OBJECTIVES: To develop and compare norms for widely used gait parameters in adults aged 70 and older using cross-sectional (conventional) and longitudinal (robust) approaches accounting for important confounders such as disease effects on gait. DESIGN: Cohort study. SETTING: General community. PARTICIPANTS: Community-dwelling older adults (> 70, N = 824) without dementia or disability. MEASUREMENTS: Eight quantitative gait parameters measured using an instrumented walkway. RESULTS: Of the 824 subjects (conventional normal (CN) sample), 304 were included in a "robust normal" (RN) sample after excluding those with prevalent or incident clinical gait abnormalities developing within 1 year of the baseline assessment to account for disease effects on gait performance. Descriptively, the RN sample showed better performance on all selected gait variables than the CN sample. For instance, mean gait velocity ± standard deviation was 105.9 ± 17.9 cm/s in the RN sample, compared with 93.3 ± 23.2 cm/s in the overall CN sample. Applying one standard deviation below the mean (70.1 cm/s) derived from the CN sample to define slow gait, 15.9% (131) in the overall cohort were classified as abnormal, whereas the RN cut-off (88.0 cm/s) classified 39.7% (327) in the overall cohort as abnormal. CONCLUSION: Cross-sectional conventional norms may underestimate gait performance in aging. Longitudinal robust norms provide more-accurate estimates of normal gait performance and thus may improve early detection of gait disorders in older adults.
OBJECTIVES: To develop and compare norms for widely used gait parameters in adults aged 70 and older using cross-sectional (conventional) and longitudinal (robust) approaches accounting for important confounders such as disease effects on gait. DESIGN: Cohort study. SETTING: General community. PARTICIPANTS: Community-dwelling older adults (> 70, N = 824) without dementia or disability. MEASUREMENTS: Eight quantitative gait parameters measured using an instrumented walkway. RESULTS: Of the 824 subjects (conventional normal (CN) sample), 304 were included in a "robust normal" (RN) sample after excluding those with prevalent or incident clinical gait abnormalities developing within 1 year of the baseline assessment to account for disease effects on gait performance. Descriptively, the RN sample showed better performance on all selected gait variables than the CN sample. For instance, mean gait velocity ± standard deviation was 105.9 ± 17.9 cm/s in the RN sample, compared with 93.3 ± 23.2 cm/s in the overall CN sample. Applying one standard deviation below the mean (70.1 cm/s) derived from the CN sample to define slow gait, 15.9% (131) in the overall cohort were classified as abnormal, whereas the RN cut-off (88.0 cm/s) classified 39.7% (327) in the overall cohort as abnormal. CONCLUSION: Cross-sectional conventional norms may underestimate gait performance in aging. Longitudinal robust norms provide more-accurate estimates of normal gait performance and thus may improve early detection of gait disorders in older adults.
Authors: Matteo Cesari; Stephen B Kritchevsky; Brenda W H J Penninx; Barbara J Nicklas; Eleanor M Simonsick; Anne B Newman; Frances A Tylavsky; Jennifer S Brach; Suzanne Satterfield; Douglas C Bauer; Marjolein Visser; Susan M Rubin; Tamara B Harris; Marco Pahor Journal: J Am Geriatr Soc Date: 2005-10 Impact factor: 5.562
Authors: Jennifer S Brach; Stephanie A Studenski; Subashan Perera; Jessie M VanSwearingen; Anne B Newman Journal: J Gerontol A Biol Sci Med Sci Date: 2007-09 Impact factor: 6.053
Authors: Joe Verghese; Aaron LeValley; Charles B Hall; Mindy J Katz; Anne F Ambrose; Richard B Lipton Journal: J Am Geriatr Soc Date: 2006-02 Impact factor: 5.562
Authors: Joe Verghese; Emmeline Ayers; Nir Barzilai; David A Bennett; Aron S Buchman; Roee Holtzer; Mindy J Katz; Richard B Lipton; Cuiling Wang Journal: Neurology Date: 2014-10-31 Impact factor: 9.910
Authors: Joe Verghese; Cuiling Wang; David A Bennett; Richard B Lipton; Mindy J Katz; Emmeline Ayers Journal: Alzheimers Dement Date: 2019-06-01 Impact factor: 21.566