Editorial: Exercise prescription in metabolic diseases: An efficient medicine towards prevention and cure

Metabolic disease encompasses excess adiposity, dysglycaemia, type 2 diabetes mellitus, dyslipidaemia, non-alcoholic fatty liver disease (NAFLD), and hypertension that translate to excess cardiovascular disease and increased mortality. The prevalence of metabolic disease is increasing in prevalence, driven by excessive intake of energy dense food and physical inactivity, and is a major challenge for healthcare services. Physical inactivity is a major contributor to the development of metabolic disease and regular exercise can prevent, delay, and control metabolic disease

The Role of Genetic, Dietary and Lifestyle Factors in Pediatric Metabolic Syndrome: A Review of the Literature from Prenatal to Adolescence

The metabolic syndrome (MetS) is described as a cluster of health conditions that are associated with an increased risk of cardiovascular disease. The clinical diagnosis of MetS in pediatrics is challenging due to differing criteria, although the estimated prevalence continues to rise. The increased prevalence of childhood obesity and insulin resistance, in both developed and developing countries, is believed to be a major contributor to MetS diagnosis in children. We review the current literature surrounding genetic predisposition, maternal influence, epigenetics, environmental and lifestyle factors pertaining to pediatric MetS with a specific emphasis on obesity and insulin resistance. We highlight and discuss recent, key studies in prenatal through to adolescent populations and review evidence suggesting that children may be pre-disposed to obesity and insulin resistance, prenatally. We also discuss several key lifestyle drivers of these conditions including poor nutrition and dietary habits, insufficient physical activity, use of electronic devices, over-consumption of caffeinated and/or sugar-sweetened beverages, as well as the importance of sleep during childhood and adolescence in relation to metabolic health. We conclude with recommendations for preventable methods to tackle this growing pediatric public health issue, which, if current trends continue, will undoubtedly compromise the health and longevity of the next adult generation.

The Impact of Sleep Debt on Excess Adiposity and Insulin Sensitivity in Patients with Early Type 2 Diabetes Mellitus

STUDY OBJECTIVES: We examined cross-sectional and prospective associations between sleep debt and adiposity measures, as well as homeostatic model assessment-insulin resistance (HOMA-IR) in early type 2 diabetes. METHODS: Prospective data analysis from participants of a randomized controlled trial based on an intensive lifestyle intervention (usual care, diet, or diet and physical activity). Data were collected at baseline, 6 months, and 12 months post-intervention. The study was performed across five secondary care centers in the United Kingdom. Patients (n = 593) with a recent diagnosis of type 2 diabetes were recruited. Objective height and weight were ascertained for obesity status (body mass index [BMI]; ≥ 30 kg/m(2)), waist circumference (cm) for central adiposity, and fasting blood samples drawn to examine insulin resistance (IR). Seven-day sleep diaries were used to calculate weekday sleep debt at baseline, calculated as average weekend sleep duration minus average weekday sleep duration. RESULTS: At baseline, compared to those without weekday sleep debt, those with weekday sleep debt were 72% more likely to be obese (OR = 1.72 [95% CI:1.03–2.88]). At six months, weekday sleep debt was significantly associated with obesity and IR after adjustment, OR = 1.90 (95% CI:1.10–3.30), OR = 2.07 (95% CI:1.02–4.22), respectively. A further increase at 12 months was observed for sleep debt with obesity and IR: OR = 2.10 (95% CI:1.14–3.87), OR = 3.16 (95% CI:1.38–7.24), respectively. For every 30 minutes of weekday sleep debt, the risk of obesity and IR at 12 months increased by 18% and 41%, respectively. CONCLUSIONS: Sleep debt resulted in long-term metabolic disruption, which may promote the progression of type 2 diabetes in newly diagnosed patients. Sleep hygiene/education could be an important factor for future interventions to target early diabetes. CITATION: Arora T, Chen MZ, Cooper AR, Andrews RC, Taheri S. The impact of sleep debt on excess adiposity and insulin sensitivity in patients with early type 2 diabetes mellitus. J Clin Sleep Med 2016;12(5):673–680

Systematic review of clinical practice guidelines to identify recommendations for sleep in type 2 diabetes mellitus management

Introduction Sleep quality, quantity and timing have been shown to impact glycaemic control, with a role in insulin sensitivity, glucose tolerance and HbA1C levels, in both diabetic and non-diabetic populations. The aim of this study was to identify recommendations for sleep assessment and management in international clinical practice guidelines focused on type 2 diabetes mellitus management in adults. Study design: Systematic Review. Methodology Clinical practice guidelines which focused on the management of type 2 diabetes mellitus in adults were included (n = 35). Two independent reviewers utilised the Appraisal of Guidelines for Research and Evaluation tool (AGREE) II and a third reviewer resolved any disagreements. Included guidelines were assessed for recommendations about sleep in diabetes management (n = 14). Data were extracted on sleep recommendations ,themes were generated from the extracted data and narrative syntheses were created. Results From 1114 identified papers, 35 guidelines met the inclusion criteria. Fourteen of these guidelines included recommendations pertaining to sleep, which broadly fell into five categories; sleep assessment, sleep as a therapeutic target, sleep and co-morbidities of type 2 diabetes mellitus, shift work and sleep and driving. Recommendations varied across guidelines. Conclusion Few guidelines provided recommendations relating to assessment and management of sleep in type 2 diabetes care. Most of the recommendations were related to obstructive sleep apnoea. However, few guidelines discussed sleep as a therapeutic intervention for diabetes mellitus or described the potential importance of sleep quality and duration in glycaemic control

The Effects of Dietary Intervention on HIV Dyslipidaemia: A Systematic Review and Meta-Analysis

Background Efficacy of dietary intervention for treatment and prevention of HIV-related lipid disturbances has not been well established. Methods We conducted a systematic search of electronic databases supplemented with manual searches and conference abstracts, without language restriction. All randomised controlled trials (RCTs) with blood lipid outcomes, involving dietary intervention or supplementation for the treatment or prevention of adult HIV dyslipidaemia, versus no or other intervention were included. Two authors using predefined data fields, including study quality indicators, extracted data independently. Results Eighteen studies (n = 873) met our inclusion criteria. Seven RCTs for omega-3 supplementation (n = 372), and four RCTs for dietary intervention (n = 201) were meta-analysed using random-effects models. Mild statistical heterogeneity was observed. Dietary intervention reduced triglyceride levels by −0·46 mmol/l (95%CI: −0·85 to −0·07 mmol/l) compared to control. Omega-3 supplementation reduced triglyceride levels by −1.12 mmol/l, (95%CI: −1·57 to −0·67 mmol/l) and total cholesterol, −0·36 mmol/l (95%CI: −0·67 to −0·05 mmol/l) compared to placebo/control. Conclusions Both omega-3 supplementation and dietary intervention reduced triglyceride level, with the latter possibly to a smaller extent. While dietary interventions are beneficial, more stringent dietary approaches may be necessary to fully address lipid disturbances in HIV patients

Randomised controlled pilot study to assess the feasibility of a Mediterranean Portfolio dietary intervention for cardiovascular risk reduction in HIV dyslipidaemia:A study protocol

Introduction: HIV drug treatment has greatly improved life expectancy, but increased risk of cardiovascular disease remains, potentially due to the additional burdens of infection, inflammation and antiretroviral treatment. The Mediterranean Diet has been shown to reduce cardiovascular risk and mortality in the general population, but no evidence exists for this effect in the HIV population. This study will explore the feasibility of a randomised controlled trial (RCT) to examine whether a Mediterranean-style diet that incorporates a portfolio of cholesterol-lowering foods, reduces cardiovascular risk in people with HIV dyslipidaemia. Methods and analysis: 60 adults with stable HIV infection on antiretroviral treatment and low-density lipoprotein cholesterol >3 mmol/L will be recruited from 3 West Midlands HIV services. Participants will be randomised 1:1 to 1 of 2 dietary interventions, with stratification by gender and smoking status. Participants allocated to Diet1 will receive advice to reduce saturated fat intake, and those to Diet2 on how to adopt the Mediterranean Portfolio Diet with additional cholesterol-lowering foods (nuts, stanols, soya, oats, pulses). Measurements of fasting blood lipids, body composition and arterial stiffness will be conducted at baseline, and month 6 and 12 of the intervention. Food intake will be assessed using the Mediterranean Diet Score, 3-day food diaries and metabolomic biomarkers. Questionnaires will be used to assess quality of life and process evaluation. Qualitative interviews will explore barriers and facilitators to making dietary changes, and participant views on the intervention. Qualitative data will be analysed using the Framework Method. Feasibility will be assessed in terms of trial recruitment, retention, compliance to study visits and the intervention. SD of outcomes will inform the power calculation of the definitive RCT. Ethics: The West Midlands Ethics Committee has approved this study and informed consent forms. This trial is the first to test cholesterol-lowering foods in adults with HIV

Developing Effective Questionnaire-Based Prediction Models for Type 2 Diabetes for Several Ethnicities

Background: Type 2 diabetes disproportionately affects individuals of non-white ethnicity through a complex interaction of multiple factors. Early disease prediction and detection is therefore essential and requires tools that can be deployed at large scale. We aimed to tackle this problem by developing questionnaire-based prediction models for type 2 diabetes for multiple ethnicities.Methods: Logistic regression models, using questionnaire-only features, were trained on the White population of the UK Biobank, and validated in five other ethnicities and externally in Lifelines. In total, 631,748 individuals were included for prevalence prediction and 67,083 individuals for the eight-year incidence prediction. Predictive accuracy was assessed and a detailed sensitivity analysis was conducted to assess potential clinical utility. Furthermore, we compared the questionnaire algorithms to clinical non-laboratory type 2 diabetes risk tools.Findings: Our algorithms accurately predicted type 2 diabetes prevalence (AUC=0·901) and eight-year incidence (AUC=0·873) in the White UK Biobank population. Both models replicate well in Lifelines, with AUCs of 0·917 and 0·817 for prevalence and incidence. Both models performed consistently well across ethnicities, with AUCs of 0·855 to 0·894 for prevalence and from 0·819 to 0·883 for incidence. These models generally outperformed two clinically validated non-laboratory tools and correctly reclassified >3,000 type 2 diabetes cases. Model performance improved with the addition of blood biomarkers, but not with the addition of physical measurements.Interpretation: Easy-to-implement, questionnaire-based models can predict prevalent and incident type 2 diabetes with high accuracy across all ethnicities, providing a highly-scalable solution for population-wide risk stratification

The future of sleep health: a data-driven revolution in sleep science and medicine.

In recent years, there has been a significant expansion in the development and use of multi-modal sensors and technologies to monitor physical activity, sleep and circadian rhythms. These developments make accurate sleep monitoring at scale a possibility for the first time. Vast amounts of multi-sensor data are being generated with potential applications ranging from large-scale epidemiological research linking sleep patterns to disease, to wellness applications, including the sleep coaching of individuals with chronic conditions. However, in order to realise the full potential of these technologies for individuals, medicine and research, several significant challenges must be overcome. There are important outstanding questions regarding performance evaluation, as well as data storage, curation, processing, integration, modelling and interpretation. Here, we leverage expertise across neuroscience, clinical medicine, bioengineering, electrical engineering, epidemiology, computer science, mHealth and human-computer interaction to discuss the digitisation of sleep from a inter-disciplinary perspective. We introduce the state-of-the-art in sleep-monitoring technologies, and discuss the opportunities and challenges from data acquisition to the eventual application of insights in clinical and consumer settings. Further, we explore the strengths and limitations of current and emerging sensing methods with a particular focus on novel data-driven technologies, such as Artificial Intelligence