Cost-effectiveness of reducing children's sedentary time and increasing physical activity at school: the Transform-Us! intervention.

BACKGROUND: Improving physical activity and reducing sedentary behavior represent important areas for intervention in childhood in order to reduce the burden of chronic disease related to obesity and physical inactivity in later life. This paper aims to determine the cost-effectiveness of a multi-arm primary school-based intervention to increase physical activity and/or reduce sedentary time in 8-9 year old children (Transform-Us!). METHODS: Modelled cost-utility analysis, using costs and effects from a cluster randomized controlled trial of a 30-month intervention that used pedagogical and environmental strategies to reduce and break up sedentary behaviour (SB-I), promote physical activity (PA-I), or a combined approach (PA + SB-I), compared to current practice. A validated multiple-cohort lifetable model (ACE-Obesity Policy model) estimated the obesity and physical activity-related health outcomes (measured as change in body mass index and change in metabolic equivalent task minutes respectively) and healthcare cost-savings over the cohort's lifetime from the public-payer perspective, assuming the intervention was delivered to all 8-9 year old children attending Australian Government primary schools. Sensitivity analyses tested the impact on cost-effectiveness of varying key input parameters, including maintenance of intervention effect assumptions. RESULTS: Cost-effectiveness results demonstrated that, when compared to control schools, the PA-I and SB-I intervention arms were "dominant", meaning that they resulted in net health benefits and healthcare cost-savings if the intervention effects were maintained. When the costs and effects of these intervention arms were extrapolated to the Australian population, results suggested significant potential as obesity prevention measures (PA-I: 60,780 HALYs saved (95% UI 15,007-109,413), healthcare cost-savings AUD641M (95% UI AUD165M-$1.1B); SB-I: 61,126 HALYs saved (95% UI 11,770 - 111,249), healthcare cost-savings AUD654M (95% UI AUD126M-1.2B)). The PA-I and SB-I interventions remained cost-effective in sensitivity analysis, assuming the full decay of intervention effect after 10 years. CONCLUSIONS: The PA-I and SB-I Transform-Us! intervention arms represent good value for money and could lead to health benefits and healthcare cost-savings arising from the prevention of chronic disease in later life if intervention effects are sustained. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN83725066). Australia and New Zealand Clinical Trials Registry Number (ACTRN12609000715279).

Prioritizing a research agenda on built environments and physical activity: a twin panel Delphi consensus process with researchers and knowledge users.

BACKGROUND: The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.g., policy makers, practitioners). METHODS: Between September 2022 and April 2023, a three-round, modified Delphi survey was conducted among two independent panels of international researchers (n = 38) and knowledge users (n = 23) to identify similarities and differences in perceived research priorities on the built environment and PA and generate twin 'top 10' lists of the most important research needs. RESULTS: From a broad range of self-identified issues, both panels ranked in common the most pressing research priorities including stronger study designs such as natural experiments, research that examines inequalities and inequities, establishing the cost effectiveness of interventions, safety and injuries related to engagement in active transportation (AT), and considerations for climate change and climate adaptation. Additional priorities identified by researchers included: implementation science, research that incorporates Indigenous perspectives, land-use policies, built environments that support active aging, and participatory research. Additional priorities identified by knowledge users included: built environments and PA among people living with disabilities and a need for national data on trip chaining, multi-modal travel, and non-work or school-related AT. CONCLUSIONS: Five common research priorities between the two groups emerged, including (1) to better understand causality, (2) interactions with the natural environment, (3) economic evaluations, (4) social disparities, and (5) preventable AT-related injuries. The findings may help set directions for future research, interdisciplinary and intersectoral collaborations, and funding opportunities.

Is level of implementation linked with intervention outcomes? Process evaluation of the TransformUs intervention to increase children's physical activity and reduce sedentary behaviour.

BACKGROUND: TransformUs was a four-arm school-based intervention to increase physical activity and reduce sedentary behaviour among primary school children. Pedagogical and environmental strategies targeted the classroom, school grounds and family setting. The aims of this study were to evaluate program fidelity, dose, appropriateness, satisfaction and sustainability, and associations between implementation level and outcomes among the three intervention arms. METHODS: At baseline, 18-months (mid-intervention) and 30-months (post-intervention), teachers, parents and children completed surveys, and children wore GT3X ActiGraph accelerometers for 8 days at each time point to determine physical activity and sedentary time. Implementation data were pooled across the three intervention groups and teachers were categorised by level of implementation: (i) 'Low' (< 33% delivered); (ii) 'Moderate' (33-67% delivered); and (iii) 'High' (> 67% delivered). Linear and logistic mixed models examined between group differences in implementation, and the association with children's physical activity and sedentary time outcomes. Qualitative survey data were analysed thematically. RESULTS: Among intervention recipients, 52% (n = 85) of teachers, 29% (n = 331) of parents and 92% (n = 407) of children completed baseline evaluation surveys. At 18-months, teachers delivered on average 70% of the key messages, 65% set active/standing homework, 30% reported delivering > 1 standing lesson/day, and 56% delivered active breaks per day. The majority of teachers (96%) made activity/sports equipment available during recess and lunch, and also used this equipment in class (81%). Fidelity and dose of key messages and active homework reduced over time, whilst fidelity of standing lessons, active breaks and equipment use increased. TransformUs was deemed appropriate for the school setting and positively received. Implementation level and child behavioural outcomes were not associated. Integration of TransformUs into existing practices, children's enjoyment, and teachers' awareness of program benefits all facilitated delivery and sustainability. CONCLUSIONS: This study demonstrated that intervention dose and fidelity increased over time, and that children's enjoyment, senior school leadership and effective integration of interventions into school practices facilitated improved intervention delivery and sustainability. Teacher implementation level and child behavioural outcomes were unrelated, suggesting intervention efficacy was achieved irrespective of implementation variability. The potential translatability of TransformUs into practice contexts may therefore be increased. Findings have informed scale-up of TransformUs across Victoria, Australia. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. Registered 19 August 2009. Available at: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=308387&isReview=true.

Effect of commercial wearables and digital behaviour change resources on the physical activity of adolescents attending schools in socio-economically disadvantaged areas: the RAW-PA cluster-randomised controlled trial.

BACKGROUND: There has been increasing interest in using wearable activity trackers to promote physical activity in youth. This study examined the short- and longer-term effects of a wearable activity tracker combined with digital behaviour change resources on the physical activity of adolescents attending schools in socio-economically disadvantaged areas. METHODS: The Raising Awareness of Physical Activity (RAW-PA) Study was a 12-week, multicomponent intervention that combined a Fitbit Flex (and accompanying app), and online digital behaviour change resources and weekly challenges delivered via Facebook. RAW-PA was evaluated using a cluster-randomised controlled trial with 275 adolescents (50.2% female; 13.7 ± 0.4 years) from 18 Melbourne secondary schools (intervention n = 9; wait-list control group n = 9). The primary outcome was moderate- to vigorous-intensity physical activity (MVPA), measured using hip-worn ActiGraph accelerometers. The secondary outcome was self-reported physical activity. Data were collected at baseline, 12-weeks (immediately post-intervention), and 6-months post-intervention (follow-up). Multilevel models were used to determine the effects of the intervention on daily MVPA over time, adjusting for covariates. RESULTS: No significant differences were observed between intervention and wait-list control adolescents' device-assessed MVPA immediately post-intervention. At 6-months post-intervention, adolescents in the intervention group engaged in 5 min (95% CI: - 9.1 to - 1.0) less MVPA per day than those in the wait-list control group. Males in the intervention group engaged in 11 min (95% CI: - 17.6 to - 4.5) less MVPA than males in the wait-list control group at 6-months post-intervention. No significant differences were observed for females at either time point. For self-reported physical activity, no significant effects were found at 12-weeks and 6-months post-intervention. CONCLUSIONS: Combining a wearable activity tracker with digital behaviour change resources and weekly challenges did not increase inactive adolescents' accelerometer-derived and self-reported physical activity levels immediately post-intervention. This contrasts previous research that has suggested wearable activity tracker may increase youth physical activity levels in the short-term. Lower engagement in MVPA 6-months post-intervention was observed for males but not for females, though it is unclear why this finding was observed. The results suggest wearable activity trackers, in combination with supporting materials, may not be effective for increasing physical activity levels in adolescents. TRIAL REGISTRATION: ACTRN12616000899448 . Australian and New Zealand Clinical Trials Registry. Registered 7 July 2016.

Is replacing sedentary time with bouts of physical activity associated with inflammatory biomarkers in children?

This study aimed to investigate the theoretical impact of reallocating a specific amount of sedentary time with an equal amount of (a) total and (b) ≥1-minute bout-accumulated time spent in different activity intensities, on inflammatory biomarkers in 8- to 9-year-old children. Accelerometry and inflammatory biomarker baseline data from the Transform-Us! Study (complete cases n = 149) were utilized. Isotemporal linear models with the Gaussian distribution and identity link functions were used to assess associations between the activity replacements and seven individual inflammatory biomarkers, including C-reactive protein (CRP), and Interleukin (IL)-2, IL-6, IL-8, and IL-10, as well as combined inflammatory and pro-inflammatory composite scores. Eighty-five percent of children met physical activity recommendations. Replacing 10 minutes of sedentary time per day with VPA, regardless of how this was accumulated, was beneficially associated with CRP and both combined composite scores. In contrast, replacing 10 min/day of sedentary time with ≥ 1-minute MPA bouts was detrimentally associated with CRP and the inflammatory composite score. Substitutions with other activity intensities were not significantly associated with any individual inflammatory biomarkers, or combined inflammatory and pro-inflammatory composite scores. In healthy and active school-aged children, evidence of the theoretical impact of replacing sedentary time with physical activity, regardless of intensity or accumulation, on markers of systemic inflammation was limited. Longitudinal research is needed to investigate the long-term impacts of reallocating sedentary time with physical activity, and particularly VPA, for inflammatory biomarkers in children, including those with increased risk of inflammation.

Changes in volume and bouts of physical activity and sedentary time across early childhood: a longitudinal study.

BACKGROUND: Understanding changes in physical activity and sedentary time (SED) during early childhood may provide insights into how to effectively promote a healthy start to life. This study examined changes in total volume and bouts of SED, light- (LPA), and moderate- to vigorous-intensity physical activity (MVPA) across early childhood, and explored differences in change between boys and girls. METHODS: Data were drawn from 330 children participating in the Melbourne InFANT Program, collected between 2008 and 2013 and analysed in 2017. Children's physical activity and SED were assessed for at least 7 days at each timepoint using ActiGraph GT1M accelerometers at 19 months, 3.5 and 5 years of age. Total volume of SED (≤100 counts per minute [CPM]), LPA (101-1680 CPM) and MVPA (≥1681 CPM) were expressed as a percentage of wear time, and the frequency (number of bouts/day) and duration (mins/bout) of SED, LPA and MVPA bouts ≥1 min were calculated at each time point. Multilevel models with random intercepts and slopes were used to examine changes in total volume and bouts of SED, LPA and MVPA for boys and girls. RESULTS: Compared to aged 19 months, children's total volume of SED and LPA decreased at 3.5 and 5 years old, while MVPA increased. The frequency of SED bouts at 3.5 and 5 years was greater than at 19 months, but the duration was shorter. Additionally, the frequency and duration of LPA bouts was lower and MVPA bout frequency and duration was greater at 3.5 and 5 years. In general, there was no evidence of sex differences in trajectories of children's physical activity and SED. However, variations in trajectory were observed at the individual child level. CONCLUSIONS: Children's total volume and bouts of SED, LPA and MVPA change across early childhood, mostly in a favourable direction. Trajectories appear to be similar for boys and girls. Investigation of individual variation in trajectories is likely to provide greater insight into associations between physical activity and future health and behavioural outcomes.

Compensatory changes in physical activity and sedentary time in children and adolescents with cystic fibrosis.

Physical activity (PA) is a key element in Cystic Fibrosis (CF) treatment strategies, yet little is known as to whether activity compensation occurs. This study examined whether PA and/or sedentary time on one day were temporally associated with time spent in these intensities the following day in youth with CF. Time spent sedentary and in different PA intensities were objectively-measured for seven consecutive days in 50 youth (22 boys; 12.0 ± 2.7 years); 25 with mild-to-moderate CF and 25 age- and sex-matched controls. Multilevel analyses (day and child) were conducted using generalised linear latent and mixed models. On any given day, every additional 10 minutes spent in sedentary time or moderate-to-vigorous physical activity (MVPA) were associated with 1.9 (95%CI: -3.6 to -1.2) and 12.4 (95%CI: -22.1 to -2.9) minutes less sedentary time the following day, respectively. These temporal associations were also observed when split by group (3.1 vs. 1.9 minutes for healthy and CF, respectively). These findings indicate that youth do not compensate their PA, irrespective of disease status, between days, but may compensate their sedentary time between days. Experimental studies are warranted to fully elucidate whether compensatory responses to PA and sedentary time occur, which is fundamental for informing PA promotion strategies.

Higher circulating androgens and higher physical activity levels are associated with less central adiposity and lower risk of cardiovascular death in older men.

OBJECTIVE: Low endogenous sex hormones and low physical activity (PA) levels have been associated with CVD risk. Whether these interact to influence CVD outcomes remains unclear. We assessed whether sex hormone concentrations and PA were additively associated with lower central adiposity and CVD risk. PATIENTS: 3351 community-dwelling men, mean age 77 years. MEASUREMENTS: Baseline testosterone (T), dihydrotestosterone (DHT) and oestradiol (E2) were assayed. Levels of PA were ascertained by questionnaire. Men were stratified using median splits into high hormone + high PA (H/H), high hormone + low PA (H/L); low hormone + high PA (L/H) and low hormone + low PA (L/L) groups. RESULTS: A total of 865 CVD events and 499 CVD deaths occurred during 10-year mean follow-up. Men with higher T, DHT or SHBG and higher PA had the lowest BMI, waist circumference and risk of metabolic syndrome. Men with higher T had the lowest risk of incident CVD events, irrespective of PA level. Men with higher T or DHT and higher PA had the lowest risk of dying from CVD (eg, hazard ratios for T/PA H/H 0.76 P = 0.031; H/L 0.85 P = 0.222; L/H 0.80 P = 0.075; L/L 1.00). CONCLUSION: Higher circulating androgens and higher PA were associated with less central adiposity at baseline and fewer CVD deaths during follow-up. These findings are consistent with a potential additive effect of androgens and PA on cardiometabolic outcomes in older men.

Intervertebral disc status is associated with vertebral marrow adipose tissue and muscular endurance.

PURPOSE: Low back pain is a major public health issue. Identifying factors associated with better intervertebral disc (IVD) characteristics gives insight into IVD metabolism and highlights intervention targets for improvement of IVD health. This cross-sectional study investigates whether IVD T2-relaxation time on magnetic resonance imaging (MRI) is associated with vertebral fat fraction (VFF; to quantify marrow adipose tissue), trunk muscle cross-sectional area (CSA), muscle function and physical activity (PA). METHODS: Seventy-nine healthy subjects (35 males, 44 females) without history of spinal disease were included. Lumbar IVDs T2-relaxation time, lumbar VFF and CSA of multifidus, erector spinae, quadratus lumborum, and psoas muscles were quantified via MRI. Isometric trunk flexion and extension endurance times as well as habitual PA levels and exposure to occupational spine risk factors were documented. Pearson-partial correlations adjusted for anthropometric differences by controlling for vertebral body height. RESULTS: Higher IVD T2-time correlated with: (a) lower VFF (r = - 0.27, p < 0.05), (b) greater trunk extensor muscle endurance (r = 0.37, p < 0.01), and (c) greater trunk flexor muscle endurance (r = 0.30, p < 0.01) but not with muscle CSA. Lower VFF also correlated with greater extensor muscle endurance (r = - 0.26, p < 0.05) and habitual PA (MET-mins per week) (r = - 0.24, p < 0.05). CONCLUSION: This is the first study to show that better IVD hydration is associated with lower VFF and that greater physical activity is associated with favourable levels of vertebral marrow adipose tissue in young healthy individuals. Reduced vertebral marrow adipose tissue may specifically improve IVD hydration via improved nutrient supply. These slides can be retrieved under Electronic Supplementary Material.

Specific Modulation of Vertebral Marrow Adipose Tissue by Physical Activity.

Marrow adipose tissue (MAT) accumulation with normal aging impacts the bone, hemopoiesis, and metabolic pathways. We investigated whether exercise was associated with lower MAT, as measured by vertebral marrow fat fraction (VFF) on magnetic resonance imaging. A total of 101 healthy individuals (54 females) aged 25 to 35 years without spine or bone disease but with distinct exercise histories were studied. Long-distance runners (67 km/wk, n = 25) exhibited lower mean lumbar VFF (27.9% [8.6%] versus 33.5% [6.0%]; p = 0.0048) than non-sporting referents (n = 24). In habitual joggers (28 km/wk, n = 30), mean lumbar VFF was 31.3% (9.0%) (p = 0.22 versus referents) and 6.0 percentage points lower than referents at vertebrae T10 , T11 , and T12 (p ≤ 0.023). High-volume road cycling (275 km/wk, n = 22) did not impact VFF. 3D accelerations corresponding to faster walking, slow jogging, and high-impact activities correlated with lower VFF, whereas low-impact activities and sedentary time correlated with higher mean lumbar VFF (all p ≤ 0.05). Given an estimated adipose bone marrow conversion of 7% per decade of life, long distance runners, with 5.6 percentage points lower VFF, showed an estimated 8-year younger vertebral marrow adipose tissue phenotype. Regression analysis showed a 0.7 percentage point reduction in mean lumbar VFF with every 9.4 km/wk run (p = 0.002). This study presents the first evidence in humans or animals that specific volumes and types of exercise may influence the age-determined adipose marrow conversion and result in low MAT. These results identify a potentially modifiable risk factor for prevalent chronic conditions related to bone metabolism, hemopoietic production, and other metabolic functions with potential global health applications. © 2017 American Society for Bone and Mineral Research.

Physical Activity and Sedentary Time Patterns in Children and Adolescents With Cystic Fibrosis and Age- and Sex-Matched Healthy Controls.

BACKGROUND: Regular physical activity (PA) is increasingly recognized as important in the care of patients with cystic fibrosis (CF), but there is a dearth of evidence regarding physical activity levels or how these are accrued in those with CF. METHODS: PA was measured by a hip-worn accelerometer for 7 consecutive days in 18 children [10 boys; 12.4 (2.8) y] with mild to moderate CF and 18 age- and sex-matched controls [10 boys; 12.5 (2.7) y]. RESULTS: Both children with CF and healthy children demonstrated similar physical activity levels and patterns of accumulation across the intensity spectrum, with higher levels of PA during weekdays in both groups. Forced expiratory volume in 1 second was predicted by high light PA in children with CF compared with low light PA in healthy children. CONCLUSION: These findings highlight weekends and light PA as areas warranting further research for the development of effective intervention strategies to increase PA in the youth CF population.

Temporal and bidirectional associations between physical activity and sleep in primary school-aged children.

The directionality of the relationship between children's physical activity and sleep is unclear. This study examined the temporal and bidirectional associations between objectively measured physical activity, energy expenditure, and sleep in primary school-aged children. A subgroup of children (n = 65, aged 8-11 years) from the Fitness, Activity and Skills Testing Study conducted in Melbourne, Australia, had their sleep and physical activity assessed using the SenseWear Pro Armband for 8 consecutive days. Outcome measures included time spent in light-intensity physical activiy (LPA), moderate- to vigorous-intensity physical activity (MVPA), activity energy expenditure (AEE), time in bed, total sleep time, and sleep efficiency. Multilevel analyses were conducted using generalized linear latent mixed models to determine whether physical activity on 1 day was associated with sleep outcomes that night, and whether sleep during 1 night was associated with physical activity the following day. No significant associations were observed between time in bed, total sleep time, and sleep efficiency with LPA, MVPA, and AEE in either direction. This study found no temporal or bidirectional associations between objectively measured physical activity, AEE, and sleep. Future research is needed to understand other sleep dimensions that may impact on or be influenced by physical activity to provide potential intervention targets to improve these outcomes.

Criterion validity of the activPAL™ and ActiGraph for assessing children's sitting and standing time in a school classroom setting.

BACKGROUND: Few studies have investigated the accuracy of the ActiGraph (AG) GTX3 accelerometer for assessing children's sitting and standing time. The activPAL (aP) has an inclinometer function that enables it to distinguish between sitting/lying and standing; however, its accuracy for assessing sitting and standing in older children is unknown. This study validated the accuracy of these devices for estimating sitting and standing time in a school classroom against a criterion measure of direct observation (DO). FINDINGS: Forty children in grades 5-7 wore both devices while being video recorded during two school lessons. AG and aP data were simultaneously collected in 15-s epochs. Individual participant DO and aP data were recorded as total time spent sitting/lying, standing and stepping. AG data were converted into time spent sitting and standing using previously established cut-points. Compared with DO, the aP underestimated sitting time (mean bias = -1.9 min, 95 % LoA = -8.9 to 5.2 min) and overestimated standing time (mean bias = 1.8 min, 95% LoA = -9.6 to 13.3 min). The best-performing AG cut-point across both sitting and standing (<75 counts/15 s) was more accurate than the aP, underestimating sitting time (mean bias = -0.8 min, 95 % LoA = -10.5 to 9.9 min) and standing time (mean bias = -0.4 min, 95% LoA = -9.8 to 9.1 min), but was less precise as evidenced by wider LoAs and poorer correlations with DO (sitting r = 0.86 aP vs 0.80 AG; standing r = 0.78 aP vs 0.60 AG). CONCLUSIONS: The aP demonstrated good accuracy and precision for assessing free-living sitting and standing time in classroom settings. The AG was most accurate using a cut-point of < 75 counts/15 s. Further studies should validate the monitors in settings with greater inter- and intra-individual variation in movement patterns.

Too hot to move? Objectively assessed seasonal changes in Australian children's physical activity.

BACKGROUND: Seasonal variations may influence children's physical activity patterns. The aim of this study was to examine how children's objectively-measured physical activity differed across seasons, and whether different seasonal patterns were observed for boys and girls. METHODS: Three hundred and twenty-six children aged 8-11 years from nine primary schools in Melbourne, Australia, participated in the study. Physical activity was measured every 15-s using hip-mounted GT3X+ ActiGraph accelerometers for seven consecutive days in the Winter (n = 249), Spring (n = 221), Summer (n = 174) and Autumn (n = 152) school terms. Time spent in moderate (MPA), vigorous (VPA) and moderate- to vigorous-intensity physical activity (MVPA) at each time point was derived using age-specific cut-points. Meteorological data (maximum temperature, precipitation, daylight hours) were obtained daily during each season. Longitudinal data were analysed using multilevel analyses, adjusted for age, sex, accelerometer wear time, number of valid days, and meteorological variables. RESULTS: Compared to Winter, children engaged in significantly less MPA (-5.0 min) and MVPA (-7.8 min) in Summer. Girls engaged in less MVPA in Spring (-18 min) and Summer (-9.2 min) and more MVPA in Autumn (9.9 min) compared to Winter. Significant changes in MPA and VPA bout frequency and duration were also observed. Significant decreases in VPA bout frequency (3.4 bouts) and duration (2.6 min) were observed for girls in Spring compared to Winter. No significant seasonal changes were observed for boys for all intensities and physical activity accumulation. CONCLUSIONS: Physical activity decreased in Summer compared to Winter, contrasting previous research that typically reports that children are most active in summer. Greater fluctuations were observed for girls' activity levels. In addition, girls' activity duration and bouts appeared to be more susceptible to seasonal changes compared to boys. The results suggest that strategies to promote physical activity may be needed in Australia during the hot summer months, particularly for girls.

Associations of Low- and High-Intensity Light Activity with Cardiometabolic Biomarkers.

PURPOSE: Light-intensity physical activity (LIPA) accounts for much of adults' waking hours (≈40%) and substantially contributes to overall daily energy expenditure. Encompassing activity behaviors of low intensity (standing with little movement) to those of higher intensity (slow walking), LIPA is ubiquitous, yet little is known about how associations with health may vary depending on its intensity. We examined the associations of objectively assessed LIPA (categorized as either low LIPA [LLPA] or high LIPA [HLPA]) and moderate- to vigorous-intensity activity with cardiometabolic risk biomarkers. METHODS: Cardiometabolic biomarkers were measured in 4614 US adults (47 ± 17 yr) who participated in the 2003-2004 and 2005-2006 National Health and Nutrition Examination Survey cycles. Multiple linear regression analyses examined the associations of three accelerometer-derived physical activity (SD increment per day) intensity categories (LLPA, 100-761 counts per minute; HLPA, 762-1951 counts per minute; moderate-intensity physical activity [MPA], 1952-5724 counts per minute; vigorous-intensity physical activity [VPA], ≥5725 counts per minute) with cardiometabolic biomarkers, adjusting for potential sociodemographic, behavioral, and medical confounders. RESULTS: All intensities of physical activity were beneficially associated with waist circumference, C-reactive protein, triglycerides, fasting insulin, ß-cell function, and insulin sensitivity (P < 0.05); only some activity intensities showed significant associations with systolic blood pressure (LLPA), body mass index, HDL cholesterol, fasting glucose, and 2-h plasma glucose (HLPA, MPA, and VPA). Generally, effect size increased with intensity of physical activity. Overall, further adjustment for waist circumference attenuated associations with MPA and VPA to a greater extent than associations with LLPA and HLPA. CONCLUSIONS: The cross-sectional findings provide novel evidence for the potential benefits of increasing both LLPA and HLPA. They further reinforce the established importance of moderate- to vigorous-intensity activity, the mainstay of public health recommendations.

Early childhood predictors of toddlers' physical activity: longitudinal findings from the Melbourne InFANT Program.

BACKGROUND: Young children are at risk of not meeting physical activity recommendations. Identifying factors from the first year of life which influence toddlers' physical activity levels may help to develop targeted intervention strategies. The purpose of this study was to examine early childhood predictors of toddlers' physical activity across the domains of maternal beliefs and behaviours, infant behaviours and the home environment. METHODS: Data from 206 toddlers (53% male) participating in the Melbourne InFANT Program were collected in 2008-2010 and analysed in 2012. Mothers completed a survey of physical activity predictors when their child was 4- (T1) and 9- months old (T2). Physical activity was assessed by ActiGraph GT1M accelerometers at 19- months (T3) of age. RESULTS: One infant behaviour at T1 and one maternal belief and two infant behaviours at T2 showed associations with physical activity at T3 and were included in multivariate analyses. After adjusting for the age at which the child started walking and maternal education, the time spent with babies of a similar age at 4-months (ß = 0.06, 95% CI [0.02, 0.10]) and the time spent being physically active with their mother at 9-months (ß = 0.06, 95% CI [0.01, 0.12]) predicted children's physical activity at 19-months of age. CONCLUSIONS: Promotion of peer-interactions and maternal-child co-participation in physical activity could serve as a health promotion strategy to increase physical activity in young children. Future research is required to identify other early life predictors not assessed in this study and to examine whether these factors predict physical activity in later life stages.

Light-intensity physical activity and cardiometabolic biomarkers in US adolescents.

BACKGROUND: The minimal physical activity intensity that would confer health benefits among adolescents is unknown. The purpose of this study was to examine the associations of accelerometer-derived light-intensity (split into low and high) physical activity, and moderate- to vigorous-intensity physical activity with cardiometabolic biomarkers in a large population-based sample. METHODS: The study is based on 1,731 adolescents, aged 12-19 years from the 2003/04 and 2005/06 National Health and Nutrition Examination Survey. Low light-intensity activity (100-799 counts/min), high light-intensity activity (800 counts/min to <4 METs) and moderate- to vigorous-intensity activity (≥ 4 METs, Freedson age-specific equation) were accelerometer-derived. Cardiometabolic biomarkers, including waist circumference, systolic blood pressure, diastolic blood pressure, HDL-cholesterol, and C-reactive protein were measured. Triglycerides, LDL- cholesterol, insulin, glucose, and homeostatic model assessments of ß-cell function (HOMA-%B) and insulin sensitivity (HOMA-%S) were also measured in a fasting sub-sample (n=807). RESULTS: Adjusted for confounders, each additional hour/day of low light-intensity activity was associated with 0.59 (95% CI: 1.18-0.01) mmHG lower diastolic blood pressure. Each additional hour/day of high light-intensity activity was associated with 1.67 (2.94-0.39) mmHG lower diastolic blood pressure and 0.04 (0.001-0.07) mmol/L higher HDL-cholesterol. Each additional hour/day of moderate- to vigorous-intensity activity was associated with 3.54 (5.73-1.35) mmHG lower systolic blood pressure, 5.49 (1.11-9.77)% lower waist circumference, 25.87 (6.08-49.34)% lower insulin, and 16.18 (4.92-28.53)% higher HOMA-%S. CONCLUSIONS: Time spent in low light-intensity physical activity and high light-intensity physical activity had some favorable associations with biomarkers. Consistent with current physical activity recommendations for adolescents, moderate- to vigorous-intensity activity had favorable associations with many cardiometabolic biomarkers. While increasing MVPA should still be a public health priority, further studies are needed to identify dose-response relationships for light-intensity activity thresholds to inform future recommendations and interventions for adolescents.

Examination of mid-intervention mediating effects on objectively assessed sedentary time among children in the Transform-Us! cluster-randomized controlled trial.

BACKGROUND: The optimal targets and strategies for effectively reducing sedentary behavior among young people are unknown. Intervention research that explores changes in mediated effects as well as in outcome behaviors is needed to help inform more effective interventions. Therefore, the purpose of this study was to examine the mid-intervention mediating effects on children's objectively assessed classroom and total weekday sedentary time in the Transform-Us! intervention. METHODS: The results are based on 293 children, aged 7- to 9-years-old at baseline, from 20 schools in Melbourne, Australia. Each school was randomly allocated to one of four groups, which targeted reducing sedentary time in the school and family settings (SB; n = 74), increasing or maintaining moderate- to vigorous-intensity physical activity in the school and family settings (PA; n = 75), combined SB and PA (SB + PA; n = 80), or the current practice control (C; n = 64). Baseline and mid-intervention data (5-9 months) were collected in 2010 and analyzed in 2012. Classroom and total weekday sedentary time was objectively assessed using ActiGraph accelerometers. The hypothesized mediators including, child enjoyment, parent and teacher outcome expectancies, and child perceived access to standing opportunities in the classroom environment, were assessed by questionnaire. RESULTS: The SB + PA group spent 13.3 min/day less in weekday sedentary time at mid-intervention compared to the control group. At mid-intervention, children in the SB group had higher enjoyment of standing in class (0.9 units; 5-unit scale) and all intervention groups had more positive perceptions of access to standing opportunities in the classroom environment (0.3-0.4 units; 3-unit scale), compared to the control group. However, none of the hypothesized mediator variables had an effect on sedentary time; thus, no mediating effects were observed. CONCLUSIONS: While beneficial intervention effects were observed on some hypothesized mediating variables and total weekday sedentary time at mid-intervention, no significant mediating effects were found. Given the dearth of existing information, future intervention research is needed that explores mediated effects. More work is also needed on the development of reliable mediator measures that are sensitive to change overtime. TRIAL REGISTRATION: ACTRN12609000715279. ISRCTN83725066.

5-year changes in afterschool physical activity and sedentary behavior.

BACKGROUND: The afterschool period holds promise for the promotion of physical activity, yet little is known about the importance of this period as children age. PURPOSE: To examine changes in physical activity of children aged 5-6 years and 10-12 years and their sedentary time in the afterschool period over 3 and 5 years, and to determine the contribution of this period to daily physical activity and sedentary behavior over time. METHODS: Data from two longitudinal studies conducted in Melbourne, Australia, were used. Accelerometer data were provided for 2053 children at baseline (Children Living in Active Neighbourhoods Study [CLAN]: 2001; Health, Eating and Play Study [HEAPS]: 2002/2003); 756 at 3-year follow-up (time point 2 [T2]); and 622 at 5-year follow-up (T3). Light (LPA), moderate (MPA) and vigorous (VPA) physical activity were determined using age-adjusted cut-points. Sedentary time was defined as ≤ 100 counts/minute. Multilevel analyses, conducted in April 2012, assessed change in physical activity and sedentary time and the contributions of the afterschool period to overall levels. RESULTS: Afterschool MPA and VPA decreased among both cohorts, particularly in the younger cohort, who performed less than half of their baseline levels at T3 (MPA: T1=24 minutes; T3=11 minutes; VPA: T1=12 minutes; T3=4 minutes). LPA also declined in the older cohort. Afterschool sedentary time increased among the younger (T1=42 minutes; T3=64 minutes) and older cohorts (T1=57 minutes; T3=84 minutes). The contribution of the afterschool period to overall MPA and VPA increased in the older cohort from 23% to 33% over 5 years. In the younger cohort, the contribution of the afterschool period to daily MPA and VPA decreased by 3% over 5 years. CONCLUSIONS: The importance of the afterschool period for children's physical activity increases with age, particularly as children enter adolescence.

Agreement between activPAL and ActiGraph for assessing children's sedentary time.

BACKGROUND: Accelerometers have been used to determine the amount of time that children spend sedentary. However, as time spent sitting may be detrimental to health, research is needed to examine whether accelerometer sedentary cut-points reflect the amount of time children spend sitting. The aim of this study was to: a) examine agreement between ActiGraph (AG) cut-points for sedentary time and objectively-assessed periods of free-living sitting and sitting plus standing time using the activPAL (aP); and b) identify cut-points to determine time spent sitting and sitting plus standing. METHODS: Forty-eight children (54% boys) aged 8-12 years wore a waist-mounted AG and thigh-mounted aP for two consecutive school days (9-3:30 pm). AG data were analyzed using 17 cut-points between 50-850 counts·min-1 in 50 counts·min-1 increments to determine sedentary time during class-time, break time and school hours. Sitting and sitting plus standing time were obtained from the aP for these periods. Limits of agreement were computed to evaluate bias between AG50 to AG850 sedentary time and sitting and sitting plus standing time. Receiver Operator Characteristic (ROC) analyses identified AG cut-points that maximized sensitivity and specificity for sitting and sitting plus standing time. RESULTS: The smallest mean bias between aP sitting time and AG sedentary time was AG150 for class time (3.8 minutes), AG50 for break time (-0.8 minutes), and AG100 for school hours (-5.2 minutes). For sitting plus standing time, the smallest bias was observed for AG850. ROC analyses revealed an optimal cut-point of 96 counts·min-1 (AUC = 0.75) for sitting time, which had acceptable sensitivity (71.7%) and specificity (67.8%). No optimal cut-point was obtained for sitting plus standing (AUC = 0.51). CONCLUSIONS: Estimates of free-living sitting time in children during school hours can be obtained using an AG cut-point of 100 counts·min-1. Higher sedentary cut-points may capture both sitting and standing time.