Multimodal training protocols on unstable rather than stable surfaces better improve dynamic balance ability in older adults.

Aging Balance control External perturbation Proprioception Strength

Journal

European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity
ISSN: 1813-7253
Titre abrégé: Eur Rev Aging Phys Act
Pays: Germany
ID NLM: 101284836

Informations de publication

Date de publication:
12 Jul 2024
Historique:
received: 09 04 2024
accepted: 26 06 2024
medline: 13 7 2024
pubmed: 13 7 2024
entrez: 12 7 2024
Statut: epublish

Résumé

There has been growing interest in using unstable devices in training protocols. This study aimed to assess the effectiveness of two multimodal exercise interventions (i.e., on stable and unstable surfaces) on dynamic balance control and lower limb strength in older adults. Sixty-two older adults were randomly assigned to two intervention groups (N = 20, stable group; N = 19, unstable group), and to a control group (N = 18). In this single-blinded randomized controlled study, the two intervention groups underwent a 12-week training program twice a week for 45 min, consisting of strength and balance exercises. The stable (ST) group performed the training program over stable surfaces, while the unstable (UNST) group over unstable surfaces. Dynamic balance was assessed by computing the center of pressure (CoP) trajectory while a driven movable platform induced an unexpected perturbation of the base of support. Specifically, we considered the following CoP-related parameters within a 2.5-s temporal window from the beginning of the perturbation: displacement (Area95), mean velocity (Unit Path), anterior-posterior first peak (FP), post perturbation variability (PPV), and maximal oscillations (ΔCoPMax). The dominant quadriceps strength was measured through an isometric maximal voluntary contraction on an instrumented chair. Four out of five CoP-related parameters (i.e., Area95, Unit Path, ΔCoPMax, and PPV) significantly improved in the UNST group from a minimum of 14.28% (d = 0.44) to a maximum of 52.82% (d = 0.58). The ST group significantly improved only in two (i.e., ΔCoPMax, and PPV) out of five CoP-related parameters with an enhancement of 12.48% (d = 0.68) and 19.10% (d = 1.06). Both intervention groups increased the maximal isometric quadriceps strength (UNST:17.27%, d = 0.69; ST:22.29%, d = 0.98). The control group did not show changes in any of the parameters considered. Stable surfaces promoted faster increments of muscular strength. Unstable surfaces were more effective in enhancing dynamic balance efficiency. These findings suggested the employment of multimodal training on unstable rather than stable surfaces to potentially lower the incidence of falls in older adults. NCT05769361, retrospectively registered 13 March 2023, https://clinicaltrials.gov/study/NCT05769361?lat=45.3661864&lng=11.8209139&locStr=Padova,%20Italy&distance=50&page=11&rank=107 .

Sections du résumé

BACKGROUND BACKGROUND
There has been growing interest in using unstable devices in training protocols. This study aimed to assess the effectiveness of two multimodal exercise interventions (i.e., on stable and unstable surfaces) on dynamic balance control and lower limb strength in older adults.
METHODS METHODS
Sixty-two older adults were randomly assigned to two intervention groups (N = 20, stable group; N = 19, unstable group), and to a control group (N = 18). In this single-blinded randomized controlled study, the two intervention groups underwent a 12-week training program twice a week for 45 min, consisting of strength and balance exercises. The stable (ST) group performed the training program over stable surfaces, while the unstable (UNST) group over unstable surfaces. Dynamic balance was assessed by computing the center of pressure (CoP) trajectory while a driven movable platform induced an unexpected perturbation of the base of support. Specifically, we considered the following CoP-related parameters within a 2.5-s temporal window from the beginning of the perturbation: displacement (Area95), mean velocity (Unit Path), anterior-posterior first peak (FP), post perturbation variability (PPV), and maximal oscillations (ΔCoPMax). The dominant quadriceps strength was measured through an isometric maximal voluntary contraction on an instrumented chair.
RESULTS RESULTS
Four out of five CoP-related parameters (i.e., Area95, Unit Path, ΔCoPMax, and PPV) significantly improved in the UNST group from a minimum of 14.28% (d = 0.44) to a maximum of 52.82% (d = 0.58). The ST group significantly improved only in two (i.e., ΔCoPMax, and PPV) out of five CoP-related parameters with an enhancement of 12.48% (d = 0.68) and 19.10% (d = 1.06). Both intervention groups increased the maximal isometric quadriceps strength (UNST:17.27%, d = 0.69; ST:22.29%, d = 0.98). The control group did not show changes in any of the parameters considered.
CONCLUSIONS CONCLUSIONS
Stable surfaces promoted faster increments of muscular strength. Unstable surfaces were more effective in enhancing dynamic balance efficiency. These findings suggested the employment of multimodal training on unstable rather than stable surfaces to potentially lower the incidence of falls in older adults.
TRIAL REGISTRATION BACKGROUND
NCT05769361, retrospectively registered 13 March 2023, https://clinicaltrials.gov/study/NCT05769361?lat=45.3661864&lng=11.8209139&locStr=Padova,%20Italy&distance=50&page=11&rank=107 .

Identifiants

pubmed: 38997647
doi: 10.1186/s11556-024-00353-8
pii: 10.1186/s11556-024-00353-8
doi:

Banques de données

ClinicalTrials.gov
['NCT05769361']

Types de publication

Journal Article

Langues

eng

Pagination

19

Subventions

Organisme : Progetti di ricerca di Rilevante Interesse Nazionale (PRIN)
ID : 2017RS5M44

Informations de copyright

© 2024. The Author(s).

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Auteurs

Alex Rizzato (A)

Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padova, 35131, Italy.

Matteo Bozzato (M)

Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padova, 35131, Italy.

Luca Rotundo (L)

Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padova, 35131, Italy.

Giuseppe Zullo (G)

Department of Industrial Engineering, University of Padova, Via Venezia, 1, Padova, 35131, Italy.

Giuseppe De Vito (G)

Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padova, 35131, Italy.

Antonio Paoli (A)

Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padova, 35131, Italy.

Giuseppe Marcolin (G)

Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padova, 35131, Italy. giuseppe.marcolin@unipd.it.

Classifications MeSH