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Aims/hypothesis: The study aimed to examine the associations between objectively measured sedentary time, breaks in sedentary time, moderate-to-vigorous physical activity (MVPA) and total physical activity with markers of cardiometabolic health in a population with known risk factors for type 2 diabetes mellitus. Methods: This study reports data from two ongoing diabetes prevention programmes. Participants with known risk factors were recruited from primary care practices located within the East Midlands, UK, over the period 2010-2011. ActiGraph GT3X accelerometers (15 s epochs) were used to assess sedentary time (

Aims: To examine the independent associations between relative protein intake (g kg−1 day 1) and markers of physical function in those with type 2 diabetes, while also comparing with current guidelines for protein intake. Methods: This analysis reports data from the ongoing Chronotype of Patients with Type 2 Diabetes and Effect on Glycaemic Control (CODEC) study. Functional assessments included: Short Physical Performance Battery (SPPB), 60 s sit-to-stand (STS-60), 4-m gait speed, time to rise from a chair (×5) and handgrip strength. Participants also completed a self-reported 4 day diet diary. Regression analyses assessed whether relative protein intake was associated with markers of physical function. Interaction terms assessed whether the associations were modified by sex, age, HbA1c or body mass index (BMI). Results413 participants were included (mean ± SD:age = 65.0 ± 7.7 years, 33% female, BMI = 30.6 ± 5.1 kg/m2). The average total protein intake was 0.88 ± 0.31 g kg⁻¹ day⁻¹ . 33% of individuals failed to meet the reference nutrient intake for the United Kingdom (≥0.75 g kg⁻¹ day⁻¹ ), and 87% for European recommendations (≥1.2 g kg⁻¹ day⁻¹ ). After adjustment, each 0.5 g/kg of protein intake was associated with an 18.9% (95% CI: 2.3, 35.5) higher SPPB score, 22.7% (1.1, 44.3) more repetitions in STS-60, 21.1% (4.5, 37.7) faster gait speed and 33.2% (16.9, 49.5) lower chair rise time. There were no associations with handgrip strength or any interactions. Conclusions: Relative protein intake was positively associated with physical function outcomes, even after consideration of total energy intake. As a number of individuals were below the current guidelines, protein intake may be a modifiable factor of importance for people with type 2 diabetes. Refereed/Peer-reviewed

Background Type 2 diabetes is a leading cause of mortality globally and accounts for significant health resource expenditure. Increased physical activity can reduce the risk of diabetes. However, the longer-term clinical effectiveness and cost-effectiveness of physical activity interventions in those at high risk of type 2 diabetes is unknown. Objectives To investigate whether or not Walking Away from Diabetes (Walking Away) – a low-resource, 3-hour group-based behavioural intervention designed to promote physical activity through pedometer use in those with prediabetes – leads to sustained increases in physical activity when delivered with and without an integrated mobile health intervention compared with control. Design Three-arm, parallel-group, pragmatic, superiority randomised controlled trial with follow-up conducted at 12 and 48 months. Setting Primary care and the community. Participants Adults whose primary care record included a prediabetic blood glucose measurement recorded within the past 5 years [HbA1c ≥ 42 mmol/mol (6.0%), Interventions Participants were randomised (1 : 1 : 1) using a web-based tool to (1) control (information leaflet), (2) Walking Away with annual group-based support or (3) Walking Away Plus (comprising Walking Away, annual group-based support and a mobile health intervention that provided automated, individually tailored text messages to prompt pedometer use and goal-setting and provide feedback, in addition to biannual telephone calls). Participants and data collectors were not blinded; however, the staff who processed the accelerometer data were blinded to allocation. Main outcome measures The primary outcome was accelerometer-measured ambulatory activity (steps per day) at 48 months. Other objective and self-reported measures of physical activity were also assessed. Results A total of 1366 individuals were randomised (median age 61 years, median body mass index 28.4 kg/m2, median ambulatory activity 6638 steps per day, women 49%, black and minority ethnicity 28%). Accelerometer data were available for 1017 (74%) and 993 (73%) individuals at 12 and 48 months, respectively. The primary outcome assessment at 48 months found no differences in ambulatory activity compared with control in either group (Walking Away Plus: 121 steps per day, 97.5% confidence interval –290 to 532 steps per day; Walking Away: 91 steps per day, 97.5% confidence interval –282 to 463). This was consistent across ethnic groups. At the intermediate 12-month assessment, the Walking Away Plus group had increased their ambulatory activity by 547 (97.5% confidence interval 211 to 882) steps per day compared with control and were 1.61 (97.5% confidence interval 1.05 to 2.45) times more likely to achieve 150 minutes per week of objectively assessed unbouted moderate to vigorous physical activity. In the Walking Away group, there were no differences compared with control at 12 months. Secondary anthropometric, biomechanical and mental health outcomes were unaltered in either intervention study arm compared with control at 12 or 48 months, with the exception of small, but sustained, reductions in body weight in the Walking Away study arm (≈ 1 kg) at the 12- and 48-month follow-ups. Lifetime cost-effectiveness modelling suggested that usual care had the highest probability of being cost-effective at a threshold of £20,000 per quality-adjusted life-year. Of 50 serious adverse events, only one (myocardial infarction) was deemed possibly related to the intervention and led to the withdrawal of the participant from the study. Limitations Loss to follow-up, although the results were unaltered when missing data were replaced using multiple imputation. Conclusions Combining a physical activity intervention with text messaging and telephone support resulted in modest, but clinically meaningful, changes in physical activity at 12 months, but the changes were not sustained at 48 months. Future work Future research is needed to investigate which intervention types, components and features can help to maintain physical activity behaviour change over the longer term. Trial registration Current Controlled Trials ISRCTN83465245. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 77. See the NIHR Journals Library website for further project information.

Refereed/Peer-reviewed Introduction Higher levels of physical activity are associated with lower cardiometabolic risk. However, the relative contribution of overall activity and the intensity of activity are unclear. Our aim was to determine the relative contribution of overall activity and intensity distribution of activity to cardiometabolic risk in a cross-sectional analysis of apparently healthy office workers and in people with one or more chronic disease. Methods Clustered cardiometabolic risk score was calculated from mean arterial pressure, high-density lipoprotein cholesterol, triglycerides and HbA1c. Open-source software (GGIR) was used to generate average acceleration and intensity gradient from wrist-worn accelerometer data for two data sets: office-workers who did not have a self-reported medical condition (n = 399, 70% women) and adults with one or more chronic disease (n = 1137, 34% women). Multiple linear regression analyses were used to assess the relative contribution of overall activity and intensity of activity to cardiometabolic risk. Results When mutually adjusted, both overall activity and intensity of activity were independently associated with cardiometabolic risk in the healthy group (P < 0.05). However, for the CD group, although mutually adjusted associations for average acceleration were significantly associated with cardiometabolic risk (P < 0.001), intensity was not. In healthy individuals, cardiometabolic risk was lower in those with high overall activity and/or intensity of activity, and who also undertook at least 10 min brisk walking. In those with a chronic disease, risk was lower in those who undertook at least 60 min slow walking. Conclusions These findings suggest interventions aiming to optimize cardiometabolic health in healthy adults could focus on increasing both intensity and amount of physical activity. However, in those with chronic disease, increasing the amount of activity undertaken, regardless of intensity, may be more appropriate.

IntroductionLow self-compassion and poor sleep quality have been identified as potential key predictors of distress in type 2 diabetes (T2D). This study investigated relationships between sleep behaviors (sleep duration, social jetlag and daytime sleepiness), diabetes-related distress (DRD) and self-compassion in people with T2D.Research design and methodsThis cross-sectional study used data from 467 people with T2D derived from self-report questionnaires, accelerometer-assessed sleep measures and demographic information (clinicaltrials.gov registration: NCT02973412). All participants had a diagnosis of T2D and no comorbid sleep disorder (excluding obstructive sleep apnea). Hierarchical multiple regression and mediation analysis were used to quantify relationships between self-compassion, sleep variables and DRD.ResultsSignificant predictors of DRD included two negative subscales of the Self-Compassion Scale (SCS), and daytime sleepiness. The ‘overidentified’ and ‘isolation’ SCS subscales were particularly important in predicting distress. Daytime sleepiness also partially mediated the influence of self-compassion on DRD, potentially through self-care around sleep.ConclusionsDaytime sleepiness and negative self-compassion have clear associations with DRD for people with T2D. The specific negative subscale outcomes suggest that strengthening individuals’ ability to mindfully notice thoughts and experiences without becoming enmeshed in them, and reducing a sense of separateness and difference, might be key therapeutic targets for improving well-being in T2D. Psychological interventions should include approaches focused on reducing negative self-compassion and improving sleep behavior. Equally, reducing DRD may carry beneficial outcomes for sleep and self-compassion. Further work is however crucial to establish causation and long-term impact, and for development of relevant clinical resources.

Funder: Department of Health, Isotemporal substitution modelling (ISM) and compositional isotemporal modelling (CISM) are statistical approaches used in epidemiology to model the associations of replacing time in one physical behaviour with time in another. This study's aim was to use both ISM and CISM to examine and compare associations of reallocating 60 min of sitting into standing or stepping with markers of cardiometabolic health. Cross-sectional data collected during three randomised control trials (RCTs) were utilised. All participants (n = 1554) were identified as being at high risk of developing type 2 diabetes. Reallocating 60 min from sitting to standing and to stepping was associated with a lower BMI, waist circumference, and triglycerides and higher high-density lipoprotein cholesterol using both ISM and CISM (p < 0.05). The direction and magnitude of significant associations were consistent across methods. No associations were observed for hemoglobin A1c, total cholesterol, or low-density lipoprotein cholesterol for either method. Results of both ISM and CISM were broadly similar, allowing for the interpretation of previous research, and should enable future research in order to make informed methodological, data-driven decisions.

Aims: Restrictions during the COVID-19 crisis will have impacted on opportunities to be active. We aimed to (a) quantify the impact of COVID-19 restrictions on accelerometer-assessed physical activity and sleep in people with type 2 diabetes and (b) identify predictors of physical activity during COVID-19 restrictions. Methods: Participants were from the UK Chronotype of Patients with type 2 diabetes and Effect on Glycaemic Control (CODEC) observational study. Participants wore an accelerometer on their wrist for 8 days before and during COVID-19 restrictions. Accelerometer outcomes included the following: overall physical activity, moderate-to-vigorous physical activity (MVPA), time spent inactive, days/week with ≥30-minute continuous MVPA and sleep. Predictors of change in physical activity taken pre-COVID included the following: age, sex, ethnicity, body mass index (BMI), socio-economic status and medical history. Results: In all, 165 participants (age (mean±S.D = 64.2 ± 8.3 years, BMI=31.4 ± 5.4 kg/m2, 45% women) were included. During restrictions, overall physical activity was lower by 1.7 mg (~800 steps/day) and inactive time 21.9 minutes/day higher, but time in MVPA and sleep did not statistically significantly change. In contrast, the percentage of people with ≥1 day/week with ≥30-minute continuous MVPA was higher (34% cf. 24%). Consistent predictors of lower physical activity and/or higher inactive time were higher BMI and/or being a woman. Being older and/or from ethnic minorities groups was associated with higher inactive time. Conclusions: Overall physical activity, but not MVPA, was lower in adults with type 2 diabetes during COVID-19 restrictions. Women and individuals who were heavier, older, inactive and/or from ethnic minority groups were most at risk of lower physical activity during restrictions Refereed/Peer-reviewed

BACKGROUND: Objectively measured physical activity (PA) intensity has traditionally been categorised as light, moderate and vigorous using laboratory calibrated cut-points. The relative contribution of time spent across a spectrum of accelerometer-determined intensities on health outcomes is less clear. PURPOSE: To assess the relationship between objectively measured PA intensity on a continuous scale and markers of insulin sensitivity. METHODS: Participants at high risk of type 2 diabetes were recruited from primary care (Leicestershire, UK). PA was measured using an ActiGraph accelerometer. Fasting and post-challenge glucose and insulin levels were assessed using an oral glucose tolerance test. Insulin sensitivity (IS) was calculated using the Matsuda-IS and HOMA-IS indices. Log-linear regression modelling was used to assess the relationship between PA intensity, in 500 count per min (cpm) increments, with markers of IS. Models were controlled for known confounders. RESULTS: Complete data were available for 569 participants. PA intensity was favourably associated with fasting and 2 hour insulin and IS, with the association increasing in magnitude with each 500 cpm increment. Differences in HOMA-IS per 10 min of PA ranged from 12.4% (95% confidence intervals 3.7, 21.8%) to 26.8% (11.0, 44.7%) within the moderate-intensity PA category (from 2000-2499 cpm to 3500-3999 cpm). For Matsuda IS, these differences were 22.0% (10.3, 34.9%) and 34.7% (13.9, 59.3%) respectively. Significant associations for fasting insulin were no longer observed after controlling for BMI, whereas differences associated with 2 hour insulin and IS were attenuated but still significant. CONCLUSION: PA of any intensity may positively influence glucose regulation and insulin sensitivity in individuals at high risk of T2DM in a dose-response manner. Further research is required to identify the intensity thresholds at which clinically relevant benefits occur in this population. Refereed/Peer-reviewed