scholarly journals Behavioral Measures in Myopic and Non-myopic High Schoolers During the COVID Pandemic

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Divya Shukla ◽  
Lisa Ostrin
Keyword(s):  
Physical Activity ◽  
Sleep Duration ◽  
Refractive Error ◽  
Light Exposure ◽  
Electronic Devices ◽  
Behavioral Measures ◽  
Visual Behaviors ◽  
Working Distance ◽  
Near Work ◽  
High Schoolers

Purpose: The purpose of this study is to understand how the visual activity of highschool students in Houston changed due to quarantine and online learning during the COVID-19 pandemic, and whether these behaviors were different between myopes and non-myopes. Methods: Thirty-one participants (16.3±0.8 years, 8 females), including 12 myopes and 8 non-myopes, wore a Clouclip and Actiwatch for a week. The Clouclip records working distance and the Actiwatch measures light exposure, physical activity, and sleep duration. A questionnaire was also completed regarding demographics, ocular history, and visual behaviors. Results: Data showed that myopic participants engaged in near work (working distances of 10 to <60 cm) for 8.4±2.6 hours on a week day and 6.5±2.1 hours on a weekend day. Non-myopic participants engaged in near work for 6.1±2.7 hours on a week day and 4.5±1.9 hours on a weekend day. While weekend near work was significantly different between refractive error groups (P<.05), weekday near work (P=.08) was not. There were no differences between refractive error groups for daily light exposure (P = .89), time outdoors (P = .44), or sleep duration (P = .80). Conclusions: There was no significant change in sleep duration and physical activity regardless of refractive error over the pandemic, while results revealed a significant decrease in outdoor light exposure and the increase in near and intermediate work, especially with electronic devices such as the computer.

scholarly journals Later sleep timing predicts accelerated summer weight gain among elementary school children: a prospective observational study

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jennette P. Moreno ◽  
Javad Razjouyan ◽  
Houston Lester ◽  
Hafza Dadabhoy ◽  
Mona Amirmazaheri ◽  
...  
Keyword(s):  
Physical Activity ◽  
Observational Study ◽  
Sleep Duration ◽  
Obesity Prevention ◽  
Prospective Observational Study ◽  
Light Exposure ◽  
Activity Level ◽  
Activity Levels ◽  
School Year ◽  
Children’S Sleep

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.

scholarly journals Electronic Devices and Applications to Track Physical Activity

JAMA ◽  
2015 ◽  
Vol 313 (20) ◽  
pp. 2079 ◽  
Author(s):  
Jennifer Schrack ◽  
Vadim Zipunnikov ◽  
Ciprian Crainiceanu
Keyword(s):  
Physical Activity ◽  
Electronic Devices

scholarly journals Socioeconomic Inequities in Youth Participation in Physical Activity and Sports

2021 ◽  
Vol 18 (13) ◽  
pp. 6946
Author(s):  
Pooja S. Tandon ◽  
Emily Kroshus ◽  
Katharine Olsen ◽  
Kimberly Garrett ◽  
Pingping Qu ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sports Participation ◽  
Youth Participation ◽  
Cross Sectional Survey ◽  
Middle School Children ◽  
Cross Sectional ◽  
Potential Benefits ◽  
Physical Activity Recommendations ◽  
High Schoolers ◽  
Activity Recommendations

Access to opportunities for physical activity and sports, and therefore potential benefits of participation, are distributed inequitably. The aims of this study were to describe and compare youth experiences related to sport and physical activity by socioeconomic factors. A cross-sectional survey was conducted of students in 5–12th grades in King County, Washington, USA. Students were asked about physical activity and sports experiences and about demographic factors including family affluence, which was categorized as low, medium, and high. Participants were 1038 youth (50% girls, 58% non-White, and 32% from homes where languages other than English are spoken). Children from low-affluence families reported fewer days/week of physical activity, fewer sports sampled, and lower rates of ever playing sports. Greater proportions of children from low-affluence families reported these barriers to sports: (1) don’t want to get hurt, (2) don’t feel welcome on teams, (3) too expensive, and (4) transportation. Middle school children from high-affluence families had three times higher odds of meeting physical activity recommendations, and high-affluence high schoolers had three times higher odds of ever participating in sports compared to peers from low-affluence families. Socioeconomic status was inversely associated with outcomes related to youth physical activity and sports participation. The disproportionately reported barriers to sports participation are modifiable, and cross-sector solutions can help promote play equity.

scholarly journals Associations between objectively measured physical activity, sedentary behaviour and time in bed among 75+ community-dwelling Danish older adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Behaviour ◽  
Sleep Duration ◽  
Activity Level ◽  
Time In Bed ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity ◽  
Vector Magnitude

Abstract Background Older adults are recommended to sleep 7–8 h/day. Time in bed (TIB) differs from sleep duration and includes also the time of lying in bed without sleeping. Long TIB (≥9 h) are associated with self-reported sedentary behavior, but the association between objectively measured physical activity, sedentary behavior and TIB is unknown. Methods This study was based on cross-sectional analysis of the Healthy Ageing Network of Competence (HANC Study). Physical activity and sedentary behaviour were measured by a tri-axial accelerometer (ActiGraph) placed on the dominant wrist for 7 days. Sedentary behavior was classified as < 2303 counts per minute (cpm) in vector magnitude and physical activity intensities were categorized, as 2303–4999 and ≥ 5000 cpm in vector magnitude. TIB was recorded in self-reported diaries. Participants were categorized as UTIB (usually having TIB 7–9 h/night: ≥80% of measurement days), STIB (sometimes having TIB 7–9 h/night: 20–79% of measurement days), and RTIB (rarely having TIB 7–9 h/night: < 20% of measurement days). Multinominal regression models were used to calculate the relative risk ratios (RRR) of being RTIB and STIB by daily levels of physical activity and SB, with UTIB as the reference group. The models were adjusted for age, sex, average daily nap length and physical function. Results Three hundred and fourty-one older adults (median age 81 (IQR 5), 62% women) were included with median TIB of 8 h 21 min (1 h 10 min)/day, physical activity level of 2054 (864) CPM with 64 (15) % of waking hours in sedentary behavior. Those with average CPM within the highest tertile had a lower RRR (0.33 (0.15–0.71), p = 0.005) for being RTIB compared to those within the lowest tertile of average CPM. Accumulating physical activity in intensities 2303–4999 and ≥ 5000 cpm/day did not affect the RRR of being RTIB. RRR of being RTIB among highly sedentary participants (≥10 h/day of sedentary behavior) more than tripled compared to those who were less sedentary (3.21 (1.50–6.88), p = 0.003). Conclusions For older adults, being physically active and less sedentary was associated with being in bed for 7–9 h/night for most nights (≥80%). Future longitudinal studies are warranted to explore the causal relationship sbetween physical activity and sleep duration.

667 Effects of Sleep-Extend on glucose metabolism in women with a history of gestational diabetes: A pilot study

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A261-A261
Author(s):  
Sirimon Reutrakul ◽  
Pamela Martyn-Nemeth ◽  
Laurie Quinn ◽  
Kirstie Danielson ◽  
Brett Rydzon ◽  
...  
Keyword(s):  
Physical Activity ◽  
Pilot Study ◽  
Glucose Metabolism ◽  
Gestational Diabetes ◽  
Sleep Duration ◽  
Control Group ◽  
Healthy Living ◽  
Short Sleep ◽  
History Of ◽  
Sleep Extension

Abstract Introduction Experimental and epidemiological data have linked insufficient sleep to increased diabetes risk. Women with a history of gestational diabetes (GDM) have a 7-fold greater risk of developing type 2 diabetes. This pilot study explored the feasibility of a sleep extension intervention in women with a history of GDM and short sleep, and the effects on glucose metabolism. Methods Women age 18–45 years with a history of GDM (at least 1 year postpartum) and actigraphy confirmed short sleep duration (&lt;7h/night) on weekdays were randomized at a ratio of 1 control (healthy living information) to 2 cases (6 weeks of “Sleep Extend” intervention: use of a Fitbit, weekly digital content, interactive tools, and coach delivered feedback in order to increase sleep duration). An oral glucose tolerance test (OGTT), 7-day actigraphy recording and questionnaires were obtained at baseline and 6 weeks (at the end of the intervention). Results Twelve women (mean (SD) age 40.3 (4.5) years) participated (n=8 Sleep Extend, n=4 control). Compared to baseline, nightly sleep duration increased in Sleep Extend group (+30.6 (48.8) minutes) but decreased in the control group (-6.8 (22.9) minutes). Both fasting and 2-h glucose levels from OGTT increased in both groups but were greater in the control group (Sleep extend vs. healthy living: fasting glucose +2.1 (9.8) vs. +12.8 (7.3) mg/dL; 2-h glucose +8.2 (21.9) vs. +20.0 (19.4) mg/dL). Self-reported sleep quality improved in both groups. When compared controls, Sleep Extend participants reported improved fatigue symptoms (Promis fatigue score change -5.1 (9.3) vs. 7.0 (1.0), p=0.008), and self-reported physical activity tended to increase (+1614 (3659) vs. -2900 (3922) MET-minutes/week). Combining all participants, an increase in sleep duration correlated with a decrease in fatigue (r= -.62, p=0.04) and anxiety symptoms (r= -.69, p=0.02). Conclusion Sleep extension through coaching and use of remote monitoring is feasible in women with a history of GDM. It appears to decrease fatigue and may improve glucose metabolism and physical activity. Support (if any) NIDDK P30 DK092949

Association of Behavioral Phenotypes With Changes in Sleep During a Workplace Wellness Program

2021 ◽  
pp. 089011712110150
Author(s):  
Kimberly J. Waddell ◽  
Sujatha Changolkar ◽  
Gregory Szwartz ◽  
Sarah Godby ◽  
Mitesh S. Patel
Keyword(s):  
Physical Activity ◽  
Sleep Duration ◽  
Physical Activity Intervention ◽  
Secondary Analysis ◽  
The United States ◽  
Behavioral Phenotype ◽  
Workplace Wellness ◽  
Wellness Program ◽  
Behavioral Phenotypes ◽  
Physically Active

Purpose: Examine changes in sleep duration by 3 behavioral phenotypes during a workplace wellness program with overweight and obese adults. Design: Secondary analysis of a randomized clinical trial Setting: Remotely monitored intervention conducted across the United States Subjects: 553 participants with a body mass index ≥25 Intervention: Participants were randomized to 1 of 4 study arms: control, gamification with support, gamification with collaboration, and gamification with competition to increase their physical activity. All participants were issued a wrist-worn wearable device to record their daily physical activity and sleep duration. Measures: The primary outcome was change in daily sleep duration from baseline during the 24 week intervention and follow-up period by study arm within behavioral phenotype class. Analysis: Linear mixed effects regression. Results: Participants who had a phenotype of less physically active and less social at baseline, in the gamification with collaboration arm, significantly increased their sleep duration during the intervention period (30.2 minutes [95% CI 6.9, 53.5], P = 0.01), compared to the control arm. There were no changes in sleep duration among participants who were more extroverted and motivated or participants who were less motivated and at-risk. Conclusions: Changes in sleep during a physical activity intervention varied by behavioral phenotype. Behavioral phenotypes may help to precisely identify who is likely to improve sleep duration during a physical activity intervention.

scholarly journals Physical Activity, Screen Time, and Sleep Duration of Children Aged 6–9 Years in 25 Countries: An Analysis within the WHO European Childhood Obesity Surveillance Initiative (COSI) 2015–2017

Obesity Facts ◽  
2020 ◽  
pp. 1-13
Author(s):  
Stephen Whiting ◽  
Marta Buoncristiano ◽  
Peter Gelius ◽  
Karim Abu-Omar ◽  
Mary Pattison ◽  
...  
Keyword(s):  
Physical Activity ◽  
Childhood Obesity ◽  
Sleep Duration ◽  
Screen Time ◽  
School Administrators ◽  
Well Being ◽  
Pooled Analysis ◽  
Physical And Mental Health ◽  
Short Sleep Duration ◽  
Nationally Representative

<b><i>Background:</i></b> Children are becoming less physically active as opportunities for safe active play, recreational activities, and active transport decrease. At the same time, sedentary screen-based activities both during school and leisure time are increasing. <b><i>Objectives:</i></b> This study aimed to evaluate physical activity (PA), screen time, and sleep duration of girls and boys aged 6–9 years in Europe using data from the WHO European Childhood Obesity Surveillance Initiative (COSI). <b><i>Method:</i></b> The fourth COSI data collection round was conducted in 2015–2017, using a standardized protocol that included a family form completed by parents with specific questions about their children’s PA, screen time, and sleep duration. <b><i>Results:</i></b> Nationally representative data from 25 countries was included and information on the PA behaviour, screen time, and sleep duration of 150,651 children was analysed. Pooled analysis showed that: 79.4% were actively playing for &#x3e;1 h each day, 53.9% were not members of a sport or dancing club, 50.0% walked or cycled to school each day, 60.2% engaged in screen time for &#x3c;2 h/day, and 84.9% slept for 9–11 h/night. Country-specific analyses of these behaviours showed pronounced differences, with national prevalences in the range of 61.7–98.3% actively playing for &#x3e;1 h/day, 8.2–85.6% were not members of a sport or dancing club, 17.7–94.0% walked or cycled to school each day, 32.3–80.0% engaged in screen time for &#x3c;2 h/day, and 50.0–95.8% slept for 9–11 h/night. <b><i>Conclusions:</i></b> The prevalence of engagement in PA and the achievement of healthy screen time and sleep duration are heterogenous across the region. Policymakers and other stakeholders, including school administrators and parents, should increase opportunities for young people to participate in daily PA as well as explore solutions to address excessive screen time and short sleep duration to improve the overall physical and mental health and well-being of children.

scholarly journals Prevalence and correlates of adherence to movement guidelines among urban and rural children in Mozambique: a cross-sectional study

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Taru Manyanga ◽  
Joel D. Barnes ◽  
Jean-Philippe Chaput ◽  
Peter T. Katzmarzyk ◽  
Antonio Prista ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sleep Duration ◽  
Screen Time ◽  
Cross Sectional Study ◽  
Rural Children ◽  
Sectional Study ◽  
Cross Sectional ◽  
Middle Income ◽  
Middle Income Countries ◽  
Low Middle Income Countries

Abstract Background Insufficient physical activity, short sleep duration, and excessive recreational screen time are increasing globally. Currently, there are little to no data describing prevalences and correlates of movement behaviours among children in low-middle-income countries. The few available reports do not include both urban and rural respondents, despite the large proportion of rural populations in low-middle-income countries. We compared the prevalence of meeting 24-h movement guidelines and examined correlates of meeting the guidelines in a sample of urban and rural Mozambican schoolchildren. Methods This is cross-sectional study of 9–11 year-old children (n = 683) recruited from 10 urban and 7 rural schools in Mozambique. Moderate- to vigorous-intensity physical activity (MVPA) and sleep duration were measured by waist-worn Actigraph GT3X+ accelerometers. Accelerometers were worn 24 h/day for up to 8 days. Recreational screen time was self-reported. Potential correlates of meeting 24-h movement guidelines were directly measured or obtained from validated items of context-adapted questionnaires. Multilevel multivariable logit models were used to determine the correlates of movement behaviours. Meeting 24-h movement guidelines was defined as ≥60 min/day of MVPA, ≤2 h/day of recreational screen time, and between 9 and 11 h/night of sleep. Results More rural (17.7%) than urban (3.6%) children met all three 24-h movement guidelines. Mean MVPA was lower (82.9 ± 29.5 min/day) among urban than rural children (96.7 ± 31.8 min/day). Rural children had longer sleep duration (8.9 ± 0.7 h/night) and shorter recreational screen time (2.7 ± 1.9 h/day) than their urban counterparts (8.7 ± 0.9 h/night and 5.0 ± 2.3 h/day respectively). Parental education (OR: 0.37; CI: 0.16–0.87), school location (OR: 0.21; CI: 0.09–0.52), and outdoor time (OR: 0.67; CI: 0.53–0.85) were significant correlates of meeting all three 24-h movement guidelines. Conclusions Prevalence and correlates of meeting movement guidelines differed between urban and rural schoolchildren in Mozambique. On average, both groups had higher daily MVPA minutes, shorter sleep duration, and higher recreational screen time than the 24-h movement guidelines recommend. These findings (e.g., higher than recommended mean daily MVPA minutes) differ from those from high-income countries and highlight the need to sample from both urban and rural areas.

scholarly journals 660 Chronotype Associations with Insomnia, Depressive Symptoms, and Changes in Sleep and Health Behaviors during the COVID-19 Pandemic

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A258-A258
Author(s):  
Megan Petrov ◽  
Matthew Buman ◽  
Dana Epstein ◽  
Shawn Youngstedt ◽  
Nicole Hoffmann ◽  
...  
Keyword(s):  
Physical Activity ◽  
Depressive Symptoms ◽  
Health Behaviors ◽  
Screen Time ◽  
Online Survey ◽  
Light Exposure ◽  
Multinomial Logistic Regression ◽  
Depression Scale ◽  
Time In Bed ◽  
Significant Difference

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&lt;0.001), reported greater ISI (F[3,503]=5.3, p=.001) and CES-D-10 scores (F[3,492]=7.9, p&lt;.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):

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