{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T14:10:37Z","timestamp":1790086237273,"version":"4.0.1"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:00:00Z","timestamp":1661904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000957","name":"Alzheimer\u2019s Association","doi-asserted-by":"publisher","award":["AARG-20-683875, PI: KC"],"award-info":[{"award-number":["AARG-20-683875, PI: KC"]}],"id":[{"id":"10.13039\/100000957","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001167","name":"Larry L. Hillblom Foundation Network","doi-asserted-by":"publisher","award":["2014-A-004-NET"],"award-info":[{"award-number":["2014-A-004-NET"]}],"id":[{"id":"10.13039\/100001167","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:p>\n                    Physical activity (PA) is associated with preserved age-related body and brain health. However, PA quantification can vary. Commercial-grade wearable monitors are objective, low burden tools to capture PA but are less well validated in older adults. Self-report PA questionnaires are widely accepted and more frequently used but carry inherent limitations. We aimed to compare these commonly used PA measures against one another and examine their convergent validity with a host of relevant outcomes. We also examined the factors that drive differences in PA self-reporting styles in older adults. 179 older adults completed 30-day Fitbit Flex2\u2122 monitoring and reported PA levels\n                    <jats:italic>via<\/jats:italic>\n                    two widely used PA questionnaires: PASE and CHAMPS-METs (metabolic expenditure calories burned). Participants also completed measures of cardiometabolic (hypertension diagnosis, resting heart rate, A1C levels), cognitive (memory, processing speed, executive functioning), and brain MRI (medial temporal lobe volume) outcomes. The discrepancy between objective Fitbit monitoring and self-reported PA was evaluated using a sample-based z difference score. There were only modest relationships across all PA metrics. Fitbit step count demonstrated a stronger association with the PASE, whereas Fitbit calories burned was more strongly associated with CHAMPS-MET. Fitbit outcomes had more consistent convergence with relevant outcomes of interest (e.g., cardiometabolic and brain health indices) when compared to subjective measures; however, considerable heterogeneity within these associations was observed. A higher degree of overreporting was associated with worse memory and executive performances, as well as hypertension diagnoses. We build on prior findings that wearable, digital health indicators of PA demonstrate greater construct validity than self-report in older adults. We further show important clinical features (e.g., poorer cognitive status) of older adults that could contribute to a higher level of overreporting on self-report measures. Characterization of what PA measures truly operationalize will help elucidate relationships between most relevant facets of PA and outcomes of interest.\n                  <\/jats:p>","DOI":"10.3389\/fdgth.2022.869790","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:51:11Z","timestamp":1661907071000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":59,"title":["Physical activity measurement in older adults: Wearables versus 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