Can clinical factors estimate insulin resistance in type 1 diabetes?

An insulin resistance syndrome (IRS) score was developed based on clinical risk factors in adults with childhood-onset type 1 diabetes in the Epidemiology of Diabetes Complications (EDC) Study and was validated using euglycemic-hyperinsulinemic clamp studies. Hypertension, waist-to-hip ratio (WHR), triglyceride and HDL cholesterol levels, family history of type 2 diabetes, and glycemic control were risk factors used to define the score. A score of 1 (lowest likelihood IRS) to 3 (highest likelihood IRS) was assigned for each risk factor. Eligible subjects (n = 24) were recruited from the EDC cohort based on tertile of IRS score. Subjects received an overnight insulin infusion to normalize glucose levels, then underwent a 3-h euglycemic-hyperinsulinemic (60 mU x m(-2) x min(-1)) clamp. Glucose disposal rate (GDR) was determined during the last 30 min of the clamp. The GDR differed significantly by IRS group (9.65 +/- 2.99, 8.02 +/- 1.39, and 5.68 +/- 2.16 mg x kg(-1) x min(-1), P < 0.01). The GDR was inversely correlated with the IRS score (r = -0.64, P < 0.01). Using linear regression, the combination of risk factors that yielded the highest adjusted r2 value (0.57, P < 0.001) were WHR, hypertension, and HbA1. This study found that clinical risk factors can be used to identify subjects with type 1 diabetes who are insulin resistant, and it provides validation of a score based on clinical factors to determine the extent of insulin resistance in type 1 diabetes. This score will be applied to the entire EDC population in future studies to determine the effect of insulin resistance on complications.

Improved glycemic control reduces the impact of weight gain on cardiovascular risk factors in type 1 diabetes. The Epidemiology of Diabetes Complications Study.

OBJECTIVE: To assess the prevalence and incidence of being overweight in type 1 diabetes, to identify factors associated with weight gain and improved glycemic control, and to examine relationships among weight gain, glycemic control, and cardiovascular risk factors. RESEARCH DESIGN AND METHODS: The prevalence and incidence of being overweight in the Pittsburgh Epidemiology of Diabetes Complications (EDC) cohort (n = 441) were compared with the general population (National Health and Nutrition Examination Survey [NHANES]). Factors associated with weight gain and improved glycemic control were identified, and relationships among weight gain, glycemic control, and cardiovascular risk factors were examined over a 6.9 +/- 2.2-year period. RESULTS: At baseline, the prevalence of being overweight (BMI > 27.8 kg/m2 for men and > 27.3 kg/m2 for women) was 10.4 and 11.4%, respectively, and was lower than the age- and sex-specific estimate for the general population (P < 0.05). The incidence of being overweight was comparable in men (12.6%) and women (11.8%) and did not differ from the general population (P = 0.98). Weight gain correlated with improvements in HbA1c (r = -0.21, P < 0.001). Patients with the highest baseline HbA1c levels gained the most weight and had the greatest improvement in glycemic control. A lower baseline BMI was also associated with a greater improvement in glycemic control. Weight gain favorably influenced the lipid profile in the setting of improved glycemic control, but adversely influenced the lipid profile in the absence of improved glycemic control. Weight change was directly associated with blood pressure change, but the incidence of hypertension was more strongly influenced by the development of nephropathy. CONCLUSIONS: The prevalence of being overweight in type 1 diabetes remains lower than that in the general population. Moderate weight gain did not adversely affect the cardiovascular risk profile in the setting of improved glycemic control.

The association between a family history of type 2 diabetes and coronary artery disease in a type 1 diabetes population.

OBJECTIVE: To examine whether a potential marker for type 2 diabetes (family history) is related to CAD in type 1 diabetic subjects. The two major types of primary diabetes, type 1 and type 2, are both associated with an increased risk of developing coronary artery disease (CAD). However, the etiology and associated risk factors may differ by type of diabetes. In type 2 diabetes, CAD is likely to be linked with the insulin resistance associated with the type 2 "process," while CAD in type 1 diabetes has, so far, been more closely linked to renal disease. Because the etiologies of type 1 and type 2 diabetes are different, it is possible that some CAD in type 1 diabetes may be related to the coexistence of type 2 diabetes susceptibility (i.e., insulin resistance). RESEARCH DESIGN AND METHODS: We evaluated the interrelationships between family history of type 2 diabetes (age at onset > 30 years, no insulin for 1st year) and presence of CAD in a cohort of childhood-onset type 1 diabetic subjects using the Pittsburgh Epidemiology of Diabetes Complications study (n = 658). RESULTS: A first-degree family history of type 2 diabetes was reported in 112 subjects, and CAD was present in 119 subjects. Those subjects reporting a family history of type 2 diabetes were significantly older, had a longer duration of type 1 diabetes, had higher triglyceride and LDL cholesterol levels, and had a borderline significantly increased Beck depression inventory. Sex differences in CAD risk factors were also noted. Using logistic regression analysis, the odds ratio (95% CI) for the presence of CAD in association with a family history of NIDDM was 1.89 (1.27-2.84). The odds ratio (95% CI) after adjusting for disease duration, triglycerides, hypertension, Beck depression, and nephropathy status was 1.45 (0.87-2.28). CONCLUSIONS: We conclude that a family history of type 2 diabetes is a risk factor for CAD in type 1 diabetic subjects. This supports the concept that insulin resistance may contribute to development of CAD in type 1 diabetes.

Congestive heart failure in type 2 diabetes: prevalence, incidence, and risk factors.

OBJECTIVE: To estimate the prevalence and incidence of congestive heart failure (CHF) in populations with and without type 2 diabetes and to identify risk factors for diabetes-associated CHF. RESEARCH DESIGN AND METHODS: We searched the inpatient and outpatient electronic medical records of 9,591 individuals diagnosed with type 2 diabetes before 1 January 1997 and those of an age- and sex-matched control group without diabetes for a diagnosis of CHF. Among those without a baseline diagnosis of CHF, we searched forward for 30 months for incident cases of CHF. We constructed multiple logistic regression models to identify risk factors for both prevalent and incident CHF. RESULTS: CHF was prevalent in 11.8% (n = 1,131) of diabetic subjects and 4.5% (n = 435) of control subjects at baseline. We observed incident cases of CHF in 7.7% of diabetic subjects free of CHF at baseline (650 of 8,460) and in 3.4% of control subjects (314 of 9,156). In diabetic subjects, age, diabetes duration, insulin use, ischemic heart disease, and elevated serum creatinine were independent risk factors for both prevalent and incident CHF. Better glycemic control at baseline, and improved glycemic and blood pressure control at follow-up predicted the development of CHF. CONCLUSIONS: Despite controlling for age, duration of diabetes, presence of ischemic heart disease, and presence of hypertension, insulin use was associated with both prevalent and incident CHF. Why insulin use and better glycemic control both at baseline and follow-up independently predicted CHF deserves further study.

Low-density lipoprotein particle size and coronary artery disease in a childhood-onset type 1 diabetes population.

Low-density lipoprotein (LDL) cholesterol has been widely recognized as a strong predictor of coronary artery disease (CAD). Recently, studies have examined the influence of LDL particle size (an integral part of the insulin resistance syndrome) on the development of CAD in the general population. This report examines the correlates of LDL particle size and its association with CAD in a type 1 diabetes population. We evaluated the interrelationships between LDL particle size and the presence of CAD in a cohort of childhood-onset type 1 diabetic subjects using the Pittsburgh Epidemiology of Diabetes Complications (EDC) study. LDL particle size was measured in 337 subjects (mean age, 35.6 years; mean diabetes duration, 27.2 years) who underwent the 8-year follow-up examination. LDL particle size was determined by vertical polyacrylamide gel (2% to 16%) electrophoresis. Subjects with the small dense LDL particle phenotype (<235.5 angstroms) [corrected] had a longer diabetes duration, higher cholesterol, triglyceride, LDL, fibrinogen, waist to hip ratio (WHR), and hemoglobin A1 (HbA1), and lower high-density lipoprotein (HDL) cholesterol compared with subjects with the large LDL particle phenotype (>257 angstroms) [corrected]. Males were also more likely to have an increased body mass index (BMI) and CAD, while females were more likely to have hypertension and a family history of type 2 diabetes (a potential marker of insulin resistance and CAD risk). The odds ratio ([OR] 95% confidence, interval [CI]) using logistic regression analysis for LDL particle size in association with CAD was 0.79 (0.60 to 1.04). Multivariate modeling indicated that the duration of type 1 diabetes, depressive symptomatology, and triglycerides were independently associated with the presence of CAD. We conclude that although small dense LDL particle size is associated with CAD in our type 1 diabetes population, its borderline association can largely be explained by the triglyceride concentration. However, as in the general population, LDL particle size is associated with many elements of the insulin resistance syndrome, including a family history of type 2 diabetes, and is likely an important element in the contribution of insulin resistance to the development of CAD in type 1 diabetes.

Do tissue plasminogen activator-plasminogen activator inhibitor-1 complexes relate to the complications of insulin-dependent diabetes mellitus? Pittsburgh Epidemiology of Diabetes Complications Study.

The purpose of this study was to examine the potential relationship of tissue plasminogen activator-plasminogen activator inhibitor-1 (tPA-PAI-1) complexes and diabetic complications in individuals with insulin-dependent diabetes mellitus (IDDM). To address this issue, data from the third follow-up visit of participants in the Epidemiology of Diabetes Complications (EDC) study were examined. There were 454 participants, aged 32 +/- 8 years, with duration of IDDM of 23 +/- 8 years. Higher levels of tPA-PAI-1 complexes were seen for both men and women with IDDM complications. Specifically, statistically significant differences were seen in men with neuropathy (1.81 +/- 0.9 versus 1.42 +/- 0.8 ng/mL, p < 0.01), microalbuminuria (1.77 +/- 1.1 versus 1.35 +/- 0.6 ng/mL, p < 0.01), retinopathy (1.67 +/- 0.9 versus 1.43 +/- 0.8 ng/mL, p < 0.05), and lower extremity arterial disease (1.93 +/- 0.7 versus 1.50 +/- 0.9 ng/mL, p < 0.05) versus men without the particular complication. In women, higher complex levels were shown for those with retinopathy (1.51 +/- 0.8 versus 1.29 +/- 1.1 ng/mL, p < 0.01). Potential mechanisms for the relationship of higher complex levels and diabetic complications include an altered fibrinolytic response and/or insulin resistance. Because the results are cross sectional, it cannot be established whether the higher concentration of complexes is a result of the presence of complications or are antecedent. Prospective follow-up will be required to determine if tPA-PAI-1 complexes are predictive of the development of IDDM complications.

Estimated coronary heart disease attributable to insulin resistance in populations with and without type 2 diabetes mellitus.

OBJECTIVE: To estimate the annual number and costs of coronary heart disease (CHD) events in the United States attributable to insulin resistance among individuals with and without type 2 diabetes. RESEARCH DESIGN AND METHODS: Medline-indexed articles and government statistical reports were screened for data on the prevalence of insulin resistance, the relative risk of CHD by insulin resistance status, and number of CHD events per year among individuals with and without type 2 diabetes. These data were used to estimate the number of CHD events per year by insulin resistance and type 2 diabetes status, the proportion of CHD events attributable to insulin resistance, and the annual cost of these events. RESULTS: Of the 171,000 annual CHD events in the type 2 diabetes population, 164,000 (96%) occurred in those with insulin resistance, 80,000 of which were attributable to insulin resistance. Of the 929,000 annual CHD events in the non-type 2 diabetes population, 162,000 (17%) occurred in patients with insulin resistance, 58,000 of which were attributable to insulin resistance. Thus, insulin resistance is responsible for 46.8%, 6.2%, and 12.5% of the annual CHD events in the type 2 diabetes, non-type 2 diabetes, and total US population, respectively. The estimated annual total cost of these insulin resistance-attributable events was $12.5 billion in the United States in 1999, of which $6.6 billion were direct medical costs. CONCLUSION: Preventing or modifying insulin resistance may reduce the morbidity, mortality, and costs associated with CHD.