A novel physical activity metric predicts cognitive and brain aging and ADRD risk

Project Summary Low physical activity (PA) levels have been associated with elevated risk of Alzheimer’s dementia and related disorders (ADRD). The bulk of this evidence has been derived from self-report measures of PA and focused solely on PA volume and intensity. Objective PA assessment and quantifying dynamics of continuous PA fluctuations over time using accelerometry may extend this area of science by identifying early changes in functional capacity and emergent motor dysfunction, allowing for a deeper understanding of how such changes are connected to brain aging and AD risk. We thus developed a novel metric – “PA complexity” using the multiscale entropy (MSE) method to quantify daily activity patterns by analyzing continuous accelerometer signals and apply this complexity measure to a diverse older population in the Human Connectome Project – Connectomics in Brain Aging and Dementia. This proposed study aims to (1) explore the associations between PA complexity and cognitive function across multiple domains and risk of mild cognitive impairment (MCI) and AD, (2) determine whether low PA complexity relates to AT(N) biomarker classifications and white matter hyperintensities, (3) and examine whether low PA complexity is associated with brain atrophy. This study is significant because (1) understanding the link between complexity of daily PA patterns, cognitive function, and brain atrophy has the potential to yield new insights into the underlying mechanisms connecting motor dysfunction to brain aging, (2) identifying altered complexity of activity patterns as preclinical indicators of ADRD will suggest novel directions for tailored interventions to further prevent or delay the onset of ADRD.