Mao Qing, Wang Jingjing, Zuo Shuang, Xu Liyou, Ji Liu, Li Haishan
Department of Emergency, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, 230011 Hefei, Anhui, China.
Rev Cardiovasc Med. 2025 Jul 28;26(7):36792. doi: 10.31083/RCM36792. eCollection 2025 Jul.
The hemoglobin glycation index (HGI) presents a discrepancy between observed and predicted glycosylated hemoglobin (HbA1c) and fasting blood glucose values. Meanwhile, compared to the HbA1c values, the HGI provides a more comprehensive reflection of blood glucose variability across populations. However, no studies have examined the association between the HGI and all-cause, cardiac, and cardiovascular mortalities in the general population. Hence, this study aimed to investigate these relationships using data from the National Health and Nutrition Examination Survey (NHANES) database.
Participants were stratified into four groups based on the HGI quartiles. Weighted multivariable Cox proportional hazards models were used to assess the associations between HGI and all-cause, cardiovascular, and cardiac mortality. Kaplan-Meier survival analysis based on the HGI quartiles and log-rank tests were employed to compare differences in primary and secondary endpoints. Additionally, restricted cubic spline (RCS) curves were used to explore nonlinear relationships between the HGI and endpoints, identifying inflection points. Subgroup analyses and interaction tests were conducted to assess the robustness of the findings.
In comparing the baseline characteristics of endpoints across all-cause mortality, cardiac mortality, and cardiovascular mortality, significantly higher mortality rates were observed in the high HGI quartile group (Q4) compared to the other three groups (Q1, Q2, and Q3) ( < 0.05). Kaplan-Meier curves demonstrated increased mortality risks in the high HGI group across all endpoints ( < 0.05). Multivariable Cox proportional hazards models indicated that high HGI levels were associated with all-cause mortality (Q4: hazard ratio (HR) (95% confidence interval (CI)) = 1.232 (1.065, 1.426); = 0.005), cardiac mortality (HR (95% CI) = 1.516 (1.100, 2.088); = 0.011) and cardiovascular mortality (HR (95% CI) = 1.334 (1.013, 1.756); = 0.039). Low HGI was associated only with all-cause mortality (Q1: HR (95% CI) = 1.269 (1.082, 1.488); = 0.003). RCS analysis confirmed a U-shaped relationship between the HGI and all three outcome events. Subgroup analyses and interaction tests supported the robustness of the conclusions.
This study demonstrates a U-shaped association between the HGI and overall mortality, cardiac mortality, and cardiometabolic mortality in the general population. Specifically, the high HGI value represented a risk factor for all-cause, cardiac, and cardiovascular mortality. In contrast, low HGI values were associated only with all-cause mortality in the general population.
血红蛋白糖化指数（HGI）显示了观察到的糖化血红蛋白（HbA1c）与预测值以及空腹血糖值之间的差异。同时，与HbA1c值相比，HGI能更全面地反映不同人群的血糖变异性。然而，尚无研究探讨HGI与普通人群全因死亡率、心脏死亡率和心血管死亡率之间的关联。因此，本研究旨在利用美国国家健康与营养检查调查（NHANES）数据库中的数据来调查这些关系。
参与者根据HGI四分位数分为四组。采用加权多变量Cox比例风险模型评估HGI与全因死亡率、心血管死亡率和心脏死亡率之间的关联。基于HGI四分位数的Kaplan-Meier生存分析和对数秩检验用于比较主要和次要终点的差异。此外，使用受限立方样条（RCS）曲线探索HGI与终点之间的非线性关系，确定拐点。进行亚组分析和交互检验以评估研究结果的稳健性。
在比较全因死亡率、心脏死亡率和心血管死亡率终点的基线特征时，与其他三组（Q1、Q2和Q3）相比，高HGI四分位数组（Q4）的死亡率显著更高（<0.05）。Kaplan-Meier曲线显示，高HGI组在所有终点的死亡风险均增加（<0.05）。多变量Cox比例风险模型表明，高HGI水平与全因死亡率相关（Q4：风险比（HR）（95%置信区间（CI））=1.232（1.065，1.426）；=0.005）、心脏死亡率（HR（95%CI）=1.516（1.100，2.088）；=0.011）和心血管死亡率（HR（95%CI）=1.334（1.013，1.756）；=0.039）。低HGI仅与全因死亡率相关（Q1：HR（95%CI）=1.269（1.082，1.488）；=0.003）。RCS分析证实HGI与所有三个结局事件之间呈U形关系。亚组分析和交互检验支持了结论的稳健性。
本研究表明，在普通人群中，HGI与总体死亡率、心脏死亡率和心脏代谢死亡率之间呈U形关联。具体而言，高HGI值是全因、心脏和心血管死亡率的危险因素。相比之下，低HGI值仅与普通人群的全因死亡率相关。
