Abstract
Context
Cardiovascular disease (CVD) is a major cause of mortality in adults with type 1 diabetes.
Objective
We prospectively evaluated CVD risk factors in a large, contemporary cohort of adults with type 1 diabetes living in the United States.
Design
Observational study of CVD and CVD risk factors over a median of 5.3 years.
Setting
The T1D Exchange clinic network.
Patients
Adults (age ≥ 18 years) with type 1 diabetes and without known CVD diagnosed before or at enrollment.
Main Outcome Measure
Associations between CVD risk factors and incident CVD were assessed by multivariable logistic regression.
Results
The study included 8,727 participants (53% female, 88% non-Hispanic white, median age 33 years [interquartile ratio {IQR} = 21, 48], type 1 diabetes duration 16 years [IQR = 9, 26]). At enrollment, median HbA1c was 7.6% (66 mmol/mol) (IQR = 6.9 [52], 8.6 [70]), 33% used a statin, and 37% used blood pressure medication. Over a mean follow-up of 4.6 years, 325 (3.7%) participants developed incident CVD. Ischemic heart disease was the most common CVD event. Increasing age, body mass index, HbA1c, presence of hypertension and dyslipidemia, increasing duration of diabetes, and diabetic nephropathy were associated with increased risk for CVD. There were no significant gender differences in CVD risk.
Conclusion
HbA1c, hypertension, dyslipidemia and diabetic nephropathy are important risk factors for CVD in adults with type 1 diabetes. A longer follow-up is likely required to assess the impact of other traditional CVD risk factors on incident CVD in the current era.
Despite advances in diabetes care and increased life expectancy, adults with type 1 diabetes (T1D) have a 10-fold increase in cardiovascular disease (CVD) risk in addition to earlier onset of CVD and a two- to fourfold increased death rate attributed to CVD compared with the general population (1–3).
The Diabetes Control and Complications Trial (DCCT), the Epidemiology of Diabetes Interventions and Complications (EDIC), and the Pittsburgh Epidemiology of Diabetes Complications (EDC) have contributed much to the current understanding of CVD risk in T1D (1,4–7). Glycemic control, diabetes duration, and traditional CVD risk factors have been associated with CVD risk in T1D (4,8,9). Intensive diabetes management focused on improved long-term glycemic control reduced the incidence of CVD by 30% (4,5,7). In addition, studies have consistently reported nephropathy as an independent CVD risk factor in adults with T1D (10–12). Population-based studies using national registries from the United Kingdom and Sweden demonstrated similar findings to the DCCT/EDIC and EDC studies (3,13,14).
Over the past decade, there has been remarkable improvement in diabetes care, increased adoption of advanced diabetes technologies such as insulin pumps and continuous glucose monitors (15), and greater use of angiotensin-converting enzyme inhibitors and statins. The impact of these advances in T1D care on CVD outcomes warrants further investigation. We evaluated the incidence and factors associated with CVD in adults with T1D participating in the T1D Exchange Clinic Network Registry, the largest registry of adults with T1D in the United States.
Materials and Methods
The T1D Exchange Clinic Network Registry enrolled 25 833 persons with T1D from 67 US-based pediatric and adult endocrinology practices between September 2010 and August 2012 (16).
Eligible participants were aged ≥ 18 years with diabetes duration > 1 year, had no history of a CVD event or cerebrovascular disease before enrollment into the registry, and had at least 1 year of follow-up data. Informed consent was obtained according to institutional review board requirements from participants.
Baseline and annual data were collected by participant-reported questionnaires and medical chart data extraction using standardized electronic data collection forms (16). Demographic data, including education level, annual household income, insurance status, and tobacco use, were collected through participant questionnaires. Data regarding anthropometrics, medical history, diabetes management, medication use, and laboratory data were obtained from medical records.
Participants were followed for a median of 5.3 years (interquartile ratio [IQR] = 2.9, 6.1) (minimum of 29 days and maximum of 8.8 years). Incident CVD was defined as medical record documentation of coronary ischemic heart disease, cerebrovascular disease, or congestive heart failure during their registry follow-up period.
The values for HbA1c used in the models were obtained at enrollment in the registry. HbA1c variability was calculated as the standard deviation of all HbA1c measurements taken in the 12 months leading up to registry enrollment, including the measurement taken at the enrollment visit. The median number of HbA1c values per participant was 3 (IQR = 2, 4). For those with only 1 HbA1c value the SD of HbA1c was set equal to missing.
Measurements for low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), triglycerides, and blood pressure were taken from medical records from the participants registry enrollment visit. A participant’s atherogenic index (triglyceride [TG]/HDL) was calculated by dividing their TG level (mg/dL) by their HDL-C (mg/dL) (17). A value > 2 has been shown to be related to CVD; therefore, 2 was used as a cutoff point to create a binary variable (18).
Estimated glomerular filtration rate (eGFR) was calculated using the serum creatinine level and Chronic Kidney Disease Epidemiology Collaboration equation (19). Diabetic nephropathy was defined as having either microalbuminuria, macroalbuminuria, or an eGFR < 60 mL/min/1.73 m2. Microalbuminuria was defined as a random urine albumin-creatinine ratio between 30 and 300 mg/g for either 2 consecutive clinic visits or at least 2 of 3 consecutive visits (20). Macroalbuminuria was defined as a random urine albumin-creatinine ratio > 300 mg/g for 2 consecutive clinic visits or at least 2 of 3 consecutive visits (20). Diagnosis of hypertension, dyslipidemia, and diabetic neuropathy (peripheral and autonomic) were based on medical diagnosis documented at enrollment in the registry.
Statistical Methods
Multivariable logistic regression models assessed the association between incident CVD and demographic, clinical, and diabetes-specific characteristics. Odds ratios and 95% confidence intervals are reported from the models. The atherogenic index (TG/HDL) was log-transformed because of skewness before being included in the models. Since a TG/HDL ratio > 2 has been shown to be associated with increased CVD risk, a log TG/HDL > 0.3 defined an elevated level.
Potential confounders were assessed through bivariate analysis and stepwise logistic regression models. Because of missing data, lipid-based variables were not included in the full multivariate model. Instead, each lipid measure was assessed in separate logistic models, which included factors found to be significant in the original multivariate model. Age, T1D duration, registry follow-up period, insurance status, and education were determined to be confounding factors and were adjusted for in the final models.
Sensitivity analysis were conducted to evaluate the effect of age and statin medication use on the association between diabetes-specific risk factors and CVD. Age groups were created based on the 25th, 50th, and 75th age percentiles among those with incident CVD. Logistic regression models stratified by age group and statin use were used to obtain odds ratios. To adjust for multiple comparisons, an alpha of 0.01 was used as a threshold for statistical significance. Analyses were performed using SAS v9.4 (Cary, NC).
Results
A total of 8,727 participants with established diabetes of 1 year or greater were eligible. Table 1 summarizes the baseline characteristics of the cohort. Participants (53% female) had a median age of 33 years (IQR = 21, 48) with median duration of 16 years (IQR = 9, 26). A majority of participants were non-Hispanic white (88%), 45% had at least a bachelor’s degree, and 56% were either overweight or obese. Insulin pumps and continuous glucose monitors were used by 57% and 18% of participants, respectively. Median HbA1c was 7.6% (60 mmol/mol) (IQR = 6.9% [52 mmol/mol], 8.6% [70 mmol/mol]). Among the 1343 women with menopausal status available, 755 (56%) were in menopause.
Table 1.
Baseline Characteristics
| N | 8,727 |
|---|---|
| Demographics | |
| Age, median [IQR] | 33 [21, 48] |
| Age group, n (%) | |
| <20 | 1399 (16) |
| 20–<35 | 3167 (36) |
| 35–<50 | 2223 (25) |
| 50–<65 | 1541 (18) |
| ≥65 | 397 (5) |
| Female, n (%) | 4624 (53) |
| Non-Hispanic white, n (%) | 7702 (88) |
| Education ≥ college degree, n (%) | 3717 (45) |
| Income ≥ $75 000, n (%) | 3297 (52) |
| Private insurance, n (%) | 6246 (81) |
| Clinical Characteristics | |
| Overweight/obese, n (%) | 3900 (56) |
| Tobacco use, n (%) | 799 (10) |
| Hypertension, n (%) | 2377 (27) |
| Antihypertensive medication use, n (%) | 3228 (37) |
| Dyslipidemia, n (%) | 2798 (32) |
| Statin use, n (%) | 2921 (33) |
| Diabetes Characteristics | |
| T1D duration (y), median [IQR] | 16 [9, 26] |
| Insulin pump use, n (%) | 4991 (57) |
| CGM use n (%) | 1533 (18) |
| HbA1c, median [IQR] | 7.6 [6.9, 8.6] |
| Longitudinal HbA1c SDa, median [IQR] | 0.4 [0.2, 0.6] |
| Nephropathy, n (%) | 1052 (12) |
CGM, continuous glucose monitoring system; IQR, interquartile range; T1D, type 1 diabetes.
aSD of HbA1c values taken during registry enrollment.
Study participants who developed CVD were followed for a median period of 5.7 years (IQR = 5.0, 6.2) compared with 5.3 years (IQR = 2.8, 6.1) for participants who did not develop CVD. There were 139 confirmed deaths during follow-up. The incidence proportion of CVD was 3.7% (325/8727). Among those diagnosed with CVD, 88% had ischemic heart disease, 9.9% had cerebrovascular disease, and 10.8% had congestive heart failure. Three percent of participants experienced both ischemic heart disease and cerebrovascular disease, 6% experienced both ischemic heart disease and congestive heart failure, 0.9% experienced both cerebrovascular disease and congestive heart failure, and 0.7% experienced all 3 conditions.
Comparison of traditional and diabetes-specific cardiovascular risk factors between adults with T1D who developed incident CVD and adults with T1D without CVD is provided in Table 2 and association between these risk factors and incident CVD is presented in Fig. 1. Compared with those without CVD, participants with incident CVD were more likely to be older (median 53 years [IQR = 42, 62] vs. and 32 years [IQR = 21, 47]; P < .001), obese or overweight (72% vs. 56%; P = .05), diagnosed with hypertension (64% vs. 26%; P < .001), diagnosed with dyslipidemia (58% vs. 31%; P = .03), and have a higher atherogenic index (P < .001) (Table 2) adjusting for age, education, insurance status, duration of T1D, and length of enrollment in the registry. Baseline systolic blood pressure was not significantly higher among those with incident CVD compared with those with no diagnosis of CVD (mean ± SD = 126 ± 17 vs. 121 ± 14 mm Hg; P = .16). There was no association between baseline diastolic blood pressure and incident CVD (P = .83) (Table 2).
Table 2.
Comparison of Participants Developing and Not Developing Incident CVD
| CVD n = 325 | Non-CVD n = 8,402 | |
|---|---|---|
| Baseline Traditional Risk Factors | ||
| Sex (female), n (%) | 186 (57) | 4438 (53) |
| Race (non-Hispanic white), n (%) | 299 (92) | 7403 (88) |
| Obese/overweight, n (%) | 163 (72) | 3737 (56) |
| Tobacco use, n (%) | 33 (10) | 766 (10) |
| Hypertension, n (%) | 209 (64) | 2168 (26) |
| Systolic BP, mean ± SD | 126 ± 17 | 121 ± 14 |
| Diastolic BP, mean ± SD | 71 ± 9 | 72 ± 9 |
| Dyslipidemia, n (%) | 187 (58) | 2611 (31) |
| LDL-C (mg/dL), mean ± SD | 92 ± 31 | 93 ± 27 |
| Log (TG/HDL), mean ± SD | 0.4 ± 0.8 | 0.3 ± 0.7 |
| Log (TG/HDL) > 0.3, n (%) | 147 (51) | 3265 (47) |
| BMI, mean ± SD | 28 ± 5.0 | 27 ± 5.0 |
| Statin use, n (%) | 210 (65) | 2711 (32) |
| Antihypertensive use, n (%) | 254 (78) | 2974 (35) |
| Baseline Diabetes-Specific Factors | ||
| Age, y; median [IQR] | 53 [42, 62] | 32 [21, 47] |
| T1D duration, y; median [IQR] | 31 [19, 40] | 15 [9, 25] |
| Insulin dose, units/kg; median [IQR] | 0.5 [0.4, 0.7] | 0.6 [0.5, 0.8] |
| HbA1c, %; median [IQR] | 7.7 [7.0, 8.6] | 7.6 [6.9, 8.6] |
| Longitudinal HbA1c SDa, %; median [IQR] | 0.4 [0.2, 0.6] | 0.4 [0.2, 0.6] |
| Nephropathy, n (%) | 113 (35) | 939 (11) |
| Microalbuminuria, n (%) | 50 (15) | 533 (6) |
| Macroalbuminuria, n (%) | 14 (4) | 105 (1) |
| eGFR < 60, n (%) | 77 (25) | 431 (6) |
| Neuropathy (autonomic), n (%) | 15 (5) | 130 (2) |
| Neuropathy (peripheral), n (%) | 26 (8) | 202 (2) |
| CGM use, n (%) | 53 (16) | 1480 (18) |
| Pump use, n (%) | 201 (62) | 4790 (57) |
Data are mean ± SD, median [IQR], or %; T1D; type 1 diabetes.
BMI, body mass index; BP, blood pressure; CVD, cardiovascular disease; CGM, continuous glucose monitoring system; eGFR, estimated glomerular filtration rate; HDL, high density lipoprotein; IQR, interquartile ratio; LDL-C, low density lipoprotein cholesterol; TG, triglyceride.
aSD of HbA1c values taken during registry enrollment.
Figure 1.
Association between risk factors and incident CVD. BP; blood pressure; HDL, high density lipoprotein; LDL-C, low density lipoprotein cholesterol; OR, odds ratio; T1D; type 1 diabetes; TG, triglyceride. 1ORs adjusted for age, T1D duration, Registry follow-up, insurance status, and education level. Adjusted ORs based on 1-unit increase in HbA1c, HbA1c SD, and log (TG/HDL), and 10-unit increase in LDL, BP, age, and T1D duration. 2SD of HbA1c values taken during Registry enrollment.
Age-adjusted incident CVD was associated with longer diabetes duration (median 31 years [IQR = 19, 40] vs. 15 years (IQR = 9, 25); P < .001) (Table 2). Incident CVD was associated with a higher HbA1c (adjusted means = 8.4% [68 mmol/mol] vs. 8.1% [66 mmol/mol]; P < 0.001) when adjusted for education, insurance, age, diabetes duration, and length of enrollment in the registry.
Nephropathy was significantly associated with incident CVD; 35% of participants diagnosed with CVD compared with 11% of non-CVD participants had nephropathy (P < .001) (Table 2). In the CVD cohort, 15% were classified as having microalbuminuria, 4% as having macroalbuminuria, and 25% had an eGFR < 60. In the non-CVD cohort, 6% were classified as having microalbuminuria, 1% as having macroalbuminuria, and 6% had an eGFR < 60. Microalbuminuria, macroalbuminuria, and an eGFR < 60 were all associated with an increased risk of incident CVD (all P < .01).
In a sensitivity analysis, odds ratios stratified by age group were calculated for diabetes-specific risk factors (Supplemental Table 1 (21)). Diabetic nephropathy and diabetes duration were significantly associated with incident CVD across all age strata. Odds ratios were also stratified by the use of statin medications (Supplemental Table 2 (21)). Diabetic nephropathy, diabetes duration, and having an eGFR < 60 were significantly associated with CVD among both those using and not using statins.
Discussion
The 5-year incidence of CVD in adults with established T1D was 3.7%. Ischemic heart disease was the most common CVD event. The incidence rate of CVD was lower in our study compared with previous studies, which may be due to differences in CVD definition and length of follow-up between our study and previously published studies. In the DCCT/EDIC study, 184 of 1441 (12.7%) participants had at least 1 CVD event over a mean of 26 years of follow-up (22). In the Pittsburgh EDC study, the incidence of CVD was 39.1% over an average follow-up of 25 years (6). Similarly, registry-based studies from Europe have reported incidence of CVD from 3% to 10% over variable follow-up periods (3,13,14). Because age is an independent risk factor for CVD, the shorter follow-up period in the T1D Exchange Clinic Registry likely contributes to the lower incidence of CVD in the present analysis.
Age, overweight and obesity, hypertension, and dyslipidemia were associated with increased risk of incident CVD. Our findings are similar to previously published studies (1,3-9,12). However, tobacco use was not associated with CVD in our study, but this may be due to the very few participants using tobacco and lack of precision.
TG to HDL-C ratio was associated with increased CVD risk; however, LDL-C levels were not associated with CVD risk. Most studies of cohorts with and without diabetes report TG levels and low HDL-C as an independent risk factor for CVD (1,3-9,12). Studies in T1D have shown a minimal effect of LDL-C on CVD risk in contradistinction to studies in the general population and those with type 2 diabetes (23,24). Mean LDL-C in adults with T1D who developed CVD over a mean of 5.3 years in our study was 92 mg/dL, which is lower than earlier published studies (4,6,25). Similarly, a prospective study of CVD risk in T1D (CACTI Study) showed increased coronary calcification in adults with T1D despite better lipid levels in men and women with T1D compared with controls without diabetes regardless of age, sex, or previous use of statin therapy (8). Some have postulated that the LDL-C particle size and its oxidation is different in people with T1D (26), which also depend on glycemic control (4); therefore, CVD risk is higher in people with T1D even at near-normal LDL levels. Studies have suggested a reduction in CVD risk with statin therapy irrespective of baseline LDL-C levels (27). Considering the high CVD risk with relatively normal LDL levels, our findings support the American Diabetes Association guidelines on initiation of statin therapy in adults with T1D who are 40 years and older who have at least 1 CVD risk factor regardless of lipid levels (28).
HbA1c and longer duration of diabetes were associated with a 20% to 30% increase in odds of CVD in our study, which is consistent with prior studies (1,3-5,7-9,12). In the DCCT/EDIC study, HbA1c was an independent risk factor for CVD, and intensive diabetes management, which significantly lowered HbA1c, was associated with reduced CVD events over 30 years of observational follow-up (22). Despite the well-recognized importance of glycemic control in reducing micro- and macrovascular complication risk, most adults with T1D in our study had suboptimal glycemic control. Less than 30% of participants had an HbA1c below 7% (53 mmol/mol), whereas 56% had an HbA1c between 7% and 9% (53 and 75 mmol/mol), and 17% had an HbA1c above 9% (75 mmol/mol).
Some studies have reported higher CVD events in women with T1D compared with women without diabetes and men with T1D (29). We did not find a significant increase in CVD risk in women with T1D compared with men with T1D. The DCCT/EDIC study has previously shown that CVD-reducing interventions were underused in women compared with men with T1D (30). However, a recent study from the T1D Exchange Clinic Registry suggested better utilization of diabetes technology in women with T1D and similar level of glycemic control compared with men with T1D (31), which may have account for the lack of sex differences in incident CVD. However, real-life longitudinal evaluation is warranted to understand sex differences in CVD risk.
Similar to previous studies, we report a strong association between diabetic nephropathy and CVD risk (10,11). Studies have linked albuminuria with insulin resistance, inflammation, oxidative stress, and endothelial dysfunction, suggesting albuminuria is a marker for widespread vascular damage and CVD (32). Our study confirms the findings of previous studies and reinforces the need to prevent diabetic nephropathy in adults with T1D and, when present, the need for aggressive management of CVD risk factors to improve long-term CVD outcomes.
To our knowledge, this is first evaluation of incident CVD and associated risk factors in adults with T1D from a national registry in the United States. The large sample size and prospective follow-up of the cohort for a median of 5.3 years in real-world conditions are major strengths of this study. There are limitations to the present analysis. CVD was defined based on electronic medical records, which may have resulted in underreporting of CVD events. Although studies have reported good sensitivity and specificity of electronic medical records in identifying prevalence and incident CVD (33), CVD risk may have been underestimated as silent cardiac ischemia and/that remained undetected and unreported. The observational nature of the study and possibility of unmeasured confounders may have influenced the associations. We were unable to assess statin type (e.g. low- vs. high-intensity) or duration of statin use, which may have affected both LDL concentrations and CVD prevalence in this cohort.
In conclusion, the 5-year incidence of CVD in adults with established T1D was 3.7% in the T1D Exchange Clinic Registry. Age, longer duration of diabetes, overweight and obesity, HbA1c, hypertension, dyslipidemia, and diabetic nephropathy were associated with increased risk for CVD. Further research is needed to confirm CVD risk factors in people with T1D as well as effective mitigation strategies to reduce the increased risk of CVD mortality in this population.
Acknowledgments
The authors thank all participants and clinicians who contributed to T1D Exchange Clinic Registry.
Financial Support: Supported through the Leona M. and Harry B. Helmsley Charitable Trust.
Author Contributions: V.N.S. researched data and wrote/edited the manuscript. R.B., M.W., and N.C.F. performed statistical analyses and wrote/edited the manuscript. R.P.B., M.K., J.C., F.B., K.N., I.L., P.H., K.M.S., L.A.D., J.S., R.P., S.A., J.S.B., E.C., S.P., and S.N.M. researched data, contributed to data interpretation, and reviewed/edited the manuscript. N.F. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and accuracy of the data analysis.
Glossary
Abbreviations
- CVD
cardiovascular disease
- DCCT
Diabetes Control and Complications Trial
- EDC
Pittsburgh Epidemiology of Diabetes Complications
- EDIC
Epidemiology of Diabetes Interventions and Complications
- eGFR
estimated glomerular filtration rate
- HDL-C
high-density lipoprotein cholesterol
- IQR
interquartile range
- LDL-C
low-density lipoprotein cholesterol
- T1D
type 1 diabetes
- TG
triglyceride
Additional Information
Disclosure Summary: V.N.S.’s employer has received research funding from Jaeb Center for Health Research, Center for Women’ Health at the University of Colorado, National Institute of Health (National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Diabetes and Digestive and Kidney Diseases), Eyenuk, Sanofi US, Mylan, and Dexcom Inc., and received honoraria through the University of Colorado from Sanofi US and Dexcom Inc. R.B., M.W., N.C.F., R.P.B., M.K., J.C., F.B., K.N., I.L., P.H., K.M.S.., L.A.D., J.S., R.P., S.A., J.S.B., E.C., S.P., and S.N.M. have no relevant conflict of interests to disclose.
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