Time use and dimensions of healthy sleep: A cross-sectional study of Australian children and adults.

BACKGROUND: Sleep is increasingly recognized as a multidimensional construct that occurs within the 24-hour day. Despite advances in our understanding, studies continue to consider the relationship between sleep, sedentary time and physical activity separately, and not as part of the 24-hour day. AIMS: To determine the association between the 24-hour activity composition and dimensions of healthy sleep. METHODS: This study examined data on 1168 children (mean age 12years; 49% female) and 1360 adults (mean age 44years; 87% female) collected as part of the Child Health CheckPoint study. Participants were asked to wear a GENEActiv monitor (Activinsights, Cambs, UK) on their nondominant wrist for eight consecutive days to measure 24-hour time-use. Compositional data analysis was used to examine the association between time use (actigraphy-derived sleep duration, sedentary time, light physical activity and moderate-vigorous physical activity) and dimensions of healthy sleep. Healthy sleep was conceptualized in terms of continuity/efficiency, timing, alertness/sleepiness, satisfaction/quality, and regularity. Time allocations were also examined. RESULTS: The 24-hour activity composition was significantly associated with all objectively measured and self-report dimensions of healthy sleep in both children and adults. Allocating more time to sleep was associated with earlier sleep onsets, later sleep offsets, less efficient and more consistent sleep patterns for both children and adults. CONCLUSION: This study highlights the integral relationship between daily activities and dimensions of sleep. Considering sleep within the 24-hour day activity composition framework may help inform lifestyle decisions to improve sleep health.

The association between reallocations of time and health using compositional data analysis: a systematic scoping review with an interactive data exploration interface.

BACKGROUND: How time is allocated influences health. However, any increase in time allocated to one behaviour must be offset by a decrease in others. Recently, studies have used compositional data analysis (CoDA) to estimate the associations with health when reallocating time between different behaviours. The aim of this scoping review was to provide an overview of studies that have used CoDA to model how reallocating time between different time-use components is associated with health. METHODS: A systematic search of four electronic databases (MEDLINE, Embase, Scopus, SPORTDiscus) was conducted in October 2022. Studies were eligible if they used CoDA to examine the associations of time reallocations and health. Reallocations were considered between movement behaviours (sedentary behaviour (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) or various activities of daily living (screen time, work, household chores etc.). The review considered all populations, including clinical populations, as well as all health-related outcomes. RESULTS: One hundred and three studies were included. Adiposity was the most commonly studied health outcome (n = 41). Most studies (n = 75) reported reallocations amongst daily sleep, SB, LPA and MVPA. While other studies reported reallocations amongst sub-compositions of these (work MVPA vs. leisure MVPA), activity types determined by recall (screen time, household chores, passive transport etc.) or bouted behaviours (short vs. long bouts of SB). In general, when considering cross-sectional results, reallocating time to MVPA from any behaviour(s) was favourably associated with health and reallocating time away from MVPA to any behaviour(s) was unfavourably associated with health. Some beneficial associations were seen when reallocating time from SB to both LPA and sleep; however, the strength of the association was much lower than for any reallocations involving MVPA. However, there were many null findings. Notably, most of the longitudinal studies found no associations between reallocations of time and health. Some evidence also suggested the context of behaviours was important, with reallocations of leisure time toward MVPA having a stronger favourable association for health than reallocating work time towards MVPA. CONCLUSIONS: Evidence suggests that reallocating time towards MVPA from any behaviour(s) has the strongest favourable association with health, and reallocating time away from MVPA toward any behaviour(s) has the strongest unfavourable association with health. Future studies should use longitudinal and experimental study designs, and for a wider range of outcomes.

Changes in fitness and fatness in Australian schoolchildren during the summer holidays: fitness lost, fatness regained? A cohort study.

BACKGROUND: Emerging evidence suggests that children's fatness increases and fitness declines at a greater rate during the summer holiday period, compared with the school year. The aim of this study was to compare rates of change in fitness and fatness over the in-term and summer holiday periods among Australian schoolchildren. A secondary aim was to explore whether rates of change differed according to the child's sex, socio-economic status (SES), pubertal status and weight status. METHODS: Children (n = 381) initially in Grade 4 (age 9) were recruited for this 2-year longitudinal study. Fatness (% body fat, BMI z-score, waist-to-height ratio) and fitness (20-m shuttle run and standing broad jump) were measured at the start and end of two consecutive years. Rates of change were calculated for the two in-school periods (Grades 4 and 5) and for the summer holiday period. Rates of change in fatness and fitness between in-school and holiday periods were compared, and differences in rates of change according to sex, socio-economic status, and weight status were explored. RESULTS: During the holidays, percentage body fat increased at a greater rate (annualised rate of change [RoC]: +3.9 vs. Grade 4 and + 4.7 vs. Grade 5), and aerobic fitness declined at a greater rate (RoC - 4.7 vs. Grade 4 and - 4.4 vs. Grade 5), than during the in-school periods. There were no differences in rates of change for BMI z-score, waist-to-height ratio or standing broad jump. Body fatness increased faster in the holidays (relative to the in-school period) in children who are overweight and from low-SES families. Aerobic fitness declined more rapidly in the holidays in children who are overweight. CONCLUSION: This study highlights that during the summer holiday period, children experience greater increases in fatness and declines in fitness, with children who live with low-SES families and are overweight being more affected. The findings suggest the need for targeted interventions during this period to address these negative health trends. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry, identifier ACTRN12618002008202. Retrospectively registered on 14 December 2018.

Polygenic Risk Scores and the Risk of Childhood Overweight/Obesity in Association With the Consumption of Sweetened Beverages: A Population-Based Cohort Study.

Background: Sugar-sweetened beverage (SSB) and non-nutritive sweetened beverage (NNSB) consumption is associated with obesity and are targets for population-level dietary interventions. In children (<16 years), we evaluate whether SSB or NNSB consumption is associated with subsequent (2 years later) overweight and/or obesity, and the effect of consumption on subsequent overweight/obesity differs by BMI polygenic risk score (BMI-PRS). Methods: The nationally representative Longitudinal-Study-of-Australian-Children had biennial data collection from birth (n = 5107) until age 14/15 years (n = 3127). At age 11/12 years, a comprehensive biomedical assessment, including PRS assessment, was undertaken (n = 1422). Parent- or self-reported beverage consumption (SSBs: soft drinks, energy drinks, and/or juice; NNSBs: diet drinks) was measured as any/none over previous 24 hours. BMI-PRS was derived using published results (high PRS ≥75th percentile). At ages 4/5-14/15 children were classified as having obesity, overweight/obesity, or not having overweight/obesity using BMI z-score (CDC cut points). Results: SSB consumption had limited association with subsequent overweight/obesity. NNSB consumption was associated with ∼8% more children with subsequent overweight/obesity at most ages. In older children with high BMI-PRS, associations between NNSB consumption and subsequent overweight/obesity strengthened with age [at age 14-15 for high BMI-PRS, difference in proportion with overweight/obesity among NNSB consumers vs. nonconsumers = 0.38 (95% confidence interval: 0.22 to 0.55, p ≤ 0.001)]. There was limited association between SSB consumption and BMI-PRS. Conclusion: NNSB consumption was associated with increased risk of overweight/obesity for children with greater genetic risk at older ages (12-15 years). Focused intervention among children with high genetic risk could target NNSB consumption; however, reverse causality (children with genetic risk and/or high BMI consume more NNSBs) cannot be excluded.

Socioeconomic disadvantage and polygenic risk for high BMI magnify obesity risk across childhood: a longitudinal, population, cohort study.

BACKGROUND: Across the life course, socioeconomic disadvantage disproportionately afflicts those with genetic predispositions to inflammatory diseases. We describe how socioeconomic disadvantage and polygenic risk for high BMI magnify the risk of obesity across childhood, and using causal analyses, explore the hypothetical impact of intervening on socioeconomic disadvantage to reduce adolescent obesity. METHODS: Data were drawn from a nationally representative Australian birth cohort, with biennial data collection between 2004 and 2018 (research and ethics committee approved). We generated a polygenic risk score for BMI using published genome-wide association studies. We measured early-childhood disadvantage (age 2-3 years) with a neighbourhood census-based measure and a family-level composite of parent income, occupation, and education. We used generalised linear regression (Poisson-log link) to estimate the risk of overweight or obesity (BMI ≥85th percentile) at age 14-15 years for children with early-childhood disadvantage (quintiles 4-5) versus average (quintile 3) and least disadvantage (quintiles 1-2), for those with high and low polygenic risk separately. FINDINGS: For 1607 children (n=796 female, n=811 male; 31% of the original cohort [N=5107]), polygenic risk and disadvantage were both associated with overweight or obesity; effects of disadvantage were more marked as polygenic risk increased. Of children with polygenic risk higher than the median (n=805), 37% of children living in disadvantage at age 2-3 years had an overweight or obese BMI by adolescence, compared with 26% of those with least disadvantage. For genetically vulnerable children, causal analyses indicated that early neighbourhood intervention to lessen disadvantage (to quintile 1-2) would reduce risk of adolescent overweight or obesity by 23% (risk ratio 0·77; 95% CI 0·57-1·04); estimates for improving family environments were similar (0·59; 0·43-0·80). INTERPRETATION: Actions addressing socioeconomic disadvantage could mitigate polygenic risk for developing obesity. This study benefits from population-representative longitudinal data but is limited by sample size. FUNDING: Australian National Health and Medical Research Council.

Children's activity and diet behaviours in the summer holidays versus school year.

BACKGROUND: Evidence shows children gain more weight during the summer holidays versus the school year. OBJECTIVES: To examine within-child differences in activity and diet behaviours during the summer holidays versus the school year. METHODS: Children (mean age 9.4 years; 37% male) wore accelerometers (GENEActiv; n = 133), reported activities (Multimedia Activity Recall for Children and Adolescents; n = 133) and parents reported child diet (n = 133) at five timepoints over 2 years capturing school and summer holiday values. Mixed-effects models were used to compare school and summer holiday behaviours. RESULTS: Children spent less time in moderate- to vigorous-physical activity (-12 min/day; p = 0.001) and sleep (-12 min/day; p < 0.001) and more time sedentary (+27 min/day; p < 0.001) during summer holidays versus the school year. Screentime (+70 min/day; p < 0.001), domestic/social activities (+43 min/day; p = <0.001), self-care (+24 min/day; p < 0.001), passive transport (+22 min/day; p = 0.001) and quiet time (+16 min/day; p = 0.012) were higher during the summer holidays, compensating for less time in school-related activities (-164 min/day; p < 0.001). Diet quality was lower (-4 points; p < 0.001) and children consumed fewer serves of fruit (-0.4 serves; p < 0.001) during the summer holidays versus the school year. CONCLUSIONS: Children are displaying poorer activity and diet behaviours during the summer holidays, which may contribute to accelerated weight gain over the holiday period.

Branched-chain amino acids and sleep: a population-derived study of Australian children aged 11-12 years and their parents.

Micronutrients, particularly amino acids, are thought to play an important role in sleep regulation and maintenance. While tryptophan is a known predictor of sleep, less is known about branched-chain amino acids (BCAAs), which compete with tryptophan for transport across the blood-brain barrier. The aim of this study was to determine the association between BCAAs and actigraphy-derived sleep duration, timing and efficiency, and self-reported trouble sleeping. This study examined data on children and adults collected as part of the Child Health CheckPoint study. Linear mixed models, adjusted for geographic clustering, were used to determine the association between BCAAs and sleep characteristics. Complete-case analysis was conducted for 741 children aged 11-12 years old (51% females) and 941parents (87% mothers). While BCAAs were significantly associated with children's sleep duration, timing and self-reported trouble sleeping, no associations were observed in adults, in fully adjusted models. In children, higher levels of BCAAs are associated with shorter sleep duration, delayed sleep timing, and more frequent reports of trouble sleeping.

Results from the Australian 2022 Report Card on physical activity for children and young people.

Background: Past Physical Activity Report Cards have indicated a minority of Australian children and young people are sufficiently active. The purpose of this paper is to summarise grades across 10 indicators of the 2022 Australian Physical Activity Report Card, to assess physical activity behaviours and supports. Methods: A development team consisting of research experts synthesised and evaluated national and state level data to inform grades for each indicator. Data were drawn from nationally and state/territory representative datasets spanning 2016-2021. Results: Overall Physical Activity Levels and Screen Time were both assigned grades of D-, remaining the worst performing indicators. Australia's best performing indicator was Community and the Built Environment (A-), followed by Organised Sport and Physical Activity (B-). Remaining indicators were Family and Peers (C+), School (C+), Strategies and Investments (C-), Active Transport (D-) and Physical Fitness (D-). Active Play was unable to be graded, due to lack of consensus on a primary metric for this indicator and a lack of representative data. Conclusion: Evidence suggests that physical activity levels of Australian children remain consistently low, despite access to and availability of facilities and open spaces. There is a strong need for a National Physical Activity Plan to address this. The theme for the 2022 Australian Physical Activity Report Card, REBOOT! Reimagining physically active lives encourages us all to think more imaginatively about how we might engage all children and young people through diverse physical activity opportunities to be more active.

Top 10 International Priorities for Physical Fitness Research and Surveillance Among Children and Adolescents: A Twin-Panel Delphi Study.

BACKGROUND: The measurement of physical fitness has a history that dates back nearly 200 years. Recently, there has been an increase in international research and surveillance on physical fitness creating a need for setting international priorities that could help guide future efforts. OBJECTIVE: This study aimed to produce a list of the top 10 international priorities for research and surveillance on physical fitness among children and adolescents. METHODS: Using a twin-panel Delphi method, two independent panels consisting of 46 international experts were identified (panel 1 = 28, panel 2 = 18). The panel participants were asked to list up to five priorities for research or surveillance (round 1), and then rated the items from their own panel on a 5-point Likert scale of importance (round 2). In round 3, experts were asked to rate the priorities identified by the other panel. RESULTS: There was strong between-panel agreement (panel 1: rs = 0.76, p < 0.01; panel 2: rs = 0.77, p < 0.01) in the priorities identified. The list of the final top 10 priorities included (i) "conduct longitudinal studies to assess changes in fitness and associations with health". This was followed by (ii) "use fitness surveillance to inform decision making", and (iii) "implement regular and consistent international/national fitness surveys using common measures". CONCLUSIONS: The priorities identified in this study provide guidance for future international collaborations and research efforts on the physical fitness of children and adolescents over the next decade and beyond.

Parenting Styles and Their Associations With Children's Body Composition, Activity Patterns, Fitness, Diet, Health, and Academic Achievement.

Background: Evidence regarding the impact of parenting style on health and other outcomes is inconsistent and limited by measurement quality and type. This study will examine associations between parenting style and children's objectively assessed activity patterns, body composition, fitness, diet, health, and academic achievement. Methods: Two hundred fifty-five children (mean age: 9.4 years) from Adelaide, Australia, were included. Parenting style (items from Child Rearing Questionnaire and National Longitudinal Survey of Children and Youth to assess Authoritative, Authoritarian, Permissive, Disengaged parenting), diet, and health were proxy-reported by parents. Body composition, fitness, and 24 hour activity patterns were objectively measured, and children reported screen-time. Academic achievement was measured using standardized tests in reading and mathematics. Mixed models were used to regress parenting style against activity patterns, body composition, fitness, diet, health, and academic achievement, adjusted for age, sex, socioeconomic position, and pubertal stage. Results: Children with Disengaged parents had poorer activity patterns: less moderate to vigorous physical activity (standard mean difference [SMD] relative to grand mean = -0.23), light physical activity (SMD = -0.13) and sleep (SMD = -0.18), more sitting (SMD = 0.45), later bedtime (SMD = 0.18), lower overall energy expenditure (SMD = -0.23), and poorer overall self-reported health (SMD = -0.30). Children with Permissive parents had generally better activity patterns (SMD = 0.25-0.32). Children with Authoritative parents were more likely to meet dietary guidelines for fruit intake (SMD = 0.12). There were no associations for Authoritarian parenting style or for academic achievement, body composition, or fitness. Conclusions: Disengaged parenting was detrimental, while Permissive parenting was beneficial for activity patterns. As parenting styles may be malleable, future interventions may target Permissive parenting to improve children's activity patterns. Trial registration: Australia New Zealand Clinical Trials Registry, identifier ACTRN12618002008202. Retrospectively registered on 14 December 2018.

Multidimensional Sleep and Cardiometabolic Risk Factors for Type 2 Diabetes: Examining Self-Report and Objective Dimensions of Sleep.

PURPOSE: The purpose of the study was to determine the association between objective and self-report measures of sleep and cardiometabolic risk factors for type 2 diabetes. METHODS: This study examines data on Australian adults, collected as part of the Child Health CheckPoint study. Sleep was examined in terms of actigraphy-derived sleep duration, timing, efficiency and variability; and self-report trouble sleeping. Cardiometabolic risk factors for type 2 diabetes were examined in terms of body mass index and biomarkers of inflammation and dyslipidemia. Generalized estimating equations, adjusted for geographic clustering, were used to determine the association between measures of sleep and cardiometabolic risk factors. RESULTS: Complete case analysis was conducted for 1017 parents (87% mothers). Both objective and self-report measures of sleep were significantly but weakly associated with cardiometabolic risk factors. CONCLUSION: Both objective and self-report measures of sleep are significantly associated with cardiometabolic risk factors for type 2 diabetes. Self-report troubled sleep is associated with poorer cardiometabolic health, independent of actigraphy-derived sleep parameters.

Parent wellbeing, family screen time and socioeconomic status during early childhood predict physical activity of Aboriginal and Torres Strait Islander children at ages 8-13.

OBJECTIVES: Physical activity is holistically linked to culture and wellbeing among Aboriginal and Torres Strait Islander peoples, the First Nation Peoples of Australia. Socioecological correlates of high physical activity among Indigenous children include living in a remote area and low screen time but little is known about early life determinants of physical activity. This paper examines sociodemographic, family, community, cultural, parent social and emotional wellbeing determinants of physical activity among Aboriginal and Torres Strait Islander children. DESIGN: Longitudinal cohort study. METHODS: The Longitudinal Study of Indigenous Children, the largest First Nations child cohort study in the world, primarily collects data through parental report. Multiple logistic regression analyses examined Wave 1 (age 0-5 years) predictors of achieving ≥1 h/day of physical activity at Wave 9 (aged 8-13 years). RESULTS: Of the 1181 children, 596 (50.5 %) achieved ≥1 h of physical activity every day. Achieving ≥1 h/day of physical activity at Wave 9 was associated with the following Wave 1 determinants: high parent social and emotional wellbeing (resilience; adjusted odds ratio 1.87 (95 % confidence interval: 1.32-2.65)), living in remote (odds ratio 3.66 (2.42-5.54)), regional (odds ratio 2.98 (2.13-4.18)) or low socioeconomic areas (odds ratio 1.85 (1.08-3.17)), main source of family income not wages/salaries (odds ratio 0.66 (0.46-0.97)), and if families played electronic games (odds ratio 0.72 (0.55-0.94)). CONCLUSIONS: To achieve high physical activity levels among Aboriginal and Torres Strait Islander children, high parental culture specific social and emotional wellbeing and low family screen time in early life may compensate for apparently low socio-economic circumstances, including living in remote areas.

Does APOE ɛ4 Status Change How 24-Hour Time-Use Composition Is Associated with Cognitive Function? An Exploratory Analysis Among Middle-to-Older Adults.

BACKGROUND: The 24 h time-use composition of physical activity, sedentary behavior, and sleep is linked to cognitive function in adults and may contribute to future dementia risk. However, the impact of reallocating time between behaviors may differ depending on an individual's genetic dementia risk. OBJECTIVE: To explore if there is an interaction between 24 h time-use composition and genetic dementia risk in relation to cognitive function, and to simulate how time-reallocations are associated with cognitive function across different levels of genetic dementia risk. METHODS: Cross-sectional global cognition, executive function, genetic dementia risk (at least one apolipoprotein (APOE) ɛ4 allele versus none) and 7 days of 24 h accelerometry (average daily time-use composition of moderate-to-vigorous physical activity (MVPA), light physical activity, sedentary behavior, sleep) were collected from 82 adults (65.6±7.5 years, 49 females). Linear regression was used to explore the relationship between time-use composition and cognitive measures, testing for interaction between APOE ɛ4 status and time-use composition. The models were used to simulate time reallocations in both APOE ɛ4 status groups. RESULTS: The 24 h time-use composition was associated with global cognition (F = 2.4, p = 0.02) and executive function (F = 2.6, p = 0.01). For both measures, the association differed according to genetic risk (interactions p < 0.001). In both APOE groups, reallocating time to MVPA was beneficially associated with measures of cognitive function, but associations were larger among those with at least one APOE ɛ4 allele. CONCLUSION: Genetic dementia risk may impact the effectiveness of activity interventions. Increasing MVPA may provide greater benefits among those with higher genetic dementia risk.

Can adult polygenic scores improve prediction of body mass index in childhood?

BACKGROUND/OBJECTIVES: Modelling genetic pre-disposition may identify children at risk of obesity. However, most polygenic scores (PGSs) have been derived in adults, and lack validation during childhood. This study compared the utility of existing large-scale adult-derived PGSs to predict common anthropometric traits (body mass index (BMI), waist circumference, and body fat) in children and adults, and examined whether childhood BMI prediction could be improved by combining PGSs and non-genetic factors (maternal and earlier child BMI). SUBJECTS/METHODS: Participants (n = 1365 children, and n = 2094 adults made up of their parents) were drawn from the Longitudinal Study of Australian Children. Children were weighed and measured every two years from 0-1 to 12-13 years, and adults were measured or self-reported measurements were obtained concurrently (average analysed). Participants were genotyped from blood or oral samples, and PGSs were derived based on published genome-wide association studies. We used linear regression to compare the relative utility of these PGSs to predict their respective traits at different ages. RESULTS: BMI PGSs explained up to 12% of child BMI z-score variance in 10-13 year olds, compared with up to 15% in adults. PGSs for waist circumference and body fat explained less variance (up to 8%). An interaction between BMI PGSs and puberty (p = 0.001-0.002) suggests the effect of some variants may differ across the life course. Individual BMI measures across childhood predicted 10-60% of the variance in BMI at 12-13 years, and maternal BMI and BMI PGS each added 1-9% above this. CONCLUSION: Adult-derived PGSs for BMI, particularly those derived by modelling between-variant interactions, may be useful for predicting BMI during adolescence with similar accuracy to that obtained in adulthood. The level of precision presented here to predict BMI during childhood may be relevant to public health, but is likely to be less useful for individual clinical purposes.

Associations between meeting 24-hour movement guidelines and academic achievement in Australian primary school-aged children.

BACKGROUND: Few studies have investigated associations between academic achievement and meeting recommendations from the 24-hour (24-h) movement guidelines. The specific guidelines associated with the most benefit academic achievement are unknown. Utilizing both self-report and objective movement data, this study examined associations between academic achievement and meeting individual recommendations and combinations of recommendations from the 24-h movement guidelines (sleep, physical activity, and screen time). METHODS: Data from CheckPoint, a cross-sectional study nested between Waves 6 and 7 of the Longitudinal Study of Australian Children, were used. Movement behaviors were measured using 24-h wrist-worn accelerometry (GENEActiv (Activinsights, Kimbolton, UK)) and were self-reported by children using the Multimedia Activity Recall for Children and Adolescents. Academic achievement was measured using a nationally administered standardized test in literacy and numeracy. Analysis of covariance, with t tests with sequential Bonferroni adjustments, was used to compare academic achievement with all possible combinations of meeting recommendations, adjusting for demographic confounders. Two models were considered: guideline compliance assessed by self-report (n = 1270, mean age = 11.99 years, 52% males) and by accelerometry (for moderate-to-vigorous intensity physical activity (MVPA) and sleep)) and self-report (screen time) in combination (n = 927, mean age = 11.97 years, 52% males). RESULTS: Literacy achievement significantly differed based on self-report (F(7, 1258) = 3.08, p = 0.003) and accelerometer derived (F(7, 915) = 2.40, p = 0.02) guideline compliance. Numeracy achievement significantly differed based on self-report (F(7, 1258) = 2.92, p = 0.005) but not accelerometer derived guideline compliance (F(7, 915) = 0.80, p = 0.58). When assessed by self-report, children who met all guidelines (t(334) = -4.05, p = 0.0001) or met the screen time and sleep guidelines in combination (t(125) = -5.02, p < 0.001) had superior literacy achievement. Meeting the self-report MVPA guideline in any combination was associated with higher numeracy scores (p < 0.05). Post-hoc analyses showed no differences in academic achievement for any category of accelerometer derived guideline compliance. CONCLUSION: The findings suggest that limiting recreational screen time is important for literacy achievement and that encouraging compliance with the MVPA guideline is important for numeracy achievement.

Takeaway food, sugar-sweetened beverages and preclinical cardiometabolic phenotypes in children and adults.

AIMS: To investigate relationships between takeaway food and sugar-sweetened beverage (SSB) consumption with cardiometabolic phenotypes during childhood and mid-adulthood. METHOD: Design: Cross-sectional Child Health CheckPoint within the national population-representative Longitudinal Study of Australian Children. Participants: 1838 children (mean age 11.5 years; 49.1% female) and 1846 adults (mean age 43.7 years; 87.6% female). Exposures: Self-reported takeaway food and SSB consumption ('frequent': ≥ weekly). Outcomes: Functional (pulse wave velocity (PWV), blood pressure (BP)) and structural (carotid intima-media thickness, retinal microvascular calibre) preclinical cardiovascular phenotypes; lipids (total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides). Analysis: Linear regression (exposure: takeaway or SSB consumption, individually or together) adjusted for age, sex and socio-economic position; and mediation analysis for body mass index (BMI). RESULTS: Associations were small among children (standardized mean difference (SMD) ≤0.15). In adults, associations were stronger with functional, but not structural, cardiovascular phenotypes and lipids, particularly for frequent takeaway food consumption (e.g. PWV (0.20 m/s; 95% confidence interval (CI) 0.03 to 0.37); systolic (3.3 mmHg; 95% CI 1.3 to 5.3) and diastolic BP (1.4 mmHg; 95% CI 0.2 to 2.6); LDL (0.10 mmol/L; 95% CI 0.02 to 0.18); HDL (-0.14 mmol/L; 95% CI -0.19 to -0.10) and triglycerides (0.30 mmol/L; 95% CI 0.12 to 0.48)]. BMI mediated associations between takeaway food consumption and PWV, BP, HDL and TG (proportion of mediation 34% to 75%), while mediation effects were smaller for SSB consumption. CONCLUSIONS: Frequent takeaway food consumption in adults was associated with adverse blood lipids and vascular function (mainly via BMI). Lack of strong associations in children highlights opportunities for prevention.

"A 15% Reduction in Physical Inactivity Will Be Achieved in Australasia by 2030"-Audience Votes Negative in Online Debate.

The Australasian Society for Physical Activity aims to advance the science and practice of physical activity in Australia, New Zealand, the Pacific Islands, East Asia, South Asia, Southeast Asia, and Oceania. Fun, enjoyment, and cross-disciplinary discourse are important to ensure the network of physical activity professionals and our collective voice continues to grow. In May 2021, Australasian Society for Physical Activity's Early Career Network curated an engaging online Physical Activity Debate attended by 206 professionals. This commentary provides a synopsis of the debate and the central arguments presented by the affirmative and negatives teams. The authors describe the debate format and interactive design of the online Physical Activity Debate to provide insights for future online events that aim to boost interaction among physical activity professionals from various disciplines.

Are all MVPA minutes equal? Associations between MVPA characteristics, independent of duration, and childhood adiposity.

BACKGROUND: The inverse relationship between moderate-to-vigorous physical activity (MVPA) duration and childhood adiposity is well established. Less is known about how characteristics of MVPA accumulation may be associated with adiposity, independent of MVPA duration. This study aimed to investigate how the MVPA characteristics of children, other than duration (bout length, time of day, day-to-day consistency, intensity), were associated with adiposity. METHODS: Cross-sectional study of the Australian arm of the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) (participants: n = 424, age range 9-11, 44% male). Adiposity was determined by percent body fat via bioelectrical impedance. MVPA duration and characteristics (bout length, time of day, consistency, intensity) were derived from 7-day, 24-h accelerometry. Generalised estimating equations were used to examine the individual and multivariate associations between MVPA characteristics and adiposity. RESULTS: Univariate analyses showed that higher MVPA duration (ß range = - 0.26,-0.15), longer bouts of MVPA (ß range = 0.15,0.22) and higher MVPA intensity (ß range = - 0.20,-0.13) were all inversely associated with adiposity (all p < 0.05). When models were adjusted for MVPA duration, only MVPA intensity (ß range = - 0.16,-0.04) showed consistent significant associations with adiposity. CONCLUSIONS: Characteristics of MVPA other than duration and intensity appear to be unrelated to adiposity.