Association between Accelerometer-Measured Light-Intensity Physical Activity and Cognitive Function in Older Adults

Hsiao, Chi; Wen, Chia-Hsien; Yen, Hsin Yen; Hsueh, Ming Chun; Liao, Yung

doi:10.1007/s12603-022-1749-0

Cited by 10 publications

(5 citation statements)

References 25 publications

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“…Similar to the later study, two other studies explored the relationship of objectively measured physical activity measured by a triaxial accelerometer worn for seven consecutive days, and cognitive function among older adult population [24,25]. Both studies reported significant association between light physical activity and cognitive function assessed by the MiniMental State Examination (MMSE) scale [24], and the Montreal Cognitive Assessment (MoCA) [25]. The latter study also revealed that moderatetovigorous physical activity, and total physical activity had a significant linear relationship with cognitive function [25].…”

Section: Objectively Measured Physical Activity and Cognitive Functionmentioning

confidence: 82%

The association between objectively measured physical activity, screen time, and cognitive function: A narrative review

Shalash,

Arumugam,

Qadah

et al. 2024

Fiz Pol

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Aim. This narrative review aimed to investigate the association of objectively measured physical activity and screen time on cognitive function among young adults. Methods. We conducted searches on EBSCO and Google Scholar to identify relevant studies published in English within the last decade. The search terms included keywords such as "physical activity" or "exercise," and "screen time" or "screen exposure," along with "cognition" or "cognitive function." Results. Almost all studies conducted on older adults showed positive associations between physical activity assessed objectively using an accelerometer, screen time, and cognitive function. Conflicting results were observed between physical activity and cognitive functions in young and middle-aged adults. More studies are required to confirm the association between objectively measured physical activity and cognitive function, given the limited availability of studies. Conclusion. The overall findings of this narrative review highlight the negative impact of sedentary behavior on cognitive health, emphasizing the need to incorporate physical activity into our lifestyles to prevent future cognitive decline. Moreover, the impact of screen time and media content yielded contradictory findings on cognitive functions among different age groups, but mostly confirmed the negative effects of passive screen exposure on cognitive functions among children and adolescents. This review highlights the need for future studies to use standardized and objective methods to measure cognitive function, screen time, and media content in different populations, especially among young and middle-aged adults, to raise awareness regarding screen time.

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Section: Objectively Measured Physical Activity and Cognitive Functionmentioning

confidence: 82%

The association between objectively measured physical activity, screen time, and cognitive function: A narrative review

Shalash,

Arumugam,

Qadah

et al. 2024

Fiz Pol

View full text Add to dashboard Cite

show abstract

“…Increased physical activity level, including a low amount of light-intensity physical activity, has been associated with a reduced risk of dementia [ 50 ], and increasing light physical activity helps to maintain cognitive function among community-dwelling older adults [ 51 ]. Additionally, light activity as low as 10 minutes per day measured through accelerometers was previously shown to be associated with better cognitive function, while light physical activity performed ≥3 hours per day could be a protective factor for maintaining cognitive function in older adults [ 52 , 53 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

Xu,

Kim,

Chung

et al. 2024

JMIR Form Res

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Background Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI). Objective This study aimed to use data collected from fitness trackers to predict MCI status. Methods In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status. Results Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time. Conclusions Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

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“…We recruited 208 older adults aged ≥ 65 years who visited the geriatric outpatient clinic at a medical center in Taipei City, Taiwan, between September 2020 and March 2021 for treatment or health check-up. The detailed inclusion and exclusion criteria were as described in our previous study [19]. Briefly, older adults who could walk independently and had no severe hearing or visual impairment affecting communication were included.…”

Section: Participantsmentioning

confidence: 99%

Effect of isotemporal substitution of sedentary behavior with different intensities of physical activity on the muscle function of older adults in the context of a medical center

et al. 2023

Self Cite

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Background Engaging in physical activity and reducing sedentary time in daily life may enable older individuals to maintain muscle mass. This study aimed to investigate the effects of replacing sedentary behavior with light physical activity (LPA) or moderate-to-vigorous physical activity (MVPA) on the muscle function of older adults at a medical center in Taiwan. Methods We recruited 141 older adults (51.1% men; 81.1 ± 6.9 years old) and asked them to wear a triaxial accelerometer on the waist to measure their sedentary behavior and physical activity. Functional performance was assessed based on handgrip strength, Timed Up and Go (TUG) test, gait speed, and five-times-sit-to-stand test (5XSST). Isotemporal substitution analysis was performed to examine the effect of substituting 60 min of sedentary time with 60 min of LPA, MVPA, and combined LPA and MVPA in different proportions. Results Reallocating 60 min of sedentary behavior per day to LPA was associated with better handgrip strength (Beta [B] = 1.587, 95% confidence interval [CI] = 0.706, 2.468), TUG test findings (B = -1.415, 95% CI = -2.186, -0.643), and gait speed (B = 0.042, 95% CI = 0.007, 0.078). Reallocating 60 min of sedentary behavior per day to MVPA was associated with better gait speed (B = 0.105, 95% CI = 0.018, 0.193) and 5XSST findings (B = -0.060, 95% CI = -0.117, -0.003). In addition, each 5-min increment in MVPA in the total physical activity replacing 60 min of sedentary behavior per day resulted in greater gait speed. Replacing 60 min of sedentary behavior with 30-min of LPA and 30-min of MVPA per day significantly decreased the 5XSST test time. Conclusion Our study indicates that introducing LPA and a combination of LPA and MVPA to specifically replace sedentary behavior may help maintain muscle function in older adults.

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Association between Accelerometer-Measured Light-Intensity Physical Activity and Cognitive Function in Older Adults

Cited by 10 publications

References 25 publications

The association between objectively measured physical activity, screen time, and cognitive function: A narrative review

The association between objectively measured physical activity, screen time, and cognitive function: A narrative review

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

Effect of isotemporal substitution of sedentary behavior with different intensities of physical activity on the muscle function of older adults in the context of a medical center

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