OBJECTIVE

Uncertainty remains regarding the predictive value of various glycemic measures as they relate to the risk of diabetes and its complications. Using the cutoffs recommended by the American Diabetes Association’s 2010 criteria, we determined the associations of fasting plasma glucose (FPG), 2-h postload glucose (2h-PG), and HbA1c with the outcomes.

RESEARCH DESIGN AND METHODS

Baseline medical history, FPG, 2h-PG, and HbA1c were obtained from a population-based cohort of 193,846 adults aged ≥40 years in China during 2011–2012. A follow-up visit was conducted during 2014–2016 in order to assess incident diabetes, cardiovascular disease (CVD), cancer, and mortality.

RESULTS

We documented 8,063 cases of diabetes, 3,014 CVD-related events, 1,624 cases of cancer, and 2,409 deaths during up to 5 years of follow-up. Multivariable-adjusted risk ratios (95% CIs) of diabetes associated with prediabetes based on FPG of 100–125 mg/dL, 2h-PG of 140–199 mg/dL, or HbA1c of 5.7–6.4% (39–47 mmol/mol) were 1.60 (1.43–1.79), 2.72 (2.43–3.04), and 1.49 (1.36–1.62), respectively. Restricted cubic spline analyses suggested J-shaped associations of FPG, 2h-PG, and HbA1c levels with CVD, cancer, and mortality. Multivariable-adjusted hazard ratios (95% CIs) associated with untreated diabetes based on FPG ≥126 mg/dL, 2h-PG ≥200 mg/dL, or HbA1c ≥6.5% (48 mmol/mol) were 1.18 (1.05–1.33), 1.31 (1.18–1.45), and 1.20 (1.07–1.34) for CVD; 1.10 (0.92–1.32), 1.44 (1.25–1.67), and 1.08 (0.92–1.28) for cancer; and 1.37 (1.20–1.57), 1.57 (1.41–1.76), and 1.33 (1.17–1.52) for mortality, respectively. 2h-PG remained significantly associated with outcomes in models including FPG and HbA1c as spline terms. Furthermore, 2h-PG significantly improved the ability of the C statistic to predict diabetes, CVD, and mortality.

CONCLUSIONS

2h-PG remains independently predictive of outcomes in models including FPG and HbA1c. Therefore, in addition to FPG and HbA1c, routine testing of 2h-PG should be considered in order to better assess the risks of outcomes.

Diabetes has become a major cause of death and disability worldwide (1). The prevalence of diabetes has more than quadrupled in China during the past two decades (2,3). It has been estimated that 113.9 million Chinese adults had diabetes and 493.4 million had prediabetes in 2010 (3).

Fasting plasma glucose (FPG), 2-h postload glucose (2h-PG), and HbA1c have been used to test glycemia, but uncertainty remains regarding their predictive utility in determining the risk of incident diabetes, cardiovascular disease (CVD), cancer, and mortality (46). Only a few prospective studies have compared all three glycemic measures in the same participants, and they reported conflicting findings (79). The Atherosclerosis Risk in Communities (ARIC) study showed that prediabetes defined on the basis of HbA1c provided better risk discrimination for clinical complications and all-cause mortality (9). Other studies, however, reported that 2h-PG better predicted CVD and mortality (7,8). These studies all had limited sample sizes. The values of the three glycemic measures in predicting risk of diabetes were not directly compared. In addition, the three glycemic measures were obtained from the ARIC study participants at different visits (9).

Using the established cutoffs for prediabetes and diabetes recommended by American Diabetes Association (ADA) 2010 criteria, we compared the associations of FPG, 2h-PG, and HbA1c levels with the incidences of diabetes, CVD, and cancer, and all-cause mortality, among participants from the China Cardiometabolic Disease and Cancer Cohort (4C) Study, a prospective cohort study of Chinese adults aged ≥40 years.

Study Participants

The 4C Study was a multicenter, population-based, prospective cohort study investigating the associations of glucose homeostasis with clinical outcomes including diabetes, CVD, cancer, and all-cause mortality.

Between 2011 and 2012, a total of 259,657 individuals aged ≥40 years were recruited from 25 communities throughout various regions of China in order to participate in the Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal (REACTION) Study (10,11). The main objectives of the REACTION Study were to demonstrate whether abnormal glucose metabolism (prediabetes and diabetes) was associated with increased risk for cancer in the Chinese population and to identify factors that modify the risk of cancer among individuals with abnormal glucose metabolism (10,11). Eligible men and women aged ≥40 years were identified from local resident registration systems. Trained community health workers visited eligible individuals’ homes and invited them to participate in the study.

In 2014, funding allowed the study to do a follow-up examination visit. Because of limited funds, however, only 193,846 participants from 20 communities from various geographic regions in China, selected to represent the general population, were invited to participate. In addition, the objectives of the study were extended in order to investigate the association of glycemia measures with the incidence of diabetes, CVD, and cancer, and with mortality. Therefore, the study was renamed as the 4C Study.

The study was approved by the Medical Ethics Committee of Ruijin Hospital, Shanghai Jiaotong University. All study participants provided written informed consent.

Baseline Data Collection

The study visits took place in the mornings at local community clinics. Participants were required to fast for ≥10 h before their clinic visits. Trained study personnel used a standard questionnaire to obtain data on participants’ sociodemographic information, lifestyle risk factors, and medical history. Physical activity was assessed using the International Physical Activity Questionnaire (12). Moderate and vigorous physical activity was defined as ≥150 min/week of moderate-intensity physical activity, or 75 min/week of vigorous aerobic activity, or an equivalent combination of moderate-intensity and vigorous aerobic activities (13). Trained study nurses measured body weight, height, waist circumference, and blood pressure according to a standard protocol (14). Three blood pressure measurements were obtained with participants in a seated position after 5 min of quiet rest. In addition, participants were required to avoid alcohol, cigarettes, coffee/tea, and exercise for ≥30 min before their blood pressure was measured. An automated blood pressure and pulse monitor (model HEM-752 FUZZY; OMRON, Dalian, China) was used for obtaining measurements, and one of four cuff sizes (pediatric, regular adult, large, or thigh) was chosen on the basis of the participant’s arm circumference.

All participants underwent an oral glucose tolerance test, and plasma glucose was obtained at 0 and 2 h during the test. Plasma glucose concentrations were analyzed locally by using the glucose oxidase or the hexokinase method within 2 h after collecting the blood sample under a stringent quality control program. Previous research has shown these two methods of glucose measurement to be highly consistent (15,16). All regional laboratories passed a national standardization program and a study-specific quality assurance program. A Hemoglobin Capillary Collection System (Bio-Rad Laboratories, Hercules, CA) was used to collect capillary whole blood from a finger. Blood was shipped at 2–8°C to a certified central laboratory at Ruijin Hospital, Shanghai, China. This clinical laboratory is certificated by the U.S. National Glycohemoglobin Standardization Program and passed the Laboratory Accreditation Program of the College of American Pathologists. HbA1c was determined by using high-performance liquid chromatography (VARIANT II System; Bio-Rad Laboratories). Serum insulin, total cholesterol, LDL cholesterol, HDL cholesterol, and triglycerides were measured at the cen-tral laboratory by using an ARCHITECT ci16200 autoanalyzer (Abbott Laboratories, Abbott Park, IL).

Follow-up and Outcome Assessment

During 2014–2016, all participants were invited to attend an in-person follow-up visit. Trained staff queried lifestyle risk factors and medical history using the same standard questionnaire as was used at baseline. Anthropometric values and blood pressure were measured, oral glucose tolerance tests performed, and blood samples obtained by using the same protocols that were used during the baseline examination. If patients were hospitalized or had visited an emergency department, trained staff used a standard form to obtain data—including medical history, physical examination findings, laboratory tests, treatments, and diagnosis at discharge—from the participants’ medical records. In addition, photocopies were obtained of selected sections of a given participant’s inpatient record, discharge summary, electrocardiogram, and pathology reports.

Information on vital status and clinical outcomes was collected from local death and disease registries of the National Disease Surveillance Point System and National Health Insurance System. Two members of the outcome adjudication committee independently verified each clinical event, and discrepancies were adjudicated through discussion involving other members of the committee. All members of the committee were unaware of the baseline risk factors of study participants.

Incident diabetes was defined as any one or a combination of FPG ≥126 mg/dL, 2h-PG ≥200 mg/dL, HbA1c ≥6.5% (48 mmol/mol), or a self-reported previous diagnosis by health care professionals at a follow-up visit among participants without diabetes at baseline.

Incident CVD was defined as the first instance of myocardial infarction, stroke, hospitalization or treatment for heart failure, and cardiovascular death during follow-up. Myocardial infarction was defined by characteristic changes in levels of troponin T and the creatine kinase–MB isoform, symptoms of myocardial ischemia, changes in electrocardiogram results, or a combination of these. Stroke was defined as a fixed neurological deficit lasting >24 h and having a presumably vascular cause. Heart failure was identified by hospitalization, or an emergency department visit with medical therapy, for a clinical syndrome presenting with multiple signs and symptoms consistent with cardiac decompensation or inadequate cardiac pump function. Incident cancer was defined as the first occurrence of any type of cancer at any site during follow-up.

Statistical Analyses

Cumulative incidence (95% CI) of diabetes was calculated for a mean of 3.8 years’ follow-up. We used relative risk regression to examine the associations between glycemic measures at baseline and risk of incident diabetes (17). We adjusted multivariable models for baseline age, sex, BMI, family history of diabetes, cigarette smoking, alcohol consumption, education, physical activity, systolic blood pressure, HDL cholesterol, LDL cholesterol, and triglycerides.

Potential nonlinear associations between the levels of glycemia and the incidence of clinical outcomes were examined with restricted cubic splines (18). Analyses adjusted for multiple variables, and the highest and lowest 0.5% was trimmed for each glycemic measure. A knot was located at the 5th, 50th, and 95th percentiles for each of the three glycemic measures. Tests for nonlinearity, which compared a model containing only the linear term with a model containing the linear and restricted cubic spline terms, were conducted by using likelihood ratio tests. If a test for nonlinearity was not significant, we conducted a test for linearity, comparing a model containing the linear term with a model containing only the covariates of interest.

We calculated incidence rate (95% CI) per 1,000 person-years, and we used Cox proportional hazards models to investigate the associations of baseline glycemic measures and subsequent CVD, cancer, and all-cause mortality (19). In the time-to-event analysis, data were censored at the time of the clinical event, death, or the end of follow-up—whichever occurred first. In addition to the aforementioned covariables, we included baseline glycemic measures as spline terms in the mutually adjusted model to compare the strength of associations with clinical outcomes.

To assess the added value of individual or a combination of glycemic measures in prediction models, we included continuous glycemic measures in the models of subsequent diabetes and categorized glycemic measures using the cutoffs recommended by the 2019 ADA criteria; these measures were added to the models of subsequent CVD, cancer, and all-cause mortality. We calculated the difference (C statistic) with or without glycemic measures, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) (20). The C statistic measures concordance between model-based risk estimates and observed events. NRI and IDI measure the incremental prognostic effect that a new biomarker will have when added to an existing prediction model. We used bootstrapping methods to obtain 95% CIs.

We used SAS version 9.2 (SAS Institute) to conduct statistical analyses and R version 3.4.2 (R Foundation for Statistical Computing) to create Cox models with restricted cubic splines.

Among 193,846 study participants, 170,240 (87.8%) were followed up in 2014–2016. We excluded 12,677 with treated diabetes and 6,074 with one or more glycemic measures missing at baseline, leaving 151,489 for this analysis. Additionally, 22,632 participants with untreated diabetes at baseline and 22,364 without glucose measures at follow-up were excluded from diabetes analyses, 7,503 participants with CVD and 2,148 with cancer at baseline were excluded from the respective analyses, and 22,652 participants without follow-up data on CVD and cancer were also excluded (Supplementary Fig. 1).

Baseline characteristics of participants without treated diabetes are presented in Table 1 according to categories of glycemic measures. In addition, baseline characteristics of participants without a history of diagnosed diabetes (including treated and untreated diabetes) are reported in Supplementary Table 1. Baseline characteristics of participants who were and who were not lost to follow-up are shown in Supplementary Table 2.

Table 1

Baseline characteristics of 151,489 study participants without treated diabetes, according to plasma glucose and HbA1c levels

FPG, mg/dL
2h-PG, mg/dL
HbA1c, %
<100100–125≥126P value<140140–199≥200P value<5.7% (39 mmol/mol)5.7–6.4% (39–47 mmol/mol)≥6.5% (48 mmol/mol)P value
Participants 84,260 (55.6) 55,365 (36.6) 11,864 (7.8) <0.001 96,394 (63.6) 37,784 (25.0) 17,311 (11.4) <0.001 58,996 (39.0) 76,082 (50.2) 16,411 (10.8) <0.001 
Age, years 55.6 ± 9.2 57.7 ± 8.9 58.7 ± 8.8 <0.001 55.4 ± 8.9 58.3 ± 9.1 59.60 ± 8.9 <0.001 54.3 ± 9.1 57.8 ± 8.7 59.6 ± 8.6 <0.001 
Male sex 26,003 (30.9) 20,162 (36.4) 5,187 (43.7) <0.001 32,243 (33.5) 12,261 (32.5) 6,848 (39.6) <0.001 20,911 (35.4) 24,517 (32.2) 5,924 (36.1) <0.001 
BMI, kg/m2 24.2 ± 3.5 25.1 ± 3.6 26.0 ± 3.6 <0.001 24.22 ± 3.5 25.18 ± 3.6 25.82 ± 3.7 <0.001 24.0 ± 3.4 24.8 ± 3.6 26.2 ± 3.6 <0.001 
High school or higher education  31,904 (37.9) 18,721 (33.8) 3,954 (33.3) <0.001 35,562 (36.9) 13,179 (34.9) 5,838 (33.7) 0.02 21,212 (36.0) 27,697 (36.4) 5,670 (34.6) 0.10 
Current cigarette smoking 12,057 (14.3) 7,772 (14.0) 2,033 (17.1) <0.001 14,672 (15.2) 4,574 (12.1) 2,616 (15.1) <0.001 9,065 (15.4) 10,412 (13.7) 2,385 (14.5) <0.001 
Current alcohol drinking 7,349 (8.7) 6,364 (11.5) 1,604 (13.5) <0.001 9,620 (10.0) 3,736 (9.9) 1,961 (11.3) <0.001 6,803 (11.5) 7,009 (9.2) 1,505 (9.2) <0.001 
Moderate and vigorous physical activity 11,221 (13.3) 7,401 (13.4) 1,411 (11.9) 0.005 12,871 (13.4) 5,072 (13.4) 2,090 (12.1) <0.001 7,199 (12.2) 10,712 (14.1) 2,122 (12.9) <0.001 
Family history of diabetes 9,012 (10.7) 6,519 (11.8) 1,945 (16.4) <0.001 10,034 (10.4) 4,733 (12.5) 2,709 (15.7) <0.001 5,602 (9.5) 9,102 (12.0) 2,772 (16.9) <0.001 
Systolic blood pressure, mmHg 130.2 ± 20.4 135.7 ± 20.4 141.4 ± 20.9 <0.001 130.7 ± 20.4 135.8 ± 20.5 140.8 ± 20.8 <0.001 131.3 ± 20.7 133.2 ± 20.7 138.9 ± 20.6 <0.001 
Fasting HDL cholesterol, mg/dL 53.1 ± 14.0 51.4 ± 14.1 49.1 ± 13.2 <0.001 53.3 ± 14.2 50.6 ± 13.6 49.3 ± 13.7 <0.001 53.9 ± 14.5 51.6 ± 13.8 48.4 ± 12.7 <0.001 
Fasting LDL cholesterol, mg/dL 110.6 ± 33.2 113.8 ± 34.5 118.3 ± 35.9 <0.001 110.8 ± 33.3 114.2 ± 34.5 117.4 ± 35.9 <0.001 107.5 ± 32.0 114.6 ± 34.4 119.5 ± 36.2 <0.001 
Fasting triglycerides, mg/dL 107.2 (78.0–153.2) 124.0 (87.7–179.8) 150.6 (104.5–223.2) <0.001 106.3 (77.1–150.6) 131.1 (93.0–188.7) 149.7 (104.5–217.9) <0.001 104.5 (76.2–149.7) 119.6 (85.0–171.0) 150.6 (105.4–217.5) <0.001 
FPG, mg/dL 92.0 ± 6.2 108.87 ± 6.4 160.70 ± 44.9 <0.001 97.0 ± 11.2 104.5 ± 13.7 138.1 ± 46.2 <0.001 96.3 ± 11.5 101.5 ± 13.0 139.2 ± 46.9 <0.001 
2-h PG, mg/dL 119.6 ± 33.6 145.9 ± 45.7 260.4 ± 99.2 <0.001 108.4 ± 19.6 162.8 ± 16.2 268.2 ± 71.7 <0.001 119.4 ± 34.4 135.9 ± 42.2 235.7 ± 97.0 <0.001 
HbA1c, % 5.7 ± 0.4 5.9 ± 0.5 7.5 ± 1.8 <0.001 5.7 ± 0.5 5.9 ± 0.5 7.1 ± 1.6 <0.001 5.3 ± 0.3 6.0 ± 0.2 7.5 ± 1.5 <0.001 
FPG, mg/dL
2h-PG, mg/dL
HbA1c, %
<100100–125≥126P value<140140–199≥200P value<5.7% (39 mmol/mol)5.7–6.4% (39–47 mmol/mol)≥6.5% (48 mmol/mol)P value
Participants 84,260 (55.6) 55,365 (36.6) 11,864 (7.8) <0.001 96,394 (63.6) 37,784 (25.0) 17,311 (11.4) <0.001 58,996 (39.0) 76,082 (50.2) 16,411 (10.8) <0.001 
Age, years 55.6 ± 9.2 57.7 ± 8.9 58.7 ± 8.8 <0.001 55.4 ± 8.9 58.3 ± 9.1 59.60 ± 8.9 <0.001 54.3 ± 9.1 57.8 ± 8.7 59.6 ± 8.6 <0.001 
Male sex 26,003 (30.9) 20,162 (36.4) 5,187 (43.7) <0.001 32,243 (33.5) 12,261 (32.5) 6,848 (39.6) <0.001 20,911 (35.4) 24,517 (32.2) 5,924 (36.1) <0.001 
BMI, kg/m2 24.2 ± 3.5 25.1 ± 3.6 26.0 ± 3.6 <0.001 24.22 ± 3.5 25.18 ± 3.6 25.82 ± 3.7 <0.001 24.0 ± 3.4 24.8 ± 3.6 26.2 ± 3.6 <0.001 
High school or higher education  31,904 (37.9) 18,721 (33.8) 3,954 (33.3) <0.001 35,562 (36.9) 13,179 (34.9) 5,838 (33.7) 0.02 21,212 (36.0) 27,697 (36.4) 5,670 (34.6) 0.10 
Current cigarette smoking 12,057 (14.3) 7,772 (14.0) 2,033 (17.1) <0.001 14,672 (15.2) 4,574 (12.1) 2,616 (15.1) <0.001 9,065 (15.4) 10,412 (13.7) 2,385 (14.5) <0.001 
Current alcohol drinking 7,349 (8.7) 6,364 (11.5) 1,604 (13.5) <0.001 9,620 (10.0) 3,736 (9.9) 1,961 (11.3) <0.001 6,803 (11.5) 7,009 (9.2) 1,505 (9.2) <0.001 
Moderate and vigorous physical activity 11,221 (13.3) 7,401 (13.4) 1,411 (11.9) 0.005 12,871 (13.4) 5,072 (13.4) 2,090 (12.1) <0.001 7,199 (12.2) 10,712 (14.1) 2,122 (12.9) <0.001 
Family history of diabetes 9,012 (10.7) 6,519 (11.8) 1,945 (16.4) <0.001 10,034 (10.4) 4,733 (12.5) 2,709 (15.7) <0.001 5,602 (9.5) 9,102 (12.0) 2,772 (16.9) <0.001 
Systolic blood pressure, mmHg 130.2 ± 20.4 135.7 ± 20.4 141.4 ± 20.9 <0.001 130.7 ± 20.4 135.8 ± 20.5 140.8 ± 20.8 <0.001 131.3 ± 20.7 133.2 ± 20.7 138.9 ± 20.6 <0.001 
Fasting HDL cholesterol, mg/dL 53.1 ± 14.0 51.4 ± 14.1 49.1 ± 13.2 <0.001 53.3 ± 14.2 50.6 ± 13.6 49.3 ± 13.7 <0.001 53.9 ± 14.5 51.6 ± 13.8 48.4 ± 12.7 <0.001 
Fasting LDL cholesterol, mg/dL 110.6 ± 33.2 113.8 ± 34.5 118.3 ± 35.9 <0.001 110.8 ± 33.3 114.2 ± 34.5 117.4 ± 35.9 <0.001 107.5 ± 32.0 114.6 ± 34.4 119.5 ± 36.2 <0.001 
Fasting triglycerides, mg/dL 107.2 (78.0–153.2) 124.0 (87.7–179.8) 150.6 (104.5–223.2) <0.001 106.3 (77.1–150.6) 131.1 (93.0–188.7) 149.7 (104.5–217.9) <0.001 104.5 (76.2–149.7) 119.6 (85.0–171.0) 150.6 (105.4–217.5) <0.001 
FPG, mg/dL 92.0 ± 6.2 108.87 ± 6.4 160.70 ± 44.9 <0.001 97.0 ± 11.2 104.5 ± 13.7 138.1 ± 46.2 <0.001 96.3 ± 11.5 101.5 ± 13.0 139.2 ± 46.9 <0.001 
2-h PG, mg/dL 119.6 ± 33.6 145.9 ± 45.7 260.4 ± 99.2 <0.001 108.4 ± 19.6 162.8 ± 16.2 268.2 ± 71.7 <0.001 119.4 ± 34.4 135.9 ± 42.2 235.7 ± 97.0 <0.001 
HbA1c, % 5.7 ± 0.4 5.9 ± 0.5 7.5 ± 1.8 <0.001 5.7 ± 0.5 5.9 ± 0.5 7.1 ± 1.6 <0.001 5.3 ± 0.3 6.0 ± 0.2 7.5 ± 1.5 <0.001 

Values are number (percent), mean ± SD, or median (interquartile range). To convert the values for cholesterol to millimoles per liter, multiply by 0.02586. To convert the values for triglycerides to millimoles per liter, multiply by 0.01129. To convert the values for glucose to millimoles per liter, multiply by 0.05551.

Glycemic Measures and Incident Diabetes

During up to 5 years of follow-up (mean 3.8 years), 8,063 incident cases of diabetes were counted among 106,493 participants without a history of diabetes at baseline. The cumulative incidence of diabetes increased with the number of abnormal glycemic measures and was higher in individuals with isolated impaired glucose tolerance (8.8%) than in those with isolated impaired fasting glucose (5.0%) or isolated elevated HbA1c (4.7%) (P < 0.001 for group difference). Furthermore, the incidence of diabetes was higher in individuals with impaired glucose tolerance and impaired fasting glucose (12.7%) and in those with impaired glucose tolerance and elevated HbA1c (13.3%) than in those with combined impaired fasting glucose and elevated HbA1c (9.2%). Individuals with three abnormal glycemic measures had the highest incidence of diabetes (21.3%) (Table 2).

Table 2

Cumulative incidence and risk ratio of diabetes according to glucose tolerance status over a mean follow-up of 3.8 years among study participants without diagnosed diabetes and without undiagnosed diabetes at baseline

VariableGlucose tolerance
Study participants, n (%)Incident diabetes
Age- and sex-adjusted model
Multivariable-adjusted modela
FPG, mg/dL2h-PG, mg/dLHbA1c, % (mmol/mol)Participants, nCumulative incidence, %Risk ratio (95% CI)P valueRisk ratio (95% CI)P value
Normal glucose tolerance <100 <140 <5.7 (39) 30,291 (28.4) 880 2.9 1.00 (reference)  1.00 (reference)  
Isolated impaired fasting glucose 100–125 <140 <5.7 (39) 9,138 (8.6) 454 5.0 1.66 (1.49–1.86) <0.001 1.60 (1.43–1.79) <0.001 
Isolated impaired glucose tolerance <100 140–199 <5.7 (39) 4,970 (4.7) 437 8.8 2.93 (2.62–3.27) <0.001 2.72 (2.43–3.04) <0.001 
Isolated elevated HbA1c <100 <140 5.7–6.4 (39–47) 25,380 (23.8) 1,184 4.7 1.56 (1.43–1.70) <0.001 1.49 (1.36–1.62) <0.001 
Combined impaired fasting glucose and impaired glucose tolerance 100–125 140–199 <5.7 (39) 3,983 (3.7) 507 12.7 4.21 (3.79–4.68) <0.001 3.71 (3.33–4.13) <0.001 
Combined impaired fasting glucose and elevated HbA1c 100–125 <140 5.7–6.4 (39–47) 14,433 (13.6) 1,320 9.2 3.00 (2.76–3.26) <0.001 2.68 (2.46–2.92) <0.001 
Combined impaired glucose tolerance and elevated HbA1c <100 140–199 5.7–6.4 (39–47) 7,727 (7.3) 1,030 13.3 4.37 (4.00–4.77) <0.001 3.87 (3.53–4.23) <0.001 
Combined impaired fasting glucose, impaired glucose tolerance, and elevated HbA1c 100–125 140–199 5.7–6.4 (39–47) 10,571 (9.9) 2,251 21.3 6.91 (6.40–7.46) <0.001 5.84 (5.40–6.32) <0.001 
VariableGlucose tolerance
Study participants, n (%)Incident diabetes
Age- and sex-adjusted model
Multivariable-adjusted modela
FPG, mg/dL2h-PG, mg/dLHbA1c, % (mmol/mol)Participants, nCumulative incidence, %Risk ratio (95% CI)P valueRisk ratio (95% CI)P value
Normal glucose tolerance <100 <140 <5.7 (39) 30,291 (28.4) 880 2.9 1.00 (reference)  1.00 (reference)  
Isolated impaired fasting glucose 100–125 <140 <5.7 (39) 9,138 (8.6) 454 5.0 1.66 (1.49–1.86) <0.001 1.60 (1.43–1.79) <0.001 
Isolated impaired glucose tolerance <100 140–199 <5.7 (39) 4,970 (4.7) 437 8.8 2.93 (2.62–3.27) <0.001 2.72 (2.43–3.04) <0.001 
Isolated elevated HbA1c <100 <140 5.7–6.4 (39–47) 25,380 (23.8) 1,184 4.7 1.56 (1.43–1.70) <0.001 1.49 (1.36–1.62) <0.001 
Combined impaired fasting glucose and impaired glucose tolerance 100–125 140–199 <5.7 (39) 3,983 (3.7) 507 12.7 4.21 (3.79–4.68) <0.001 3.71 (3.33–4.13) <0.001 
Combined impaired fasting glucose and elevated HbA1c 100–125 <140 5.7–6.4 (39–47) 14,433 (13.6) 1,320 9.2 3.00 (2.76–3.26) <0.001 2.68 (2.46–2.92) <0.001 
Combined impaired glucose tolerance and elevated HbA1c <100 140–199 5.7–6.4 (39–47) 7,727 (7.3) 1,030 13.3 4.37 (4.00–4.77) <0.001 3.87 (3.53–4.23) <0.001 
Combined impaired fasting glucose, impaired glucose tolerance, and elevated HbA1c 100–125 140–199 5.7–6.4 (39–47) 10,571 (9.9) 2,251 21.3 6.91 (6.40–7.46) <0.001 5.84 (5.40–6.32) <0.001 

Diabetes was defined as FPG ≥126 mg/dL (7.0 mmol/L), 2h-PG ≥200 mg/dL (11.1 mmol/L), HbA1c ≥6.5% (48 mmol/mol), or self-report of a physician diagnosis of diabetes and use of antidiabetes medications at the follow-up visits.

aAdjusted for age, sex, BMI, family history of diabetes, smoking, drinking, education status, physical activity, systolic blood pressure, HDL cholesterol, LDL cholesterol, and triglycerides.

After adjusting for important covariables, we found that elevated FPG, 2h-PG, and HbA1c are significant predictive indicators of incident diabetes. The risk ratio (95% CI) of diabetes associated with isolated impaired glucose tolerance (2.72 [2.43–3.04]) was significantly greater than that associated with isolated impaired fasting glucose (1.60 [1.43–1.79]) or isolated elevated HbA1c (1.49 [1.36–1.62]) (Table 2). The risk ratio associated with combined impaired glucose tolerance and either impaired fasting glucose (3.71 [3.33–4.13]) or elevated HbA1c (3.87 [3.53–4.23]) was significantly greater than that associated with combined impaired fasting glucose and elevated HbA1c (2.68 [2.46–2.92]). The risk ratio associated with three abnormal glycemic measures (5.84 [5.40–6.32]) was significantly greater than that for any two abnormal measures.

The multivariable-adjusted risk ratio (95% CI) of incident diabetes associated with prediabetes based on fasting glucose of 100–125 mg/dL was 2.03 (1.94–2.12); that based on 2h-PG of 140–199 mg/dL was 2.78 (2.66–2.90), and that based on HbA1c of 5.7–6.4% was 1.85 (1.76–1.95) (Supplementary Table 3). When all three glycemic measures were included in the same model simultaneously, the risk ratio (95% CI) of diabetes associated with prediabetes based on 2h-PG of 140–199 mg/dL (2.20 [2.10–2.30]) was significantly greater than those associated with prediabetes based on FPG of 100–125 mg/dL (1.46 [1.40–1.53]) or elevated HbA1c (1.44 [1.37–1.51]) (Supplementary Table 3). Results of a sensitivity analysis that use self-reported physician-diagnosed diabetes are shown in Supplementary Table 4; the associations between glycemic measures and incident diabetes were similar.

Glycemic Measures and CVD, Cancer, and Mortality

Among 151,489 participants not receiving antidiabetes treatment at baseline, we identified 3,014 incident cardiovascular events (450 myocardial infarctions, 1,787 strokes, 195 cases of heart failure, and 582 cardiovascular deaths), 1,624 incident cases of cancer (325 lung, 167 breast, 156 colorectal, 135 liver, 134 stomach, 83 thyroid, 57 pancreatic, and 49 esophageal cancers, and 518 cancers at other sites), and 2,409 deaths.

Multivariable-adjusted restricted cubic spline analyses suggested “J-shaped” associations of glycemic markers with CVD, cancer, and all-cause mortality. We found evidence of nonlinear associations of FPG and HbA1c with CVD, cancer, and all-cause mortality. The analyses also suggested significant nonlinear relationships between 2h-PG and both CVD and all-cause mortality, but not cancer. Evidence indicated a significant linear relationship between 2h-PG and cancer (P < 0.001) (Fig. 1). In a sensitivity analysis among individuals without a history of diabetes, the associations between glycemic measures and clinical outcomes were similar (Supplementary Fig. 2).

Figure 1

Multivariable-adjusted hazard ratios of CVD (top row), cancer (middle row), and all-cause mortality (bottom row) in participants without treated diabetes at baseline. The solid lines indicate multivariate-adjusted hazard ratios and the dashed lines indicate the 95% CIs derived from restricted cubic spline regression. A knot is located at the 5th, 50th, and 95th percentiles for each of the three glycemic measures (FPG [left], 2h-PG [middle], HbA1c [right]), and the highest and lowest 0.5% of each glycemic measure was trimmed. The Cox regression was adjusted for age, sex, BMI, family history of diabetes, smoking, drinking, education status, physical activity, systolic blood pressure, HDL cholesterol, LDL cholesterol, and triglycerides.

Figure 1

Multivariable-adjusted hazard ratios of CVD (top row), cancer (middle row), and all-cause mortality (bottom row) in participants without treated diabetes at baseline. The solid lines indicate multivariate-adjusted hazard ratios and the dashed lines indicate the 95% CIs derived from restricted cubic spline regression. A knot is located at the 5th, 50th, and 95th percentiles for each of the three glycemic measures (FPG [left], 2h-PG [middle], HbA1c [right]), and the highest and lowest 0.5% of each glycemic measure was trimmed. The Cox regression was adjusted for age, sex, BMI, family history of diabetes, smoking, drinking, education status, physical activity, systolic blood pressure, HDL cholesterol, LDL cholesterol, and triglycerides.

Multivariable-adjusted hazard ratios (95% CIs) associated with untreated diabetes based on fasting glucose ≥126 mg/dL, 2h-PG ≥200 mg/dL, or HbA1c ≥6.5% (48 mmol/mol) were 1.18 (1.05–1.33), 1.31 (1.18–1.45), and 1.20 (1.07–1.34) for CVD; 1.10 (0.92–1.32), 1.44 (1.25–1.67), and 1.08 (0.92–1.28) for cancer; and 1.37 (1.20–1.57), 1.57 (1.41–1.76), and 1.33 (1.17–1.52) for all-cause mortality, respectively (model 2, Table 3). When all three glycemic measures were included as spline terms in the same model simultaneously (model 3, Table 3), the hazard ratios (95% CIs) for 2h-PG remained significantly and positively associated with CVD (1.30 [1.14–1.49]), cancer (1.62 [1.36–1.93]), and all-cause mortality (1.58 [1.38–1.81]). In addition, prediabetes defined as 2h-PG of 140–199 mg/dL remained consistently and significantly associated with risk of CVD and all-cause mortality. Further adjustments for additional risk factors and study site did not alter our findings (Supplementary Tables 5–8). The risk estimates for CVD, cancer, and all-cause mortality based on the higher cutoffs of 6.1 mmol/L for impaired fasting glucose and 6.0% for elevated HbA1c did not change significantly (Supplementary Table 9). In a sensitivity analysis, among individuals without a history of diagnosed diabetes, the associations between glycemic measures and clinical outcomes were similar (Supplementary Table 10). Moreover, sensitivity analyses using a common population that excluded individuals with diabetes, CVD, and cancer at baseline did not change the study findings (Supplementary Tables 11 and 12).

Table 3

Incidence and hazard ratios of CVD, cancer, and all-cause mortality among participants without treated diabetes at baseline

Person-years, nEvents, nIncidence per 1,000 person-years (95% CI)Model 1a
Model 2b
Model 3c
Hazard ratio (95% CI)P valueHazard ratio (95% CI)P valueHazard ratio (95% CI)P value
CVD incidence          
 FPG, mg/dL          
  <100 248,463 1,568 6.31 (6.00–6.63) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  100–125 156,344 1,086 6.94 (6.54–7.37) 0.98 (0.90–1.05) 0.53 0.90 (0.83–0.97) 0.009 0.87 (0.79–0.94) <0.001 
  ≥126 32,561 360 11.06 (9.94–12.26) 1.42 (1.27–1.59) <0.001 1.18 (1.05–1.33) 0.007 0.89 (0.75–1.06) 0.19 
 2h-PG, mg/dL          
  <140 282,942 1,598 5.65 (5.37–5.93) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  140–199 107,041 875 8.17 (7.64–8.73) 1.18 (1.08–1.28) 0.001 1.12 (1.03–1.22) 0.009 1.14 (1.05–1.25) 0.002 
  ≥200 47,384 541 11.42 (10.48–12.42) 1.49 (1.35–1.64) <0.001 1.31 (1.18–1.45) <0.001 1.30 (1.14–1.49) <0.001 
 HbA1c, %          
  <5.7 174,245 1,040 5.97 (5.61–6.34) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  5.7–6.4 218,596 1,496 6.84 (6.50–7.20) 0.92 (0.85–1.00) 0.05 0.93 (0.86–1.01) 0.09 0.93 (0.85–1.01) 0.09 
  ≥6.5 44,527 478 10.74 (9.79–11.74) 1.28 (1.15–1.43) <0.001 1.20 (1.07–1.34) 0.002 1.07 (0.92–1.24) 0.39 
Cancer incidence          
 FPG, mg/dL          
  <100 258,903 895 3.45 (3.23–3.69) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  100–125 165,591 580 3.50 (3.22–3.80) 0.93 (0.84–1.03) 0.17 0.96 (0.86–1.06) 0.40 0.92 (0.82–1.03) 0.13 
  ≥126 35,045 149 4.25 (3.60–4.99) 1.05 (0.88–1.25) 0.60 1.10 (0.92–1.32) 0.29 0.82 (0.64–1.05) 0.16 
 2h-PG, mg/dL          
  <140 293,722 919 3.13 (2.93–3.34) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  140–199 114,118 430 3.77 (3.42–4.14) 1.04 (0.93–1.17) 0.51 1.08 (0.96–1.21) 0.21 1.11 (0.99–1.26) 0.08 
  ≥200 51,699 275 5.32 (4.71–5.99) 1.35 (1.18–1.54) <0.001 1.44 (1.25–1.67) <0.001 1.62 (1.36–1.93) <0.001 
 HbA1c, %          
  <5.7 180,094 606 3.36 (3.10–3.64) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  5.7–6.4 230,654 806 3.49 (3.26–3.74) 0.89 (0.80–0.99) 0.03 0.92 (0.82–1.03) 0.13 0.90 (0.81–1.01) 0.08 
  ≥6.5 48,791 212 4.35 (3.78–4.97) 1.01 (0.86–1.18) 0.94 1.08 (0.92–1.28) 0.35 0.88 (0.72–1.09) 0.25 
All-cause mortality          
 FPG, mg/dL          
  <100 326,893 1,268 3.88 (3.67–4.10) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  100–125 207,835 855 4.11 (3.84–4.40) 0.91 (0.83–0.99) 0.03 0.95 (0.87–1.04) 0.26 0.90 (0.82–0.99) 0.04 
  ≥126 44,847 286 6.38 (5.66–7.16) 1.25 (1.10–1.42) 0.001 1.37 (1.20–1.57) <0.001 0.99 (0.83–1.20) 0.98 
 2h-PG, mg/dL          
  <140 368,432 1,243 3.37 (3.19–3.57) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  140–199 144,726 681 4.71 (4.36–5.07) 1.05 (0.95–1.15) 0.33 1.13 (1.02–1.24) 0.02 1.15 (1.04–1.27) 0.005 
  ≥200 66,416 485 7.30 (6.67–7.98) 1.41 (1.27–1.57) <0.001 1.57 (1.41–1.76) <0.001 1.58 (1.38–1.81) <0.001 
 HbA1c, %          
  <5.7 226,004 836 3.70 (3.45–3.96) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  5.7–6.4 290,789 1,197 4.11 (3.89–4.36) 0.87 (0.80–0.96) 0.003 0.99 (0.90–1.08) 0.78 0.97 (0.88–1.06) 0.47 
  ≥6.5 62,782 376 5.99 (5.40–6.63) 1.08 (0.95–1.22) 0.23 1.33 (1.17–1.52) <0.001 1.06 (0.89–1.26) 0.47 
Person-years, nEvents, nIncidence per 1,000 person-years (95% CI)Model 1a
Model 2b
Model 3c
Hazard ratio (95% CI)P valueHazard ratio (95% CI)P valueHazard ratio (95% CI)P value
CVD incidence          
 FPG, mg/dL          
  <100 248,463 1,568 6.31 (6.00–6.63) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  100–125 156,344 1,086 6.94 (6.54–7.37) 0.98 (0.90–1.05) 0.53 0.90 (0.83–0.97) 0.009 0.87 (0.79–0.94) <0.001 
  ≥126 32,561 360 11.06 (9.94–12.26) 1.42 (1.27–1.59) <0.001 1.18 (1.05–1.33) 0.007 0.89 (0.75–1.06) 0.19 
 2h-PG, mg/dL          
  <140 282,942 1,598 5.65 (5.37–5.93) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  140–199 107,041 875 8.17 (7.64–8.73) 1.18 (1.08–1.28) 0.001 1.12 (1.03–1.22) 0.009 1.14 (1.05–1.25) 0.002 
  ≥200 47,384 541 11.42 (10.48–12.42) 1.49 (1.35–1.64) <0.001 1.31 (1.18–1.45) <0.001 1.30 (1.14–1.49) <0.001 
 HbA1c, %          
  <5.7 174,245 1,040 5.97 (5.61–6.34) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  5.7–6.4 218,596 1,496 6.84 (6.50–7.20) 0.92 (0.85–1.00) 0.05 0.93 (0.86–1.01) 0.09 0.93 (0.85–1.01) 0.09 
  ≥6.5 44,527 478 10.74 (9.79–11.74) 1.28 (1.15–1.43) <0.001 1.20 (1.07–1.34) 0.002 1.07 (0.92–1.24) 0.39 
Cancer incidence          
 FPG, mg/dL          
  <100 258,903 895 3.45 (3.23–3.69) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  100–125 165,591 580 3.50 (3.22–3.80) 0.93 (0.84–1.03) 0.17 0.96 (0.86–1.06) 0.40 0.92 (0.82–1.03) 0.13 
  ≥126 35,045 149 4.25 (3.60–4.99) 1.05 (0.88–1.25) 0.60 1.10 (0.92–1.32) 0.29 0.82 (0.64–1.05) 0.16 
 2h-PG, mg/dL          
  <140 293,722 919 3.13 (2.93–3.34) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  140–199 114,118 430 3.77 (3.42–4.14) 1.04 (0.93–1.17) 0.51 1.08 (0.96–1.21) 0.21 1.11 (0.99–1.26) 0.08 
  ≥200 51,699 275 5.32 (4.71–5.99) 1.35 (1.18–1.54) <0.001 1.44 (1.25–1.67) <0.001 1.62 (1.36–1.93) <0.001 
 HbA1c, %          
  <5.7 180,094 606 3.36 (3.10–3.64) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  5.7–6.4 230,654 806 3.49 (3.26–3.74) 0.89 (0.80–0.99) 0.03 0.92 (0.82–1.03) 0.13 0.90 (0.81–1.01) 0.08 
  ≥6.5 48,791 212 4.35 (3.78–4.97) 1.01 (0.86–1.18) 0.94 1.08 (0.92–1.28) 0.35 0.88 (0.72–1.09) 0.25 
All-cause mortality          
 FPG, mg/dL          
  <100 326,893 1,268 3.88 (3.67–4.10) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  100–125 207,835 855 4.11 (3.84–4.40) 0.91 (0.83–0.99) 0.03 0.95 (0.87–1.04) 0.26 0.90 (0.82–0.99) 0.04 
  ≥126 44,847 286 6.38 (5.66–7.16) 1.25 (1.10–1.42) 0.001 1.37 (1.20–1.57) <0.001 0.99 (0.83–1.20) 0.98 
 2h-PG, mg/dL          
  <140 368,432 1,243 3.37 (3.19–3.57) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  140–199 144,726 681 4.71 (4.36–5.07) 1.05 (0.95–1.15) 0.33 1.13 (1.02–1.24) 0.02 1.15 (1.04–1.27) 0.005 
  ≥200 66,416 485 7.30 (6.67–7.98) 1.41 (1.27–1.57) <0.001 1.57 (1.41–1.76) <0.001 1.58 (1.38–1.81) <0.001 
 HbA1c, %          
  <5.7 226,004 836 3.70 (3.45–3.96) 1.00 (reference)  1.00 (reference)  1.00 (reference)  
  5.7–6.4 290,789 1,197 4.11 (3.89–4.36) 0.87 (0.80–0.96) 0.003 0.99 (0.90–1.08) 0.78 0.97 (0.88–1.06) 0.47 
  ≥6.5 62,782 376 5.99 (5.40–6.63) 1.08 (0.95–1.22) 0.23 1.33 (1.17–1.52) <0.001 1.06 (0.89–1.26) 0.47 

aModel 1 was adjusted for age and sex.

bModel 2 included model 1 variables plus BMI, family history of diabetes, cigarette smoking (current, former, and never smoker), alcohol consumption (current, former, and never), high school or higher education, moderate and vigorous physical activity, systolic blood pressure, HDL cholesterol, LDL cholesterol, and triglycerides.

cModel 3 included model 2 variables plus baseline 2h-PG and HbA1c (as spline terms) for the FPG category, model 2 variables plus baseline FPG and HbA1c (as spline terms) for the 2h-PG category, and model 2 variables plus baseline FPG and 2h-PG (as spline terms) for the HbA1c category.

We also performed stratified analyses according to age, sex, BMI, and smoking status (Supplementary Tables 13–16). We found that the risk estimates were generally similar for incident cancer and all-cause mortality across subgroups. For incident CVD, we observed significant differences in age (P = 0.01 for interaction) and BMI (P < 0.001 for interaction) across strata.

Predictive Values of Glycemic Measures

The C statistic (95% CI) of the predictive models of conventional risk factors was 0.652 (0.646–0.658) for incident diabetes. The addition of continuous glycemic measures to diabetes-predictive models significantly improved discrimination (Table 4). The C statistic, IDI, and NRI were significantly increased by adding FPG, 2h-PG, or HbA1c. The addition of two or three glycemic measures simultaneously further improved discrimination, especially for models including 2h-PG.

Table 4

Improvement in predicting diabetes, CVD, cancer, and all-cause mortality by adding FPG, 2h-PG, and HbA1c to conventional risk factorsa

Diabetes incidencec
CVD incidenced
Cancer incidenced
All-cause mortalityd
∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)
Adding a single glycemic measureb             
 FPG 0.043 (0.038–0.048) 2.208 (2.086–2.331) 37.694 (35.420–39.967) 0.001 (0.0005–0.002) 0.034 (0.015–0.054) 1.250 (−2.289 to 4.789) 0.000 (−0.001 to 0.002) 0.006 (0.0001–0.011) 1.778 (−2.983 to 6.593) 0.001 (0.0002–0.002) 0.051 (0.020–0.081) −0.892 (−4.951 to 3.168) 
 2h-PG 0.064 (0.058–0.070) 3.442 (3.288–3.596) 51.415 (49.171–53.658) 0.001 (0.0003–0.002) 0.044 (0.016–0.072) 20.322 (16.660–23.985) 0.002 (−0.001 to 0.004) 0.039 (0.022–0.055) 8.242 (3.780–12.703) 0.003 (0.002–0.005) 0.112 (0.056–0.169) 17.859 (13.885–21.833) 
 HbA1c 0.034 (0.029–0.038) 1.527 (1.439–1.615) 34.959 (32.709–37.209) 0.001 (0.0003–0.002) 0.024 (0.006–0.042) 1.300 (−2.389 to 4.988) 0.001 (−0.001 to 0.002) 0.007 (0.001–0.014) 1.322 (−3.640 to 6.285) 0.001 (0.0002–0.002) 0.034 (0.005–0.062) 5.571 (1.963–9.180) 
Adding two glycemic measuresb             
 FPG and 2h-PG 0.080 (0.074–0.086) 4.560 (4.373–4.746) 56.856 (54.633–59.080) 0.003 (0.002–0.005) 0.058 (0.030–0.085) −6.717 (−10.398 to 3.035) 0.003 (−0.001 to 0.006) 0.057 (0.036–0.079) −1.090 (−6.031 to 3.850) 0.004 (0.002–0.005) 0.151 (0.093–0.211) 15.308 (11.337–19.279) 
 FPG and HbA1c 0.058 (0.052–0.063) 3.131 (2.983–3.278) 46.620 (44.376–48.863) 0.002 (0.001–0.004) 0.047 (0.023–0.071) 2.620 (−0.968 to 6.208) 0.001 (−0.001 to 0.003) 0.012 (0.004–0.020) 3.853 (−1.037 to 8.744) 0.001 (0.0004–0.003) 0.065 (0.030–0.101) 2.813 (−1.230 to 6.854) 
 2h-PG and HbA1c 0.078 (0.072–0.083) 4.434 (4.254–4.614) 55.761 (53.538–57.985) 0.002 (0.001–0.003) 0.044 (0.019–0.069) −5.87 (−9.532, 2.213) 0.003 (−0.001 to 0.006) 0.049 (0.030–0.068) 3.10 (−1.842 to 8.047) 0.004 (0.002–0.005) 0.118 (0.061–0.175) 14.945 (10.981–18.908) 
Adding all three glycemic measuresb (FPG, 2h-PG, and HbA1c0.088 (0.082–0.094) 5.247 (5.043–5.450) 59.472 (57.260–61.683) 0.004 (0.002–0.005) 0.069 (0.039–0.098) 8.456 (4.7787–12.1339) 0.004 (−0.00002 to 0.007) 0.063 (0.041–0.0847) 8.223 (3.263–13.183) 0.004 (0.002–0.006) 0.155 (0.095–0.214) 11.594 (7.557–15.632) 
Diabetes incidencec
CVD incidenced
Cancer incidenced
All-cause mortalityd
∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)∆ C statistic (95% CI)IDI, % (95% CI)NRI, % (95% CI)
Adding a single glycemic measureb             
 FPG 0.043 (0.038–0.048) 2.208 (2.086–2.331) 37.694 (35.420–39.967) 0.001 (0.0005–0.002) 0.034 (0.015–0.054) 1.250 (−2.289 to 4.789) 0.000 (−0.001 to 0.002) 0.006 (0.0001–0.011) 1.778 (−2.983 to 6.593) 0.001 (0.0002–0.002) 0.051 (0.020–0.081) −0.892 (−4.951 to 3.168) 
 2h-PG 0.064 (0.058–0.070) 3.442 (3.288–3.596) 51.415 (49.171–53.658) 0.001 (0.0003–0.002) 0.044 (0.016–0.072) 20.322 (16.660–23.985) 0.002 (−0.001 to 0.004) 0.039 (0.022–0.055) 8.242 (3.780–12.703) 0.003 (0.002–0.005) 0.112 (0.056–0.169) 17.859 (13.885–21.833) 
 HbA1c 0.034 (0.029–0.038) 1.527 (1.439–1.615) 34.959 (32.709–37.209) 0.001 (0.0003–0.002) 0.024 (0.006–0.042) 1.300 (−2.389 to 4.988) 0.001 (−0.001 to 0.002) 0.007 (0.001–0.014) 1.322 (−3.640 to 6.285) 0.001 (0.0002–0.002) 0.034 (0.005–0.062) 5.571 (1.963–9.180) 
Adding two glycemic measuresb             
 FPG and 2h-PG 0.080 (0.074–0.086) 4.560 (4.373–4.746) 56.856 (54.633–59.080) 0.003 (0.002–0.005) 0.058 (0.030–0.085) −6.717 (−10.398 to 3.035) 0.003 (−0.001 to 0.006) 0.057 (0.036–0.079) −1.090 (−6.031 to 3.850) 0.004 (0.002–0.005) 0.151 (0.093–0.211) 15.308 (11.337–19.279) 
 FPG and HbA1c 0.058 (0.052–0.063) 3.131 (2.983–3.278) 46.620 (44.376–48.863) 0.002 (0.001–0.004) 0.047 (0.023–0.071) 2.620 (−0.968 to 6.208) 0.001 (−0.001 to 0.003) 0.012 (0.004–0.020) 3.853 (−1.037 to 8.744) 0.001 (0.0004–0.003) 0.065 (0.030–0.101) 2.813 (−1.230 to 6.854) 
 2h-PG and HbA1c 0.078 (0.072–0.083) 4.434 (4.254–4.614) 55.761 (53.538–57.985) 0.002 (0.001–0.003) 0.044 (0.019–0.069) −5.87 (−9.532, 2.213) 0.003 (−0.001 to 0.006) 0.049 (0.030–0.068) 3.10 (−1.842 to 8.047) 0.004 (0.002–0.005) 0.118 (0.061–0.175) 14.945 (10.981–18.908) 
Adding all three glycemic measuresb (FPG, 2h-PG, and HbA1c0.088 (0.082–0.094) 5.247 (5.043–5.450) 59.472 (57.260–61.683) 0.004 (0.002–0.005) 0.069 (0.039–0.098) 8.456 (4.7787–12.1339) 0.004 (−0.00002 to 0.007) 0.063 (0.041–0.0847) 8.223 (3.263–13.183) 0.004 (0.002–0.006) 0.155 (0.095–0.214) 11.594 (7.557–15.632) 

aConventional risk factors included age, sex, BMI, family history of diabetes, smoking, drinking, high school or higher education, moderate or vigorous physical activity, systolic blood pressure, LDL cholesterol, HDL cholesterol, and triglycerides.

bContinuous glycemic measures were included in the models of subsequent diabetes, and categorized glycemic measures—including FPG (<100, 100–125, and ≥126 mg/dL), 2h-PG (<140, 140–199, and ≥200 mg/dL), and HbA1c (<5.7, 5.7–6.4, and ≥6.5%)—were added in the models of subsequent CVD, subsequent cancer, and all-cause mortality.

cExcludes participants with diabetes at baseline.

dExcludes participants receiving antidiabetes treatment (oral hypoglycemic agents or insulin) at baseline.

The C statistic (95% CI) of the predictive models of conventional risk factors was 0.740 (0.732–0.749) for incident CVD, 0.657 (0.643–0.671) for cancer, and 0.792 (0.783–0.802) for all-cause mortality. The addition of categorized 2h-PG or a combination of 2h-PG and other glycemic measures slightly but significantly increased the C statistic, IDI, and NRI for predicting CVD (Table 4). Likewise, the addition of categorized 2h-PG significantly increased IDI and NRI for predicting cancer risk. Adding categorized 2h-PG or HbA1c slightly but significantly increased the C statistic, IDI, and NRI for predicting all-cause mortality. The addition of categorized 2h-PG improved discrimination most; also including FPG and HbA1c did not further improve the model. We observed similar predictive values of different glycemic measures among individuals without a history of diagnosed diabetes in a sensitivity analysis (Supplementary Table 17).

This large, population-based prospective study found that elevated FPG, 2h-PG, and HbA1c are significant predictive indicators of incident diabetes and its complications. 2h-PG remained significantly associated with the risk of diabetes, CVD, and cancer, and with all-cause mortality, in models including FPG and HbA1c. Furthermore, 2h-PG significantly improved the prediction of diabetes, CVD, and all-cause mortality over conventional risk factors. These findings have important clinical implications.

FPG, 2h-PG, and HbA1c have all been shown to be related to the risk of diabetes in epidemiological studies (2124). Our study, however, contributes new knowledge about the relative importance of individual measures and their combinations in predicting the risk of incident diabetes. Specifically, these findings indicate that 2h-PG or combinations of 2h-PG with other glycemic measures better predict risk than FPG, HbA1c, or their combination. The combination of three glycemic measures best predicts risk of diabetes.

Our study observed nonlinear associations of glycemic measures with CVD and all-cause mortality, which is consistent with findings from other observational studies (24,25). In the Emerging Risk Factors Collaboration (ERFC), which included data from 73 prospective studies involving 294,998 participants, nonlinear associations with CVD were reported for fasting glucose, postload glucose, and HbA1c (25). Prediabetes defined on the basis of fasting glucose, postload glucose, and HbA1c was associated with higher risk of CVD and all-cause mortality in prospective studies (5,6). In our study, only prediabetes defined by 2h-PG was significantly associated with increased risk of CVD and all-cause mortality. It has been reported that compared to FPG, the glucose tolerance test is more sensitive in identifying individuals who are at high risk for prediabetes and diabetes among Asian populations (2,26). Intriguingly, we also observed differences in the associations of the different glycemic measures across age and BMI strata. Further investigations are warranted in order to validate our findings and explore the detailed relationship and potential mechanisms.

Postload hyperglycemia differs from fasting hyperglycemia with regard to pathophysiology and the risk of diabetes-related clinical outcomes, and it mainly results from moderate to severe insulin resistance and from an impaired late-phase insulin secretory response to oral glucose. Our findings indicated that 2h-PG remained independently associated with risk of CVD and all-cause mortality in models with FPG and HbA1c, and it improved risk prediction more than did FBG or HbA1c. When using the same cutoffs, the ARIC study and ERFC reported that HbA1c better predicts risk for CVD (9,24,25). In those studies, however, not all three glycemic measures were obtained at the same visit. Methodological and study population differences notwithstanding, the reasons why our results do not agree with the ARIC study and ERFC findings are unclear. By contrast, several prospective studies—including the Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study, the Diabetes Epidemiology: Collaborative Analysis of Diagnostic Criteria in Europe (DECODE) Study, and the Framingham Offspring Study—reported that 2h-PG better predicted risk for CVD and mortality than did FPG or HbA1c (8,27,28).

Elevated blood glucose has been associated with an increased risk of cancer in several prospective studies (2931). In ∼1.3 million men and women in Korea, elevated fasting serum glucose levels and a diagnosis of diabetes were independent risk factors for cancer overall and for several prevalent cancers (29). In a pooled analysis of 274,126 men and 275,818 women from six European cohorts, fasting glucose was associated with an increased risk of cancer overall and at several sites (30). In 29,629 Japanese adults aged 46–80 years, elevated HbA1c was associated with overall cancer risk (31). In our study, 2h-PG, but not FPG or HbA1c, was associated with overall cancer.

The primary strengths of this study are its population-based design, its large sample size, and its ability to compare the risks of FPG, 2h-PG, and HbA1c as they relate to CVD, cancer, and all-cause mortality simultaneously. Although comparisons of the strength of the relationships between the glycemic variables and outcome must take into account their collinearity, the given analysis suggests that postload glucose may be a stronger predictor than the other two variables. Our study does have a number of important limitations. First, the study participants were only followed for a mean of 3.8 years. This relatively short follow-up duration reduced the number of clinical events and the study’s statistical power, especially for determining cancer incidence and all-cause mortality. However, we have counted 1,624 incident cancer cases and 2,409 total deaths. Second, the study participants only had one follow-up visit, and glycemic measures were obtained at only two time points (the baseline and follow-up visits). This could limit the accuracy of the timing of diagnoses, especially diabetes. The methods by which we collected data regarding clinical outcomes may also limit the sensitivity of ascertaining outcomes. Third, 12.2% of study participants were lost to follow-up. Rural-to-urban migration and urban redevelopment in China have contributed to this loss. In the diabetes analysis, 13.1% participants did not have an OGTT and an HbA1c test at follow-up and thus were excluded from the final analysis for incident diabetes. Fourth, anemia and hemoglobin might affect HbA1c measurement, but that was not measured in this study. Nevertheless, this study was conducted among the general population. In a sensitivity analysis, further adjustment for self-reported anemia did not change the study findings. Single measurements of FPG, 2h-PG, and HbA1c are subject to within-person variability. High variability in any of the measures could lead to imprecise associations and regression dilution bias of associations between glycemic measures and study outcomes (32). Fifth, microvascular complications, which are more specific complications of diabetes than cardiovascular events, cancer, or all-cause mortality, were not included as an outcome. Finally, the interpretations and conclusions of this study and others in the literature are fundamentally dependent on the approach used to model the three glycemic markers. In this study we used cutoffs established by 2010 ADA criteria for prediabetes and diabetes based on FPG, 2h-PG, and HbA1c to compare their associations with the outcomes. Although the risk estimates did not change significantly for CVD, cancer, and all-cause mortality based on the higher cutoffs of 6.1 mmol/L for impaired fasting glucose and 6.0% for elevated HbA1c, additional caution should be taken to balance the appropriate sensitivity and specificity of a glycemic marker.

In conclusion, our findings suggest that 2h-PG remains independently predictive of the outcomes in models including FPG and HbA1c. Therefore, in addition to FPG and HbA1c measurements, 2h-PG should be considered for routine testing in order to better assess the risks of diabetes, CVD, cancer, and all-cause mortality.

Acknowledgments. The authors thank all study participants.

Funding. The research reported in this publication was supported by the National Basic Research Program of China (973 Program) (award no. 2015CB553601); the Ministry of Science and Technology of the People’s Republic of China (award nos. 2016YFC1305600, 2016YFC1305202, 2016YFC0901200, 2016YFC1304904, 2017YFC1310700, and 2018YFC1311800); and the National Natural Science Foundation of China (award nos. 81700764, 81670795, 81621061, and 81561128019).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. J.L., J.H., G.N., W.W., and Y.B. conceived and designed the study. J.L., M.L., K.P., R.D., and D.C. analyzed data. X.T., R H., L.S., Q.S., X.Y., L.Y., Z.Z., G.Q., Q.W., G.C., Z.G., G.W., F.S., Z.L., Y.Q., Li C., Y.H., Q.L., Z.Y., Y.Z., C.L., Y.W., S.W., T.Y., H.D., Lu.C., J.Z., and Y.M. collected data. J.L., J.H., M.L., X.T., R.H., L.S., Q.S., K.P., M.X., Y.X., Y.C., X.Y., L.Y., T.W., Z.Z., G.Q., Q.W., G.C., M.D., D.Z., Z.G., G.W., F.S., Z.L., Y.Q., Li C., Y.H., Q.L., Z.Y., Y.Z., R.D., D.C., C.L., Y.W., S.W., T.Y., Z.L., H.D., D.L., S.L., Z.T.B., Lu.C., J.Z., Y.M., G.N., W.W., and Y.B. wrote and revised the manuscript and had final approval of the submitted and published versions. G.N., W.W., and Y.B. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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Supplementary data