It is unclear what level of moderate to vigorous intensity physical activity (MVPA) offsets the health risks of sitting.
The purpose of this study was to examine the joint and stratified associations ...of sitting and MVPA with all-cause and cardiovascular disease (CVD) mortality, and to estimate the theoretical effect of replacing sitting time with physical activity, standing, and sleep.
A longitudinal analysis of the 45 and Up Study calculated the multivariable-adjusted hazard ratios (HRs) of sitting for each sitting-MVPA combination group and within MVPA strata. Isotemporal substitution modeling estimated the per-hour HR effects of replacing sitting.
A total of 8,689 deaths (1,644 due to CVD) occurred among 149,077 participants over an 8.9-year (median) follow-up. There was a statistically significant interaction between sitting and MVPA only for all-cause mortality. Sitting time was associated with both mortality outcomes in a nearly dose-response manner in the least active groups reporting <150 MVPA min/week. For example, among those reporting no MVPA, the all-cause mortality HR comparing the most sedentary (>8 h/day) to the least sedentary (<4 h/day) groups was 1.52 (95% confidence interval: 1.13 to 2.03). There was inconsistent and weak evidence for elevated CVD and all-cause mortality risks with more sitting among those meeting the lower (150 to 299 MVPA min/week) or upper (≥300 MVPA min/week) limits of the MVPA recommendation. Replacing sitting with walking and MVPA showed stronger associations among high sitters (>6 sitting h/day) where, for example, the per-hour CVD mortality HR for sitting replaced with vigorous activity was 0.36 (95% confidence interval: 0.17 to 0.74).
Sitting is associated with all-cause and CVD mortality risk among the least physically active adults; moderate-to-vigorous physical activity doses equivalent to meeting the current recommendations attenuate or effectively eliminate such associations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PURPOSEThe study aims were to compare raw triaxial accelerometer output from ActiGraph GT3X+ (AG) and GENEActiv (GA) placed on the hip and the wrist and to develop regression equations for estimating ...energy expenditure.
METHODSThirty children (7–11 yr) and 30 adults (18–65 yr) completed eight activities (ranging from lying to running) while wearing one AG and one GA on the hip and the wrist. Oxygen consumption (V˙O2) was measured with indirect calorimetry. Analysis involved the use of ANOVA to examine the effect of activity, brand, and placement on the acceleration values, intraclass correlation coefficient to evaluate the agreement between the two brands and placements, and linear regression to establish intensity thresholds.
RESULTSA significant difference in acceleration values between the hip and the wrist placement was found (P < 0.001). The output from the wrist placement was, in general, higher compared with that from the hip. There was no main effect of monitor brand in adults (P < 0.12) and children (P < 0.73), and the intraclass correlation coefficient showed a strong agreement (0.96–0.99). However, a three-way interaction and systematic error between the brands was found in children. Acceleration from both brands and placements showed a strong correlation with V˙O2. The intensity classification accuracy of the developed thresholds for both brands and placements was, in general, higher for adults compared with that for children and was greater for sedentary/light (93%–97%), and vigorous activities (68%–92%) than that for moderate activities (33%–59%).
CONCLUSIONSAccelerometer outputs from AG and GA seem comparable when attached to the same body location in adults, whereas inconsistent differences are apparent between the two brands and placements in children, hence limiting the comparability between brands in this age group.
Summary To implement effective non-communicable disease prevention programmes, policy makers need data for physical activity levels and trends. In this report, we describe physical activity levels ...worldwide with data for adults (15 years or older) from 122 countries and for adolescents (13–15-years-old) from 105 countries. Worldwide, 31·1% (95% CI 30·9–31·2) of adults are physically inactive, with proportions ranging from 17·0% (16·8–17·2) in southeast Asia to about 43% in the Americas and the eastern Mediterranean. Inactivity rises with age, is higher in women than in men, and is increased in high-income countries. The proportion of 13–15-year-olds doing fewer than 60 min of physical activity of moderate to vigorous intensity per day is 80·3% (80·1–80·5); boys are more active than are girls. Continued improvement in monitoring of physical activity would help to guide development of policies and programmes to increase activity levels and to reduce the burden of non-communicable diseases.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Physical inactivity is one of the four leading risk factors for global mortality. Accurate measurement of physical activity (PA) and in particular by physical activity questionnaires (PAQs) remains a ...challenge. The aim of this paper is to provide an updated systematic review of the reliability and validity characteristics of existing and more recently developed PAQs and to quantitatively compare the performance between existing and newly developed PAQs.A literature search of electronic databases was performed for studies assessing reliability and validity data of PAQs using an objective criterion measurement of PA between January 1997 and December 2011. Articles meeting the inclusion criteria were screened and data were extracted to provide a systematic overview of measurement properties. Due to differences in reported outcomes and criterion methods a quantitative meta-analysis was not possible.In total, 31 studies testing 34 newly developed PAQs, and 65 studies examining 96 existing PAQs were included. Very few PAQs showed good results on both reliability and validity. Median reliability correlation coefficients were 0.62-0.71 for existing, and 0.74-0.76 for new PAQs. Median validity coefficients ranged from 0.30-0.39 for existing, and from 0.25-0.41 for new PAQs.Although the majority of PAQs appear to have acceptable reliability, the validity is moderate at best. Newly developed PAQs do not appear to perform substantially better than existing PAQs in terms of reliability and validity. Future PAQ studies should include measures of absolute validity and the error structure of the instrument.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently ...used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus.
The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified.
Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015.
The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific.
This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/+ accelerometer, in order to obtain more valid and comparable data.
CRD42016039991.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
CONTEXT Sparse data exist on the combined associations between physical activity and sedentary time with cardiometabolic risk factors in healthy children. OBJECTIVE To examine the independent and ...combined associations between objectively measured time in moderate- to vigorous-intensity physical activity (MVPA) and sedentary time with cardiometabolic risk factors. DESIGN, SETTING, AND PARTICIPANTS Pooled data from 14 studies between 1998 and 2009 comprising 20 871 children (aged 4-18 years) from the International Children's Accelerometry Database. Time spent in MVPA and sedentary time were measured using accelerometry after reanalyzing raw data. The independent associations between time in MVPA and sedentary time, with outcomes, were examined using meta-analysis. Participants were stratified by tertiles of MVPA and sedentary time. MAIN OUTCOME MEASURES Waist circumference, systolic blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, and insulin. RESULTS Times (mean SD min/d) accumulated by children in MVPA and being sedentary were 30 (21) and 354 (96), respectively. Time in MVPA was significantly associated with all cardiometabolic outcomes independent of sex, age, monitor wear time, time spent sedentary, and waist circumference (when not the outcome). Sedentary time was not associated with any outcome independent of time in MVPA. In the combined analyses, higher levels of MVPA were associated with better cardiometabolic risk factors across tertiles of sedentary time. The differences in outcomes between higher and lower MVPA were greater with lower sedentary time. Mean differences in waist circumference between the bottom and top tertiles of MVPA were 5.6 cm (95% CI, 4.8-6.4 cm) for high sedentary time and 3.6 cm (95% CI, 2.8-4.3 cm) for low sedentary time. Mean differences in systolic blood pressure for high and low sedentary time were 0.7 mm Hg (95% CI, −0.07 to 1.6) and 2.5 mm Hg (95% CI, 1.7-3.3), and for high-density lipoprotein cholesterol, differences were −2.6 mg/dL (95% CI, −1.4 to −3.9) and −4.5 mg/dL (95% CI, −3.3 to −5.6), respectively. Geometric mean differences for insulin and triglycerides showed similar variation. Those in the top tertile of MVPA accumulated more than 35 minutes per day in this intensity level compared with fewer than 18 minutes per day for those in the bottom tertile. In prospective analyses (N = 6413 at 2.1 years’ follow-up), MVPA and sedentary time were not associated with waist circumference at follow-up, but a higher waist circumference at baseline was associated with higher amounts of sedentary time at follow-up. CONCLUSION Higher MVPA time by children and adolescents was associated with better cardiometabolic risk factors regardless of the amount of sedentary time.
Summary Background High amounts of sedentary behaviour have been associated with increased risks of several chronic conditions and mortality. However, it is unclear whether physical activity ...attenuates or even eliminates the detrimental effects of prolonged sitting. We examined the associations of sedentary behaviour and physical activity with all-cause mortality. Methods We did a systematic review, searching six databases (PubMed, PsycINFO, Embase, Web of Science, Sport Discus, and Scopus) from database inception until October, 2015, for prospective cohort studies that had individual level exposure and outcome data, provided data on both daily sitting or TV-viewing time and physical activity, and reported effect estimates for all-cause mortality, cardiovascular disease mortality, or breast, colon, and colorectal cancer mortality. We included data from 16 studies, of which 14 were identified through a systematic review and two were additional unpublished studies where pertinent data were available. All study data were analysed according to a harmonised protocol, which categorised reported daily sitting time and TV-viewing time into four standardised groups each, and physical activity into quartiles (in metabolic equivalent of task MET-hours per week). We then combined data across all studies to analyse the association of daily sitting time and physical activity with all-cause mortality, and estimated summary hazard ratios using Cox regression. We repeated these analyses using TV-viewing time instead of daily sitting time. Findings Of the 16 studies included in the meta-analysis, 13 studies provided data on sitting time and all-cause mortality. These studies included 1 005 791 individuals who were followed up for 2–18·1 years, during which 84 609 (8·4%) died. Compared with the referent group (ie, those sitting <4 h/day and in the most active quartile >35·5 MET-h per week), mortality rates during follow-up were 12–59% higher in the two lowest quartiles of physical activity (from HR=1·12, 95% CI 1·08–1·16, for the second lowest quartile of physical activity <16 MET-h per week and sitting <4 h/day; to HR=1·59, 1·52–1·66, for the lowest quartile of physical activity <2·5 MET-h per week and sitting >8 h/day). Daily sitting time was not associated with increased all-cause mortality in those in the most active quartile of physical activity. Compared with the referent (<4 h of sitting per day and highest quartile of physical activity >35·5 MET-h per week), there was no increased risk of mortality during follow-up in those who sat for more than 8 h/day but who also reported >35·5 MET-h per week of activity (HR=1·04; 95% CI 0·99–1·10). By contrast, those who sat the least (<4 h/day) and were in the lowest activity quartile (<2·5 MET-h per week) had a significantly increased risk of dying during follow-up (HR=1·27, 95% CI 1·22–1·31). Six studies had data on TV-viewing time (N=465 450; 43 740 deaths). Watching TV for 3 h or more per day was associated with increased mortality regardless of physical activity, except in the most active quartile, where mortality was significantly increased only in people who watched TV for 5 h/day or more (HR=1·16, 1·05–1·28). Interpretation High levels of moderate intensity physical activity (ie, about 60–75 min per day) seem to eliminate the increased risk of death associated with high sitting time. However, this high activity level attenuates, but does not eliminate the increased risk associated with high TV-viewing time. These results provide further evidence on the benefits of physical activity, particularly in societies where increasing numbers of people have to sit for long hours for work and may also inform future public health recommendations. Funding None.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In the past few decades, the field of physical activity has grown and evolved in scope, depth, visibility and impact around the world. Global progress has been observed in research and practice in ...physical activity regarding surveillance, health outcomes, correlates/determinants, interventions, translation and policy. The 2012 and 2016
series on physical activity provide some of the most comprehensive global analysis on various topics within physical activity. Based on the
series and other key developments in the field, literature searches, and expert group meetings and consultation, we provide a global summary on the progress of, gaps in and future directions for physical activity research in the following areas: (1) surveillance and trends, (2) correlates and determinants, (3) health outcomes and (4) interventions, programmes and policies. Besides lessons learnt within each specific area, several recommendations are shared across areas of research, including improvement in measurement, applying a global perspective with a growing emphasis on low-income and middle-income countries, improving inclusiveness and equity in research, making translation an integral part of research for real-world impact, taking an 'upstream' public health approach, and working across disciplines and sectors to co-design research and co-create solutions. We have summarised lessons learnt and recommendations for future research as 'roadmaps' in progress to encourage moving the field of physical activity towards achieving population-level impact globally.
In a registry-based randomized clinical trial, 6629 patients with suspected acute myocardial infarction who did not have hypoxemia were assigned to either supplemental oxygen or ambient air. ...Supplemental oxygen did not reduce all-cause mortality at 1 year.
Abstract Background A 1-h algorithm based on high-sensitivity cardiac troponin T (hs-cTnT) testing at presentation and again 1 h thereafter has been shown to accurately rule out acute myocardial ...infarction. Objectives The goal of the study was to evaluate the diagnostic accuracy of the 1-h algorithm when supplemented with patient history and an electrocardiogram (ECG) (the extended algorithm) for predicting 30-day major adverse cardiac events (MACE) and to compare it with the algorithm using hs-cTnT alone (the troponin algorithm). Methods This prospective observational study enrolled consecutive patients presenting to the emergency department (ED) with chest pain, for whom hs-cTnT testing was ordered at presentation. Hs-cTnT results at 1 h and the ED physician’s assessments of patient history and ECG were collected. The primary outcome was an adjudicated diagnosis of 30-day MACE defined as acute myocardial infarction, unstable angina, cardiogenic shock, ventricular arrhythmia, atrioventricular block, cardiac arrest, or death of a cardiac or unknown cause. Results In the final analysis, 1,038 patients were included. The extended algorithm identified 60% of all patients for rule-out and had a higher sensitivity than the troponin algorithm (97.5% vs. 87.6%; p < 0.001). The negative predictive value was 99.5% and the likelihood ratio was 0.04 with the extended algorithm versus 97.8% and 0.17, respectively, with the troponin algorithm. The extended algorithm ruled-in 14% of patients with a higher sensitivity (75.2% vs. 56.2%; p < 0.001) but a slightly lower specificity (94.0% vs. 96.4%; p < 0.001) than the troponin algorithm. The rule-in arms of both algorithms had a likelihood ratio >10. Conclusions A 1-h combination algorithm allowed fast rule-out and rule-in of 30-day MACE in a majority of ED patients with chest pain and performed better than the troponin-alone algorithm.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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