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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 reveal

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 reveal

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 reveal

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 reveal

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 reveal

Purpose: This study assessed the effects of upper-body rowing exercise on cardiorespiratory fitness, traditional cardiometabolic risk factors, and vascular health in individuals with spinal cord injury (SCI). Methods: Seventeen male and female adults with chronic (> 1 yr) motor-complete and incomplete SCI (level of injury: C4-L3) were randomized to control (CON, n = 9) or exercise (UBROW, n = 8). Participants in UBROW performed 12-week, 3 weekly sessions of 30-min upper-body ergometer rowing exercise, complying with current exercise guidelines for SCI. Cardiorespiratory fitness (V˙ O2peak), traditional risk factors (lipid profile, glycemic control) as well as inflammatory and vascular endothelium-derived biomarkers (derived from fasting blood samples) were measured before and after 6 (6W) and 12 weeks (12W). Brachial artery resting diameter and flow-mediated dilation (FMD) were determined by ultrasound as exploratory outcomes. Results: UBROW increased V˙O2peak from baseline (15.1 ± 5.1 mL/kg/min; mean ± SD) to 6W (16.5 ± 5.3; P < 0.01) and 12W (17.5 ± 6.1; P < 0.01). UBROW increased resting brachial artery diameter from baseline (4.80 ± 0.72 mm) to 12W (5.08 ± 0.91; P < 0.01), with no changes at 6W (4.96 ± 0.91), and no changes in CON. There were no significant time-by-group interactions in traditional cardiometabolic blood biomarkers, or in unadjusted or baseline diameter corrected FMD. Explorative analyses revealed inverse correlations between changes (∆12W-baseline) in endothelin-1 and changes in resting diameter (r = − 0.56) and FMD% (r = − 0.60), both P < 0.05. Conclusion: These results demonstrate that 12 weeks of upper-body rowing complying with current exercise guidelines for SCI improves cardiorespiratory fitness and increases resting brachial artery diameter. In contrast, the exercise intervention had no or

Purpose: Remote ischaemic preconditioning (RIPC) refers to the protection conferred to tissues and organs via brief periods of ischaemia in a remote vascular territory, including the brain. Recent studies in humans report that RIPC provides neuroprotection against recurrent (ischaemic) stroke. To better understand the ability of RIPC to improve brain health, the present study explored the potential for RIPC to acutely improve cerebrovascular function.Methods: Eleven young healthy (females n = 6, age; 28.1 ± 3.7 years) and 9 older individuals (females n = 4, age 52.5 ± 6.7 years) at increased risk for stroke (cardiovascular disease risk factors) underwent assessments of cerebrovascular function, assessed by carbon dioxide (CO2) reactivity and cerebral autoregulation during normo- and hypercapnia (5% CO2) following 40 mins of bilateral arm RIPC or a sham condition. Squat-to-stand manoeuvres were performed to induce changes in blood pressure to assess cerebral autoregulation (0.10 Hz) and analysed via transfer function.Results: We found no change in middle cerebral artery velocity or blood pressure across 40 mins of RIPC. Application of RIPC resulted in no change in CO2 reactivity slopes (sham vs RIPC, 1.97 ± 0.88 vs 2.06 ± 0.69 cm/s/mmHg P = 0.61) or parameters of cerebral autoregulation during normocapnia (sham vs RIPC, normalised gain%, 1.27 ± 0.25 vs 1.22 ± 0.35, P = 0.46).Conclusion: This study demonstrates that a single bout of RIPC does not influence cerebrovascular function acutely in healthy individuals, or those at increased cardiovascular risk. Given the previously reported protective role of RIPC on stroke recurrence in humans, it is possible that repeated bouts of RIPC may be necessary to impart beneficial effects on cerebrovascular function.

Purpose: Remote ischaemic preconditioning (RIPC) refers to the protection conferred to tissues and organs via brief periods of ischaemia in a remote vascular territory, including the brain. Recent studies in humans report that RIPC provides neuroprotection against recurrent (ischaemic) stroke. To better understand the ability of RIPC to improve brain health, the present study explored the potential for RIPC to acutely improve cerebrovascular function.Methods: Eleven young healthy (females n = 6, age; 28.1 ± 3.7 years) and 9 older individuals (females n = 4, age 52.5 ± 6.7 years) at increased risk for stroke (cardiovascular disease risk factors) underwent assessments of cerebrovascular function, assessed by carbon dioxide (CO2) reactivity and cerebral autoregulation during normo- and hypercapnia (5% CO2) following 40 mins of bilateral arm RIPC or a sham condition. Squat-to-stand manoeuvres were performed to induce changes in blood pressure to assess cerebral autoregulation (0.10 Hz) and analysed via transfer function.Results: We found no change in middle cerebral artery velocity or blood pressure across 40 mins of RIPC. Application of RIPC resulted in no change in CO2 reactivity slopes (sham vs RIPC, 1.97 ± 0.88 vs 2.06 ± 0.69 cm/s/mmHg P = 0.61) or parameters of cerebral autoregulation during normocapnia (sham vs RIPC, normalised gain%, 1.27 ± 0.25 vs 1.22 ± 0.35, P = 0.46).Conclusion: This study demonstrates that a single bout of RIPC does not influence cerebrovascular function acutely in healthy individuals, or those at increased cardiovascular risk. Given the previously reported protective role of RIPC on stroke recurrence in humans, it is possible that repeated bouts of RIPC may be necessary to impart beneficial effects on cerebrovascular function.

Background: Remote ischaemic preconditioning (rIPC) may improve cardiac/cerebrovascular outcomes of ischaemic events. Ischaemic damage caused by cardiovascular/cerebrovascular disease are primary causes of mortality in type 2 diabetes mellitus (T2DM). Due to the positive effects from a bout of rIPC within the vasculature, we explored if daily rIPC could improve endothelial and cerebrovascular function. The aim of this pilot study was to obtain estimates for the change in conduit artery and cerebrovascular function following a 7-day rIPC intervention.Methods: Twenty-one patients with T2DM were randomly allocated to either 7-day daily upper-arm rIPC (4x5 min 220 mmHg, interspaced by 5-min reperfusion) or control. We examined peripheral endothelial function using flow mediated dilation (FMD) before and after ischemia-reperfusion injury (IRI, 20 min forearm ischaemic-20 min reperfusion) and cerebrovascular function, assessed by dynamic cerebral autoregulation (dCA) at three time points; pre, post and 8 days post intervention.Results: For exploratory purposes, we performed statistical analysis on our primary comparison (pre-to-post) to provide an estimate of the change in the primary and secondary outcome variables. Using pre-intervention data as a covariate, the change from pre-post in FMD was 1.3% (95%CI: 0.69 to 3.80; P=0.09) and 0.23 %cm s-1 %.mmHg-1mm Hg/% (-0.12, 0.59; P=0.18) in dCA normalised gain with rIPC versus control. Based upon this, a sample size of 20 and 50 for FMD and normalised gain, respectively, in each group would provide 90% power to detect statistically significant (P<0.05) between-group difference in a randomised controlled trial.Conclusion: We provide estimates of sample size for a randomised control trial exploring the impact of daily rIPC for 7 days on peripheral endothelial and cerebrovascular function. The directional changes outline from our pilot

Background: Remote ischaemic preconditioning (rIPC) may improve cardiac/cerebrovascular outcomes of ischaemic events. Ischaemic damage caused by cardiovascular/cerebrovascular disease are primary causes of mortality in type 2 diabetes mellitus (T2DM). Due to the positive effects from a bout of rIPC within the vasculature, we explored if daily rIPC could improve endothelial and cerebrovascular function. The aim of this pilot study was to obtain estimates for the change in conduit artery and cerebrovascular function following a 7-day rIPC intervention.Methods: Twenty-one patients with T2DM were randomly allocated to either 7-day daily upper-arm rIPC (4x5 min 220 mmHg, interspaced by 5-min reperfusion) or control. We examined peripheral endothelial function using flow mediated dilation (FMD) before and after ischemia-reperfusion injury (IRI, 20 min forearm ischaemic-20 min reperfusion) and cerebrovascular function, assessed by dynamic cerebral autoregulation (dCA) at three time points; pre, post and 8 days post intervention.Results: For exploratory purposes, we performed statistical analysis on our primary comparison (pre-to-post) to provide an estimate of the change in the primary and secondary outcome variables. Using pre-intervention data as a covariate, the change from pre-post in FMD was 1.3% (95%CI: 0.69 to 3.80; P=0.09) and 0.23 %cm s-1 %.mmHg-1mm Hg/% (-0.12, 0.59; P=0.18) in dCA normalised gain with rIPC versus control. Based upon this, a sample size of 20 and 50 for FMD and normalised gain, respectively, in each group would provide 90% power to detect statistically significant (P<0.05) between-group difference in a randomised controlled trial.Conclusion: We provide estimates of sample size for a randomised control trial exploring the impact of daily rIPC for 7 days on peripheral endothelial and cerebrovascular function. The directional changes outline from our pilot

Background: Remote ischaemic preconditioning (rIPC) may improve cardiac/cerebrovascular outcomes of ischaemic events. Ischaemic damage caused by cardiovascular/cerebrovascular disease are primary causes of mortality in type 2 diabetes mellitus (T2DM). Due to the positive effects from a bout of rIPC within the vasculature, we explored if daily rIPC could improve endothelial and cerebrovascular function. The aim of this pilot study was to obtain estimates for the change in conduit artery and cerebrovascular function following a 7-day rIPC intervention.Methods: Twenty-one patients with T2DM were randomly allocated to either 7-day daily upper-arm rIPC (4x5 min 220 mmHg, interspaced by 5-min reperfusion) or control. We examined peripheral endothelial function using flow mediated dilation (FMD) before and after ischemia-reperfusion injury (IRI, 20 min forearm ischaemic-20 min reperfusion) and cerebrovascular function, assessed by dynamic cerebral autoregulation (dCA) at three time points; pre, post and 8 days post intervention.Results: For exploratory purposes, we performed statistical analysis on our primary comparison (pre-to-post) to provide an estimate of the change in the primary and secondary outcome variables. Using pre-intervention data as a covariate, the change from pre-post in FMD was 1.3% (95%CI: 0.69 to 3.80; P=0.09) and 0.23 %cm s-1 %.mmHg-1mm Hg/% (-0.12, 0.59; P=0.18) in dCA normalised gain with rIPC versus control. Based upon this, a sample size of 20 and 50 for FMD and normalised gain, respectively, in each group would provide 90% power to detect statistically significant (P<0.05) between-group difference in a randomised controlled trial.Conclusion: We provide estimates of sample size for a randomised control trial exploring the impact of daily rIPC for 7 days on peripheral endothelial and cerebrovascular function. The directional changes outline from our pilot