Dataset Information

Time spent cycling, walking, running, standing and sedentary: a cross-sectional analysis of accelerometer-data from 1670 adults in the Copenhagen City Heart Study : Physical behaviours among 1670 Copenhageners.

ABSTRACT: BACKGROUND:Information about how much time adults spend cycling, walking and running can be used for planning and evaluating initiatives for active, healthy societies. The objectives of this study were to describe how much time adult Copenhageners cycle, walk, run, stand and spend sedentary using accelerometers, and to describe differences between population groups. METHODS:In the fifth examination of the Copenhagen City Heart Study, 2335 individuals gave consent to wear accelerometers (skin-attached; right thigh and iliac crest; 24?h/day, 7 consecutive days) of which 1670 fulfilled our inclusion criteria (?16?h/day for ?5?days; median wear time: 23.8?h/day). Daily time spent cycling, walking, running, standing and sedentary was derived from accelerometer-based data using the Acti4 software, and differences between sex, age groups, level of education and BMI were investigated using Kruskal-Wallis rank sum tests. RESULTS:Among those cycling (61%), the median cycling time was 8.3?min/day. The median time walking, running, standing and sedentary was 82.6, 0.1, 182.5 and 579.1?min/day, respectively. About 88% walked fast (i.e., ?100 steps/min) ?30?min/day. The shortest duration and lowest prevalence of cycling, walking and running were found among older individuals, those with a low level of education, and individuals being overweight or obese. CONCLUSIONS:We found a long duration and high prevalence of cycling and walking, but also that many adult Copenhageners spent much time sedentary. Population groups with low participation in physical activities such as cycling and walking should be targeted in future initiatives towards an active, healthy society.

SUBMITTER: Johansson MS

PROVIDER: S-EPMC6814105 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Time spent cycling, walking, running, standing and sedentary: a cross-sectional analysis of accelerometer-data from 1670 adults in the Copenhagen City Heart Study : Physical behaviours among 1670 Copenhageners.

Johansson Melker Staffan MS Korshøj Mette M Schnohr Peter P Marott Jacob Louis JL Prescott Eva Irene Bossano EIB Søgaard Karen K Holtermann Andreas A

BMC public health 20191024 1

<h4>Background</h4>Information about how much time adults spend cycling, walking and running can be used for planning and evaluating initiatives for active, healthy societies. The objectives of this study were to describe how much time adult Copenhageners cycle, walk, run, stand and spend sedentary using accelerometers, and to describe differences between population groups.<h4>Methods</h4>In the fifth examination of the Copenhagen City Heart Study, 2335 individuals gave consent to wear accelerom ...[more]

PMID: 31651272

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Project description:PURPOSE:Environmental perceptions and psychological measures appear to be associated with walking and cycling behaviour; however, their influence is still unclear. We assessed these associations using baseline data from a quasi-experimental cohort study of the effects of major transport infrastructural developments in Cambridge, UK. METHODS:Postal surveys were sent to adults who travel to work in Cambridge (n = 1582). Questions asked about travel modes and time spent travelling to and from work in the last week, perceptions of the route, psychological measures regarding car use and socio-demographic characteristics. Participants were classified into one of two categories according to time spent walking for commuting ('no walking' or 'some walking') and one of three categories for cycling ('no cycling', '1-149 min/wk' and ' ? 150 min/wk'). RESULTS:Of the 1164 respondents (68% female, mean (SD) age: 42.3 (11.4) years) 30% reported any walking and 53% reported any cycling to or from work. In multiple regression models, short distance to work and not having access to a car showed strong positive associations with both walking and cycling. Furthermore, those who reported that it was pleasant to walk were more likely to walk to or from work (OR = 4.18, 95% CI 3.02 to 5.78) and those who reported that it was convenient to cycle on the route between home and work were more likely to do so (1-149 min/wk: OR = 4.60, 95% CI 2.88 to 7.34; ? 150 min/wk: OR = 3.14, 95% CI 2.11 to 4.66). Positive attitudes in favour of car use were positively associated with time spent walking to or from work but negatively associated with cycling to or from work. Strong perceived behavioural control for car use was negatively associated with walking. CONCLUSIONS:In this relatively affluent sample of commuters, a range of individual and household characteristics, perceptions of the route environment and psychological measures relating to car use were associated with walking or cycling to and from work. Taken together, these findings suggest that social and physical contexts of travel decision-making should be considered and that a range of influences may require to be addressed to bring about behaviour change.

Project description:BackgroundThe evidence for the prospective relationships between specific physical activities (PA), sedentary behaviours (SB) and sleep on subsequent total PA levels is scarce. The purpose of this study was to examine prospective associations of self-reported PA, SB and sleep, and changes in these with subsequent accelerometer-measured PA.MethodsA sub-sample of 91,648 UK Biobank participants reported moderate-to-vigorous PA (MVPA), lifestyle activities, TV viewing, computer use and sleep through screen-based questionnaires at baseline (2006-2010), and provided valid accelerometry data (dominant wrist-worn for 7 days between 2013 and 2015). A further sub-sample of 7709 participants repeated the screen-based questionnaires between 2012 and 2013.ResultsIn both women (n = 51,545) and men (n = 40,103), positive associations were observed between all self-reported measures of PA at baseline (MVPA, lifestyle/job-related activities, active transporting modes) and accelerometer-measured PA levels at follow-up (median 5.7 years); an exception was 'walking/standing at work' in women. Sedentary time at work, TV viewing and computer use were inversely associated with PA at follow-up. Sleeping either more or less than 7 h/day at baseline was associated with lower PA at follow-up (except for ≤6 h/day in men). In the repeat self-report sub-sample (median 4.3 years), relatively higher physical activity at follow-up was observed in those who maintained or achieved favourable levels of MVPA, walking for pleasure, strenuous sports, other exercises, heavy DIY (in women), heavy physical work, and walking/standing at work (in women), sedentary time at work, getting about methods (in women), commuting methods (in women), TV viewing, computer use or sleep.ConclusionsInitial levels of PA, SB and sleep, and changes in these variables were generally associated with subsequent accelerometer-measured PA in the expected directions, suggesting these specific behaviours all contribute to the total volume of physical activity over time and could thus be targets for intervention.

Project description:BackgroundConsiderable effort has been devoted to mapping the functional and effective connectivity of the human brain, but these efforts have largely been limited to tasks involving stationary subjects. Recent advances with high-density electroencephalography (EEG) and Independent Components Analysis (ICA) have enabled study of electrocortical activity during human locomotion. The goal of this work was to measure the effective connectivity of cortical activity during human standing and walking.MethodsWe recorded 248-channels of EEG as eight young healthy subjects stood and walked on a treadmill both while performing a visual oddball discrimination task and not performing the task. ICA parsed underlying electrocortical, electromyographic, and artifact sources from the EEG signals. Inverse source modeling methods and clustering algorithms localized posterior, anterior, prefrontal, left sensorimotor, and right sensorimotor clusters of electrocortical sources across subjects. We applied a directional measure of connectivity, conditional Granger causality, to determine the effective connectivity between electrocortical sources.ResultsConnections involving sensorimotor clusters were weaker for walking than standing regardless of whether the subject was performing the simultaneous cognitive task or not. This finding supports the idea that cortical involvement during standing is greater than during walking, possibly because spinal neural networks play a greater role in locomotor control than standing control. Conversely, effective connectivity involving non-sensorimotor areas was stronger for walking than standing when subjects were engaged in the simultaneous cognitive task.ConclusionsOur results suggest that standing results in greater functional connectivity between sensorimotor cortical areas than walking does. Greater cognitive attention to standing posture than to walking control could be one interpretation of that finding. These techniques could be applied to clinical populations during gait to better investigate neural substrates involved in mobility disorders.

Project description:This study aimed to examine the validity and accuracy of wrist accelerometers for classifying sedentary behavior (SB) in children.Fifty-seven children (5-8 and 9-12 yr) completed an ~170-min protocol, including 15 semistructured activities and transitions. Nine ActiGraph (GT3X+) and two GENEActiv wrist cut points were evaluated. Direct observation was the criterion measure. The accuracy of wrist cut points was compared with that achieved by the ActiGraph hip cut point (?25 counts per 15 s) and the thigh-mounted activPAL3. Analyses included equivalence testing, Bland-Altman procedures, and area under the receiver operating curve (ROC-AUC).The most accurate ActiGraph wrist cut points (Kim; vector magnitude, ?3958 counts per 60 s; vertical axis, ?1756 counts per 60 s) demonstrated good classification accuracy (ROC-AUC = 0.85-0.86) and accurately estimated SB time in 5-8 yr (equivalence P = 0.02; mean bias = 4.1%, limits of agreement = -20.1% to 28.4%) and 9-12 yr (equivalence P < 0.01; -2.5%, -27.9% to 22.9%). The mean bias of SB time estimates from Kim were smaller than ActiGraph hip (5-8 yr: 15.8%, -5.7% to 37.2%; 9-12 yr: 17.8%, -3.9% to 39.5%) and similar to or smaller than activPAL3 (5-8 yr: 12.6%, -39.8% to 14.7%; 9-12 yr: -1.4%, -13.9% to 11.0%), although classification accuracy was similar to ActiGraph hip (ROC-AUC = 0.85) but lower than activPAL3 (ROC-AUC = 0.92-0.97). Mean bias (5-8 yr: 6.5%, -16.1% to 29.1%; 9-12 yr: 10.5%, -13.6% to 34.6%) for the most accurate GENEActiv wrist cut point (Schaefer: ?0.19 g) was smaller than ActiGraph hip, and activPAL3 in 5-8 yr, but larger than activPAL3 in 9-12 yr. However, SB time estimates from Schaefer were not equivalent to direct observation (equivalence P > 0.05) and classification accuracy (ROC-AUC = 0.79-0.80) was lower than for ActiGraph hip and activPAL3.The most accurate SB ActiGraph (Kim) and GENEActiv (Schaefer) wrist cut points can be applied in children with similar confidence as the ActiGraph hip cut point (?25 counts per 15 s), although activPAL3 was generally more accurate.

Dataset Information

Time spent cycling, walking, running, standing and sedentary: a cross-sectional analysis of accelerometer-data from 1670 adults in the Copenhagen City Heart Study : Physical behaviours among 1670 Copenhageners.

Publications

Time spent cycling, walking, running, standing and sedentary: a cross-sectional analysis of accelerometer-data from 1670 adults in the Copenhagen City Heart Study : Physical behaviours among 1670 Copenhageners.

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