31st Jan 2024

Introduction: This study analysed the associations between sleep duration, sedentary behaviour (SB), and physical activity (PA) in children and adolescents. Understanding these associations is crucial due to their impact on overall health and well-being and the potential to develop interventions that promote healthier habits. Methods: Participants were 1231 subjects aged 10 to 18 years. Sleep was measured with the Pittsburgh Sleep Quality Index (PSQI), PA was measured with the International Physical Activity Questionnaire (IPAQ), and SB was estimated through a questionnaire assessing daily time (h) spent on personal computers for study (PCS) and leisure (PCL), tablets, smartphones (SPH), social networks (SN), watching television (TV), total screen time (TST), and sitting (ST). Participants were categorized into two groups based on sleep duration: “less than 8 hours” and “more than 8 hours” per day. Mann-Whitney U test was used to compare differences between two independent groups and Logistic Regression was employed to predict the probability of an event occurring. SB (+2h, -2h) and PA (active, inactive) variables were recoded into binary variables. All statistical analyses were performed in SPSS with a significance level set at 5% (P<0.05). Results: Participants with less than 8h of sleep per day spent less time watching TV (p=0.034) but more time on PCL (p=0.02), smartphones (p<0.001), social networks (p<0.001), and higher TST (p<0.001). For logistic regression, the overall model was statistically significant when compared to the null model, X2(8)=40.792, p<0.001. Those spending more than 2h using PCL (OR=1.429, p=0.004), SPH (OR=1.427, p=0.024), and SN (OR=1.349, p=0.035) are more likely to sleep less than 8h. No associations were found for PA. Conclusions: These findings suggest that SB are associated with sleep hours. Recommendations for improving sleep habits might involve moderating these behaviours. The Portuguese Foundation for Science and Technology (FCT) supported this work under the project UIDB04045/2020.

Background: only 28.8% of preschoolers in worldwide meet World Health Organization´s recommendations for sleep time. While this low prevalence could be associated with screen time (ST), this relation between sleep duration with physical activity (PA) and sedentary behavior (SB) remains inconsistent, especially on week and weekend days. Aim: to describe preschoolers´ profiles of time accumulated in PA, SB, and ST among short and adequate sleepers’ preschoolers during week and weekend days. Methods: 148 Brazilian preschoolers (53.6±8.9 months) participated in the study (77 females). PA and SB were measured with accelerometry (Actigraph®, wGT3-X), hip protocol, during seven consecutive days. Sleep duration and ST were parent-reported in a face-to-face interview. Comparative analyses were developed to verify differences between bedtime and wake-up time, light PA (LPA), moderate PA (MPA), vigorous PA (VPA), and moderate to vigorous PA (MVPA), SB and ST of short and adequate sleepers, on weekdays and weekends. The t-test was used for unpaired samples (p<0.05). Results: on weekdays, adequate sleepers slept earlier than short sleepers (08:25:55pm vs. 09:53:20pm), and there was no difference regarding wake-up time, or on weekends. On weekdays, adequate sleepers accumulated more time in SB (3344.2±271.3min vs. 2241.5±243.8min; p<0.001, Cohen's d= -0.92), VPA ( 139.6±16min vs. 94.4±69.9min; p0.05). Conclusion: adequate sleepers go to bed earlier on weekdays. Also, they spent more time in vigorous and moderate to vigorous physical activity during the week.

Introduction: preschool is an environment of opportunities for child development through the provision of pedagogical, social, and structural tools that can facilitate or restrict the practice of physical activity (PA). This can happen through pedagogical aspects of teachers, such as a practice that encourages PA, as well as training teachers focused on planning and applying PA, and also through the availability of adequate physical structure. This study verified the association of the built (AC) and perceived (AP) environment of preschool, pedagogical aspects of teachers (PP), and moderate to vigorous physical activity (MVPA) of preschoolers. Methods: One hundred forty-one preschoolers (67 boys, 4.4 ± 0.7 years) were evaluated. MVPA was assessed by accelerometry. The AC was evaluated objectively through an audit. The AP and the teachers’ pedagogical aspects were evaluated by face-to-face interviews (EPAO – Environment Assessment and Policy Observation). The structural equation method was used through univariate multiple regression to analyse the associations of AC, AP PP, and MVPA of preschool children. Results: For AC: there were positive associations between the number of spaces for games (b = 0.35, p < 0.001) and the number of resources available (b = 0.23, p = 0.004) and negative associations between the school's aesthetics (b = – 0.22, p = 0.002) and children's MVPA. For AP: there were positive associations between teachers' perception of their classrooms (b = 0.50, p = 0.012) and greater quantities of portable structures for PA (b = 0.26, p = 0.029), with and negative associations between the number of physical structures for PA (b = – 0.21, p = 0.019), and children's MVPA. Conclusions: Preschool AC and AP are positively related to preschoolers' MVPA. Strategies to increase the time spent on AFMS within preschool must consider the environment and factors interrelated to the context.

Introduction: when recommendations of movement behaviours are analysed as an unique composition, the three movement behaviours predict preschoolers’ executive function (EF) more strongly than in isolation. However, until now, it is not well-known how adhering to the different recommendations in isolation (physical activity (PA), sleep, or screen time) or in combination (PA + sleep, PA + screen time, sleep + screen time, or PA + sleep + screen time), are associated with EF in preschoolers. This study identified the most critical variables in an association network between combined compliance with 24-hour movement behaviours recommendations and EF in low-income preschoolers. Methods: eighty-three children (50.6% boys; 53.5 months of age) were assessed for physical activity (PA) screen time, sleep duration, sex, age, and EF. The adherence to the various combinations of movement behaviours was used for the analyses, and network analysis was performed to determine the most critical variables. Results: from the emerging network, it was observed that the variable with the greatest Expected Influence was the combined adherence to PA + sleep recommendations (1.964). Conclusions: the most sensitive network variables were combined adherence to PA and sleep recommendations. These results suggest that future interventions to improve EF in preschoolers should consider promoting these healthy behaviors in their strategies.

Introduction
Despite the publication of the World Health Organization (WHO) guidelines on movement behaviours (physical activity, sedentary behaviour, and sleep) for the Under 5s five years ago, there is limited evidence on compliance with the guidelines in a low-income Sub-Saharan African context. We examined the prevalence and correlates of meeting the total physical activity (TPA), sedentary behaviour, and sleep guidelines among 3- and 4-year-olds in Malawi.

Methods
Our study comprised 417 children (51.5% girls) aged 3-4 years from 24 urban and rural early childhood education and care (ECEC) centres in Malawi. Daily step-count was measured by hip-worn ActiGraph GT3X accelerometers, and children were classified as meeting the TPA guideline if they averaged at least 11,500 steps/day. Child’s restrained sitting, sedentary screentime, and sleep duration were reported by parents using a questionnaire. We determined the correlates of meeting the WHO guidelines using multivariable survey logistic regression.

Results
On average, children reportedly slept for 11.2 hours/day (standard error [SE]=0.1) and accumulated 24,269 steps/day (SE=391). The prevalence of meeting the TPA, restrained sitting and sedentary screen time, and sleep duration guidelines were 98.4% (95% confidence interval [CI]=96.0–99.4), 90.9% (95% CI=84.2–94.9), 79.4% (95% CI=71.2–85.7), and 90.6% (95% CI=87.3–93.2), respectively. Nearly three-quarters met the combined guideline (70.5%; 95% CI: 62.4–77.4). Girls had significantly higher odds of meeting the restrained sitting guideline (adjusted OR=3.59; 95% CI=1.36–9.48; p=0.012). Additionally, children from urban settings had significantly lower odds of meeting the restrained sitting, sedentary screentime, and sleep duration guidelines. We did not identify any correlates for meeting the TPA guideline.

Conclusions
We found exceptionally high prevalence meeting the WHO 24-hour movement behaviour guidelines in our sample of young children from a low-income Sub-Saharan African context, which is suggestive of a population in a pre-physical activity transition. Meeting the guidelines was influenced by factors such as residential settings and sex.

Introduction: By 2030, 23% of Brazilian children aged 5-9 years are projected to be living with obesity. Childhood obesity leads to insufficient physical activity (PA), with recommendation being of a minimum of 60-min of daily moderate-to-vigorous PA (MVPA), assessable using accelerometers. A notable limitation of accelerometer-assessed MVPA lies in its dependence on cut-offs. Studies have proposed metrics to monitor PA independently of cut-offs: i) the average acceleration (ACC), ii) the intensity gradient – IG; and iii) the minimum acceleration of a portion of the day (MX). Although studies have demonstrated associations between ACC, IG, and MX metrics and health, these were predominantly focused on eutrophic children, leaving a gap in understanding of PA patterns in children with obesity. This study aims to describe ACC, IG, and MX and investigate associations between obesity-related outcomes in children with obesity. Methods: Fifty-one children with obesity (23 girls; mean age 9.3±1.6 years) participated in this investigation. Wrist-worn accelerometers (ActiGraph GT3X) were used for 7-days, and raw acceleration in milli-gravity (mg) was obtained to calculate ACC, IG, and MX metrics. Descriptive analyses were conducted, along with linear regressions to establish associations between ACC and IG with body mass index (BMI), the percentage of the 95th percentile (%BMIp95), percentage of body fat (%BF) assessed using bioimpedance, and waist-to-hip ratio (WHR). Children’s average ACC and IG was 37.4±10.9 mg and -2.19±0.16, respectively. Both M60 (179.7±79.9) and M120 (110.4±34.4) fell below what is considered MVPA. IG was negatively associated with BMI (b= -12.74; -22.42 – -3.06), %BMIp95 (b= -58.2; -103.22 – -13.17), %BF (b= -20.99; -36.69 – -5.28), WHR (b=-0.12; -0.21 – -0.03) in models adjusted for sex, age, and fat-free mass. When ACC was included in the model, no independent associations were demonstrated for ACC and IG. Conclusion: Children with obesity exhibit low levels of MX metrics. The IG may play a crucial role in improving BMI, %BMIp95, %BF, and WHR in children with obesity. Metrics indicating the most active periods suggest that young children living with obesity need to increase their most active portion of the day to meet current PA guidelines

Introduction
Movement behaviours such as physical activity(PA), sedentary time(ST) and sleep (SL) are vital determinants for health. These health behaviours are likely to develop and form during early childhood. Across the research literature there is a dearth of data that explores young people’s movement behaviours considering ethnic and gender differences. The purpose of this research is to explore the levels of children’s accelerometer measured movement behaviours (physical activity, sleep and sedentary time) living in an ethnic diverse city.

Methods
Born in Bradford is a world leading birth cohort following the lives of 13,000 children from the ethnically diverse and economically deprived city of Bradford, UK. From 2017-2020, a sub-cohort of 2321 children, aged 7-10 years were invited and had parental consent to wear an Actilife triaxial accelerometer around their waist for 24 hours, 7 days a week. Accelerometers were fitted on children during school time. Evenson, Sadeh and Tudor-locke cut-points were applied to estimate average daily minutes moderate-to-vigorous physical activity (MVPA), ST, and SL. Simple descriptive statistics are presented here but inferential statistics will be presented at conference.

Results
A total of 1508 (65%) children (51.5% of Pakistani heritage(PH), 30.2% White British(WB) had valid data (2 weekdays and 1 weekend) to estimate MVPA, ST and SL values.

For MVPA, the mean daily minutes and 95% confidence intervals (CI) were; ALL=60.5 95%CI[59.2, 61.7], Girls=53.1 95%CI[51.7, 54.6], Boys=68.3 95%CI[66.4, 70.2], PH=55.9 95%CI[54.3, 57.6], WB=67.6 95%CI[65.2, 70.0].

For ST, ALL=450.9 95%CI[447.8, 454.0], Girls=453.6 95%CI[449.3, 457.8], Boys=450.9 95%CI[447.8, 454.0], PH=457.1 95%CI[452.8, 461.4], WB=437.1 95%CI[431.4, 442.7].

For SL, ALL=506.9 95%CI[502.6, 511.3], Girls=511.9 95%CI[506.5, 517.7]. Boys=501.6 95%CI[495.3, 508.1], PH=502.9 95%CI[496.7, 509.3], WB=514.6 95%CI[505.6, 523.6].

Conclusions.
Ethnic and gender differences were found in MVPA and ST values, but not in sleep. Further analysis is required to understand the complex relationship between movement behaviours, gender and ethnicity.

Introduction: Adolescence is a critical period in the which high fat accrual is associated with increased risk of overweight (OW) in adulthood. Adolescent fitness, a component of physical activity, also influences adult weight status. This study investigated longitudinally the links between adolescent fat accrual and fitness on subsequent adult fat mass. Methods: 76 adult males from the Saskatchewan Growth and Development Study (SGDS) (1964-2010), were assessed serially from 7-17 years of age and again at 40-50 years of age. A biological age (BA; years from peak height velocity (PHV=0)) was calculated. Skinfold measures were used to derive TBF (%) and trunk fat (Tfat, mm). OW was defined by age and sex specific %TBF cut-offs. A fitness score was calculated from measures of VO2max, strength and fitness performance. In adulthood, participants were put into tertiles using DXA derived percent total body fat (TBF) (G1≤20.6%; G2 >20.6%<27%; G3 ≥27%). ANOVA was used to find mean differences. Results: In adolescence, prior to PHV, all subjects were normal weight (NW); however, TBF in G3 was significantly higher than G1 and G2 from BA’s -4 to 0 (p 23.6; 100% in G2 and G3). Only G3 became OW before emerging adulthood. Adolescent TBF, Tfat and fitness score differed between groups (p<0.05). Tfat was significantly higher in G3 compared to G1 from BA’s -4 to +3 (p<0.05) and G1 and G2 had higher fitness scores (p<0.05). Conclusion: These findings suggest that 5 years around the attainment of PHV is a critical period for fat accrual and physical fitness development on adult weight status. Results also suggest that OW adults may be at heightened health risk due to concomitant gains in Tfat around PHV, even those classified as normal weight during adolescence.

Introduction: The diversity of the UK student population has increased dramatically in recent years. Whilst previous literature has identified differences in anthropometric outcomes between gender and ethnic groups, the extent to which these factors influence adverse cardiometabolic health outcomes in students is currently unclear. The present study therefore aimed to identify differences in the prevalence of adverse cardiometabolic health outcomes between gender and ethnic groups in UK university students.
Methods: Physiological testing was conducted across three years (2021-2023). Data from each year were combined to form a single cross-sectional dataset (n=1,299). Independent samples t-tests assessed differences between genders and one-way ANOVAs assessed differences between ethnic groups.
Results: Gender differences were present for all variables other than BMI and diastolic blood pressure (BP). The prevalence of overweight, obesity and hypertension were higher in males compared to females, whereas the prevalence of high waist circumference and high waist-to-hip ratio (WHR) was highest in females. The prevalence of poor glycaemic control was similar between males and females. Additionally, differences between ethnic groups were present for all variables other than hip circumference and diastolic BP (P<0.05). The prevalence of overweight, obesity, high waist circumference and impaired glycaemic control was highest in Black students, whereas the prevalence of high WHR and waist-to-height ratio (WHtR) was highest in Asian students. Finally, the prevalence of hypertension was highest in White students.
Conclusions: Overall, the results highlight differences in the prevalence of adverse cardiometabolic health outcomes in UK university students when separated by gender and ethnicity. These findings should be considered when developing strategies to promote healthy lifestyles in the context of higher education.

Background: Recently, the prevalence of adverse cardiometabolic health outcomes has increased in UK young adults. University students now make up a significant proportion of this population and their health-related behaviours are poorer than aged-matched normative data. Additionally, students experience negative changes in anthropometric outcomes during their university career, but the influence of university life on cardiometabolic health outcomes is currently unclear. This study aimed to determine the prevalence of adverse cardiometabolic health outcomes in undergraduate university students and assess differences between year groups. Methods: Data were collected across three years (2021-2023). Three independent cohorts of students’ (n=1,299) completed five physiological tests. One-way ANOVAs were used to assess differences between year groups. Results: 34.5% were classified as having overweight or obesity and 19.0% had a ‘high’ or ‘very high’ waist circumference. 11.0% had a high waist to hip ratio (WHR) while 25.5% had a high waist to height ratio (WHtR). 12.7% were classified as hypertensive and 3.3% had a [HbA1c] ≥42mmol/mol, indicating impaired glucose regulation. The prevalence of overweight/obesity, high waist circumference and hypertension was highest in 3rd year students whereas the prevalence of high WHR, WHtR and [HbA1c] was highest in 1st year students. Third years had higher diastolic blood pressure than 2nd years, and 1st years had higher HbA1c than 2nd and 3rd years (P<0.01). Conclusion: Overall, these results indicate that the proportion of students presenting with adverse outcomes of cardiometabolic health is greater than or comparable to age-matched normative data. These data provide an update on the prevalence of adverse cardiometabolic health outcomes in UK university students and demonstrate that differences exist between year groups. Further longitudinal data is required to assess changes across a typical undergraduate degree program.