Aims/hypothesis Sedentary (sitting) behaviours are ubiquitous in modern society. We conducted a systematic review and meta-analysis to examine the association of sedentary time with diabetes, cardiovascular disease and cardiovascular and all-cause mortality. Methods Medline, Embase and the Cochrane Library databases were searched for terms related to sedentary time and health outcomes. Cross-sectional and prospective studies were included. RR/HR and 95% CIs were extracted by two independent reviewers. Data were adjusted for baseline event rate and pooled using a random-effects model. Bayesian predictive effects and intervals were calculated to indicate the variance in outcomes that would be expected if new studies were conducted in the future. Results Eighteen studies (16 prospective, two cross-sectional) were included, with 794,577 participants. Fifteen of these studies were moderate to high quality. The greatest sedentary time compared with the lowest was associated with a 112% increase in the RR of diabetes (RR 2.12; 95% credible interval [CrI] 1.61, 2.78), a 147% increase in the RR of cardiovascular events (RR 2.47; 95% CI 1.44, 4.24), a 90% increase in the risk of cardiovascular mortality (HR 1.90; 95% CrI 1.36, 2.66) and a 49% increase in the risk of all-cause mortality (HR 1.49; 95% CrI 1.14, 2.03). The predictive effects and intervals were only significant for diabetes. Conclusions/interpretation Sedentary time is associated with an increased risk of diabetes, cardiovascular disease and cardiovascular and all-cause mortality; the strength of the association is most consistent for diabetes.

ObjectiveTo examine the dose-response associations between accelerometer assessed total physical activity, different intensities of physical activity, and sedentary time and all cause mortality.DesignSystematic review and harmonised meta-analysis.Data sourcesPubMed, PsycINFO, Embase, Web of Science, Sport Discus from inception to 31 July 2018.Eligibility criteriaProspective cohort studies assessing physical activity and sedentary time by accelerometry and associations with all cause mortality and reported effect estimates as hazard ratios, odds ratios, or relative risks with 95% confidence intervals.Data extraction and analysisGuidelines for meta-analyses and systematic reviews for observational studies and PRISMA guidelines were followed. Two authors independently screened the titles and abstracts. One author performed a full text review and another extracted the data. Two authors independently assessed the risk of bias. Individual level participant data were harmonised and analysed at study level. Data on physical activity were categorised by quarters at study level, and study specific associations with all cause mortality were analysed using Cox proportional hazards regression analyses. Study specific results were summarised using random effects meta-analysis.Main outcome measureAll cause mortality.Results39 studies were retrieved for full text review; 10 were eligible for inclusion, three were excluded owing to harmonisation challenges (eg, wrist placement of the accelerometer), and one study did not participate. Two additional studies with unpublished mortality data were also included. Thus, individual level data from eight studies (n=36 383; mean age 62.6 years; 72.8% women), with median follow-up of 5.8 years (range 3.0-14.5 years) and 2149 (5.9%) deaths were analysed. Any physical activity, regardless of intensity, was associated with lower risk of mortality, with a non-linear dose-response. Hazards ratios for mortality were 1.00 (referent) in the first quarter (least active), 0.48 (95% confidence interval 0.43 to 0.54) in the second quarter, 0.34 (0.26 to 0.45) in the third quarter, and 0.27 (0.23 to 0.32) in the fourth quarter (most active). Corresponding hazards ratios for light physical activity were 1.00, 0.60 (0.54 to 0.68), 0.44 (0.38 to 0.51), and 0.38 (0.28 to 0.51), and for moderate-to-vigorous physical activity were 1.00, 0.64 (0.55 to 0.74), 0.55 (0.40 to 0.74), and 0.52 (0.43 to 0.61). For sedentary time, hazards ratios were 1.00 (referent; least sedentary), 1.28 (1.09 to 1.51), 1.71 (1.36 to 2.15), and 2.63 (1.94 to 3.56).ConclusionHigher levels of total physical activity, at any intensity, and less time spent sedentary, are associated with substantially reduced risk for premature mortality, with evidence of a non-linear dose-response pattern in middle aged and older adults.Systematic review registrationPROSPERO CRD42018091808.

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

High-quality measurement is essential in all elements of sedentary behaviour epidemiology, from determining associations with health outcomes to the development and evaluation of behaviour change interventions. Sedentary behaviour measurement remains relatively under-developed, although new instruments, both objective and subjective, show considerable promise and warrant further testing.

Research indicates that high levels of sedentary behavior (sitting or lying with low energy expenditure) are adversely associated with health. A key factor in improving our understanding of the impact of sedentary behavior (and patterns of sedentary time accumulation) on health is the use of objective measurement tools that collect date and time-stamped activity information. One such tool is the activPAL monitor. This thigh-worn device uses accelerometer-derived information about thigh position to determine the start and end of each period spent sitting/lying, standing, and stepping, as well as stepping speed, step counts, and postural transitions. The activPAL is increasingly being used within field-based research for its ability to measure sitting/lying via posture. We summarise key issues to consider when using the activPAL in physical activity and sedentary behavior field-based research with adult populations. It is intended that the findings and discussion points be informative for researchers who are currently using activPAL monitors or are intending to use them. Pre-data collection decisions, monitor preparation and distribution, data collection considerations, and manual and automated data processing possibilities are presented using examples from current literature and experiences from 2 research groups from the UK and Australia.

Background The impact of COVID-19 on physical and mental health and employment after hospitalisation with acute disease is not well understood. The aim of this study was to determine the effects of COVID-19-related hospitalisation on health and employment, to identify factors associated with recovery, and to describe recovery phenotypes. MethodsThe Post-hospitalisation COVID-19 study (PHOSP-COVID) is a multicentre, long-term follow-up study of adults (aged ≥18 years) discharged from hospital in the UK with a clinical diagnosis of COVID-19, involving an assessment between 2 and 7 months after discharge, including detailed recording of symptoms, and physiological and biochemical testing. Multivariable logistic regression was done for the primary outcome of patient-perceived recovery, with age, sex, ethnicity, body-mass index, comorbidities, and severity of acute illness as covariates. A posthoc cluster analysis of outcomes for breathlessness, fatigue, mental health, cognitive impairment, and physical performance was done using the clustering large applications k-medoids approach. The study is registered on the ISRCTN Registry (ISRCTN10980107). Findings We report findings for 1077 patients discharged from hospital between March 5 and Nov 30, 2020, who underwent assessment at a median of 5•9 months (IQR 4•9-6•5) after discharge. Participants had a mean age of 58 years (SD 13); 384 (36%) were female, 710 (69%) were of white ethnicity, 288 (27%) had received mechanical ventilation, and 540 (50%) had at least two comorbidities. At follow-up, only 239 (29%) of 830 participants felt fully recovered, 158 (20%) of 806 had a new disability (assessed by the Washington Group Short Set on Functioning), and 124 (19%) of 641 experienced a health-related change in occupation. Factors associated with not recovering were female sex, middle age (40-59 years), two or more comorbidities, and more severe acute illness. The magnitude of the persistent health burden was substantial but only weakly associated with the severity of acute illness. Four clusters were identified with different severities of mental and physical health impairment (n=767): very severe (131 patients, 17%), severe (159, 21%), moderate along with cognitive impairment (127, 17%), and mild (350, 46%). Of the outcomes used in the cluster analysis, all were closely related except for cognitive impairment. Three (3%) of 113 patients in the very severe cluster, nine (7%) of 129 in the severe cluster, 36 (36%) of 99 in the moderate cluster, and 114 (43%) of 267 in the mild cluster reported feeling fully recovered. Persistently elevated serum C-reactive protein was positively associated with cluster severity.Interpretation We identified factors related to not recovering after hospital admission with COVID-19 at 6 months after discharge (eg, female sex, middle age, two or more comorbidities, and more acute severe illness), and four different recovery phenotypes. The severity of physical and mental health impairments were closely related, whereas cognitive health impairments w...

BackgroundIn recent years there has been a growing interest in the relationship between sedentary behaviour (sitting) and health outcomes. Only recently have there been studies assessing the association between time spent in sedentary behaviour and the metabolic syndrome. The aim of this study is to quantify the association between sedentary behaviour and the metabolic syndrome in adults using meta-analysis.Methodology/Principal FindingsMedline, Embase and the Cochrane Library were searched using medical subject headings and key words related to sedentary behaviours and the metabolic syndrome. Reference lists of relevant articles and personal databases were hand searched. Inclusion criteria were: (1) cross sectional or prospective design; (2) include adults ≥18 years of age; (3) self-reported or objectively measured sedentary time; and (4) an outcome measure of metabolic syndrome. Odds Ratio (OR) and 95% confidence intervals for metabolic syndrome comparing the highest level of sedentary behaviour to the lowest were extracted for each study. Data were pooled using random effects models to take into account heterogeneity between studies. Ten cross-sectional studies (n = 21393 participants), one high, four moderate and five poor quality, were identified. Greater time spent sedentary increased the odds of metabolic syndrome by 73% (OR 1.73, 95% CI 1.55–1.94, p<0.0001). There were no differences for subgroups of sex, sedentary behaviour measure, metabolic syndrome definition, study quality or country income. There was no evidence of statistical heterogeneity (I2 = 0.0%, p = 0.61) or publication bias (Eggers test t = 1.05, p = 0.32).ConclusionsPeople who spend higher amounts of time in sedentary behaviours have greater odds of having metabolic syndrome. Reducing sedentary behaviours is potentially important for the prevention of metabolic syndrome.

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