Dataset Information

Delayed sleep timing is associated with low levels of free-living physical activity in normal sleeping adults.

ABSTRACT:

Objective and background

We and others have reported that experimentally induced short sleep does not affect resting metabolic rate and leads to increased laboratory-measured 24-h energy expenditure. Here, we aimed to determine if sleep timing and/or quality are related to physical activity (PA) levels.

Methods

Measures of PA via waist actigraphy, sleep diary, and sleep quality questionnaires were collected over a 7-18-day period in 22 adults (mean age ± standard deviation (SD): 35.8 ± 4.6 years, and mean body mass index ± SD: 23.8 ± 1.1 kg/m(2)) who were on their habitual sleep-wake and activity schedules.

Results

During the recording period, mean (±SD) bedtime and wake times were 00:17 ± 1:07 h (range: 22:02-02:07 h) and 08:20 ± 1:14 h (range: 06:30-10:11 h), respectively. After controlling for sleep duration, later bedtime, wake time, and midpoint of sleep were associated with less time spent in moderate-to-vigorous PA (p = 0.013, p = 0.005, and p = 0.007, respectively), and increased time in sedentary PA (p = 0.016, p = 0.013, and p = 0.013, respectively).

Conclusions

Current results suggest that even relatively small alterations in sleep timing may influence PA. However, causality cannot be inferred from this cross-sectional study. Clinical intervention studies should be conducted to assess the relationship between sleep timing and energy balance.

SUBMITTER: Shechter A

PROVIDER: S-EPMC4260995 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Publications

Delayed sleep timing is associated with low levels of free-living physical activity in normal sleeping adults.

Shechter Ari A St-Onge Marie-Pierre MP

Sleep medicine 20140902 12

<h4>Objective and background</h4>We and others have reported that experimentally induced short sleep does not affect resting metabolic rate and leads to increased laboratory-measured 24-h energy expenditure. Here, we aimed to determine if sleep timing and/or quality are related to physical activity (PA) levels.<h4>Methods</h4>Measures of PA via waist actigraphy, sleep diary, and sleep quality questionnaires were collected over a 7-18-day period in 22 adults (mean age ± standard deviation (SD): 3 ...[more]

PMID: 25311835

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Project description:BackgroundWearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.ObjectiveThis study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2.MethodsA free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0.ResultsLarge variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA.ConclusionsThis study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.

Project description:BackgroundAdequate sleep and physical activity promote longevity among older adults. Caffeine supplementation could be used to increase activity levels, but its effects have not been examined in real-world settings where potential trade-offs regarding sleep quality are also considered. This study sought to examine associations between caffeine intake and accelerometer-derived sleep and activity among older adults under free-living conditions.MethodsCross-sectional data were gathered from older adults aged 65 + in the 2011-14 National Health and Nutrition Examination Surveys (NHANES). Sleep parameters were derived from accelerometer data using a data-driven machine learning approach. Caffeine consumption was categorized based on weight (in mg/kg: 0, > 0 to 1, > 1 to 2, > 2 to 3, > 3) and absolute consumption (in mg: 0, > 0 to 100, > 100 to 200, > 200 to 300, > 300). Multivariable survey weighted regression models were used to examine associations between caffeine with average total daytime activity, highly active minutes, sleep duration, and sleep efficiency. Covariate adjustments included demographics, body mass index, smoking, alcohol, sleep disorders, sleep parameters (for activity outcomes), and daytime activity (for sleep outcomes).ResultsN = 1,629 NHANES participants were included. Caffeine consumption was highest in the morning. In adjusted models, older adults who consumed > 3 mg/kg were 16.5% more active during the day (95% CI: 9.0, 24.4) and were highly active for 42.8 additional minutes (95% CI: 20.3, 65.4) compared to non-consumers. Similar results were observed for absolute consumption (mg), and significant but lower magnitude effects were observed for lower levels of consumption. Caffeine showed no association with sleep efficiency, while low levels of consumption (≤ 1 mg/kg, ≤ 200 mg) were associated with longer sleep duration.ConclusionsUnder free-living dietary, sleep, and activity patterns, this study found older adults who consumed caffeine were more active than non-consumers. Overall consumption was not associated with sleep efficiency but was associated with longer sleep duration at ≤ 1 mg/kg and ≤ 200 mg. Future causal studies should determine the effectiveness of caffeine for promoting higher activity in older adult populations.

Dataset Information

Delayed sleep timing is associated with low levels of free-living physical activity in normal sleeping adults.

Objective and background

Methods

Results

Conclusions

Publications

Delayed sleep timing is associated with low levels of free-living physical activity in normal sleeping adults.

Similar Datasets

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