Measurement of physical activity, sedentary time and continuous glucose concentrations: novel techniques for behavioural profiling

STUDY 1. INTRODUCTION. Insufficient physical activity is a major risk factor for developing type 2 diabetes. Using isotemporal substitution models, the influence of replacing modest durations of sedentary time with physical activity on diabetes risk scores can be studied. The aims of this study were to examine the relationship between diabetes risk scores, sedentary time and physical activity measured using wrist worn accelerometry, and to model the changes in risk scores by reallocating movement behaviours from lower to a higher intensity. METHODS. Data from 251 (93 males; aged 56.7 ± 8.8) participants from a mixed ethnicity cohort from Leicestershire, UK were selected for analysis. The relationship between diabetes risk (using the Leicester Diabetes Risk Assessment Score), physical activity and sedentary time was identified using multiple linear regressions and isotemporal substitution analysis. Models were calculated for main effects and also adjusted for peak oxygen uptake (VO2) and accelerometer wear time. RESULTS. Both unadjusted and adjusted models revealed that diabetes risk was inversely related to sedentary time, and positively related to light and moderate to vigorous physical activity (MVPA) (p < 0.0005). Unadjusted, the replacement of sedentary time with 10 minutes of either light or MVPA resulted in a reduction in diabetes risk score of −0.22 and −0.54, respectively. There was an eight to nine times greater reduction in risk for the same MVPA replacement models when the least active participants were compared to the pooled analysis (3.601 unadjusted). CONCLUSION. Diabetes risk is associated with sedentary time and physical activity estimated from wrist worn accelerometry. The replacement of sedentary time with MVPA is most beneficial for the least active individuals. STUDY 2. INTRODUCTION. Most associations between physical behaviours and health are assessed using intensity and duration based estimations; however, individuals accrue physical activity in differing ways and behavioural profiles have been linked with varying cardiometabolic risk factors. The frequency or regularity of behaviour may hold additional relationships with health, but have not been extensively explored. Accelerometers provide researchers with a large stream of raw data to analyse. The aim of this paper was to calculate a novel method of behavioural regularity called sample entropy from wrist worn accelerometry and to ascertain whether there are associations with cardiometabolic risk factors in adults. METHODS. Data from 290 (107 males; aged 57.0 ± 8.8) participants from a mixed ethnicity cohort from Leicestershire, UK were selected for analysis. Entropy scores were calculated using 60-second count data within MATLAB. The relationship between entropy scores, physical activity, sedentary time and cardiometabolic risk factors was identified using multiple linear regressions. Models were calculated for main effects and also adjusted for age, sex, accelerometer wear time and body mass index (BMI). RESULTS. Sample entropy scores were significantly related to high-density lipoprotein (HDL) cholesterol (b = 0.148, p = 0.042), triglycerides (b = −0.293, p = 0.042) and glycated haemoglobin (HbA1c) (b = −0.225, p = 0.006), even after adjustment for confounding variables. Traditional intensity estimates of physical activity were not associated; however, the frequency of breaks in sedentary time were significantly related to entropy scores (b = 0.004, p = 0.002). CONCLUSION. Using a novel measure of signal complexity, associations have been revealed with cardiometabolic risk factors; however further analysis in a larger, more diverse dataset is required to ascertain the utility of this technique within behavioural research and if so, what constitutes typical/average levels of entropy within a population. STUDY 3. INTRODUCTION. Acute physiological changes such as reductions in postprandial glucose excursions have been demonstrated within experimental studies that have compared being physically active to sedentary conditions. However, for this information to be truly useful, the coupling of behaviour and glucose data in a free-living environment needs to be achieved. The aim of the study was to ascertain if there is a relationship between objectively measured physical activity, sedentary time and glucose variability using glucose monitoring in an adult population. METHODS. Data from 29 participants recruited from a mixed gender sample from Leicestershire, UK were selected for analysis. Physical activity, sedentary time and interstitial glucose was measured continuously over 14 days using an accelerometer and the Freestyle Libre flash glucose monitor. Daily time (minutes) spent sedentary, and in light activity and moderate to vigorous physical activity (MVPA) were regressed against glycaemic variability indices including daily mean (average) glucose, standard deviation and mean amplitude of glycaemic excursions (MAGE). Generalised Estimating Equations were calculated between behaviour and glycaemic variability variables. Models were calculated for main effects and also adjusted for age, gender and accelerometer wear time. RESULTS. Physical activity and sedentary time were associated with measures of glucose variability, however low fitness individuals showed a stronger relationship between MVPA and MAGE (MAGE: whole sample b = −0.002, low fitness b = −0.012. Additionally, after adjustment for covariates, sedentary time was positively associated with a higher daily mean glucose (b = 0.001, p = 0.001) and MAGE (b = 0.002, p < 0.0005) for the low fitness group. MVPA was negatively associated with mean glucose (b = −0.004, p < 0.0005) and MAGE (b = −0.012, p < 0.0005); however, standard deviation of glucose was not associated with behaviour of any intensity. The magnitudes of the relationships were small, although participants were non-diabetics and exhibited relatively good glucose control i.e. minimal fluctuations in daily glucose variability. CONCLUSION. This study shows that sedentary time, physical activity and glucose variability are related. Despite supporting the previous laboratory research, it is uncertain whether any changes in glucose will reliably occur in all individuals. MVPA confers the largest reductions in glucose variability indices, yet as one of the few studies to couple behaviour and glucose data, more research is needed on larger and more diverse samples

A digital lifestyle behaviour change intervention for the prevention of type 2 diabetes:A qualitative study exploring intuitive engagement with real-time glucose and physical activity feedback

BACKGROUND: Mobile health technologies have advanced to now allow monitoring of the acute physiological responses to lifestyle behaviours. Our aim was to explore how people engaged with real-time feedback on their physical activity and glucose levels over several weeks. METHODS: Semi-structured interviews with 26 participants (61.5% female, 56.6 years) at moderate-to-high risk of developing type 2 diabetes were conducted. Interviews were completed after participants took part in an intervention comprising a flash glucose monitor (Freestyle Libre) and a physical activity monitor (Fitbit Charge 2). Purposive sampling ensured representation of ages, genders and group allocations. RESULTS: Inductive thematic analysis revealed how individuals intuitively used, interpreted and acted on feedback from wearable technologies. Six key themes emerged: triggers of engagement with the technologies, links between behaviour and health, lack of confidence, changes to movement behaviours, changes to diet and barriers to lifestyle behaviour change. CONCLUSIONS: Our findings demonstrate that accessing behavioural and physiological feedback can increase self-awareness of how lifestyle impacts short-term health. Some participants noticed a link between the feedback presented by the two devices and changed their behaviour but many did not. Training and educational support, as well as efforts to optimize how feedback is presented to users, are needed to sustain engagement and behaviour change. Extensions of this work to involve people with diabetes are also warranted to explore whether behavioural and physiological feedback in parallel can encourage better diabetes self-management. TRIAL REGISTRATION: ISRCTN Registry, ISRCTN17545949 , 12/05/2017, prospectively registered

Octreotide in the Control of Post-Sclerotherapy Bleeding from Oesophageal Varices, Ulcers and Oesophagitis

Bleeding from oesophageal varices, oesophageal ulcers or oesophagitis is occasionally massive and difficult to control. Octreotide, a synthetic analogue of somatostin lowers portal pressure and collateral blood flow including that through varices, increases lower oesophageal sphincter pressure, and inhibits the gastric secretion of acid as well as pepsin. Our current experience suggests it is effective in controlling acute variceal haemorrhage. Therefore we have examined the efficacy of octreotide in the control of postsclerotherapy bleeding from oesophageal varices, oesophageal ulcers and oesophagitis. During the study period 77 patients experienced a significant gastrointestinal bleed (blood pressure < 100 mm Hg, pulse > 100 beats per min or the need to transfuse 2 or more units of blood to restore the haemoglobin level) following injection sclerotherapy of oesophageal varices. The source of bleeding was varices in 42 patients, oesophageal ulcers in 31 and oesophagitis in 4. All patients received a continuous intravenous infusion of octreotide (50 μg/h) for between 40–140h. If bleeding was not controlled in the first 12h after commencing octreotide hourly bolus doses (50 μg) for 24h were superimposed on the continuous infusion. Haemorrhage was successfully controlled by an infusion of octreotide in 38 of the 42 patients with bleeding from varices, in 30 of 31 patients with oesophageal ulceration, and all patients with oesophagitis. In the 1 patient with persistent bleeding from oesophageal ulceration and in 2 of the 4 with continued haemorrhage from varices, haemostasis was achieved by hourly boluses of 50 μg octreotide for 24h in addition to the continuous infusion. No major complications were associated with octreotide administration. The results of this study clearly indicate that octreotide is a safe and effective treatment for the control of severe haemorrhage after technically successful injection sclerotherapy

Using digital health technologies to understand the association between movement behaviors and interstitial glucose: Exploratory analysis

© Andrew P Kingsnorth, Maxine E Whelan, James P Sanders, Lauren B Sherar, Dale W Esliger. Background: Acute reductions in postprandial glucose excursions because of movement behaviors have been demonstrated in experimental studies but less so in free-living settings. Objective: The objective of this study was to explore the nature of the acute stimulus-response model between accelerometer-assessed physical activity, sedentary time, and glucose variability over 13 days in nondiabetic adults. Methods: This study measured physical activity, sedentary time, and interstitial glucose continuously over 13 days in 29 participants (mean age in years: 44.9 [SD 9.1]; female: 59%, 17/29; white: 90%, 26/29; mean body mass index: 25.3 [SD 4.1] ) as part of the Sensing Interstitial Glucose to Nudge Active Lifestyles (SIGNAL) research program. Daily minutes spent sedentary, in light activity, and moderate to vigorous physical activity were associated with daily mean glucose, SD of glucose, and mean amplitude of glycemic excursions (MAGE) using generalized estimating equations. Results: After adjustment for covariates, sedentary time in minutes was positively associated with a higher daily mean glucose (mmol/L; beta=0.0007; 95% CI 0.00030-0.00103; P < .001), SD of glucose (mmol/L; beta=0.0006; 95% CI 0.00037-0.00081; P < .001), and MAGE (mmol/L; beta=0.002; 95% CI 0.00131-0.00273; P < .001) for those of a lower fitness. Additionally, light activity was inversely associated with mean glucose (mmol/L; beta=−0.0004; 95% CI −0.00078 to −0.00006; P=.02), SD of glucose (mmol/L; beta=−0.0006; 95% CI −0.00085 to −0.00039; P < .001), and MAGE (mmol/L; beta=−0.002; 95% CI −0.00285 to −0.00146; P < .001) for those of a lower fitness. Moderate to vigorous physical activity was only inversely associated with mean glucose (mmol/L; beta=−0.002; 95% CI −0.00250 to −0.00058; P=.002). Conclusions: Evidence of an acute stimulus-response model was observed between sedentary time, physical activity, and glucose variability in low fitness individuals, with sedentary time and light activity conferring the most consistent changes in glucose variability. Further work is required to investigate the coupling of movement behaviors and glucose responses in larger samples and whether providing these rich data sources as feedback could induce lifestyle behavior change

Sensing interstitial glucose to nudge active lifestyles (SIGNAL): Feasibility of combining novel self-monitoring technologies for persuasive behaviour change

© Article author(s) 2017. Introduction Increasing physical activity (PA) reduces the risk of developing diabetes, highlighting the role of preventive medicine approaches. Changing lifestyle behaviours is difficult and is often predicated on the assumption that individuals are willing to change their lifestyles today to reduce the risk of developing disease years or even decades later. The self-monitoring technologies tested in this study will present PA feedback in real time, parallel with acute physiological data. Presenting the immediate health benefits of being more physically active may help enact change by observing the immediate consequences of that behaviour. The present study aims to assess user engagement with the self-monitoring technologies in individuals at moderate-to-high risk of developing type 2 diabetes. Methods and analysis 45 individuals with a moderate-to-high risk, aged ≥40 years old and using a compatible smartphone, will be invited to take part in a 7-week protocol. Following 1 week of baseline measurements, participants will be randomised into one of three groups: group 1 -glucose feedback followed by biobehavioural feedback (glucose plus PA); group 2 - PA feedback followed by biobehavioural feedback; group 3 - biobehavioural feedback. A PA monitor and a flash glucose monitor will be deployed during the intervention. Participants will wear both devices throughout the intervention but blinded to feedback depending on group allocation. The primary outcome is the level of participant engagement and will be assessed by device use and smartphone usage. Feasibility will be assessed by the practicality of the technology and screening for diabetes risk. Semistructured interviews will be conducted to explore participant experiences using the technologies. Trial registration number ISRCTN17545949. Registered on 15/05/2017

Public Health and Policy Issues of Hernia Surgery in Africa

Abstract Inguinal hernia repair has been overlooked as a public health priority in Africa, with its high prevalence largely unrecognized, and traditional public health viewpoints assuming that not enough infrastructure, human resources, or financing capacity are available for effective service provision. Emerging evidence suggests that inguinal hernias in Ghana are approximately ten times as prevalent as in high-income countries, are much more longstanding and severe, and can be repaired with low-cost techniques using mosquito net mesh through international collaboration. Outcomes from surgery are comparable to published literature, and potential exists for scaling up capacity. Special attention must be paid to creating financing systems that encourage eventual local selfsustainability

Resistance to data loss from the Freestyle Libre:Impact on glucose variability indices and recommendations for data analysis

Like many wearables, flash glucose monitoring relies on user compliance and is subject to missing data. As recent research is beginning to utilise glucose technologies as behaviour change tools, it is important to understand whether missing data is tolerable. Complete Freestyle Libre data files were amputed to remove 1-6 hours of data both at random and over mealtimes (breakfast, lunch and dinner). Absolute percent errors (MAPE) and intraclass correlation coefficients (ICC) were calculated to evaluate agreement and reliability. Thirty-two (91%) participants provided at least one complete day (24-hours) of data (age: 44.8±8.6 years, female: 18 (56%); mean fasting glucose: 5.0±0.6 mmol/L). Mean and CONGA (60 minutes) were robust to data loss (MAPE ≤3%). Larger errors were calculated for standard deviation, coefficient of variation (CV) and MAGE at increasing missingness (MAPE 2-10%, 2-9% and 4-18%, respectively). ICC decreased as missing data increased, with most indicating excellent reliability (>0.9) apart from certain MAGE ICC, which indicated good reliability (0.84-0.9). Researchers and clinicians should be aware of the potential for larger errors when reporting standard deviation, CV and MAGE at higher rates of data loss in nondiabetic populations. But where mean and CONGA are of interest, data loss is less of a concern. Novelty: As research now utilises flash glucose monitoring as behavioural change tools in nondiabetic populations, it is important to consider the influence of missing data. Glycaemic variability indices of mean and CONGA are robust to data loss, but standard deviation, CV and MAGE are influenced at higher rates of missingness

Examining the use of glucose and physical activity self-monitoring technologies in individuals at moderate to high risk of developing type 2 diabetes: randomized trial

Background Self-monitoring of behavior (namely, diet and physical activity) and physiology (namely, glucose) has been shown to be effective in type 2 diabetes (T2D) and prediabetes prevention. By combining self-monitoring technologies, the acute physiological consequences of behaviors could be shown, prompting greater consideration to physical activity levels today, which impact the risk of developing diabetes years or decades later. However, until recently, commercially available technologies have not been able to show individuals the health benefits of being physically active. Objective The objective of this study was to examine the usage, feasibility, and acceptability of behavioral and physiological self-monitoring technologies in individuals at risk of developing T2D. Methods A total of 45 adults aged ≥40 years and at moderate to high risk of T2D were recruited to take part in a 3-arm feasibility trial. Each participant was provided with a behavioral (Fitbit Charge 2) and physiological (FreeStyle Libre flash glucose monitor) monitor for 6 weeks, masked according to group allocation. Participants were allocated to glucose feedback (4 weeks) followed by glucose and physical activity (biobehavioral) feedback (2 weeks; group 1), physical activity feedback (4 weeks) followed by biobehavioral feedback (2 weeks; group 2), or biobehavioral feedback (6 weeks; group 3). Participant usage (including time spent on the apps and number of glucose scans) was the primary outcome. Secondary outcomes were the feasibility (including recruitment and number of sensor displacements) and acceptability (including monitor wear time) of the intervention. Semistructured qualitative interviews were conducted at the 6-week follow-up appointment. Results For usage, time spent on the Fitbit and FreeStyle Libre apps declined over the 6 weeks for all groups. Of the FreeStyle Libre sensor scans conducted by participants, 17% (1798/10,582) recorded rising or falling trends in glucose, and 24% (13/45) of participants changed ≥1 of the physical activity goals. For feasibility, 49% (22/45) of participants completed the study using the minimum number of FreeStyle Libre sensors, and a total of 41 sensors were declared faulty or displaced. For acceptability, participants wore the Fitbit for 40.1 (SD 3.2) days, and 20% (9/45) of participants and 53% (24/45) of participants were prompted by email to charge or sync the Fitbit, respectively. Interviews unearthed participant perceptions on the study design by suggesting refinements to the eligibility criteria and highlighting important issues about the usability, wearability, and features of the technologies. Conclusions Individuals at risk of developing T2D engaged with wearable digital health technologies providing behavioral and physiological feedback. Modifications are required to both the study and to commercially available technologies to maximize the chances of sustained usage and behavior change. The study and intervention were feasible to conduct and acceptable to most participants. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN) 17545949; isrctn.com/ISRCTN1754594

Physical activity and respiratory health (PhARaoH): Data from a cross-sectional study

The dataset consists of a densely phenotyped sample of adults collected from March to August 2014. The dataset captures behavioural, physical, physiological and psychosocial characteristics of individuals with and without a General Practitioner diagnosis of chronic obstructive pulmonary disease (COPD). Data were collected at Glenfield Hospital on 436 individuals (139 COPD patients and 297 apparently healthy adults) aged 40–75 years, residing in Leicestershire and Rutland, United Kingdom. The dataset includes seven days of raw wrist-worn accelerometry, venous blood biomarkers, non-invasive point-of-care cardio-metabolic risk profiles, physical measures and questionnaire data