The Potential Impact of Displacing Sedentary Time in Adults with Type 2 Diabetes.

This is the final published version. Available from Lippincott, Williams & Wilkins via the DOI in this record.PURPOSE: Sedentary time, in particular, prolonged unbroken sedentary time, is detrimental to health and displaces time spent in either light or moderate intensity physical activity. This cross-sectional study aimed to identify the potential impact of reallocating time from sedentary behaviors to more active behaviors on measures of body composition and metabolic health in people with type 2 diabetes. METHODS: Participants were 519 adults with newly diagnosed type 2 diabetes who had been recruited to the Early Activity in Diabetes (Early ACTID) randomized controlled trial. Waist-worn accelerometers were used to obtain objective measurement of sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) at baseline alongside clinical measurements and fasting blood samples to determine cholesterol, triglycerides, HOMA-IR, and glucose. Isotemporal substitution modeling was performed to determine the potential impact of reallocating 30 min of sedentary time accumulated in a single bout (long bout) with 30 min of interrupted sedentary time, LPA, or MVPA. RESULTS: Sedentary time accounted for 65% of the waking day, of which 45% was accumulated in prolonged (≥30 min) bouts. Reallocation of 30 min of long-bout sedentary time with 30 min of short-bout sedentary time was associated with lower body mass index (BMI) (adjusted β, -0.60; 95% confidence interval [CI], -1.00, -0.21) and waist circumference (WC) (adjusted β, -1.16; 95% CI, -2.08, -0.25). Stronger effects were seen for LPA and MVPA. Reallocation of 30 min of long-bout sedentary time with LPA was associated with higher HDL-cholesterol (adjusted β, 0.02; 95% CI, 0.00-0.03 mmol·L). CONCLUSIONS: Encouraging adults with newly diagnosed type 2 diabetes to break up prolonged periods of sedentary time may be an effective strategy for improving body composition and metabolic health.National Institute for Health Research (NIHR

Socioeconomic position and childhood sedentary time: evidence from the PEACH project.

notes: PMCID: PMC3844440© 2013 Pulsford et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Associations between socioeconomic position (SEP) and sedentary behaviour in children are unclear. Existing studies have used aggregate measures of weekly sedentary time that could mask important differences in the relationship between SEP and sedentary time at different times of the day or between weekdays and weekend days. These studies have also employed a variety of measures of SEP which may be differentially associated with sedentary time. This paper examines associations of multiple indicators of SEP and accelerometer-measured, temporally specific, sedentary time in school children.National Prevention Research InitiativeWorld Cancer Research Fund (WCRF UK

An Exact Formula for the Average Run Length to False Alarm of the Generalized Shiryaev-Roberts Procedure for Change-Point Detection under Exponential Observations

We derive analytically an exact closed-form formula for the standard minimax Average Run Length (ARL) to false alarm delivered by the Generalized Shiryaev-Roberts (GSR) change-point detection procedure devised to detect a shift in the baseline mean of a sequence of independent exponentially distributed observations. Specifically, the formula is found through direct solution of the respective integral (renewal) equation, and is a general result in that the GSR procedure's headstart is not restricted to a bounded range, nor is there a "ceiling" value for the detection threshold. Apart from the theoretical significance (in change-point detection, exact closed-form performance formulae are typically either difficult or impossible to get, especially for the GSR procedure), the obtained formula is also useful to a practitioner: in cases of practical interest, the formula is a function linear in both the detection threshold and the headstart, and, therefore, the ARL to false alarm of the GSR procedure can be easily computed.Comment: 9 pages; Accepted for publication in Proceedings of the 12-th German-Polish Workshop on Stochastic Models, Statistics and Their Application

"I've made this my lifestyle now": a prospective qualitative study of motivation for lifestyle change among people with newly diagnosed type two diabetes mellitus

This is the final published version. Available from BMC via the DOI in this record.The datasets generated and/or analysed during the current study are not publicly available due to the level of personal information that is contained in the qualitative transcripts.Background: Diagnosis with Type 2 Diabetes is an opportunity for individuals to change their physical activity and dietary behaviours. Diabetes treatment guidelines recommend theory-based, patient-centred care and advocate the provision of support for patient motivation but the motivational experiences of people newly diagnosed with diabetes have not been well studied. Framed in self-determination theory, this study aimed to qualitatively explore how this patient group articulate and experience different types of motivation when attempting lifestyle change. Methods: A secondary analysis of semi-structured interview data collected with 30 (n female = 18, n male = 12) adults who had been newly diagnosed with type two diabetes and were participants in the Early ACTID trial was undertaken. Deductive directed content analysis was performed using NVivo V10 and researcher triangulation to identify and describe patient experiences and narratives that reflected the motivation types outlined in selfdetermination theory and if/how these changed over time. Results: The findings revealed the diversity in motivation quality both between and within individuals over time and that patients with newly-diagnosed diabetes have multifaceted often competing motivations for lifestyle behaviour change. Applying self-determination theory, we identified that many participants reported relatively dominant controlled motivation to comply with lifestyle recommendations, avoid their non-compliance being “found out” or supress guilt following lapses in behaviour change attempts. Such narratives were accompanied by experiences of frustrating slow behaviour change progress. More autonomous motivation was expressed as something often achieved over time and reflected goals to improve health, quality of life or family time. Motivational internalisation was evident and some participants had integrated their behaviour change to a new way of life which they found resilient to common barriers. Conclusions: Motivation for lifestyle change following diagnosis with type two diabetes is complex and can be relatively low in self-determination. To achieve the patient empowerment aspirations of current national health care plans, intervention developers, and clinicians would do well to consider the quality not just quantity of their patients’ motivation.National Institute for Health Research (NIHR

The effect of moving to East Village, the former London 2012 Olympic and Paralympic Games Athletes' Village, on mode of travel (ENABLE London study, a natural experiment)

Background Interventions to encourage active modes of travel (walking, cycling) may improve physical activity levels, but longitudinal evidence is limited and major change in the built environment / travel infrastructure may be needed. East Village (the former London 2012 Olympic Games Athletes Village) has been repurposed on active design principles with improved walkability, open space and public transport and restrictions on residential car parking. We examined the effect of moving to East Village on adult travel patterns. Methods One thousand two hundred seventy-eight adults (16+ years) seeking to move into social, intermediate, and market-rent East Village accommodation were recruited in 2013–2015, and followed up after 2 years. Individual objective measures of physical activity using accelerometry (ActiGraph GT3X+) and geographic location using GPS travel recorders (QStarz) were time-matched and a validated algorithm assigned four travel modes (walking, cycling, motorised vehicle, train). We examined change in time spent in different travel modes, using multilevel linear regresssion models adjusting for sex, age group, ethnicity, housing group (fixed effects) and household (random effect), comparing those who had moved to East Village at follow-up with those who did not. Results Of 877 adults (69%) followed-up, 578 (66%) provided valid accelerometry and GPS data for at least 1 day (≥540 min) at both time points; half had moved to East Village. Despite no overall effects on physical activity levels, sizeable improvements in walkability and access to public transport in East Village resulted in decreased daily vehicle travel (8.3 mins, 95%CI 2.5,14.0), particularly in the intermediate housing group (9.6 mins, 95%CI 2.2,16.9), and increased underground travel (3.9 mins, 95%CI 1.2,6.5), more so in the market-rent group (11.5 mins, 95%CI 4.4,18.6). However, there were no effects on time spent walking or cycling

Accretion, Primordial Black Holes and Standard Cosmology

Primordial Black Holes evaporate due to Hawking radiation. We find that the evaporation time of primordial black holes increase when accretion of radiation is included.Thus depending on accretion efficiency more and more number of primordial black holes are existing today, which strengthens the idea that the primordial black holes are the proper candidate for dark matter.Comment: 11 pages, 3 figure

Sedentary time and markers of inflammation in people with newly diagnosed type 2 diabetes

This is the final version. Available on open access from Elsevier via the DOI in this recordBACKGROUND AND AIMS: We investigated whether objectively measured sedentary time was associated with markers of inflammation in adults with newly diagnosed type 2 diabetes. METHODS AND RESULTS: We studied 285 adults (184 men, 101 women, mean age 59.0 ± 9.7) who had been recruited to the Early ACTivity in Diabetes (Early ACTID) randomised controlled trial. C-reactive protein (CRP), adiponectin, soluble intracellular adhesion molecule-1 (sICAM-1), interleukin-6 (IL-6), and accelerometer-determined sedentary time and moderate-vigorous physical activity (MVPA) were measured at baseline and after six-months. Linear regression analysis was used to investigate the independent cross-sectional and longitudinal associations of sedentary time with markers of inflammation. At baseline, associations between sedentary time and IL-6 were observed in men and women, an association that was attenuated following adjustment for waist circumference. After 6 months of follow-up, sedentary time was reduced by 0.4 ± 1.2 h per day in women, with the change in sedentary time predicting CRP at follow-up. Every hour decrease in sedentary time between baseline and six-months was associated with 24% (1, 48) lower CRP. No changes in sedentary time between baseline and 6 months were seen in men. CONCLUSIONS: Higher sedentary time is associated with IL-6 in men and women with type 2 diabetes, and reducing sedentary time is associated with improved levels of CRP in women. Interventions to reduce sedentary time may help to reduce inflammation in women with type 2 diabetes.National Institute for Health Research (NIHR

Survival of Lactobacillus sakei during heating, drying and storage in the dried state when growth has occurred in the presence of sucrose or monosodium glutamate

Spray-dried cells of Lactobacillus sakei CTC 494 survived ca. 60% longer in the spray dried state when cells were grown in the presence of 20 g sucrose l)1 or 12.5 g monosodium glutamate l)1. No significant differences were observed in viability during storage in the freeze dried state with the addition of these compounds to the growth medium, nor in survival during a heat treatment (55ºC). Both sucrose and glutamate in the growth medium suppressed intracellular accumulation of total amino acids and changed the overall pattern of the individual amino acids. Glutamate in the growth medium enhanced intracellular glutamate by ca. 38

An open-source tool to identify active travel from hip-worn accelerometer, GPS and GIS data.

BACKGROUND: Increases in physical activity through active travel have the potential to have large beneficial effects on populations, through both better health outcomes and reduced motorized traffic. However accurately identifying travel mode in large datasets is problematic. Here we provide an open source tool to quantify time spent stationary and in four travel modes(walking, cycling, train, motorised vehicle) from accelerometer measured physical activity data, combined with GPS and GIS data. METHODS: The Examining Neighbourhood Activities in Built Living Environments in London study evaluates the effect of the built environment on health behaviours, including physical activity. Participants wore accelerometers and GPS receivers on the hip for 7 days. We time-matched accelerometer and GPS, and then extracted data from the commutes of 326 adult participants, using stated commute times and modes, which were manually checked to confirm stated travel mode. This yielded examples of five travel modes: walking, cycling, motorised vehicle, train and stationary. We used this example data to train a gradient boosted tree, a form of supervised machine learning algorithm, on each data point (131,537 points), rather than on journeys. Accuracy during training was assessed using five-fold cross-validation. We also manually identified the travel behaviour of both 21 participants from ENABLE London (402,749 points), and 10 participants from a separate study (STAMP-2, 210,936 points), who were not included in the training data. We compared our predictions against this manual identification to further test accuracy and test generalisability. RESULTS: Applying the algorithm, we correctly identified travel mode 97.3% of the time in cross-validation (mean sensitivity 96.3%, mean active travel sensitivity 94.6%). We showed 96.0% agreement between manual identification and prediction of 21 individuals' travel modes (mean sensitivity 92.3%, mean active travel sensitivity 84.9%) and 96.5% agreement between the STAMP-2 study and predictions (mean sensitivity 85.5%, mean active travel sensitivity 78.9%). CONCLUSION: We present a generalizable tool that identifies time spent stationary and time spent walking with very high precision, time spent in trains or vehicles with good precision, and time spent cycling with moderate precisionIn studies where both accelerometer and GPS data are available this tool complements analyses of physical activity, showing whether differences in PA may be explained by differences in travel mode. All code necessary to replicate, fit and predict to other datasets is provided to facilitate use by other researchers

Investigating and dealing with publication bias and other reporting biases in meta-analyses:a review

A P value, or the magnitude or direction of results can influence decisions about whether, when, and how research findings are disseminated. Regardless of whether an entire study or a particular study result is unavailable because investigators considered the results to be unfavourable, bias in a meta-analysis may occur when available results differ systematically from missing results. In this paper, we summarize the empirical evidence for various reporting biases that lead to study results being unavailable for inclusion in systematic reviews, with a focus on health research. These biases include publication bias and selective nonreporting bias. We describe processes that systematic reviewers can use to minimize the risk of bias due to missing results in meta-analyses of health research, such as comprehensive searches and prospective approaches to meta-analysis. We also outline methods that have been designed for assessing risk of bias due to missing results in meta-analyses of health research, including using tools to assess selective nonreporting of results, ascertaining qualitative signals that suggest not all studies were identified, and generating funnel plots to identify small-study effects, one cause of which is reporting bias. This article is protected by copyright. All rights reserved