Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Diabetes. Jul 15, 2026; 17(7): 119712
Published online Jul 15, 2026. doi: 10.4239/wjd.119712
Digital health technologies for diabetes-centered five-condition co-management in China: Theoretical foundations, practical experience, and technical challenges
Jia-Li Xu, Cheng Luo, Cheng-Zheng Duan, Shi-Yu Xu, Zhi-Qiang Wu, Li-Ya Ye, Zhi-Peng Li, Mao-Sen Wang, Xian-Mei Yu, Dong-Juan He
Jia-Li Xu, Xian-Mei Yu, Dong-Juan He, Department of Endocrinology, The Second People’s Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
Cheng Luo, Cheng-Zheng Duan, Shi-Yu Xu, Department of Endocrinology, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People’s Hospital, Quzhou 324000, Zhejiang Province, China
Zhi-Qiang Wu, Department of Surgery, The Second People’s Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
Li-Ya Ye, Department of Gynecology, The Second People’s Hospital of Quzhou, Quzhou 324000, Zhejiang Province, China
Zhi-Peng Li, Second Department of Orthopedics, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
Mao-Sen Wang, Department of Technology Research and Development, Southeast Digital Economy Development Research Institute, Quzhou 324003, Zhejiang Province, China
Co-first authors: Jia-Li Xu and Cheng Luo.
Co-corresponding authors: Xian-Mei Yu and Dong-Juan He.
Author contributions: Xu JL, Luo C, and He DJ contributed to conceptualization; Xu JL, Luo C, and Duan CZ contributed to methodology; Xu JL, Luo C, Duan CZ, and Li ZP contributed to formal analysis; Xu JL, Luo C, Xu SY, Wu ZQ, and Wang MS contributed to data curation; Xu JL, Luo C, Duan CZ, Li ZP, and Wang MS contributed to visualization; Xu JL and Luo C wrote original draft as co-first authors; Duan CZ and Xu SY contributed to validation; Xu SY, Wu ZQ, and Ye LY did investigation; Wu ZQ, Ye LY, Wang MS, and Yu XM contributed to resources; Duan CZ, Xu SY, Li ZP, Yu XM, and He DJ contributed to writing - review and editing; Li ZP contributed to software; Yu XM and He DJ contributed to supervision, project administration, and funding acquisition as co-corresponding authors. All authors read and approved the final manuscript.
AI contribution statement: ChatGPT was used only for language polishing and writing assistance. All scientific content, including the study design, data collection, analysis, and interpretation, is entirely the original work of the authors. The authors take full responsibility for the content, quality, and accuracy of the manuscript.
Supported by Quzhou Science and Technology Bureau, No. 2025K114.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Dong-Juan He, MD, Dean, Professor, Department of Endocrinology, The Second People’s Hospital of Quzhou, No. 338 Xin’an Avenue, Qujiang District, Quzhou 324000, Zhejiang Province, China.
hedongjuan1247@wmu.edu.cn
Received: February 4, 2026
Revised: March 31, 2026
Accepted: May 19, 2026
Published online: July 15, 2026
Processing time: 156 Days and 0.8 Hours
Type 2 diabetes mellitus in China is increasingly accompanied by a clustering of metabolic abnormalities, hypertension, dyslipidemia, hyperuricemia, and excess body weight/obesity, forming a mutually reinforcing network that amplifies cardiometabolic risk and accelerates target-organ damage. Traditional single-disease management and specialty silos leave substantial residual risk and are difficult to scale in primary care. This review delineates the rationale and evolving practice of diabetes-centered five-condition co-management in China, integrating shared mechanisms of glucotoxicity, lip toxicity, urate dysmetabolism, and obesity-related inflammation with relevant policy and academic consensus. We synthesize real-world digital health experience and emerging artificial intelligence applications across screening, multimodal monitoring, risk stratification, individualized target setting, and precision lifestyle and pharmacologic interventions, and discuss data-driven collaborative networks linking tertiary hospitals, primary care, and community management to enable closed-loop follow-up. Finally, we critically examine technical, ethical, and regulatory challenges, particularly data interoperability and governance, privacy protection, algorithmic bias and interpretability, and workflow integration, and propose research priorities, including multicenter evaluations with clinically meaningful endpoints and scalable, primary-care-appropriate solutions.
Core Tip: Diabetes-centered five-condition co-management integrates glycemic control with concurrent management of hypertension, dyslipidemia, hyperuricemia, and obesity to address shared cardiometabolic pathophysiology and synergistic risk amplification. This review synthesizes the epidemiologic rationale, mechanistic links, and evidence from digital health-enabled care models, highlighting how continuous monitoring, personalized decision support, and multidisciplinary workflows can improve target attainment and adherence. We propose a practical implementation framework with measurable endpoints, risk stratification, and governance requirements for artificial intelligence tools, while outlining barriers such as interoperability, equity, and long-term safety and effectiveness evaluation in real-world settings.
