Age-related differences in foot structure and mobility
Notice bibliographique
Résumé
Previous research has suggested that changes in foot anthropometrics occur with age, however, these age-related changes remain unclear. The use of portable technology, such as of three-dimensional (3D) body scanners, to collect foot anthropometrics facilitates the exploration of potential differences between and within individuals. Therefore, the purpose of this study was to examine age-related differences in foot anthropometrics using a 3D foot scanner. Sixteen young (8 males, 8 females, mean age 23.6±3.7 years) and sixteen older (8 males, 8 females, mean age 71.6±5.9 years) adults without foot deformities or lower-extremity injuries were recruited. Eight anthropometric measures of each foot were obtained during weight bearing (WB) and non-weight bearing (NWB) conditions using a portable, white light, 3D scanner (TechMed 3D Inc., QC). Measures included dorsal arch height (DAH), foot length (FL), truncated foot length (TFL), forefoot width (FFW), midfoot width (MFW), rearfoot width (RFW), arch height ratio (AHR) and foot mobility magnitude (FMM). Significant differences in foot measures between age groups were analyzed using an independent samples t-test. A secondary comparison between age groups was also evaluated using an analysis of covariance (ANCOVA) with TFL as a covariate. The older group had greater arch height ratio (AHR) during weight bearing (WB) and non-weight bearing (NWB), as well as greater dorsal arch height (DAH) in the NWB condition, suggesting that the older group had a higher arch. Further, the older group had significantly greater rearfoot width (RFW) during WB than the younger group, indicating a greater splay of the metatarsus in the older group. After controlling for the TFL, the older group also showed a greater DAH in the NWB condition. In addition, the forefoot width (FFW), RFW and midfoot width (MFW) in the NWB condition were also significantly greater for the older adults. Furthermore, for the WB condition, the older group had significantly greater DAH and RFW. Additionally, the older group showed less mobility of the foot. Preliminary results based on the sample size of the study provide evidence of anthropometric foot variations between younger and older adults. Examining differences in foot structure and mobility between younger and older adults is fundamental for comprehending foot mechanics and function during movements, such as gait.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».