204 research outputs found

    Insulin therapy and dietary adjustments to normalize glycaemia and prevent nocturnal hypoglycaemia after evening exercise in type 1 diabetes: a randomized controlled trial

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    Introduction Evening-time exercise is a frequent cause of severe hypoglycemia in type 1 diabetes, fear of which deters participation in regular exercise. Recommendations for normalizing glycemia around exercise consist of prandial adjustments to bolus insulin therapy and food composition, but this carries only short-lasting protection from hypoglycemia. Therefore, this study aimed to examine the impact of a combined basal-bolus insulin dose reduction and carbohydrate feeding strategy on glycemia and metabolic parameters following evening exercise in type 1 diabetes. Methods Ten male participants (glycated hemoglobin: 52.4±2.2 mmol/mol), treated with multiple daily injections, completed two randomized study-days, whereby administration of total daily basal insulin dose was unchanged (100%), or reduced by 20% (80%). Participants attended the laboratory at ∼08:00 h for a fasted blood sample, before returning in the evening. On arrival (∼17:00 h), participants consumed a carbohydrate meal and administered a 75% reduced rapid-acting insulin dose and 60 min later performed 45 min of treadmill running. At 60 min postexercise, participants consumed a low glycemic index (LGI) meal and administered a 50% reduced rapid-acting insulin dose, before returning home. At ∼23:00 h, participants consumed a LGI bedtime snack and returned to the laboratory the following morning (∼08:00 h) for a fasted blood sample. Venous blood samples were analyzed for glucose, glucoregulatory hormones, non-esterified fatty acids, β-hydroxybutyrate, interleukin 6, and tumor necrosis factor α. Interstitial glucose was monitored for 24 h pre-exercise and postexercise. Results Glycemia was similar until 6 h postexercise, with no hypoglycemic episodes. Beyond 6 h glucose levels fell during 100%, and nine participants experienced nocturnal hypoglycemia. Conversely, all participants during 80% were protected from nocturnal hypoglycemia, and remained protected for 24 h postexercise. All metabolic parameters were similar. Conclusions Reducing basal insulin dose with reduced prandial bolus insulin and LGI carbohydrate feeding provides protection from hypoglycemia during and for 24 h following evening exercise. This strategy is not associated with hyperglycemia, or adverse metabolic disturbances

    Estimating sleep parameters using an accelerometer without sleep diary

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    This is the final version. Available from the publisher via the DOI in this record.Wrist worn raw-data accelerometers are used increasingly in large-scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window) was compared against sleep diary in 3752 participants (range = 60–82 years) and polysomnography in sleep clinic patients (N = 28) and in healthy good sleepers (N = 22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.Medical Research Council (MRC)National Institute of Health (NIH

    Habitual Physical Activity in Mitochondrial Disease

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    Mitochondrial disease is the most common neuromuscular disease and has a profound impact upon daily life, disease and longevity. Exercise therapy has been shown to improve mitochondrial function in patients with mitochondrial disease. However, no information exists about the level of habitual physical activity of people with mitochondrial disease and its relationship with clinical phenotype.Habitual physical activity, genotype and clinical presentations were assessed in 100 patients with mitochondrial disease. Comparisons were made with a control group individually matched by age, gender and BMI. = −0.49; 95% CI −0.33, −0.63, P<0.01). There were no systematic differences in physical activity between different genotypes mitochondrial disease.These results demonstrate for the first time that low levels of physical activity are prominent in mitochondrial disease. Combined with a high prevalence of obesity, physical activity may constitute a significant and potentially modifiable risk factor in mitochondrial disease

    Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study

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    BACKGROUND: Physical activity has not been objectively measured in prospective cohorts with sufficiently large numbers to reliably detect associations with multiple health outcomes. Technological advances now make this possible. We describe the methods used to collect and analyse accelerometer measured physical activity in over 100,000 participants of the UK Biobank study, and report variation by age, sex, day, time of day, and season. METHODS: Participants were approached by email to wear a wrist-worn accelerometer for seven days that was posted to them. Physical activity information was extracted from 100Hz raw triaxial acceleration data after calibration, removal of gravity and sensor noise, and identification of wear / non-wear episodes. We report age- and sex-specific wear-time compliance and accelerometer measured physical activity, overall and by hour-of-day, week-weekend day and season. RESULTS: 103,712 datasets were received (44.8% response), with a median wear-time of 6.9 days (IQR:6.5-7.0). 96,600 participants (93.3%) provided valid data for physical activity analyses. Vector magnitude, a proxy for overall physical activity, was 7.5% (2.35mg) lower per decade of age (Cohen's d = 0.9). Women had a higher vector magnitude than men, apart from those aged 45-54yrs. There were major differences in vector magnitude by time of day (d = 0.66). Vector magnitude differences between week and weekend days (d = 0.12 for men, d = 0.09 for women) and between seasons (d = 0.27 for men, d = 0.15 for women) were small. CONCLUSIONS: It is feasible to collect and analyse objective physical activity data in large studies. The summary measure of overall physical activity is lower in older participants and age-related differences in activity are most prominent in the afternoon and evening. This work lays the foundation for studies of physical activity and its health consequences. Our summary variables are part of the UK Biobank dataset and can be used by researchers as exposures, confounding factors or outcome variables in future analyses.The UK Biobank Activity Project and the collection of activity data from participants was funded by the Wellcome Trust (https://wellcome.ac.uk/) and the Medical Research Council (http://www.mrc.ac.uk/). The analysis was supported by the British Heart Foundation Centre of Research Excellence at Oxford (http://www.cardioscience.ox.ac.uk/bhf-centre-of-research-excellence) [grant number RE/13/1/30181 to AD], the Li Ka Shing Foundation (http://www.lksf.org/) [to AD], the UK Medical Research Council (http://www.mrc.ac.uk/) [grant numbers MC_UU_12015/1 and MC_UU_12015/3 to NW and SB], the RCUK Digital Economy Research Hub on Social Inclusion through the Digital Economy (SiDE) (http://www.rcuk.ac.uk/) [EP/G066019/1 to NH], the EPSRC Centre for Doctoral Training in Digital Civics (https://www.epsrc.ac.uk/)[EP/L016176/1 to DJ], and the National Institute for Health Research (http://www.nihr.ac.uk/) [SRF-2011-04-017 to MIT]. The MRC and Wellcome Trust played a key role in the decision to establish UK Biobank, and the accelerometer data collection. No funding bodies had any role in the analysis, decision to publish, or preparation of the manuscript

    Exercise therapy in Type 2 diabetes

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    Structured exercise is considered an important cornerstone to achieve good glycemic control and improve cardiovascular risk profile in Type 2 diabetes. Current clinical guidelines acknowledge the therapeutic strength of exercise intervention. This paper reviews the wide pathophysiological problems associated with Type 2 diabetes and discusses the benefits of exercise therapy on phenotype characteristics, glycemic control and cardiovascular risk profile in Type 2 diabetes patients. Based on the currently available literature, it is concluded that Type 2 diabetes patients should be stimulated to participate in specifically designed exercise intervention programs. More attention should be paid to cardiovascular and musculoskeletal deconditioning as well as motivational factors to improve long-term treatment adherence and clinical efficacy. More clinical research is warranted to establish the efficacy of exercise intervention in a more differentiated approach for Type 2 diabetes subpopulations within different stages of the disease and various levels of co-morbidity
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