Kristell Pothier1, Tudor Vrinceanu2, Brittany Intzandt3, Laurent Bosquet4, Antony D Karelis5, Maxime Lussier6, T T Minh Vu7, Anil Nigam8, Karen Z H Li9, Nicolas Berryman10, Louis Bherer11. 1. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; PERFORM Centre, Concordia University, Montréal, Canada; EA 2114, Psychologie des Âges de la Vie et Adaptation, University of Tours, Tours, France. Electronic address: kpothier@univ-tours.fr. 2. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; Research Centre, Montreal Heart Institute, Montréal, Canada; Department of Medicine, University of Montréal, Montréal, Canada. 3. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; PERFORM Centre, Concordia University, Montréal, Canada; Research Centre, Montreal Heart Institute, Montréal, Canada. 4. Laboratory MOVE (EA 6314), Faculty of Sport Sciences, University of Poitiers, Poitiers, France. 5. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; Département des Sciences de l'Activité Physique, Université du Québec à Montréal, Montréal, QC, Canada. 6. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; Rehabilitation Science, Faculty of Medicine, University of Montréal, Montréal, Canada. 7. Department of Medicine, University of Montréal, Montréal, Canada; Research Centre, Centre hospitalier de l'Université de Montréal, Montréal, Canada. 8. Research Centre, Montreal Heart Institute, Montréal, Canada; Department of Medicine, University of Montréal, Montréal, Canada. 9. PERFORM Centre, Concordia University, Montréal, Canada; Department of Psychology, Concordia University, Montreal, QC, Canada; Centre for Research in Human Development, Concordia University, Montreal, QC, Canada. 10. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; Laboratory MOVE (EA 6314), Faculty of Sport Sciences, University of Poitiers, Poitiers, France; Département des Sciences de l'Activité Physique, Université du Québec à Montréal, Montréal, QC, Canada; Department of Sports Studies, Bishop's University, Sherbrooke, Canada. 11. Research Centre, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada; PERFORM Centre, Concordia University, Montréal, Canada; Research Centre, Montreal Heart Institute, Montréal, Canada; Department of Medicine, University of Montréal, Montréal, Canada. Electronic address: louis.bherer@umontreal.ca.
Abstract
OBJECTIVES: Mobility is a complex but crucial clinical outcome in older adults. Past observational studies have highlighted that cardiorespiratory fitness (CRF), energy cost of walking (ECW), and cognitive switching abilities are associated with mobility performance, making these key determinants of mobility intervention targets to enhance mobility in older adults. The objective of this study was to compare, in the same design, the impact of three training methods - each known to improve either CRF, ECW, or cognitive switching abilities - on mobility in healthy older adults. METHODS:Seventy-eight participants (69.28 ± 4.85yo) were randomly assigned to one of three twelve-week interventions: Aerobic Exercise (AE; n = 26), Gross Motor Abilities (GMA; n = 27), or Cognitive (COG; n = 25) training. Each intervention was designed to improve one of the three key determinants of mobility (CRF, ECW, and cognitive switching). Primary outcomes (usual gait speed, and TUG performance) and the three mobility determinants were measured before and after the intervention. RESULTS: Repeated-measures ANOVAs showed a time effect for TUG performance (F(1,75) = 14.92, p < .001): all groups equally improved after the intervention (ΔTUGpost-pre, in seconds, with 95% CI: AE = -0.44 [-0.81 to -0.08]; GMA = -0.60 [-1.10 to -0.10]; COG = -0.33 [-0.71 to 0.05]). No significant between group differences were observed. CRF was improved in the AE group only (Hedges' G = 0.27, small effect), ECW and cognitive switching improved the most in the GMA (Hedges' G = -0.78, moderate effect) and COG groups (Hedges' G = -1.93, large effect) respectively. Smaller improvements in ECW were observed following AE and COG trainings (Hedges' G: AE = -0.39, COG = -0.36, both small effects) as well as in cognitive switching following AE and GMA training (Hedges' G: AE = -0.42, GMA = -0.21, both small effects). DISCUSSION: This study provides further support to the notion that multiple interventional approaches (aerobic, gross motor exercise, or cognitive training) can be employed to improve functional mobility in older adults, giving them, and professionals, more options to promote healthy ageing.
RCT Entities:
OBJECTIVES: Mobility is a complex but crucial clinical outcome in older adults. Past observational studies have highlighted that cardiorespiratory fitness (CRF), energy cost of walking (ECW), and cognitive switching abilities are associated with mobility performance, making these key determinants of mobility intervention targets to enhance mobility in older adults. The objective of this study was to compare, in the same design, the impact of three training methods - each known to improve either CRF, ECW, or cognitive switching abilities - on mobility in healthy older adults. METHODS: Seventy-eight participants (69.28 ± 4.85yo) were randomly assigned to one of three twelve-week interventions: Aerobic Exercise (AE; n = 26), Gross Motor Abilities (GMA; n = 27), or Cognitive (COG; n = 25) training. Each intervention was designed to improve one of the three key determinants of mobility (CRF, ECW, and cognitive switching). Primary outcomes (usual gait speed, and TUG performance) and the three mobility determinants were measured before and after the intervention. RESULTS: Repeated-measures ANOVAs showed a time effect for TUG performance (F(1,75) = 14.92, p < .001): all groups equally improved after the intervention (ΔTUGpost-pre, in seconds, with 95% CI: AE = -0.44 [-0.81 to -0.08]; GMA = -0.60 [-1.10 to -0.10]; COG = -0.33 [-0.71 to 0.05]). No significant between group differences were observed. CRF was improved in the AE group only (Hedges' G = 0.27, small effect), ECW and cognitive switching improved the most in the GMA (Hedges' G = -0.78, moderate effect) and COG groups (Hedges' G = -1.93, large effect) respectively. Smaller improvements in ECW were observed following AE and COG trainings (Hedges' G: AE = -0.39, COG = -0.36, both small effects) as well as in cognitive switching following AE and GMA training (Hedges' G: AE = -0.42, GMA = -0.21, both small effects). DISCUSSION: This study provides further support to the notion that multiple interventional approaches (aerobic, gross motor exercise, or cognitive training) can be employed to improve functional mobility in older adults, giving them, and professionals, more options to promote healthy ageing.
Authors: S Ahmed Hassan; Leandro Viçosa Bonetti; Karina Tamy Kasawara; Matthew B Stanbrook; Dmitry Rozenberg; W Darlene Reid Journal: Cells Date: 2022-05-11 Impact factor: 7.666