142 research outputs found

    Effects of interrupting prolonged sitting with physical activity breaks on blood glucose, insulin and triacylglycerol measures : a systematic review and meta-analysis

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    Abstract: Background: Physical activity (PA) breaks in sitting time might attenuate metabolic markers relevant to the prevention of type 2 diabetes. Objectives: The primary aim of this paper was to systematically review and meta-analyse trials that compared the effects of breaking up prolonged sitting with bouts of PA throughout the day (INT) versus continuous sitting (SIT) on glucose, insulin and triacylglycerol (TAG) measures. A second aim was to compare the effects of INT versus continuous exercise (EX) on glucose, insulin and TAG measures. Methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) recommendations. Eligibility criteria consisted of trials comparing INT vs. SIT or INT vs. one bout of EX before or after sitting, in participants aged 18 or above, who were classified as either metabolically healthy or impaired, but not with other major health conditions such as chronic obstructive pulmonary disease or peripheral arterial disease. Results: A total of 42 studies were included in the overall review, whereas a total of 37 studies were included in the meta-analysis. There was a standardised mean difference (SMD) of − 0.54 (95% CI − 0.70, − 0.37, p = 0.00001) in favour of INT compared to SIT for glucose. With respect to insulin, there was an SMD of − 0.56 (95% CI − 0.74, − 0.38, p = 0.00001) in favour of INT. For TAG, there was an SMD of − 0.26 (95% CI − 0.44, − 0.09, p = 0.002) in favour of INT. Body mass index (BMI) was associated with glucose responses (β = − 0.05, 95% CI − 0.09, − 0.01, p = 0.01), and insulin (β = − 0.05, 95% CI − 0.10, − 0.006, p = 0.03), but not TAG (β = 0.02, 95% CI − 0.02, 0.06, p = 0.37). When energy expenditure was matched, there was an SMD of − 0.26 (95% CI − 0.50, − 0.02, p = 0.03) in favour of INT for glucose, but no statistically significant SMDs for insulin, i.e. 0.35 (95% CI − 0.37, 1.07, p = 0.35), or TAG i.e. 0.08 (95% CI − 0.22, 0.37, p = 0.62). It is worth noting that there was possible publication bias for TAG outcomes when PA breaks were compared with sitting. Conclusion: The use of PA breaks during sitting moderately attenuated post-prandial glucose, insulin, and TAG, with greater glycaemic attenuation in people with higher BMI. There was a statistically significant small advantage for PA breaks over continuous exercise for attenuating glucose measures when exercise protocols were energy matched, but no statistically significant differences for insulin and TAG

    Default Mode Dynamics for Global Functional Integration.

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    UNLABELLED: The default mode network (DMN) has been traditionally assumed to hinder behavioral performance in externally focused, goal-directed paradigms and to provide no active contribution to human cognition. However, recent evidence suggests greater DMN activity in an array of tasks, especially those that involve self-referential and memory-based processing. Although data that robustly demonstrate a comprehensive functional role for DMN remains relatively scarce, the global workspace framework, which implicates the DMN in global information integration for conscious processing, can potentially provide an explanation for the broad range of higher-order paradigms that report DMN involvement. We used graph theoretical measures to assess the contribution of the DMN to global functional connectivity dynamics in 22 healthy volunteers during an fMRI-based n-back working-memory paradigm with parametric increases in difficulty. Our predominant finding is that brain modularity decreases with greater task demands, thus adapting a more global workspace configuration, in direct relation to increases in reaction times to correct responses. Flexible default mode regions dynamically switch community memberships and display significant changes in their nodal participation coefficient and strength, which may reflect the observed whole-brain changes in functional connectivity architecture. These findings have important implications for our understanding of healthy brain function, as they suggest a central role for the DMN in higher cognitive processing. SIGNIFICANCE STATEMENT: The default mode network (DMN) has been shown to increase its activity during the absence of external stimulation, and hence was historically assumed to disengage during goal-directed tasks. Recent evidence, however, implicates the DMN in self-referential and memory-based processing. We provide robust evidence for this network's active contribution to working memory by revealing dynamic reconfiguration in its interactions with other networks and offer an explanation within the global workspace theoretical framework. These promising findings may help redefine our understanding of the exact DMN role in human cognition.This research was supported by the Evelyn Trust (RUAG/018). In addition, DV received funding from the Yousef Jameel Academic Program; DKM is supported by the NIHR Cambridge Biomedical Centre (RCZB/004), and an NIHR Senior Investigator Award (RCZB/014), and EAS is funded by the Stephen Erskine Fellowship Queens’ College Cambridge.This is the author accepted manuscript. The final version is available from Society for Neuroscience via http://dx.doi.org/10.1523/JNEUROSCI.2135-15.201

    Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review

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    Background: Cardiovascular disease accounts for 17.9 million deaths globally each year. Many research study data sets have been collected to answer questions regarding the relationship between cardiometabolic health and accelerometer-measured physical activity. This scoping review aimed to map the available data sets that have collected accelerometer-measured physical activity and cardiometabolic health markers. These data were then used to inform the development of a publicly available resource, the Global Physical Activity Data set (GPAD) catalogue.Objective: This review aimed to systematically identify data sets that have measured physical activity using accelerometers and cardiometabolic health markers using either an observational or interventional study design.Methods: Databases, trial registries, and gray literature (inception until February 2021; updated search from February 2021 to September 2022) were systematically searched to identify studies that analyzed data sets of physical activity and cardiometabolic health outcomes. To be eligible for inclusion, data sets must have measured physical activity using an accelerometric device in adults aged ≥18 years; a sample size >400 participants (unless recruited participants in a low- and middle-income country where a sample size threshold was reduced to 100); used an observational, longitudinal, or trial-based study design; and collected at least 1 cardiometabolic health marker (unless only body mass was measured). Two reviewers screened the search results to identify eligible studies, and from these, the unique names of each data set were recorded, and characteristics about each data set were extracted from several sources.Results: A total of 17,391 study reports were identified, and after screening, 319 were eligible, with 122 unique data sets in these study reports meeting the review inclusion criteria. Data sets were found in 49 countries across 5 continents, with the most developed in Europe (n=53) and the least in Africa and Oceania (n=4 and n=3, respectively). The most common accelerometric brand and device wear location was Actigraph and the waist, respectively. Height and body mass were the most frequently measured cardiometabolic health markers in the data sets (119/122, 97.5% data sets), followed by blood pressure (82/122, 67.2% data sets). The number of participants in the included data sets ranged from 103,712 to 120. Once the review processes had been completed, the GPAD catalogue was developed to house all the identified data sets.Conclusions: This review identified and mapped the contents of data sets from around the world that have collected potentially harmonizable accelerometer-measured physical activity and cardiometabolic health markers. The GPAD catalogue is a web-based open-source resource developed from the results of this review, which aims to facilitate the harmonization of data sets to produce evidence that will reduce the burden of disease from physical inactivity

    Too much sitting and all-cause mortality: is there a causal link?

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    Background: Sedentary behaviours (time spent sitting, with low energy expenditure) are associated with deleterious health outcomes, including all-cause mortality. Whether this association can be considered causal has yet to be established. Using systematic reviews and primary studies from those reviews, we drew upon Bradford Hill's criteria to consider the likelihood that sedentary behaviour in epidemiological studies is likely to be causally related to all-cause (premature) mortality. Methods: Searches for systematic reviews on sedentary behaviours and all-cause mortality yielded 386 records which, when judged against eligibility criteria, left eight reviews (addressing 17 primary studies) for analysis. Exposure measures included self-reported total sitting time, TV viewing time, and screen time. Studies included comparisons of a low-sedentary reference group with several higher sedentary categories, or compared the highest versus lowest sedentary behaviour groups. We employed four Bradford Hill criteria: strength of association, consistency, temporality, and dose-response. Evidence supporting causality at the level of each systematic review and primary study was judged using a traffic light system depicting green for causal evidence, amber for mixed or inconclusive evidence, and red for no evidence for causality (either evidence of no effect or no evidence reported). Results: The eight systematic reviews showed evidence for consistency (7 green) and temporality (6 green), and some evidence for strength of association (4 green). There was no evidence for a dose-response relationship (5 red). Five reviews were rated green overall. Twelve (67 %) of the primary studies were rated green, with evidence for strength and temporality. Conclusions: There is reasonable evidence for a likely causal relationship between sedentary behaviour and all-cause mortality based on the epidemiological criteria of strength of association, consistency of effect, and temporality

    Associations of objectively measured moderate-to-vigorous-intensity physical activity and sedentary time with all-cause mortality in a population of adults at high risk of type 2 diabetes mellitus

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    The relationships of physical activity and sedentary time with all-cause mortality in those at high risk of type 2 diabetes mellitus (T2DM) are unexplored. To address this gap in knowledge,we examined the associations of objectively measured moderate-to-vigorous-intensity physical activity (MVPA) and sedentary time with all-cause mortality in a population of adults at high risk of T2DM. In 2010–2011, 712 adults (Leicestershire, U.K.), identified as being at high risk of T2DM, consented to be followed up for mortality.MVPA and sedentary time were assessed by accelerometer; those with valid data (≥10 hours of wear-time/day with ≥4 days of data) were included. Cox proportional hazards regression models, adjusted for potential confounders, were used to investigate the independent associations of MVPA and sedentary time with all-cause mortality. 683 participants (250 females (36.6%)) were included and during a mean follow-up period of 5.7 years, 26 deaths were registered. Every 10% increase in MVPA time/day was associated with a 5% lower risk of all-cause mortality [Hazard Ratio (HR): 0.95 (95% Confidence Interval (95% CI): 0.91, 0.98); p=0.004]; indicating that for the average adult in this cohort undertaking approximately 27.5 minutes of MVPA/day, this benefit would be associated with only 2.75 additional minutes of MVPA/day. Conversely, sedentary time showed no association with all-cause mortality [HR (every 10-minute increase in sedentary time/day): 0.99 (95% CI: 0.95, 1.03); p=0.589]. These data support the importance of MVPA in adults at high risk of T2DM. The association between sedentary time and mortality in this population needs further investigation

    Non-exercise equations to estimate fitness in white European and South Asian men

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    © 2015 American College of Sports Medicine PURPOSE: Cardiorespiratory fitness is a strong, independent predictor of health, whether it is measured in an exercise test or estimated in an equation. The purpose of this study was to develop and validate equations to estimate fitness in middle-aged white European and South Asian men. METHODS: Multiple linear regression models (n=168, including 83 white European and 85 South Asian men) were created using variables that are thought to be important in predicting fitness (VO2 max, mL⋅kg⋅min): age (years); BMI (kg·m); resting heart rate (beats⋅min); smoking status (0=never smoked, 1=ex or current smoker); physical activity expressed as quintiles (0=quintile 1, 1=quintile 2, 2=quintile 3, 3=quintile 4, 4=quintile 5), categories of moderate- to vigorous-intensity physical activity (0=150-225 min⋅wk, 3=>225-300 min⋅wk, 4=>300 min⋅wk), or minutes of moderate- to vigorous-intensity physical activity (min⋅wk); and, ethnicity (0=South Asian, 1=white). The leave-one-out-cross-validation procedure was used to assess the generalizability and the bootstrap and jackknife resampling techniques were used to estimate the variance and bias of the models. RESULTS: Around 70% of the variance in fitness was explained in models with an ethnicity variable, such as: VO2 max = 77.409 - (age*0.374) – (BMI*0.906) – (ex or current smoker*1.976) + (physical activity quintile coefficient) – (resting heart rate*0.066) + (white ethnicity*8.032), where physical activity quintile 1 is 1, 2 is 1.127, 3 is 1.869, 4 is 3.793, and 5 is 3.029. Only around 50% of the variance was explained in models without an ethnicity variable. All models with an ethnicity variable were generalizable and had low variance and bias. CONCLUSION: These data demonstrate the importance of incorporating ethnicity in non-exercise equations to estimate cardiorespiratory fitness in multi-ethnic populations
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