Evidence map›Paper›PMID 42151916›Full record

ArticleBMC endocrine disorders2026

State transitions and related factors of type 2 diabetes based on multi-state Markov model among a Chinese health check-up cohort.

Xue-Jiao Yang, Qiong Wu, Yan Xu, Zhen-Yun Li, Dai-Yi Zhang, Jian-Hong Pu

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Article in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Xue-Jiao Yang *Health Management Center, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Qiong Wu *Taizhou People's Hospital Affiliated to Nanjing Medical University, Taizhou, China.
Yan XuHealth Management Center, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Zhen-Yun LiHealth Management Center, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Dai-Yi ZhangHealth Management Center, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China. 18896588579@163.com.
Jian-Hong PuHealth Management Center, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China. sdfyjkgl@163.com.

Funding

Suzhou Medical and Health Innovation Project of the Science and Technology Tackling Program SYWD2025343the Health Care Issues for Cadres in Jiangsu Province BJ2009the Science and Technology Plan of Suzhou, Jiangsu Province SKY2022044
6 · The paper itself

Abstract

backgroundTo explore the transitions of different blood glucose states based on a multi-state Markov model among the Chinese health check-up population.

methodsIn this research, the multi-state Markov model was built based on 4776 blood glucose status assessments in 1677 Chinese participants. A quantitative longitudinal study was conducted to explore diabetes progression, providing information on the transition probability, the sojourn time, and the risk factors in three blood glucose states, namely normal (state 1), prediabetes (state 2), and diabetes (state 3).

resultsAmong 4776 transition cases, there were 318 cases (6.7%) with remission (state 2→1), 3505 cases (73.4%) with stable disease (state 1→1, 2→2, 3→3), and 953 cases (19.9%) with progressive disease (state 1→2, 1→3, 2→3). The probability of progression from normal state to diabetes was 1.1% within 1 year and increased to 11.9% within 6 years. Increased age, blood pressure, and body mass index were risk factors for progression to diabetes in the normal state or prediabetes.

conclusionsThis article serves as a reference for targeted interventions for diabetes progression among the Chinese health check-up population. Obesity, hypertension and hyperlipidemia are risk factors that worsen the progression of diabetes, and preventive actions should be taken at an early stage. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Diabetes Mellitus, Type 2Markov ChainsPrediabetic StateAdultBlood GlucoseBody Mass IndexChinaDisease ProgressionFemaleFollow-Up StudiesHumansLongitudinal StudiesMaleMiddle AgedPrognosisRisk FactorsBlood GlucoseDiabetesMulti-state Markov modelPrediabetesProactive preventionTransition probability

Identifiers

PMID42151916
PMCPMC13353005

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.