Daily and hourly patterns of physical activity and sedentary behavior of older adults: Atherosclerosis risk in communities (ARIC) study

Dooley, Erin E.; Pompeii, Lisa; Palta, Priya; Martínez-Amezcua, Pablo; Hornikel, Bjoern; Evenson, Kelly R.; Schrack, Jennifer A.; Gabriel, Kelley Pettee

doi:10.1016/j.pmedr.2022.101859

Cited by 8 publications

(12 citation statements)

References 57 publications

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“… 1 , 6 , 7 The participants had low between-day variability among postmenopausal women; therefore, we simplified the model and explored weekly patterns. It should be noted that our findings are in contrast to other studies of older adults that found less physical activity on Sundays compared to Saturdays, 30 – 33 and higher sedentary behavior on the weekends compared to the weekdays. 34 …”

Section: Discussioncontrasting

confidence: 99%

“…We also explored latent class patterns by both clock time and time since awake, with the latter being superior with regards to missing data. Our findings were similar to other studies of older adults in that physical activity generally peaked earlier in the morning and declined the rest of the day overall, 31 , 32 , 35 – 37 for men, 33 and for women. 38 This pattern is in contrast to another study of younger adults that accumulated more physical activity in the afternoon and sustained their physical activity levels longer.…”

Section: Discussionsupporting

confidence: 91%

“… 38 This pattern is in contrast to another study of younger adults that accumulated more physical activity in the afternoon and sustained their physical activity levels longer. 37 Our findings also concurred with others that found sedentary behavior to be more common toward the end of the day, 31 particularly with fewer sedentary breaks. 34 …”

Section: Discussionsupporting

confidence: 90%

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Accelerometry-assessed physical activity and sedentary behavior patterns using single- and multi-component latent class analysis among postmenopausal women

Evenson,

Wen,

et al. 2024

Womens Health (Lond Engl)

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Background: Patterns of physical activity and sedentary behavior among postmenopausal women are not well characterized. Objectives: To describe the patterns of accelerometer-assessed physical activity and sedentary behavior among postmenopausal women. Design: Cross-sectional study. Methods: Women 63–97 years (n = 6126) wore an ActiGraph GT3X + accelerometer on their hip for 1 week. Latent class analysis was used to classify women by patterns of percent of wake time in physical activity and sedentary behavior over the week. Results: On average, participants spent two-thirds of their day in sedentary behavior (62.3%), 21.1% in light low, 11.0% in light high, and 5.6% in moderate-to-vigorous physical activity. Five classes emerged for each single-component model for sedentary behavior and light low, light high, and moderate-to-vigorous physical activity. Six classes emerged for the multi-component model that simultaneously considered the four behaviors together. Conclusion: Unique profiles were identified in both single- and multi-component models that can provide new insights into habitual patterns of physical activity and sedentary behavior among postmenopausal women. Implications: The multi-component approach can contribute to refining public health guidelines that integrate recommendations for both enhancing age-appropriate physical activity levels and reducing time spent in sedentary behavior.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 90%

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Accelerometry-assessed physical activity and sedentary behavior patterns using single- and multi-component latent class analysis among postmenopausal women

Evenson,

Wen,

et al. 2024

Womens Health (Lond Engl)

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“…During the first 6 months of visit 6, a subset of participants were also offered to wear an ActiGraph accelerometer as part of a physical activity and falls study. More complete information and inclusion/exclusion criteria for the Zio XT data collection in ARIC visit 6 are presented elsewhere [19,20].…”

Section: Participantsmentioning

confidence: 99%

Validation of a Zio XT Patch Accelerometer for the Objective Assessment of Physical Activity in the Atherosclerosis Risk in Communities (ARIC) Study

Davoudi,

Urbanek,

Etzkorn

et al. 2024

Sensors

Self Cite

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Background: Combination devices to monitor heart rate/rhythms and physical activity are becoming increasingly popular in research and clinical settings. The Zio XT Patch (iRhythm Technologies, San Francisco, CA, USA) is US Food and Drug Administration (FDA)-approved for monitoring heart rhythms, but the validity of its accelerometer for assessing physical activity is unknown. Objective: To validate the accelerometer in the Zio XT Patch for measuring physical activity against the widely-used ActiGraph GT3X. Methods: The Zio XT and ActiGraph wGT3X-BT (Actigraph, Pensacola, FL, USA) were worn simultaneously in two separately-funded ancillary studies to Visit 6 of the Atherosclerosis Risk in Communities (ARIC) Study (2016–2017). Zio XT was worn on the chest and ActiGraph was worn on the hip. Raw accelerometer data were summarized using mean absolute deviation (MAD) for six different epoch lengths (1-min, 5-min, 10-min, 30-min, 1-h, and 2-h). Participants who had ≥3 days of at least 10 h of valid data between 7 a.m–11 p.m were included. Agreement of epoch-level MAD between the two devices was evaluated using correlation and mean squared error (MSE). Results: Among 257 participants (average age: 78.5 ± 4.7 years; 59.1% female), there were strong correlations between MAD values from Zio XT and ActiGraph (average r: 1-min: 0.66, 5-min: 0.90, 10-min: 0.93, 30-min: 0.93, 1-h: 0.89, 2-h: 0.82), with relatively low error values (Average MSE × 106: 1-min: 349.37 g, 5-min: 86.25 g, 10-min: 56.80 g, 30-min: 45.46 g, 1-h: 52.56 g, 2-h: 54.58 g). Conclusions: These findings suggest that Zio XT accelerometry is valid for measuring duration, frequency, and intensity of physical activity within time epochs of 5-min to 2-h.

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“…As a result, these scores can be associated with health and ageing markers. In general, studies in older adults have found that both short and prolonged MVPA episodes throughout the day associate with healthier body composition (lower weight or fat percentages) [19], can improve cardio-metabolic health [9, 20, 21, 22], and lower the risk of multi-morbidity [23].…”

Section: Introductionmentioning

confidence: 99%

Changes in the physical behaviour of older adults during the 13 weeks GOTO intervention explain a boost in immuno-metabolic health

Paraschiakos,

Bogaards,

Knobbe

et al. 2023

Preprint

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BackgroundThe aging population faces numerous health challenges, with sedentary behavior and decreased physical activity being paramount. We explore the physical behaviour of older adults in the GOTO combined lifestyle intervention study and its related immuno-metabolic health effects.MethodsThe research utilized accelerometers and machine learning to assess physical activity behaviours during a 13-week program of increased physical activity and decreased calorie intake. Subsequently, the association of variation in physical behaviour with immuno-metabolic health parameters is investigated cross-sectionally at baseline and longitudinally using sex-stratified linear regression and linear mixed regression respectively.ResultsParticipants exhibited physical behaviors similar to their age-matched peers from the UK-Biobank. Interestingly, gender-based differences were evident, with men and women showing distinct daily physical behavioural patterns. At baseline, a positive correlation was found between higher physical behavior and a healthier immune-metabolic profile, particularly in men. The longitudinal changes depict an overall boost in activity levels, predominantly among women. While increasing general activity and engaging in intense exercises proved advantageous for physical health, the immune-metabolic health benefits were more pronounced in men.ConclusionThe short-term GOTO intervention underscores the significance of regular physical activity in promoting healthy aging even in middle to older age. Gender differences in behavior and health benefits deserve much more attention though. Our results advocate the broader implementation of such programs and emphasize the utility of technology, like accelerometers and machine learning, in both monitoring and promoting active lifestyles among older adults.

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Daily and hourly patterns of physical activity and sedentary behavior of older adults: Atherosclerosis risk in communities (ARIC) study

Cited by 8 publications

References 57 publications

Accelerometry-assessed physical activity and sedentary behavior patterns using single- and multi-component latent class analysis among postmenopausal women

Accelerometry-assessed physical activity and sedentary behavior patterns using single- and multi-component latent class analysis among postmenopausal women

Validation of a Zio XT Patch Accelerometer for the Objective Assessment of Physical Activity in the Atherosclerosis Risk in Communities (ARIC) Study

Changes in the physical behaviour of older adults during the 13 weeks GOTO intervention explain a boost in immuno-metabolic health

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