Abstract
Trials of intensive glucose control have not improved cardiovascular disease (CVD) risk in populations with type 2 diabetes; however, in the general population, reports are inconsistent about the effects of maintaining lower glucose levels. Some speculate that low glycemic values are associated with increased glycemic variability, which is in turn associated with higher CVD risk. It has also been suggested that fasting glucose and hemoglobin A1c (HbA1c) in the lower ranges have a different relationship with CVD and mortality. In 4990 participants from the Multi-Ethnic Study of Atherosclerosis, we used logistic regression to investigate associations of low fasting glucose (<80 mg/dL) and HbA1c (<5.0%) from baseline and averaged across follow-up with incident CVD and mortality over 13 years. We used normal glycemic ranges (80 to <100 mg/dL and 5.0 to <5.7%) as references and analyzed glycemic levels with visit-matched covariates. We adjusted for potential confounding by age, sex, race/ethnicity, education, income, smoking status, body mass index, total cholesterol level, cholesterol medications, high-density lipoprotein cholesterol, and hypertension. Low baseline glucose and HbA1c were positively, but not significantly, associated with mortality, whereas low average fasting glucose and HbA1c were strongly and significantly associated with incident CVD [glucose OR, 2.04 (95% CI, 1.38-3.00); HbA1c OR, 2.01 (95% CI, 1.58-2.55)] and mortality [glucose OR, 1.93 (95% CI, 1.33-2.79); HbA1c OR, 2.51 (95% CI, 2.00-3.15)]. These results were not due to type 2 diabetes or medication use. Glucose variability did not explain CVD risk beyond average glucose levels. Chronic low fasting glucose and HbA1c may be better indicators of risk than a single low measurement.
Keywords: cardiovascular disease, epidemiology, fasting glucose, HbA1c, mortality
Once questioned as an intermediate condition, impaired fasting glucose (100 to <125 mg/dL) has now been shown to confer cardiovascular disease (CVD) risk even though it is below the diabetic range (≥126 mg/dL) [1]. Similarly, there is now evidence that low blood glucose levels [<80 mg/dL fasting or hemoglobin A1c (HbA1c) <5.0%] without reported clinical hypoglycemia may also indicate metabolic dysregulation and confer increased risk for CVD or mortality [2–10]. It remains unknown whether low glucose itself places some individuals at risk or whether low glucose is a marker for glycemic variability, which has consistently been associated with CVD events and mortality in those with type 2 diabetes [11–14]. Research on hypoglycemia has predominantly been focused on iatrogenic hypoglycemia resulting from glucose-lowering therapy in type 2 diabetes. The unexpected findings about the failure of intensive glucose control interventions in type 2 diabetes to prevent CVD events and the possibility that such interventions may even increase mortality have heightened the uncertainty around lower glucose values in individuals without type 2 diabetes as well [15]. Few studies have investigated the relationship of low fasting glucose or HbA1c with CVD outcomes in the general population [6, 16, 17]. Similarly, few have investigated whether glucose variability is associated with CVD outcomes beyond a single measurement [11, 12, 14, 18].
Increasing evidence supports the need to study CVD outcomes in the population of individuals who consistently have fasting and/or average glucose levels in the lower ranges [2, 3, 6, 7, 16, 17]. Thus, we sought to determine whether low fasting glucose (<80 mg/dL), low HbA1c (<5.0%), or glycemic variability (coefficient of variation) are associated with incident CVD and all-cause mortality in individuals without type 2 diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Following up on prior work in MESA on fasting glucose at baseline and CVD [19] and based on previous evidence of a J-shaped association [2, 3, 20–22], we hypothesized that low HbA1c would be similarly associated with all-cause mortality. Extending this work, our primary hypothesis was that glycemic levels averaged over follow-up would be stronger predictors of CVD and mortality than baseline measurements alone. We further hypothesized that higher glycemic variability would be associated with increased risk for CVD and all-cause mortality, independent of fasting glucose or HbA1c level. Finally, we hypothesized that these associations would differ by age, sex, and race/ethnicity. Our interest in heterogeneity is based on prior literature suggesting that the relationship between other risk factors, mainly obesity, and CVD is stronger in younger individuals [23], and the knowledge that the distribution of glucose is generally lower in women than in men [24, 25], and the likelihood of hypoglycemia higher [26].
1. Methods
A. Study Population
MESA includes 6809 participants without known CVD at baseline starting in 2000 with visits approximately every 2 years [27]. Participants from six sites around the United States were oversampled by four racial/ethnic groups and were aged 45 to 84 years at baseline. We excluded participants with type 1 diabetes (n = 10), resulting in a total of 6799 MESA participants for this analysis. Because HbA1c is measured at only two of the five study visits (visits 2 and 5), there were fewer participants available for analysis of HbA1c. After excluding eight participants who experienced a CVD event before visit 2 and 662 participants who did not return for these two visits or could not be followed for events, the analysis for HbA1c included 6129 participants.
Although the primary investigation of this study is of low glucose values, to investigate the shape of the relationships across the whole range of values while avoiding the known problems with hypoglycemia in those being treated for type 2 diabetes, we excluded measurements from the low, normal, and impaired ranges of glucose (20, 83, and 195 mg/dL, respectively) and HbA1c (6, 50, and 165%, respectively), separately, if participants had a diagnosis of type 2 diabetes. Cutpoints for fasting glucose and HbA1c categories are described in the following section. This resulted in 6501 participants with fasting glucose at baseline (916 low, 4074 normal, 937 impaired, and 574 with fasting glucose in the diabetic range) and 5908 participants with HbA1c at baseline (552 low, 3249 normal, 1416 impaired, and 691 with HbA1c in the diabetic range). For average glucose and average HbA1c, we similarly excluded observations from any visit with diagnosed type 2 diabetes from the low, normal, and impaired categories, and additionally excluded glycemic measurements that occurred after a CVD event. When calculating measures of variability, we also excluded measurements that occurred after a CVD event. All participants provided written informed consent and all MESA activities were approved by the institutional review boards from the participating institutions.
B. Measurement and Categorization of Glycemic Levels
Fasting glucose was measured at every visit using the glucose oxidase method and the Vitros analyzer (Johnson & Johnson Clinical Diagnostics, Rochester, NY). We categorized participants by fasting glucose level at baseline, averaged across follow-up, and variability across follow-up. Low fasting glucose was categorized as low (<80 mg/dL); normal (80 to <100 mg/dL); impaired (100 to <126 mg/dL); and diabetic (≥126 mg/dL). We chose this cut-point for low fasting glucose for consistency with prior research [4, 7, 28] and to avoid small numbers in the low group. We defined high fasting glucose variability as the highest quartile of glucose coefficient of variation across all fasting glucose measurements (from visits 1 through 5).
Similar to the approach for fasting glucose, we categorized participants by HbA1c level at baseline (visit 2), averaged across follow-up, and by variability across follow-up. HbA1c was categorized as low (<5.0%), normal (5 to <5.7%), impaired (5.7 to <6.5%), and diabetes (≥6.5%) based on the most common cutpoints used in prior research [2, 3, 20–22]. High HbA1c variability was defined as the highest quartile of HbA1c coefficient of variation across both HbA1c measurements (at visits 2 and 5).
C. Cardiovascular Events and All-Cause Mortality
MESA participants were followed for incident events of coronary artery disease, stroke, heart failure, combined CVD, and all-cause mortality through 2013. All events were adjudicated and median follow-up time was 12.2 years. A full description of follow-up and adjudication procedures for these events has been previously published [29]. A combined cardiovascular outcome was created and included coronary heart disease, stroke, heart failure, and CVD death. Events classified as hard clinical events included: myocardial infarction, resuscitated cardiac arrest, coronary heart disease death, stroke, and stroke death. The primary analysis includes all events, combining hard clinical events with definite or probable angina if followed by revascularization, other atherosclerotic death, and other CVD deaths.
D. Covariates
Age, sex, race/ethnicity, smoking status, education, and income were collected at the baseline interview by self-report. CVD risk factors were measured at the baseline clinic visit using a standardized protocol [27]. We defined high cholesterol as total cholesterol ≥200 mg/dL or use of lipid-lowering medications; low high-density lipoprotein (HDL) cholesterol as <50 mg/dL for women or <40 mg/dL for men; and hypertension as systolic blood pressure ≥140 mm Hg, or diastolic blood pressure ≥90 mm Hg, or use of blood pressure–lowering medications. Body mass index (BMI) was calculated as measured weight (in kilograms) divided by the square of the measured height (square meters).
E. Statistical Analysis
We described the study population by low and normal fasting glucose and HbA1c at baseline using t tests and χ2 tests for continuous and categorical variables respectively. We used Cox proportional hazards models to assess the association between HbA1c categories at baseline with incident CVD and all-cause mortality. We then used multivariable logistic regression models to determine the association of fasting glucose and HbA1c categories at baseline (visit 1 and visit 2, respectively) and averaged across follow-up with incident CVD and mortality, using the normal range (80 to <100 mg/dL and 5.0 to <5.7% for fasting glucose and HbA1c, respectively) as reference categories throughout the analysis. We chose logistic regression to account for the cumulative exposure across the study period and adjusted for covariates matched to the initial visit of glycemic data collection (visit 1 for fasting glucose and visit 2 for HbA1c). This approach is also accessible for use in a clinical context, making use of easily available summary measures when complex repeated measures analysis would infeasible. We adjusted these models for confounders in a series of nested models, including age, sex, race/ethnicity, socioeconomic status, and other CVD risk factors including high total cholesterol, low HDL cholesterol, BMI, and hypertension. We formally tested these associations for heterogeneity by age, sex, and race/ethnicity by including a multiplicative interaction term in the model. We conducted sensitivity analyses to assess whether the association with combined CVD was the same when using hard clinical CVD events compared with all CVD events and whether adjusting for glucose variability explained the results for average fasting glucose and HbA1c. We also assessed the most extreme scenario by comparing participants in the low glycemic categories at every visit to those who had normal levels at every visit. We investigated the robustness of results in specified subgroups. Finally, we evaluated the association between glycemic variability and CVD outcomes, using likelihood ratio tests to formally test whether variability improved the model fit.
2. Results
Unadjusted baseline characteristics of study participants are displayed in Table 1. MESA participants with low fasting glucose or HbA1c at baseline were younger, had higher education and income, and lower levels of CVD risk factors compared with those with normal glucose or HbA1c. Participants with average low fasting glucose and HbA1c had higher incident CVD [fasting glucose: low 11.86% (SD, 1.83) vs normal 9.80% (SD, 0.44); HbA1c: low 12.86% (SD, 1.13) vs normal 9.16% (SD, 0.51)] and mortality [fasting glucose: low 17.63% (SD, 2.16) vs normal 12.39% (SD, 0.49); HbA1c: low 26.96% (SD, 1.50) vs normal 10.96% (SD, 0.55)] compared with participants with average values in the normal range.
Table 1.
Mean (SD) Baseline Characteristics of 4990 MESA Participants Without Diabetes for Low and Normal Range Fasting Glucose and HbA1c
| Fasting Glucose | HbA1ca | |||||
|---|---|---|---|---|---|---|
| Model | Low (<80 mg/dL) | Normal (80 to <100 mg/dL) | P for Differencea | Low (<5.0%) | Normal (5.0 to <5.7%) | P for Differenceb |
| N | 916 | 4074 | 552 | 3249 | ||
| Fasting glucose, mg/dL | 75.8 (0.11) | 88.5 (0.08) | – | 85.3 (0.53) | 87.8 (0.19) | – |
| HbA1c, % | 5.23 (0.01) | 5.43 (0.01) | – | 4.73 (0.86) | 5.33 (0.32) | – |
| Age, y | 58.5 (0.34) | 62.0 (0.16) | <0.001 | 58.4 (0.43) | 61.2 (0.18) | <0.001 |
| Sex, % female | 69.4 (0.02) | 52.2 (0.01) | <0.001 | 49.3 (2.12) | 52.5 (0.87) | 0.19 |
| Race, % | ||||||
| White | 53.3 (1.65) | 41.1 (0.78) | 53.6 (2.11) | 48.0 (0.87) | ||
| Asian | 6.22 (0.80) | 12.3 (0.52) | <0.001 | 6.27 (1.03) | 12.1 (0.57) | <0.001 |
| African American | 23.9 (1.41) | 25.8 (0.69) | 23.5 (1.80) | 20.3 (0.70) | ||
| Hispanic | 16.6 (1.23) | 20.8 (0.64) | 16.7 (1.58) | 19.5 (0.69) | ||
| Education, % ≥high school | 89.6 (1.01) | 84.0 (0.58) | <0.001 | 88.5 (1.35) | 86.7 (0.59) | 0.20 |
| Income, % ≥$35,000 | 63.5 (1.59) | 55.1 (0.78) | <0.001 | 67.6 (1.98) | 59.9 (0.85) | <0.001 |
| Current smoking, % | 15.7 (1.20) | 12.6 (0.52) | 0.011 | 10.9 (1.32) | 11.0(0.54) | 0.92 |
| Total intentional exercise, METS | 1573 (67.5) | 1625 (38.8) | 0.56 | 1723 (97.3) | 1627 (39.8) | 0.42 |
| BMI, kg/m2 | 26.3 (0.15) | 27.9 (0.08) | <0.001 | 27.2 (0.20) | 27.4 (0.09) | 0.36 |
| High cholesterol, %c | 47.4 (1.65) | 53.0 (0.78) | 0.0026 | 43.7 (2.10) | 54.5 (0.870) | <0.001 |
| LDL cholesterol, mg/dL | 113.3 (1.04) | 118.9 (0.49) | <0.001 | 108.2 (1.330) | 115.4 (0.56) | <0.001 |
| HDL cholesterol, mg/dL | 57.2 (0.53) | 51.5 (0.23) | <0.001 | 54.5 (0.76) | 53.4 (0.27) | 0.15 |
| Triglycerides, mg/dL | 109.2 (2.11) | 126.4 (1.17) | <0.001 | 121.5 (2.99) | 125.4 (1.29) | 0.24 |
| Hypertension, % | 30.3 (1.52) | 41.0 (0.77) | <0.001 | 35.9 (2.04) | 38.8 (0.85) | 0.19 |
| Systolic BP, mm Hg | 119.5 (0.70) | 125.6 (0.33) | <0.001 | 121.8 (0.35) | 120.3 (0.85) | 0.11 |
| Kidney disease, % | 1.82 (0.13) | 2.22 (0.15) | 0.13 | 2.51 (0.16) | 1.76 (0.13) | 0.57 |
| Across follow-up | ||||||
| Cardiovascular disease, % | 8.52 (0.92) | 9.97 (0.47) | 0.21 | 8.15 (1.17) | 9.26 (0.51) | 0.40 |
| Mortality, % | 10.9 (1.03) | 12.4 (0.51) | 0.21 | 10.4 (0.54) | 10.5 (1.31) | 0.92 |
Abbreviations: BP, blood pressure; LDL, low-density lipoprotein; METS, metabolic equivalents.
Baseline for HbA1c is visit 2.
Based on t tests for continuous variables and χ2 tests for categorical variables.
High cholesterol >200 mg/dL or medication use.
There was little evidence from logistic regression that low fasting glucose or low HbA1c at baseline were significantly associated with CVD or all-cause mortality (Fig. 1). HbA1c in the impaired and diabetes ranges at baseline was significantly associated with increased risk for CVD and mortality after adjustment for age, sex, race/ethnicity, income, and education (Table 2). These estimates were attenuated by adjustment for other CVD risk factors (Fig. 1 and Table 2). Similar results for fasting glucose have been previously reported [19].
Figure 1.
Association of fasting glucose and HbA1c with cardiovascular disease and all-cause mortality (OR and 95% CI) in 6483 MESA participants. Fasting glucose categories: low (<80 mg/dL), normal (80 to <100 mg/dL), impaired (100 to <126 mg/dL), and diabetes (≥126 mg/dL). HbA1c categories: low (<5.0%), normal (5.0 to <5.7%), impaired (5.7 to <6.5%), and diabetes (≥6.5%). All measurements from participants with diagnosed type 2 diabetes have been removed from the low, normal, and impaired categories. All models adjusted for age, sex, race/ethnicity, education, income, smoking status, BMI, total cholesterol level and medication use, HDL cholesterol, and hypertension status.
Table 2.
Cox Proportional HRs and 95% CIs for CVD and All-Cause Mortality by Baseline HbA1c Category in 6775 MESA Participants
| Baseline HbA1c Categories | |||||
|---|---|---|---|---|---|
| Model | Events | Low (<5.0%) | Normal (5.0 to <5.7%) | Impaired (5.7 to <6.5%) | Diabetic (≥6.5%) |
| CVD | |||||
| 1 | 621 | 1.08 (0.79-1.49) | 1.00 (ref) | 1.30 (1.08-1.56) | 1.83 (1.46-2.28) |
| 2 | 620 | 1.04 (0.76-1.44) | 1.00 (ref) | 1.33 (1.10-1.61) | 1.82 (1.45-2.30) |
| 3 | 620 | 1.08 (0.79-1.49) | 1.00 (ref) | 1.21 (1.00-1.47) | 1.53 (1.21-1.95) |
| All-cause mortality | |||||
| 1 | 781 | 1.29 (0.98-1.71) | 1.00 (ref) | 1.26 (1.07-1.49) | 1.61 (1.32-1.97) |
| 2 | 779 | 1.21 (0.92-1.60) | 1.00 (ref) | 1.22 (1.03-1.45) | 1.55 (1.25-1.91) |
| 3 | 779 | 1.24 (0.94-1.63) | 1.00 (ref) | 1.21 (1.02-1.44) | 1.51 (1.22-1.88) |
Bold indicates where estimates are significantly different from the normal category at the P < 0.05 level. All HbA1c measurements from participants with diagnosed type 2 diabetes have been removed from the low, normal, and impaired categories. Model 1, adjusted for age; model 2, model 1 + sex, race, income, and education; model 3, model 2 + current smoking, BMI, total cholesterol and lipid medications, HDL cholesterol, and hypertension.
Abbreviation: HR, hazard ratio.
In contrast to baseline values, low average fasting glucose and low average HbA1c were strongly and significantly associated with CVD and mortality (Fig. 1). Estimates for impaired and diabetes categories were generally similar for average glycemic values compared with baseline. There appeared to be a J-shaped relationship of average fasting glucose and HbA1c with CVD and mortality. Despite slightly stronger low fasting glucose associations for women, white and Hispanics, nonsmokers, and participants older than 70, there was no significant heterogeneity by age, sex, or race/ethnicity; results were generally robust to other subgroup stratification (Table 3). Being in the low glycemic category at every visit (fasting glucose <80 mg/dL or HbA1c <5.0% at every visit) had similar results to having low average values (average fasting glucose <80 mg/dL or average HbA1c <5.0%) when compared with having normal values at every visit [fasting glucose and CVD OR = 1.45 (95% CI, 0.74-2.85); fasting glucose and mortality OR = 3.40 (95% CI, 1.93-6.02); HbA1c and CVD OR = 0.94 (95% CI, 0.58-1.52); HbA1c and mortality OR = 1.53 (95% CI, 1.04-2.24)] (data not shown).
Table 3.
Sensitivity Analyses for Low Average Fasting Glucose and HbA1c Compared With the Normal Category With CVD and All-Cause Mortality in MESA Participants Without Diabetes, Stratified by Selected Factors (OR and 95% CI)
| Average Fasting Glucose (<80 vs 80 to <100 mg/dL) | Average HbA1c (<5.0% vs 5.0 to <5.7%) | |||
|---|---|---|---|---|
| Subgroup | Cardiovascular Disease | All-Cause Mortality | Cardiovascular Disease | All-Cause Mortality |
| Primary analysis (n = 4544)a | 2.04 (1.38-3.00) | 1.93 (1.33-2.79) | 2.01 (1.58-2.55) | 2.51 (2.00-3.15) |
| Adjusted for variability (n = 4113)b | 1.85 (1.15-2.99) | 1.81 (1.15-2.86) | 3.09 (1.59-6.02) | 2.05 (0.93-4.53) |
| Hard CVD events only (n = 4544) | 2.23 (1.46-3.40) | – | 1.84 (1.41-2.41) | – |
| Sex | ||||
| Women (n = 2523) | 2.23 (1.37-3.64) | 2.21 (1.39-3.50) | 1.59 (1.10-2.32) | 2.44 (1.76-3.39) |
| Men (n = 2021) | 1.77 (0.93-3.39) | 1.73 (0.91-3.30) | 2.37 (1.74-3.24) | 2.64 (1.93-3.62) |
| P for difference | 0.67 | 0.75 | 0.18 | 0.80 |
| Age | ||||
| <70 y (n = 3374) | 1.47 (0.85-2.53) | 1.56 (0.93-2.61) | 2.26 (1.66-3.09) | 3.07 (2.25-4.19) |
| ≥70 y (n = 1170) | 2.57 (1.47-4.50) | 1.90 (1.14-3.18) | 1.96 (1.29-2.66) | 2.08 (1.52-2.84) |
| P for difference | 0.096 | 0.79 | 0.38 | 0.21 |
| Race/ethnicity | ||||
| White (n = 2001) | 2.06 (1.23-3.45) | 2.65 (1.61-4.36) | 2.39 (1.70-3.35) | 2.96 (2.11-4.17) |
| Asian (n = 528) | 2.46 (0.27-22.4) | 1.21 (0.13-11.4) | 6.96 (2.64-18.3) | 1.44 (0.66-3.12) |
| African American (n = 1152) | 1.66 (0.74-3.71) | 1.21 (0.60-2.45) | 1.78 (1.11-2.85) | 2.26 (1.50-3.40) |
| Hispanic (n = 863) | 2.94 (1.10-7.85) | 1.95 (0.67-5.63) | 1.13 (0.62-2.08) | 2.58 (1.45-4.59) |
| P for difference | 0.70 | 0.35 | 0.89 | 0.15 |
| Current smoking | ||||
| No (n = 3928) | 2.22 (1.45-3.39) | 1.94 (1.28-2.94) | 2.09 (1.60-2.72) | 2.62 (2.04-3.37) |
| Yes (n = 616) | 1.34 (0.51-3.53) | 2.11 (0.91-4.91) | 1.89 (1.07-3.35) | 2.08 (1.22-3.55) |
| P for difference | 0.33 | 0.87 | 0.76 | 0.44 |
| Cancer | ||||
| No (n = 4151) | 1.55 (1.01-2.40) | 1.85 (1.27-2.68) | 1.00 (0.67-1.50) | 1.86 (1.29-2.70) |
| Yes (n = 350) | 1.00 (0.26-3.80) | 1.38 (0.48-4.06) | 2.07 (0.79-5.42) | 2.15 (0.90-5.14) |
| P for difference | 0.56 | 0.62 | 0.18 | 0.76 |
| Hormone therapy usec | ||||
| No (n = 1478) | 1.52 (0.72-3.19) | 1.81 (0.99-3.31) | 0.74 (0.43-2.06) | 1.46 (0.77-2.77) |
| Yes (n = 768) | 2.64 (1.22-5.71) | 2.84 (1.30-6.21) | 0.56 (0.13-2.47) | 1.01 (0.33-3.14) |
| P for difference | 0.31 | 0.36 | 0.76 | 0.73 |
Bold for the subgroups indicates a significant difference from primary model results at P < 0.05 level.
Primary analysis is model 3 from Table 2. Paired subgroups are mutually exclusive. For example, the cancer analysis includes only participants with a diagnosis of cancer. Sample size differs by group with smaller sample sizes for HbA1c compared with fasting glucose and for additional exclusions.
P values from likelihood ratio tests for the inclusion of variability in the model with average glucose values were: fasting glucose and CVD, P = 0.17; HbA1c and CVD, P = 0.25; fasting glucose and mortality, P = 0.053; and HbA1c and mortality, P = 0.38.
Hormone therapy is for women only.
There was modest evidence of an association between the variability in fasting glucose and CVD or mortality in participants without type 2 diabetes (Table 4). HbA1c variability was significantly and monotonically associated with odds of CVD and mortality. There was little evidence that glycemic variability is independently associated with CVD or mortality once average glycemic levels were included in the model (Table 3; likelihood ratio tests for inclusion of variability in the model for fasting glucose and CVD, P = 0.17; fasting glucose and mortality, P = 0.053; HbA1c and CVD, P = 0.25; and average HbA1c and mortality, P = 0.38).
Table 4.
Association of Variation in Fasting Glucose and HbA1c With CVD and Mortality in MESA Participants Without Diabetes (OR and 95% CI)
| CVD | All-Cause Mortality | |||
|---|---|---|---|---|
| Variation | Adjusted for Average | Variation | Adjusted for Average | |
| Fasting glucose variability, mg/dLa | ||||
| Quartile 1 | 1.0 (ref) | 1.0 (ref) | 1.0 (ref) | 1.0 (ref) |
| Quartile 2 | 0.91 (0.72-1.17) | 0.93 (0.72-1.20) | 0.77 (0.61-0.98) | 0.79 (0.61-1.01) |
| Quartile 3 | 0.91 (0.71-1.16) | 0.87 (0.67-1.13) | 0.85 (0.67-1.08) | 0.87 (0.67-1.12) |
| Quartile 4 | 1.31 (1.04-1.65) | 0.97 (0.68-1.39) | 1.20 (0.95-1.51) | 1.12 (0.80-1.56) |
| P for linear trend | 0.022 | 0.48 | 0.096 | 0.50 |
| HbA1c variability, %b | ||||
| Quartile 1 | 1.0 (ref) | 1.0 (ref) | 1.0 (ref) | 1.0 (ref) |
| Quartile 2 | 1.07 (0.77-1.49) | 0.95 (0.66-1.38) | 0.89 (0.54-1.47) | 0.81 (0.45-1.45) |
| Quartile 3 | 1.28 (0.93-1.77) | 1.15 (0.80-1.65) | 1.20 (0.74-1.96) | 1.05 (0.59-1.87) |
| Quartile 4 | 1.63 (1.20-2.23) | 1.10 (0.73-1.67) | 1.65 (1.03-2.65) | 1.65 (0.89-3.04) |
| P for linear trend | 0.001 | 0.80 | 0.017 | 0.067 |
Bold indicates significance at the P < 0.05 level. All models are adjusted for age, sex, race/ethnicity, education, income, smoking, BMI, high total cholesterol, low HDL cholesterol, statin use, and hypertension.
Abbreviation: ref, reference.
Variability cutpoints for fasting glucose: quartile 1 (<4.579706), quartile 2 (4.579706 to <6.485385), quartile 3 (6.485385 to <9.60496), and quartile 4 (>9.60496).
Variability cutpoints for HbA1c: quartile 1 (<2.481076), quartile 2 (2.481076 to <4.04061), quartile 3 (4.04061 to <6.640249), and quartile 4 (>6.640249).
3. Discussion
Low fasting glucose and low HbA1c at baseline were not significantly associated with increased risk for CVD or mortality in MESA participants without diabetes. In contrast, low average fasting glucose and low average HbA1c levels across follow-up were strongly and significantly associated with higher odds of CVD and mortality. Although higher HbA1c variability was associated with CVD, HbA1c variability did not provide additional explanation of CVD risk beyond average HbA1c.
In assessing the associations of fasting glucose and HbA1c with CVD and mortality in individuals without diabetes, prior studies found that the shape of the relationships was inconsistent and varied from linear [4, 20, 22, 28, 30, 31], mildly but not significantly J-shaped [21], or fully J-shaped even after adjustment [2–4, 6, 7, 11], with stronger associations between low HbA1c and mortality [2, 3, 20–22]. Potential mechanisms for this J-shaped association remain speculative, although suggestions that these results are due to bias have not been supported by the literature. The association between fasting glucose and CVD has been reported before in MESA with no substantial increase in risk from impaired fasting glucose compared with the normal range after adjustment [19]. Our results follow and support that work showing similar results for impaired HbA1c and adding a focus on the lower range. Our results align with the findings and summarization of the literature in The Emerging Risk Factor Collaboration meta-analysis, which reported a weak J-shaped association between baseline fasting glucose and coronary heart disease in those without type 2 diabetes, with a more pronounced J-shape for average fasting glucose [4]. Contrary to the idea that associations would be stronger for HbA1c because of its known advantages measuring glucose exposure across a longer time frame (reflecting ∼3 months of average daily glucose concentration), we found similar results for fasting glucose and HbA1c using either baseline or average values. This suggests that a single measurement of even HbA1c may not sufficiently classify those with low average glucose for CVD risk stratification, and that CVD risk is impacted more by chronic (>3 months) patterns of low glucose.
Glucose variability is increasingly considered to be a risk factor for CVD independent of hyperglycemia [32]. Our results are generally consistent with prior research, showing that glycemic variability is associated with CVD and mortality [11–14], although our results for mortality were weaker. Bouchi et al. and Takao et al. showed that HbA1c variability is associated with incident CVD, independent of mean HbA1c in those with type 2 diabetes [11, 13]. In contrast, in those without type 2 diabetes, we found that variability is not an independent determinant of CVD once average fasting glucose or HbA1c are accounted for. Our result is consistent with findings from Borg et al. in the premise that excursions into the lower glucose range may be a marker for high glycemic variability [33]. It is also possible that the CVD association of variability independent of mean value may hold only for those with type 2 diabetes or taking glucose-lowering medication. More generally, our results and those of Bouchi et al. support the need for measurement of glycemic markers at multiple time points. Coutinho et al. specify in their analysis that a single measurement of fasting glucose may lead to underestimates of the association between glucose levels and CVD [32]. Although additional measurements generally increase precision and should thus improve the performance of the average over a single measurement, it is rare that such improvement leads to a different inference. Our results support the notion that a single measurement of fasting glucose or even HbA1c is not representative of chronic exposure to hypoglycemia; however, what this means for clinical care remains uncertain.
The primary limitation of this study is that HbA1c was only measured at two time points in MESA, limiting investigation of average HbA1c and HbA1c variability; however, even a single additional measurement changed the inference for low HbA1c. Similarly, HbA1c measurement began at visit 2, limiting the follow-up time for analysis of HbA1c with events and restricting comparability with fasting glucose measurement at baseline. The small number of participants in the low fasting glucose category precludes investigation of further stratification in this range; however, even if risk increases toward the extreme values the inclusion of fasting glucose from 70 to 80 mg/dL would likely bias our estimates toward a null result. We could not rule out all known causes of nondiabetic hypoglycemia, but doubt that excluding these rare conditions would change our results. Some differential loss to follow-up is possible, but would also likely bias our results toward the null. Last, availability of information on potential sources of error in measuring HbA1c, such as hemoglobinopathy, anemia, and hemolytic disorders, is limited and residual confounding remains a possibility.
Strengths of this study include our ability to do a more comprehensive investigation into the relationship of glycemia with CVD risk and mortality, and this study adds multiple elements to the current literature. First, by including both CVD and mortality end points, we assessed whether the etiology of glycemia in the lower range differs for CVD and mortality. Second, by using MESA, we could investigate whether these associations differ by age, sex, and race/ethnicity. Third, we investigated whether the relationship with CVD and mortality differed between fasting glucose and HbA1c in the same population in an attempt to reconcile discrepancies in the literature. Finally, we used the approach of including average low fasting glucose, average low HbA1c, and glycemic variability in our investigation of the relationship between glycemia and cardiovascular risk.
In conclusion, low fasting glucose and HbA1c averages were more strongly associated with CVD and all-cause mortality than a single measurement of low glycemia at baseline. Higher HbA1c variability was also significantly associated with incident CVD, but variability did not explain the association for low average HbA1c. In individuals without type 2 diabetes, chronic glycemia lower than the normal range may be a better indicator of risk than a single low glycemic measurement, but more information is needed about the mechanisms connecting low fasting glucose and HbA1c with outcomes.
Acknowledgments
The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at www.mesa-nhlbi.org. The information contained here was derived in part from data provided by the Bureau of Vital Statistics, New York City Department of Health and Mental Hygiene.
Financial Support: This research was supported by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169 from the National Institutes of Health National Heart, Lung, and Blood Institute and by grants UL1-TR-000040 and UL1-TR-001079 from the National Center for Research Resources.
Current Affiliation: D. D. Sears’s current affiliation is the College of Health Solutions, Arizona State University, Phoenix, Arizona 85004.
Disclosure Summary: The authors have nothing to disclose.
Glossary
Abbreviations:
- BMI
body mass index
- CVD
cardiovascular disease
- HbA1c
hemoglobin A1c
- HDL
high-density lipoprotein
References and Notes
- 1. Huang Y, Cai X, Mai W, Li M, Hu Y. Association between prediabetes and risk of cardiovascular disease and all cause mortality: systematic review and meta-analysis. BMJ. 2016;355:i5953. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Aggarwal V, Schneider AL, Selvin E. Low hemoglobin A(1c) in nondiabetic adults: an elevated risk state? Diabetes Care. 2012;35(10):2055–2060. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Carson AP, Fox CS, McGuire DK, Levitan EB, Laclaustra M, Mann DM, Muntner P. Low hemoglobin A1c and risk of all-cause mortality among US adults without diabetes. Circ Cardiovasc Qual Outcomes. 2010;3(6):661–667. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J; Emerging Risk Factors Collaboration. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies [published correction appears in Lancet. 2010;376(9745):958]. Lancet. 2010;375(9733):2215–2222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Arnold LW, Wang Z. The HbA1c and all-cause mortality relationship in patients with type 2 diabetes is J-shaped: a meta-analysis of observational studies. Rev Diabet Stud. 2014;11(2):138–152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Park C, Guallar E, Linton JA, Lee D-C, Jang Y, Son DK, Han E-J, Baek SJ, Yun YD, Jee SH, Samet JM. Fasting glucose level and the risk of incident atherosclerotic cardiovascular diseases. Diabetes Care. 2013;36(7):1988–1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Wei M, Gibbons LW, Mitchell TL, Kampert JB, Stern MP, Blair SN. Low fasting plasma glucose level as a predictor of cardiovascular disease and all-cause mortality. Circulation. 2000;101(17):2047–2052. [DOI] [PubMed] [Google Scholar]
- 8. Currie CJ, Peters JR, Tynan A, Evans M, Heine RJ, Bracco OL, Zagar T, Poole CD. Survival as a function of HbA(1c) in people with type 2 diabetes: a retrospective cohort study. Lancet. 2010;375(9713):481–489. [DOI] [PubMed] [Google Scholar]
- 9. Huang ES, Liu JY, Moffet HH, John PM, Karter AJ. Glycemic control, complications, and death in older diabetic patients: the diabetes and aging study. Diabetes Care. 2011;34(6):1329–1336. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Nicholas J, Charlton J, Dregan A, Gulliford MC. Recent HbA1c values and mortality risk in type 2 diabetes. population-based case-control study. PLoS One. 2013;8(7):e68008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Bouchi R, Babazono T, Mugishima M, Yoshida N, Nyumura I, Toya K, Hayashi T, Hanai K, Tanaka N, Ishii A, Iwamoto Y. Fluctuations in HbA1c are associated with a higher incidence of cardiovascular disease in Japanese patients with type 2 diabetes. J Diabetes Investig. 2012;3(2):148–155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Parry HM, Deshmukh H, Levin D, Van Zuydam N, Elder DH, Morris AD, Struthers AD, Palmer CN, Doney AS, Lang CC. Both high and low HbA1c predict incident heart failure in type 2 diabetes mellitus. Circ Heart Fail. 2015;8(2):236–242. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Takao T, Matsuyama Y, Yanagisawa H, Kikuchi M, Kawazu S. Association between HbA1c variability and mortality in patients with type 2 diabetes. J Diabetes Complications. 2014;28(4):494–499. [DOI] [PubMed] [Google Scholar]
- 14. Lin CC, Li CI, Yang SY, Liu CS, Chen CC, Fuh MM, Chen W, Li TC. Variation of fasting plasma glucose: a predictor of mortality in patients with type 2 diabetes. Am J Med. 2012;125(4):416.e9–18. [DOI] [PubMed] [Google Scholar]
- 15. Gerstein HC, Miller ME, Byington RP, Goff DC Jr, Bigger JT, Buse JB, Cushman WC, Genuth S, Ismail-Beigi F, Grimm RH Jr, Probstfield JL, Simons-Morton DG, Friedewald WT; Action to Control Cardiovascular Risk in Diabetes Study Group. Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med. 2008;358(24):2545–2559. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Tanne D, Koren-Morag N, Goldbourt U. Fasting plasma glucose and risk of incident ischemic stroke or transient ischemic attacks: a prospective cohort study. Stroke. 2004;35(10):2351–2355. [DOI] [PubMed] [Google Scholar]
- 17. Preiss D, Welsh P, Murray HM, Shepherd J, Packard C, Macfarlane P, Cobbe S, Ford I, Sattar N. Fasting plasma glucose in non-diabetic participants and the risk for incident cardiovascular events, diabetes, and mortality: results from WOSCOPS 15-year follow-up. Eur Heart J. 2010;31(10):1230–1236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Cavalot F. Do data in the literature indicate that glycaemic variability is a clinical problem? Glycaemic variability and vascular complications of diabetes. Diabetes Obes Metab. 2013;15(Suppl 2):3–8. [DOI] [PubMed] [Google Scholar]
- 19. Yeboah J, Bertoni AG, Herrington DM, Post WS, Burke GL. Impaired fasting glucose and the risk of incident diabetes mellitus and cardiovascular events in an adult population: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2011;58(2):140–146. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Schöttker B, Rathmann W, Herder C, Thorand B, Wilsgaard T, Njølstad I, Siganos G, Mathiesen EB, Saum KU, Peasey A, Feskens E, Boffetta P, Trichopoulou A, Kuulasmaa K, Kee F, Brenner H. HbA1c levels in non-diabetic older adults – no J-shaped associations with primary cardiovascular events, cardiovascular and all-cause mortality after adjustment for confounders in a meta-analysis of individual participant data from six cohort studies. BMC Med; 2016:14:26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Brewer N, Wright CS, Travier N, Cunningham CW, Hornell J, Pearce N, Jeffreys M. A New Zealand linkage study examining the associations between A1C concentration and mortality. Diabetes Care. 2008;31(6):1144–1149. [DOI] [PubMed] [Google Scholar]
- 22. Selvin E, Steffes MW, Zhu H, Matsushita K, Wagenknecht L, Pankow J, Coresh J, Brancati FL. Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med. 2010;362(9):800–811. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Di Angelantonio E, Bhupathiraju ShN, Wormser D, Gao P, Kaptoge S, Berrington de Gonzalez A, Cairns BJ, Huxley R, Jackson ChL, Joshy G, Lewington S, Manson JE, Murphy N, Patel AV, Samet JM, Woodward M, Zheng W, Zhou M, Bansal N, Barricarte A, Carter B, Cerhan JR, Smith GD, Fang X, Franco OH, Green J, Halsey J, Hildebrand JS, Jung KJ, Korda RJ, McLerran DF, Moore SC, O’Keeffe LM, Paige E, Ramond A, Reeves GK, Rolland B, Sacerdote C, Sattar N, Sofianopoulou E, Stevens J, Thun M, Ueshima H, Yang L, Yun YD, Willeit P, Banks E, Beral V, Chen Zh, Gapstur SM, Gunter MJ, Hartge P, Jee SH, Lam TH, Peto R, Potter JD, Willett WC, Thompson SG, Danesh J, Hu FB; Global BMI Mortality Collaboration. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 2016;388(10046):776–786. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Huang W, Xu W, Zhu P, Yang H, Su L, Tang H, Liu Y. Analysis of blood glucose distribution characteristics in a health examination population in Chengdu (2007-2015). Medicine (Baltimore). 2017;96(49):e8765. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Faerch K, Borch-Johnsen K, Vaag A, Jørgensen T, Witte DR. Sex differences in glucose levels: a consequence of physiology or methodological convenience? The Inter99 study. Diabetologia. 2010;53(5):858–865. [DOI] [PubMed] [Google Scholar]
- 26. Kautzky-Willer A, Kosi L, Lin J, Mihaljevic R. Gender-based differences in glycaemic control and hypoglycaemia prevalence in patients with type 2 diabetes: results from patient-level pooled data of six randomized controlled trials. Diabetes Obes Metab. 2015;17(6):533–540. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, Greenland P, Jacob DR Jr, Kronmal R, Liu K, Nelson JC, O’Leary D, Saad MF, Shea S, Szklo M, Tracy RP. Multi-Ethnic Study of Atherosclerosis: objectives and design. Am J Epidemiol. 2002;156(9):871–881. [DOI] [PubMed] [Google Scholar]
- 28. Mongraw-Chaffin M, LaCroix AZ, Sears DD, Garcia L, Phillips LS, Salmoirago-Blotcher E, Zaslavsky O, Anderson CAM. A prospective study of low fasting glucose with cardiovascular disease events and all-cause mortality: the Women’s Health Initiative. Metabolism. 2017;70:116–124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Multi-Ethnic Study of Atherosclerosis Coordinating Center. Multi-Ethnic Study of Atherosclerosis Manual of Operations, 2017. Version 3-20-2017.www.mesa-nhlbi.org/PublicDocs/MesaMOO/MESA%20Clinical%20Events%20MOP%20(6.22.18).pdf. Accessed 2 November 2016.
- 30. Khaw K-T, Wareham N, Bingham S, Luben R, Welch A, Day N. Association of hemoglobin A1c with cardiovascular disease and mortality in adults: the European prospective investigation into cancer in Norfolk. Ann Intern Med. 2004;141(6):413–420. [DOI] [PubMed] [Google Scholar]
- 31. Levitan EB, Liu S, Stampfer MJ, Cook NR, Rexrode KM, Ridker PM, Buring JE, Manson JE. HbA1c measured in stored erythrocytes and mortality rate among middle-aged and older women. Diabetologia. 2008;51(2):267–275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Coutinho M, Gerstein HC, Wang Y, Yusuf S. The relationship between glucose and incident cardiovascular events. A metaregression analysis of published data from 20 studies of 95,783 individuals followed for 12.4 years. Diabetes Care. 1999;22(2):233–240. [DOI] [PubMed] [Google Scholar]
- 33. Borg R, Kuenen JC, Carstensen B, Zheng H, Nathan DM, Heine RJ, Nerup J, Borch-Johnsen K, Witte DR; ADAG Study Group. Real-life glycaemic profiles in non-diabetic individuals with low fasting glucose and normal HbA1c: the A1C-Derived Average Glucose (ADAG) study. Diabetologia. 2010;53(8):1608–1611. [DOI] [PMC free article] [PubMed] [Google Scholar]

