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Published on: December 18, 2016
Association Between Lifestyle at Different Life Periods and Brain Integrity in Older Adults
Anne-Laure Turpin1, Francesca Felisatti1, Léa Chauveau1
1Normandy University, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", NeuroPresage Team, GIP Cyceron, Caen, France.
Background And Objectives:
Lifestyle behaviors, including engagement in complex mental activities, have been associated with dementia risk and neuroimaging markers of aging and Alzheimer disease. However, the life period(s) at which lifestyle factors have the greatest influence on brain health remains unclear. Our objective was to determine the relative influence of lifestyle (i.e., engagement in complex mental activities) at different life periods on older adults' brain health.
Methods:
This observational study included community-dwelling cognitively unimpaired seniors (older than 65 years) from the Age-Well randomized controlled trial (Caen, France). All participants completed at baseline the Lifetime of Experiences Questionnaire, assessing engagement in complex mental activities during young adulthood (13-30 years: LEQ-young), midlife (30-65 years: LEQ-midlife), and late-life (older than 65 years: LEQ-late). LEQ scores were divided into specific and non-specific activities. Multiple regressions were conducted including LEQ scores at the 3 life periods (same model) to predict gray matter volume (GMv; structural-MRI), glucose metabolism (fluorodeoxyglucose-PET), perfusion (early-Florbetapir-PET), or amyloid burden (late-Florbetapir-PET), both in AD-signature regions and voxel-wise (significance for voxel-wise analyses: p < 0.005uncorrected, k > 100). Correlations between LEQ and neuroimaging outcomes were then compared between (1) life periods and (2) specific and non-specific activities. Analyses were controlled for age and sex.
Results:
In 135 older adults (mean age = 69.3 years; women = 61.5%), no associations were found within AD-signature regions (all p > 0.25). Voxel-wise analyses revealed no association between LEQ-young and neuroimaging. LEQ-midlife showed stronger voxel-wise associations than the other periods with GMv, notably in the anterior cingulate cortex, and with amyloid burden in the precuneus. These correlations were stronger for the LEQ-midlife specific (i.e., occupation) than the non-specific subscore (GMv: z = 3.25, p < 0.001, 95% CI [0.1292-0.5135]; amyloid: z = -1.88, p < 0.05, 95% CI [-0.3810 to -0.0113]). LEQ-late showed stronger voxel-wise associations than the other periods with perfusion and glucose metabolism in medial frontal regions. The correlation of perfusion with LEQ-late was stronger for non-specific than specific subscore (z = 2.88, p < 0.01, 95% CI [0.0894-0.4606]).
Discussion:
Lifestyle at different life periods may have complementary benefits on brain health in regions related to reserve/resilience in aging. While past (midlife) engagement could promote resistance against structural/pathologic alterations, current (late-life) engagement could enhance cognitive reserve. Future larger longitudinal studies should explore mechanisms by which lifestyle promotes reserve.
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