Prediction of good sleep with physical activity and light exposure: a preliminary study

Author(s):  
Kyung Mee Park ◽  
Sang Eun Lee ◽  
Changhee Lee ◽  
Hyun Duck Hwang ◽  
Do Hoon Yoon ◽  
...  
Author(s):  
Jennette P. Moreno ◽  
Javad Razjouyan ◽  
Houston Lester ◽  
Hafza Dadabhoy ◽  
Mona Amirmazaheri ◽  
...  

Abstract Objectives and background Social demands of the school-year and summer environment may affect children’s sleep patterns and circadian rhythms during these periods. The current study examined differences in children’s sleep and circadian-related behaviors during the school-year and summer and explored the association between sleep and circadian parameters and change in body mass index (BMI) during these time periods. Methods This was a prospective observational study with 119 children ages 5 to 8 years with three sequential BMI assessments: early school-year (fall), late school-year (spring), and beginning of the following school-year in Houston, Texas, USA. Sleep midpoint, sleep duration, variability of sleep midpoint, physical activity, and light exposure were estimated using wrist-worn accelerometry during the school-year (fall) and summer. To examine the effect of sleep parameters, physical activity level, and light exposure on change in BMI, growth curve modeling was conducted controlling for age, race, sex, and chronotype. Results Children’s sleep midpoint shifted later by an average of 1.5 h during summer compared to the school-year. After controlling for covariates, later sleep midpoints predicted larger increases in BMI during summer, (γ = .0004, p = .03), but not during the school-year. Sleep duration, sleep midpoint variability, physical activity levels, and sedentary behavior were not associated with change in BMI during the school-year or summer. Females tended to increase their BMI at a faster rate during summer compared to males, γ = .06, p = .049. Greater amounts of outdoor light exposure (γ = −.01, p = .02) predicted smaller increases in school-year BMI. Conclusions Obesity prevention interventions may need to target different behaviors depending on whether children are in or out of school. Promotion of outdoor time during the school-year and earlier sleep times during the summer may be effective obesity prevention strategies during these respective times.


SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A258-A258
Author(s):  
Megan Petrov ◽  
Matthew Buman ◽  
Dana Epstein ◽  
Shawn Youngstedt ◽  
Nicole Hoffmann ◽  
...  

Abstract Introduction Evening chronotype (i.e., night owl preference) is associated with worse insomnia and depressive symptoms, and poorer health behaviors. The aim of this study was to examine the association between chronotype and these symptoms and health behaviors during COVID-19 pandemic quarantine. Methods An online survey, distributed internationally via social media from 5/21/2020–7/1/2020, asked adults to report sociodemographic/economic information, changes in sleep (midpoint, total sleep time, sleep efficiency, time-in-bed), and health behaviors (i.e., physical activity, sedentary screen time, and outdoor light exposure patterns) from prior to during the pandemic, chronotype preference (definitely morning [DM], rather more morning [RM], rather more evening [RE], or definitely evening [DE]), and complete the Insomnia Severity Index (ISI) and the 10-item Center for Epidemiologic Studies Depression scale (CES-D-10). Multinomial logistic regression and ANCOVA models, adjusting for age and sex, examined associations of chronotype with COVID-19 pandemic related impacts on sleep, depressive symptoms, and health behaviors. Results A subsample of 579 participants (M age: 39y, range: 18–80; 73.6% female), currently under quarantine and neither pregnant nor performing shift work, represented each chronotype evenly (~25%). Participants delayed their sleep midpoint by 72.0min (SD=111.5) during the pandemic. DE chronotypes had a greater delay than morning types (M±SD DE: 91.0±9.0 vs. RM: 55.9±9.2 & DM: 66.1±9.3; p=0.046) with no significant change in other sleep patterns relative to other chronotypes. However, DE and RE chronotypes had greater odds of reporting that their new sleep/wake schedule was still not consistent with their “body clock” preference relative to morning types (Χ2[15]=54.8, p<0.001), reported greater ISI (F[3,503]=5.3, p=.001) and CES-D-10 scores (F[3,492]=7.9, p<.001), and had greater odds for increased or consistently moderate-to-high sedentary screen time (Χ2[12]=22.7, p=0.03) and decreased physical activity (Χ2[12]=22.5, p=0.03) than DM chronotype. There was no significant difference in change in outdoor light exposure by chronotype (Χ2[12]=12.1, p=0.43). Conclusion In an international online sample of adults under COVID-19 pandemic quarantine, evening chronotypes, despite taking the opportunity to delay sleep to match biological clock preference, reported their sleep/wake schedules were still inconsistent with personal preference, and reported greater insomnia and depressive symptoms, and odds of engaging in poorer health behaviors than morning chronotypes. Support (if any):


Author(s):  
Lovro Štefan ◽  
Goran Vrgoč ◽  
Tomislav Rupčić ◽  
Goran Sporiš ◽  
Damir Sekulić

The main purpose of the study was to explore the associations of sleep duration and sleep quality with physical activity (PA). In this cross-sectional study, participants were 894 elderly individuals (mean age 80 ± 3 years; 56.0% women) living in nursing homes. PA, sleep duration, and sleep quality (based on the Pittsburgh Sleep Quality Index (PSQI)) were self-reported. The associations of sleep duration and sleep quality with PA at the nursing home level were analyzed using generalized estimating equations with clustering. Participants reporting short sleep duration (<6 h; OR = 0.45; 95% CI 0.25–0.80) were less likely to report sufficient PA, yet those reporting long sleep duration (>9 h; OR = 2.61; 95% CI 1.35–5.02) and good sleep quality (<5 points; OR = 1.59; 95% CI 1.19–2.12) were more likely to report sufficient PA. When sleep duration and sleep quality were entered into the same model, the same associations remained. This study shows that elderly individuals who report short sleep duration are less likely to meet PA guidelines, while those who report long sleep duration and good sleep quality are more likely to meet PA guidelines. Strategies aiming to improve sleep duration and sleep quality are warranted.


Author(s):  
Einat Shneor ◽  
Ravid Doron ◽  
Jonathan Levine ◽  
Deena Rachel Zimmerman ◽  
Julia S. Benoit ◽  
...  

Studies using questionnaires report that COVID-19 restrictions resulted in children spending significantly less time outdoors. This study used objective measures to assess the impact of pandemic-related restrictions on children’s behavior. A total of 19 healthy 8–12-year-old boys were observed before and during social restriction periods. Of these, 11 boys were reassessed after restrictions were lifted. For each session, Actiwatches were dispensed for measures of time outdoors, activity, and sleep. Changes overall and by school status were assessed using signed-rank test and Wilcoxon rank sum tests. During restrictions, children spent significantly less time outdoors (p = 0.001), were less active (p = 0.001), and spent less time engaged in moderate-to-vigorous physical activity (p = 0.004). Sleep duration was not significantly different between sessions (p > 0.99), but bedtime and wake time shifted to a later time during restrictions (p < 0.05 for both). Time outdoors and activity returned close to pre-pandemic levels after restrictions were lifted (p > 0.05 for both). Children’s behaviors significantly changed during the COVID-19 pandemic. The reduction in outdoor light exposure is of importance due to the role of light in the etiology of myopia and vitamin D production. The reduction in physical activity may have negative health effects in terms of obesity and depression, although further research is required to ascertain the long-term effects.


Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Christopher C Imes ◽  
Zhadyra Bizhanova ◽  
Christopher E Kline ◽  
Susan M Sereika ◽  
Eileen Chasens

Introduction: Sleep health is multi-dimensional. The RSATED Sleep Health composite score, hereafter referred to as RSATED, includes regularity, satisfaction, alertness, timing, efficiency, and duration. RSATED has been associated with cardiovascular (CV) health in a nationally representative sample. However, the association between RSATED and CV health in adults with obstructive sleep apnea (OSA) and type 2 diabetes mellitus (T2DM) have not been examined. Purpose: This secondary analysis examined the associations between RSATED and CV health measures including body mass index (BMI), lipid levels, and physical activity. Methods: We used baseline data from the Diabetes Sleep Treatment Trial, a randomized controlled trial that examined if adults with co-existing OSA and T2DM treated with continuous positive airway pressure had better glycemic control compared to participants that received a non-therapeutic treatment. Data collected included questionnaires, anthropometric measurements, a lipid panel, objective physical activity (PA) data (BodyMedia), apnea-hypopnea index (AHI; ApneaLink Pro), and a modified Consensus Sleep Diary. RSATED was calculated using up to 7 days of sleep data and Epworth Sleepiness Scale (ESS). Individual components were given a score of 0 or 1 with 1 representing “good” sleep. “Good” sleep was defined as: >80% of awakenings occurring during the same time range (regularity); mean sleep quality of “good” or “very good” (satisfaction); ESS total score ≤10 (alertness); >80% of sleep midpoint occurring between 2-4 am (timing); sleep efficiency ≥85% (efficiency); and mean sleep duration of 7-9 hrs/night (duration). The total score could range from 0-6; higher scores represented better sleep. The associations between RSATED and CV health measures were examined using linear regression models. All models were adjusted for AHI, marital status, race, age, and education. Results: A total of 350 individuals underwent screening. Of the 253 participants with complete data, the majority were female (52.2%) and white (54.2%) with a mean (± SD) age of 56.6 ± 10.5 yrs, BMI of 34.2 ± 7.1, and AHI of 14.1 ± 15.1. Mean RSATED was 2.8 ± 1.2 (range 0-5). The RSATED score was not associated with any of the CV health measures. However, there was a trend for significance for better sleep health to be associated with greater vigorous PA (b = 0.46, p = .08). Whereas, greater AHI was associated with higher BMI, higher total cholesterol, greater sedentary time, and less moderate- and vigorous-intensity PA (p-values from .05 to <.0001). Conclusions: Among adults with co-existing OSA and T2DM, AHI was more strongly associated with measures of CV health than RSATED. While sleep health is essential, the underlying impact of OSA on CV health and its treatment should remain a priority. Future studies should continue to examine the associations between sleep health and other measures of health and wellness.


PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137742 ◽  
Author(s):  
Michèle Bisson ◽  
Natalie Alméras ◽  
Sébastien S. Dufresne ◽  
Julie Robitaille ◽  
Caroline Rhéaume ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Aneta Otocka-Kmiecik ◽  
Marek Lewandowski ◽  
Urszula Szkudlarek ◽  
Dariusz Nowak ◽  
Monika Orlowska-Majdak

The aim of the study was to compare the effect of maximal exercise (ME) on paraoxonase (PON) and arylesterase (ARE) activity depending on lifestyle in respect to physical activity. The study was performed on 46 young men divided into two groups: sedentary (S) and physically active (PA). All participants performed ME on a treadmill. PON1 activities, FRAP, uric acid, bilirubin, TBARS, and lipid profile were determined in their blood before, at the bout of, and after ME. No significant differences in PON1 activities were found between S and PA subjects at baseline. Nearly all biochemicals increased at ME in both groups. Both PON and ARE activity increased at the bout of ME in PA subjects and only ARE activity in S subjects. ARE/HDL-C ratio increased at the bout of ME in PA and S subjects. The difference in PON1 activity response to ME between study groups may be a result of adaptation of PA subjects to regular physical activity. We suggest that PON1 activity may be a marker of antioxidant protection at ME and an indicator of adaptation to exercise.


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