Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes. Graphical abstract

In the last few years, the muscular system has gained attention due to the discovery of the muscle-secretome and its high potency for retaining or regaining health. These cytokines, described as myokines, released by the working muscle, are involved in anti-inflammatory, metabolic and immunological processes. These are able to influence human health in a positive way and are a target of research in metabolic diseases, cancer, neurological diseases, and other non-communicable diseases. Therefore, different types of exercise training were investigated in the last few years to find associations between exercise, myokines and their effects on human health. Particularly, resistance training turned out to be a powerful stimulus to enhance myokine release. As there are different types of resistance training, different myokines are stimulated, depending on the mode of training. This narrative review gives an overview about resistance training and how it can be utilized to stimulate myokine production in order to gain a certain health effect. Finally, the question of why resistance training is an important key regulator in human health will be discussed.

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin‐dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

Regular physical activity and exercise (PA) are cornerstones of diabetes care for individuals with type 1 diabetes. In recent years, the availability of automated insulin delivery (AID) systems has improved the ability of people with type 1 diabetes to achieve the recommended glucose target ranges. PA provide additional health benefits but can cause glucose fluctuations, which challenges current AID systems. While an increasing number of clinical trials and reviews are being published on different AID systems and PA, it seems prudent at this time to collate this information and develop a position statement on the topic. This joint European Association for the Study of Diabetes (EASD)/International Society for Pediatric and Adolescent Diabetes (ISPAD) position statement reviews current evidence on AID systems and provides detailed clinical practice points for managing PA in children, adolescents and adults with type 1 diabetes using AID technology. It discusses each commercially available AID system individually and provides guidance on their use in PA. Additionally, it addresses different glucose responses to PA and provides stratified therapy options to maintain glucose levels within the target ranges for these age groups. Graphical Abstract

Physical literacy (PL), given as a multidimensional construct, is considered a person’s capacity and commitment to a physically active lifestyle. We investigated the effect of a holistic physical exercise training on PL among physically inactive adults. A non-randomised controlled study was conducted. Thirty-one physically inactive adults in the intervention group (IG; 81% females, 44 ± 16 years) participated in a holistic physical exercise training intervention once weekly for 15 weeks. A matched, non-exercising control group (CG) consisted of 30 physically inactive adults (80% female, 45 ± 11 years). PL, compliance and sociodemographic parameters were measured. PL was evaluated by a questionnaire, covering five domains: physical activity behaviour, attitude towards a physically active lifestyle, exercise motivation, knowledge and self-confidence/self-efficacy. Data were analysed using ANCOVA models, adjusted for age, gender and BMI at baseline. At post-training intervention, the IG showed significant improvements in PL (p = 0.001) and in the domains physical activity behaviour (p = 0.02) and exercise self-confidence/self-efficacy (p = 0.001), with no changes overserved for the CG regarding PL and those domains. No intervention effect were found for the other three domains, i.e. attitude, knowledge and motivation. Additionally, for the IG baseline BMI was identified to be positively correlated with physical exercise-induced improvements in PL (β = 0.51, p = 0.01). The results from this study are very useful for further public health activities, which aim at helping physically inactive adults to adopt a physically active lifestyle as well as for the development of further PL intervention strategies. This pilot-study was a first attempt to measure PL in inactive adults. Yet, a validated measurement tool is still not available. Further research is necessary to determine the psychometric properties for this PL questionnaire. German Clinical Trials Register (DRKS), DRKS00013991 , date of registration: 09.02.2018, retrospectively registered.

Aims: The efficacy of flash glucose monitoring (flash GM) systems has been demonstrated by improvements in glycaemia; however, during high rates of glucose flux, the performance of continuous glucose monitoring systems was impaired, as detailed in previous studies. This study aimed to determine the performance of the flash GM system during daily‐life glycaemic challenges such as carbohydrate‐rich meals, bolus insulin‐induced glycaemic disturbances and acute physical exercise in individuals with type 1 diabetes. Materials and methods: This study comprised four randomized trial visits with alternating pre‐ and post‐exercise bolus insulin doses. Throughout the four 14‐hour inpatient phases, 19 participants received three carbohydrate‐rich meals and performed moderate‐intensity exercise. Venous blood glucose and capillary blood glucose during exercise was compared to interstitial glucose concentrations. Flash GM accuracy was assessed by median absolute relative difference (MARD) (interquartile range [IQR]) using the Bland–Altman method and Clark error grid, as well as according to guidelines for integrated CGM approvals (Class II–510(K)). Results: The overall MARD (IQR) during inpatient phases was 14.3% (6.9%–22.8%), during hypoglycaemia (≤3.9 mmol/L) was 31.6% (16.2%–46.8%), during euglycaemia (4.0 mmol/L − 9.9 mmol/L) was 16.0% (8.5%–24.0%) and during hyperglycaemia (≥10 mmol/L) was 9.4% (5.1%–15.7%). Overall Bland–Altman analysis showed a bias (95% LoA) of 1.26 mmol/L (−1.67 to 4.19 mmol/L). The overall MARD during acute exercise was 29.8% (17.5%–39.8%), during hypoglycaemia was 45.1% (35.2%–51.1%), during euglycaemia was 30.7% (18.7%–39.2%) and during hyperglycaemia was 16.3% (10.0%–22.8%). Conclusion: Flash GM interstitial glucose readings were not sufficiently accurate within the hypoglycaemic range and during acute exercise and require confirmatory blood glucose measurements.