Physical activity, inactivity and sleep during the Diabetes Remission Clinical Trial (DiRECT).

AIMS: As sustained weight loss is vital for achieving remission of type 2 diabetes, we explored whether randomisation to weight loss plus maintenance in the DiRECT trial was associated with physical activity, inactivity or sleep. METHODS: Participants were randomised to either a dietary weight management programme or best-practice care. The weight management group were encouraged to increase daily physical activity to their sustainable maximum. Objective measurement was achieved using a wrist-worn GENEActiv accelerometer for 7 days at baseline, 12 and 24 months in both groups. RESULTS: Despite average weight loss of 10 kg at 12 months in the intervention (n = 66) group, there were no differences in total physical activity or inactivity compared with the control (n = 104) at any time point. However, in our exploratory analysis, those who lost more than 10% of their baseline body weight performed on average 11 mins/day more light activity than the <10% group at 24 months (p = 0.033) and had significantly lower bouts of Inactivity30min (interaction, p = 0.005) across 12 and 24 months. At 24 months, the ≥10% group had higher daily acceleration (38.5 ± 12.1 vs. 33.2 ± 11.1 mg, p = 0.020), and higher accelerations in the most active 5-hour period (59.4 ± 21.8 vs. 50.6 ± 18.3 mg, p = 0.023). Wakefulness after sleep onset decreased in the intervention group compared with the control group and also in the ≥10% weight loss group at 12 and 24 months. CONCLUSIONS: Randomisation to a successful intensive weight loss intervention, including regular physical activity encouragement, was not associated with increased physical activity although sleep parameters improved. Physical activity was greater, and night-time waking reduced in those who maintained >10% weight loss at 12 and 24 months. TRIAL REGISTRATION ISRCTN03267836.

Movement as Medicine for Cardiovascular Disease Prevention: Pilot Feasibility Study of a Physical Activity Promotion Intervention for At-Risk Patients in Primary Care.

BACKGROUND: Physical activity (PA) can reduce cardiovascular disease (CVD) risk factors, and although primary care settings offer a large reach to promote PA and reduce CVD risk, primary health care professionals may lack self-efficacy and tools to effectively promote PA in practice. Movement as Medicine for CVD Prevention is a suite of 2 theory-based, web-based behavioral interventions-one for health care professionals and one for patients-which may offer a pathway for promoting PA and reducing CVD risk in primary care. OBJECTIVE: This study aims to examine the feasibility and possible effects of Movement as Medicine for CVD Prevention. METHODS: This nonrandomized pilot study recruited participants from primary care organizations in the Northeast of England. Enrolled health care professionals followed a theory-based, web-based course on PA counseling and motivational interviewing techniques. After the course, health care professionals delivered behavior change consultations based on motivational interviewing to inactive individuals with >20% risk of developing CVD within 10 years. Patients were then given access to a website based on self-determination and self-regulation theories, which targeted increased levels of PA. Outcomes were assessed at baseline and after 3 months, and patient data were analyzed on an intention-to-treat basis in a multiple imputation data set. RESULTS: Recruitment rates of primary care organizations fell below expectations. A total of 11 health care professionals from 3 enrolled primary care organizations completed the web-based course and reported increases in important theoretical determinants of PA promotion in practice (eg, self-efficacy, Cohen d=1.24, 95% CI 0.67-1.80; and planning, Cohen d=0.85, 95% CI -0.01 to 1.69). A total of 83 patients were enrolled in the study, and 58 (70%) completed both the baseline and 3-month assessments. Compared with baseline, patients had higher levels of objective (Cohen d=0.77, 95% CI 0.13-1.41) but not subjective (Cohen d=0.40, 95% CI -0.03 to 0.83) moderate to vigorous PA at 3 months. Patients also reported higher levels of the PA determinants of intention, self-efficacy, intrinsic motivation, and action planning and action control at 3 months (effect sizes ranged from Cohen d=0.39 to 0.60). CONCLUSIONS: The Movement as Medicine for CVD Prevention intervention seems to have the potential to improve patient PA behaviors and important determinants of health care professionals' PA promotion practices. However, the recruitment rates of primary care organizations in this study were low and would need to be increased to examine the efficacy of the program. This study offers several insights into improving the feasibility of this primary care PA promotion pathway. TRIAL REGISTRATION: ISRCTN Registry ISRCTN14582348; http://www.isrctn.com/ISRCTN14582348.

The development, validation and application of remote blood sample collection in telehealth programmes.

INTRODUCTION: The ability to collect blood samples remotely without the involvement of healthcare professionals is a key element of future telehealth applications. We developed and validated the application of the Drawbridge OneDraw device for use at home for blood sample collection. The device was then applied in a large population-based remote monitoring study to assess changes in SARS-CoV-2 IgG antibody levels. METHODS: We tested: (1) feasibility of participants using the device at home without a healthcare professional on the upper arm and thigh sites (2) stability of the dried blood sample collected remotely (3) participant acceptability of the device compared with finger-prick and venous blood samples and the validity of SARS-CoV-2 virus antibody measurement versus venous blood sample (4) application to the Fenland COVID-19 study in which 4023 participants at 3 timepoints across 6 months. RESULTS: Participant acceptability was high, with a significantly lower median perceived pain score and 76% of participants preferring the OneDraw device over the other blood collection methods. There was high level of agreement in SARS-CoV-2 virus antibody results with venous blood samples in 120 participants (Cohen's kappa 0.68 (95% CI 0.56, 0.83). In the Fenland COVID-19 study, 92% of participants returned a sample at baseline (3702/4023), 89% at 3 months (3492/3918) and 93% at 6 months (3453/3731), with almost all samples received successfully processed (99.9%). DISCUSSION: The OneDraw device enables a standardised blood sample collection at home by participants themselves. Due to its ease-of-use and acceptability the OneDraw device is particularly useful in telehealth approaches where multiple samples need to be collected.

Curating a longitudinal research resource using linked primary care EHR data-a UK Biobank case study.

Primary care EHR data are often of clinical importance to cohort studies however they require careful handling. Challenges include determining the periods during which EHR data were collected. Participants are typically censored when they deregister from a medical practice, however, cohort studies wish to follow participants longitudinally including those that change practice. Using UK Biobank as an exemplar, we developed methodology to infer continuous periods of data collection and maximize follow-up in longitudinal studies. This resulted in longer follow-up for around 40% of participants with multiple registration records (mean increase of 3.8 years from the first study visit). The approach did not sacrifice phenotyping accuracy when comparing agreement between self-reported and EHR data. A diabetes mellitus case study illustrates how the algorithm supports longitudinal study design and provides further validation. We use UK Biobank data, however, the tools provided can be used for other conditions and studies with minimal alteration.

Exploration of Sleep as a Specific Risk Factor for Poor Metabolic and Mental Health: A UK Biobank Study of 84,404 Participants.

PURPOSE: Short and long sleep durations have adverse effects on physical and mental health. However, most studies are based on self-reported sleep duration and health status. Therefore, this longitudinal study aims to investigate objectively measured sleep duration and subsequent primary health care records in older adults to investigate the impact of sleep duration and fragmentation on physical and mental health. METHODS: Data on objective sleep duration were measured using accelerometry. Primary care health records were then obtained from the UK Biobank (n=84,404). Participants (mean age, 62.4 years) were divided into five groups according to their sleep duration derived from the accelerometry data: <5 hours, 5-6 hours, 6-7 hours, 7-8 hours and >8 hours. ICD-10 codes were used for the analysis of primary care data. Wake after sleep onset, activity level during the least active 5 hours and episodes of movement during sleep were analysed as an indication for sleep fragmentation. Binary regression models were adjusted for age, gender and Townsend deprivation score. RESULTS: A "U-shaped" relationship was found between sleep duration and diseases including diabetes, hypertension and heart disease and depression. Short and long sleep durations and fragmented sleep were associated with increased odds of disease. CONCLUSION: Six to eight hours of sleep, as well as less fragmented sleep, predicted better long-term metabolic and mental health.

Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning-Based Cross-sectional Study of the UK Biobank Accelerometer Cohort.

BACKGROUND: Between 2013 and 2015, the UK Biobank collected accelerometer traces from 103,712 volunteers aged between 40 and 69 years using wrist-worn triaxial accelerometers for 1 week. This data set has been used in the past to verify that individuals with chronic diseases exhibit reduced activity levels compared with healthy populations. However, the data set is likely to be noisy, as the devices were allocated to participants without a set of inclusion criteria, and the traces reflect free-living conditions. OBJECTIVE: This study aims to determine the extent to which accelerometer traces can be used to distinguish individuals with type 2 diabetes (T2D) from normoglycemic controls and to quantify their limitations. METHODS: Machine learning classifiers were trained using different feature sets to segregate individuals with T2D from normoglycemic individuals. Multiple criteria, based on a combination of self-assessment UK Biobank variables and primary care health records linked to UK Biobank participants, were used to identify 3103 individuals with T2D in this population. The remaining nondiabetic 19,852 participants were further scored on their physical activity impairment severity based on other conditions found in their primary care data, and those deemed likely physically impaired at the time were excluded. Physical activity features were first extracted from the raw accelerometer traces data set for each participant using an algorithm that extends the previously developed Biobank Accelerometry Analysis toolkit from Oxford University. These features were complemented by a selected collection of sociodemographic and lifestyle features available from UK Biobank. RESULTS: We tested 3 types of classifiers, with an area under the receiver operating characteristic curve (AUC) close to 0.86 (95% CI 0.85-0.87) for all 3 classifiers and F1 scores in the range of 0.80-0.82 for T2D-positive individuals and 0.73-0.74 for T2D-negative controls. Results obtained using nonphysically impaired controls were compared with highly physically impaired controls to test the hypothesis that nondiabetic conditions reduce classifier performance. Models built using a training set that included highly impaired controls with other conditions had worse performance (AUC 0.75-0.77; 95% CI 0.74-0.78; F1 scores in the range of 0.76-0.77 for T2D positives and 0.63-0.65 for controls). CONCLUSIONS: Granular measures of free-living physical activity can be used to successfully train machine learning models that are able to discriminate between individuals with T2D and normoglycemic controls, although with limitations because of the intrinsic noise in the data sets. From a broader clinical perspective, these findings motivate further research into the use of physical activity traces as a means of screening individuals at risk of diabetes and for early detection, in conjunction with routinely used risk scores, provided that appropriate quality control is enforced on the data collection protocol.

Objective sleep assessment in >80,000 UK mid-life adults: Associations with sociodemographic characteristics, physical activity and caffeine.

STUDY OBJECTIVES: Normal timing and duration of sleep is vital for all physical and mental health. However, many sleep-related studies depend on self-reported sleep measurements, which have limitations. This study aims to investigate the association of physical activity and sociodemographic characteristics including age, gender, coffee intake and social status with objective sleep measurements. METHODS: A cross-sectional analysis was carried out on 82995 participants within the UK Biobank cohort. Sociodemographic and lifestyle information were collected through touch-screen questionnaires in 2007-2010. Sleep and physical activity parameters were later measured objectively using wrist-worn accelerometers in 2013-2015 (participants were aged 43-79 years and wore watches for 7 days). Participants were divided into 5 groups based on their objective sleep duration per night (<5 hours, 5-6 hours, 6-7 hours, 7-8 hours and >8 hours). Binary logistic models were adjusted for age, gender and Townsend Deprivation Index. RESULTS: Participants who slept 6-7 hours/night were the most frequent (33.5%). Females had longer objective sleep duration than males. Short objective sleep duration (<6 hours) correlated with older age, social deprivation and high coffee intake. Finally, those who slept 6-7 hours/night were most physically active. CONCLUSIONS: Objectively determined short sleep duration was associated with male gender, older age, low social status and high coffee intake. An inverse 'U-shaped' relationship between sleep duration and physical activity was also established. Optimal sleep duration for health in those over 60 may therefore be shorter than younger groups.

Analyzing walking speeds with ankle and wrist worn accelerometers in a cohort with myotonic dystrophy.

Background: Accelerometers are accurate tools to assess movement and physical activity. However, interpreting standardly used outputs is not straightforward for populations with impaired mobility.Methods: The applicability of GENEActiv was explored in a group of 30 participants with myotonic dystrophy and compared to a group of 14 healthy-controls. All participants performed a set of tests while wearing four different accelerometers (wrists and ankles): [1] standing still; [2] ten-meters walk test; [3] six-minutes walking test; and, [4] ten-meters walk/run test.Results: Relevant findings were: [1] high intra-accelerometer reliability (i.e. 0.97 to 0.99; p < 0.001); [2] each test acceleration values differ significantly between each other; [3] no inter-accelerometer reliability between wrist-worn devices and ankle-worn; and [4] a significant difference between the myotonic dystrophy group and the healthy-controls detectable at each test (i.e. Left-ankle values at six-minutes walking test: 48±17 for the myotonic dystrophy group, vs, 74±16 for the healthy-controls; p < 0.001).Conclusions: GENEActiv demonstrated to be valid and reliable, capable of detecting walking periods and discriminating different speeds. However, inter-accelerometer reliability only applied when comparing opposite sides of the same limb. Specific movement characteristics of the myotonic dystrophy group were identified and muscle strength showed not to be a full determinant of limb acceleration.Implications for rehabilitationRehabilitation professionals in the field of neuromuscular disorders should be aware of the potential use of objective monitoring tools such as accelerometers whilst acknowledging the implications of assessing populations with altered movement patterns.Researchers should be cautious when translating accelerometry outputs previously validated in healthy populations to functionally impaired cohorts like myotonic dystrophy.Accelerometers can objectively expose movement disturbances allowing further investigations for the source of these disturbances.

Cognitive behavioural therapy with optional graded exercise therapy in patients with severe fatigue with myotonic dystrophy type 1: a multicentre, single-blind, randomised trial.

BACKGROUND: Myotonic dystrophy type 1 is the most common form of muscular dystrophy in adults and leads to severe fatigue, substantial physical functional impairment, and restricted social participation. In this study, we aimed to determine whether cognitive behavioural therapy optionally combined with graded exercise compared with standard care alone improved the health status of patients with myotonic dystrophy type 1. METHODS: We did a multicentre, single-blind, randomised trial, at four neuromuscular referral centres with experience in treating patients with myotonic dystrophy type 1 located in Paris (France), Munich (Germany), Nijmegen (Netherlands), and Newcastle (UK). Eligible participants were patients aged 18 years and older with a confirmed genetic diagnosis of myotonic dystrophy type 1, who were severely fatigued (ie, a score of ≥35 on the checklist-individual strength, subscale fatigue). We randomly assigned participants (1:1) to either cognitive behavioural therapy plus standard care and optional graded exercise or standard care alone. Randomisation was done via a central web-based system, stratified by study site. Cognitive behavioural therapy focused on addressing reduced patient initiative, increasing physical activity, optimising social interaction, regulating sleep-wake patterns, coping with pain, and addressing beliefs about fatigue and myotonic dystrophy type 1. Cognitive behavioural therapy was delivered over a 10-month period in 10-14 sessions. A graded exercise module could be added to cognitive behavioural therapy in Nijmegen and Newcastle. The primary outcome was the 10-month change from baseline in scores on the DM1-Activ-c scale, a measure of capacity for activity and social participation (score range 0-100). Statistical analysis of the primary outcome included all participants for whom data were available, using mixed-effects linear regression models with baseline scores as a covariate. Safety data were presented as descriptives. This trial is registered with ClinicalTrials.gov, number NCT02118779. FINDINGS: Between April 2, 2014, and May 29, 2015, we randomly assigned 255 patients to treatment: 128 to cognitive behavioural therapy plus standard care and 127 to standard care alone. 33 (26%) of 128 assigned to cognitive behavioural therapy also received the graded exercise module. Follow-up continued until Oct 17, 2016. The DM1-Activ-c score increased from a mean (SD) of 61·22 (17·35) points at baseline to 63·92 (17·41) at month 10 in the cognitive behavioural therapy group (adjusted mean difference 1·53, 95% CI -0·14 to 3·20), and decreased from 63·00 (17·35) to 60·79 (18·49) in the standard care group (-2·02, -4·02 to -0·01), with a mean difference between groups of 3·27 points (95% CI 0·93 to 5·62, p=0·007). 244 adverse events occurred in 65 (51%) patients in the cognitive behavioural therapy group and 155 in 63 (50%) patients in the standard care alone group, the most common of which were falls (155 events in 40 [31%] patients in the cognitive behavioural therapy group and 71 in 33 [26%] patients in the standard care alone group). 24 serious adverse events were recorded in 19 (15%) patients in the cognitive behavioural therapy group and 23 in 15 (12%) patients in the standard care alone group, the most common of which were gastrointestinal and cardiac. INTERPRETATION: Cognitive behavioural therapy increased the capacity for activity and social participation in patients with myotonic dystrophy type 1 at 10 months. With no curative treatment and few symptomatic treatments, cognitive behavioural therapy could be considered for use in severely fatigued patients with myotonic dystrophy type 1. FUNDING: The European Union Seventh Framework Programme.

Accelerometer-derived physical activity in those with cardio-metabolic disease compared to healthy adults: a UK Biobank study of 52,556 participants.

AIM: Cardio-metabolic disease and physical activity are closely related but large-scale objective studies which measure physical activity are lacking. Using the largest accelerometer cohort to date, we aimed to investigate whether there is an association between disease status and accelerometer variables after a 5-year follow-up. METHODS: 106,053 UK Biobank participants wore a wrist-worn GENEactiv monitor. Those with acceptable wear time (> 3 days) were split into 4 cardio-metabolic disease groups based on self-report disease status which was collected 5 ± 1 years prior. Multiple linear regression models were used to investigate associations, controlling for confounders and stratified for gender. RESULTS: Average daily acceleration was lower in men ('healthy'-42 ± 15 mg v 'Type 2 diabetes + cardiovascular disease (CVD)'-31 ± 12 mg) and women ('healthy'-44 ± 13 mg v 'Type 2 diabetes + CVD'-31 ± 11 mg) with cardio-metabolic disease and this was consistent across both week and weekend days. Men and women with the worst cardio-metabolic disease perform around half of moderate to vigorous physical activity on a daily basis compared to healthy individuals, and spend almost 7 h per day in 30 min inactivity bouts. Significant associations were seen between cardio-metabolic disease and accelerometer variables 5 years on when controlling for confounders. CONCLUSION: In the largest accelerometer cohort to date, there are significant associations between cardio-metabolic disease and physical activity variables after 5 years of follow-up. Triaxial accelerometers provide enhanced measurement opportunities for measuring lifestyle behaviours in chronic disease.

Electrochemical Detection of Plasma Immunoglobulin as a Biomarker for Alzheimer's Disease.

The clinical diagnosis and treatment of Alzheimer's disease (AD) represent a challenge to clinicians due to the variability of clinical symptomatology as well as the unavailability of reliable diagnostic tests. In this study, the development of a novel electrochemical assay and its potential to detect peripheral blood biomarkers to diagnose AD using plasma immunoglobulins is investigated. The immunosensor employs a gold electrode as the immobilizing substrate, albumin depleted plasma immunoglobulin as the biomarker, and polyclonal rabbit Anti-human immunoglobulin (against IgA, IgG, IgM) as the receptor for plasma conjugation. The assay showed good response, sensitivity and reproducibility in differentiating plasma immunoglobulin from AD and control subjects down to 10-9 dilutions of plasma immunoglobulin representing plasma content concentrations in the pg mL-1 range. The newly developed assay is highly sensitive, less time consuming, easy to handle, can be easily modified to detect other dementia-related biomarkers in blood samples, and can be easily integrated into portable devices.

Low physical activity, high television viewing and poor sleep duration cluster in overweight and obese adults; a cross-sectional study of 398,984 participants from the UK Biobank.

BACKGROUND: An unhealthy lifestyle is one of the greatest contributors to obesity. A number of behaviours are linked with obesity, but are often measured separately. The UK Biobank cohort of >500,000 participants allows us to explore these behaviours simultaneously. We therefore aimed to compare physical activity, television (TV) viewing and sleep duration across body mass index (BMI) categories in a large sample of UK adults. METHODS: UK Biobank participants were recruited and baseline measures were taken between 2007 and 2010 and data analysis was performed in 2015. BMI was measured objectively using trained staff. Self-report questionnaires were used to measure lifestyle behaviours including the international physical activity questionnaire (IPAQ-short form) for physical activity. During data analysis, six groups were defined based on BMI; 'Underweight' (n = 2026), 'Normal weight' (n = 132,372), 'Overweight (n = 171,030), 'Obese I' (n = 67,903), 'Obese II' (n = 18,653) and 'Obese III' (n = 7000). The odds of reporting unhealthy lifestyle behaviours (low physical activity, high TV viewing or poor sleep duration) were compared across BMI groups using logistic regression analysis. RESULTS: Overweight and obese adults were more likely to report low levels of physical activity (≤967.5 MET.mins/wk) ('Overweight'-OR [95% CI]: 1.23 [1.20 to 1.26], 'Obese I' 1.66 [1.61-1.71], 'Obese II' 2.21 [2.12-2.30], and 'Obese III' 3.13 [2.95 to 3.23]) compared to 'Normal weight' adults. The odds of reporting high TV viewing (3 h/day) was greater in 'Overweight' (1.52 [1.48 to 1.55]) and obese adults ('Obese I' 2.06 [2.00-2.12], 'Obese II' 2.69 [2.58-2.80], 'Obese III' 3.26 [3.07 to 3.47]), and poor sleep duration (<7, >8 h/night) was higher in 'Overweight' (1.09 [1.07 to 1.12]) and obese adults ('Obese I' 1.31 [1.27-1.34], 'Obese II' 1.50 [1.44-1.56], 'Obese III' (1.78 [1.68 to 1.89]) compared to the 'Normal weight' group. These lifestyle behaviours were clustered, the odds of reporting simultaneous low physical activity, high TV viewing and poor sleep (unhealthy behavioural phenotype) was higher than reporting these behaviours independently, in overweight and obese groups. 'Obese III' adults were almost six times more likely (5.47 [4.96 to 6.05]) to report an unhealthy behavioural phenotype compared to the 'Normal weight' group. CONCLUSIONS: Overweight and obese adults report low levels of physical activity, high TV viewing and poor sleep duration. These behaviours seem to cluster and collectively expose individuals to greater risk of obesity. Multiple lifestyle behaviours should be targeted in future interventions.

Measuring Habitual Physical Activity in Neuromuscular Disorders: A Systematic Review.

BACKGROUND: Free-living or habitual physical activity (HPA) refers to someone's performance in his or her free-living environment. Neuromuscular disorders (NMD) manifest through HPA, and the observation of HPA can be used to identify clinical risks and to quantify outcomes in research. This review summarizes and analyses previous studies reporting the assessment of HPA in NMD, and may serve as the basis for evidence-based decision-making when considering assessing HPA in this population. METHODS: A systematic review was performed to identify all studies related to HPA in NMD, followed by a critical appraisal of the assessment methodology and a final review of the identified HPA tools. RESULTS: A total of 22 studies were selected, reporting on eight different direct tools (or activity monitors) and ten structured patient-reported outcomes. Overall, HPA patterns in NMD differ from healthy control populations. There was a noticeable lack of validation studies for these tools and outcome measures in NMD. Very little information regarding feasibility and barriers for the application of these tools in this population have been published. CONCLUSIONS: The variety and heterogeneity of tools and methods in the published literature makes the comparison across different studies difficult, and methodological guidelines are warranted. We propose a checklist of considerations for the assessment and reporting of HPA in NMD.

Cross-sectional study of diet, physical activity, television viewing and sleep duration in 233,110 adults from the UK Biobank; the behavioural phenotype of cardiovascular disease and type 2 diabetes.

OBJECTIVES: Simultaneously define diet, physical activity, television (TV) viewing, and sleep duration across cardiometabolic disease groups, and investigate clustering of non-diet lifestyle behaviours. DESIGN: Cross-sectional observational study. SETTING: 22 UK Biobank assessment centres across the UK. PARTICIPANTS: 502,664 adults aged 37-63 years old, 54% women. 4 groups were defined based on disease status; 'No disease' (n=103,993), 'cardiovascular disease' (CVD n=113,469), 'Type 2 diabetes without CVD' (n=4074) and 'Type 2 diabetes + CVD' (n=11,574). MAIN OUTCOMES: Diet, physical activity, TV viewing and sleep duration. RESULTS: People with 'CVD' report low levels of physical activity (<918 MET min/week, OR (95% CI) 1.23 (1.20 to 1.25)), high levels of TV viewing (>3 h/day; 1.42 (1.39 to 1.45)), and poor sleep duration (<7, >8 h/night; 1.37 (1.34 to 1.39)) relative to people without disease. People with 'Type 2 diabetes + CVD' were more likely to report low physical activity (1.71 (1.64 to 1.78)), high levels of TV viewing (1.92 (1.85 to 1.99)) and poor sleep duration (1.52 (1.46 to 1.58)) relative to people without disease. Non-diet behaviours were clustered, with people with 'CVD' or 'Type 2 diabetes + CVD' more likely to report simultaneous low physical activity, high TV viewing and poor sleep duration than those without disease (2.15 (2.03 to 2.28) and 3.29 (3.02 to 3.58), respectively). By contrast, 3 in 4 adults with 'Type 2 diabetes', and 2 in 4 adults with 'CVD' have changed their diet in the past 5 years, compared with only 1 in 4 in the 'No disease' group. Models were adjusted for gender, age, body mass index, Townsend Deprivation Index, ethnicity, alcohol intake, smoking and meeting fruit/vegetable guidelines. CONCLUSIONS: Low physical activity, high TV and poor sleep duration are prominent unaddressed high-risk characteristics of both CVD and type 2 diabetes, and are likely to be clustered together.

Toward a low-cost gait analysis system for clinical and free-living assessment.

Gait is an important clinical assessment tool since changes in gait may reflect changes in general health. Measurement of gait is a complex process which has been restricted to bespoke clinical facilities until recently. The use of inexpensive wearable technologies is an attractive alternative and offers the potential to assess gait in any environment. In this paper we present the development of a low cost analysis gait system built using entirely open source components. The system is used to capture spatio-temporal gait characteristics derived from an existing conceptual model, sensitive to ageing and neurodegenerative pathology (e.g. Parkinson's disease). We demonstrate the system is suitable for use in a clinical unit and will lead to pragmatic use in a free-living (home) environment. The system consists of a wearable (tri-axial accelerometer and gyroscope) with a Raspberry Pi module for data storage and analysis. This forms ongoing work to develop gait as a low cost diagnostic in modern healthcare.

A Novel, Open Access Method to Assess Sleep Duration Using a Wrist-Worn Accelerometer.

Wrist-worn accelerometers are increasingly being used for the assessment of physical activity in population studies, but little is known about their value for sleep assessment. We developed a novel method of assessing sleep duration using data from 4,094 Whitehall II Study (United Kingdom, 2012-2013) participants aged 60-83 who wore the accelerometer for 9 consecutive days, filled in a sleep log and reported sleep duration via questionnaire. Our sleep detection algorithm defined (nocturnal) sleep as a period of sustained inactivity, itself detected as the absence of change in arm angle greater than 5 degrees for 5 minutes or more, during a period recorded as sleep by the participant in their sleep log. The resulting estimate of sleep duration had a moderate (but similar to previous findings) agreement with questionnaire based measures for time in bed, defined as the difference between sleep onset and waking time (kappa = 0.32, 95%CI:0.29,0.34) and total sleep duration (kappa = 0.39, 0.36,0.42). This estimate was lower for time in bed for women, depressed participants, those reporting more insomnia symptoms, and on weekend days. No such group differences were found for total sleep duration. Our algorithm was validated against data from a polysomnography study on 28 persons which found a longer time window and lower angle threshold to have better sensitivity to wakefulness, while the reverse was true for sensitivity to sleep. The novelty of our method is the use of a generic algorithm that will allow comparison between studies rather than a "count" based, device specific method.

A comparison of subjective and objective measures of physical activity from the Newcastle 85+ study.

BACKGROUND: Little is known about physical activity (PA) in the very old, the fastest growing age group in the population. We aimed to examine the convergent validity of subjective and objective measures of PA in adults aged over 85 years. METHODS: A total of 484 participants aged 87-89 years recruited to the Newcastle 85+ study completed a purpose-designed physical activity questionnaire (PAQ), which categorised participants as mildly active, moderately active and very active. Out of them, 337 participants wore a triaxial, raw accelerometer on the right wrist over a 5-7-day period to obtain objective measures of rest/activity, PA intensity and PA type. Data from subjective and objective measurement methods were compared. RESULTS: Self-reported PA was significantly associated with objective measures of the daily sedentary time, low-intensity PA and activity type classified as sedentary, activities of daily living and walking. Objective measures of PA were significantly different when low, moderate and high self-reported PA categories were compared (all P < 0.001). CONCLUSION: The Newcastle 85+ PAQ demonstrated convergent validity with objective measures of PA. Our findings suggest that this PAQ can be used in the very old to rank individuals according to their level of total PA.

Dose-response effects of a Web-based physical activity program on body composition and metabolic health in inactive older adults: additional analyses of a randomized controlled trial.

BACKGROUND: Low physical activity is a major risk factor for several age-related diseases. Recently, we showed in a randomized controlled trial that a 12-week Web-based intervention (Philips DirectLife) to increase physical activity was effective in increasing physical activity levels and metabolic health in an inactive population aged 60-70 years. OBJECTIVE: The goal of this paper was to assess how many participants successfully reached the physical activity level as targeted by the intervention and what the effects of the intervention on body composition and metabolic health in these successful individuals were to provide insight in the maximum attainable effect of the intervention. METHODS: Among the 235 participants in a randomized controlled trial of the Actief en Gezond Oud (AGO) study, we assessed the effects of the intervention on metabolic parameters in those who had successfully reached their personalized physical activity target compared with the entire intervention group. Furthermore, we studied the dose-response effect of increase in physical activity on metabolic outcome within the intervention group. RESULTS: Of the intervention group, 50 of 119 (42.0%) participants successfully reached the physical activity target (corresponding to a 10% increased daily physical activity on average). This group showed markedly higher effects of the intervention compared to the entire intervention group, with greater decreases in body weight (2.74 vs 1.49 kg), waist circumference (3.74 vs 2.33 cm), insulin resistance (HOMA index: 0.23 vs 0.20), and in cholesterol/HDL ratio (0.39 vs 0.20) and Framingham risk score (0.90% vs 0.54%). We found that men compared to women were more likely to be successful. The dose-response analysis showed that there was a significant association between increase in minutes spent in moderate-to-vigorous activity and body weight loss, BMI reduction, waist circumference reduction, HDL cholesterol increasing, and cholesterol/HDL ratio lowering. CONCLUSIONS: Of the intervention group, 42.0% (50/119) reached their daily physical activity end goal, which was associated with a markedly better effect on body composition and metabolic health compared to the effect in the entire intervention group. In this population, men are more likely to be successful in increasing physical activity. Findings demonstrate that improving the effect of such physical activity interventions requires finding new ways to increase the proportion of the population reaching the targeted goal. TRIAL REGISTRATION: Dutch Trial Registry: NTR 3045; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3045 (Archived by WebCite at http://www.webcitation.org/6KPw52dCc).

Reactive oxygen species production and mitochondrial dysfunction in white blood cells are not valid biomarkers of ageing in the very old.

Reliable and valid biomarkers of ageing (BoA) are needed to understand mechanisms, test interventions and predict the timing of adverse health events associated with ageing. Since increased reactive oxygen species (ROS) production and mitochondrial dysfunction are consequences of cellular senescence and may contribute causally to the ageing of organisms, we focused on these parameters as candidate BoA. Superoxide levels, mitochondrial mass and mitochondrial membrane potential in human peripheral blood mononuclear cells (PBMCs) and subpopulations (lymphocytes and monocytes) were measured in participants from the Newcastle 85+ study, a population-based study of the very old (aged 85 years and older). The intra- and inter-assay precision expressed as coefficient of variation (CV) for all parameters was acceptable (3% to 12% and 5 to 22% respectively). All parameters were stable in the short-term (1 week interval) in a sample of control individuals in the PBMCs and lymphocyte subpopulation, however they were unstable in the monocyte subpopulation; this rendered monocytes unreliable for further analysis. There was a significant association between superoxide levels and mitochondrial mass (positive in lymphocytes, p = 0.01) and between superoxide levels and mitochondrial membrane potential (negative in PBMCs, p = 0.01; positive in lymphocytes, p = 0.05). There were also significant associations between superoxide levels and mitochondrial parameters with other markers of oxidative stress-induced cellular senescence (p≤0.04), however some were in the opposite direction to expected. No associations were found between the measured parameters and age-related outcomes, including cognitive impairment, disability, co-morbidity and survival - questioning the validity of these parameters as candidate BoA in the very old.

Assessment of sleep and circadian rhythm disorders in the very old: the Newcastle 85+ Cohort Study.

OBJECTIVES: to examine the association between subjective and objective measures of sleep and wake and other health parameters in a cohort of the very old. DESIGN: a population-based cohort study. SETTING: primary care, North East England. PARTICIPANTS: four hundred and twenty-one men and women, aged 87-89, recruited to the Newcastle 85+ Study cohort. METHODS: sleep questionnaires were administered and sleep-wake patterns were assessed over 5-7 days with a novel wrist triaxial accelerometer. Associations between sleep measures and various health parameters, including mortality at 24 months, were examined. RESULTS: only 16% of participants perceived their sleep as severely disturbed as assessed with questionnaire responses. Wrist accelerometry showed marked variation between normal and abnormal sleep-wake cycles that did not correlate with the participants' perception of sleep. Impaired sleep-wake cycles were significantly associated with cognitive impairment, disability, depression, increased falls, body mass index and arthritis but not with any other specific disease markers and with decreased survival. CONCLUSIONS: commonly used sleep questionnaires do not differentiate well between those with objectively determined disturbance of sleep-wake cycles and those with normal cycles. Abnormal sleep-wake patterns are associated with institutionalisation, cognitive impairment, disability, depression and arthritis but not with other diseases; there is also an association with reduced survival.