Diabetes management dilemma: association between glycated hemoglobin levels and mortality risk in diabetic patients

Introduction

Diabetes mellitus is a chronic metabolic disorder with a rising global prevalence, currently affecting over 300 million individuals and posing a major public health challenge (1,2). Cardiovascular disease (CVD) is the most clinically significant complication of diabetes, accounting for the majority of diabetes-related morbidity and mortality (3). Individuals with diabetes are at an elevated risk of developing cardiovascular events, including coronary artery disease and stroke, which are among the leading causes of death in this population (4). Glycated hemoglobin A1c (HbA1c) is formed through irreversible non-enzymatic glycation of hemoglobin and serves as a key biomarker for long-term glycemic control (5). Clinically, HbA1c reflects average blood glucose concentrations over the preceding 2 to 3 months and is widely used in clinical management, epidemiological research, and public health surveillance (6). It is universally accepted as the reference standard for assessing chronic glycemic control, and numerous longitudinal studies have demonstrated that elevated HbA1c levels are associated with a graded increase in the risk of cardiovascular events and all-cause mortality, regardless of diabetes status (7-10). While several studies have reported that improved glycemic control reduces the risk of major cardiovascular events, others have yielded inconsistent findings, highlighting the need for further investigation (11-15). In particular, longitudinal trends in achieving HbA1c <7.0% and their association with 5-year cardiovascular mortality remain insufficiently characterized. Although current clinical guidelines recommend maintaining HbA1c levels below 7.0%, the survival benefits of such targets remain debated (16).

Therefore, this study had two primary objectives: (I) to analyze temporal trends in the proportion of U.S. adults with diabetes achieving HbA1c <7.0% between 1999 and 2014, as well as the trends in all-cause and cardiovascular mortality risks among this population; and (II) to assess the association between achieving HbA1c <7.0% and 5-year risks of cardiovascular and all-cause mortality. In addition, we explored potential cause underlying these associations. We present this article in accordance with the STROBE reporting checklist (available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-59/rc).

Methods

Study population

The National Health and Nutrition Examination Survey (NHANES) is a cross-sectional, complex, multistage probability sample survey conducted by the National Center for Health Statistics, designed to assess the health and nutritional status of the non-institutionalized U.S. population. Inclusion criteria: participants in the NHANES survey from 1999 to 2014 with a confirmed diagnosis of diabetes and aged 18 years or older. Exclusion criteria: participants with missing data on HbA1c, sampling weights, or follow-up information were excluded from the analysis. From 1999 to 2014, NHANES enrolled 82,091 participants (Figure S1). After excluding individuals without diabetes, 7,151 participants remained. We further excluded individuals with missing data on HbA1c, sampling weights, or follow-up status, resulting in a final analytic sample of 6,516 participants (Figure S1). Study protocols were ethically approved by the Institutional Review Board of the National Center for Health Statistics (Protocol Nos. 98-12, 2005-06, continuation of 2005–2006, 2011–2017, and continuation of 2011–2017), and all participants provided written informed consent. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Cohort identification

The cohort was identified as participants in the NHANES surveys from 1999 to 2014 with a confirmed diagnosis of diabetes. The criteria for diabetes included a medical diagnosis, an HbA1c percentage of at least 6.5, a fasting glucose measurement of 7.0 mmol/L or greater, or a random blood glucose reading of 11.1 mmol/L or more, an oral glucose tolerance test (OGTT) result showing blood glucose levels of 11.1 mmol/L or above, or the use of insulin or diabetes drugs (17). Patients were divided into the HbA1c <7.0% group and the HbA1c >7.0% group (18,19).

Other variable definitions

Participants had a physical examination and blood samples taken at the mobile examination center (MEC), where they also participated in in-home interviews and completed extra questionnaires. Information on age, sex, race/ethnicity, education, smoking, drinking, and comorbid conditions was self-reported by the participants. Four categories were used for race/ethnicity: White, Black, Mexican, or Other. Smoking status was categorized as former, never, or now. This study involves participants from four racial classifications: Mexican, White, Black, and Other. In this study, ‘other Hispanic’ and ‘other race—including multi-racial’ are grouped as ‘Other’, ‘Mexican American’ is denoted as ‘Mexican’, ‘non-Hispanic White’ is labeled as ‘White’, and ‘Non-Hispanic Black’ is characterized as ‘Black’.

To measure income, the income-to-poverty ratio was used, calculated by dividing the family’s annual income by the poverty threshold, which is adjusted for family size and inflation. An interview at the patient’s home was performed to collect data on their medical history and the medications they are currently prescribed for hypertension, diabetes, high cholesterol, coronary heart disease, myocardial infarction, congestive heart failure, stroke, angina, and hyperlipidemia. In a physical examination, weight and height were recorded, and the body mass index was determined by dividing the weight in kilograms by the square of the height in meters. Samples were collected from the MEC and stored at −20 ℃ before being analyzed at central laboratories using standard methods for high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL) cholesterol, and creatinine. The quantification of HDL-C was performed using two established methods: heparin-manganese (Mn²⁺) precipitation and direct immunoassay. Cholesterol was measured enzymatically by subjecting serum or plasma samples to sequential reactions, which included cholesteryl ester hydrolysis and subsequent oxidation of cholesterol’s 3β-hydroxyl group. According to the Friedewald calculation, LDL-cholesterol is computed from the measured amounts of total cholesterol, triglycerides, and HDL-C, involving very low-density lipoprotein (VLDL), LDL, and HDL.

The measurement of LDL cholesterol and glucose was restricted to survey participants who had fasted for 8 hours. Once the participant had been sitting quietly for at least 5 minutes, their blood pressure was measured by trained staff using a mercury sphygmomanometer. This study collected three blood pressure readings, and the mean of these measurements was used for analysis. Hypertension is diagnosed when the systolic blood pressure reaches 140 mmHg or higher, the diastolic blood pressure reaches 90 mmHg or higher, or when antihypertensive medication is used.

Follow-up and outcomes

The primary focus was on mortality from all causes and cardiovascular-related deaths during a 5-year follow-up. Participants in the study were followed for a duration of 5 years. The median follow-up duration in this study was 60 months, and the mean follow-up duration was 56.15 months. The mortality status for December 31, 2019 was determined using death certificate records linked to the National Death Index. The follow-up period for NHANES MEC was calculated from the examination date to the date of death or for a maximum of 5 years, whichever occurred earlier. Determining the exact cause of death using the Tenth Revision of the International Statistical Classification of Disease (ICD-10) (20). Cardiac death refers to mortality caused by heart-related conditions, identified by ICD-10 codes I00-I09, I11, I13, and I20–I51. Cardiovascular mortality is defined as death resulting from heart-related diseases (ICD-10 codes I00-I09, I11, I13, I20–I51) or cerebrovascular diseases (ICD-10 codes I60–I69). Access the online link for final mortality statistics, follow-up periods, and main causes of death here: https://ftp.cdc.gov/pub/Health_Statistics/NCHS/datalinkage/linked_mortality/).

Statistical analysis

Our analyses were conducted in accordance with NHANES guidelines, considering sample weights, clustering, and stratification to ensure the findings are generalizable to the U.S. population (21-23). To account for the complex sampling design of NHANES, we applied appropriate weights to obtain a representative sample of the U.S. national population. Group comparisons were performed using the Chi-squared test for categorical variables and t-test for continuous variables. Kaplan-Meier survival curves were constructed to estimate time-to-event outcomes, and differences between groups were assessed using the log-rank test. Logistic regression was applied to determine the statistical significance of linear or nonlinear trends in the rates of HbA1c control, cardiovascular mortality, all-cause mortality, and various medication usages. Nonlinear temporal trends were assessed by incorporating quadratic terms in the regression models, allowing for evaluation of potential curvilinear relationships over time. Cox proportional hazards regression models were employed to evaluate associations between predictors and time-to-event outcomes, with hazard ratios (HRs) and 95% confidence intervals (CIs) reported. We performed weighted multivariate Cox regression analyses for HbA1c <7.0%, while mortality served as the dependent variable. Researchers utilized the Cox proportional hazards model to perform multivariate analyses on the associations between glycated hemoglobin and mortality data. Three predefined models of adjustment [model 1: adjusted for sex, age, and ethnicity/race; model 2: adjusted for sex, age, ethnicity/race, marital, education, creatinine (µmol/L), and uric acid (µmol/L); and model 3: an extension of model 2 that includes additional adjustments for systolic and diastolic blood pressure, LDL and HDL cholesterol levels (mmol/L), triglyceride levels (mmol/L), body mass index (kg/m²), smoking habits, alcohol use, congestive heart failure, stroke, angina, and heart attack] were used. We conducted sensitivity analyses stratified by patients’ sociodemographic factors and comorbid conditions.

All statistical analyses were performed using R version 4.1.3 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided P value <0.05 was considered statistically significant. Cox regression analyses were performed using the “survival” package. Kaplan-Meier survival curves were generated using the “ggsurvplot” function from the “survminer” package and the “survfit” function from the “survival” package. Multinomial logistic regression analyses were conducted using the base R statistical package.

Results

Baseline

The sample size of our study was 6,516 individuals, with 49.41% of them being females and 50.59% males, according to Table 1 and Table S1. A total 2,788 individuals failed to achieve the target for HbA1c control, whereas 3,728 individuals successfully attained it. Ethnicity composition: White (63.22%), Black (14.59%), Other (13.34%), and Mexican (8.84%) (Table S1). Educational attainment: college or higher (45.75%), primary education or lower (12.29%), at least secondary education (24.14%), and unclear education status (17.82%) (Table S1). The HbA1c <7.0% group had an average age of 60.34±0.31 years, which was older than the HbA1c ≥7.0% group with an average age of 57.29±0.39 years (P<0.001) (Table S1). The HDL level averaged 1.26±0.01 mmol/L in individuals with HbA1c under 7.0%, higher than the 1.18±0.01 mmol/L in those with HbA1c at or above 7.0% (P<0.001). In addition, individuals in the HbA1c <7.0% category had a lower average triglyceride level (1.85±0.04 mmol/L) than those in the HbA1c ≥7.0% category (2.48±0.11 mmol/L) (P<0.001) (Table S1). Additionally, there were no differences in systolic blood pressure (SBP), creatinine, congestive heart failure, stroke, angina, heart attack, or alcohol consumption between the HbA1c <7.0% group and the HbA1c ≥7.0% group (Table S1).

Trend glycated hemoglobin control rate and mortality

The proportion of diabetic patients with HbA1c <7.0% increased from 41.61% in 1999 to 63.85% in 2006, then decreased to 58.72% in 2014 (quadratic P<0.001) (Figure 1 and Table S2). A total of 361 all-cause deaths and 113 cardiovascular-related deaths were documented during the follow-up period. However, the overall all-cause mortality rate among diabetic patients over 5 years showed no statistically significant trend from 10.79% in 1999 to 12.08% in 2014 (linear P=0.61) (Figure 1 and Table S2). Similarly, there was no statistically significant trend observed in the cardiovascular mortality rate among diabetic patients over 5 years, which ranged from 4.74% in 1999 to 4.24% in 2014 (linear P=0.37) (Figure 1 and Table S2).

Figure 1 Trend glycated hemoglobin control rate and mortality at 5-year follow-ups in diabetes. We test linear and quadratic terms for time. *** indicates a linear P<0.001 in 1999–2014 year; ### indicates a quadratic P<0.001 in 1999–2014 year; $$$ indicates a linear P<0.001 in 1999–2006 year; &&& indicates a linear P<0.001 in 2007–2014 year. There was no statistically significant trend in mortality observed for the years 1999–2014, 1999–2006, and 2007–2014. Shaded areas indicate 95% confidence intervals. All-cause mortality and cardiovascular mortality at 5-year follow-ups among participants with diabetes.

HbA1c <7.0% and risk of death

The median follow-up duration in this study was 60 months, and the mean follow-up duration was 56.15 months. The Kaplan-Meier survival curves showed that the group with HbA1c <7.0% had higher 5-year all-cause mortality (12.47% vs. 11.40%, P=0.33) and cardiovascular mortality (5.01% vs. 4.07%, P=0.09) compared to the group with HbA1c ≥7.0% (Figure 2). Using the group with HbA1c <7.0% as the reference, the HR for all-cause mortality in the HbA1c ≥7.0% group, adjusted for sex, age, and ethnicity/race, was 1.14 (95% CI: 0.94–1.37; P=0.17) (Table 2). After full adjustment in model 3, which included sociodemographic factors, comorbidities, and relevant clinical variables, the association remained nonsignificant (HR: 0.64; 95% CI: 0.36–1.13; P=0.13) (Table 2). For cardiovascular mortality, the HR in the HbA1c ≥7.0% group was 1.03 (95% CI: 0.81–1.30; P=0.82) after adjustment for sex, age, and ethnicity/race. Similarly, after full adjustment, the association remained no significant (HR: 1.11; 95% CI: 0.41–3.02; P=0.84) (Table 2). Comprehensive sensitivity analyses across all predefined demographic and clinical subgroups—including age, sex, duration of diabetes, and comorbidity burden—consistently failed to demonstrate a significant mortality benefit associated with maintaining HbA1c <7.0%, with null findings observed for both all-cause and cardiovascular mortality. Notably, individuals with a primary education level or lower exhibited a decreased risk of all-cause mortality (HR: 0.663; 95% CI: 0.485–0.906; P=0.01) and cardiovascular mortality (HR: 0.494; 95% CI: 0.285–0.857; P=0.01) in the HbA1c ≥7.0% group compared to those with HbA1c <7.0% (Figure 3, Tables S3,S4). Furthermore, HbA1c levels ≥7.0% were associated with a reduced risk of cardiovascular mortality among female patients (HR: 0.609; 95% CI: 0.410–0.906; P=0.01) and individuals with an poverty-to-income ratio (PIR) below 100% (HR: 0.593; 95% CI: 0.378–0.930; P=0.02) relative to those with HbA1c <7.0% (Figure 3, Tables S3,S4).

Figure 2 Kaplan-Meier curve for all-cause mortality and cardiovascular mortality. (A) Kaplan-Meier survival curve for all-cause mortality in patients with diagnosed diabetes: a 5-year follow-up analysis considering HbA1c control. (B) Kaplan-Meier survival curve for cardiovascular mortality in patients with diagnosed diabetes: a 5-year follow-up analysis considering HbA1c control. P values <0.05 are suggestive of an association between glycated hemoglobin control and cardiovascular mortality. HbA1c, hemoglobin A1c.

Figure 3 Forest plot for all-cause mortality and cardiovascular mortality by sociodemographic characteristics and comorbid disease. (A) HR calculated with Cox proportional hazards model. Displayed raw P values <0.05 are suggestive of an association between glycated hemoglobin control and all-cause mortality. Compared with diabetic patients with HbA1c ≥7%, those with HbA1c <7% exhibited a non-significant increase in all-cause mortality risk. (B) HR calculated with Cox proportional hazards model. Displayed raw P values <0.05 are suggestive of association between glycated hemoglobin control and cardiovascular mortality. Using HbA1c ≥7% as the reference group, patients with HbA1c <7% exhibited a non-significant increase in cardiovascular mortality risk. CI, confidence interval; HbA1c, hemoglobin A1c; HR, hazard ratio.

Trends in diabetes treatment

In our study, a total of 3,901 individuals received antidiabetic therapy, representing a weighted proportion of 59.06%. The most commonly used classes of antidiabetic medications were biguanides (25.66%), sulfonylureas (21.32%), and insulin (9.64%) (Table 3). The overall treatment rate for diabetes increased significantly from 56.40% in 1999 to 65.34% in 2014 (linear P=0.02). Specifically, sulfonylurea use declined from 30.25% in 1999 to 12.42% in 2014 (linear P<0.001), whereas biguanide use rose from 12.71% to 41.05% over the same period (linear P<0.001). In contrast, insulin use remained relatively stable, with no significant trend observed (11.01% in 1999 vs. 10.40% in 2014; linear P=0.32) (Table 3). Table S5 shows the distribution of various antidiabetic medications in relation to all-cause mortality. Use of sulfonylureas (28.81% vs. 23.43%, P<0.01) and insulin (15.68% vs. 8.49%, P<0.001) was significantly higher among participants who died compared to those who survived. Conversely, biguanide use was significantly lower in the mortality group (14.57.0% vs. 25.80%, P<0.001). No statistically significant differences in mortality were observed for thiazolidinediones, dipeptidyl peptidase-4 inhibitors (P>0.05 for all).

Discussion

Our study observed a steady increase in the proportion of diabetic patients achieving HbA1c <7.0% from 1999 to 2014. However, this improvement in glycemic control was not accompanied by a reduction in 5-year all-cause or cardiovascular mortality rates. Further analyses confirmed that maintaining HbA1c levels below 7.0% did not confer a significant reduction in the risk of cardiovascular mortality. A root cause analysis suggested that the antidiabetic drugs may have influenced these outcomes. Notably, the proportion of sulfonylurea use was significantly higher among individuals who died compared to survivors, indicating a potential association with increased mortality risk.

Despite observing an increasing trend in the control rate of HbA1c among diabetic patients in our study, there was no significant change in cardiovascular and all-cause mortality over the 5-year period. This result is intriguing. While some studies suggest a linear relationship between HbA1c levels and cardiovascular mortality, others propose a J- or U-shaped relationship (24-26). The analysis revealed a U-shaped association between HbA1c levels and mortality risk, with significantly elevated risk observed at both glycemic extremes (HbA1c ≤5.4% or ≥8.5%) (27). Compared to the reference group (HbA1c 6.5–7.5%), patients with HbA1c levels of 8.5–9.5% and ≥9.5% exhibited significantly increased all-cause mortality risk (28). Notably, HbA1c levels <6.5% showed no mortality benefit, consistent with our study findings. Our results further demonstrated that achieving HbA1c <7.0% was not associated with reduced cardiovascular or all-cause mortality. These findings underscore the necessity for more precise glycemic control stratification and large-scale prospective studies to clarify these complex relationships.

Although elevated HbA1c levels are associated with an increased risk of mortality, excessively low HbA1c levels may also pose significant cardiovascular risks. Specifically, low HbA1c levels have been linked to QT interval prolongation, which can predispose individuals to life-threatening arrhythmias and thereby increase the risk of cardiovascular death (26,29). Moreover, low blood glucose may reflect underlying conditions such as protein-energy malnutrition or systemic inflammation, both of which are independently associated with higher mortality risk (30,31). Hypoglycemia itself can impair the energy supply to vital organs, including the myocardium, leading to increased heart rate and peripheral vascular resistance, ultimately elevating the risk of cardiovascular events and death (32). Therefore, excessively low blood sugar levels can also lead to an increased risk of death. Our study found that among individuals with lower educational attainment, diabetic patients with HbA1c <7.0% had reduced risks of both cardiovascular and all-cause mortality. However, further research is needed to confirm and elucidate these findings.

Lifestyle interventions such as exercise and diet are fundamental components of glycemic control; however, glucose-lowering agents remain indispensable in the management of diabetes. To investigate why achieving HbA1c targets did not translate into reduced mortality risk in our cohort, we conducted a detailed analysis of antidiabetic medication usage. Our findings indicated that sulfonylureas, biguanides, and insulin were the most commonly prescribed drug classes. Notably, several studies have reported associations between these commonly used medications—particularly sulfonylureas—and increased mortality risk (33-35). While HbA1c control can reduce the risk of mortality, it’s crucial to consider the potential side effects of medications (33). Sulfonylureas have been implicated in increased mortality risk since the mid-20th century (31), potentially due to side effects such as weight gain, fluid retention, and hypoglycemia (36,37). Moreover, certain sulfonylureas lack selectivity for pancreatic β-cells and may interact with myocardial and vascular β-cells, thus elevating cardiovascular risk (38). In our study, nearly half of medicated diabetic patients were prescribed sulfonylureas, which may partly explain the observed increase in cardiovascular mortality.

These subgroup findings suggest that the association between HbA1c levels and mortality risk may vary across sociodemographic groups. Among individuals with a primary education level or lower, HbA1c levels ≥7.0% were unexpectedly associated with reduced risks of both all-cause and cardiovascular mortality. This finding may reflect residual confounding or differential access to care and treatment adherence among less-educated populations, as prior studies have shown that socioeconomic status influences both glycemic control and health outcomes (39,40). Similarly, the observed reduced cardiovascular mortality risk in women and individuals with a PIR <100% may be related to differences in baseline risk profiles, comorbidities, or therapeutic inertia. Prior analyses from NHANES and other cohorts have reported that glycemic targets may not benefit all subgroups equally and that overtreatment in vulnerable populations could lead to harm (41). These findings underscore the need for individualized glycemic targets based on patient characteristics and social determinants of health. However, due to the observational design of our study, these associations should be interpreted with caution.

Additionally, approximately 10% of patients in our cohort were treated with insulin. Insulin use often indicates advanced disease stages characterized by marked insulin resistance, which is itself a known marker of increased mortality risk (42). These medication-related factors may contribute to the lack of observed benefit in cardiovascular and all-cause mortality despite achieving HbA1c targets. Encouragingly, the use of sulfonylureas declined substantially during the study period—from 30.25% in 1999 to 12.42% in 2014—which may herald a potential future reduction in diabetes-related mortality. Nevertheless, further longitudinal studies are warranted to confirm this trend and to optimize antidiabetic pharmacotherapy strategies.

Strengths

This study possesses several notable methodological strengths that enhance the validity and impact of its findings. First, the utilization of a large, nationally representative NHANES dataset ensures robust external validity and enhances the generalizability of results to the U.S. adult population with diabetes. Second, the extended observation period [1999–2014] enables comprehensive analysis of longitudinal trends in glycemic control and therapeutic approaches. Third, the application of sophisticated statistical techniques—including multivariable logistic regression, Cox proportional hazards modeling with time-dependent covariates, and Kaplan-Meier survival analysis with log-rank testing—provides rigorous examination of the HbA1c-mortality relationship. Fourth, the documentation of temporal patterns in antidiabetic medication utilization, particularly the declining sulfonylurea prescription rates, offers valuable insights into evolving clinical practices. Finally, the separate analysis of cardiovascular-specific versus all-cause mortality permits more nuanced interpretation of diabetes-related outcomes.

Limitations

There are several limitations in this study. First, the study’s reliance solely on baseline data for HbA1c limited our ability to assess changes in these factors and their influence on all-cause and cardiovascular mortality during follow-up. HbA1c, the study’s primary focus, provides a snapshot of glucose levels over the past 2–3 months and tends to remain relatively stable over time. Second, although risk-factor control was defined based on current clinical guidelines and research, it’s important to acknowledge that recommendations may have evolved since the study began. Nonetheless, our exploration of alternative targets and trends in glycated hemoglobin revealed similar patterns. Third, there is a possibility of recall bias affecting the accuracy of medication data, as medication use was partially determined from participant reports. Fourth, our study covered the period from 1999 to 2014, during which prognostically beneficial hypoglycemic agents such as GLP1, SLT2, DPP4, etc., were relatively underrepresented. Finally, it is worth mentioning that our study could not reliably distinguish between type 1 and type 2 diabetes in the study population. However, given that type 2 diabetes comprises over 90% of diagnosed diabetes cases in the United States (43), our findings largely reflect risk-factor treatment and control in individuals with type 2 diabetes.

Conclusions

A discernible enhancement in HbA1c control rates was evident, however, a substantial decline in 5-year all-cause mortality and cardiovascular mortality rates was not observed among diabetic patients between 1999 and 2014. Lowering HbA1c levels below 7.0% did not exhibit a noteworthy effect on all-cause mortality and cardiovascular mortality in diabetic adults. The observed lack of mortality risk reduction associated with HbA1c control may be influenced by the differential use of antidiabetic medications, including sulfonylureas, although causality cannot be established in this observational study.

Acknowledgments

We would like to thank the China Health and Retirement Longitudinal Study (CHARLS) research team for providing the publicly available data used in this study.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-59/rc

Peer Review File: Available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-59/prf

Funding: This study was supported by Sichuan Provincial Cadre Health Research Project (China Sichuan Ganyan) (No. ZH2024-101) and by 1·3·5 Project for Disciplines of Excellence-Clinical Research Incubation Project, West China Hospital, Sichuan University (No. 2021HXFH061).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-59/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Study protocols were ethically approved by the Institutional Review Board of the National Center for Health Statistics (Protocol Nos. 98-12, 2005-06, continuation of 2005–2006, 2011–2017, and continuation of 2011–2017), and all participants provided written informed consent.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Lin CL, Chang YT, Liu WC, et al. Exploring and Developing a New Culturally-Appropriate Diabetes Distress Scale in Taiwan. Front Public Health 2022;10:838661. [Crossref] [PubMed]
2. Whiting DR, Guariguata L, Weil C, et al. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract 2011;94:311-21. [Crossref] [PubMed]
3. Paneni F, Beckman JA, Creager MA, et al. Diabetes and vascular disease: pathophysiology, clinical consequences, and medical therapy: part I. Eur Heart J 2013;34:2436-43. [Crossref] [PubMed]
4. Harding JL, Pavkov ME, Magliano DJ, et al. Global trends in diabetes complications: a review of current evidence. Diabetologia 2019;62:3-16. [Crossref] [PubMed]
5. Jakubiak GK, Chwalba A, Basek A, et al. Glycated Hemoglobin and Cardiovascular Disease in Patients Without Diabetes. J Clin Med 2024;14:53. [Crossref] [PubMed]
6. Abdul-Ghani MA, Tripathy D, DeFronzo RA. Contributions of beta-cell dysfunction and insulin resistance to the pathogenesis of impaired glucose tolerance and impaired fasting glucose. Diabetes Care 2006;29:1130-9. [Crossref] [PubMed]
7. International Expert Committee. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 2009;32:1327-34.
8. ElSayed NA, Aleppo G, Aroda VR, et al. 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care 2023;46:S19-40. [Crossref] [PubMed]
9. Sinning C, Makarova N, Völzke H, et al. Association of glycated hemoglobin A(1c) levels with cardiovascular outcomes in the general population: results from the BiomarCaRE (Biomarker for Cardiovascular Risk Assessment in Europe) consortium. Cardiovasc Diabetol 2021;20:223. [Crossref] [PubMed]
10. Cavero-Redondo I, Peleteiro B, Álvarez-Bueno C, et al. Glycated haemoglobin A1c as a risk factor of cardiovascular outcomes and all-cause mortality in diabetic and non-diabetic populations: a systematic review and meta-analysis. BMJ Open 2017;7:e015949. [Crossref] [PubMed]
11. Moss SE, Klein R, Klein BE, et al. The association of glycemia and cause-specific mortality in a diabetic population. Arch Intern Med 1994;154:2473-9.
12. Selvin E, Marinopoulos S, Berkenblit G, et al. Meta-analysis: glycosylated hemoglobin and cardiovascular disease in diabetes mellitus. Ann Intern Med 2004;141:421-31. [Crossref] [PubMed]
13. Shichiri M, Kishikawa H, Ohkubo Y, et al. Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients. Diabetes Care 2000;23:B21-9.
14. Ohkubo Y, Kishikawa H, Araki E, et al. Intensive insulin therapy prevents the progression of diabetic microvascular complications in Japanese patients with non-insulin-dependent diabetes mellitus: a randomized prospective 6-year study. Diabetes Res Clin Pract 1995;28:103-17. [Crossref] [PubMed]
15. Stettler C, Allemann S, Jüni P, et al. Glycemic control and macrovascular disease in types 1 and 2 diabetes mellitus: Meta-analysis of randomized trials. Am Heart J 2006;152:27-38. [Crossref] [PubMed]
16. Standards of medical care in diabetes--2007. Diabetes Care 2007;30:S4-S41. [Crossref] [PubMed]
17. Rooney MR, Rawlings AM, Pankow JS, et al. Risk of Progression to Diabetes Among Older Adults With Prediabetes. JAMA Intern Med 2021;181:511-9. [Crossref] [PubMed]
18. American Diabetes Association. 6. Glycemic Targets: Standards of Medical Care in Diabetes-2019. Diabetes Care 2019;42:S61-70. [Crossref] [PubMed]
19. Fang M, Wang D, Coresh J, et al. Trends in Diabetes Treatment and Control in U.S. Adults, 1999-2018. N Engl J Med 2021;384:2219-28. [Crossref] [PubMed]
20. International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10), 2nd edition. Geneva: World Health Organization; 2004.
21. Curtin LR, Mohadjer LK, Dohrmann SM, et al. The National Health and Nutrition Examination Survey: Sample Design, 1999-2006. Vital Health Stat 2 2012;1-39.
22. Curtin LR, Mohadjer LK, Dohrmann SM, et al. National Health and Nutrition Examination Survey: sample design, 2007-2010. Vital Health Stat 2 2013;1-23.
23. Johnson CL, Dohrmann SM, Burt VL, et al. National health and nutrition examination survey: sample design, 2011-2014. Vital Health Stat 2 2014;1-33.
24. Blaum CS, Volpato S, Cappola AR, et al. Diabetes, hyperglycaemia and mortality in disabled older women: The Women's Health and Ageing Study I. Diabet Med 2005;22:543-50. [Crossref] [PubMed]
25. Anyanwagu U, Mamza J, Donnelly R, et al. Relationship between HbA1c and all-cause mortality in older patients with insulin-treated type 2 diabetes: results of a large UK Cohort Study. Age Ageing 2019;48:235-40. [Crossref] [PubMed]
26. Goode KM, John J, Rigby AS, et al. Elevated glycated haemoglobin is a strong predictor of mortality in patients with left ventricular systolic dysfunction who are not receiving treatment for diabetes mellitus. Heart 2009;95:917-23. [Crossref] [PubMed]
27. Hill CJ, Maxwell AP, Cardwell CR, et al. Glycated hemoglobin and risk of death in diabetic patients treated with hemodialysis: a meta-analysis. Am J Kidney Dis 2014;63:84-94. [Crossref] [PubMed]
28. Kim DK, Ko GJ, Choi YJ, et al. Glycated hemoglobin levels and risk of all-cause and cause-specific mortality in hemodialysis patients with diabetes. Diabetes Res Clin Pract 2022;190:110016. [Crossref] [PubMed]
29. Frier BM, Schernthaner G, Heller SR. Hypoglycemia and cardiovascular risks. Diabetes Care 2011;34:S132-7. [Crossref] [PubMed]
30. Kalantar-Zadeh K, Block G, Horwich T, et al. Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol 2004;43:1439-44. [Crossref] [PubMed]
31. Menon V, Greene T, Pereira AA, et al. Glycosylated hemoglobin and mortality in patients with nondiabetic chronic kidney disease. J Am Soc Nephrol 2005;16:3411-7. [Crossref] [PubMed]
32. Wright RJ, Frier BM. Vascular disease and diabetes: is hypoglycaemia an aggravating factor? Diabetes Metab Res Rev 2008;24:353-63. [Crossref] [PubMed]
33. Azoulay L, Suissa S. Sulfonylureas and the Risks of Cardiovascular Events and Death: A Methodological Meta-Regression Analysis of the Observational Studies. Diabetes Care 2017;40:706-14. [Crossref] [PubMed]
34. Cosmi F, Shen L, Magnoli M, et al. Treatment with insulin is associated with worse outcome in patients with chronic heart failure and diabetes. Eur J Heart Fail 2018;20:888-95. [Crossref] [PubMed]
35. Bromage DI, Godec TR, Pujades-Rodriguez M, et al. Metformin use and cardiovascular outcomes after acute myocardial infarction in patients with type 2 diabetes: a cohort study. Cardiovasc Diabetol 2019;18:168. [Crossref] [PubMed]
36. Meinert CL, Knatterud GL, Prout TE, et al. A study of the effects of hypoglycemic agents on vascular complications in patients with adult-onset diabetes. II. Mortality results. Diabetes 1970;19:789-830.
37. Tahrani AA, Barnett AH, Bailey CJ. Pharmacology and therapeutic implications of current drugs for type 2 diabetes mellitus. Nat Rev Endocrinol 2016;12:566-92. [Crossref] [PubMed]
38. Krentz AJ, Bailey CJ. Oral antidiabetic agents: current role in type 2 diabetes mellitus. Drugs 2005;65:385-411. [Crossref] [PubMed]
39. Zhu Y, Sidell MA, Arterburn D, et al. Racial/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U.S. Diabetes Care 2019;42:2211-9. [Crossref] [PubMed]
40. Saydah S, Lochner K. Socioeconomic status and risk of diabetes-related mortality in the U.S. Public Health Rep 2010;125:377-88. [Crossref] [PubMed]
41. McCoy RG, Lipska KJ, Yao X, et al. Intensive Treatment and Severe Hypoglycemia Among Adults With Type 2 Diabetes. JAMA Intern Med 2016;176:969-78. [Crossref] [PubMed]
42. Ausk KJ, Boyko EJ, Ioannou GN. Insulin resistance predicts mortality in nondiabetic individuals in the U.S. Diabetes Care 2010;33:1179-85. [Crossref] [PubMed]
43. Bullard KM, Cowie CC, Lessem SE, et al. Prevalence of Diagnosed Diabetes in Adults by Diabetes Type - United States, 2016. MMWR Morb Mortal Wkly Rep 2018;67:359-61. [Crossref] [PubMed]