A-Z Diabetes Boot Camp 2026

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Diagnosis and Pathophysiology of Diabetes: Key Mechanisms and Diagnostic Approaches

Diabetes mellitus is a group of metabolic diseases marked by chronic hyperglycemia due to defects in insulin secretion, insulin action, or both. Understanding its pathophysiology and accurate diagnosis is crucial for effective management and prevention of complications.

Pathophysiology of Diabetes

• Type 1 Diabetes (T1DM): Characterized by autoimmune destruction of pancreatic β-cells, leading to absolute insulin deficiency. Autoantibodies can be detected before symptom onset, and genetic and environmental factors influence disease progression (Basevi, 2011; Katsarou et al., 2017; Bonnefond et al., 2023).
• Type 2 Diabetes (T2DM): Results from a combination of insulin resistance and inadequate compensatory insulin secretion. Key mechanisms include β-cell dysfunction, insulin resistance in muscle, liver, and adipose tissue, mitochondrial dysfunction, oxidative stress, and chronic inflammation. Obesity, lifestyle, and genetic predisposition are major contributors (Galicia-Garcia et al., 2020; Basevi, 2011; Schwartz et al., 2017; Młynarska et al., 2025; Nolan et al., 2011; Ortíz-Martínez et al., 2022).
• Other Types: Monogenic diabetes arises from single-gene mutations, while secondary diabetes can result from endocrine disorders or pancreatic diseases (Bonnefond et al., 2023; Popoviciu et al., 2023).

Diagnostic Criteria and Methods

Figure 1: Table summarizing key diagnostic criteria and methods for diabetes.

Heterogeneity and Subtypes

Recent research highlights the heterogeneity of diabetes, especially T2DM, with subtypes based on pathophysiological markers (e.g., insulin resistance, β-cell dysfunction, obesity-related, age-related) and genetic/phenotypic clustering. This stratification may guide personalized treatment and prognosis (Skyler et al., 2016; Wesolowska-Andersen et al., 2022; Wagner et al., 2020; Guo & Varghese, 2025; Bonnefond et al., 2023).

Complications and Importance of Early Diagnosis

Chronic hyperglycemia leads to microvascular (neuropathy, nephropathy, retinopathy) and macrovascular (cardiovascular disease) complications. Early and accurate diagnosis, including screening for complications, is essential to reduce morbidity and mortality (Basevi, 2011; Galiero et al., 2023; Młynarska et al., 2025; Ritchie & Abel, 2020; Moon & Jang, 2022).

Conclusion

Diabetes encompasses diverse disorders unified by hyperglycemia, with pathophysiology ranging from autoimmune β-cell destruction to insulin resistance and genetic defects. Diagnosis relies on glucose-based criteria, with emerging biomarkers and machine learning enhancing precision. Early detection and understanding of subtypes are vital for effective management and prevention of complications.

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References

Galicia-Garcia, U., Benito-Vicente, A., Jebari, S., Larrea-Sebal, A., Siddiqi, H., Uribe, K., Ostolaza, H., & Martín, C. (2020). Pathophysiology of Type 2 Diabetes Mellitus. International Journal of Molecular Sciences, 21. https://doi.org/10.3390/ijms21176275

Basevi, V. (2011). Diagnosis and Classification of Diabetes Mellitus. Diabetes Care, 34, S62 - S69. https://doi.org/10.2337/dc11-s062

Galiero, R., Caturano, A., Vetrano, E., Beccia, D., Brin, C., Alfano, M., Di Salvo, J., Epifani, R., Piacevole, A., Tagliaferri, G., Rocco, M., Iadicicco, I., Docimo, G., Rinaldi, L., Sardu, C., Salvatore, T., Marfella, R., & Sasso, F. (2023). Peripheral Neuropathy in Diabetes Mellitus: Pathogenetic Mechanisms and Diagnostic Options. International Journal of Molecular Sciences, 24. https://doi.org/10.3390/ijms24043554

Olisah, C., Smith, L., & Smith, M. (2022). Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective. Computer methods and programs in biomedicine, 220, 106773. https://doi.org/10.1016/j.cmpb.2022.106773

Skyler, J., Bakris, G., Bonifacio, E., Darsow, T., Eckel, R., Groop, L., Groop, P., Handelsman, Y., Insel, R., Mathieu, C., McElvaine, A., Palmer, J., Pugliese, A., Schatz, D., Sosenko, J., Wilding, J., & Ratner, R. (2016). Differentiation of Diabetes by Pathophysiology, Natural History, and Prognosis. Diabetes, 66, 241 - 255. https://doi.org/10.2337/db16-0806

McCance, D., Hanson, R., Pettitt, D., Bennett, P., Hadden, D., & Knowler, W. (1997). Diagnosing diabetes mellitus – do we need new criteria?. Diabetologia, 40, 247-255. https://doi.org/10.1007/s001250050671

Schwartz, S., Epstein, S., Corkey, B., Grant, S., Gavin, J., Aguilar, R., & Herman, M. (2017). A Unified Pathophysiological Construct of Diabetes and its Complications. Trends in Endocrinology & Metabolism, 28, 645-655. https://doi.org/10.1016/j.tem.2017.05.005

Młynarska, E., Czarnik, W., Dzieża, N., Jędraszak, W., Majchrowicz, G., Prusinowski, F., Stabrawa, M., Rysz, J., & Franczyk, B. (2025). Type 2 Diabetes Mellitus: New Pathogenetic Mechanisms, Treatment and the Most Important Complications. International Journal of Molecular Sciences, 26. https://doi.org/10.3390/ijms26031094

Wesolowska-Andersen, A., Brorsson, C., Bizzotto, R. et al. (2022). Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study. Cell Reports Medicine, 3. https://doi.org/10.1016/j.xcrm.2021.100477

Katsarou, A., Gudbjörnsdottir, S., Rawshani, A., Dabelea, D., Bonifacio, E., Anderson, B., Jacobsen, L., Schatz, D., & Lernmark, Å. (2017). Type 1 diabetes mellitus. Nature Reviews Disease Primers, 3. https://doi.org/10.1038/nrdp.2017.16

Wagner, R., Heni, M., Tabák, Á., Machann, J., Schick, F., Randrianarisoa, E., De Angelis, H., Birkenfeld, A., Stefan, N., Peter, A., Häring, H., & Fritsche, A. (2020). Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes. Nature Medicine, 27, 49 - 57. https://doi.org/10.1038/s41591-020-1116-9

Moon, J., & Jang, H. (2022). Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications. Diabetes & Metabolism Journal, 46, 3 - 14. https://doi.org/10.4093/dmj.2021.0335

Guo, J., & Varghese, J. (2025). 290-OR: Association of Pathophysiological Markers with Type 2 Diabetes Subtypes. Diabetes. https://doi.org/10.2337/db25-290-or

Ritchie, R., & Abel, E. (2020). Basic Mechanisms of Diabetic Heart Disease.. Circulation Research. https://doi.org/10.1161/circresaha.120.315913

Bonnefond, A., Unnikrishnan, R., Doria, A., Vaxillaire, M., Kulkarni, R., Mohan, V., Trischitta, V., & Froguel, P. (2023). Monogenic diabetes. Nature Reviews Disease Primers, 9, 1-16. https://doi.org/10.1038/s41572-023-00421-w

Nolan, C., Damm, P., & Prentki, M. (2011). Type 2 diabetes across generations: from pathophysiology to prevention and management. The Lancet, 378, 169-181. https://doi.org/10.1016/s0140-6736(11)60614-4

Popoviciu, M., Păduraru, L., Nutas, R., Ujoc, A., Yahya, G., Metwally, K., & Cavalu, S. (2023). Diabetes Mellitus Secondary to Endocrine Diseases: An Update of Diagnostic and Treatment Particularities. International Journal of Molecular Sciences, 24. https://doi.org/10.3390/ijms241612676

Ortíz-Martínez, M., González‐González, M., Martagon, A., Hlavinka, V., Willson, R., & Rito‐Palomares, M. (2022). Recent Developments in Biomarkers for Diagnosis and Screening of Type 2 Diabetes Mellitus. Current Diabetes Reports, 22, 95 - 115. https://doi.org/10.1007/s11892-022-01453-4

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Basic Carbohydrate Counting: Principles, Practice, and Impact on Diabetes Management

Basic carbohydrate counting (BCC) is a foundational dietary strategy for people with diabetes, focusing on maintaining consistent carbohydrate intake at meals to help regulate blood glucose. It is especially useful for those with type 1 or type 2 diabetes who are not on intensive insulin regimens, and serves as a stepping stone to more advanced carbohydrate counting.

What Is Basic Carbohydrate Counting?

• Definition and Approach: BCC involves learning which foods contain carbohydrates, understanding portion sizes, and aiming for a consistent amount of carbohydrates at each meal. Foods are grouped into “exchange lists,” where one exchange typically equals 10–15 grams of carbohydrates. Patients are taught to read food labels, estimate portion sizes, and use household measures to track intake (Tascini et al., 2018; Amorim et al., 2024; Ewers et al., 2019).
• Target Population: BCC is suitable for people with type 2 diabetes and those with type 1 diabetes not using intensive insulin therapy. It is less complex than advanced carbohydrate counting, which requires matching insulin doses to carbohydrate intake (Amorim et al., 2024; Ewers et al., 2019).

Benefits and Limitations

Figure 1: Table summarizing benefits and limitations of basic carb counting.

Practical Steps in BCC

• Identify carbohydrate-rich foods and use exchange lists.
• Maintain consistent carbohydrate intake at each meal.
• Read food labels and estimate portion sizes.
• Use tools like apps or pictorial quizzes to improve accuracy and engagement (Tascini et al., 2018; Thivierge et al., 2020; Amorim et al., 2024).

Summary

Basic carbohydrate counting is a practical, evidence-based approach that helps people with diabetes manage blood glucose by focusing on consistent carbohydrate intake. While it is less flexible than advanced methods, it improves glycemic control, supports weight management, and empowers patients to make informed food choices. Ongoing education and personalized support are key to maximizing its benefits.

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References

Tascini, G., Berioli, M., Cerquiglini, L., Santi, E., Mancini, G., Rogari, F., Toni, G., & Esposito, S. (2018). Carbohydrate Counting in Children and Adolescents with Type 1 Diabetes. Nutrients, 10. https://doi.org/10.3390/nu10010109

Taniguchi, M., Morita, R., Harada, R., Yoshino, F., Mukai, Y., Ikeda, M., Harada, K., Yoshiyama, M., Nakano, H., & Maeda, K. (2021). 1265-PUB: Basic Carbohydrate Counting in Patients with Type 2 Diabetes: Improvement in Glycemic Control and Effects on Body Compositions. Diabetes. https://doi.org/10.2337/db21-1265-pub

Bell, K., Barclay, A., Petocz, P., Colagiuri, S., & Brand-Miller, J. (2014). Efficacy of carbohydrate counting in type 1 diabetes: a systematic review and meta-analysis.. The lancet. Diabetes & endocrinology, 2 2, 133-40. https://doi.org/10.1016/s2213-8587(13)70144-x

Ewers, B., Bruun, J., & Vilsbøll, T. (2019). Effects of basic carbohydrate counting versus standard outpatient nutritional education (The BCC Study): study protocol for a randomised, parallel open-label, intervention study focusing on HbA1c and glucose variability in patients with type 2 diabetes. BMJ Open, 9. https://doi.org/10.1136/bmjopen-2019-032893

Thivierge, M., Waheed, M., Seel, M., & Wolf, R. (2020). 722-P: Pictorial Carbohydrate Counting: Engaging Youth with Diabetes in Nutrition Education. Diabetes, 69. https://doi.org/10.2337/db20-722-p

Ewers, B., Vilsbøll, T., Andersen, H., & Bruun, J. (2019). The dietary education trial in carbohydrate counting (DIET-CARB Study): study protocol for a randomised, parallel, open-label, intervention study comparing different approaches to dietary self-management in patients with type 1 diabetes. BMJ Open, 9. https://doi.org/10.1136/bmjopen-2019-029859

Roversi, C., Vettoretti, M., Del Favero, S., Facchinetti, A., & Sparacino, G. (2020). Modeling Carbohydrate Counting Error in Type 1 Diabetes Management. Diabetes Technology & Therapeutics, 22, 749 - 759. https://doi.org/10.1089/dia.2019.0502

Amorim, D., Miranda, F., Santos, A., Graça, L., Rodrigues, J., Rocha, M., Pereira, M., Sousa, C., Felgueiras, P., & Abreu, C. (2024). Assessing Carbohydrate Counting Accuracy: Current Limitations and Future Directions. Nutrients, 16. https://doi.org/10.3390/nu16142183

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Living with Diabetes: The Realities, Challenges, and Coping Strategies

Living with diabetes—whether type 1 or type 2—means navigating daily self-management, emotional ups and downs, and the impact on family, work, and social life. Research highlights that the experience is shaped by more than just medical routines; it involves psychological, social, and economic factors that influence quality of life and disease outcomes.

Everyday Challenges and Emotional Impact

• Constant Self-Management: People with diabetes report the relentless nature of managing diet, medication, blood glucose, and exercise. This daily “work” can feel overwhelming and is often described as a permanent burden (Sarapis et al., 2025; Da Silva et al., 2018; Ting et al., 2025; Gammeltoft et al., 2022; Paul et al., 2019; Taylor et al., 2023).
• Emotional Toll: Feelings of denial, frustration, sadness, and even grief are common, especially after diagnosis or when facing complications. Acceptance is a gradual process, and emotional struggles can interfere with self-care and adherence to treatment (Da Silva et al., 2018; Gammeltoft et al., 2022; Polonsky, 2002; Chapman et al., 2024).
• Mental Health: Anxiety, depression, and diabetes distress are prevalent and strongly linked to poorer quality of life. Mental health support tailored to the realities of diabetes is often lacking but highly needed (Sarapis et al., 2025; Alwhaibi, 2024; Polonsky, 2002; Chapman et al., 2024).

Social, Economic, and Cultural Barriers

• Family and Social Support: Support from family and friends is crucial but often limited by lack of understanding. Family routines and cultural expectations can make self-management harder, especially in diverse or low-income communities (Sarapis et al., 2025; Çakmak et al., 2025; Gammeltoft et al., 2022; Vlahovic et al., 2025; Overgaard et al., 2020).
• Financial Strain: The cost of healthy food, medications, and clinic visits is a significant barrier, particularly for those with lower socioeconomic status or in underserved areas (Sarapis et al., 2025; Çakmak et al., 2025; Adler et al., 2021; Paul et al., 2019).
• Stigma and Isolation: Stigma around diabetes can lead to secrecy, shame, and reluctance to seek help, further complicating management (Da Silva et al., 2018; Gammeltoft et al., 2022; Adler et al., 2021; Ofosu et al., 2022).

Coping and Resilience

• Personal Strategies: Many cope by adopting healthy habits, seeking social or spiritual support, and finding ways to balance diabetes with life’s demands. Flexibility and “bending the rules” can help maintain motivation and mental health (Sarapis et al., 2025; Çakmak et al., 2025; Gammeltoft et al., 2022; Da Silva et al., 2018).
• Community and Technology: Community-based programs, peer support, and technology (like apps or telehealth) can improve self-management and quality of life, especially when tailored to individual and cultural needs (Kanny et al., 2025; Taylor et al., 2023; McManus et al., 2025).

Summary

Living with diabetes is a complex, lifelong journey that extends far beyond medical management. Emotional resilience, social support, and addressing economic and cultural barriers are as vital as medication and diet. Interventions that recognize these real-world challenges—and empower individuals and families—are key to improving quality of life and health outcomes.

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References

Sarapis, K., Cao, Y., Chakra, M., Nunn, J., Rathod, P., Weber, M., Albuquerque, C., Chapman, M., Barr, R., Gilfillan, C., Skouteris, H., Oldenburg, B., Brukner, P., Beauchamp, A., & Moschonis, G. (2025). Understanding the Unmet Needs of People Living with Type 2 Diabetes in Self-Managing Their Condition. Nutrients, 17. https://doi.org/10.3390/nu17071243

Kanny, S., Hall, L., Blackhurst, D., & Sherrill, W. (2025). Community-based diabetes self-management and support program: addressing quality of life and social vulnerability. BMC Public Health, 25. https://doi.org/10.1186/s12889-025-22627-1

Çakmak, V., Sarı, E., & Özdemir, S. (2025). Experiences of adults with type 2 diabetes mellitus with low socioeconomic status: a qualitative study. BMC Public Health, 25. https://doi.org/10.1186/s12889-025-21582-1

Adjaye-Gbewonyo, K., Kretchy, I., Baatiema, L., Grijalva-Eternod, C., Sanuade, O., Amon, S., Haghparast-Bidgoli, H., Awuah, R., Lule, S., Mensah, S., Kushitor, S., Kushitor, M., Arhinful, D., & Fottrell, E. (2025). Non-communicable diseases, psychosocial wellbeing, and quality of life in Ga Mashie, Accra, Ghana: analysis from a community-based cross-sectional study. BMC Public Health, 25. https://doi.org/10.1186/s12889-025-22227-z

Da Silva, J., De Souza, E., Böschemeier, A., Costa, C., De Souza Bezerra, H., & Feitosa, E. (2018). Diagnosis of diabetes mellitus and living with a chronic condition: participatory study. BMC Public Health, 18. https://doi.org/10.1186/s12889-018-5637-9

Ting, Z., Wang, H., Kudelati, Z., Ge, Y., Alimu, A., Zhang, X., Qu, X., & Tong, L. (2025). Exploring the dynamics of self-efficacy, resilience, and self-management on quality of life in type 2 diabetes patients: A moderated mediation approach from a positive psychology perspective. PLOS ONE, 20. https://doi.org/10.1371/journal.pone.0317753

Gammeltoft, T., Bui, T., Vu, T., Vũ, Đ., Nguyen, T., & Lê, M. (2022). Everyday disease diplomacy: an ethnographic study of diabetes self-care in Vietnam. BMC Public Health, 22. https://doi.org/10.1186/s12889-022-13157-1

Scarton, L., Hebert, L., Goins, R., Umans, J., Jiang, L., Comiford, A., Chen, S., White, A., Ritter, T., & Manson, S. (2021). Diabetes and health-related quality of life among American Indians: the role of psychosocial factors. Quality of Life Research, 30, 2497 - 2507. https://doi.org/10.1007/s11136-021-02830-4

Adler, A., Trujillo, C., Schwartz, L., Drown, L., Pierre, J., Noble, C., Allison, T., Cook, R., Randolph, C., & Bukhman, G. (2021). Experience of living with type 1 diabetes in a low-income country: a qualitative study from Liberia. BMJ Open, 11. https://doi.org/10.1136/bmjopen-2021-049738

Alwhaibi, M. (2024). Depression, Anxiety, and Health-Related Quality of Life in Adults with Type 2 Diabetes. Journal of Clinical Medicine, 13. https://doi.org/10.3390/jcm13206028

Chapman, K., Cornelius, E., Wolf, W., Peter, M., & Kelly, C. (2024). 700-P: Recent and Lifetime Experiences with Diabetes Distress in Adults with Type 1 Diabetes. Diabetes. https://doi.org/10.2337/db24-700-p

Vlahovic, B., Jha, V., Stojanovic, V., Vojinovic, T., Dutta, A., Dutta, P., & Medenica, S. (2025). Enhancing patient-centered care: Evaluating quality of life in type 2 diabetes management. PLOS One, 20. https://doi.org/10.1371/journal.pone.0319369

Paul, M., Saad, A., Tagliaferro, M., Billings, J., Blecker, S., & Berry, C. (2019). 1241-P: Understanding Patients through Their Own Lens: The Lives of Individuals with Complex Diabetes as Revealed through Photo-Elicitation Interviews. Diabetes. https://doi.org/10.2337/db19-1241-p

Polonsky, W. (2002). Emotional and quality-of-life aspects of diabetes management. Current Diabetes Reports, 2, 153-159. https://doi.org/10.1007/s11892-002-0075-5

Taylor, L., Avery, L., Corner, L., Sulo, S., Rueda, R., & Trenell, M. (2023). 1788-PUB: Using the Lived Experience of Type 2 Diabetes and Its Clinical Care to Improve Diabetes Management through Use of Technology. Diabetes. https://doi.org/10.2337/db23-1788-pub

McManus, L., Vinson, C., Patel, D., Faichtinger, C., Yazdani, Z., Ray, R., Patel, R., Stokell, M., Birks, B., Gardiner, L., & Rocic, P. (2025). Positive Impact of a Specialized Summer Camp on the Correlation Between Improved Mental Health and Glycemic Control in Pediatric Type 1 Diabetic Patients. Pediatric Diabetes, 2025. https://doi.org/10.1155/pedi/4811222

Ofosu, N., Luig, T., Chiu, Y., Mumtaz, N., Yeung, R., Lee, K., Wang, N., Omar, N., Yip, L., Aleba, S., Maragang, K., Ali, M., Dormitorio, I., & Campbell-Scherer, D. (2022). Understanding the bigger picture: syndemic interactions of the immigrant and refugee context with the lived experience of diabetes and obesity. BMC Public Health, 22. https://doi.org/10.1186/s12889-021-12305-3

Zhang, Y., Li, S., Zou, Y., Wu, X., Bi, Y., Zhang, L., Yuan, Y., Gong, W., & Hayter, M. (2020). Fear of hypoglycemia in patients with type 1 and 2 diabetes: a systematic review.. Journal of clinical nursing. https://doi.org/10.1111/jocn.15538

Overgaard, M., Lundby-Christensen, L., & Grabowski, D. (2020). Disruption, worries, and autonomy in the everyday lives of adolescents with type 1 diabetes and their family members: a qualitative study of intra-familial challenges.. Journal of clinical nursing. https://doi.org/10.1111/jocn.15500

De Wit, M., De Waal, D., Bokma, J., Haasnoot, K., Houdijk, M., Gemke, R., & Snoek, F. (2008). Monitoring and Discussing Health-Related Quality of Life in Adolescents With Type 1 Diabetes Improve Psychosocial Well-Being. Diabetes Care, 31, 1521 - 1526. https://doi.org/10.2337/dc08-0394

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Exercise Prescription for People with Diabetes: Evidence-Based Guidelines

Exercise is a cornerstone of diabetes management, improving glycemic control, cardiovascular health, and overall well-being. The optimal exercise prescription varies by diabetes type, age, comorbidities, and individual goals, but several core principles are widely endorsed.

Core Recommendations

• Aerobic Exercise: Most guidelines recommend at least 150 minutes per week of moderate-to-vigorous aerobic activity, spread over at least 3 days, with no more than 2 consecutive days without exercise. Activities include brisk walking, cycling, or swimming (Kanaley et al., 2022; Mendes et al., 2015; Gallardo-Gómez et al., 2024; Hordern et al., 2012).
• Resistance Training: At least 2 sessions per week of resistance (strength) training involving major muscle groups is advised. Combining aerobic and resistance training yields greater benefits for glycemic control and body composition (Kanaley et al., 2022; Mendes et al., 2015; Gallardo-Gómez et al., 2024; Hordern et al., 2012).
• Flexibility and Balance: Especially for older adults, flexibility and balance exercises (e.g., yoga, tai chi) are recommended to reduce fall risk and enhance mobility (Kanaley et al., 2022; Kim et al., 2025; Yan et al., 2024).
• Sedentary Behavior: Reduce sedentary time by breaking up long periods of sitting with light activity every 30–60 minutes (Kanaley et al., 2022; Lewis et al., 2025; Bassin & Srinath, 2023).

Special Considerations

• Type 1 Diabetes: Exercise improves fitness and well-being but requires careful management of insulin, nutrition, and glucose monitoring to prevent hypoglycemia. Individualized adjustments to insulin and carbohydrate intake are essential (Riddell et al., 2017; Riddell & Peters, 2022; Aljawarneh et al., 2019).
• Older Adults: Both aerobic and resistance exercise are effective for glycemic control. Moderate and high-intensity exercise can significantly lower HbA1c and fasting glucose (Kim et al., 2025; Yan et al., 2024).
• Personalization: Exercise prescriptions should be tailored to individual health status, comorbidities, and preferences. Supervision or professional guidance is recommended for those with complications (Kanaley et al., 2022; Mendes et al., 2015; Hordern et al., 2012).

Summary Table: Exercise Prescription Components

Figure 1: Summary of key exercise prescription components for diabetes.

Conclusion

A structured exercise prescription—combining aerobic, resistance, and flexibility training, with attention to reducing sedentary time—should be individualized for all people with diabetes. Professional guidance and ongoing support maximize safety and effectiveness.

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

Kanaley, J., Colberg, S., Corcoran, M., Malin, S., Rodriguez, N., Crespo, C., Kirwan, J., & Zierath, J. (2022). Exercise/Physical Activity in Individuals with Type 2 Diabetes: A Consensus Statement from the American College of Sports Medicine. Medicine & Science in Sports & Exercise, 54, 353 - 368. https://doi.org/10.1249/mss.0000000000002800

Lewis, C., Rafi, E., Dobbs, B., Barton, T., Hatipoglu, B., & Malin, S. (2025). Tailoring Exercise Prescription for Effective Diabetes Glucose Management.. The Journal of clinical endocrinology and metabolism. https://doi.org/10.1210/clinem/dgae908

Mendes, R., Sousa, N., Almeida, A., Subtil, P., Guedes-Marques, F., Reis, V., & Themudo-Barata, J. (2015). Exercise prescription for patients with type 2 diabetes—a synthesis of international recommendations: narrative review. British Journal of Sports Medicine, 50, 1379 - 1381. https://doi.org/10.1136/bjsports-2015-094895

Riddell, M., Gallen, I., Smart, C., Taplin, C., Adolfsson, P., Lumb, A., Kowalski, A., Rabasa‐Lhoret, R., McCrimmon, R., Hume, C., Annan, F., Fournier, P., Graham, C., Bode, B., Galassetti, P., Jones, T., Millán, I., Heise, T., Peters, A., Petz, A., & Laffel, L. (2017). Exercise management in type 1 diabetes: a consensus statement.. The lancet. Diabetes & endocrinology, 5 5, 377-390. https://doi.org/10.1016/s2213-8587(17)30014-1

Kim, C., Park, D., Lee, Y., Kim, E., Oh, C., Lee, D., & Jeon, J. (2025). Meeting physical activity and resistance exercise guidelines associated with significantly reduced prevalence of diabetes in older adults.. Age and ageing, 54 4. https://doi.org/10.1093/ageing/afaf109

Bassin, S., & Srinath, R. (2023). The Impact of Physical Activity in Patients With Type 2 Diabetes. American Journal of Lifestyle Medicine, 19, 147 - 161. https://doi.org/10.1177/15598276231180541

Riddell, M., & Peters, A. (2022). Exercise in adults with type 1 diabetes mellitus. Nature Reviews Endocrinology, 19, 98-111. https://doi.org/10.1038/s41574-022-00756-6

Gallardo-Gómez, D., Salazar-Martínez, E., Alfonso-Rosa, R., Ramos-Munell, J., Del Pozo-Cruz, J., Del Pozo Cruz, B., & Álvarez-Barbosa, F. (2024). Optimal Dose and Type of Physical Activity to Improve Glycemic Control in People Diagnosed With Type 2 Diabetes: A Systematic Review and Meta-analysis.. Diabetes care, 47 2, 295-303. https://doi.org/10.2337/dc23-0800

Yan, X., Lu, Y., Zhang, H., Zhu, C., Tian, L., Chen, J., He, E., & Li, Y. (2024). Optimal strategies for exercise intervention in older people diabetic patients: The impacts of intensity, form, and frequency on glycemic control: An exercise prescription for older people with diabetes.. Archives of gerontology and geriatrics, 128, 105621. https://doi.org/10.1016/j.archger.2024.105621

Hordern, M., Dunstan, D., Prins, J., Baker, M., Singh, M., & Coombes, J. (2012). Exercise prescription for patients with type 2 diabetes and pre-diabetes: a position statement from Exercise and Sport Science Australia.. Journal of science and medicine in sport, 15 1, 25-31. https://doi.org/10.1016/j.jsams.2011.04.005

Aljawarneh, Y., Wardell, D., Wood, G., & Rozmus, C. (2019). A Systematic Review of Physical Activity and Exercise on Physiological and Biochemical Outcomes in Children and Adolescents With Type 1 Diabetes. Journal of Nursing Scholarship, 51, 337–345. https://doi.org/10.1111/jnu.12472

Here is a breakdown of common diabetes gadgets and devices, the nature of interactive resources, and what GLP refers to in diabetes treatment.

🩺 Diabetes Gadgets and Devices

These technologies are primarily focused on monitoring blood glucose and delivering insulin.

💻 Interactive Resources

These are tools that help with education, tracking, and connecting with care.

• Diabetes Apps: Smartphone applications that connect to your devices (CGMs, smart pens) to log blood sugar, track food, log exercise, set medication reminders, and offer educational content.
• Telehealth/Web Portals: Platforms that allow you to securely share your device data (pump, CGM) with your healthcare team for remote monitoring, check-ups, and more personalized care adjustments.
• Online Education & Support: Websites (like the American Diabetes Association or JDRF) and digital programs that offer free courses, articles, community forums, and other resources for managing the condition and mental health.

💉 GLP in Diabetes Treatment

GLP or Glucagon-Like Peptide-1. It's not a gadget, but rather a naturally occurring gut hormone that plays a key role in regulating blood sugar.

The term you are likely referring to is GLP-1 Receptor Agonists (GLP-1 RAs), which are a class of injectable or oral medications for type 2 diabetes (and sometimes obesity).

• How They Work: These medications mimic the action of natural GLP-1. They:
  1. Stimulate the pancreas to produce more insulin when blood sugar levels are high.
  2. Inhibit the release of glucagon (a hormone that raises blood sugar).
  3. Slow down the emptying of the stomach, which helps you feel fuller longer.
  4. Often lead to significant weight loss, which is beneficial for type 2 diabetes management.
• Examples: Common medications in this class include semaglutide (Ozempic, Rybelsus, Wegovy), liraglutide (Victoza, Saxenda), and dulaglutide (Trulicity). Newer medications, like tirzepatide (Mounjaro), are dual agonists, targeting both GLP-1 and GIP (Glucose-dependent insulinotropic polypeptide) receptors.
• Source: Google Gemini