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Background: This study tested if the timing of meals, physical activity, light exposure, and sleep cluster within individuals and are associated with body mass index (BMI) in a sample of free-living adults (N = 125)., Methods: Data were collected between November 2015 and March 2016 at the University of California, San Diego, Children's Hospital of Philadelphia, and Washington University in St Louis. Height and weight were measured, and BMI (kg/m 2 ) was calculated. Sleep timing was estimated using actigraphy, and timing of meals, physical activity, and light exposure were self-reported using a smartphone application. General linear models estimated the mean BMI across time categories of behaviors, adjusting for covariates. A latent class analysis was used to identify patterns of timing variables that clustered within individuals and test for associations between identified patterns and BMI., Results: Later exposure to outdoor light was associated with a lower BMI (P trend < .01). The timing of other behaviors was not independently associated with BMI. The latent class analysis identified 2 distinct groups related to behavioral timing, reflecting an "early bird" and "night owl" phenotype. These phenotypes were not associated with BMI (P > .05)., Conclusion: Timing of exposures to light, meals, sleep, and physical activity were not strongly associated with BMI in this sample.

Study Objectives: To examine associations between 24-hour rest-activity patterns and body mass index (BMI) among community-dwelling US adults. Rest-activity patterns provide a field method to study exposures related to circadian rhythms., Methods: Adults (N = 578) wore an actigraph on their nondominant wrist for 7 days. Intradaily variability and interdaily stability (IS), M10 (most active 10-hours), L5 (least active 5-hours), and relative amplitude (RA) were derived using nonparametric rhythm analysis. Mesor, acrophase, and amplitude were calculated from log-transformed count data using the parametric cosinor approach., Results: Participants were 80% female and mean (standard deviation) age was 52 (15) years. Participants with higher BMI had lower values for magnitude, RA, IS, total sleep time (TST), and sleep efficiency. In multivariable analyses, less robust 24-hour rest-activity patterns as represented by lower RA were consistently associated with higher BMI: comparing the bottom quintile (least robust) to the top quintile (most robust 24-hour rest-activity pattern) of RA, BMI was 3-kg/m2 higher (p = .02). Associations were similar in magnitude to an hour less of TST (1-kg/m2 higher BMI) or a 10% decrease in sleep efficiency (2-kg/m2 higher BMI), and independent of age, sex, race, education, and the duration of rest and/or activity., Conclusions: Lower RA, reflecting both higher night activity and lower daytime activity, was associated with higher BMI. Independent of the duration of rest or activity during the day or night, 24-hour rest, and activity patterns from actigraphy provide aggregated measures of activity that associate with BMI in community-dwelling adults., (© Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs.

Rest-activity patterns provide an indication of circadian rhythmicity in the free-living setting. We aimed to describe the distributions of rest-activity patterns in a sample of adults and children across demographic variables. A sample of adults (N = 590) and children (N = 58) wore an actigraph on their nondominant wrist for 7 days and nights. We generated rest-activity patterns from cosinor analysis (MESOR, acrophase and magnitude) and nonparametric circadian rhythm analysis (IS: interdaily stability; IV: intradaily variability; L5: least active 5-hour period; M10: most active 10-hour period; and RA: relative amplitude). Demographic variables included age, sex, race, education, marital status, and income. Linear mixed-effects models were used to test for demographic differences in rest-activity patterns. Adolescents, compared to younger children, had (1) later M10 midpoints (β = 1.12 hours [95% CI: 0.43, 1.18] and lower M10 activity levels; (2) later L5 midpoints (β = 1.6 hours [95% CI: 0.9, 2.3]) and lower L5 activity levels; (3) less regular rest-activity patterns (lower IS and higher IV); and 4) lower magnitudes (β = -0.95 [95% CI: -1.28, -0.63]) and relative amplitudes (β = -0.1 [95% CI: -0.14, -0.06]). Mid-to-older adults, compared to younger adults (aged 18-29 years), had (1) earlier M10 midpoints (β = -1.0 hours [95% CI: -1.6, -0.4]; (2) earlier L5 midpoints (β = -0.7 hours [95% CI: -1.2, -0.2]); and (3) more regular rest-activity patterns (higher IS and lower IV). The magnitudes and relative amplitudes were similar across the adult age categories. Sex, race and education level rest-activity differences were also observed. Rest-activity patterns vary across the lifespan, and differ by race, sex and education. Understanding population variation in these patterns provides a foundation for further elucidating the health implications of rest-activity patterns across the lifespan.

Purpose: This study aimed to determine whether physical activity patterns are associated with sleep later at night and if nighttime sleep is associated with physical activity patterns the next day among adult women., Methods: Women (N = 353) living throughout the United States wore a wrist and a hip accelerometer for 7 d. Total sleep time (TST, hours per night) and sleep efficiency (SE, %) were estimated from the wrist accelerometer, and moderate to vigorous physical activity (MVPA, >1040 counts per minute, h·d) and sedentary behavior (SB, <100 counts per minute, h·d) were estimated from the hip accelerometer. Mixed-effects models adjusted for age, race, body mass index, education, employment, marital status, health status, and hip accelerometer wear time were used to analyze the data. Follow-up analyses using quantile regression were used to investigate associations among women with below average TST and MVPA and above average SB., Results: The average age of our sample was 55.5 yr (SD = 10.2 yr). The majority of participants were White (79%) and married (72%), and half were employed full time (49%). The participants spent on average 8.9 and 1.1 h·d in SB and MVPA, respectively, and 6.8 h per night asleep. No associations were observed between MVPA and SB with nighttime TST or SE. There were no associations between nighttime TST and SE with MVPA or SB the next day. The findings were the same in the quantile regression analyses., Conclusion: In free-living adult women, accelerometry-estimated nighttime sleep and physical activity patterns were not associated with one another. On the basis of our observational study involving a sample of adult women, higher physical activity will not necessarily improve sleep at night on a day-to-day basis (and vice versa)., Competing Interests: The results of the present study do not constitute endorsement by ACSM

Zeitgebers such as light, eating and physical activity provide input to the circadian clock. Chronic circadian misalignment is associated with significant adverse health effects. An improved understanding of the impact of the timing of zeitgebers on the stability of 24-hour rest-activity rhythm in free-living settings may identify behavioural and environmental intervention targets. A total of 133 healthy adults, aged 21-60 years, wore a wrist actigraph for 7 consecutive days. We applied a non-parametric analysis to activity counts to derive rest-activity patterns. We administered a questionnaire through a smartphone app to collect self-reported timing of light exposure, eating episodes and physical activity. To assess the relationship between timing exposures (first and last exposure to outdoor light, first exposure to indoor light, last eating episode, first eating episode, morning physical activity proportion, evening physical activity proportion) and rest-activity or sleep outcomes (bedtimes, total sleep time, inter-daily stability, intra-daily variability, L5 and M10 midpoint), we first calculated Spearman correlations, using the false discovery rate method to control for multiple comparisons. From those significant associations, we then fit regression models adjusting for age, sex, race, household income, education level, study site, body mass index, as well as physical activity. Finally, we tested for interaction between chronotype and each timing-related exposure and stratified the analysis by morning type. All zeitgebers, except for evening physical activity proportion, were correlated with at least four of the seven sleep and rest-activity outcomes. In adjusted analysis, later timing of first (after 6:30 to 7:45 AM versus earlier) and last exposure to indoor light (after 11:00 PM versus earlier) and first (after 7:45-9:45 AM versus earlier) and last eating episode (after 8:00-09:00 PM versus earlier) were associated with a shift of 0.60-1.39 hours to later bedtimes, M10 and L5 midpoints (i.e. timing of peak activities or inactivities). Later timing of first exposure to outdoor light (after 09:30 AM versus earlier) was also associated with 0.51 (95% CI: 0.19 to 0.83) hours longer total sleep time. Higher morning physical activity proportion (> 33%) was associated with 0.95 (95% CI: −1.38 to −0.53) hours earlier in-bed time and 0.69 (95% CI: −1.14 to −0.24) hours earlier out-of-bed time, 0.92 (95% CI: −1.41 to −0.42) hours earlier M10 and 0.96 (95% CI: −1.42 to −0.49) min earlier L5 midpoint. The results did not change substantially with further adjustment for total activity. There was a significant interaction between morning chronotype and first eating episode with rest-activity patterns (p < 0.05), with first eating episode associating with timing of activities only in non-morning type adults. Timing of zeitgebers was associated with sleep and rest-activity patterns, including bedtimes, L5 and M10 midpoint. Future research should evaluate the impact of manipulating zeitgebers on both circadian rhythms and health outcomes. [ABSTRACT FROM AUTHOR]