A single day of bed rest, irrespective of energy balance, does not affect skeletal muscle gene expression or insulin sensitivity

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The initial metabolic and molecular events that underpin disuse-induced skeletal muscle deconditioning, and the contribution of energy balance, remain to be investigated. Ten young, healthy males (age: 25 ± 1 y; BMI: 25.3 ± 0.8 kg m-2 ) underwent three 24 h laboratory-based experimental periods in a randomized, crossover manner: 1) controlled habitual physical activity with an energy-balanced diet (CON); 2) strict bed rest with a diet to maintain energy balance (BR-B); and 3) strict bed rest with a diet identical to CON, consequently resulting in positive energy balance. Continuous glucose monitoring was performed throughout each visit, with vastus lateralis muscle biopsies and an oral glucose tolerance test performed before and after. In parallel with muscle samples collected from a previous 7-day bed rest study, biopsies were used to examine expression of genes associated with the regulation of muscle mass and insulin sensitivity. A single day of bed rest, irrespective of energy balance, did not lead to overt changes in whole-body substrate oxidation, indices of insulin sensitivity (i.e. HOMA-IR (BR-B: from 2.7 ± 1.7 to 3.1 ± 1.5, P > 0.05), Matsuda (BR-B: from 5.9 ± 3.3 to 5.2 ± 2.9, P > 0.05)), or 24 h glycaemic control/variability compared to CON. Seven days of bed rest led to ∼30-55% lower expression of genes involved in insulin signalling, lipid storage/oxidation, and muscle protein breakdown, whereas no such changes were observed after one day of bed rest. In conclusion, more than one day of physical inactivity is required to observe the insulin resistance and robust skeletal muscle transcriptional responses associated with bed rest and consequent alterations in energy balance.BTW received internal funding from the College of Life and Environmental Sciences, University of Exeter, to support this project. None of the other authors received funding from any funding agency in the public, commercial or not-for-profit sectors to conduct this research

A three arm cluster randomised controlled trial to test the effectiveness and cost-effectiveness of the SMART work & life intervention for reducing daily sitting time in office workers : study protocol

Background:Office-based workers typically spend 70-85% of working hours, and a large proportion of leisure time, sitting. High levels of sitting have been linked to poor health. There is a need for fully powered randomised controlled trials (RCTs) with long-term follow-up to test the effectiveness of interventions to reduce sitting. This paper describes the methodology of a three-arm cluster RCT designed to determine the effectiveness and cost-effectiveness of the SMART Work & Life intervention, delivered with and without a height-adjustable desk, for reducing daily sitting. Methods/Design:A three-arm cluster RCT of 33 clusters (660 council workers) will be conducted in three areas in England (Leicester; Manchester; Liverpool). Office groups (clusters) will be randomised to the SMART Work & Life intervention delivered with (group 1) or without (group 2) a height-adjustable desk or a control group (group 3). SMART Work & Life includes organisational (e.g., management buy-in, provision/support for standing meetings), environmental (e.g., relocating waste bins, printers), and group/individual (education, action planning, goal setting, addressing barriers, coaching, self-monitoring, social support) level behaviour change strategies, with strategies driven by workplace champions. Baseline, 3, 12 and 24 month measures will be taken. Objectively measured daily sitting time (activPAL3). objectively measured sitting, standing, stepping, prolonged sitting and moderate-to-vigorous physical activity time and number of steps at work and daily; objectively measured sleep (wrist accelerometry). Adiposity, blood pressure, fasting glucose, glycated haemoglobin, cholesterol (total, HDL, LDL) and triglycerides will be assessed from capillary blood samples. Questionnaires will examine dietary intake, fatigue, musculoskeletal issues, job performance and satisfaction, work engagement, occupational and general fatigue, stress, presenteeism, anxiety and depression and sickness absence (organisational records). Quality of life and resources used (e.g. GP visits, outpatient attendances) will also be assessed. We will conduct a full process evaluation and cost-effectiveness analysis. Discussion:The results of this RCT will 1) help to understand how effective an important simple, yet relatively expensive environmental change is for reducing sitting, 2) provide evidence on changing behaviour across all waking hours, and 3) provide evidence for policy guidelines around population and workplace health and well-being. Trial registration: ISRCTN11618007 . Registered on 21 January 2018

Acute effect of exercise intensity and duration on acylated ghrelin and hunger in men.

Published onlineJournal ArticleThis is the author accepted manuscript. The final version is available from BioScientifica via the DOI in this record.Acute exercise transiently suppresses the orexigenic gut hormone acylated ghrelin, but the extent exercise intensity and duration determine this response is not fully understood. The effects of manipulating exercise intensity and duration on acylated ghrelin concentrations and hunger were examined in two experiments. In experiment one, nine healthy males completed three, 4-hour conditions (control, moderate-intensity running (MOD) and vigorous-intensity running (VIG)), with an energy expenditure of ~2.5 MJ induced in both MOD (55 min running at 52% peak oxygen uptake (VO2peak)) and VIG (36 min running at 75% VO2peak). In experiment two, nine healthy males completed three, 9-hour conditions (control, 45 min running (EX45) and 90 min running (EX90)). Exercise was performed at 70% VO2peak In both experiments, participants consumed standardised meals, and acylated ghrelin concentrations and hunger were quantified at predetermined intervals. In experiment one, delta acylated ghrelin concentrations were lower than control in MOD (ES=0.44, P=0.01) and VIG (ES=0.98, P<0.001); VIG was lower than MOD (ES=0.54, P=0.003). Hunger ratings were similar across the conditions (P=0.35). In experiment two, delta acylated ghrelin concentrations were lower than control in EX45 (ES=0.77, P<0.001) and EX90 (ES=0.68, P<0.001); EX45 and EX90 were similar (ES=0.09, P=0.55). Hunger ratings were lower than control in EX45 (ES=0.20, P=0.01) and EX90 (ES=0.27, P=0.001); EX45 and EX90 were similar (ES=0.07, P=0.34). Hunger and delta acylated ghrelin concentrations remained suppressed at 1.5h in EX90 but not EX45. In conclusion, exercise intensity, and to a lesser extent duration, are determinants of the acylated ghrelin response to acute exercise.The research was supported by the National Institute for Health Research (NIHR) Diet, Lifestyle & Physical Activity Biomedical Research Unit based at University Hospitals of Leicester and Loughborough University. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health

Spatiotemporal effects of logging and fire on tall, wet temperate eucalypt forest birds

Forests globally are subject to disturbances such as logging and fire that create complex temporal variation in spatial patterns of forest cover and stand age. However, investigations that quantify temporal changes in biodiversity in response to multiple forms of disturbance in space and time are relatively uncommon. Over a 10-yr period, we investigated the response of bird species to spatiotemporal changes in forest cover associated with logging and wildfire in the mountain ash (Eucalyptus regnans) forests of southeastern Australia. Specifically, we examined how bird occurrence changed with shifts in the proportion of area burned or logged in a 4.5 km radius surrounding our 88 long-term field survey sites, each measuring 1 ha in size. Overall species richness was greatest in older forest patches, but declined as the amount of fire around each site increased. At the individual species level, 31 of the 37 bird species we modeled exhibited a negative response to the amount of fire in the surrounding landscape, while one species responded positively to fire. Only nine species exhibited signs of recovery in the 6 yr of surveys following the fire. Five species were more likely to be detected as the proportion of logged forest surrounding a site increased, suggesting a possible "concentration effect" with displaced birds moving into unlogged areas following harvesting of adjacent areas. We also identified relationships between the coefficients of life history attributes and spatiotemporal changes in forest cover and stand age. Large-bodied birds and migratory species were associated with landscapes subject to large amounts of fire in 2009. There were associations between old growth stands and small-bodied bird species and species that were not insectivores. Our study shows that birds in mountain ash forests are strongly associated with old growth stands and exhibit complex, time-dependent, and species-specific responses to landscape disturbance. Despite logging and fire both being high-severity perturbations, no bird species exhibited similar responses to fire and logging in the landscape surrounding our sites. Thus, species responses to one kind of landscape-scale disturbance are not readily predictable based on an understanding of the responses to another kind of (albeit superficially similar) disturbance.Threatened Species Recovery Hub of the National Environmental Science Program, Parks Victoria, and Victorian Government Department of Environment, Land, Water and Plannin

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

Background and Aims: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.Methods: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.Results: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7h sleeping, 10.4h sedentary, 3.1h standing, 1.5h LIPA, and 1.3h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30min of SB, sleep, standing, or LIPA with MVPA was associated with-0.63 (95% confidence interval-0.48,-0.79),-0.43 (-0.25,-0.59),-0.40 (-0.25,-0.56), and-0.15 (0.05,-0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. Conclusions: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.</p

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

BACKGROUND AND AIMS: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers. METHODS: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours. RESULTS: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day. CONCLUSIONS: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity

Device-Measured 24-Hour Movement Behaviors and Blood Pressure: A 6-Part Compositional Individual Participant Data Analysis in the ProPASS Consortium

BACKGROUND: Blood pressure (BP)–lowering effects of structured exercise are well-established. Effects of 24-hour movement behaviors captured in free-living settings have received less attention. This cross-sectional study investigated associations between a 24-hour behavior composition comprising 6 parts (sleeping, sedentary behavior, standing, slow walking, fast walking, and combined exercise-like activity [eg, running and cycling]) and systolic BP (SBP) and diastolic BP (DBP). // METHODS: Data from thigh-worn accelerometers and BP measurements were collected from 6 cohorts in the Prospective Physical Activity, Sitting and Sleep consortium (ProPASS) (n=14 761; mean±SD, 54.2±9.6 years). Individual participant analysis using compositional data analysis was conducted with adjustments for relevant harmonized covariates. Based on the average sample composition, reallocation plots examined estimated BP reductions through behavioral replacement; the theoretical benefits of optimal (ie, clinically meaningful improvement in SBP [2 mm Hg] or DBP [1 mm Hg]) and minimal (ie, 5-minute reallocation) behavioral replacements were identified. // RESULTS: The average 24-hour composition consisted of sleeping (7.13±1.19 hours), sedentary behavior (10.7±1.9 hours), standing (3.2±1.1 hours), slow walking (1.6±0.6 hours), fast walking (1.1±0.5 hours), and exercise-like activity (16.0±16.3 minutes). More time spent exercising or sleeping, relative to other behaviors, was associated with lower BP. An additional 5 minutes of exercise-like activity was associated with estimated reductions of –0.68 mm Hg (95% CI, –0.15, –1.21) SBP and –0.54 mm Hg (95% CI, –0.19, 0.89) DBP. Clinically meaningful improvements in SBP and DBP were estimated after 20 to 27 minutes and 10 to 15 minutes of reallocation of time in other behaviors into additional exercise. Although more time spent being sedentary was adversely associated with SBP and DBP, there was minimal impact of standing or walking. // CONCLUSIONS: Study findings reiterate the importance of exercise for BP control, suggesting that small additional amounts of exercise are associated with lower BP in a free-living setting

Device-measured 24-hour movement behaviors and blood pressure: a 6-part compositional individual participant data analysis in the ProPASS Consortium

BACKGROUND: Blood pressure (BP)-lowering effects of structured exercise are well-established. Effects of 24-hour movement behaviors captured in free-living settings have received less attention. This cross-sectional study investigated associations between a 24-hour behavior composition comprising 6 parts (sleeping, sedentary behavior, standing, slow walking, fast walking, and combined exercise-like activity [eg, running and cycling]) and systolic BP (SBP) and diastolic BP (DBP). METHODS: Data from thigh-worn accelerometers and BP measurements were collected from 6 cohorts in the Prospective Physical Activity, Sitting and Sleep consortium (ProPASS) (n=14 761; mean±SD, 54.2±9.6 years). Individual participant analysis using compositional data analysis was conducted with adjustments for relevant harmonized covariates. Based on the average sample composition, reallocation plots examined estimated BP reductions through behavioral replacement; the theoretical benefits of optimal (ie, clinically meaningful improvement in SBP [2 mm Hg] or DBP [1 mm Hg]) and minimal (ie, 5-minute reallocation) behavioral replacements were identified. RESULTS: The average 24-hour composition consisted of sleeping (7.13±1.19 hours), sedentary behavior (10.7±1.9 hours), standing (3.2±1.1 hours), slow walking (1.6±0.6 hours), fast walking (1.1±0.5 hours), and exercise-like activity (16.0±16.3 minutes). More time spent exercising or sleeping, relative to other behaviors, was associated with lower BP. An additional 5 minutes of exercise-like activity was associated with estimated reductions of -0.68 mm Hg (95% CI, -0.15, -1.21) SBP and -0.54 mm Hg (95% CI, -0.19, 0.89) DBP. Clinically meaningful improvements in SBP and DBP were estimated after 20 to 27 minutes and 10 to 15 minutes of reallocation of time in other behaviors into additional exercise. Although more time spent being sedentary was adversely associated with SBP and DBP, there was minimal impact of standing or walking. CONCLUSIONS: Study findings reiterate the importance of exercise for BP control, suggesting that small additional amounts of exercise are associated with lower BP in a free-living setting.</p

Scoping of policy impacts for regulating e-cigarettes (SPIRE): findings from a data and decision analytic model mapping project

Background E-cigarettes, also known as vapes, are lower risk products compared to conventional cigarettes, that can aid smoking cessation. However, they have been developed to also appeal to people who do not smoke, and are not harm-free. The challenge is for vaping policy to support smokers to quit whilst also protecting non-smokers from starting. Simulation modelling can be used to synthesise existing evidence and make predictions about policy impacts. This research aims to identify (a) data sources that can inform modelling of vape policies in the United Kingdom (UK) and (b) gaps in data that are required to undertake appropriate modelling. Methods We held stakeholder workshops with academic experts, policy makers and public members to understand the requirements of a simulation model of vaping policy and existing data. Based on the findings of the first workshop and a review of existing modelling studies, we undertook a set of targeted rapid reviews to augment key existing reviews. We also developed a dataset dictionary. From these, we developed key recommendations about data collection and modelling. Results There is substantial UK evidence around many of the transitions between smoking and vaping behaviours, but these have not yet been estimated simultaneously. We also identified 25 UK studies assessing the socioeconomic, psychological and social network influences on vaping behaviours. However, there is limited evidence about the effectiveness of vaping policies in the UK, the impact of industry circumvention, the health harms of vaping for people who have never smoked, longer term evidence on the smoking harms of vaping and the use and impact of illegal vapes. Conclusions Addressing the identified gaps in the evidence will require targeted new research. By fostering collaboration across disciplines and ensuring transparency and consistency in modelling, the UK can build a credible, evidence-based foundation for shaping effective vape regulation