Late-night screen time and screen time addiction as shared determinants of poor sleep and obesity in adolescents aged 11-14 years in Scotland

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The aim of this research was to explore which components of screen time usage are shared determinants of poor sleep and higher adiposity in adolescents, using data from the Teen Sleep Well Study (TSWS). Methods A cross-sectional study of adolescents aged 11-14-years in Fife, Scotland. Sleep was measured objectively using the Actigraph GT3X-BT and subjectively using validated questionnaires. Adiposity was assessed using body fat percentage and obesity was measured using body mass index percentile (BMIp). Four components of screen time were addressed using questionnaires: the timing of screen time (first and last 30 minutes of the day), quantity of screen time (weekday and weekend, via SCREENS-Q), location of screen time (use of a phone in bed, in the bedroom overnight, as an alarm), and screen time addiction (Videogaming Addiction Questionnaire (VGA-Q), Social Media Addiction Questionnaire (SMA-Q) and Mobile Phone Addiction Questionnaire (MPA-Q)). Descriptive statistics and statistical tests such as Pearson correlation tables, regression analyses and mediation analyses were used. Analyses were adjusted for the demographics of the child participant and caregiver and the wellbeing of the adolescent. Results 62 participants (33F/29M, mean age 12.2 ± 1.1 years, mean BMI percentile 60.3 ± 32.1) completed the study and were part of the analysis. Excessive late-night and early-morning screen time usage, excessive screen time on a weekend, screen time addiction and using screens in the 30-minutes prior to sleep onset were shared determinants of higher adiposity, a later chronotype and poor sleep regulation outcomes: poor sleep habits, increased insomnia symptoms and increased sleep onset variability. Mediation analyses confirmed that wellbeing of the adolescent was a mediator of the relationship between screen time outcomes and insomnia symptoms and body fat percentage. Conclusions These screen time behaviours could be targeted in health-promoting interventions. Further research should assess longitudinal relationships between different components of screen time, sleep and adiposity, when adjusted for wellbeing in adolescents. teenagers insomnia sleep disturbance screens mobile phones overweight adiposity Figures Figure 1 1. Introduction The pervasive use of digital screens, addictive social media, apps and new digital technology has become an integral part of modern adolescence, significantly influencing health outcomes [ 1 ]. During COVID-19, there was a shift to online and remote school-working and socialisation causing a shift to adolescents increasingly using screens for everyday activities and becoming more dependent on digital devices [ 2 – 5 ]. Previous research has reported that excessive screen time among adolescents has a detrimental impact on both sleep and obesity [ 1 , 6 – 9 ]. The rapid proliferation of smartphones, tablets, and computers has led to significant changes in sleep patterns, disrupting circadian rhythms and altering chronotypes [ 10 , 11 ]. Prolonged screen exposure, particularly before bedtime, is associated with delayed sleep onset [ 12 ], insomnia symptoms [ 13 ], short sleep duration [ 14 ] and increased social jetlag [ 15 ]. These disruptions in sleep habits contribute to reduced physical activity and increased sedentary behaviour [ 16 – 18 ], behaviours identified as critical factors in the rising prevalence of obesity among youth [ 19 – 21 ]. A research gap identified by systematic review was to investigate whether different components of screen time, not just overall quantity of screen time, are shared determinants of sleep and obesity in adolescents [ 6 ]. Identifying the specific components of habitual screen time that are most detrimental to health is crucial for designing effective health-promoting interventions [ 6 ]. Different aspects of screen use, such as the type of content consumed [ 22 – 24 ], the timing of usage [ 12 , 25 , 26 ], and screentime addiction [ 5 , 27 – 30 ], could each have distinct impacts on adolescent health and the developing brain. For example, engaging in stimulating activities like gaming or social media use before bedtime can exacerbate insomnia symptoms [ 14 , 31 ], whereas passive screen time, such as watching TV, has been shown to contribute more significantly to sedentary behaviour and obesity [ 32 , 33 ]. Additionally, excessive late-night screen time can interfere with critical periods of brain development, affecting cognitive functions, emotional regulation, and mental health [ 9 , 34 ]. By pinpointing these components, interventions can be tailored to address the most harmful habits. Consequently, the research question addressed by this study was: are different components of problematic screentime usage shared determinants of poor sleep and higher adiposity in adolescents? The different components of screen time examined in this study included late-night and early morning usage, quantity of screen time, location of screen time, and screen time addiction. 2. Methodology 2.1. Study design, recruitment, and procedure A cross-sectional quantitative study was conducted, including a caregiver-assessed questionnaire, adolescent-assessed questionnaire, researcher-assessed objective anthropometry, and 7–10 days of actigraphy in 11–14 year-olds (Fig. 1 ). Ethical approval from the University of St Andrews School of Medicine ethics committee was gained in January 2023 (approval code: MD16703). Adolescent participants (aged between 11–14 years) and their caregivers were recruited via flyers at leisure centres, cafes, youth centres, transport centres, University memo adverts, and online Facebook community groups. Inclusion criteria for the study included (i) being 11–14 years at recruitment, (ii) enrolled at a school in Fife, (iii) informed consent obtained from the caregiver and (iv) free of underlying health conditions and medication use. Exclusion criteria included (i) 14 years (ii) < 3 weekdays and < 1 weekend days of actigraphy data available for the adolescent participant, (iii) caregiver questionnaire, including consent, is absent, (iv) medication use and (v) already having a sibling from the same household take part in the study. A G*Power calculation was completed to determine the desired study sample size. The recommended effect, power and error sizes were used [ 36 ]. An f-test linear regression test was conducted (effect size F²= 0.30, α = 0.05, power = 0.8), which suggested a sample of 59 would be sufficient for an actual power of 0.807. 2.2. Research variables 2.2.1. Caregiver demographics Caregivers were asked to describe their relationship to the adolescent, date of birth, gender, ethnicity, marital status, and postcode. If a second adult lived in the home, for example a spouse, partner, another guardian or grandparent, their date of birth, gender and ethnicity was also recorded. Caregivers were asked “what is your highest level of education” with answers and scores of “none or few school qualifications” (0), “secondary school leaver” (1), “sixth form/college or apprenticeship” (2), “university degree” (3) or “masters or postgraduate degree” (4). Caregivers were asked to report their current employment status and shift patterns. For example, “as part of your work, do you work night shifts?” and “as part of your work do you work shifts that finish late in the evening (after 11pm)?” with answers of “never” (0) “rarely” (1), “sometimes” (2), “often” (3), “all the time” (4) and “not applicable” (0). A higher score indicating more frequent late or night shifts. If another adult lived in the household, the same questions were asked of the second household member. Caregivers were asked for their height (cm or in feet and inches) and weight (kg or stones and pounds), and BMI (kg/m 2 ) was then calculated. 2.2.2. Adolescent demographics The adolescent’s date of birth, gender, ethnicity, and pubertal status were self-reported. Pubertal status was assessed using six questions from the Health Behaviour in School-aged Children (HBSC) study [ 37 ]. Adolescent participants answered either male- or female-specific questions regarding any pubertal developments or could opt not to answer either and move on to the next section of the questionnaire. Socioenvironmental status was derived using SIMD [ 38 ] quintile data from the participant’s home postcode reported by the caregiver. 2.2.3. Anthropometry The adolescent participant’s height (m) and weight (kg) were measured three times by a trained researcher (EG), and a mean was calculated. Height was measured using a portable stadiometer (The Leicester Height Measure, Seca Ltd.) (0.1cm precision) [ 39 ], with no shoes, and standing straight with the adolescent participant’s head facing forward [ 39 ], and a mean was then calculated. Adolescent weight (kg) was assessed using Tanita body composition scales, (TBF-300M) (0.1kg precision) [ 40 ]. Derived variables included BMI ((kg/m 2 ). Body mass index percentile was derived using WHO guideline cut-offs: <5th percentile indicated underweight, ≥5th to < 85th percentile indicated healthy weight, ≥ 85th to < 95th percentile indicated overweight, and ≥ 95th percentile indicated obesity [ 41 ]. Adolescent adiposity (body fat percentage) was measured using bioelectrical impedance (Tanita body composition scales, TBF-300M) (0.1kg precision) [ 40 ], via bioelectrical impedance [ 42 ] and a mean of the three readings was then calculated [ 40 ]. This method provides reliable estimates of body composition in a quick, low cost, non-invasive manner that increases compliance [ 43 ]. Adolescent participants were asked to remove shoes and socks, wear light clothing and empty their pockets [ 40 ]. Adiposity status groups (under-fat, healthy-fat, over-fat and obese) were determined by UK age- and gender-specific validated standard cut-offs [ 44 ]. 2.2.4. Chronotype and sleep Chronotype was assessed using the 19-item Morningness Eveningness Questionnaire (MEQ) [ 45 ]. All 19-items were multiple choice, with scores being allocated to each answer and combined for a final score. A final score of ≤ 41 indicated an “evening type”, 42–58 indicated an “intermediate type” and ≥ 59 indicated a “morning type”. The MEQ has been validated in adolescents [ 46 ] and has been used in multiple sleep studies with adolescents [ 47 , 48 ]. Cronbach's α coefficients have varied across validity studies (α > 0.80) in different countries, for example New Zealand recorded reliability of α = 0.83 [ 49 ] and Slovenia recorded a reliability of α = 0.86 [ 50 ] in a normative adult sample. Sleep habits were assessed using an adapted eight-domain and 33-item children’s sleep habit questionnaire (CSHQ) [ 51 ]. The original questionnaire has been validated and used in children and adolescents [ 51 , 52 ] with the Cronbach’s α reliability coefficient ranging from 0.68 in the community and 0.78 in clinical paediatric populations [ 51 ]. The questionnaire was adapted to allow adolescent participants to self-report rather than caregiver-report. The questionnaire assesses bedtime resistance, sleep onset latency, sleep duration, sleep anxiety, night wakings, parasomnias, sleep-disordered breathing, and daytime sleepiness. Questions were asked on a Likert scale, for example “Adolescent goes to bed at the same time at night”. Answers and scores were “always (7 days)” (4), “usually (5–6 days a week)” (3), “sometimes (2–4 days a week)” (2), “rarely (one day a week)” (1) and “never” (0). A higher score indicated better and more regular sleep habits. Insomnia symptoms were assessed using the seven-item insomnia severity index (ISI) [ 53 ]. The seven questions were scored on a Likert scale 0–4. For example, “How satisfied/dissatisfied are you with your current sleep pattern?” “very satisfied” (0), “satisfied” (1), “moderately satisfied” (2), “dissatisfied” (3) and “very dissatisfied” (4). The scores of the seven items are combined, and a total score of 0–7 indicated no clinically significant insomnia, 8–14 is subthreshold insomnia, 15–21 indicated moderate clinical insomnia, and 22–28 indicated severe clinical insomnia [ 53 ]. The ISI was initially validated in 17-82-years [ 53 ] but has since been validated in the adolescent population with a Cronbach's α reliability coefficient of 0.83 [ 54 ]. Sleep onset variability was assessed by actigraphy [ 55 ], with the adolescent wearing an Actigraph GT3X-BT [ 56 ] for 7–10 days. The Actigraph GT3X-BT has been validated for capturing sleep variables (including sleep timing, efficiency and awakenings) in children and adolescents (including those with obesity) [ 55 ] against the gold standard, polysomnography (90.2% accuracy, 95.7% sensitivity and 62% specificity) [ 56 ]. In this study, for the data to be valid, ≥ 3 weekday nights and ≥ 1 weekend night was required. The sleep variables were detected and formulated using the Cole-Kripke algorithm [ 57 ], and a consensus sleep diary was used to corroborate sleep onset [ 58 ]. Sleep onset variability was defined as the standard deviation of an individual’s sleep onset. 2.2.5. Wellbeing (Quality of life) Quality of life (QoL) was self-assessed using KIDSCREEN-27 [ 59 ]. The KIDSCREEN-27 is a validated 27-item version of KIDSCREEN-52 and had a Cronbach’s alpha reliability coefficient of above 0.78 in all domains [ 60 ]. Participants answered questions on the five domains: physical wellbeing (5 items), psychological wellbeing (7 items), autonomy and caregiver relation (7 items), peers and social support (4 items) and school environment (4 items). Items were scored on a Likert scale 1–5, for example “Have your caregiver(s) treated you fairly?” was answered with “never” (5), “seldom” (4), “quite often” (3), “very often” (2) or “always” (1). A total for each domain and a total score for all 27-items is then calculated, a higher score indicated a poorer QoL. 2.2.6. Screen time Quantity of screen time : Self-assessed using two domains from the validated SCREENS questionnaire (SCREENS-Q): screen media environment and children’s screen use [ 61 ]. Participants were asked to report how many different types of electronic devices were in the household and how often the adolescent participant had access to them on a weekday and weekend. Adolescents were also asked about whether the caregiver set screen time guidelines, how often the adolescent participant used screen time guidelines and how long the adolescent participant used screen media on a weekday and weekend. Timing of screen time : Late-night and early-morning screen time was assessed by four questions: (1) “How may days do you use your phone on a weekday in the first 30 minutes after waking up?” and (2) “How may days do you use your phone on a weekday in the last 30 minutes before bed?”, and the answers were “none”, “1–2 days a week”, “3–4 days a week” or “5 days a week”. The same questions were asked for the weekend with answers of “none”, “one day at the weekend” or “both days at the weekend”. Location of screen time : Whether the adolescent used screen time in bed or in the bedroom was assessed using three questions reported by the adolescent: (1) Do you use screens whilst in bed? (2) Do you use screens in your bedroom? (3) Do you use your phone as an alarm? Screen time addiction : Social media addiction (SMA-Q), video gaming addiction (VGA-Q) and mobile phone addiction (MPA-Q), were self-assessed using three domains from the Adolescent Brain and Cognitive Development study questionnaire (ABCD): VGA-Q (six items), SMA-Q (six items) and MPA-Q (8 items) [ 62 ]. THE VGA-Q and SMA-Q, both consisted of a Likert scale with answers “Never” (0), “Very rarely” (1), “Rarely” (2), “Sometimes” (3), “Often” (4) and “Very often” (5) [ 62 ]. The MPA-Q also consisted of a Likert scale with answers “Strongly disagree” (1), “Disagree” (2), “Somewhat disagree” (3), “Neither disagree, nor agree” (4), “Somewhat agree” (5), “Agree” (6), “Strongly disagree” (7) [ 62 ]. A The MPA-Q was validated [ 63 ] and further used [ 64 ] in adolescents prior to the ABCD study use. The SMA-Q and VGA-Q were first used and validated by the ABCD study and were designed based off the validated Bergen Facebook Addiction Scale [ 65 ]. Higher scores for each individual questionnaire, SMA-Q, VGA-Q and MPA-Q indicated the individual was increasingly addicted to the social media, videogaming and mobile phone use, respectively. 2.3. Statistical analysis The data were extracted and analysed using SPSS 28 Statistics and R. Missing data were assessed using the Little’s Missing Completely At Random (MCAR) test [ 66 ]. Frequency diagrams and descriptive tables were used to demonstrate sample characteristics of the adolescent participants and caregivers. T-tests were used to assess the difference between adiposity status groups (under-fat and healthy-fat versus over-fat and obese). Pearson correlations and descriptive statistics were used to identify correlations between screen time and sleep, obesity, and adiposity in the adolescent participants. Block-wise regression analysis was used to examine which screen time variables were independently associated with the sleep and adiposity outcomes (Table 2 ). Adjusted variables were selected based on associations identified in unadjusted analyses or have been previously identified as shared determinants of poor sleep and obesity in adolescents [ 6 ]. Block 1 and 2 adjusted for demographics of the adolescents and caregivers, respectively, that were associated with poor sleep and obesity in the unadjusted analyses. Block 3 adjusted for wellbeing (QoL) as an indicator of wellbeing. Block 4 of the regression analysis included the screen time variable. Significant associations from the regression analyses were identified using a ± 10% difference (β ≤-0.1 or ≥ 0.1). Based on the regression analysis, the sleep and obesity variables with the strongest association with screen time were used to conduct mediation analyses using the laavan package on R [ 67 ]. The mediation analysis was conducted to examine whether wellbeing (QoL) mediated the relationship between screen time and sleep and adiposity. Table 1 , Adjusted variables in the blockwise regression analyses of screen time on adiposity and sleep outcomes in adolescent participants Block number Adjusted for 1 Gender Ethnicity 2 Maternal employment status Maternal night shifts Maternal late shifts Maternal BMI 3 Quality of life 4 One screen time habit (i) Timing of screen time (last 30min and first 30min of the day) (ii) Quantity of screen time (on a weekday and weekend) (iii) Location of screen time (use phone in bed, in the bedroom and as an alarm) (iv) Addictive tendencies of screen time (social media, videogaming and mobile phone addiction) Key: BMI – body mass index; min – minutes 3. Results 3.1. Sample description Sixty-six participants were initially recruited to the study, 62 completed the study and were included in the study analysis. The adolescent participants included in the analysis were from North-East Fife, Scotland, including 29 males and 33 females, with a mean age of 12.2 ± 1.1 years (Table 2 ). Mean body fat percentage was 22.3 ± 11.5% and mean BMIp 60.3 ± 32.1. There were significant differences between adiposity groups (under-fat/healthy-fat: UF/HF (n = 40) and over-fat/obese: OF/OB (n = 22)) across all sleep outcomes, (Table 3 ) and screen time dimensions (Table 4 ). Sleep characteristics reported in adolescents in the over-fat and obese adiposity status include later chronotype, poorer sleep habits, more severe insomnia symptoms, later sleep onset and longer sleep onset latency compared with those in the under-fat/ healthy-fat group (Table 3 ). Significant differences between body fat status groups were reported in the timing of screen time (screen time use in the first 30 minutes of the day and the last 30 minutes of the day), quantity of screen time (hours of screen time on a weekday and weekend), location of screen time (phone use in bed, having phone in the bedroom overnight and using phone as an alarm) and screen time addiction (videogaming, social media and mobile phone) (Table 4 ). 3.2. Unadjusted associations 3.2.1. Screen time and adiposity Higher adiposity (higher body fat percentage, larger waist circumference, larger hip circumference, larger waist-to-hip ratio, larger waist-to-height ratio) and a higher BMIp were meaningfully associated with early morning and late-night screen time (weekday and weekend), a higher screen time quantity (weekday and weekend), screen time addiction (videogaming, social media and mobile phone) and use of phone in bed, in the bedroom overnight and as an alarm. 3.2.2. Screen time and sleep Poorer sleep outcomes (a later chronotype, poorer sleep habits, more severe insomnia symptoms, later sleep onset on a weekday and weekend, a higher sleep onset variability and longer sleep onset latency on a weekday and weekend) were meaningfully associated with early morning and late-night screen time (weekday and weekend), a higher screen time quantity weekday and weekend), screen time addiction (videogaming, social media and mobile phone) and use of phone in bed, in the bedroom overnight and as an alarm. Table 2 , Participant characteristics: adolescent and caregiver demographics Demographic variables Total N % Mean SD Adolescent gender Male 29 46.8 Female 33 53.2 Adolescent age (year) 62 12.2 1.1 Adolescent ethnic minority White British 50 80.6 Other 12 19.4 Adolescent body development Male 29 7.9 3.3 Female 33 10.6 3.6 Adolescent body fat percentage (%) Male 29 18.9 12.6 Female 33 25.2 9.6 Adolescent body mass index percentile Male 29 62.3 32.4 Female 33 58.3 32.3 Adolescent and caregiver SES (SIMD) SIMD rank 62 5209.5 1259.2 Quintile 1 0 0.0 Quintile 2 0 0.0 Quintile 3 10 16.1 4.3 0.8 Quintile 4 35 56.5 Quintile 5 17 27.4 Highest level of maternal education ≤ 16 years 4 6.5 16–18 years 13 21.0 Undergraduate 18 29.0 Postgraduate 27 43.5 Maternal employment status Full-time 34 54.9 Part-time 21 33.9 Student 2 3.2 Retired/ homemaker 3 4.8 Other 2 3.2 Frequency of maternal night shifts Never/NA 54 87.1 Rarely 0 0 Sometimes 1 1.6 Often 7 11.3 Frequency of maternal late shifts Never/NA 47 75.8 Rarely 4 6.5 Sometimes 5 8.1 Often 6 9.7 Maternal age (years) 62 44.46 7.23 Maternal BMI (kg/m 2 ) 62 24.62 4.70 Number of caregiver household figures 62 1.76 0.43 Key: BMI – Body mass index; kg – kilograms; m – metres; NA – not applicable; SD – Standard deviation; SIMD – Scottish Index of Multiple Deprivation (2020) Table 3 , Participant characteristics: adolescent sleep by adiposity status Sleep outcome UF/HF (n = 40) OF/OB (n = 22) Total (n = 60) p-value Mean SD Mean SD Mean SD Morningness-eveningness questionnaire 51.15 9.37 30.91 10.51 43.97 13.77 < .001 Child sleep habits questionnaire 43.10 10.74 59.82 10.39 49.03 13.27 < .001 Insomnia severity index 6.13 5.77 23.09 4.68 12.15 9.79 < .001 Sleep onset (time) WD 22:38 00:55 00:29 00:45 23:17 01:14 < .001 WE 23:23 01:11 01:54 01:11 00:17 01:41 < .001 Sleep onset latency (mins) WD 27.52 21.38 51.05 14.27 35.87 22.16 < .001 WE 28.83 26.16 44.45 25.93 34.37 26.94 0.028 Key: HF – healthy-fat; OB – obese; OF – over-fat; mins – minutes; WD – weekday; WE - weekend Table 4 , Adolescent screentime by adiposity status Screen time variable UF/HF OF/OB Total p-value N % Mean SD N % Mean SD N Mean SD Timing of screen time First 30 minutes of the day (WD) None 19 30.6 1 1.6 20 < .001 1–2 days a week 12 19.4 1 1.6 13 < .001 3–4 days a week 6 9.7 2 3.2 8 < .001 5 days a week 3 4.8 18 29.0 21 < .001 Last 30 minutes of the day (WD) None 19 30.6 0 0.0 19 < .001 1–2 days a week 11 17.7 1 1.6 12 < .001 3–4 days a week 8 12.9 4 6.5 12 < .001 5 days a week 2 3.2 17 27.4 19 < .001 First 30 minutes of the day (WE) None 17 27.4 0 0.0 17 < .001 1 day 17 27.4 3 4.8 20 < .001 Both days 6 9.7 19 30.6 25 < .001 Last 30 minutes of the day (WD) None 17 27.4 0 0.0 17 < .001 1 day 21 33.9 5 8.1 26 < .001 Both days 2 3.2 17 27.4 19 < .001 Screen time addiction Videogaming 40 9.30 4.69 22 25.55 7.28 62 15.06 9.68 < .001 Social media 40 11.27 8.03 22 28.09 8.21 62 17.24 11.41 < .001 Mobile phone 40 23.63 11.31 22 46.45 8.66 62 31.73 15.13 < .001 Quantity of screen time Quantity of screen time WD 40 7.45 4.27 22 14.95 2.87 62 10.11 5.26 < .001 WE 40 9.17 4.70 22 17.27 2.71 62 12.05 5.65 < .001 Var 40 1.80 1.90 22 2.32 1.29 62 1.98 1.71 0.258 Location of screen time Use of phone in bed Yes 19 30.6 22 35.5 41 < .001 No 21 33.9 0 0.0 22 < .001 Phone in the bedroom overnight Yes 21 33.9 22 35.5 43 < .001 No 19 30.6 0 0.0 19 < .001 Phone as an alarm Yes 11 17.7 22 35.5 33 < .001 No 29 46.8 0 0.0 29 < .001 Key: HF – healthy-fat; N – number; OB – obese; OF – over-fat; mins – minutes; SD – standard deviation; WD – weekday; WE – weekend; var - variability 3.3. Adjusted associations Model summaries for blocks 1, 2, 3, and 4 (i-iv) have been reported in Table 5 . 3.3.1. Screen time and body fat percentage Frequent late-night screen time usage (β = 2.834, CI (95%) = 1.514, 4.154), frequent use of a phone in bed (β = 3.399, CI (95%) = 2.850, 13.413) and videogaming addiction (β = .312, CI (95%) = .061, .563) were significantly associated with higher body fat percentage in adolescents (A1). The independent coefficients of the quantity of screen time were not significantly associated with body fat percentage (A1). 3.3.2. Screen time and body mass index percentile Frequent late-night screen time usage (β = 6.970, CI (95%) = 1.207, 12.732) and videogaming addiction (β = 1.082, CI (95%) = .069, 2.095) were significantly associated with higher BMIp in adolescents (A1). The independent coefficients of the quantity and location of screen time were not significantly associated with BMIp (A1). 3.3.3. Screen time and chronotype Frequent early morning screen time (β= -1.772, CI (95%) = -3.503, − .041) and a higher quantity of screen time on a weekend (β= -1.098, CI (95%) = -2.117, − .077) were significantly associated with a later chronotype in adolescents (A1). The independent coefficients of the location of screen time and screen time addiction were not significantly associated with chronotype in adolescents (A1). 3.3.4. Screen time and sleep habits A higher quantity of screen time on a weekend (β = 1.404, CI (95%) = .018, 2.789) and keeping the phone in the bedroom overnight (compared with not) (β= -8.956, CI (95%) = -17.820, − .091) were significantly associated with poorer sleep habits in adolescents (A1). The independent coefficients of the timing of screen time and screen time addiction were not significantly associated with sleep habits in adolescents (A1). 3.3.5. Screen time and insomnia symptoms Frequent early morning screen time usage (β = 1.391, CI (95%) = .253, 2.528), frequent late-night screen time usage (β = 1.800, CI (95%) = .659, 2.940), frequent use of a phone as an alarm (compared with not) (β = 7.629, CI (95%) = 3.589, 11.670), videogaming addiction (β = .427, CI (95%) = .243, .611) and social media addiction (β = .227, CI (95%) = .001, .453) were significantly associated with more severe insomnia symptoms in adolescents (A1). The independent coefficients of the quantity of screen time were not significantly associated with insomnia symptoms in adolescents (A1). 3.3.6. Screen time and sleep onset variability Frequent late-night screen time usage (β = 932.539, CI (95%) = 386.246, 1478.831) was significantly associated with a larger sleep onset variability in adolescents (A1). The independent coefficients of the quantity and location of screen time and screen time addiction were not significantly associated with sleep onset variability in adolescents (A1). Table 5 , Model summaries of the blockwise regression of screen time behaviours on adiposity, obesity, and sleep outcomes in adolescents Model 1 (adjusted for demographics of the adolescent participants) Model 2 (adjusted for model 1 + demographics of the caregivers) Model 3 (adjusted for model 2 + wellbeing of the adolescent participants) Model 4 (adjusted for model 3 + one screen time variable (i) timing (ii) quantity (%), (iii) location or (iv) addiction of the adolescent participants R² AdjR² F p R² AdjR² F p R² AdjR² F p R² AdjR² ΔAdjR² F p Dependent variable Body fat percentage 0.103 0.072 3.373 0.041 0.341 0.269 4.747 < 0.001 0.74 0.707 21.994 < 0.001 (i) 0.856 0.831 0.124 34.284 < .001 (ii) 0.779 0.741 0.034 20.366 < .001 (iii) 0.835 0.803 0.096 25.854 < .001 (iv) 0.848 0.818 0.111 28.423 < .001 Body mass index percentile 0.071 0.039 2.254 0.114 0.258 0.177 3.190 0.009 0.551 0.492 9.454 < 0.001 (i) 0.650 0.589 0.097 10.716 < .001 (ii) 0.567 0.492 0.000 7.561 < .001 (iii) 0.606 0.528 0.036 7.834 < .001 (iv) 0.684 0.622 0.130 11.044 < .001 Chronotype 0.062 0.031 1.965 0.149 0.256 0.175 3.161 0.010 0.79 0.763 28.994 < 0.001 (i) 0.827 0.797 0.034 29.671 < .001 (ii) 0.816 0.784 0.021 25.586 < .001 (iii) 0.807 0.769 0.006 21.323 < .001 (iv) 0.822 0.787 0.024 23.572 < .001 Sleep habits 0.044 0.011 1.352 0.267 0.267 0.187 3.331 0.007 0.599 0.547 11.537 < .001 (i) 0.620 0.554 0.007 9.43 < .001 (ii) 0.634 0.57 0.023 10.001 < .001 (iii) 0.638 0.567 0.020 8.973 < .001 (iv) 0.616 0.54 -0.007 8.168 < .001 Insomnia symptoms 0.043 0.011 1.327 0.273 0.317 0.242 4.248 0.001 0.744 0.711 22.406 < .001 (i) 0.852 0.827 0.116 33.351 < .001 (ii) 0.792 0.756 0.045 21.978 < .001 (iii) 0.834 0.801 0.090 25.586 < .001 (iv) 0.888 0.866 0.155 40.379 < .001 Sleep onset variability 0.074 0.043 2.371 0.102 0.320 0.254 4.455 < .001 0.715 0.678 19.317 < .001 (i) 0.796 0.761 0.083 22.563 < .001 (ii) 0.780 0.742 0.064 20.457 < .001 (iii) 0.764 0.717 0.039 16.467 < .001 (iv) 0.777 0.733 0.055 17.789 < .001 Key: AdjR² - AdjR²; DV – dependent variable. Red – Reduction in the change of AdjR²; Green – Increase in the change of AdjR². 3.4. Mediation analysis: Wellbeing and relationship between screentime, adiposity and sleep 3.4.1. Late-night screentime and body fat percentage and insomnia symptoms The model’s direct, indirect and total effects were statistically significant. Quality of life partially mediated 21.9% of the relationship between late-night screen time and body fat percentage, and 36.3% of the relationship between late-night screen time and insomnia symptoms (Table 6 ). 3.4.2. Early morning screentime and body fat percentage and insomnia symptoms The model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 30.4% of the relationship between early morning screen time and body fat percentage, and 37.7% of the relationship between early morning screen time and insomnia symptoms (Table 6 ). Table 6 , Mediation analysis of quality of life on the relationship between the timing of screentime and body fat percentage and insomnia symptoms Estimate (β) SE Confidence interval (95%) z-value p-value % mediation Lower Upper Late-night screen time and body fat percentage Indirect 1.109 0.409 0.375 1.950 2.710 0.007 21.9 Direct 3.957 0.551 2.890 5.064 7.181 < 0.001 78.1 Total 5.066 0.421 4.222 5.894 12.019 < 0.001 100.0 Late-night screen time and insomnia symptoms Indirect 1.572 0.486 0.839 2.757 3.235 0.001 36.3 Direct 2.754 0.568 1.461 3.695 4.849 < 0.001 63.7 Total 4.326 0.261 3.789 4.808 16.579 < 0.001 100.0 Early morning screen time and body fat percentage Indirect 1.377 0.470 0.512 2.361 2.930 0.003 30.4 Direct 3.159 0.567 2.060 4.318 5.571 < 0.001 69.6 Total 4.536 0.433 3.659 5.389 10.234 < 0.001 100.0 Early morning screen time and insomnia symptoms Indirect 1.542 0.480 0.7227 2.587 3.214 0.001 37.7 Direct 2.545 0.599 1.232 3.601 4.249 < 0.001 62.3 Total 4.087 0.289 3.449 4.602 14.118 < 0.001 100.0 3.4.3. Videogaming addiction and body fat percentage and insomnia symptoms he model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 34.6% of the relationship between videogaming addiction and body fat percentage, and 36.3% of the relationship between videogaming addiction and insomnia symptoms (Table 7 ). 3.4.4. Social media addiction and body fat percentage and insomnia symptoms The model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 17.4% of the relationship between social media addiction and body fat percentage, and 35.0% of the relationship between social media addiction and insomnia symptoms (Table 7 ). 3.4.5. Mobile phone addiction and body fat percentage and insomnia symptoms The model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 10.6% of the relationship between mobile phone addiction and body fat percentage, and 34.0% of the relationship between mobile phone addiction and insomnia symptoms (Table 7 ). Table 7 , Mediation analysis of quality of life on the relationship between screentime addiction and body fat percentage and insomnia symptoms Estimate (β) SE Confidence interval (95%) z-value p-value % mediation Lower Upper Videogaming addiction and body fat percentage Indirect 0.320 0.108 0.111 0.552 2.961 0.003 34.6 Direct 0.604 0.148 0.321 0.906 4.087 < .001 65.4 Total 0.925 0.095 0.751 1.117 9.711 < .001 100.0 Videogaming addiction and insomnia symptoms Indirect 0.282 0.084 0.130 0.462 3.365 0.001 31.9 Direct 0.601 0.089 0.418 0.776 6.779 < .001 68.1 Total 0.883 0.044 0.806 0.979 19.948 < .001 100.0 Social media addiction and body fat percentage Indirect 0.151 0.077 0.003 0.311 1.959 0.050 17.4 Direct 0.717 0.113 0.503 0.954 6.329 < .001 82.6 Total 0.868 0.077 0.727 1.019 11.294 < .001 100.0 Social media addiction and insomnia symptoms Indirect 0.257 0.070 0.134 0.412 3.654 < .001 35.0 Direct 0.477 0.098 0.274 0.661 4.853 < .001 65.0 Total 0.734 0.059 0.615 0.839 12.525 < .001 100.0 Mobile phone addiction and body fat percentage Indirect 0.069 0.082 − .102 0.231 0.844 0.399 10.6 Direct 0.581 0.110 0.376 0.800 5.283 < .001 89.4 Total 0.650 0.056 0.544 0.755 11.652 < .001 100.0 Mobile phone addiction and insomnia symptoms Indirect 0.188 0.079 0.029 0.342 2.381 0.017 34.0 Direct 0.365 0.098 0.161 0.556 3.707 < .001 66.0 Total 0.553 0.039 0.474 0.626 14.232 < .001 100.0 3.4.6. Weekday screen time and body fat percentage and insomnia symptoms The model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 39.8% of the relationship between weekday screen time and body fat percentage, and 58.1% of the relationship between weekday screen time and insomnia symptoms (Table 8 ). 3.4.7. Weekend screentime and body fat percentage and insomnia symptoms The model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 38.0% of the relationship between weekend screen time and body fat percentage, and 51.4% of the relationship between weekend screen time and insomnia symptoms (Table 8 ). Table 8 , Mediation analysis of quality of life on the relationship between the quantity of screentime and body fat percentage and insomnia symptoms Estimate (β) SE Confidence interval (95%) z-value p-value % mediation Lower Upper Weekday screen time and body fat percentage Indirect 0.659 0.198 0.280 1.071 3.334 0.001 39.8 Direct 0.994 0.288 0.508 1.602 3.459 0.001 60.6 Total 1.654 0.205 1.276 2.085 8.085 < .001 100.0 Weekday screen time and insomnia symptoms Indirect 0.820 0.194 0.427 1.193 4.224 < .001 58.1 Direct 0.590 0.226 0.187 1.090 2.612 0.009 41.9 Total 1.411 0.131 1.170 1.665 10.785 < .001 100.00 Weekend screen time and body fat percentage Indirect 0.590 0.178 0.244 0.969 3.315 0.001 38.0 Direct 0.964 0.244 0.505 1.485 3.945 < .001 62.0 Total 1.554 0.183 1.242 1.946 8.491 < .001 100.0 Weekend screen time and insomnia symptoms Indirect 0.694 0.166 0.379 1.020 4.180 < .001 51.4 Direct 0.657 0.192 0.306 1.055 3.442 0.001 48.6 Total 1.351 0.122 1.116 1.601 11.062 < .001 100.0 4. Discussion 4.1. Overview of findings The findings from this study highlighted that late-night screentime, a higher quantity of screen time on a weekend, using phone as an alarm and videogaming addiction were shared determinants of a later chronotype, poor regulation of sleep onset (including irregular sleep habits, variability in sleep onset and increased insomnia symptoms), adiposity and obesity. These four dimensions of problematic screen time behaviour should therefore be considered when designing health-promoting interventions to improve bedtime routine, improve sleep regularity, reduce pre-sleep onset problems, and reduce adiposity. 4.2. Late-night and bedroom screen time use as a shared determinant of poor sleep and adiposity Screen time in the 30 minutes before sleep onset was associated with a later chronotype and poor regulation of sleep onset (higher sleep onset variability, insomnia symptoms, poorer sleep habit), which would likely contribute to a shorter sleep duration. Evening screen time exposure has been associated with poor sleep duration across many age ranges including toddlers [ 68 ], young children [ 69 ], adolescents [ 69 ] and young adults [ 70 ]. Adolescents with excessive text-messaging whilst in bed, post-bedtime, have been shown to have a shorter sleep duration, increased daytime sleepiness and poorer academic attainment [ 71 – 74 ]. This is because late-night screen time has been shown to suppress melatonin production due to excessive blue-light exposure [ 70 , 75 ]. The exposure contributes to circadian disruption and consequently poor sleep duration and daytime sleepiness [ 68 ]. In support of the current findings, late-night screen usage and excessive screen usage has been shown to be significantly associated with later chronotype [ 10 , 76 , 77 ], increased irregularity of sleep habits [ 77 ], increased insomnia symptoms [ 22 , 78 , 79 ], increased onset latency [ 78 ] and increased sleep onset variability [ 77 ]. Longitudinal research has demonstrated that an excessive quantity of screen time and screen time addiction are predictors of increased insomnia symptoms [ 11 , 80 ] and adiposity [ 81 , 82 ]. The effect of screen time on sleep habits, chronotype or circadian misalignment, and sleep onset variability has not been examined longitudinally to assess directionality. 4.3. Screen time addiction as a shared determinant of poor sleep and adiposity Our findings showed that videogaming addiction was a shared determinant of insomnia symptoms and adiposity. The HBSC study, a large multi-country study of adolescents, found that 13–16 year-olds who were addicted to videogames had significantly later sleep onset, experienced insomnia symptoms, a longer sleep onset latency, a shorter sleep duration, and a larger social jetlag, than those not addicted to videogames [ 83 ]. Furthermore, a multi-analysis study investigating videogaming addiction across different ages within a school in the USA found that videogaming addictive tendencies can start in pre-adolescence [ 23 ]. The negative impact of videogaming addiction, however, was reported at 12-years, with adolescent’s ignoring responsibilities, reducing their sleep in order to play videogames, and neglecting physical activity and socialising outside [ 23 ]. Adolescents with videogaming addiction also engage with late-night screen time, screen time in the bedroom and excessive screen time [ 13 , 84 , 85 ]. Screen time, videogaming, social media and mobile phones, have been designed to encourage digital addictiveness [ 84 , 86 , 87 ], and some are even designed to target adolescents. For example, social media apps target adolescents with short-form videos which have been sown to be more addictive than long-form videos and encourage ‘doom-scrolling’ in adolescents. Consequently, trying to address the addictive tendencies of screen time is difficult. Therefore, a combined approach to an intervention, targeting multiple screen time components may be beneficial for reducing screen time addiction, and improving sleep and obesity. 4.4. The role of weekday/weekend variation in the relationship between screen time, sleep and adiposity The screen time variables identified as determinants of sleep and adiposity showed weekday/weekend variation, with poor weekend screen time habits being more consistently reported as shared determinants of poor sleep and adiposity than weekday habits. For example, excessive screentime on a weekend was identified as a determinant of poor sleep, which implies weekday-to-weekend variation in screen time habits could potentially contribute to unhealthy lifestyles. Previous research has shown that there are variations in screen time activity patterns on a weekday and weekend, with adolescents using excessive screen time on an evening and on a weekend [ 88 – 90 ]. Additionally, the variation in screen time on a weekend is more prominent in girls than boys [ 90 ], and those from a lower SES and with caregivers of a lower education level [ 91 ]. Researchers have discussed whether excessive screen time on a weekend occurs because it is being used as a parenting tool (reward system) [ 92 ], occurs due to an absence or inconsistency in the presence of parental figures (for example, opportunistic if parents work shift patterns) [ 92 ], occurs due to a lifestyle choice the adolescent makes to spend time with peers [ 63 ] and or whether it is learnt behaviour from the family [ 93 ]. Consequently, it has been suggested that interventions targeting weekend behaviour, using a family or parent-dyad setting and school-settings to target peer group social screen time behaviours. 4.5. Wellbeing as a mediator of the relationship between screen time, sleep and adiposity The findings from this study indicated that the quality of life of the adolescent acts as a mediator of the relationships between the different components of screen time and insomnia symptoms and increased adiposity. Wellbeing mediates a larger proportion of the relationship between screen time and insomnia than between screen time and body fat percentage. Specifically, wellbeing accounted for over 50% of the association between weekday and weekend screen time and insomnia symptoms, compared with less than 40% for body fat percentage. A smaller mediating effect of wellbeing was observed for screen time addiction. For instance, wellbeing mediated 11% of the relationship between mobile phone addiction and body fat percentage, compared with 35% for insomnia symptoms. These findings suggest that late-night and early screen use, as well as screen time addiction, may indirectly impair sleep onset and increase adiposity in adolescents through the impact on wellbeing. Previous research has shown that high levels of screen time, particularly through devices like smartphones and tablets, can lead to difficulties in initiating sleep due to the effects of blue light exposure and cognitive overstimulation [ 75 , 94 , 95 ]. This disruption in sleep onset can adversely affect adolescents' wellbeing, contributing to increased stress and emotional distress [ 4 , 96 – 98 ], which may further exacerbate sedentary behaviours [ 99 – 103 ] and unhealthy eating habits [ 104 – 107 ], ultimately heightening the risk of obesity. The findings indicate that wellbeing may play a crucial role in the relationship between screen time and sleep and obesity and that future interventions would need to consider psychological and emotional factors when addressing sleep and obesity issues related to screen time [ 108 , 109 ]. Improving wellbeing in adolescents could help mitigate the adverse effects of screen usage on insomnia and obesity [ 108 , 109 ]. Wellbeing-focused intervention components, such as mindfulness and regular physical activity could also be combined with screen time modifications to maximise the impact of the intervention on adolescent sleep and reduction of obesity [ 110 , 111 ]. 4.6. Strengths and limitations There were multiple strengths of this study, one being the successful recruitment of participants and family members to the study, with little missing data. This indicates interest from North-east Fife for studies examining behaviours, sleep and obesity across early to late adolescence. Recruitment to the TSWS was effective, reaching the target calculated as required to perform the intended regression analyses. This was the first study to measure multiple screen time variables (timing, quantity, location, and addiction) and investigate the association with objective and subjective poor sleep and objective adiposity in adolescents. The measurement tools used for assessing the quantity of screen time and screen time addiction were validated, however, the timing and location of screen time outcomes were assessed using novel questionnaires due to these variables not being routinely assessed. A strength in our measurement of screen timing was that specific questions were asked about the first and last 30 minutes of the day for weekday and weekend separately, which is not often reported on in the literature. The strength of this measurement is that it gives a specific behavioural target that could be easily modified in an intervention, as opposed to minimising the quantity of screen time overall, which has been highlighted as a barrier to previous screen time interventions [ 8 , 9 ]. The wide range of variables collected as part of the TSWS questionnaires and actigraphy enabled the identification of specific individual behaviours that should be considered as targets for intervention, as opposed to using latent class analysis to identifying groups of behaviours or an umbrella of behaviours (for example screen time, rather than specific measures of screen time like addiction, timing of screen time, quantity, and location of use). Due to the cross-sectional design, directionality of the associations cannot be determined. Moreover, adolescent participants and caregivers, whilst recruited from the community, were from one county of Scotland (North-east Fife) and consequently, the ethnicity and SES may not be representative of the whole of Scotland. A final limitation of the TSWS was that with seven actiwatches available for the data collection, the duration of data collection (February-May) meant some participants had more favourable weather and longer daylight hours than others which could have effected their activity levels and mood [ 112 ]. 5. Conclusion The results from this study have indicated that multiple dimensions of problematic screen time behaviours, including late-night and early morning screen time, a higher quantity of screen time (weekend), using a phone in the bedroom overnight and as an screen time addiction, should be considered as shared determinants of higher adiposity, a later chronotype and poor regulation of sleep onset. Poor quality of life mediates the relationship between all screen time components with insomnia symptoms and higher adiposity. Further research should consider interventions modifying the late-night screen time usage, weekend usage and wellbeing to assess if small and manageable change to screen time behaviour has an effect on subsequent sleep and adiposity in adolescents. Declarations Data availability statement: The data that support the findings will be available in the University of St Andrews library repository at https://research-repository.st-andrews.ac.uk/ following an embargo (May 2028) Funding statement: This review was supported by the University of St Andrews as part of a doctoral research program Conflicts of interest: There are no conflicts of interest The dataset(s) supporting the conclusions of this article will be available in the University of St Andrews repository in May 2028 (currently under embargo). 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Paudel, S., et al., Associations of changes in physical activity and discretionary screen time with incident obesity and adiposity changes: longitudinal findings from the UK Biobank. Int J Obes (Lond), 2022. 46 (3): p. 597-604. Hamre, R., et al., Gaming Behaviors and the Association with Sleep Duration, Social Jetlag, and Difficulties Falling Asleep among Norwegian Adolescents. International Journal of Environmental Research and Public Health, 2022. 19 (3): p. 1765. Hjetland, G.J., et al., The association between self-reported screen time, social media addiction, and sleep among Norwegian University students. Frontiers in public health, 2021. 9 : p. 794307. Brautsch, L.A., et al., Digital media use and sleep in late adolescence and young adulthood: A systematic review. Sleep Medicine Reviews, 2023. 68 : p. 101742. Adorjan, M. and R. Ricciardelli, Smartphone and social media addiction: Exploring the perceptions and experiences of Canadian teenagers. 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Magid, H.S.A., et al., Disentangling individual, school, and neighborhood effects on screen time among adolescents and young adults in the United States. Preventive medicine, 2021. 142 : p. 106357. Ozturk Eyimaya, A. and A. Yalçin Irmak, Relationship Between Parenting Practices and Children's Screen Time During the COVID-19 Pandemic in Turkey. Journal of Pediatric Nursing, 2021. 56 : p. 24-29. Lauricella, A.R., E. Wartella, and V.J. Rideout, Young children's screen time: The complex role of parent and child factors. Journal of Applied Developmental Psychology, 2015. 36 : p. 11-17. Duffy, J.F. and K.P. Wright Jr, Entrainment of the human circadian system by light. Journal of biological rhythms, 2005. 20 (4): p. 326-338. Foster, R., Fundamentals of circadian entrainment by light. Lighting Research & Technology, 2021. 53 (5): p. 377-393. Mougharbel, F., et al., Longitudinal associations between different types of screen use and depression and anxiety symptoms in adolescents. Front Public Health, 2023. 11 : p. 1101594. Tandon, P.S., et al., Association of Children's Physical Activity and Screen Time With Mental Health During the COVID-19 Pandemic. JAMA Netw Open, 2021. 4 (10): p. e2127892. Zhang, Y., et al., The relationships between screen time and mental health problems among Chinese adults. J Psychiatr Res, 2022. 146 : p. 279-285. Chaput, J.P., et al., Electronic screens in children's bedrooms and adiposity, physical activity and sleep: do the number and type of electronic devices matter? Can J Public Health, 2014. 105 (4): p. e273-9. Harrington, D.M., et al., Concurrent screen use and cross-sectional association with lifestyle behaviours and psychosocial health in adolescent females. Acta Paediatr, 2021. 110 (7): p. 2164-2170. Jerome, G.J., et al., Physical Activity Levels and Screen Time among Youth with Overweight/Obesity Using Mental Health Services. Int J Environ Res Public Health, 2022. 19 (4). Nagata, J.M., et al., Association of Physical Activity and Screen Time With Body Mass Index Among US Adolescents. JAMA Netw Open, 2023. 6 (2): p. e2255466. Seral-Cortes, M., et al., Mediterranean Diet, Screen-Time-Based Sedentary Behavior and Their Interaction Effect on Adiposity in European Adolescents: The HELENA Study. Nutrients, 2021. 13 (2). Jensen, M.L., et al., Television viewing and using screens while eating: Associations with dietary intake in children and adolescents. Appetite, 2022. 168 : p. 105670. Kracht, C.L., et al., Association of Night-Time Screen-Viewing with Adolescents' Diet, Sleep, Weight Status, and Adiposity. Int J Environ Res Public Health, 2022. 19 (2). Lyngdoh, M., et al., Diet, Physical Activity, and Screen Time among School Students in Manipur. Indian J Community Med, 2019. 44 (2): p. 134-137. Tambalis, K.D., et al., Screen time and its effect on dietary habits and lifestyle among schoolchildren. Cent Eur J Public Health, 2020. 28 (4): p. 260-266. Haghjoo, P., et al., Screen time increases overweight and obesity risk among adolescents: a systematic review and dose-response meta-analysis. BMC primary care, 2022. 23 (1): p. 161. Zhang, P., et al., Effect of screen time intervention on obesity among children and adolescent: A meta-analysis of randomized controlled studies. Preventive Medicine, 2022. 157 : p. 107014. de Lara Perez, B. and M. Delgado-Rios, Mindfulness-based programs for the prevention of childhood obesity: A systematic review. Appetite, 2022. 168 : p. 105725. Godsey, J., The role of mindfulness based interventions in the treatment of obesity and eating disorders: An integrative review. Complementary Therapies in Medicine, 2013. 21 (4): p. 430-439. Wong, L.S., et al., Moderate-to-vigorous intensity physical activity during school hours in a representative sample of 10–11-year-olds in Scotland. Journal of Science and Medicine in Sport, 2023. 26 (2): p. 120-124. Additional Declarations No competing interests reported. Supplementary Files TSWSBMCMedicineAdditionalfile.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 14 Jan, 2025 Reviews received at journal 07 Jan, 2025 Reviewers agreed at journal 16 Dec, 2024 Reviews received at journal 12 Dec, 2024 Reviewers agreed at journal 10 Dec, 2024 Reviewers invited by journal 08 Nov, 2024 Editor invited by journal 07 Nov, 2024 Editor assigned by journal 04 Nov, 2024 Submission checks completed at journal 04 Nov, 2024 First submitted to journal 04 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5386674","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":378338234,"identity":"2a6ebcbd-72a0-4710-8eeb-e658c9e312b2","order_by":0,"name":"Emma Louise Gale","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie2RsUrEQBBARxZyzYZpZ/9iw4Fw1f5KjsBVQRCbFEdYEWJpa3Ec9wlWV29YSBWxjaSJjVWKLa3UO64QhKzaWeyrhpl5zAwDEAj8S5hJXHEK6StrfEqUXlF76v6twqWLq78oiLvkQWzLEmaPdV8UVsHMDoy304q4HzJ5ubcE/CJbtK1dar6SjHfTiuxMI8XekDL5ubiu+hQgB8bdtKK6+vYt3pQEOB6U914dAr8i8QZkrBkBHafo/kzTcYpnMeoimFNjhaZxvtDNx7KiV1lvPOfj3ZNL3LpEwDx51uuVQsxehrGZVoDSb4kIfngkoL8cCAQCAYBPoaVQQz0wHO0AAAAASUVORK5CYII=","orcid":"","institution":"University of St Andrews","correspondingAuthor":true,"prefix":"","firstName":"Emma","middleName":"Louise","lastName":"Gale","suffix":""},{"id":378338238,"identity":"247d1262-3bb3-48c5-b904-b64b0996934f","order_by":1,"name":"Andrew James Williams","email":"","orcid":"","institution":"University of Edinburgh","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"James","lastName":"Williams","suffix":""},{"id":378338239,"identity":"c3a3cedd-1f74-433c-836e-01541a89b79b","order_by":2,"name":"Joanne E Cecil","email":"","orcid":"","institution":"University of St Andrews","correspondingAuthor":false,"prefix":"","firstName":"Joanne","middleName":"E","lastName":"Cecil","suffix":""}],"badges":[],"createdAt":"2024-11-04 09:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5386674/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5386674/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70386081,"identity":"7558c2a2-1d89-4899-a409-7456985da9a3","added_by":"auto","created_at":"2024-12-02 17:18:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":180555,"visible":true,"origin":"","legend":"\u003cp\u003eCross-sectional primary research study protocol (TSWS), including pre-study caregiver consent, Consultation 1, Home component and Consultation 2 [35]\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5386674/v1/53c32ea31dbad57aefa673f5.png"},{"id":70388233,"identity":"94bb3b60-daf7-4376-bba0-4dcb96ec6485","added_by":"auto","created_at":"2024-12-02 17:25:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2093889,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5386674/v1/7a4d7a68-eef1-463e-8d57-9a9d49222cae.pdf"},{"id":70386060,"identity":"d08c6400-0b23-4f25-a396-5977e16b2d7c","added_by":"auto","created_at":"2024-12-02 17:18:01","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":112334,"visible":true,"origin":"","legend":"","description":"","filename":"TSWSBMCMedicineAdditionalfile.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5386674/v1/5fe43838edb0921caa8d9688.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Late-night screen time and screen time addiction as shared determinants of poor sleep and obesity in adolescents aged 11-14 years in Scotland","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe pervasive use of digital screens, addictive social media, apps and new digital technology has become an integral part of modern adolescence, significantly influencing health outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. During COVID-19, there was a shift to online and remote school-working and socialisation causing a shift to adolescents increasingly using screens for everyday activities and becoming more dependent on digital devices [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Previous research has reported that excessive screen time among adolescents has a detrimental impact on both sleep and obesity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The rapid proliferation of smartphones, tablets, and computers has led to significant changes in sleep patterns, disrupting circadian rhythms and altering chronotypes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Prolonged screen exposure, particularly before bedtime, is associated with delayed sleep onset [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], insomnia symptoms [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], short sleep duration [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and increased social jetlag [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These disruptions in sleep habits contribute to reduced physical activity and increased sedentary behaviour [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], behaviours identified as critical factors in the rising prevalence of obesity among youth [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA research gap identified by systematic review was to investigate whether different components of screen time, not just overall quantity of screen time, are shared determinants of sleep and obesity in adolescents [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Identifying the specific components of habitual screen time that are most detrimental to health is crucial for designing effective health-promoting interventions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Different aspects of screen use, such as the type of content consumed [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], the timing of usage [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], and screentime addiction [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], could each have distinct impacts on adolescent health and the developing brain. For example, engaging in stimulating activities like gaming or social media use before bedtime can exacerbate insomnia symptoms [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], whereas passive screen time, such as watching TV, has been shown to contribute more significantly to sedentary behaviour and obesity [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, excessive late-night screen time can interfere with critical periods of brain development, affecting cognitive functions, emotional regulation, and mental health [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. By pinpointing these components, interventions can be tailored to address the most harmful habits.\u003c/p\u003e \u003cp\u003eConsequently, the research question addressed by this study was: are different components of problematic screentime usage shared determinants of poor sleep and higher adiposity in adolescents? The different components of screen time examined in this study included late-night and early morning usage, quantity of screen time, location of screen time, and screen time addiction.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design, recruitment, and procedure\u003c/h2\u003e \u003cp\u003eA cross-sectional quantitative study was conducted, including a caregiver-assessed questionnaire, adolescent-assessed questionnaire, researcher-assessed objective anthropometry, and 7\u0026ndash;10 days of actigraphy in 11\u0026ndash;14 year-olds (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Ethical approval from the University of St Andrews School of Medicine ethics committee was gained in January 2023 (approval code: MD16703).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdolescent participants (aged between 11\u0026ndash;14 years) and their caregivers were recruited via flyers at leisure centres, cafes, youth centres, transport centres, University memo adverts, and online Facebook community groups. Inclusion criteria for the study included (i) being 11\u0026ndash;14 years at recruitment, (ii) enrolled at a school in Fife, (iii) informed consent obtained from the caregiver and (iv) free of underlying health conditions and medication use. Exclusion criteria included (i)\u0026thinsp;\u0026lt;\u0026thinsp;11 years or \u0026gt;\u0026thinsp;14 years (ii)\u0026thinsp;\u0026lt;\u0026thinsp;3 weekdays and \u0026lt;\u0026thinsp;1 weekend days of actigraphy data available for the adolescent participant, (iii) caregiver questionnaire, including consent, is absent, (iv) medication use and (v) already having a sibling from the same household take part in the study. A G*Power calculation was completed to determine the desired study sample size. The recommended effect, power and error sizes were used [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. An f-test linear regression test was conducted (effect size F\u0026sup2;= 0.30, α\u0026thinsp;=\u0026thinsp;0.05, power\u0026thinsp;=\u0026thinsp;0.8), which suggested a sample of 59 would be sufficient for an actual power of 0.807.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Research variables\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Caregiver demographics\u003c/h2\u003e \u003cp\u003eCaregivers were asked to describe their relationship to the adolescent, date of birth, gender, ethnicity, marital status, and postcode. If a second adult lived in the home, for example a spouse, partner, another guardian or grandparent, their date of birth, gender and ethnicity was also recorded. Caregivers were asked \u0026ldquo;what is your highest level of education\u0026rdquo; with answers and scores of \u0026ldquo;none or few school qualifications\u0026rdquo; (0), \u0026ldquo;secondary school leaver\u0026rdquo; (1), \u0026ldquo;sixth form/college or apprenticeship\u0026rdquo; (2), \u0026ldquo;university degree\u0026rdquo; (3) or \u0026ldquo;masters or postgraduate degree\u0026rdquo; (4). Caregivers were asked to report their current employment status and shift patterns. For example, \u0026ldquo;as part of your work, do you work night shifts?\u0026rdquo; and \u0026ldquo;as part of your work do you work shifts that finish late in the evening (after 11pm)?\u0026rdquo; with answers of \u0026ldquo;never\u0026rdquo; (0) \u0026ldquo;rarely\u0026rdquo; (1), \u0026ldquo;sometimes\u0026rdquo; (2), \u0026ldquo;often\u0026rdquo; (3), \u0026ldquo;all the time\u0026rdquo; (4) and \u0026ldquo;not applicable\u0026rdquo; (0). A higher score indicating more frequent late or night shifts. If another adult lived in the household, the same questions were asked of the second household member. Caregivers were asked for their height (cm or in feet and inches) and weight (kg or stones and pounds), and BMI (kg/m\u003csup\u003e2\u003c/sup\u003e) was then calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Adolescent demographics\u003c/h2\u003e \u003cp\u003eThe adolescent\u0026rsquo;s date of birth, gender, ethnicity, and pubertal status were self-reported. Pubertal status was assessed using six questions from the Health Behaviour in School-aged Children (HBSC) study [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Adolescent participants answered either male- or female-specific questions regarding any pubertal developments or could opt not to answer either and move on to the next section of the questionnaire. Socioenvironmental status was derived using SIMD [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] quintile data from the participant\u0026rsquo;s home postcode reported by the caregiver.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Anthropometry\u003c/h2\u003e \u003cp\u003eThe adolescent participant\u0026rsquo;s height (m) and weight (kg) were measured three times by a trained researcher (EG), and a mean was calculated. Height was measured using a portable stadiometer (The Leicester Height Measure, Seca Ltd.) (0.1cm precision) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], with no shoes, and standing straight with the adolescent participant\u0026rsquo;s head facing forward [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and a mean was then calculated. Adolescent weight (kg) was assessed using Tanita body composition scales, (TBF-300M) (0.1kg precision) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Derived variables included BMI ((kg/m\u003csup\u003e2\u003c/sup\u003e). Body mass index percentile was derived using WHO guideline cut-offs: \u0026lt;5th percentile indicated underweight, \u0026ge;5th to \u0026lt;\u0026thinsp;85th percentile indicated healthy weight, \u0026ge;\u0026thinsp;85th to \u0026lt;\u0026thinsp;95th percentile indicated overweight, and \u0026ge;\u0026thinsp;95th percentile indicated obesity [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdolescent adiposity (body fat percentage) was measured using bioelectrical impedance (Tanita body composition scales, TBF-300M) (0.1kg precision) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], via bioelectrical impedance [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and a mean of the three readings was then calculated [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This method provides reliable estimates of body composition in a quick, low cost, non-invasive manner that increases compliance [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Adolescent participants were asked to remove shoes and socks, wear light clothing and empty their pockets [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Adiposity status groups (under-fat, healthy-fat, over-fat and obese) were determined by UK age- and gender-specific validated standard cut-offs [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Chronotype and sleep\u003c/h2\u003e \u003cp\u003e \u003cem\u003eChronotype\u003c/em\u003e was assessed using the 19-item Morningness Eveningness Questionnaire (MEQ) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. All 19-items were multiple choice, with scores being allocated to each answer and combined for a final score. A final score of \u0026le;\u0026thinsp;41 indicated an \u0026ldquo;evening type\u0026rdquo;, 42\u0026ndash;58 indicated an \u0026ldquo;intermediate type\u0026rdquo; and \u0026ge;\u0026thinsp;59 indicated a \u0026ldquo;morning type\u0026rdquo;. The MEQ has been validated in adolescents [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and has been used in multiple sleep studies with adolescents [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Cronbach's α coefficients have varied across validity studies (α\u0026thinsp;\u0026gt;\u0026thinsp;0.80) in different countries, for example New Zealand recorded reliability of α\u0026thinsp;=\u0026thinsp;0.83 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and Slovenia recorded a reliability of α\u0026thinsp;=\u0026thinsp;0.86 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] in a normative adult sample.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSleep habits\u003c/em\u003e were assessed using an adapted eight-domain and 33-item children\u0026rsquo;s sleep habit questionnaire (CSHQ) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The original questionnaire has been validated and used in children and adolescents [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] with the Cronbach\u0026rsquo;s α reliability coefficient ranging from 0.68 in the community and 0.78 in clinical paediatric populations [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The questionnaire was adapted to allow adolescent participants to self-report rather than caregiver-report. The questionnaire assesses bedtime resistance, sleep onset latency, sleep duration, sleep anxiety, night wakings, parasomnias, sleep-disordered breathing, and daytime sleepiness. Questions were asked on a Likert scale, for example \u0026ldquo;Adolescent goes to bed at the same time at night\u0026rdquo;. Answers and scores were \u0026ldquo;always (7 days)\u0026rdquo; (4), \u0026ldquo;usually (5\u0026ndash;6 days a week)\u0026rdquo; (3), \u0026ldquo;sometimes (2\u0026ndash;4 days a week)\u0026rdquo; (2), \u0026ldquo;rarely (one day a week)\u0026rdquo; (1) and \u0026ldquo;never\u0026rdquo; (0). A higher score indicated better and more regular sleep habits.\u003c/p\u003e \u003cp\u003e \u003cem\u003eInsomnia symptoms\u003c/em\u003e were assessed using the seven-item insomnia severity index (ISI) [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The seven questions were scored on a Likert scale 0\u0026ndash;4. For example, \u0026ldquo;How satisfied/dissatisfied are you with your current sleep pattern?\u0026rdquo; \u0026ldquo;very satisfied\u0026rdquo; (0), \u0026ldquo;satisfied\u0026rdquo; (1), \u0026ldquo;moderately satisfied\u0026rdquo; (2), \u0026ldquo;dissatisfied\u0026rdquo; (3) and \u0026ldquo;very dissatisfied\u0026rdquo; (4). The scores of the seven items are combined, and a total score of 0\u0026ndash;7 indicated no clinically significant insomnia, 8\u0026ndash;14 is subthreshold insomnia, 15\u0026ndash;21 indicated moderate clinical insomnia, and 22\u0026ndash;28 indicated severe clinical insomnia [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The ISI was initially validated in 17-82-years [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] but has since been validated in the adolescent population with a Cronbach's α reliability coefficient of 0.83 [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eSleep onset variability\u003c/em\u003e was assessed by actigraphy [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], with the adolescent wearing an Actigraph GT3X-BT [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] for 7\u0026ndash;10 days. The Actigraph GT3X-BT has been validated for capturing sleep variables (including sleep timing, efficiency and awakenings) in children and adolescents (including those with obesity) [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] against the gold standard, polysomnography (90.2% accuracy, 95.7% sensitivity and 62% specificity) [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In this study, for the data to be valid, \u0026ge;\u0026thinsp;3 weekday nights and \u0026ge;\u0026thinsp;1 weekend night was required. The sleep variables were detected and formulated using the Cole-Kripke algorithm [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], and a consensus sleep diary was used to corroborate sleep onset [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Sleep onset variability was defined as the standard deviation of an individual\u0026rsquo;s sleep onset.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5. Wellbeing (Quality of life)\u003c/h2\u003e \u003cp\u003e \u003cem\u003eQuality of life (QoL)\u003c/em\u003e was self-assessed using KIDSCREEN-27 [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The KIDSCREEN-27 is a validated 27-item version of KIDSCREEN-52 and had a Cronbach\u0026rsquo;s alpha reliability coefficient of above 0.78 in all domains [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Participants answered questions on the five domains: physical wellbeing (5 items), psychological wellbeing (7 items), autonomy and caregiver relation (7 items), peers and social support (4 items) and school environment (4 items). Items were scored on a Likert scale 1\u0026ndash;5, for example \u0026ldquo;Have your caregiver(s) treated you fairly?\u0026rdquo; was answered with \u0026ldquo;never\u0026rdquo; (5), \u0026ldquo;seldom\u0026rdquo; (4), \u0026ldquo;quite often\u0026rdquo; (3), \u0026ldquo;very often\u0026rdquo; (2) or \u0026ldquo;always\u0026rdquo; (1). A total for each domain and a total score for all 27-items is then calculated, a higher score indicated a poorer QoL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.6. Screen time\u003c/h2\u003e \u003cp\u003e\u003cem\u003eQuantity of screen time\u003c/em\u003e: Self-assessed using two domains from the validated SCREENS questionnaire (SCREENS-Q): screen media environment and children\u0026rsquo;s screen use [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Participants were asked to report how many different types of electronic devices were in the household and how often the adolescent participant had access to them on a weekday and weekend. Adolescents were also asked about whether the caregiver set screen time guidelines, how often the adolescent participant used screen time guidelines and how long the adolescent participant used screen media on a weekday and weekend.\u003c/p\u003e \u003cp\u003e \u003cem\u003eTiming of screen time\u003c/em\u003e: Late-night and early-morning screen time was assessed by four questions: (1) \u0026ldquo;How may days do you use your phone on a weekday in the first 30 minutes after waking up?\u0026rdquo; and (2) \u0026ldquo;How may days do you use your phone on a weekday in the last 30 minutes before bed?\u0026rdquo;, and the answers were \u0026ldquo;none\u0026rdquo;, \u0026ldquo;1\u0026ndash;2 days a week\u0026rdquo;, \u0026ldquo;3\u0026ndash;4 days a week\u0026rdquo; or \u0026ldquo;5 days a week\u0026rdquo;. The same questions were asked for the weekend with answers of \u0026ldquo;none\u0026rdquo;, \u0026ldquo;one day at the weekend\u0026rdquo; or \u0026ldquo;both days at the weekend\u0026rdquo;.\u003c/p\u003e \u003cp\u003e \u003cem\u003eLocation of screen time\u003c/em\u003e: Whether the adolescent used screen time in bed or in the bedroom was assessed using three questions reported by the adolescent: (1) Do you use screens whilst in bed? (2) Do you use screens in your bedroom? (3) Do you use your phone as an alarm?\u003c/p\u003e \u003cp\u003e \u003cem\u003eScreen time addiction\u003c/em\u003e: Social media addiction (SMA-Q), video gaming addiction (VGA-Q) and mobile phone addiction (MPA-Q), were self-assessed using three domains from the Adolescent Brain and Cognitive Development study questionnaire (ABCD): VGA-Q (six items), SMA-Q (six items) and MPA-Q (8 items) [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. THE VGA-Q and SMA-Q, both consisted of a Likert scale with answers \u0026ldquo;Never\u0026rdquo; (0), \u0026ldquo;Very rarely\u0026rdquo; (1), \u0026ldquo;Rarely\u0026rdquo; (2), \u0026ldquo;Sometimes\u0026rdquo; (3), \u0026ldquo;Often\u0026rdquo; (4) and \u0026ldquo;Very often\u0026rdquo; (5) [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The MPA-Q also consisted of a Likert scale with answers \u0026ldquo;Strongly disagree\u0026rdquo; (1), \u0026ldquo;Disagree\u0026rdquo; (2), \u0026ldquo;Somewhat disagree\u0026rdquo; (3), \u0026ldquo;Neither disagree, nor agree\u0026rdquo; (4), \u0026ldquo;Somewhat agree\u0026rdquo; (5), \u0026ldquo;Agree\u0026rdquo; (6), \u0026ldquo;Strongly disagree\u0026rdquo; (7) [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. A The MPA-Q was validated [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] and further used [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] in adolescents prior to the ABCD study use. The SMA-Q and VGA-Q were first used and validated by the ABCD study and were designed based off the validated Bergen Facebook Addiction Scale [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Higher scores for each individual questionnaire, SMA-Q, VGA-Q and MPA-Q indicated the individual was increasingly addicted to the social media, videogaming and mobile phone use, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe data were extracted and analysed using SPSS 28 Statistics and R. Missing data were assessed using the Little\u0026rsquo;s Missing Completely At Random (MCAR) test [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Frequency diagrams and descriptive tables were used to demonstrate sample characteristics of the adolescent participants and caregivers. T-tests were used to assess the difference between adiposity status groups (under-fat and healthy-fat versus over-fat and obese). Pearson correlations and descriptive statistics were used to identify correlations between screen time and sleep, obesity, and adiposity in the adolescent participants. Block-wise regression analysis was used to examine which screen time variables were independently associated with the sleep and adiposity outcomes (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Adjusted variables were selected based on associations identified in unadjusted analyses or have been previously identified as shared determinants of poor sleep and obesity in adolescents [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Block 1 and 2 adjusted for demographics of the adolescents and caregivers, respectively, that were associated with poor sleep and obesity in the unadjusted analyses. Block 3 adjusted for wellbeing (QoL) as an indicator of wellbeing. Block 4 of the regression analysis included the screen time variable. Significant associations from the regression analyses were identified using a\u0026thinsp;\u0026plusmn;\u0026thinsp;10% difference (β \u0026le;-0.1 or \u0026ge;\u0026thinsp;0.1). Based on the regression analysis, the sleep and obesity variables with the strongest association with screen time were used to conduct mediation analyses using the laavan package on R [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The mediation analysis was conducted to examine whether wellbeing (QoL) mediated the relationship between screen time and sleep and adiposity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Adjusted variables in the blockwise regression analyses of screen time on adiposity and sleep outcomes in adolescent participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlock number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted for\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaternal employment status\u003c/p\u003e \u003cp\u003eMaternal night shifts\u003c/p\u003e \u003cp\u003eMaternal late shifts\u003c/p\u003e \u003cp\u003eMaternal BMI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuality of life\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne screen time habit\u003c/p\u003e \u003cp\u003e(i) Timing of screen time (last 30min and first 30min of the day)\u003c/p\u003e \u003cp\u003e(ii) Quantity of screen time (on a weekday and weekend)\u003c/p\u003e \u003cp\u003e(iii) Location of screen time (use phone in bed, in the bedroom and as an alarm)\u003c/p\u003e \u003cp\u003e(iv) Addictive tendencies of screen time (social media, videogaming and mobile phone addiction)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003eKey: BMI \u0026ndash; body mass index; min \u0026ndash; minutes\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Sample description\u003c/h2\u003e \u003cp\u003eSixty-six participants were initially recruited to the study, 62 completed the study and were included in the study analysis. The adolescent participants included in the analysis were from North-East Fife, Scotland, including 29 males and 33 females, with a mean age of 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 years (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMean body fat percentage was 22.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5% and mean BMIp 60.3\u0026thinsp;\u0026plusmn;\u0026thinsp;32.1. There were significant differences between adiposity groups (under-fat/healthy-fat: UF/HF (n\u0026thinsp;=\u0026thinsp;40) and over-fat/obese: OF/OB (n\u0026thinsp;=\u0026thinsp;22)) across all sleep outcomes, (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and screen time dimensions (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sleep characteristics reported in adolescents in the over-fat and obese adiposity status include later chronotype, poorer sleep habits, more severe insomnia symptoms, later sleep onset and longer sleep onset latency compared with those in the under-fat/ healthy-fat group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Significant differences between body fat status groups were reported in the timing of screen time (screen time use in the first 30 minutes of the day and the last 30 minutes of the day), quantity of screen time (hours of screen time on a weekday and weekend), location of screen time (phone use in bed, having phone in the bedroom overnight and using phone as an alarm) and screen time addiction (videogaming, social media and mobile phone) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Unadjusted associations\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Screen time and adiposity\u003c/h2\u003e \u003cp\u003eHigher adiposity (higher body fat percentage, larger waist circumference, larger hip circumference, larger waist-to-hip ratio, larger waist-to-height ratio) and a higher BMIp were meaningfully associated with early morning and late-night screen time (weekday and weekend), a higher screen time quantity (weekday and weekend), screen time addiction (videogaming, social media and mobile phone) and use of phone in bed, in the bedroom overnight and as an alarm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Screen time and sleep\u003c/h2\u003e \u003cp\u003ePoorer sleep outcomes (a later chronotype, poorer sleep habits, more severe insomnia symptoms, later sleep onset on a weekday and weekend, a higher sleep onset variability and longer sleep onset latency on a weekday and weekend) were meaningfully associated with early morning and late-night screen time (weekday and weekend), a higher screen time quantity weekday and weekend), screen time addiction (videogaming, social media and mobile phone) and use of phone in bed, in the bedroom overnight and as an alarm.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Participant characteristics: adolescent and caregiver demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eDemographic variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdolescent gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdolescent age (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdolescent ethnic minority\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdolescent body development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdolescent body fat percentage (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdolescent body mass index percentile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e32.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eAdolescent and caregiver SES (SIMD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSIMD rank\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5209.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1259.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuintile 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuintile 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuintile 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuintile 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuintile 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHighest level of maternal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;16 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u0026ndash;18 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eMaternal employment status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull-time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePart-time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetired/ homemaker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFrequency of maternal night shifts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever/NA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOften\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFrequency of maternal late shifts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever/NA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOften\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of caregiver household figures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eKey: BMI \u0026ndash; Body mass index; kg \u0026ndash; kilograms; m \u0026ndash; metres; NA \u0026ndash; not applicable; SD \u0026ndash; Standard deviation; SIMD \u0026ndash; Scottish Index of Multiple Deprivation (2020)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Participant characteristics: adolescent sleep by adiposity status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSleep outcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUF/HF (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eOF/OB (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorningness-eveningness questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eChild sleep habits questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsomnia severity index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSleep onset (time)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22:38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e00:55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e00:29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e00:45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23:17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e01:14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23:23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e01:11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e01:54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e01:11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e00:17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e01:41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSleep onset latency (mins)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eKey: HF \u0026ndash; healthy-fat; OB \u0026ndash; obese; OF \u0026ndash; over-fat; mins \u0026ndash; minutes; WD \u0026ndash; weekday; WE - weekend\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Adolescent screentime by adiposity status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eScreen time variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eUF/HF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003eOF/OB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"15\" nameend=\"c15\" namest=\"c1\"\u003e \u003cp\u003eTiming of screen time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFirst 30 minutes of the day (WD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2 days a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4 days a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 days a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLast 30 minutes of the day (WD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2 days a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;4 days a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 days a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFirst 30 minutes of the day (WE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLast 30 minutes of the day (WD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"15\" nameend=\"c15\" namest=\"c1\"\u003e \u003cp\u003eScreen time addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVideogaming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e7.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e9.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e8.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e17.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e11.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMobile phone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e11.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e46.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e8.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e31.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e15.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"15\" nameend=\"c15\" namest=\"c1\"\u003e \u003cp\u003eQuantity of screen time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eQuantity of screen time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e10.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e12.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"15\" nameend=\"c15\" namest=\"c1\"\u003e \u003cp\u003eLocation of screen time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse of phone in bed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhone in the bedroom overnight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhone as an alarm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"16\"\u003eKey: HF \u0026ndash; healthy-fat; N \u0026ndash; number; OB \u0026ndash; obese; OF \u0026ndash; over-fat; mins \u0026ndash; minutes; SD \u0026ndash; standard deviation; WD \u0026ndash; weekday; WE \u0026ndash; weekend; var - variability\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Adjusted associations\u003c/h2\u003e \u003cp\u003eModel summaries for blocks 1, 2, 3, and 4 (i-iv) have been reported in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. Screen time and body fat percentage\u003c/h2\u003e \u003cp\u003eFrequent late-night screen time usage (β\u0026thinsp;=\u0026thinsp;2.834, CI (95%)\u0026thinsp;=\u0026thinsp;1.514, 4.154), frequent use of a phone in bed (β\u0026thinsp;=\u0026thinsp;3.399, CI (95%)\u0026thinsp;=\u0026thinsp;2.850, 13.413) and videogaming addiction (β\u0026thinsp;=\u0026thinsp;.312, CI (95%)\u0026thinsp;=\u0026thinsp;.061, .563) were significantly associated with higher body fat percentage in adolescents (A1). The independent coefficients of the quantity of screen time were not significantly associated with body fat percentage (A1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. Screen time and body mass index percentile\u003c/h2\u003e \u003cp\u003eFrequent late-night screen time usage (β\u0026thinsp;=\u0026thinsp;6.970, CI (95%)\u0026thinsp;=\u0026thinsp;1.207, 12.732) and videogaming addiction (β\u0026thinsp;=\u0026thinsp;1.082, CI (95%)\u0026thinsp;=\u0026thinsp;.069, 2.095) were significantly associated with higher BMIp in adolescents (A1). The independent coefficients of the quantity and location of screen time were not significantly associated with BMIp (A1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. Screen time and chronotype\u003c/h2\u003e \u003cp\u003eFrequent early morning screen time (β= -1.772, CI (95%) = -3.503, \u0026minus;\u0026thinsp;.041) and a higher quantity of screen time on a weekend (β= -1.098, CI (95%) = -2.117, \u0026minus;\u0026thinsp;.077) were significantly associated with a later chronotype in adolescents (A1). The independent coefficients of the location of screen time and screen time addiction were not significantly associated with chronotype in adolescents (A1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4. Screen time and sleep habits\u003c/h2\u003e \u003cp\u003eA higher quantity of screen time on a weekend (β\u0026thinsp;=\u0026thinsp;1.404, CI (95%)\u0026thinsp;=\u0026thinsp;.018, 2.789) and keeping the phone in the bedroom overnight (compared with not) (β= -8.956, CI (95%) = -17.820, \u0026minus;\u0026thinsp;.091) were significantly associated with poorer sleep habits in adolescents (A1). The independent coefficients of the timing of screen time and screen time addiction were not significantly associated with sleep habits in adolescents (A1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.3.5. Screen time and insomnia symptoms\u003c/h2\u003e \u003cp\u003eFrequent early morning screen time usage (β\u0026thinsp;=\u0026thinsp;1.391, CI (95%)\u0026thinsp;=\u0026thinsp;.253, 2.528), frequent late-night screen time usage (β\u0026thinsp;=\u0026thinsp;1.800, CI (95%)\u0026thinsp;=\u0026thinsp;.659, 2.940), frequent use of a phone as an alarm (compared with not) (β\u0026thinsp;=\u0026thinsp;7.629, CI (95%)\u0026thinsp;=\u0026thinsp;3.589, 11.670), videogaming addiction (β\u0026thinsp;=\u0026thinsp;.427, CI (95%)\u0026thinsp;=\u0026thinsp;.243, .611) and social media addiction (β\u0026thinsp;=\u0026thinsp;.227, CI (95%)\u0026thinsp;=\u0026thinsp;.001, .453) were significantly associated with more severe insomnia symptoms in adolescents (A1). The independent coefficients of the quantity of screen time were not significantly associated with insomnia symptoms in adolescents (A1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.3.6. Screen time and sleep onset variability\u003c/h2\u003e \u003cp\u003eFrequent late-night screen time usage (β\u0026thinsp;=\u0026thinsp;932.539, CI (95%)\u0026thinsp;=\u0026thinsp;386.246, 1478.831) was significantly associated with a larger sleep onset variability in adolescents (A1). The independent coefficients of the quantity and location of screen time and screen time addiction were not significantly associated with sleep onset variability in adolescents (A1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Model summaries of the blockwise regression of screen time behaviours on adiposity, obesity, and sleep outcomes in adolescents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"19\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003cp\u003e\u003cem\u003e(adjusted for demographics of the adolescent participants)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003cp\u003e\u003cem\u003e(adjusted for model 1\u0026thinsp;+\u0026thinsp;demographics of the caregivers)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003cp\u003e\u003cem\u003e(adjusted for model 2\u0026thinsp;+\u0026thinsp;wellbeing of the adolescent participants)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c19\" namest=\"c14\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003cp\u003e\u003cem\u003e(adjusted for model 3\u0026thinsp;+\u0026thinsp;one screen time variable (i) timing (ii) quantity (%), (iii) location or (iv) addiction of the adolescent participants\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAdjR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eAdjR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eAdjR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003eAdjR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003eΔAdjR\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"19\" nameend=\"c19\" namest=\"c1\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBody fat percentage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e0.041\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e4.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e21.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(i)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.124\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e34.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(ii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.034\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e20.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.096\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e25.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.111\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e28.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBody mass index percentile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e9.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(i)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.097\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e10.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(ii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e7.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.036\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e7.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.130\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e11.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eChronotype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e28.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(i)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.034\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e29.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(ii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.021\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e25.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.006\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e21.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.024\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e23.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSleep habits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e11.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(i)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.007\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e9.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(ii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.023\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e10.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.020\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e8.973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e-0.007\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e8.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eInsomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e4.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e22.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(i)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.116\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e33.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(ii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.045\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e21.978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.090\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e25.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.155\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e40.379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSleep onset variability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e4.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e19.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(i)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.083\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e22.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(ii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.064\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e20.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iii)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.039\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e16.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(iv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003e0.055\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e17.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eKey: AdjR\u0026sup2; - AdjR\u0026sup2;; DV \u0026ndash; dependent variable. Red \u0026ndash; Reduction in the change of AdjR\u0026sup2;; Green \u0026ndash; Increase in the change of AdjR\u0026sup2;.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Mediation analysis: Wellbeing and relationship between screentime, adiposity and sleep\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1. Late-night screentime and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003eThe model\u0026rsquo;s direct, indirect and total effects were statistically significant. Quality of life partially mediated 21.9% of the relationship between late-night screen time and body fat percentage, and 36.3% of the relationship between late-night screen time and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2. Early morning screentime and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003eThe model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 30.4% of the relationship between early morning screen time and body fat percentage, and 37.7% of the relationship between early morning screen time and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Mediation analysis of quality of life on the relationship between the timing of screentime and body fat percentage and insomnia symptoms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEstimate (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eConfidence interval (95%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ez-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% mediation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eLate-night screen time and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eLate-night screen time and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e63.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eEarly morning screen time and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e69.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eEarly morning screen time and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003e3.4.3. Videogaming addiction and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003ehe model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 34.6% of the relationship between videogaming addiction and body fat percentage, and 36.3% of the relationship between videogaming addiction and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section3\"\u003e \u003ch2\u003e3.4.4. Social media addiction and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003eThe model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 17.4% of the relationship between social media addiction and body fat percentage, and 35.0% of the relationship between social media addiction and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section3\"\u003e \u003ch2\u003e3.4.5. Mobile phone addiction and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003eThe model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 10.6% of the relationship between mobile phone addiction and body fat percentage, and 34.0% of the relationship between mobile phone addiction and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Mediation analysis of quality of life on the relationship between screentime addiction and body fat percentage and insomnia symptoms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEstimate (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eConfidence interval (95%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ez-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% mediation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eVideogaming addiction and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eVideogaming addiction and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eSocial media addiction and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eSocial media addiction and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eMobile phone addiction and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e89.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eMobile phone addiction and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section3\"\u003e \u003ch2\u003e3.4.6. Weekday screen time and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003eThe model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 39.8% of the relationship between weekday screen time and body fat percentage, and 58.1% of the relationship between weekday screen time and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section3\"\u003e \u003ch2\u003e3.4.7. Weekend screentime and body fat percentage and insomnia symptoms\u003c/h2\u003e \u003cp\u003eThe model revealed statistically significant direct, indirect, and total effects. Quality of life partially mediated 38.0% of the relationship between weekend screen time and body fat percentage, and 51.4% of the relationship between weekend screen time and insomnia symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e, Mediation analysis of quality of life on the relationship between the quantity of screentime and body fat percentage and insomnia symptoms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEstimate (β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eConfidence interval (95%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ez-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% mediation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eWeekday screen time and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eWeekday screen time and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eWeekend screen time and body fat percentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eWeekend screen time and insomnia symptoms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e48.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec33\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Overview of findings\u003c/h2\u003e \u003cp\u003eThe findings from this study highlighted that late-night screentime, a higher quantity of screen time on a weekend, using phone as an alarm and videogaming addiction were shared determinants of a later chronotype, poor regulation of sleep onset (including irregular sleep habits, variability in sleep onset and increased insomnia symptoms), adiposity and obesity. These four dimensions of problematic screen time behaviour should therefore be considered when designing health-promoting interventions to improve bedtime routine, improve sleep regularity, reduce pre-sleep onset problems, and reduce adiposity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Late-night and bedroom screen time use as a shared determinant of poor sleep and adiposity\u003c/h2\u003e \u003cp\u003eScreen time in the 30 minutes before sleep onset was associated with a later chronotype and poor regulation of sleep onset (higher sleep onset variability, insomnia symptoms, poorer sleep habit), which would likely contribute to a shorter sleep duration. Evening screen time exposure has been associated with poor sleep duration across many age ranges including toddlers [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], young children [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e], adolescents [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] and young adults [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Adolescents with excessive text-messaging whilst in bed, post-bedtime, have been shown to have a shorter sleep duration, increased daytime sleepiness and poorer academic attainment [\u003cspan additionalcitationids=\"CR72 CR73\" citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. This is because late-night screen time has been shown to suppress melatonin production due to excessive blue-light exposure [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. The exposure contributes to circadian disruption and consequently poor sleep duration and daytime sleepiness [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn support of the current findings, late-night screen usage and excessive screen usage has been shown to be significantly associated with later chronotype [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], increased irregularity of sleep habits [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], increased insomnia symptoms [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e], increased onset latency [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] and increased sleep onset variability [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Longitudinal research has demonstrated that an excessive quantity of screen time and screen time addiction are predictors of increased insomnia symptoms [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e] and adiposity [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. The effect of screen time on sleep habits, chronotype or circadian misalignment, and sleep onset variability has not been examined longitudinally to assess directionality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Screen time addiction as a shared determinant of poor sleep and adiposity\u003c/h2\u003e \u003cp\u003eOur findings showed that videogaming addiction was a shared determinant of insomnia symptoms and adiposity. The HBSC study, a large multi-country study of adolescents, found that 13\u0026ndash;16 year-olds who were addicted to videogames had significantly later sleep onset, experienced insomnia symptoms, a longer sleep onset latency, a shorter sleep duration, and a larger social jetlag, than those not addicted to videogames [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Furthermore, a multi-analysis study investigating videogaming addiction across different ages within a school in the USA found that videogaming addictive tendencies can start in pre-adolescence [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The negative impact of videogaming addiction, however, was reported at 12-years, with adolescent\u0026rsquo;s ignoring responsibilities, reducing their sleep in order to play videogames, and neglecting physical activity and socialising outside [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdolescents with videogaming addiction also engage with late-night screen time, screen time in the bedroom and excessive screen time [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Screen time, videogaming, social media and mobile phones, have been designed to encourage digital addictiveness [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e], and some are even designed to target adolescents. For example, social media apps target adolescents with short-form videos which have been sown to be more addictive than long-form videos and encourage \u0026lsquo;doom-scrolling\u0026rsquo; in adolescents. Consequently, trying to address the addictive tendencies of screen time is difficult. Therefore, a combined approach to an intervention, targeting multiple screen time components may be beneficial for reducing screen time addiction, and improving sleep and obesity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003e4.4. The role of weekday/weekend variation in the relationship between screen time, sleep and adiposity\u003c/h2\u003e \u003cp\u003eThe screen time variables identified as determinants of sleep and adiposity showed weekday/weekend variation, with poor weekend screen time habits being more consistently reported as shared determinants of poor sleep and adiposity than weekday habits. For example, excessive screentime on a weekend was identified as a determinant of poor sleep, which implies weekday-to-weekend variation in screen time habits could potentially contribute to unhealthy lifestyles. Previous research has shown that there are variations in screen time activity patterns on a weekday and weekend, with adolescents using excessive screen time on an evening and on a weekend [\u003cspan additionalcitationids=\"CR89\" citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. Additionally, the variation in screen time on a weekend is more prominent in girls than boys [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e], and those from a lower SES and with caregivers of a lower education level [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. Researchers have discussed whether excessive screen time on a weekend occurs because it is being used as a parenting tool (reward system) [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e], occurs due to an absence or inconsistency in the presence of parental figures (for example, opportunistic if parents work shift patterns) [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e], occurs due to a lifestyle choice the adolescent makes to spend time with peers [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] and or whether it is learnt behaviour from the family [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Consequently, it has been suggested that interventions targeting weekend behaviour, using a family or parent-dyad setting and school-settings to target peer group social screen time behaviours.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Wellbeing as a mediator of the relationship between screen time, sleep and adiposity\u003c/h2\u003e \u003cp\u003eThe findings from this study indicated that the quality of life of the adolescent acts as a mediator of the relationships between the different components of screen time and insomnia symptoms and increased adiposity. Wellbeing mediates a larger proportion of the relationship between screen time and insomnia than between screen time and body fat percentage. Specifically, wellbeing accounted for over 50% of the association between weekday and weekend screen time and insomnia symptoms, compared with less than 40% for body fat percentage. A smaller mediating effect of wellbeing was observed for screen time addiction. For instance, wellbeing mediated 11% of the relationship between mobile phone addiction and body fat percentage, compared with 35% for insomnia symptoms. These findings suggest that late-night and early screen use, as well as screen time addiction, may indirectly impair sleep onset and increase adiposity in adolescents through the impact on wellbeing. Previous research has shown that high levels of screen time, particularly through devices like smartphones and tablets, can lead to difficulties in initiating sleep due to the effects of blue light exposure and cognitive overstimulation [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. This disruption in sleep onset can adversely affect adolescents' wellbeing, contributing to increased stress and emotional distress [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR97\" citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e], which may further exacerbate sedentary behaviours [\u003cspan additionalcitationids=\"CR100 CR101 CR102\" citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e] and unhealthy eating habits [\u003cspan additionalcitationids=\"CR105 CR106\" citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e], ultimately heightening the risk of obesity. The findings indicate that wellbeing may play a crucial role in the relationship between screen time and sleep and obesity and that future interventions would need to consider psychological and emotional factors when addressing sleep and obesity issues related to screen time [\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e]. Improving wellbeing in adolescents could help mitigate the adverse effects of screen usage on insomnia and obesity [\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e]. Wellbeing-focused intervention components, such as mindfulness and regular physical activity could also be combined with screen time modifications to maximise the impact of the intervention on adolescent sleep and reduction of obesity [\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e, \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec38\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Strengths and limitations\u003c/h2\u003e \u003cp\u003eThere were multiple strengths of this study, one being the successful recruitment of participants and family members to the study, with little missing data. This indicates interest from North-east Fife for studies examining behaviours, sleep and obesity across early to late adolescence. Recruitment to the TSWS was effective, reaching the target calculated as required to perform the intended regression analyses. This was the first study to measure multiple screen time variables (timing, quantity, location, and addiction) and investigate the association with objective and subjective poor sleep and objective adiposity in adolescents. The measurement tools used for assessing the quantity of screen time and screen time addiction were validated, however, the timing and location of screen time outcomes were assessed using novel questionnaires due to these variables not being routinely assessed. A strength in our measurement of screen timing was that specific questions were asked about the first and last 30 minutes of the day for weekday and weekend separately, which is not often reported on in the literature. The strength of this measurement is that it gives a specific behavioural target that could be easily modified in an intervention, as opposed to minimising the quantity of screen time overall, which has been highlighted as a barrier to previous screen time interventions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The wide range of variables collected as part of the TSWS questionnaires and actigraphy enabled the identification of specific individual behaviours that should be considered as targets for intervention, as opposed to using latent class analysis to identifying groups of behaviours or an umbrella of behaviours (for example screen time, rather than specific measures of screen time like addiction, timing of screen time, quantity, and location of use).\u003c/p\u003e \u003cp\u003eDue to the cross-sectional design, directionality of the associations cannot be determined. Moreover, adolescent participants and caregivers, whilst recruited from the community, were from one county of Scotland (North-east Fife) and consequently, the ethnicity and SES may not be representative of the whole of Scotland. A final limitation of the TSWS was that with seven actiwatches available for the data collection, the duration of data collection (February-May) meant some participants had more favourable weather and longer daylight hours than others which could have effected their activity levels and mood [\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":" \u003cp\u003eThe results from this study have indicated that multiple dimensions of problematic screen time behaviours, including late-night and early morning screen time, a higher quantity of screen time (weekend), using a phone in the bedroom overnight and as an screen time addiction, should be considered as shared determinants of higher adiposity, a later chronotype and poor regulation of sleep onset. Poor quality of life mediates the relationship between all screen time components with insomnia symptoms and higher adiposity. Further research should consider interventions modifying the late-night screen time usage, weekend usage and wellbeing to assess if small and manageable change to screen time behaviour has an effect on subsequent sleep and adiposity in adolescents.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement: \u003c/strong\u003eThe data that support the findings will be available in the University of St Andrews library repository at https://research-repository.st-andrews.ac.uk/ following an embargo (May 2028)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement:\u003c/strong\u003e This review was supported by the University of St Andrews as part of a doctoral research program\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u003c/strong\u003e There are no conflicts of interest\u003c/p\u003e\n\u003cp\u003eThe dataset(s) supporting the conclusions of this article will be available in the University of St Andrews repository in May 2028 (currently under embargo). Additional file 1 (A1) \u0026ndash; \u0026ldquo;TSWS \u0026ndash; BMC Medicine - Additional file.xlsx\u0026rdquo; Excel File showing the regression analyses coefficients.\u003c/p\u003e\n\n\n\n"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eStiglic, N. and R.M. Viner, Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open, 2019. \u003cstrong\u003e9\u003c/strong\u003e(1): p. e023191.\u003c/li\u003e\n \u003cli\u003eMoitra, P. and J. Madan, Impact of screen time during COVID-19 on eating habits, physical activity, sleep, and depression symptoms: A cross-sectional study in Indian adolescents. 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JAMA Netw Open, 2023. \u003cstrong\u003e6\u003c/strong\u003e(2): p. e2255466.\u003c/li\u003e\n \u003cli\u003eSeral-Cortes, M., et al., Mediterranean Diet, Screen-Time-Based Sedentary Behavior and Their Interaction Effect on Adiposity in European Adolescents: The HELENA Study. Nutrients, 2021. \u003cstrong\u003e13\u003c/strong\u003e(2).\u003c/li\u003e\n \u003cli\u003eJensen, M.L., et al., Television viewing and using screens while eating: Associations with dietary intake in children and adolescents. Appetite, 2022. \u003cstrong\u003e168\u003c/strong\u003e: p. 105670.\u003c/li\u003e\n \u003cli\u003eKracht, C.L., et al., Association of Night-Time Screen-Viewing with Adolescents\u0026apos; Diet, Sleep, Weight Status, and Adiposity. 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BMC primary care, 2022. \u003cstrong\u003e23\u003c/strong\u003e(1): p. 161.\u003c/li\u003e\n \u003cli\u003eZhang, P., et al., Effect of screen time intervention on obesity among children and adolescent: A meta-analysis of randomized controlled studies. Preventive Medicine, 2022. \u003cstrong\u003e157\u003c/strong\u003e: p. 107014.\u003c/li\u003e\n \u003cli\u003ede Lara Perez, B. and M. Delgado-Rios, Mindfulness-based programs for the prevention of childhood obesity: A systematic review. Appetite, 2022. \u003cstrong\u003e168\u003c/strong\u003e: p. 105725.\u003c/li\u003e\n \u003cli\u003eGodsey, J., The role of mindfulness based interventions in the treatment of obesity and eating disorders: An integrative review. Complementary Therapies in Medicine, 2013. \u003cstrong\u003e21\u003c/strong\u003e(4): p. 430-439.\u003c/li\u003e\n \u003cli\u003eWong, L.S., et al., Moderate-to-vigorous intensity physical activity during school hours in a representative sample of 10\u0026ndash;11-year-olds in Scotland. Journal of Science and Medicine in Sport, 2023. \u003cstrong\u003e26\u003c/strong\u003e(2): p. 120-124.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-global-and-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Global and Public Health](https://bmcglobalpublichealth.biomedcentral.com/)","snPcode":"44263","submissionUrl":"https://submission.springernature.com/new-submission/44263/3","title":"BMC Global and Public Health","twitterHandle":"@BMC_GPH","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"teenagers, insomnia, sleep disturbance, screens, mobile phones, overweight, adiposity","lastPublishedDoi":"10.21203/rs.3.rs-5386674/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5386674/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eThe overall quantity of screen time has been associated with short sleep duration and increasingly sedentary lifestyles, leading to adiposity. The aim of this research was to explore which components of screen time usage are shared determinants of poor sleep and higher adiposity in adolescents, using data from the Teen Sleep Well Study (TSWS).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study of adolescents aged 11-14-years in Fife, Scotland. Sleep was measured objectively using the Actigraph GT3X-BT and subjectively using validated questionnaires. Adiposity was assessed using body fat percentage and obesity was measured using body mass index percentile (BMIp). Four components of screen time were addressed using questionnaires: the timing of screen time (first and last 30 minutes of the day), quantity of screen time (weekday and weekend, via SCREENS-Q), location of screen time (use of a phone in bed, in the bedroom overnight, as an alarm), and screen time addiction (Videogaming Addiction Questionnaire (VGA-Q), Social Media Addiction Questionnaire (SMA-Q) and Mobile Phone Addiction Questionnaire (MPA-Q)). Descriptive statistics and statistical tests such as Pearson correlation tables, regression analyses and mediation analyses were used. Analyses were adjusted for the demographics of the child participant and caregiver and the wellbeing of the adolescent.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e62 participants (33F/29M, mean age 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 years, mean BMI percentile 60.3\u0026thinsp;\u0026plusmn;\u0026thinsp;32.1) completed the study and were part of the analysis. Excessive late-night and early-morning screen time usage, excessive screen time on a weekend, screen time addiction and using screens in the 30-minutes prior to sleep onset were shared determinants of higher adiposity, a later chronotype and poor sleep regulation outcomes: poor sleep habits, increased insomnia symptoms and increased sleep onset variability. Mediation analyses confirmed that wellbeing of the adolescent was a mediator of the relationship between screen time outcomes and insomnia symptoms and body fat percentage.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese screen time behaviours could be targeted in health-promoting interventions. Further research should assess longitudinal relationships between different components of screen time, sleep and adiposity, when adjusted for wellbeing in adolescents.\u003c/p\u003e","manuscriptTitle":"Late-night screen time and screen time addiction as shared determinants of poor sleep and obesity in adolescents aged 11-14 years in Scotland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-02 16:24:28","doi":"10.21203/rs.3.rs-5386674/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-14T17:02:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-07T11:36:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282698054753685029573558267559855717473","date":"2024-12-16T09:24:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-12T20:54:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303531040652423563271756176235454272294","date":"2024-12-11T02:57:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-08T11:25:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-11-07T15:34:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-04T10:54:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-04T09:46:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Global and Public Health","date":"2024-11-04T09:11:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-global-and-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Global and Public Health](https://bmcglobalpublichealth.biomedcentral.com/)","snPcode":"44263","submissionUrl":"https://submission.springernature.com/new-submission/44263/3","title":"BMC Global and Public Health","twitterHandle":"@BMC_GPH","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"044451fc-6c70-466d-919f-e19116a62efc","owner":[],"postedDate":"December 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-04-22T15:38:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-02 16:24:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5386674","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5386674","identity":"rs-5386674","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}