TY - JOUR
T1 - Prediction of Gait Speed by Spatiotemporal Parameters in Residential Aged Care Residents
AU - Keogh, Justin
AU - Fien, Samantha
AU - Henwood, Timothy
AU - Climstein, Mike
PY - 2016/6
Y1 - 2016/6
N2 - The majority of older Australians, especially residential aged care (RAC) adults, have decreased physical activity, leading to poor physicalfunction such as reduced gait speed, strength, and balance (Peel et al., 2013). Specifically, individuals with slower gait speeds are at higher risk ofdisability, cognitive impairment, institutionalisation, falls, and mortality (Abellan Van Kan et al., 2009). The aim was to describe gait spatiotemporalcharacteristics and determine if the spatiotemporal gait parameters (e.g., step length, step rate) could predict gait speed in RAC adults. Methods: A totalof 100 older RAC adults (85.6 ± 6.7 years, range 66–99 years, 66 females) provided informed consent. Participants completed three trials of their habitualgait speed over the 3.66-m long Gaitmat II pressure mat system. The Gaitmat II allowed calculation of gait speed as well as many spatiotemporal gaitparameters including step length, stride length, support base, step time, swing time, stance time, single support time, and double support time. Thesespatiotemporal parameters were input into univariable and multivariable regression analyses to predict gait speed. Results: The multivariable linearregression involving all independent secondary spatiotemporal outcomes identified the following factors (stride length, support base, and step time) thatpredicted walking speed (r2 = .89). Stride length was the strongest predictor, with each 0.1 m increase in stride length resulting in an average 0.09 (95%CI 0.06–0.13) m/s faster preferred gait speed. Conclusion: While more research is required, preliminary evidence suggests that three spatiotemporalparameters (stride length, support base, and step time) predict gait speed in RAC residents. Therefore, interventions focusing on improving these threespatiotemporal parameters may increase gait speed in this population. References: Peel, N.M., Kuys, S.S., & Klein, K. (2013). Gait speed as a measurein geriatric assessment in clinical settings: a systematic review. J Gerontol A Biol Sci Med Sci. 68(1):39–46. Abellan Van Kan, G., Rolland, Y., Andrieu,S., Bauer, J., Beauchet, O., Bonnefoy, M., et al. (2009). Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older peoplean international academy on nutrition and aging (IANA) task force. JNHA: Clinical Neurosciences. 13:881–889
AB - The majority of older Australians, especially residential aged care (RAC) adults, have decreased physical activity, leading to poor physicalfunction such as reduced gait speed, strength, and balance (Peel et al., 2013). Specifically, individuals with slower gait speeds are at higher risk ofdisability, cognitive impairment, institutionalisation, falls, and mortality (Abellan Van Kan et al., 2009). The aim was to describe gait spatiotemporalcharacteristics and determine if the spatiotemporal gait parameters (e.g., step length, step rate) could predict gait speed in RAC adults. Methods: A totalof 100 older RAC adults (85.6 ± 6.7 years, range 66–99 years, 66 females) provided informed consent. Participants completed three trials of their habitualgait speed over the 3.66-m long Gaitmat II pressure mat system. The Gaitmat II allowed calculation of gait speed as well as many spatiotemporal gaitparameters including step length, stride length, support base, step time, swing time, stance time, single support time, and double support time. Thesespatiotemporal parameters were input into univariable and multivariable regression analyses to predict gait speed. Results: The multivariable linearregression involving all independent secondary spatiotemporal outcomes identified the following factors (stride length, support base, and step time) thatpredicted walking speed (r2 = .89). Stride length was the strongest predictor, with each 0.1 m increase in stride length resulting in an average 0.09 (95%CI 0.06–0.13) m/s faster preferred gait speed. Conclusion: While more research is required, preliminary evidence suggests that three spatiotemporalparameters (stride length, support base, and step time) predict gait speed in RAC residents. Therefore, interventions focusing on improving these threespatiotemporal parameters may increase gait speed in this population. References: Peel, N.M., Kuys, S.S., & Klein, K. (2013). Gait speed as a measurein geriatric assessment in clinical settings: a systematic review. J Gerontol A Biol Sci Med Sci. 68(1):39–46. Abellan Van Kan, G., Rolland, Y., Andrieu,S., Bauer, J., Beauchet, O., Bonnefoy, M., et al. (2009). Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older peoplean international academy on nutrition and aging (IANA) task force. JNHA: Clinical Neurosciences. 13:881–889
U2 - 10.1123/japa.24.s1.s48
DO - 10.1123/japa.24.s1.s48
M3 - Meeting Abstract
SN - 1063-8652
VL - 24
SP - S36-S36
JO - Journal of Aging and Physical Activity
JF - Journal of Aging and Physical Activity
ER -