17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Examining the day-to-day bidirectional associations between physical activity, sedentary behavior, screen time, and sleep health during school days in adolescents

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Adolescence is a vulnerable period for experiencing poor sleep health. Growing studies have demonstrated lifestyle behaviors including physical activity (PA), screen time (SCT), and sedentary behaviors (SED) as the potential factors associated with sleep health in adolescents; yet, the evidence is inconclusive and the directionality of temporal associations across school days are not well understood. This study examined the day-to-day bidirectional associations of lifestyle behaviors with sleep health parameters in adolescents.

          Methods

          A total of 263 adolescents (58% boys) in 6 th - 8 th grades wore an accelerometer for 24-hour across the three consecutive school days and completed recording SCT in time-diary and answering sleep quality (SQ) questions for each day. Sleep-wake patterns as well as time spent in moderate- and vigorous-intensity PA (MVPA) and SED were objectively quantified from the wrist-worn accelerometry data across the two segments of the day (during and after school hours). Mixed model analyses were conducted to test bidirectional associations between lifestyle factors and sleep health parameters in each temporal direction across the days. Additionally, indirect associations across the days were tested using an autoregressive cross-lagged model analysis in the framework of path analysis.

          Results

          MVPA minutes in a day did not predict sleep health parameters that night. The bidirectional associations were partially observed between SED and sleep health, but the significance and direction of the associations largely varied by the time segment of a day as well as types of sleep health parameters. Additionally, greater SCT during the day was associated with lower SQ that night (b = -0.010; P = .018), and greater SQ was associated with greater MVPA during school hours (b = 6.45; P = .028) and lower SED after school hours (b = -39.85; P = .029) the next day. Lastly, there were significant indirect associations of SCT with sleep health parameters across the days indicating multi-day lagged effects of SCT on sleep health the later nights.

          Conclusion

          This study highlights the importance of lowering SCT for better sleep health in adolescents during school days. Additionally, perceived SQ is shown to be a potential significant predictor promoting healthy behaviors the next day independent of sleep-wake patterns. Further studies are warranted to confirm the observed temporal associations between SCT, SQ, and behavioral outcomes in this vulnerable population.

          Related collections

          Most cited references53

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Youth Risk Behavior Surveillance — United States, 2017

          Problem Health-risk behaviors contribute to the leading causes of morbidity and mortality among youth and adults in the United States. In addition, significant health disparities exist among demographic subgroups of youth defined by sex, race/ethnicity, and grade in school and between sexual minority and nonsexual minority youth. Population-based data on the most important health-related behaviors at the national, state, and local levels can be used to help monitor the effectiveness of public health interventions designed to protect and promote the health of youth at the national, state, and local levels. Reporting Period Covered September 2016–December 2017. Description of the System The Youth Risk Behavior Surveillance System (YRBSS) monitors six categories of priority health-related behaviors among youth and young adults: 1) behaviors that contribute to unintentional injuries and violence; 2) tobacco use; 3) alcohol and other drug use; 4) sexual behaviors related to unintended pregnancy and sexually transmitted infections (STIs), including human immunodeficiency virus (HIV) infection; 5) unhealthy dietary behaviors; and 6) physical inactivity. In addition, YRBSS monitors the prevalence of other health-related behaviors, obesity, and asthma. YRBSS includes a national school-based Youth Risk Behavior Survey (YRBS) conducted by CDC and state and large urban school district school-based YRBSs conducted by state and local education and health agencies. Starting with the 2015 YRBSS cycle, a question to ascertain sexual identity and a question to ascertain sex of sexual contacts were added to the national YRBS questionnaire and to the standard YRBS questionnaire used by the states and large urban school districts as a starting point for their questionnaires. This report summarizes results from the 2017 national YRBS for 121 health-related behaviors and for obesity, overweight, and asthma by demographic subgroups defined by sex, race/ethnicity, and grade in school and by sexual minority status; updates the numbers of sexual minority students nationwide; and describes overall trends in health-related behaviors during 1991–2017. This reports also summarizes results from 39 state and 21 large urban school district surveys with weighted data for the 2017 YRBSS cycle by sex and sexual minority status (where available). Results Results from the 2017 national YRBS indicated that many high school students are engaged in health-risk behaviors associated with the leading causes of death among persons aged 10–24 years in the United States. During the 30 days before the survey, 39.2% of high school students nationwide (among the 62.8% who drove a car or other vehicle during the 30 days before the survey) had texted or e-mailed while driving, 29.8% reported current alcohol use, and 19.8% reported current marijuana use. In addition, 14.0% of students had taken prescription pain medicine without a doctor’s prescription or differently than how a doctor told them to use it one or more times during their life. During the 12 months before the survey, 19.0% had been bullied on school property and 7.4% had attempted suicide. Many high school students are engaged in sexual risk behaviors that relate to unintended pregnancies and STIs, including HIV infection. Nationwide, 39.5% of students had ever had sexual intercourse and 9.7% had had sexual intercourse with four or more persons during their life. Among currently sexually active students, 53.8% reported that either they or their partner had used a condom during their last sexual intercourse. Results from the 2017 national YRBS also indicated many high school students are engaged in behaviors associated with chronic diseases, such as cardiovascular disease, cancer, and diabetes. Nationwide, 8.8% of high school students had smoked cigarettes and 13.2% had used an electronic vapor product on at least 1 day during the 30 days before the survey. Forty-three percent played video or computer games or used a computer for 3 or more hours per day on an average school day for something that was not school work and 15.4% had not been physically active for a total of at least 60 minutes on at least 1 day during the 7 days before the survey. Further, 14.8% had obesity and 15.6% were overweight. The prevalence of most health-related behaviors varies by sex, race/ethnicity, and, particularly, sexual identity and sex of sexual contacts. Specifically, the prevalence of many health-risk behaviors is significantly higher among sexual minority students compared with nonsexual minority students. Nonetheless, analysis of long-term temporal trends indicates that the overall prevalence of most health-risk behaviors has moved in the desired direction. Interpretation Most high school students cope with the transition from childhood through adolescence to adulthood successfully and become healthy and productive adults. However, this report documents that some subgroups of students defined by sex, race/ethnicity, grade in school, and especially sexual minority status have a higher prevalence of many health-risk behaviors that might place them at risk for unnecessary or premature mortality, morbidity, and social problems (e.g., academic failure, poverty, and crime). Public Health Action YRBSS data are used widely to compare the prevalence of health-related behaviors among subpopulations of students; assess trends in health-related behaviors over time; monitor progress toward achieving 21 national health objectives; provide comparable state and large urban school district data; and take public health actions to decrease health-risk behaviors and improve health outcomes among youth. Using this and other reports based on scientifically sound data is important for raising awareness about the prevalence of health-related behaviors among students in grades 9–12, especially sexual minority students, among decision makers, the public, and a wide variety of agencies and organizations that work with youth. These agencies and organizations, including schools and youth-friendly health care providers, can help facilitate access to critically important education, health care, and high-impact, evidence-based interventions.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The influence of sleep quality, sleep duration and sleepiness on school performance in children and adolescents: A meta-analytic review.

            Insufficient sleep, poor sleep quality and sleepiness are common problems in children and adolescents being related to learning, memory and school performance. The associations between sleep quality (k=16 studies, N=13,631), sleep duration (k=17 studies, N=15,199), sleepiness (k=17, N=19,530) and school performance were examined in three separate meta-analyses including influential factors (e.g., gender, age, parameter assessment) as moderators. All three sleep variables were significantly but modestly related to school performance. Sleepiness showed the strongest relation to school performance (r=-0.133), followed by sleep quality (r=0.096) and sleep duration (r=0.069). Effect sizes were larger for studies including younger participants which can be explained by dramatic prefrontal cortex changes during (early) adolescence. Concerning the relationship between sleep duration and school performance age effects were even larger in studies that included more boys than in studies that included more girls, demonstrating the importance of differential pubertal development of boys and girls. Longitudinal and experimental studies are recommended in order to gain more insight into the different relationships and to develop programs that can improve school performance by changing individuals' sleep patterns. Copyright 2009 Elsevier Ltd. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Electronic media use and sleep in school-aged children and adolescents: A review.

              Electronic media have often been considered to have a negative impact on the sleep of children and adolescents, but there are no comprehensive reviews of research in this area. The present study identified 36 papers that have investigated the relationship between sleep and electronic media in school-aged children and adolescents, including television viewing, use of computers, electronic gaming, and/or the internet, mobile telephones, and music. Many variables have been investigated across these studies, although delayed bedtime and shorter total sleep time have been found to be most consistently related to media use. A model of the mechanisms by which media use may affect sleep is presented and discussed as a vehicle for future research. Copyright 2010 Elsevier B.V. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                3 September 2020
                2020
                : 15
                : 9
                : e0238721
                Affiliations
                [1 ] Department of Kinesiology and Health Sciences, Virginia Commonwealth University, Richmond, Virginia, United States of America
                [2 ] Department of Kinesiology, University of Texas at San Antonio, San Antonio, Texas, United States of America
                [3 ] Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, Texas United States of America
                [4 ] Education Academy, Vytautas Magnus University, Kaunas, Lithuania
                [5 ] Department of Social and Behavioral Medicine, Kagoshima University Graduate Medical School, Kagoshima, Japan
                University of Kentucky, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6134-0100
                Article
                PONE-D-20-18361
                10.1371/journal.pone.0238721
                7470331
                32881930
                0c56c5e4-6996-4e14-a8ef-c5093771072c
                © 2020 Kim et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 June 2020
                : 21 August 2020
                Page count
                Figures: 1, Tables: 5, Pages: 18
                Funding
                This study was supported by the Paffenbarger-Blair Fund for Epidemiological Research on Physical Activity awarded to YK from the American College of Sports Medicine ( https://www.acsm.org/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Sleep
                Social Sciences
                Sociology
                Education
                Schools
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                People and Places
                Population Groupings
                Age Groups
                Children
                Adolescents
                People and Places
                Population Groupings
                Families
                Children
                Adolescents
                Medicine and Health Sciences
                Public and Occupational Health
                Behavioral and Social Aspects of Health
                Engineering and Technology
                Electronics Engineering
                Electronics
                Accelerometers
                Biology and Life Sciences
                Psychology
                Behavior
                Sedentary Behavior
                Social Sciences
                Psychology
                Behavior
                Sedentary Behavior
                Medicine and Health Sciences
                Public and Occupational Health
                Health Screening
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content132

                Cited by15

                Most referenced authors733