Table 1.
Studies examining the relationship between brain structure and function and gait variability in older adults without diagnosed neurological diseases
| Author, yr | Sample (N, Female%, Age, usual gait) | Gait variability assessment | Neuroimaging assessment | covariates | Analysis | Main findings |
|---|---|---|---|---|---|---|
| Rosano et al. 2007 | N=331 78.3 (4.0) NS |
Step length variability, step width variability, stance time variability (CoV) using the GaitMat II | MRI: infarcts and WM hyperintensities | Age, sex, cognitive function, cardiovascular disease | General | Higher step length variability and stance time variability were associated with greater brain infarcts, asal ganglia infarcts, and severity of WM hyperintensities. There were no significant associations of step width variability with these neuroimaging markers. |
| Srikanth et al. 2009 | N=294, 44.6%F 72.3 (7.0) 1.13m/s |
A summary score consisted of stride length variability, stride time variability, and step width variability (SD) using the GAITRite system | MRI: WM hyperintensities | Age, sex, total brain volume, other physiological variables | General | A higher gait variability score was associated with greater WM lesions. |
| Annweiler et al. 2014 | N=115, 43.5%F 70.4 (4.4) 1.08m/s |
Stride time variability (CoV) using the GAITRite system | MRI: ventricle sub-volumes | Age, sex, cumulative illness rating scale, mini-mental state exam score, go/no-go, brain vascular burden, depressive symptoms, psychoactive drugs, vision, proprioception, body mass index, muscle strength, and gait velocity | General | Higher stride time variability was associated with larger temporal horns. Those in the top tertile of stride time variability had larger middle portions of ventricular bodies than those in the middle tertile of stride time variability. |
| Beauchet et al. 2014 | N=71, 59.7%F 69.0 (0.8) NS |
Stride time variability (CoV) using footswitches | MRI: whole brain GM and WM volumes | Age, sex, body mass index, and total brain matter volume | VBM | Higher stride time variability was associated with smaller right angular gyrus. |
| Beauchet et al. 2015 | N=47, 48.9%F 69.7 (3.6) 1.13m/s |
Stride time variability, swing time variability, and stride width variability (CoV) using the GAITRite system | MRI: Hippocampal volume | Age, sex, body mass index, drugs taken daily, mini-mental state exam score, history of falls, gait speed, and white matter signal-intensity abnormality scoring. | One ROI | Higher stride time variability was associated with greater hippocampal volume. There were no significant associations of swing time variability or stride width variability with hippocampal volume. |
| Manor et al. 2012 | without diabetes: N=89, 51.7%F 63.5(8.2), NS; with type 2 diabetes: N=68, 45.6%F 63.6(7.8), NS. |
Stride time variability (CoV) using footswitches | MRI: Global and 7 ROIs of GM volumes (left and right precentral, postcentral, dorsolateral prefrontal cortex, and cerebellum | Age, sex, body mass | General and multiple ROIs | In those without diabetes, stride time variability was not associated with global or regional volumes. In those with diabetes and without diabetic peripheral neuropathy, higher stride time variability was associated with smaller GM volume and cerebellum. |
| De Laat et al. 2011 | N=484, 43.4% F 65.6 (8.9) 1.3 m/s |
Stride length variability, stride time variability, and stride width variability (CoV) using the GAITRite system | DTI: Fractional anisotropy and mean diffusivity of total WM lesions and normal appearing WM MRI: total brain volume |
Age, sex, height, and total brain volume, additional adjustment for WM lesions | General | Higher stride length variability was associated with higher mean diffusivity of normal appearing WM and smaller brain volume. Higher stride time variability was associated with lower fractional anisotropy and higher mean diffusivity of normal appearing WM and smaller brain volume. Higher stride width variability was associated with higher mean diffusivity of WM lesions. |
| Rosso et al. 2014 | N=265, 57.4%F 82.9 (2.7) 0.91 m/s |
Step length variability (CoV) using the GaitMat II | DTI: Mean diffusivity of 17 GM ROIs (pre- and postcentral gyri, putamen, caudate, thalamus, supplementary motor, precuneus, inferior parietal, pallidum, anterior cingulate, middle frontal gyrus, superior parietal, hippocampus, entorhinal cortex, parahippocampal gyrus, amygdala, posterior cingulate) | Gait speed, demographic, health, functional covariates | Multiple ROIs | The association between step length variability and GM integrity was strongest for the hippocampus and anterior cingulate cortex compared to other ROIs. |
| Tian et al. 2015 | Young-old: N=209, 65.1%F 62.1 (4.9) NS. Old-old: N=233, 48.9%F 78.2 (5.4) NS. |
Lap time variation (detrended SD) from the 400m walk test | DTI: Fractional anisotropy of 9 WM tracts of interest (superior longitudinal, inferior fronto-occipital, and uncinate fasciculi, corpus callosum, anterior limb of the internal capsule, and the anterior corona radiata) | Age, sex, height, weight, global white matter hyperintensities, and mean lap time | Multiple tracts of interest | Independent of WM hyperintensities, higher lap time variation was associated with lower fractional anisotropy in the body of the corpus callosum only in the young-old. |
| Tian et al. 2016 | N=449, 56.8%F 70.8 (9.7) NS. |
Lap time variation (detrended SD) from the 400m walk test | DTI: Mean diffusivity of 16 GM ROIs (pre- and postcentral gyri, supplementary motor cortex, putamen, caudate, thalamus proper, middle frontal gyrus, superior parietal lobe, hippocampus, parahippocampus, entorhinal cortex, amygdala, precuneus, posterior cingulate cortex, anterior and middle cingulate cortices) | Age, sex, height, weight, mean lap time, and additional adjustment for hypertension and diabetes | Multiple ROIs and VBM | Higher lap time variation was associated with higher mean diffusivity of the precuneus, the middle cingulate cortex and the anterior cingulate cortex. |
| Verlinden et al. 2016 | N=2330, 55.1% F 65.9 (9.2) NS |
Stride length variability and stride time variability obtained from principle components analysis (SD) using the GAITRite system | DTI: Fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity in 14 WM tracts of interest that were categorized into brainstem, projection, association, limbic, and callosal tracts | Age, age2, sex, height, weight, education, interval between MRI and gait assessment, phase- and frequency-encoding direction of the diffusion scan, intracranial volume, lacunar infarcts, and tract-specific WM and WM lesion volumes | Multiple tracts of interest | Higher stride length variability was associated with higher mean diffusivity across association tracts and the posterior thalamic radiation. |
| Zimmerm an et al. 2009 | N=34, 55.9% F 80.37 (5.77) 0.96m/s |
Stride length variability (SD) using the GAITRite system | MRI: hippocampal volume MRS: NAA/Cr of the hippocampus |
Age, sex, education, ethnicity, weight, midsagittal area, gait speed | One ROI | There were no significant associations between stride length variability and neuronal integrity of the hippocampus or hippocampal volume. |
| Wennberg et al. 2016 | N=611, 49.3% F 62.7 1.22 m/s |
Stance time variability (CoV) using the GAITRite system | PiB-PET: amyloid deposition in 8 ROIs (prefrontal, orbitofrontal, parietal, temporal, anterior cingulate, posterior cingulate, and motor-specific region) | Age, sex, body mass index, education, ApoE ε4 allele, Charlson comorbidity index, depression, and AD-signature neurodegeneration. | Multiple ROI | Higher stance time variability was associated with higher amyloid deposition in all ROIs. After stratification by sex, these associations were only present in women. |
| Shimada et al. 2013 | N=24, 100% F 75–82 NS |
Step length variability (CoV) assessed on a treadmill using an infrared ray device | FDG-PET: brain glucose uptake | None. | Multiple ROIs | The primary sensorimotor cortex was activated more during treadmill walking than the resting condition in low than high variability group. The hippocampus and WM of the middle and superior temporal gyrus was deactivated more during treadmill waking than the resting condition in high than low variability group. |
| Rochester et al. 2012 | N=22, 59.1%F 67.43(8.43) 1.31m/s |
Gait speed variability, stride time variability, stride length variability and step width variability (SD) using the GAITRite system | TMS: Cholinergic function of the motor cortex | Age, motor disease severity, and cognition | One ROI | There was no significant association between short-latency afferent inhibition and gait variability. |
Note: NS=not specified; ROI=regions of interest; SD=standard deviation; CoV=coefficient of variance; NS=not specified; MRS= magnetic resonance spectroscopy; MRI= magnetic resonance imaging; DTI=diffusion tensor imaging; SPECT=Single photon emission computed tomography; VBM=Voxel-based morphometry; WM=white matter; GM=gray matter; TMS=transcranial magnetic stimulation, FDG-PET=fluorodeoxyglucose-positron emission tomography; NAA/Cr=N-acetylaspartate/creatine ratio.