White matter hyperintensities predict functional decline in voiding, mobility, and cognition in older adults.
OBJECTIVE
To compare magnetic resonance imaging data with functional assessments of mobility, urinary control, and cognition to determine common or distinctive features in the distribution of brain white matter hyperintensities (WMHs) associated with functional decline and impairment.


METHODS
Baseline data from subjects aged 75 to 89 enrolled in a longitudinal study. Assessors and subjects were blinded to group assignment.


METHODS
Healthy community-dwelling volunteers.


METHODS
Ninety-nine subjects were enrolled using a balanced 3 x 3 matrix stratified according to age and mobility performance. Exclusion criteria were medication, systemic conditions, and neurological diseases that can compromise mobility.


METHODS
WMHs were identified using a semi-automated segmentation method, and regional burdens were assessed using a white matter parcellation atlas. Quantitative measures of mobility, urinary incontinence (UI) severity, and executive function and processing speed were obtained.


RESULTS
WMHs occur predictably in predominantly periventricular areas. There were powerful correlations between total (tWMH) and regional (rWMH) WMH, with correlation coefficients of 0.5 to 0.9 for eight of 10 structures analyzed. tWMH predicted functional measures of UI, mobility, executive function, and processing speed nearly as well as the best regional measures. The total volume of WMHs independently explains 5% to 11% of the variability for mobility, UI severity, executive function, and processing speed and is a sensitive (0.7-0.8) predictor of functional decline. The odds of decline in each of the three functional domains was 1.5 to 2.4 times greater with each 1% increase in tWMH.


CONCLUSIONS
This work establishes the importance of brain WMH burden in three major geriatric syndromes. The findings support the inclusion of total WMH burden as a risk factor in the predictive and diagnostic criteria.
Wakefield
Dorothy B
DB
Department of Neurology, University of Connecticut Health Center, Farmington, Connecticut 06030, USA.
Moscufo
Nicola
N
Guttmann
Charles R
CR
Kuchel
George A
GA
Kaplan
Richard F
RF
Pearlson
Godfrey
G
Wolfson
Leslie
L
D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping; D003072:Cognition Disorders / Q000473:pathology*; D003430:Cross-Sectional Studies; D004311:Double-Blind Method; D005260:Female; D020233:Gait Disorders, Neurologic / Q000473:pathology*; D006801:Humans; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D008297:Male; D051346:Mobility Limitation; D009413:Nerve Fibers, Myelinated / Q000473:pathology; D012044:Regression Analysis; D014549:Urinary Incontinence / Q000473:pathology*