Temporal Dynamics and Associations of Device-based Activity Distribution Metrics and Everyday Cognition in Older Adults - The escalating incidence of Alzheimer’s disease and related dementias (ADRD) places a tremendous
economic burden on society and families across the globe. To date, medical approaches for preventing and
treating AD/ADRD have yielded limited success. Preventive strategies, such as physical activity, hold promise
for sustaining cognition and thus reducing AD/ADRD risks in older adults. However, this literature has focused
exclusively on the effects of the total amount of time or volume of higher-intensity physical activity (or exercise)
on cognitive health. Beyond the total volume amount performed, older adults accumulate their physical activity
through irregular lifestyle activity bouts (e.g., intermittent short periods of walking activities) throughout the day.
How these lifestyle activity bouts are accumulated and allocated from day-to-day may represent a scalable and
relatively more achievable behavioral target that may generate cognitive benefits. When older adults’ cognition
is sustained on a daily basis without drastic variations over time, their risks for developing AD/ADRD can be
reduced as a result. Thus, the proposed study is designed to bridge the knowledge gap by determining
whether the distribution of lifestyle physical activity bouts is associated with the mean level and the variability in
older adults’ daily cognitive function. This study will leverage mobile technology to collect data on daily physical
activity bouts and daily cognitive function using a research-grade accelerometer and validated cognitive
assessment smartphone app. To achieve our study objectives, we will recruit older adults who have higher
risks for developing AD/ADRD and will repeatedly measure their daily physical activity bouts and performance-
based cognitive function. A total of 84 high-risk older adults (ages 60+, 40% African American or other races
besides White/Non-Hispanic) will be recruited from the local community. Eligible participants will wear the
lightweight activPAL accelerometer for 21 days to capture the distribution of their daily bouts of physical
activity. During the same 21-day period, they will also complete up to five ultra-brief cognitive tests delivered by
the NIH-funded M2C2 app during waking time each day. We will apply intensive longitudinal data analysis via
an NIH-funded statistical program to answer our research questions. This study will determine if specific
distributions of lifestyle physical activity bouts represent a promising behavioral target that can be engaged in
future efficacy trials for sustaining cognitive health in everyday life. Findings will also provide an evidence-
based foundation for advancing ADRD preventive science to reduce AD/ADRD risks or slowing down the
pathological process during the long pre-clinical AD/ADRD phase.
