Evidence mapPaperPMID 41188815Full record

ArticleBMC endocrine disorders2025

Hemoglobin glycation index can be used as a predictor of diabetes mellitus and prediabetes: a cohort study.

Jing-Xian Bai, De-Gang Mo, Min Liu, Tao Liu, Qian-Feng Han, Heng-Chen Yao

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Article in BMC endocrine disorders, 2025. 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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6 authors.

Jing-Xian Bai *Shandong First Medical University, Jinan, 250117, China.
De-Gang Mo *School of Medicine, Qingdao University, 266000, Qingdao, China.
Min LiuShandong First Medical University, Jinan, 250117, China.
Tao LiuDepartment of Cardiology, Liaocheng People's Hospital, Liaocheng, 252000, China. 13563504653@163.com.
Qian-Feng HanDepartment of Cardiology, Liaocheng People's Hospital, Liaocheng, 252000, China. hqfg01@163.com.
Heng-Chen YaoShandong First Medical University, Jinan, 250117, China. yaohc66@126.com.

Funding

Hori- zontal research project of Shandong University No.3450012001901The Natural Science Foundation of Shandong Province No.ZR2016HM49Traditional Chinese Medicine Science and Technology Development Plan Project of Shandong Province No.2019-0891
6 · The paper itself

Abstract

backgroundDiabetes mellitus (DM) is a significant global public health concern, with prediabetes serving as a critical stage between normoglycemia and DM. Without intervention, individuals with prediabetes face an increased risk of developing DM, underscoring the need for effective preventive measures. The Hemoglobin Glycation Index (HGI)-which measures the discrepancy between actual and predicted glycated hemoglobin (HbA1c) levels-has shown promise in predicting the onset of both microvascular and macrovascular complications associated with DM. However, its potential role in assessing the risk of developing DM or prediabetes remains to be fully established. This study aims to investigate the predictive capacity of HGI for both DM and prediabetes.

methodThis retrospective cohort study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), involving participants aged 45 years and older who were assessed in 2011 and followed up in 2015. Univariate and multivariate logistic regression models were employed to analyze the relationship between HGI and the incidence of prediabetes and DM. Dose-response analyses were conducted using restricted cubic splines, and subgroup analyses were performed based on various demographic and health-related factors.

resultsAmong 3,963 participants, 187 individuals (4.72%) developed prediabetes within four years, and 107 individuals (2.70%) developed DM. HGI was independently associated with an increased risk of developing both DM and prediabetes, with adjusted odds ratios of 1.61 (95% confidence interval [CI]: 1.19-2.16, p = 0.001) and 2.03 (95% CI: 1.40-2.94, p < 0.001), respectively. A linear relationship was observed between HGI and both DM and prediabetes. An interaction effect was identified between age and HGI; specifically, the association between higher HGI and incident DM was more pronounced in individuals aged 45 to 60 years. Among this age group, the OR was 3.93 (95% CI: 2.19-7.05, p < 0.001).

conclusionHGI is identified as an independent risk factor for both DM and prediabetes, demonstrating its utility in predicting the likelihood of their development, particularly within the population aged 45 to 60. These findings highlight the potential of HGI as a valuable biomarker for the early identification of DM risk, thereby facilitating the formulation of targeted intervention strategies.

trial registrationNot applicable.

Indexed as

BiomarkersDiabetes MellitusGlycated HemoglobinPrediabetic StateAgedChinaCohort StudiesFemaleFollow-Up StudiesHumansIncidenceLongitudinal StudiesMaleMiddle AgedPrognosisRetrospective StudiesBiomarkersGlycated Hemoglobinhemoglobin A1c protein, humanCHARLSDiabetes mellitusHemoglobin glycation indexPrediabetes

Identifiers

PMID41188815
PMCPMC12584477

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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 Socratic graph.