ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023
Association Between Hemoglobin Glycation Index and Metabolic Syndrome in Middle-Aged and Older People.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Hemoglobin glycation index correlates with the prognoses of critically ill patients with hyperlipidemia: a retrospective cohort study from the MIMIC-IV database.BMC endocrine disorders · 2026Article
- Association between hemoglobin glycation index and delirium after gastric surgery: Based upon the MIMIC-IV.Medicine · 2026Article
- Sex-specific in the nonlinear associations of hemoglobin glycation index and all-cause mortality in the general US adult population: results from NHANES 1999-2018.Nutrition & metabolism · 2026Article
- Article
- Impact of hemoglobin glycation index on prognosis in critical patients with acute ischemic stroke: A retrospective cohort study using MIMIC-IV 2.2 database.Scientific reports · 2025Article
- Association of Hemoglobin Glycation Index With All-Cause Mortality, Cardiac Mortality, and Cardiovascular Mortality in the General Population: A Retrospective Cohort Study of NHANES Data.Reviews in cardiovascular medicine · 2025Article
- Article
- Glycated haemoglobin index is a new predictor for all-cause mortality and cardiovascular mortality in the adults.Scientific reports · 2024Article
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Purpose: Hemoglobin glycation index (HGI) is used to describe the difference between estimated and measured glycated hemoglobin A1c (HbA1c). The present study aimed to investigate the association between metabolic syndrome (MetS) and HGI in middle-aged and elderly Chinese. Patients and Methods: In this cross-sectional study, a multi-stage random sampling method was used to select objects from the permanent residents aged 35 years and above living in Ganzhou, Jiangxi, China. The demographic information, history of illness, physical examination, and blood biochemistry data were obtained. HGI was calculated from fasting plasma glucose (FPG) and HbA1c (HGI = measured HbA1c value - predicted HbA1c value). All participants were divided into low HGI and high HGI groups using the median HGI as a cut-off value. Univariate analysis was used to detect the influencing factors of HGI, and Logistic regression analysis was adopted to analyze the relationship between significant variables found in univariate analysis, MetS, or MetS's components and HGI. Results: A total of 1826 participants were enrolled in the study, and the prevalence of MetS was 27.4%. There were 908 in the low HGI group and 918 in the high HGI group, and the prevalence of MetS was 23.7% and 31.0%, respectively. Logistic regression analysis showed that the prevalence of MetS in the high HGI group was higher than that in the low HGI group (OR=1.384, 95% CI:1.110~1.725), further analysis showed that HGI was related with abdominal obesity (OR=1.287, 95% CI:1.061~1.561), hypertension (OR=1.349, 95% CI:1.115~1.632), and hypercholesterolemia (OR=1.376, 95% CI:1.124~1.684) (all P < 0.05). After adjusting for age, sex, and serum uric acid (UA), the relationship still existed. Conclusion: This study found that HGI is directly associated with MetS.
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