Comparison of Gait Parameters for Predicting Cognitive Decline: The Mayo Clinic Study of Aging.
Previous studies reported that slower gait speed might predict cognitive impairment and dementing illnesses, supporting the role of gait speed as a possible subclinical marker of cognitive impairment. However, the predictive value of other gait parameters for cognitive decline is unclear.



To investigate and compare the association with, and prediction of, specific gait parameters for cognition in a population-based sample.



The analysis included 3,426 cognitively normal participants enrolled in the Mayo Clinic Study of Aging. At baseline and every 15 months (mean follow-up = 1.93 years), participants had a study coordinator evaluation, neurological examination, and a neuropsychological assessment using nine tests that covered four domains. Gait parameters were assessed with the GAITRite® instrument. General linear mixed effects models were used to compute the annualized rate of change in cognitive domain z-scores, controlling for age, sex, education, depression, comorbidities, body mass index, APOE ɛ4 allele, and visit number, and excluding individuals with a history of stroke, alcoholism, Parkinson's disease, subdural hematoma, and normal pressure hydrocephalus.



Spatial (stride length), temporal (ambulatory time, gait speed, step count, cadence, double support time), and spatiotemporal (cadence) gait parameters, and greater intraindividual variability in stride length, swing time, and stance time were associated with a significant decline in global cognition and in specific domains including memory, executive function, visuospatial, and language.



Spatial, temporal, and spatiotemporal measures of gait and greater variability of gait parameters were associated with and predictive of both global- and domain-specific cognitive decline.
Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.|Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Rodolfo
R
Savica
Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Alexandra M V
AM
Wennberg
Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Clinton
C
Hagen
Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Kelly
K
Edwards
Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.|Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Rosebud O
RO
Roberts
Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA.
John H
JH
Hollman
Department of Neurology, Mayo Clinic, Rochester, MN, USA.
David S
DS
Knopman
Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Bradley F
BF
Boeve
Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA.
Mary M
MM
Machulda
Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.|Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Ronald C
RC
Petersen
Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.|Department of Neurology, Mayo Clinic, Rochester, MN, USA.
Michelle M
MM
Mielke
D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D060825:Cognitive Dysfunction / Q000175:diagnosis / Q000503:physiopathology*; D018672:Community Health Planning; D005260:Female; D005500:Follow-Up Studies; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D012720:Severity of Illness Index
Cognition; GAITRite® instrument; epidemiology; gait variability
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