cognition than walking activity. Moreover, early changes in gait speed predict later changes in cognition, but not vice versa. Thus, declining gait speed appears to be a leading indicator for cognitive decline in older adults.
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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».