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Free-living wrist and hip accelerometry forecast cognitive decline among older adults without dementia over 1- or 5-years in two distinct observational cohorts

Medicine and Health

Free-living wrist and hip accelerometry forecast cognitive decline among older adults without dementia over 1- or 5-years in two distinct observational cohorts

C. Shi, N. Babiker, et al.

This groundbreaking study uncovers how free-living accelerometry data can predict cognitive decline in older adults without dementia, achieving impressive accuracy levels. Conducted by leading researchers, including Chengjian Shi and Andrey Rzhetsky, the work highlights innovative methods that could transform clinical practices.... show more
Abstract
The prevalence of major neurocognitive disorders is expected to rise over the next 3 decades as the number of adults ≥65 years old increases. Noninvasive screening capable of flagging individuals most at risk of subsequent cognitive decline could trigger closer monitoring and preventive strategies. In this study, we used free-living accelerometry data to forecast cognitive decline within 1- or 5-years in older adults without dementia using two cohorts. The first cohort, recruited in the south side of Chicago, wore hip accelerometers for 7 continuous days. The second cohort, nationally recruited, wore wrist accelerometers continuously for 72 h. Separate classifier models forecasted 1-year cognitive decline with over 85% accuracy using hip data and forecasted 5-year cognitive decline with nearly 70% accuracy using wrist data, significant improvements compared to demographics and comorbidities alone. The proposed models are readily translatable to clinical practices serving ageing populations.
Publisher
npj Aging
Published On
Jun 06, 2022
Authors
Chengjian Shi, Niser Babiker, Jacek K. Urbanek, Robert L. Grossman, Megan Huisingh-Scheetz, Andrey Rzhetsky
Tags
cognitive decline
accelerometry
older adults
machine learning
predictive modeling
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