Assessment of physical capacity and metabolic parameters in marathon runners with type 1 diabetes: an observational study

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Several reports have documented the successful completion of marathons by individuals and groups with T1DM. Understanding these athletes' metabolic characteristics and physical performance could lead to safer and more effective management strategies. This study aimed to evaluate the physical capacity and metabolic parameters of individuals with T1DM who ran a marathon. Methods Five men with T1DM and five healthy controls who had completed a marathon took part in this study. Each participant underwent dual-energy X-ray absorptiometry (DXA) to assess body composition, indirect calorimetry to measure resting metabolic rate, and a maximal exercise test on a cycle ergometer to determine peak oxygen uptake (VO2max). Results We included men aged 44.0 (34.00–48.0) years with diabetes duration of 10.0 (6.0–14.0) years. Their median body mass index was 22.5 (22.0-23.3) and glycated hemoglobin was 5.8 (5.6–6.9)%. Three out of five participants achieved a time in range exceeding 70% for the 90 days preceding the marathon. Their glycemic variability coefficient was 34.6 (27.8–39.5)%. The median fat tissue content was 21.8 (20.2–24.7)%. and muscle tissue content was 73.6 (70.5–74.1)%. The median basal metabolic rate was 1932.0 (1859.0-2046.0) kcal. and the VO2 max was 44.2 (36.5–44.3) ml•kg-1•min-1. Healthy controls did not differ significantly in VO2max and metabolic parameters. Conclusions People with type 1 diabetes who complete a marathon demonstrate good metabolic control and high physical capacity. Trial Registration The trial was registered in ClinicalTrials.gov on April 13, 2025. The registration identification number is NCT06935903. Type 1 Diabetes Physical Activity Physical Endurance Absorptiometry Oxygen Consumption Background Physical activity provides numerous benefits for individuals with type 1 diabetes mellitus (T1DM), bringing similar advantages as it does for the general population. These benefits include improved insulin sensitivity, lipid profile, bone health, and psychological well-being, as well as reduction in cardiovascular risk, weight, and blood pressure [ 1 ]. However, participating in extreme physical exertion poses unique challenges for individuals with T1DM and their healthcare teams [ 1 ]. Despite these difficulties, more people with T1DM participate in endurance events like marathons [ 2 ]. A marathon, a long-distance race of 42.195 km is a particularly demanding event, even for people without diabetes [ 3 ]. Studies have documented successful marathon completion by athletes with T1DM, often achieved through meticulous pre-race planning, carbohydrate intake adjustments, and close blood sugar monitoring [ 4 , 5 ]. However, these athletes' specific physical capacity and metabolic characteristics have not yet been investigated. The maximal oxygen uptake (VO2max) indicates cardiorespiratory fitness used to assess an individual’s physical capacity. It is defined as the maximal integrated capacity of the pulmonary, cardiovascular, and muscular systems to uptake, transport, and utilize oxygen [ 6 ]. Typically, men exhibit V ˙ O 2 max values approximately 20% higher than women [ 7 ]. The meta-analysis based on 3278 individuals with T1DM reported the mean VO2 max 38.5 mL/min/kg. VO2max is negatively correlated with glycated hemoglobin (HbA1c) [ 8 ]. Accurate resting energy expenditure (REE) measurement is crucial for adequately assessing an individual’s nutritional requirements [ 9 , 10 ]. Predictive equations like the Harris-Benedict equation are often inadequate because they fail to consider various disease-related factors affecting REE, especially in people with T1DM [ 11 , 12 ]. In clinical settings, indirect calorimetry remains the only reliable method for measuring REE [ 9 , 10 ]. The most accurate method to assess body composition is densitometry (DXA) which estimates the percentage of fat tissue, bone tissue, and lean tissue [ 13 ]. Long-distance runners tend to have low adipose tissue percentage, but people with type 1 diabetes have a higher fat percentage than people without diabetes [ 14 , 15 ]. This knowledge gap hinders our understanding of the physiological adaptations that enable T1DM individuals to excel in such demanding events. While case reports showcase individual triumphs [ 4 , 5 ], a more comprehensive analysis is needed. Furthermore, most existing research focuses on shorter endurance activities like half-marathons [ 16 , 17 ] with limited data on the specific metabolic adaptations required to complete a full marathon in individuals with T1DM. Therefore, this study aims to evaluate the physical capacity and metabolic parameters of individuals with T1DM who have completed a marathon. Material and Methods This study investigated the physical capacity and metabolic parameters of five male participants with T1DM and five healthy controls who had completed a marathon. Written informed consent was obtained from all participants. The study adhered to the ethical guidelines set by the local Ethical Committee (approval No.1245/18) and followed the principles of the Declaration of Helsinki [18]. Participants with confirmed T1DM were recruited between August and September 2023 through flyers, online advertisements, and collaborations with local marathon organizations. The inclusion criteria were: A diagnosis of T1DM for at least 1 year. Age ≥ 18 years. Written informed consent and adherence to the study protocol. The exclusion criteria included: Pregnancy. Use of medications significantly affecting metabolism or exercise performance Presence of chronic medical or psychiatric conditions limiting safe participation Presence of advanced chronic complications of diabetes: proliferative retinopathy, dia-betic kidney disease in stages III–V, cardiovascular diseases Inability to safely complete maximal exercise testing. This study included a control group of five healthy male marathon runners to provide a comparative baseline for the physical capacity and metabolic parameters of participants with T1DM. The control group was matched to the T1DM participants in terms of age, sex, and similar training backgrounds to ensure comparability in physical activity levels. All control participants were free from any chronic medical conditions or medications that could potentially influence metabolism or exercise performance. The control group was recruited through local running clubs, online advertisements, and marathon events during the same timeframe as the T1DM group (August to September 2023). Each participant completed a form detailing illness history, complications, coexisting diseases, and smoking status. The initial assessments included anamnesis and physical examination. A comprehensive baseline assessment was conducted at a single visit to gather information on demographics, medical history, and diabetes management practices. Demographic and anthropometric data were recorded, including age, sex, height, weight, and body mass index (BMI), defining obesity (BMI ≥ 30.0) and overweight (25.0 ≤ BMI < 30.0). A detailed medical history was collected, including T1DM duration, the presence of diabetes-related complications, and any other relevant medical conditions. Information was also gathered regarding the type of insulin regimen (MDI or CSII), daily insulin dosage, and HbA1c (standardized laboratory assay). Self-reported blood glucose monitoring frequency and the history of hypoglycemic events were documented. Additionally, participants reported engagement in regular physical activity, including type, duration, and frequency of exercise over the past year. Dual-energy X-ray absorptiometry (DXA) assessed body composition, including fat mass, lean mass, and bone mineral density. Whole-body DXA scans were conducted using a Hologic Horizon DXA System® (Quirugil, Bogotá, Colombia) with Discovery software, version 12.3 (Bellingham, WA, USA). A single trained operator performed all scans following standard laboratory protocol [19]. Subjects were positioned supine with arms at their sides and palms in a neutral position. To ensure consistent data quality, the equipment was calibrated daily with a known calibration standard according to the manufacturer’s guidelines (step phantom scan for body composition calibration). We calculated body fat percentage using the following equation: (fat mass / (fat mass + bone-free lean tissue mass + bone mineral content) × 100). The DXA device was calibrated each morning with a phantom before measurements. The DXA directly measured total body fat in grams and percentage, and android fat mass in grams. Resting metabolic rate (RMR) tests were conducted using indirect calorimetry with a Vyntus CPX (Vyaire Medical, Mettawa, IL, USA), calibrated daily with standard gases according to the manufacturer guidelines. Tests were performed in a quiet, dimly lit room maintained at 21–22°C. Each participant lay supine, and after a 5-minute acclimation, data were recorded for 25 minutes. The initial 5 minutes were discarded, and the subsequent 20 minutes were used for analysis [20]. Participants, who arrived after an 8-hour overnight fast, were asked to remain still but awake throughout the assessment. For consistency, a ventilated hood was used instead of a mouthpiece and nose clip, reducing measurement variability for the respiratory exchange ratio. Oxygen (V˙O2) and carbon dioxide (V˙CO2) data, recorded every 10 seconds, were converted to kcal/day using the Weir equation, with mean respiratory exchange ratio, carbohydrate, and fat oxidation rates calculated based on the Zuntz table [20, 21]. This protocol aligns with best practices from Compher et al [20]. A metabolic cart (e.g., Vyntus CPX, Vyaire Medical, Mettawa, IL, USA) was used during a maximal exercise test on a specialized cycle ergometer (e.g., Excalibur Sport 2, Lode, Groningen, The Netherlands) to assess peak oxygen uptake (VO2max). The system was calibrated before each test according to the manufacturer's instructions. The cardiopulmonary exercise testing (CPET) protocol involved collecting initial gas exchange measurements while participants rested comfortably. Afterward, a three-minute light cycling warm-up period was followed. The progressive exercise phase commenced with a low workload that gradually increased at predetermined increments (15–20 watts per minute) until volitional exhaustion or symptom-limited termination. The highest oxygen consumption (VO2) achieved during the CPET was defined as the VO2max. Data Analysis Descriptive statistics (median, interquartile range) were used to summarize participant characteristics, physical capacity measures, and metabolic parameters. We performed all statistical analyses using custom R scripts (version 4.4.1, R Project for Statistical Computing, Vienna, Austria). Categorical data are reported as counts (percentages), whereas numerical data are presented as medians (25th–75th percentiles). We used the Mann-Whitney U test to compare numerical variables and the Chi-square test to analyze categorical variables. Dedicated software provided by the manufacturer was used to analyze CPET data: Peak oxygen uptake (VO2max) Respiratory exchange ratio (RER) Ventilation (VE) Workload at peak VO2 (Wpeak) Gas exchange threshold (GET) Maximal predicted oxygen uptake in men was calculated using the Wasserman and Hansen method: W = (predicted VO 2 max − VO 2 unloaded)/103 [22, 23]. Results The participants with T1DM were all men, with a median age of 44.0 years (range 34.00–48.0 years) and a median diabetes duration of 10.0 years (range 6.0–14.0 years). Their basic characteristics are presented in Table 1 . They had a normal body mass index (BMI) 22.5 kg/m² (22.0-23.3 kg/m²). The runners with T1DM had no severe coexisting diseases. One was diagnosed with hypertension, another with hypothyroidism (with thyroid-stimulating hormone levels within the normal range) and hyperlipidemia. The remaining participants had no diseases other than T1DM. Table 1 General characteristics of type 1 diabetes marathon runners Parameter Participant 1 Participant 2 Participant 3 Participant 4 Participant 5 All participants (n = 5) Age [years] 32 34 48 44 55 44 (34–48) Diabetes duration [years] 6 10 1 14 42 10 (6–14) Diabetes complications - - - - Non-proliferative retinopathy 1/5 Time of sports per week [hours] 12 6 12 3.5 4 6 (4–12) Running time [years] 8 8 13 5 11 8 (8–11) height (m) 1.8 1.83 1.72 1.89 1.77 1.8 (1.8–1.8) Body mass (kg) 73 84 65.1 78 73 73 (73–78) BMI [kg/m^2] 22.5 25.1 22.0 21.8 23.3 22.5 (22-23.3) HbA1c [%] 5.8 6.9 5.3 5.6 6.9 5.8 (5.6–6.9) HbA1c [mmol/mol] 40 52 34 38 52 40 (38–52) TIR [%] 70.0 60.0 100.0 91.0 67.0 70 (65–90) TAR [%] 17.0 37.0 0 8.0 32.0 20 (4-34.5) TBR [%] 13.0 3.0 0 1.0 1.0 1 (0.5-8) Average glycemia 118.0 158.0 107.0 130.0 163.0 130 (118–158) CV [%] 44.0 39.5 12.5 27.8 34.6 34.6 (27.8–39.5) Marathon time [minutes] 188.9 239.3 268.6 299.9 218.0 239.3 (218.0-268.6) HbA1c - glycated hemoglobin TIR - time in range TAR – time above range TBR – time below range CV - coefficient of variation of glycemia- BMI - body mass index The control group consisted of five men aged 47 (range: 43–47) - marathon runners matched to the T1DM participants. They presented no significant differences in the basic characteristics (Table 2 ). They had no chronic diseases. Table 2 Comparison of T1DM participants and healthy controls Clinical feature T1DM participants n = 5 (50%) Healthy controls n = 5 (50%) p-value General characteristics Men 5 (100%) 5 (100%) 1 Age [years] 44 (34–49) 47 (43–47) 0.69 Height [m] 1.8 (1.77–1.83) 1.82 (1.8–1.88) 0.69 Weight [kg] 73 (73–78) 82 (76–83) 0.55 BMI [kg/m^2] 22.5 (22-23.3) 23.5 (23.5–23.7) 0.31 DXA adipose tissue percentage [%] 21.8 (20.2–24.7) 23.2 (22.9–24) 0.84 lean tissue percentage [%] 78.2 (75.3–79.8) 76.8 (74.5–77.1) 0.69 BMD [g/cm2] 1.2 (1.18–1.24) 1.25 (1.22–1.26) 0.22 FAT mass [kg] 15.9 (14.3–18.6) 17.3 (15.6–19.6) 0.69 Muscle mass [kg] 53.9 (53.7–54.1) 54.4 (54.3–57.1) 0.42 Bone mass [kg] 2.76 (2.74–2.87) 2.92 (2.72–3.03) 0.69 Indirect calorimetry RMR [Kcal/day] 1932 (1859–2046) 2059 (1944–2138) 0.42 Spirometry FVC [L] 5.3 (5.2–5.6) 5.3 (5.2–5.5) 0.55 VC max [L] 5.7 (5.6–5.7) 5.7 (5.2–5.8) 0.84 FEV1[%] 76.7 (73.8–78) 74.5 (74.4–75.5) 0.84 Spiroergometry VO2 max [ml•kg-1•min-1] 44.2 (36.5–44.3) 49.6 (37.1–52.1) 0.42 RMR - resting metabolic rate FVC - forced vital capacity VC max - maximal vital capacity FEV1 - forced expiratory volume in 1 second VO2 max - maximal oxygen uptake BMD - bone mineral density- p < 0.05 bolded Runners with T1DM demonstrated good glycemic control with HbA1c of 5.8(5.6–6.9)%/ 40 (38–52) mmol/mol. All of them had running experience of at least 5 years and 3 of them had finished the marathon in the past. They did not experience severe hypoglycemia or ketoacidosis during the year before the marathon. Based on the Clarke hypoglycemia questionnaire results, all T1DM participants demonstrated hypoglycemia awareness. Three out of five T1DM participants achieved a time in range (TIR) exceeding 70% for 90 days before the marathon, indicating good overall glycemic control in the pre-competition period. The glycemic variability coefficient was 34.6% (range 27.8–39.5%), suggesting moderate glycemic variability among the participants. Daily insulin intake varied from 0.26 to 0.59 units/kg/day. The basal insulin dose was 13 (7–22) units, and the preprandial insulin dose was 20.25 (14.25-27) units. Table 3 summarizes the metabolic and physical capacity parameters. DXA analysis shows that runners with T1DM had a body fat percentage of 21.8% (20.2–24.7%) and a muscle mass percentage of 73.6% (70.5–74.1%), indicating relatively low fat mass and high muscle mass in this group of marathon participants. Table 3 Physical capacity and metabolic parameters of type 1 diabetes marathon runners Parameter Participant 1 Participant 2 Participant 3 Participant 4 Participant 5 Densitometry adipose tissue percentage [%] 21.8 27.2 17.3 24.7 20.2 lean tissue percentage [%] 74.1 70.5 78.6 69.1 73.6 BMD (g/cm2) 1.2 1.3 1.1 1.2 1.2 Indirect calorimetry RMR (Kcal/day) 2046.0 2126.0 1859.0 1932.0 1851.0 Spirometry FVC (L) 5.62 5.874 5.349 4.422 5.215 VC max [L] 5.665 6.115 5.652 4.883 5.617 FEV1[%] 73.786 78.002 73.198 78.613 76.686 Spiroergometry VO2 max [ml•kg-1•min-1] 50.2 44.2 36.5 31.4 44.3 RMR - resting metabolic rate FVC - forced vital capacity VC max - maximal vital capacity FEV1 - forced expiratory volume in 1 second VO2 max - maximal oxygen uptake BMD - bone mineral density The participants’ mean resting metabolic rate (RMR) reached 1932 kcal (1859–2046 kcal), reflecting their baseline energy expenditure. Their peak oxygen uptake (VO2max), a key measure of cardiorespiratory fitness, was 44.2 ml·kg⁻¹·min⁻¹ (36.5–44.3 ml·kg⁻¹·min⁻¹), which was slightly lower than that of the healthy controls. However, this difference did not reach statistical significance. None of the other measured parameters demonstrated significant differences between T1DM runners and the control group (Table 2 ). Discussion This study assessed the characteristics, metabolic parameters, and physical capacity of marathon runners with T1DM. T1DM individuals can achieve high levels of physical fitness and successfully compete in marathons. We found no significant differences between T1DM runners and matched healthy controls in VO2max, RMR and body composition. A marathon run is an exhausting feat that requires training preparation and an adequate energy supply [ 3 ]. Carbohydrates stored in the muscles and liver in the form of glycogen are the primary source of energy during a long-distance run [ 2 ]. In healthy people, insulin secretion decreases via increased sympathoadrenal drive during endurance exercise. It is strictly regulated depending on exercise intensity and current glycemia. The lack of pancreas insulin secretion in people with T1DM results in difficulties in avoiding episodes of hypoglycemia and hyperglycemia during the marathon [ 2 , 3 ]. Therefore, among runners with T1DM, the time spent in euglycemia (70-180mg/dl) is significantly lower for people with T1DM compared to healthy controls [ 24 ]. However, during the half-marathon, runners with T1DM and a training history of at least 5 years achieved similar performance times compared to healthy controls [ 16 ]. The participants in this study demonstrated good glycemic control, with a mean HbA1c of 5.8%/40 mmol/mol. Three out of five participants achieved a time in range exceeding 70% for the 90 days before the marathon, indicating excellent pre-competition glycemic management. Their moderate glycemic variability coefficient suggests potential areas for further optimization, but it does not appear to have hindered their marathon performance [ 2 , 25 ]. The man with T1DM who finished the marathon was described for the first time in 1987 in the British Journal of Sports Medicine. He was a 35-year-old man with T1DM lasting 17 years and no complications [ 26 ]. On 1 November 1992, the International Diabetic Athletes Association organized support for runners with T1DM during a marathon in New York City. Thirteen participants took part in this event [ 4 ]. Another observational study was performed on 12 participants with type 1 diabetes running the Paris Marathon using continuous glucose monitoring. All of them finished the marathon safely without episodes of hypoglycemia. Compared to marathon runners who took part in the 2016 marathon in Paris, our participants were older (44 vs. 40 years), had lower HbA1c (5.8 vs. 6.8%/40 vs 51 mmol/mol), had longer diabetes duration (10 vs. 8 years), and had slightly lower BMI (22.5 vs. 23.1 kg/m2). Despite these challenges, several studies have shown the effectiveness of using advanced technologies like insulin pumps, continuous glucose monitoring (CGM), and closed-loop systems in maintaining glycemic control during exercise [ 27 – 29 ]. Case studies have demonstrated the successful marathon completion with CGM and strategic carbohydrate consumption [ 5 , 30 ]. The body composition analysis revealed a low fat mass and a high muscle mass percentage, consistent with the physical demands of marathon running. However, healthy men attending triathlons presented a lower fat percentage [ 7 ]. Their high basal metabolic rate reflects the increased energy expenditure required to maintain this level of lean body mass. Peak oxygen uptake (VO2 max) is a key indicator of cardiorespiratory fitness, and the participants in this study demonstrated a level comparable to trained athletes. According to Mysliwiec et al., T1DM individuals with higher VO2 max tend to experience fewer glycemic excursions and need less carbohydrate supplementation than people with lower VO2 max [ 31 ]. The meta-analysis based on 3278 individuals with T1DM showed a mean VO2 max of 38.5 mL/min/kg [ 8 ]. In our study, marathon runners achieved higher values − 44.2 ml•kg-1•min-1 (range 36.5–44.3 ml•kg-1•min-1). The Vo2 max results achieved by healthy amateurs running the marathon were similar [ 32 ]. Healthy men taking part in triathlon regularly presented better VO2 max than participants of our study (59.67 ± 5.81 ml•kg-1•min-1), but they were younger and trained in different types of sports [ 7 ]. These findings align with previous studies highlighting the benefits of physical activity for people with T1DM [ 1 ]. Regular exercise offers numerous advantages, including improved insulin sensitivity, weight management, and cardiovascular health [ 1 ]. This study adds to the growing evidence that well-controlled T1DM should not be a barrier to marathon participation. However, careful planning, meticulous glycemic monitoring, and potentially advanced diabetes management technologies are crucial for safe and successful completion. Our study has limitations. The small sample size restricts the generalizability of the findings. A larger, more diverse cohort would provide a more comprehensive picture of the physical characteristics and metabolic profiles of marathon runners with T1DM. However, the small sample size and the specific demographic of the participants in this study highlight the need for further research. Future studies should focus on larger and more diverse cohorts, explore the long-term effects of endurance sports, and evaluate the latest diabetes management technologies to develop comprehensive guidelines for T1DM athletes. By addressing these areas, we can better support T1DM individuals in pursuing their athletic goals safely and effectively. Conclusions To conclude, people with T1DM who complete a marathon demonstrate good metabolic control and high physical capacity. Abbreviations BMI – Body Mass Index CGM – Continuous Glucose Monitoring CPET – Cardiopulmonary Exercise Testing CSII – Continuous Subcutaneous Insulin Infusion DXA – Dual-energy X-ray Absorptiometry GET – Gas Exchange Threshold HbA1c – Glycated Hemoglobin MDI – Multiple Daily Injections REE – Resting Energy Expenditure RER – Respiratory Exchange Ratio RMR – Resting Metabolic Rate T1DM – Type 1 Diabetes Mellitus TIR – Time in Range VE – Ventilation VO₂max – Maximal (Peak) Oxygen Uptake Wpeak – Workload at Peak VO₂ Declarations Ethics approval and consent to participate This study was conducted according to the decision of the Ethical Committee of Poznan University of Medical Sciences (approval No.1245/18) and followed the principles of the Declaration of Helsinki. All participants provided written informed consent. Consent for publication Not applicable Availability of data and materials The datasets generated and analyzed during the current study are not publicly available due to privacy and confidentiality restrictions related to participant data. Still, they are available from the corresponding author on reasonable request. Competing interests Not applicable Funding Project "Development of the University Centre for Sports and Medical Studies in Poznań” (NdS/544750/2021/2022) as part of the Science for Society of the Department of Education and Science Authors' contributions AG, MK, MD, and DZZ conceptualized the study. AG, MK, MD, AK, MP, and PB developed the methodology. AG, MK, and MD performed the formal analysis and investigation. MK wrote the original draft of the manuscript. MK, MD, PB, AK, MP, AA, MMa, AB, AS, MMi, DZZ, and AG reviewed and edited the manuscript. AG and DZZ acquired the funding. MK, MD, PB, AK, MP, AA, MMa, AB, AS, MMi, DZZ, and AG provided the necessary resources. AG and DZZ supervised the project. All authors read and approved the final manuscript. Acknowledgements The authors would like to express their sincere gratitude to Przemysław Guzik, Coordinator of the University Centre for Sports and Medical Studies in Poznań, for his invaluable support and guidance throughout this research project. We also wish to extend our appreciation to all the marathon participants, whose commitment and collaboration were essential to the successful completion of this study. Clinical trial registration statement This study is registered at ClinicalTrials.gov: https://clinicaltrials.gov/study/NCT06935903?term=NCT06935903&rank=1. The registration identification number is NCT06935903. References Chimen M, Kennedy A, Nirantharakumar K, et al (2012) What are the health benefits of physical activity in type 1 diabetes mellitus? A literature review. 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British Journal of Sports Medicine 21:51. https://doi.org/10.1136/bjsm.21.1.51-a O M, Mc R, Ml E, et al (2020) Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA). Diabetologia 63:. https://doi.org/10.1007/s00125-020-05263-9 Eckstein ML, Weilguni B, Tauschmann M, et al (2021) Time in Range for Closed-Loop Systems versus Standard of Care during Physical Exercise in People with Type 1 Diabetes: A Systematic Review and Meta-Analysis. J Clin Med 10:2445. https://doi.org/10.3390/jcm10112445 Yardley JE, Iscoe KE, Sigal RJ, et al (2013) Insulin Pump Therapy Is Associated with Less Post-Exercise Hyperglycemia than Multiple Daily Injections: An Observational Study of Physically Active Type 1 Diabetes Patients. Diabetes Technology & Therapeutics 15:84–88. https://doi.org/10.1089/dia.2012.0168 Boom L van den, Ziko H, Mader JK (2021) Safely finishing a half marathon by an adult with type 1 diabetes using a commercially available hybrid closed‐loop system. Journal of Diabetes Investigation 12:450. https://doi.org/10.1111/jdi.13356 Myśliwiec A, Skalska M, Michalak A, et al (2021) Responses to Low- and High-Intensity Exercise in Adolescents with Type 1 Diabetes in Relation to Their Level of VO2 Max. Int J Environ Res Public Health 18:692. https://doi.org/10.3390/ijerph18020692 Billat V, Palacin F, Poinsard L, et al (2022) Heart Rate Does Not Reflect the %VO2max in Recreational Runners during the Marathon. Int J Environ Res Public Health 19:12451. https://doi.org/10.3390/ijerph191912451 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Nov, 2025 Read the published version in BMC Sports Science, Medicine and Rehabilitation → Version 1 posted Reviewers agreed at journal 10 Jun, 2025 Reviewers agreed at journal 10 Jun, 2025 Reviewers agreed at journal 10 Jun, 2025 Reviewers invited by journal 10 Jun, 2025 Editor assigned by journal 09 Jun, 2025 Editor invited by journal 04 Jun, 2025 Submission checks completed at journal 04 Jun, 2025 First submitted to journal 04 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6666251","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":469237965,"identity":"b0569635-7c43-4834-a0e4-13e816fe1f2d","order_by":0,"name":"Michał Kulecki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIie3PMUvEMBTA8XcE6pKza0TxMzwQKnKDH8Sl0OGWFtcOUgoFR12vcPgZnE5ueyHQWyKuBW9QhE4OdbnZRE4UIYe3ieRPAiHklxAAn+8Pdvpw/UR9bpfx164w88BpWj2QE20PGULfCHcSSpkaXm5DBuU9yfqmKHCRNC89qLNjYPKRw9JJGLuK6W2mBOpujAQqm5dBMuLQOUkAhLKekcA2jYQlt8SjfQ7KSTjEqIbTwpDz1ZqEq41EQGpIyewrwecrwUaCoonlpFF7te4ioXGczavg6GSK7r9gWKm+vyjC3UXSiTwfZXc71XP7mi8PXeTnDWawjwX9UqyVbRvi8/l8/7x3255ffPZbeoYAAAAASUVORK5CYII=","orcid":"","institution":"Poznan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Michał","middleName":"","lastName":"Kulecki","suffix":""},{"id":469237967,"identity":"8abbe060-01d6-40a6-a313-52e82eaf32ae","order_by":1,"name":"Marcin Daroszewski","email":"","orcid":"","institution":"Poznan University of Medical 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Dorota","middleName":"","lastName":"Zozulińska-Ziółkiewicz","suffix":""},{"id":469237978,"identity":"efd4643b-a3d4-4a8d-b6b8-333e74c86c74","order_by":11,"name":"Andrzej Gawrecki","email":"","orcid":"","institution":"Poznan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Andrzej","middleName":"","lastName":"Gawrecki","suffix":""}],"badges":[],"createdAt":"2025-05-14 17:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6666251/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6666251/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13102-025-01303-2","type":"published","date":"2025-11-03T15:56:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":95563896,"identity":"d2cbf7ec-d2ba-4c61-8ccd-11e8c99e0353","added_by":"auto","created_at":"2025-11-10 16:01:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1043792,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6666251/v1/2e4a8ec6-f4ce-4d1e-8951-1aef7cec789e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of physical capacity and metabolic parameters in marathon runners with type 1 diabetes: an observational study","fulltext":[{"header":"Background","content":"\u003cp\u003ePhysical activity provides numerous benefits for individuals with type 1 diabetes mellitus (T1DM), bringing similar advantages as it does for the general population. These benefits include improved insulin sensitivity, lipid profile, bone health, and psychological well-being, as well as reduction in cardiovascular risk, weight, and blood pressure [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, participating in extreme physical exertion poses unique challenges for individuals with T1DM and their healthcare teams [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite these difficulties, more people with T1DM participate in endurance events like marathons [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA marathon, a long-distance race of 42.195 km is a particularly demanding event, even for people without diabetes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Studies have documented successful marathon completion by athletes with T1DM, often achieved through meticulous pre-race planning, carbohydrate intake adjustments, and close blood sugar monitoring [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, these athletes' specific physical capacity and metabolic characteristics have not yet been investigated.\u003c/p\u003e \u003cp\u003eThe maximal oxygen uptake (VO2max) indicates cardiorespiratory fitness used to assess an individual\u0026rsquo;s physical capacity. It is defined as the maximal integrated capacity of the pulmonary, cardiovascular, and muscular systems to uptake, transport, and utilize oxygen [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Typically, men exhibit \u003cem\u003eV\u003c/em\u003e˙\u003cem\u003eO\u003c/em\u003e2\u003cem\u003emax\u003c/em\u003e values approximately 20% higher than women [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The meta-analysis based on 3278 individuals with T1DM reported the mean VO2 max 38.5 mL/min/kg. VO2max is negatively correlated with glycated hemoglobin (HbA1c) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccurate resting energy expenditure (REE) measurement is crucial for adequately assessing an individual\u0026rsquo;s nutritional requirements [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Predictive equations like the Harris-Benedict equation are often inadequate because they fail to consider various disease-related factors affecting REE, especially in people with T1DM [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In clinical settings, indirect calorimetry remains the only reliable method for measuring REE [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe most accurate method to assess body composition is densitometry (DXA) which estimates the percentage of fat tissue, bone tissue, and lean tissue [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Long-distance runners tend to have low adipose tissue percentage, but people with type 1 diabetes have a higher fat percentage than people without diabetes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis knowledge gap hinders our understanding of the physiological adaptations that enable T1DM individuals to excel in such demanding events. While case reports showcase individual triumphs [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], a more comprehensive analysis is needed. Furthermore, most existing research focuses on shorter endurance activities like half-marathons [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] with limited data on the specific metabolic adaptations required to complete a full marathon in individuals with T1DM.\u003c/p\u003e \u003cp\u003eTherefore, this study aims to evaluate the physical capacity and metabolic parameters of individuals with T1DM who have completed a marathon.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eThis study investigated the physical capacity and metabolic parameters of five male participants with T1DM and five healthy controls who had completed a marathon. Written informed consent was obtained from all participants. The study adhered to the ethical guidelines set by the local Ethical Committee (approval No.1245/18) and followed the principles of the Declaration of Helsinki [18].\u003c/p\u003e\n\u003cp\u003eParticipants with confirmed T1DM were recruited between August and September 2023 through flyers, online advertisements, and collaborations with local marathon organizations. The inclusion criteria were:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eA diagnosis of T1DM for at least 1 year.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAge ≥ 18 years.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eWritten informed consent and adherence to the study protocol.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe exclusion criteria included:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003ePregnancy.\u003c/li\u003e\n \u003cli\u003eUse of medications significantly affecting metabolism or exercise performance\u003c/li\u003e\n \u003cli\u003ePresence of chronic medical or psychiatric conditions limiting safe participation\u003c/li\u003e\n \u003cli\u003ePresence of advanced chronic complications of diabetes: proliferative retinopathy, dia-betic kidney disease in stages III–V, cardiovascular diseases\u003c/li\u003e\n \u003cli\u003eInability to safely complete maximal exercise testing.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis study included a control group of five healthy male marathon runners to provide a comparative baseline for the physical capacity and metabolic parameters of participants with T1DM. The control group was matched to the T1DM participants in terms of age, sex, and similar training backgrounds to ensure comparability in physical activity levels. All control participants were free from any chronic medical conditions or medications that could potentially influence metabolism or exercise performance. The control group was recruited through local running clubs, online advertisements, and marathon events during the same timeframe as the T1DM group (August to September 2023).\u003c/p\u003e\n\u003cp\u003eEach participant completed a form detailing illness history, complications, coexisting diseases, and smoking status. The initial assessments included anamnesis and physical examination.\u003c/p\u003e\n\u003cp\u003eA comprehensive baseline assessment was conducted at a single visit to gather information on demographics, medical history, and diabetes management practices. Demographic and anthropometric data were recorded, including age, sex, height, weight, and body mass index (BMI), defining obesity (BMI ≥ 30.0) and overweight (25.0 ≤ BMI \u0026lt; 30.0).\u003c/p\u003e\n\u003cp\u003eA detailed medical history was collected, including T1DM duration, the presence of diabetes-related complications, and any other relevant medical conditions. Information was also gathered regarding the type of insulin regimen (MDI or CSII), daily insulin dosage, and HbA1c (standardized laboratory assay).\u003c/p\u003e\n\u003cp\u003eSelf-reported blood glucose monitoring frequency and the history of hypoglycemic events were documented. Additionally, participants reported engagement in regular physical activity, including type, duration, and frequency of exercise over the past year.\u003c/p\u003e\n\u003cp\u003eDual-energy X-ray absorptiometry (DXA) assessed body composition, including fat mass, lean mass, and bone mineral density. Whole-body DXA scans were conducted using a Hologic Horizon DXA System® (Quirugil, Bogotá, Colombia) with Discovery software, version 12.3 (Bellingham, WA, USA). A single trained operator performed all scans following standard laboratory protocol [19]. Subjects were positioned supine with arms at their sides and palms in a neutral position. To ensure consistent data quality, the equipment was calibrated daily with a known calibration standard according to the manufacturer’s guidelines (step phantom scan for body composition calibration). We calculated body fat percentage using the following equation: (fat mass / (fat mass + bone-free lean tissue mass + bone mineral content) × 100). The DXA device was calibrated each morning with a phantom before measurements. The DXA directly measured total body fat in grams and percentage, and android fat mass in grams.\u003c/p\u003e\n\u003cp\u003eResting metabolic rate (RMR) tests were conducted using indirect calorimetry with a Vyntus CPX (Vyaire Medical, Mettawa, IL, USA), calibrated daily with standard gases according to the manufacturer guidelines. Tests were performed in a quiet, dimly lit room maintained at 21–22°C. Each participant lay supine, and after a 5-minute acclimation, data were recorded for 25 minutes. The initial 5 minutes were discarded, and the subsequent 20 minutes were used for analysis [20].\u003c/p\u003e\n\u003cp\u003eParticipants, who arrived after an 8-hour overnight fast, were asked to remain still but awake throughout the assessment. For consistency, a ventilated hood was used instead of a mouthpiece and nose clip, reducing measurement variability for the respiratory exchange ratio. Oxygen (V˙O2) and carbon dioxide (V˙CO2) data, recorded every 10 seconds, were converted to kcal/day using the Weir equation, with mean respiratory exchange ratio, carbohydrate, and fat oxidation rates calculated based on the Zuntz table [20, 21]. This protocol aligns with best practices from Compher et al [20].\u003c/p\u003e\n\u003cp\u003eA metabolic cart (e.g., Vyntus CPX, Vyaire Medical, Mettawa, IL, USA) was used during a maximal exercise test on a specialized cycle ergometer (e.g., Excalibur Sport 2, Lode, Groningen, The Netherlands) to assess peak oxygen uptake (VO2max). The system was calibrated before each test according to the manufacturer's instructions.\u003c/p\u003e\n\u003cp\u003eThe cardiopulmonary exercise testing (CPET) protocol involved collecting initial gas exchange measurements while participants rested comfortably. Afterward, a three-minute light cycling warm-up period was followed. The progressive exercise phase commenced with a low workload that gradually increased at predetermined increments (15–20 watts per minute) until volitional exhaustion or symptom-limited termination.\u003c/p\u003e\n\u003cp\u003eThe highest oxygen consumption (VO2) achieved during the CPET was defined as the VO2max.\u003c/p\u003e\n\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eData Analysis\u003c/h2\u003e\n \u003cp\u003eDescriptive statistics (median, interquartile range) were used to summarize participant characteristics, physical capacity measures, and metabolic parameters. We performed all statistical analyses using custom R scripts (version 4.4.1, R Project for Statistical Computing, Vienna, Austria). Categorical data are reported as counts (percentages), whereas numerical data are presented as medians (25th–75th percentiles). We used the Mann-Whitney U test to compare numerical variables and the Chi-square test to analyze categorical variables.\u003c/p\u003e\n \u003cp\u003eDedicated software provided by the manufacturer was used to analyze CPET data:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ePeak oxygen uptake (VO2max)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eRespiratory exchange ratio (RER)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eVentilation (VE)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eWorkload at peak VO2 (Wpeak)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eGas exchange threshold (GET)\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cdiv\u003e\n \u003cp\u003eMaximal predicted oxygen uptake in men was calculated using the Wasserman and Hansen method:\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eW = (predicted VO\u003csub\u003e2\u003c/sub\u003emax − VO\u003csub\u003e2\u003c/sub\u003eunloaded)/103 [22, 23].\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe participants with T1DM were all men, with a median age of 44.0 years (range 34.00\u0026ndash;48.0 years) and a median diabetes duration of 10.0 years (range 6.0\u0026ndash;14.0 years). Their basic characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. They had a normal body mass index (BMI) 22.5 kg/m\u0026sup2; (22.0-23.3 kg/m\u0026sup2;). The runners with T1DM had no severe coexisting diseases. One was diagnosed with hypertension, another with hypothyroidism (with thyroid-stimulating hormone levels within the normal range) and hyperlipidemia. The remaining participants had no diseases other than T1DM.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral characteristics of type 1 diabetes marathon runners\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipant 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParticipant 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eParticipant 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParticipant 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eParticipant 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAll participants (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge [years]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44 (34\u0026ndash;48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes duration [years]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (6\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNon-proliferative retinopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1/5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime of sports per week [hours]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (4\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRunning time [years]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (8\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eheight (m)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.8 (1.8\u0026ndash;1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody mass (kg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73 (73\u0026ndash;78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI [kg/m^2]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.5 (22-23.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHbA1c [%]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.8 (5.6\u0026ndash;6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHbA1c [mmol/mol]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40 (38\u0026ndash;52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTIR [%]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70 (65\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTAR [%]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20 (4-34.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTBR [%]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0.5-8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAverage glycemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e130.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e163.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e130 (118\u0026ndash;158)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCV [%]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.6 (27.8\u0026ndash;39.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarathon time [minutes]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e268.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e299.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e218.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e239.3 (218.0-268.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eHbA1c - glycated hemoglobin\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eTIR - time in range\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eTAR \u0026ndash; time above range\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eTBR \u0026ndash; time below range\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCV - coefficient of variation of glycemia-\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eBMI - body mass index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe control group consisted of five men aged 47 (range: 43\u0026ndash;47) - marathon runners matched to the T1DM participants. They presented no significant differences in the basic characteristics (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). They had no chronic diseases.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of T1DM participants and healthy controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eClinical feature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1DM participants\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;5 (50%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHealthy controls\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;5 (50%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eGeneral characteristics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge [years]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (34\u0026ndash;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (43\u0026ndash;47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHeight [m]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8 (1.77\u0026ndash;1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.82 (1.8\u0026ndash;1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWeight [kg]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (73\u0026ndash;78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 (76\u0026ndash;83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI [kg/m^2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5 (22-23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.5 (23.5\u0026ndash;23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDXA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eadipose tissue percentage [%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.8 (20.2\u0026ndash;24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.2 (22.9\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003elean tissue percentage [%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.2 (75.3\u0026ndash;79.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.8 (74.5\u0026ndash;77.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMD [g/cm2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2 (1.18\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.25 (1.22\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFAT mass [kg]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9 (14.3\u0026ndash;18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3 (15.6\u0026ndash;19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMuscle mass [kg]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.9 (53.7\u0026ndash;54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.4 (54.3\u0026ndash;57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBone mass [kg]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76 (2.74\u0026ndash;2.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.92 (2.72\u0026ndash;3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndirect calorimetry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRMR [Kcal/day]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1932 (1859\u0026ndash;2046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2059 (1944\u0026ndash;2138)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpirometry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFVC [L]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3 (5.2\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3 (5.2\u0026ndash;5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVC max [L]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.7 (5.6\u0026ndash;5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7 (5.2\u0026ndash;5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFEV1[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.7 (73.8\u0026ndash;78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.5 (74.4\u0026ndash;75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpiroergometry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVO2 max [ml\u0026bull;kg-1\u0026bull;min-1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.2 (36.5\u0026ndash;44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.6 (37.1\u0026ndash;52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eRMR - resting metabolic rate\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eFVC - forced vital capacity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eVC max - maximal vital capacity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eFEV1 - forced expiratory volume in 1 second\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eVO2 max - maximal oxygen uptake\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMD - bone mineral density-\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 bolded\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRunners with T1DM demonstrated good glycemic control with HbA1c of 5.8(5.6\u0026ndash;6.9)%/ 40 (38\u0026ndash;52) mmol/mol. All of them had running experience of at least 5 years and 3 of them had finished the marathon in the past. They did not experience severe hypoglycemia or ketoacidosis during the year before the marathon. Based on the Clarke hypoglycemia questionnaire results, all T1DM participants demonstrated hypoglycemia awareness.\u003c/p\u003e \u003cp\u003eThree out of five T1DM participants achieved a time in range (TIR) exceeding 70% for 90 days before the marathon, indicating good overall glycemic control in the pre-competition period. The glycemic variability coefficient was 34.6% (range 27.8\u0026ndash;39.5%), suggesting moderate glycemic variability among the participants. Daily insulin intake varied from 0.26 to 0.59 units/kg/day. The basal insulin dose was 13 (7\u0026ndash;22) units, and the preprandial insulin dose was 20.25 (14.25-27) units.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the metabolic and physical capacity parameters. DXA analysis shows that runners with T1DM had a body fat percentage of 21.8% (20.2\u0026ndash;24.7%) and a muscle mass percentage of 73.6% (70.5\u0026ndash;74.1%), indicating relatively low fat mass and high muscle mass in this group of marathon participants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysical capacity and metabolic parameters of type 1 diabetes marathon runners\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipant 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParticipant 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eParticipant 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParticipant 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eParticipant 5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDensitometry\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadipose tissue percentage [%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elean tissue percentage [%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMD (g/cm2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndirect calorimetry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMR (Kcal/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2046.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2126.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1859.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1932.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1851.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpirometry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFVC (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVC max [L]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.617\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEV1[%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpiroergometry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVO2 max [ml\u0026bull;kg-1\u0026bull;min-1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eRMR - resting metabolic rate\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eFVC - forced vital capacity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eVC max - maximal vital capacity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eFEV1 - forced expiratory volume in 1 second\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eVO2 max - maximal oxygen uptake\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eBMD - bone mineral density\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe participants\u0026rsquo; mean resting metabolic rate (RMR) reached 1932 kcal (1859\u0026ndash;2046 kcal), reflecting their baseline energy expenditure. Their peak oxygen uptake (VO2max), a key measure of cardiorespiratory fitness, was 44.2 ml\u0026middot;kg⁻\u0026sup1;\u0026middot;min⁻\u0026sup1; (36.5\u0026ndash;44.3 ml\u0026middot;kg⁻\u0026sup1;\u0026middot;min⁻\u0026sup1;), which was slightly lower than that of the healthy controls. However, this difference did not reach statistical significance. None of the other measured parameters demonstrated significant differences between T1DM runners and the control group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed the characteristics, metabolic parameters, and physical capacity of marathon runners with T1DM. T1DM individuals can achieve high levels of physical fitness and successfully compete in marathons. We found no significant differences between T1DM runners and matched healthy controls in VO2max, RMR and body composition.\u003c/p\u003e \u003cp\u003eA marathon run is an exhausting feat that requires training preparation and an adequate energy supply [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Carbohydrates stored in the muscles and liver in the form of glycogen are the primary source of energy during a long-distance run [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In healthy people, insulin secretion decreases via increased sympathoadrenal drive during endurance exercise. It is strictly regulated depending on exercise intensity and current glycemia. The lack of pancreas insulin secretion in people with T1DM results in difficulties in avoiding episodes of hypoglycemia and hyperglycemia during the marathon [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, among runners with T1DM, the time spent in euglycemia (70-180mg/dl) is significantly lower for people with T1DM compared to healthy controls [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, during the half-marathon, runners with T1DM and a training history of at least 5 years achieved similar performance times compared to healthy controls [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe participants in this study demonstrated good glycemic control, with a mean HbA1c of 5.8%/40 mmol/mol. Three out of five participants achieved a time in range exceeding 70% for the 90 days before the marathon, indicating excellent pre-competition glycemic management. Their moderate glycemic variability coefficient suggests potential areas for further optimization, but it does not appear to have hindered their marathon performance [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe man with T1DM who finished the marathon was described for the first time in 1987 in the British Journal of Sports Medicine. He was a 35-year-old man with T1DM lasting 17 years and no complications [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. On 1 November 1992, the International Diabetic Athletes Association organized support for runners with T1DM during a marathon in New York City. Thirteen participants took part in this event [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Another observational study was performed on 12 participants with type 1 diabetes running the Paris Marathon using continuous glucose monitoring. All of them finished the marathon safely without episodes of hypoglycemia. Compared to marathon runners who took part in the 2016 marathon in Paris, our participants were older (44 vs. 40 years), had lower HbA1c (5.8 vs. 6.8%/40 vs 51 mmol/mol), had longer diabetes duration (10 vs. 8 years), and had slightly lower BMI (22.5 vs. 23.1 kg/m2).\u003c/p\u003e \u003cp\u003eDespite these challenges, several studies have shown the effectiveness of using advanced technologies like insulin pumps, continuous glucose monitoring (CGM), and closed-loop systems in maintaining glycemic control during exercise [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Case studies have demonstrated the successful marathon completion with CGM and strategic carbohydrate consumption [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe body composition analysis revealed a low fat mass and a high muscle mass percentage, consistent with the physical demands of marathon running. However, healthy men attending triathlons presented a lower fat percentage [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Their high basal metabolic rate reflects the increased energy expenditure required to maintain this level of lean body mass.\u003c/p\u003e \u003cp\u003ePeak oxygen uptake (VO2 max) is a key indicator of cardiorespiratory fitness, and the participants in this study demonstrated a level comparable to trained athletes. According to Mysliwiec et al., T1DM individuals with higher VO2 max tend to experience fewer glycemic excursions and need less carbohydrate supplementation than people with lower VO2 max [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The meta-analysis based on 3278 individuals with T1DM showed a mean VO2 max of 38.5 mL/min/kg [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In our study, marathon runners achieved higher values \u0026minus;\u0026thinsp;44.2 ml\u0026bull;kg-1\u0026bull;min-1 (range 36.5\u0026ndash;44.3 ml\u0026bull;kg-1\u0026bull;min-1). The Vo2 max results achieved by healthy amateurs running the marathon were similar [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Healthy men taking part in triathlon regularly presented better VO2 max than participants of our study (59.67\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81 ml\u0026bull;kg-1\u0026bull;min-1), but they were younger and trained in different types of sports [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese findings align with previous studies highlighting the benefits of physical activity for people with T1DM [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Regular exercise offers numerous advantages, including improved insulin sensitivity, weight management, and cardiovascular health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study adds to the growing evidence that well-controlled T1DM should not be a barrier to marathon participation. However, careful planning, meticulous glycemic monitoring, and potentially advanced diabetes management technologies are crucial for safe and successful completion.\u003c/p\u003e \u003cp\u003eOur study has limitations. The small sample size restricts the generalizability of the findings. A larger, more diverse cohort would provide a more comprehensive picture of the physical characteristics and metabolic profiles of marathon runners with T1DM.\u003c/p\u003e \u003cp\u003eHowever, the small sample size and the specific demographic of the participants in this study highlight the need for further research. Future studies should focus on larger and more diverse cohorts, explore the long-term effects of endurance sports, and evaluate the latest diabetes management technologies to develop comprehensive guidelines for T1DM athletes. By addressing these areas, we can better support T1DM individuals in pursuing their athletic goals safely and effectively.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eTo conclude, people with T1DM who complete a marathon demonstrate good metabolic control and high physical capacity.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI \u0026ndash; Body Mass Index\u003c/p\u003e\n\u003cp\u003eCGM \u0026ndash; Continuous Glucose Monitoring\u003c/p\u003e\n\u003cp\u003eCPET \u0026ndash; Cardiopulmonary Exercise Testing\u003c/p\u003e\n\u003cp\u003eCSII \u0026ndash; Continuous Subcutaneous Insulin Infusion\u003c/p\u003e\n\u003cp\u003eDXA \u0026ndash; Dual-energy X-ray Absorptiometry\u003c/p\u003e\n\u003cp\u003eGET \u0026ndash; Gas Exchange Threshold\u003c/p\u003e\n\u003cp\u003eHbA1c \u0026ndash; Glycated Hemoglobin\u003c/p\u003e\n\u003cp\u003eMDI \u0026ndash; Multiple Daily Injections\u003c/p\u003e\n\u003cp\u003eREE \u0026ndash; Resting Energy Expenditure\u003c/p\u003e\n\u003cp\u003eRER \u0026ndash; Respiratory Exchange Ratio\u003c/p\u003e\n\u003cp\u003eRMR \u0026ndash; Resting Metabolic Rate\u003c/p\u003e\n\u003cp\u003eT1DM \u0026ndash; Type 1 Diabetes Mellitus\u003c/p\u003e\n\u003cp\u003eTIR \u0026ndash; Time in Range\u003c/p\u003e\n\u003cp\u003eVE \u0026ndash; Ventilation\u003c/p\u003e\n\u003cp\u003eVO₂max \u0026ndash; Maximal (Peak) Oxygen Uptake\u003c/p\u003e\n\u003cp\u003eWpeak \u0026ndash; Workload at Peak VO₂\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted according to the decision of the Ethical Committee of Poznan University of Medical Sciences (approval No.1245/18) and followed the principles of the Declaration of Helsinki. All participants provided written informed consent.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to privacy and confidentiality restrictions related to participant data. Still, they are available from the corresponding author on reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProject \u0026quot;Development of the University Centre for Sports and Medical Studies in Poznań\u0026rdquo; (NdS/544750/2021/2022) as part of the Science for Society of the Department of Education and Science\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAG, MK, MD, and DZZ conceptualized the study. AG, MK, MD, AK, MP, and PB developed the methodology. AG, MK, and MD performed the formal analysis and investigation. MK wrote the original draft of the manuscript. MK, MD, PB, AK, MP, AA, MMa, AB, AS, MMi, DZZ, and AG reviewed and edited the manuscript. AG and DZZ acquired the funding. MK, MD, PB, AK, MP, AA, MMa, AB, AS, MMi, DZZ, and AG provided the necessary resources. AG and DZZ supervised the project. All authors read and approved the final manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Przemysław Guzik, Coordinator of the University Centre for Sports and Medical Studies in Poznań, for his invaluable support and guidance throughout this research project. We also wish to extend our appreciation to all the marathon participants, whose commitment and collaboration were essential to the successful completion of this study. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is registered at ClinicalTrials.gov: https://clinicaltrials.gov/study/NCT06935903?term=NCT06935903\u0026amp;rank=1. The registration identification number is NCT06935903.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChimen M, Kennedy A, Nirantharakumar K, et al (2012) What are the health benefits of physical activity in type 1 diabetes mellitus? A literature review. Diabetologia 55:542\u0026ndash;551. https://doi.org/10.1007/s00125-011-2403-2\u003c/li\u003e\n\u003cli\u003eRiddell MC, Scott SN, Fournier PA, et al (2020) The competitive athlete with type 1 diabetes. Diabetologia 63:1475\u0026ndash;1490. https://doi.org/10.1007/s00125-020-05183-8\u003c/li\u003e\n\u003cli\u003eRapoport BI (2010) Metabolic Factors Limiting Performance in Marathon Runners. PLoS Comput Biol 6:e1000960. https://doi.org/10.1371/journal.pcbi.1000960\u003c/li\u003e\n\u003cli\u003eGrimm J-J, Muchnick S (1993) Type I Diabetes and Marathon Running. Diabetes Care 16:1624. https://doi.org/10.2337/diacare.16.12.1624a\u003c/li\u003e\n\u003cli\u003eThuillier P, Domun N, Sonnet E, et al (2022) Prevention of exercise-induced hypoglycemia in 12 patients with type 1 diabetes running the Paris Marathon using continuous glucose monitoring: A prospective, single-center observational study. Diabetes Metab 48:101321. https://doi.org/10.1016/j.diabet.2022.101321\u003c/li\u003e\n\u003cli\u003ePoole DC, Wilkerson DP, Jones AM (2008) Validity of criteria for establishing maximal O2 uptake during ramp exercise tests. Eur J Appl Physiol 102:403\u0026ndash;410. https://doi.org/10.1007/s00421-007-0596-3\u003c/li\u003e\n\u003cli\u003eLassen MCH, Biering-S\u0026oslash;rensen T, J\u0026oslash;rgensen PG, et al (2021) Sex differences in the association between myocardial function and prognosis in type 1 diabetes without known heart disease: the Thousand \u0026amp; 1 Study. Eur Heart J Cardiovasc Imaging 22:1017\u0026ndash;1025. https://doi.org/10.1093/ehjci/jeaa227\u003c/li\u003e\n\u003cli\u003eMl E, F A, Fjr D, et al (2022) Association of HbA1c with VO2max in Individuals with Type 1 Diabetes: A Systematic Review and Meta-Analysis. Metabolites 12:. https://doi.org/10.3390/metabo12111017\u003c/li\u003e\n\u003cli\u003eAchamrah N, Delsoglio M, De Waele E, et al (2021) Indirect calorimetry: The 6 main issues. Clinical Nutrition 40:4\u0026ndash;14. https://doi.org/10.1016/j.clnu.2020.06.024\u003c/li\u003e\n\u003cli\u003eOshima T, Berger MM, De Waele E, et al (2017) Indirect calorimetry in nutritional therapy. A position paper by the ICALIC study group. Clinical Nutrition 36:651\u0026ndash;662. https://doi.org/10.1016/j.clnu.2016.06.010\u003c/li\u003e\n\u003cli\u003eHarris JA, Benedict FG (1918) A Biometric Study of Human Basal Metabolism. Proceedings of the National Academy of Sciences 4:370\u0026ndash;373. https://doi.org/10.1073/pnas.4.12.370\u003c/li\u003e\n\u003cli\u003eDayan A, Ergen N, Bulgurlu SS (2024) Assessment of estimated and measured resting metabolic rates in type 1 and type 2 diabetes mellitus. Heliyon 10:e28248. https://doi.org/10.1016/j.heliyon.2024.e28248\u003c/li\u003e\n\u003cli\u003eShepherd JA, Ng BK, Sommer MJ, Heymsfield SB (2017) Body composition by DXA. Bone 104:101\u0026ndash;105. https://doi.org/10.1016/j.bone.2017.06.010\u003c/li\u003e\n\u003cli\u003eNsamba J, Eroju P, Drenos F, Mathews E (2022) Body Composition Characteristics of Type 1 Diabetes Children and Adolescents: A Hospital-Based Case-Control Study in Uganda. Children (Basel) 9:1720. https://doi.org/10.3390/children9111720\u003c/li\u003e\n\u003cli\u003eKutac P, Bunc V, Buzga M, et al (2023) The effect of regular running on body weight and fat tissue of individuals aged 18 to 65. Journal of Physiological Anthropology 42:28. https://doi.org/10.1186/s40101-023-00348-x\u003c/li\u003e\n\u003cli\u003eMourot L, Fornasiero A, Rakobowchuk M, et al (2020) Similar cardiovascular and autonomic responses in trained type 1 diabetes mellitus and healthy participants in response to half marathon. Diabetes Res Clin Pract 160:107995. https://doi.org/10.1016/j.diabres.2019.107995\u003c/li\u003e\n\u003cli\u003eMurillo S, Brugnara L, Novials A (2010) One year follow-up in a group of half-marathon runners with type-1 diabetes treated with insulin analogues. J Sports Med Phys Fitness 50:506\u0026ndash;510\u003c/li\u003e\n\u003cli\u003eSawicka-Gutaj N, Gruszczyński D, Guzik P, et al (2022) Publication ethics of human studies in the light of the Declaration of Helsinki \u0026ndash; a mini-review. Journal of Medical Science 91:e700\u0026ndash;e700. https://doi.org/10.20883/medical.e700\u003c/li\u003e\n\u003cli\u003eSutter T, Duboeuf F, Chapurlat R, et al (2021) DXA body composition corrective factors between Hologic Discovery models to conduct multicenter studies. Bone 142:115683. https://doi.org/10.1016/j.bone.2020.115683\u003c/li\u003e\n\u003cli\u003eCompher C, Frankenfield D, Keim N, et al (2006) Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc 106:881\u0026ndash;903. https://doi.org/10.1016/j.jada.2006.02.009\u003c/li\u003e\n\u003cli\u003eWeir JBDB (1949) New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol 109:1\u0026ndash;9. https://doi.org/10.1113/jphysiol.1949.sp004363\u003c/li\u003e\n\u003cli\u003eHansen JE, Sue DY, Wasserman K (1984) Predicted values for clinical exercise testing. Am Rev Respir Dis 129:S49-55. https://doi.org/10.1164/arrd.1984.129.2P2.S49\u003c/li\u003e\n\u003cli\u003eNeder JA, Phillips DB, Marillier M, et al (2021) Clinical Interpretation of Cardiopulmonary Exercise Testing: Current Pitfalls and Limitations. Front Physiol 12:552000. https://doi.org/10.3389/fphys.2021.552000\u003c/li\u003e\n\u003cli\u003eMoser O, Mueller A, Eckstein ML, et al (2020) Improved glycaemic variability and basal insulin dose reduction during a running competition in recreationally active adults with type 1 diabetes\u0026mdash;A single-centre, prospective, controlled observational study. PLOS ONE 15:e0239091. https://doi.org/10.1371/journal.pone.0239091\u003c/li\u003e\n\u003cli\u003eAraszkiewicz A et al 2022 Guidelines on the management of patients with diabetes. Current Topics in Diabetes 2022 | Curr Top Diabetes, 2022; 2 (1): 1\u0026ndash;134\u003c/li\u003e\n\u003cli\u003eJensen TH, Darre E, Holmich P, Jahnsen F (1987) Insulin-dependent diabetes mellitus and marathon running. British Journal of Sports Medicine 21:51. https://doi.org/10.1136/bjsm.21.1.51-a\u003c/li\u003e\n\u003cli\u003eO M, Mc R, Ml E, et al (2020) Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA). Diabetologia 63:. https://doi.org/10.1007/s00125-020-05263-9\u003c/li\u003e\n\u003cli\u003eEckstein ML, Weilguni B, Tauschmann M, et al (2021) Time in Range for Closed-Loop Systems versus Standard of Care during Physical Exercise in People with Type 1 Diabetes: A Systematic Review and Meta-Analysis. J Clin Med 10:2445. https://doi.org/10.3390/jcm10112445\u003c/li\u003e\n\u003cli\u003eYardley JE, Iscoe KE, Sigal RJ, et al (2013) Insulin Pump Therapy Is Associated with Less Post-Exercise Hyperglycemia than Multiple Daily Injections: An Observational Study of Physically Active Type 1 Diabetes Patients. Diabetes Technology \u0026amp; Therapeutics 15:84\u0026ndash;88. https://doi.org/10.1089/dia.2012.0168\u003c/li\u003e\n\u003cli\u003eBoom L van den, Ziko H, Mader JK (2021) Safely finishing a half marathon by an adult with type 1 diabetes using a commercially available hybrid closed‐loop system. Journal of Diabetes Investigation 12:450. https://doi.org/10.1111/jdi.13356\u003c/li\u003e\n\u003cli\u003eMyśliwiec A, Skalska M, Michalak A, et al (2021) Responses to Low- and High-Intensity Exercise in Adolescents with Type 1 Diabetes in Relation to Their Level of VO2 Max. Int J Environ Res Public Health 18:692. https://doi.org/10.3390/ijerph18020692\u003c/li\u003e\n\u003cli\u003eBillat V, Palacin F, Poinsard L, et al (2022) Heart Rate Does Not Reflect the %VO2max in Recreational Runners during the Marathon. Int J Environ Res Public Health 19:12451. https://doi.org/10.3390/ijerph191912451\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Type 1 Diabetes, Physical Activity, Physical Endurance, Absorptiometry, Oxygen Consumption","lastPublishedDoi":"10.21203/rs.3.rs-6666251/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6666251/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIndividuals with type 1 diabetes mellitus (T1DM) participating in extreme physical exertion, such as marathon running, pose unique challenges for both participants and their healthcare teams. Several reports have documented the successful completion of marathons by individuals and groups with T1DM. Understanding these athletes' metabolic characteristics and physical performance could lead to safer and more effective management strategies. This study aimed to evaluate the physical capacity and metabolic parameters of individuals with T1DM who ran a marathon.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFive men with T1DM and five healthy controls who had completed a marathon took part in this study. Each participant underwent dual-energy X-ray absorptiometry (DXA) to assess body composition, indirect calorimetry to measure resting metabolic rate, and a maximal exercise test on a cycle ergometer to determine peak oxygen uptake (VO2max).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe included men aged 44.0 (34.00\u0026ndash;48.0) years with diabetes duration of 10.0 (6.0\u0026ndash;14.0) years. Their median body mass index was 22.5 (22.0-23.3) and glycated hemoglobin was 5.8 (5.6\u0026ndash;6.9)%. Three out of five participants achieved a time in range exceeding 70% for the 90 days preceding the marathon. Their glycemic variability coefficient was 34.6 (27.8\u0026ndash;39.5)%. The median fat tissue content was 21.8 (20.2\u0026ndash;24.7)%. and muscle tissue content was 73.6 (70.5\u0026ndash;74.1)%. The median basal metabolic rate was 1932.0 (1859.0-2046.0) kcal. and the VO2 max was 44.2 (36.5\u0026ndash;44.3) ml\u0026bull;kg-1\u0026bull;min-1. Healthy controls did not differ significantly in VO2max and metabolic parameters.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePeople with type 1 diabetes who complete a marathon demonstrate good metabolic control and high physical capacity.\u003c/p\u003e\u003ch2\u003eTrial Registration\u003c/h2\u003e \u003cp\u003eThe trial was registered in ClinicalTrials.gov on April 13, 2025. 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