240 research outputs found
Statistical analysis of daily seismic event rate as a precursor to volcanic eruptions
Full text linkWe analyse time series of daily seismic event rate for the Kilauea, Hawaii, volcano between 1959 and 2000. Individual eruptions are not always preceded by an increase in event rate, and many increases in event rate do not lead to eruption. However, a mean field accelerating behaviour does emerge 10–15 days before eruption in data stacked in phase with the eruption time. In phase space the pre-eruptive dynamics is well defined by Voight's [1988] equation, but so is that of the seismicity in the period between eruptions. We conclude that the underlying dynamics of the 'background' seismicity is similar to that of magma eruption. We use Bayesian methods to compare different time-to-failure models that have been suggested for precursors. Only a short-term forecast can be achieved, using a linear fit to inverse rate
The epigenetic clock and objectively measured sedentary and walking behavior in older adults: The Lothian Birth Cohort 1936
Full text linkBackground: Estimates of biological age derived from DNA-methylation patterns-known as the epigenetic clock-are associated with mortality, physical and cognitive function, and frailty, but little is known about their relationship with sedentary behavior or physical activity. We investigated the cross-sectional relationship between two such estimates of biological age and objectively measured sedentary and walking behavior in older people. Methods: Participants were 248 members of the Lothian Birth Cohort 1936. At age 79 years, sedentary behavior and physical activity were measured over 7 days using an activPAL activity monitor. Biological age was estimated using two measures of DNA methylation-based age acceleration-i.e., extrinsic and intrinsic epigenetic age acceleration. We used linear regression to assess the relationship between these two estimates of biological age and average daily time spent sedentary, number of sit-to-stand transitions, and step count. Results: Of the six associations examined, only two were statistically significant in initial models adjusted for age and sex alone. Greater extrinsic age acceleration was associated with taking fewer steps (regression coefficient (95% CI) - 0.100 (- 0.008, - 0.001), and greater intrinsic age acceleration was associated with making more sit-to-stand transitions (regression coefficient (95% CI) 0.006 (0.0001, 0.012). When we controlled for multiple statistical testing, neither of these associations survived correction (both P ≥ 0.17). Conclusion: In this cross-sectional study of 79-year-olds, we found no convincing evidence that biological age, as indexed by extrinsic or intrinsic epigenetic age acceleration, was associated with objectively measured sedentary or walking behavior.</p
Attitudes to ageing and objectively-measured sedentary and walking behaviour in older people:The Lothian Birth Cohort 1936
Full text linkBackground: Prolonged sitting and low activity—both common in older people--are associated with increased mortality and poorer health. Whether having a more negative attitude to ageing is associated with higher levels of these behaviours is unclear. Objective: We investigated the prospective relationship between attitudes to ageing and objectively measured sedentary and walking behaviour.Methods: Participants were 271 members of the Lothian Birth Cohort 1936. At age 72 years, participants completed the Attitudes to Ageing Questionnaire which assesses attitudes on three domains--Psychosocial loss, Physical change and Psychological growth. At age 79 years, participants wore an activPAL activity monitor for seven days. The outcome measures were average daily time spent sedentary, number of sit-to-stand transitions, and step count.Results: There were no significant associations between any of the Attitude to Ageing domain scores and time spent sedentary or number of sit-to-stand transitions. In sex-adjusted analysis, having a more positive attitude to ageing as regards Physical change was associated with a slightly higher daily step count, for a SD increment in score, average daily step count was greater by 1.5% (95% CI 0.6%, 2.4%). On further adjustment for potential confounding factors these associations were no longer significant. Conclusion: We found no evidence that attitudes to ageing at age 72 were predictive of sedentary or walking behaviour seven years later. Future studies should examine whether attitudes to ageing are associated with objectively measured walking or sedentary behaviour at the same point in time. The existence of such an association could inform the development of interventions
TASST framework.
No full textReproduced from Fig 1 Dall PM, Coulter EH, Fitzsimons CF, Skelton DA, Chastin SFM, on behalf of the Seniors USP Team. The TAxonomy of Self-reported Sedentary behaviour Tools (TASST) framework for development, comparison and evaluation of self-report tools: content analysis and systematic review. BMJ Open 2017;7:e013844 [9].</p
The scatter of time-delays in shear-wave splitting above small earthquakes
Full text linkMeasurements of time-delays in seismic shear-wave splitting above small earthquakes typically display a scatter of often as much as ±80 per cent about the mean. Changes in the average time-delay appear to be related to changes of stress, but applications of this potentially powerful tool have been handicapped by the previously inexplicable scatter in time-delays above earthquakes. In contrast, measurements of shear-wave time-delays in controlled-source exploration seismics are typically well controlled and display little scatter. Previous estimates of possible causes of scatter cannot produce sufficient variation specifically above earthquakes. Here we show that 90°-flips in shear-wave polarizations due to fluctuating high pore-fluid pressures on seismically-active fault planes are the most likely cause of the scatter
Positive and negative well-being and objectively measured sedentary behaviour in older adults: evidence from three cohorts
Full text linkBackground:
Sedentary behaviour is related to poorer health independently of time spent in moderate to vigorous physical activity. The aim of this study was to investigate whether wellbeing or symptoms of anxiety or depression predict sedentary behaviour in older adults.
Method:
Participants were drawn from the Lothian Birth Cohort 1936 (LBC1936) (n = 271), and the West of Scotland Twenty-07 1950s (n = 309) and 1930s (n = 118) cohorts. Sedentary outcomes, sedentary time, and number of sit-to-stand transitions, were measured with a three-dimensional accelerometer (activPAL activity monitor) worn for 7 days. In the Twenty-07 cohorts, symptoms of anxiety and depression were assessed in 2008 and sedentary outcomes were assessed ~ 8 years later in 2015 and 2016. In the LBC1936 cohort, wellbeing and symptoms of anxiety and depression were assessed concurrently with sedentary behaviour in 2015 and 2016. We tested for an association between wellbeing, anxiety or depression and the sedentary outcomes using multivariate regression analysis.
Results:
We observed no association between wellbeing or symptoms of anxiety and the sedentary outcomes. Symptoms of depression were positively associated with sedentary time in the LBC1936 and Twenty-07 1950s cohort, and negatively associated with number of sit-to-stand transitions in the LBC1936. Meta-analytic estimates of the association between depressive symptoms and sedentary time or number of sit-to-stand transitions, adjusted for age, sex, BMI, long-standing illness, and education, were β = 0.11 (95% CI = 0.03, 0.18) and β = − 0.11 (95% CI = − 0.19, −0.03) respectively.
Conclusion:
Our findings indicate that depressive symptoms are positively associated with sedentary behavior. Future studies should investigate the causal direction of this association
Author Correction: Attributes and predictors of long COVID
Full text linkIn the version of this article initially published, linkage of the following authors to affiliation 3 (Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK) was incorrect: Benjamin Murray, Thomas Varsavsky, Mark S. Graham, Kerstin Klaser, Michela Antonelli, Liane S. Canas, Erika Molteni, Marc Modat, M. Jorge Cardoso and Sebastien Ourselin. The correct linkage is to affiliation 1 (School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK). The error has been corrected in the HTML and PDF versions of the article
Does dynamic tailoring of a narrative-driven exergame result in higher user engagement among adolescents? results from a cluster-randomized controlled trial
Full text linkPhysical activity interventions for youth are direly needed given low adherence to physical activity guidelines, but many interventions suffer from low user engagement. Exergames that require bodily movement while played may provide an engaging form of physical activity intervention but are not perceived as engaging to all. This study aimed to evaluate whether dynamic tailoring in a narrative-driven mobile exergame for adolescents played in leisure settings, can create higher user engagement compared to a non-tailored exergame. A cluster-randomized controlled trial assessed differences in user engagement between a dynamically tailored (based on an accel-erometer sensor integrated in a T-shirt) and non-tailored condition. In total, 94 participants (M age = 14.61 ± 0.1.93; 35% female) participated and were assigned to one of the two conditions. User engagement was measured via a survey and game metric data. User engagement was low in both conditions. Narrative sensation was higher in the dynamically tailored condition, but the non-tai-lored condition showed longer play-time. User suggestions to create a more appealing game included simple and more colorful graphics, avoiding technical problems, more variety and shorter missions and multiplayer options. Less cumbersome or more attractive sensing options than the smart T-shirt may offer a more engaging solution, to be tested in future research.</p
Dynamics of sedentary behaviours and systems-based approach : future challenges and opportunities in the life course epidemiology of sedentary behaviours
Full text linkThis chapter challenges our current thinking about sedentary behaviours and offers new paradigms to move forward to understand the complex nature of sedentary behaviours and their determinants. Sedentary behaviours are ubiquitous and changing in nature over time: with advances in media and IT, TV time is decreasing, but overall screen time is growing. Understanding the non-linear temporal dynamics of sedentary behaviours and how people accumulate, or break, sitting time appears a crucial step to design innovative strategies. Since multiple factors at different levels (proximal, distal) are interacting to drive sedentary time, new perspectives combining a life course perspective and complexity science are needed. Systems-based approach and adaptive dynamical systems modelling will help model the interaction between factors and feedback loops. A systems-based framework for the study of sedentary behaviours called SOS (Systems of Sedentary behaviours) has been established by a transdisciplinary research group within the framework of the European DEDIPAC Knowledge Hub. Novel methods of enquiry are required to progress the field, including methodologies for analysis such as probabilistic modelling techniques (Bayesian networks), simulation studies investigating different scenarios of possible societal changes and their effect on sedentary behaviours, and innovations in measuring accurately other dimensions such as context and type of sedentary behaviours. Finally, future opportunities for innovative data collection and analysis (big data) and innovative interventions (natural experiments, solutionist, and participatory approach) are highlighted for their potential to benefit sedentary behaviours research and work more efficiently towards public health solutions to tackle this new threat of modern life
Author Correction: Attributes and predictors of long COVID
No full textIn the version of this article initially published, linkage of the following authors to affiliation 3 (Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK) was incorrect: Benjamin Murray, Thomas Varsavsky, Mark S. Graham, Kerstin Klaser, Michela Antonelli, Liane S. Canas, Erika Molteni, Marc Modat, M. Jorge Cardoso and Sebastien Ourselin. The correct linkage is to affiliation 1 (School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK). The error has been corrected in the HTML and PDF versions of the article.</p
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