Equivalency of sleep estimates: comparison of three research-grade accelerometers

Introduction:This study examined equivalency of sleep estimates from Axivity, GENEActiv and ActiGraph accelerometers worn on non-dominant and dominant wrist, and with and without using a sleep log to guide the algorithm.Methods:Forty-seven young adults wore an Axivity, GENEActiv and ActiGraph accelerometer continuously on both wrists for 4-7 seven days. Sleep time, sleep window, sleep efficiency, sleep onset and wake time were produced using the open-source GGIR package. For each outcome, agreement between accelerometer brands, dominant and non-dominant wrists, and with and without a sleep log, was examined using pairwise 95% equivalence tests (±10% equivalence zone), intra-class correlation coefficients (ICCs) with 95% confidence intervals and limits of agreement (LoA).Results:All sleep outcomes were within a 10% equivalence zoneirrespective of brand, wrist, or use of a sleep log. ICCs were poor-to-good for sleep time (ICCs>0.66) and sleep window (ICCs>0.56). Most ICCs were good-to-excellent for sleepefficiency (ICCs>0.73), sleep onset (ICCs>0.88) and wake time (ICCs>0.87). There werelow levels of mean bias, however wide 95% LoA for sleep time, sleep window, sleep onsetand wake time outcomes. Sleep time (up to 25 min) and sleep window (up to 29 min) werehigher when sleep log was not used. Conclusion: The present findings suggest that sleepoutcomes from the Axivity, GENEActiv and ActiGraph, when analysed identically, arecomparable across studies with different accelerometer brands and wear protocols at a grouplevel. However, caution is advised when comparing studies that differ on sleep logavailability.</p

The impact of COVID-19 restrictions on accelerometer-assessed physical activity and sleep in individuals with type 2 diabetes

AimsRestrictions 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.MethodsParticipants 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.ResultsIn 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.ConclusionsOverall 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.</div

Promotion of healthy eating in clubs with junior teams in Australia: A cross-sectional study of club representatives and parents

Issues addressed: To: (i) describe the prevalence of policies and practices promoting healthy eating implemented by sports clubs with junior teams; (ii) examine differences in such practices across geographic and operational characteristics of clubs; and (iii) describe the attitudes of club representatives and parents regarding the acceptability of sports clubs implementing policies and practices to promote healthy eating. Methods: Cross-sectional telephone surveys of junior community football club management representatives and parents/carers of junior players were conducted in the states of New South Wales and Victoria, Australia in 2016. Results: Seventy-nine of the 89 club representatives approached to participate completed the telephone survey. All clubs (100%; 95% CI 96.2-100.0) reported recommending fruit or water be provided to players after games or at half-time, 24% (95% CI 14.4-33.7) reported promoting healthy food options through prominent positioning at point of sale and only 8% (95% CI 1.6-13.6) of clubs had a written healthy eating policy. There were no significant differences between the mean number of healthy eating policies and practices implemented by club socio-economic or geographic characteristics. Club representatives and parents/carers were supportive of clubs promoting healthy eating for junior players. Conclusions: While there is strong support within sporting clubs with junior teams for policies and practices to promote healthy eating, their implementation is highly variable. So what?: A considerable opportunity remains for health promotion policy and practice improvement in clubs with junior teams, particularly regarding policies related to nutrition. © 2018 Australian Health Promotion Associatio

Alcohol and fast food sponsorship in sporting clubs with junior teams participating in the ‘Good Sports’ program: A cross-sectional study

Objective: To examine: alcohol and fast food sponsorship of junior community sporting clubs; the association between sponsorship and club characteristics; and parent and club representative attitudes toward sponsorship. Methods: A cross-sectional telephone survey of representatives from junior community football clubs across New South Wales and Victoria, Australia, and parents/carers of junior club members. Participants were from junior teams with Level 3 accreditation in the ‘Good Sports’ program. Results: A total of 79 club representatives and 297 parents completed the survey. Half of participating clubs (49%) were sponsored by the alcohol industry and one-quarter (27%) were sponsored by the fast food industry. In multivariate analyses, the odds of alcohol sponsorship among rugby league clubs was 7.4 (95%CI: 1.8–31.0, p=<0.006) that of AFL clubs, and clubs located in regional areas were more likely than those in major cities to receive fast food industry sponsorship (OR= 9.1; 95%CI: 1.0–84.0, p=0.05). The majority (78–81%) of club representatives and parents were supportive of restrictions to prohibit certain alcohol sponsorship practices, but a minority (42%) were supportive of restrictions to prohibit certain fast food sponsorship practices. Conclusions: Large proportions of community sports clubs with junior members are sponsored by the alcohol industry and the fast food industry. There is greater acceptability for prohibiting sponsorship from the alcohol industry than the fast food industry. Implications for public health: Health promotion efforts should focus on reducing alcohol industry and fast food industry sponsorship of junior sports clubs. © 2020 The Author

Implementing health policies in Australian junior sports clubs: An RCT

Background: This pilot study aimed to test the potential effectiveness and acceptability of an intervention to support the implementation of 16 recommended policies and practices to improve the health promotion environment of junior sporting clubs. Reported child exposure to health promoting practices at clubs was also assessed. Methods: A cluster randomised trial was conducted with eight football leagues. Fourty-one junior football clubs belonging to four leagues in the intervention group received support (e.g. physical resources, recognition and rewards, systems and prompts) to implement 16 policies and practices that targeted child exposure to alcohol, tobacco, healthy food and beverages, and participation in physical activity. Thirty-eight clubs belonging to the four control group leagues did not receive the implementation intervention. Study outcomes were assessed via telephone interviews with nominated club representatives and parents of junior players. Between group differences in the mean number of policies and practices implemented at the club level at follow-up were examined using a multiple linear regression model. Results: While the intervention was found to be acceptable, there was no significant difference between the mean number of practices and policies reported to be implemented by intervention and control clubs at post-intervention (Estimate - 0.05; 95% CI -0.91, 0.80; p = 0.90). There was also no significant difference in the proportion of children reported to be exposed to: alcohol (OR 1.16; 95% CI 0.41, 3.28; p = 0.78); tobacco (OR 0.97; CI 0.45, 2.10; p = 0.94); healthy food purchases (OR 0.49; CI 0.11, 2.27; p = 0.35); healthy drink purchases (OR 1.48; CI 0.72, 3.05; p = 0.27); or participation in physical activity (OR 0.76; CI 0.14, 4.08; p = 0.74). Conclusions: Support strategies that better address barriers to the implementation of health promotion interventions in junior sports clubs are required. Trial registration: Retrospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12617001044314). © 2019 The Author(s)

Self-compassion, metabolic control and health status in individuals with type 2 diabetes: a UK observational study.

Aims: Self-compassion is a modifiable characteristic, linked with psychological well being and intrinsic motivation to engage in positive health behaviours. We aimed to explore levels of self-compassion in individuals with type 2 diabetes (T2DM) and their association with levels of depression, diabetes-related distress and glycaemic control. Methods: A cross-sectional study in 176 patients with T2DM in Leicester, UK, using three self-report questionnaires: the Self Compassion Scale (SCS); Patient Health Questionnaire (PHQ-9), and Diabetes Distress Scale (DDS-17). Demographic data, medical history and blood samples were collected. Results: Majority of participants were male (n=120, 68.2%), with median [IQR] age and HbA1 c of 66 [60, 71] years and 7.3 [6.7, 8.0] %, respectively. Multivariable analysis adjusting for age, gender, ethnicity and diabetes duration revealed significant association of all three scores with HbA1 c : per one standard deviation increase of each score, a -0.16% reduction in HbA1 c for SCS (p=0.027), 0.21% increase for PHQ-9 (p=0.012) and 0.33% increase for DDS-17 (p<0.001). Conclusions: Higher levels of self-compassion and lower levels of depressive symptoms were associated with significantly better long-term diabetes control. These results reinforce the importance of emphasis on psychological parameters, including self-compassion, in the multi-disciplinary management of T2DM. We identify this as a potential area for intervention in UK practice

Device-measured physical activity behaviours, and physical function, in people with type 2 diabetes mellitus and peripheral artery disease: A cross-sectional study

Aim: To quantify differences in device-measured physical activity (PA) behaviours, and physical function (PF), in people with type 2 diabetes mellitus (T2DM) with and without peripheral artery disease (PAD). Materials and methods: Participants from the Chronotype of Patients with T2DM and Effect on Glycaemic Control cross-sectional study wore accelerometers on their non-dominant wrist for up to 8-days to quantify: volume and intensity distribution of PA, time spent inactive, time in light PA, moderate-to-vigorous PA in at least 1-minute bouts (MVPA1min), and the average intensity achieved during the most active continuous 2, 5, 10, 30, and 60-minute periods of the 24-h day. PF was assessed using the short physical performance battery (SPPB), the Duke Activity Status Index (DASI), sit-to-stand repetitions in 60 s (STS-60); hand-grip strength was also assessed. Differences between subjects with and without PAD were estimated using regressions adjusted for possible confounders. Results: 736 participants with T2DM (without diabetic foot ulcers) were included in the analysis, 689 had no PAD. People with T2DM and PAD undertake less PA (MVPA1min: −9.2 min [95 % CI: −15.3 to −3.0; p = 0.004]) (light intensity PA: −18.7 min [−36.4 to −1.0; p = 0.039]), spend more time inactive (49.2 min [12.1 to 86.2; p = 0.009]), and have reduced PF (SPPB score: −1.6 [−2.5 to −0.8; p = 0.001]) (DASI score: −14.8 [−19.8 to −9.8; p = 0.001]) (STS-60 repetitions: −7.1 [−10.5 to −3.8; p = 0.001]) compared to people without; some differences in PA were attenuated by confounders. Reduced intensity of activity for the most active continuous 2–30 min in the 24-h day, and reduced PF, persisted after accounting for confounders. There were no significant differences in hand-grip strength. Conclusions: Findings from this cross-sectional study suggest that, the presence of PAD in T2DM may have been associated with lower PA levels and PF.</p

The rationale and design of a cross-sectional study to investigate and describe the Chronotype of Patients with Type 2 Diabetes and the Effect on Glycaemic Control: The CODEC study

Introduction A person’s chronotype is their entrained preference for sleep time within the 24-hour clock. It is described by the well-known concept of the ‘lark’ (early riser) and ‘owl’ (late sleeper). Evidence suggests that the ‘owl’ is metabolically disadvantaged due to the standard organisation of our society which favours the ‘lark’ and places physiological stresses on this chronotype. The aim of this study is to explore cardiometabolic health between the lark and owl in a population with an established metabolic condition - Type 2 Diabetes. Methods This cross-sectional, multi-site study aims to recruit 2247 participants from both secondary and primary care settings. The primary objective is to compare glycaemic control between late and early chronotypes. Secondary objectives include determining if late-chronotype is associated with poorer cardiometabolic health and other lifestyle factors, including well-being, compared to early-chronotype; describing the prevalence of the five different chronotypes in this cohort and examining the trends in glycaemic control, cardiometabolic health, well-being and lifestyle factors across chronotype. Analysis The primary outcome (HbA1c), linear regression analysis will compare HbA1c between early and late chronotypes, with and without adjustment for confounding variables. Chronotype will be modelled as a categorical variable with all five levels (from extreme-morning to extremelate type), and as a continuous variable to calculate p for trend across the five categories. A number of models will be created; unadjusted through to adjusted with age, sex, ethnicity, BMI, duration of diabetes, family history of diabetes, current medication and dietary habits. All secondary outcomes will be analysed using the same method. Ethics Ethical approval from the West Midlands - Black Country Research Ethics Committee (16/WM/0457). Dissemination The results will be disseminated through publication in peer reviewed medical journal, relevant medical/health conferences and a summary report sent to patients. Registration details Registered on clinicaltrials.gov NCT02973412 (23.11.20116