Interactive Effects of Keto Diet and High-Fiber Intervention on Energy Metabolism in Patients with Diabetes and Obesity

Article Sidebar

PDF
Published: 2026-01-12
Keywords:
ketogenic diet, high-fiber diet, fat oxidation, thermic effect, HbA1c, energy metabolism, type 2 diabetes

Main Article Content

Elena Rossi
Department of Metabolism and Systems Biology, Kyoto University, Kyoto, 606-8501, Japan
David K. Morgan
Department of Metabolism and Systems Biology, Kyoto University, Kyoto, 606-8501, Japan
Hiroshi Tanaka
Department of Metabolism and Systems Biology, Kyoto University, Kyoto, 606-8501, Japan

Abstract

This study investigated how ketogenic and high-fiber diets, alone and together, affect energy use and blood sugar control in adults with obesity and type 2 diabetes. Sixty participants completed three eight-week diet phases-a ketogenic diet, a high-fiber diet, and a combined plan-using a randomized crossover design. Energy use was measured by indirect calorimetry, and blood sugar was tracked with HbA1c and continuous glucose monitoring. The ketogenic diet raised fat oxidation from 32% to 61% (p < 0.001), while the high-fiber diet increased the thermic effect of food from 6.8% to 9.1% (p = 0.01). The combined diet led to the greatest drop in HbA1c (−1.6 ± 0.4%, p < 0.001) and a 22% decrease in blood sugar swings. These findings show that low-carbohydrate and high-fiber diets improve metabolism through different but complementary ways-one by increasing fat use, the other by raising thermogenesis. Using both diets together may help improve energy balance and glucose control in people with type 2 diabetes, though longer studies are needed to test lasting effects.

Article Details

Issue

Vol. 2 No. 1 (2026): 2025 International Conference on Artificial Intelligence, Data Science and Intelligent Engineering (AIDSIE 2025)

Section

Articles

How to Cite

Interactive Effects of Keto Diet and High-Fiber Intervention on Energy Metabolism in Patients with Diabetes and Obesity. (2026). Journal of Sustainability, Policy, and Practice, 2(1), 21-26. https://schoalrx.com/index.php/jspp/article/view/72

References

1. Y. T. Wondmkun, "Obesity, insulin resistance, and type 2 diabetes: Associations and therapeutic implications," Diabetes, Metabolic Syndrome and Obesity, pp. 3611-3616, 2020.

2. Y. Wang, Y. Wen, X. Wu, L. Wang, and H. Cai, "Modulation of gut microbiota and glucose homeostasis through high-fiber dietary intervention in type 2 diabetes management," 2024. doi: 10.53469/wjimt.2024.07(06).04

3. R. D. Feinman, W. K. Pogozelski, A. Astrup, R. K. Bernstein, E. J. Fine, E. C. Westman, and N. Worm, "Dietary carbohydrate restriction as the first approach in diabetes management: Critical review and evidence base," Nutrition, vol. 31, no. 1, pp. 1-13, 2015. doi: 10.1016/j.nut.2014.06.011

4. M. Mazhar, Y. Zhu, and L. Qin, "The interplay of dietary fibers and intestinal microbiota affects type 2 diabetes by generating short-chain fatty acids," Foods, vol. 12, no. 5, p. 1023, 2023. doi: 10.3390/foods12051023

5. G. Wang, “Performance evaluation and optimization of photovoltaic systems in urban environments,” Int. J. New Dev. Eng. Soc., vol. 9, pp. 42–49, 2025, doi: 10.25236/IJNDES.2025.090106.

6. A. J. Scheen, and L. F. Van Gaal, "Combating the dual burden: Therapeutic targeting of common pathways in obesity and type 2 diabetes," The Lancet Diabetes & Endocrinology, vol. 2, no. 11, pp. 911-922, 2014. doi: 10.1016/s2213-8587(14)70004-x

7. G. Ge, R. Zelig, T. Brown, and D. R. Radler, "A review of the effect of the ketogenic diet on glycemic control in adults with type 2 diabetes," Precision Nutrition, vol. 4, no. 1, p. e00100, 2025.

8. A. Paoli, "The influence of physical exercise, ketogenic diet, and time-restricted eating on de novo lipogenesis: A narrative review," Nutrients, vol. 17, no. 4, p. 663, 2025. doi: 10.3390/nu17040663

9. Y. Wang, Y. Wen, X. Wu, and H. Cai, "Application of ultrasonic treatment to enhance antioxidant activity in leafy vegetables," International Journal of Advance in Applied Science Research, vol. 3, pp. 49-58, 2024.

10. J. Xu, H. Wang, and H. Trimbach, "An OWL ontology representation for machine-learned functions using linked data," In 2016 IEEE International Congress on Big Data (BigData Congress), June, 2016, pp. 319-322. doi: 10.1109/bigdatacongress.2016.48

11. M. Yuan, H. Mao, W. Qin, and B. Wang, "A BIM-driven digital twin framework for human-robot collaborative construction with on-site scanning and adaptive path planning," 2025. doi: 10.1109/cvaa66438.2025.11193176

12. J. A. Martinez, S. Navas-Carretero, W. H. Saris, and A. Astrup, "Personalized weight loss strategies-the role of macronutrient distribution," Nature Reviews Endocrinology, vol. 10, no. 12, pp. 749-760, 2014.

13. H. Chen, P. Ning, J. Li, and Y. Mao, "Energy consumption analysis and optimization of speech algorithms for intelligent terminals," 2025. doi: 10.1109/caibda65784.2025.11183212

14. L. D. Clamp, "The role of metabolic rate and substrate utilization in the maintenance of body weight, body composition and insulin sensitivity," 2019.

15. C. Wu, J. Zhu, and Y. Yao, "Identifying and optimizing performance bottlenecks of logging systems for augmented reality platforms," 2025. doi: 10.20944/preprints202509.0357.v1

16. E. B. Giuntini, F. A. H. Sardá, and E. W. de Menezes, "The effects of soluble dietary fibers on glycemic response: An overview and futures perspectives," Foods, vol. 11, no. 23, p. 3934, 2022. doi: 10.3390/foods11233934

17. S. Tsitsou, C. Athanasaki, G. Dimitriadis, and E. Papakonstantinou, "Acute effects of dietary fiber in starchy foods on glycemic and insulinemic responses: A systematic review of randomized controlled crossover trials," Nutrients, vol. 15, no. 10, p. 2383, 2023. doi: 10.3390/nu15102383

18. D. Chen, J. Liu, J. Wu, and J. S. Suk, "Enhancing nanoparticle penetration through airway mucus to improve drug delivery efficacy in the lung," Expert Opinion on Drug Delivery, vol. 18, no. 5, pp. 595-606, 2021. doi: 10.1080/17425247.2021.1854222

19. H. S. Lee, and J. Lee, "Influences of ketogenic diet on body fat percentage, respiratory exchange rate, and total cholesterol in athletes: A systematic review and meta-analysis," International Journal of Environmental Research and Public Health, vol. 18, no. 6, p. 2912, 2021. doi: 10.3390/ijerph18062912

20. K. Xu, Y. Lu, S. Hou, K. Liu, Y. Du, M. Huang, and X. Sun, "Detecting anomalous anatomic regions in spatial transcriptomics with STANDS," Nature Communications, vol. 15, no. 1, p. 8223, 2024. doi: 10.1038/s41467-024-52445-9

21. J. Bruning, A. Chapp, G. A. Kaurala, R. Wang, S. Techtmann, and Q. H. Chen, "Gut microbiota and short chain fatty acids: Influence on the autonomic nervous system," Neuroscience Bulletin, vol. 36, no. 1, pp. 91-95, 2020.

22. W. Sun, “Integration of Market-Oriented Development Models and Marketing Strategies in Real Estate,” European Journal of Business, Economics & Management, vol. 1, no. 3, pp. 45–52, 2025

23. T. Deng, M. Huang, K. Xu, Y. Lu, Y. Xu, S. Chen, and X. Sun, "LEGEND: Identifying co-expressed genes in multimodal transcriptomic sequencing data," Preprint, pp. 2024-10, 2024. doi: 10.1101/2024.10.27.620451

24. S. Yuan, “Data Flow Mechanisms and Model Applications in Intelligent Business Operation Platforms”, Financial Economics Insights, vol. 2, no. 1, pp. 144–151, 2025, doi: 10.70088/m66tbm53.

25. C. Koliaki, T. Spinos, Spinou, E. Brinia, D. Mitsopoulou, and N. Katsilambros, "Defining the optimal dietary approach for safe, effective and sustainable weight loss in overweight and obese adults," In Healthcare, September, 2018, p. 73.