Diabetes Care
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Rewers, M.
Right arrow Articles by Savage, P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Rewers, M.
Right arrow Articles by Savage, P.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Diabetes Care 27:781-787, 2004
© 2004 by the American Diabetes Association, Inc.

Metabolic Syndrome/Insulin Resistance/Pre-Diabetes
Original Article

Insulin Sensitivity, Insulinemia, and Coronary Artery Disease

The Insulin Resistance Atherosclerosis Study

Marian Rewers, MD, PHD1, Daniel Zaccaro, MS2, Ralph D’Agostino, Jr., PHD2, Steven Haffner, MD, MPH3, Mohammed F. Saad, MD4, Joe V. Selby, MD, MPH5, Richard Bergman, PHD6 and Peter Savage, MD7 for the Insulin Resistance Atherosclerosis Study Investigators

1 Barbara Davis Center, University of Colorado HSC, Denver, Colorado
2 Department of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
3 Department of Medicine, University of Texas HS, San Antonio, Texas
4 Department of Medicine, University of California Los Angeles, Los Angeles, California
5 Department of Physiology and Biophysics, University of Southern California, Los Angeles, California
6 Kaiser Research Center, Northern California, Division of Research, Oakland, California
7 Division of Epidemiology and Clinical Applications, National Heart, Lung, and Blood Institute, Bethesda, Maryland

Address correspondence and reprint requests to Marian Rewers, MD, PhD, Barbara Davis Center, University of Colorado Health Sciences Center, B-140, 4200 E 9th Ave., Denver, CO 80262. E-mail: marian.rewers{at}uchsc.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 
OBJECTIVE—The aim of this study was to evaluate whether low insulin sensitivity (Si) measured using a modified frequently sampled intravenous glucose tolerance test with minimal model analysis is associated with coronary artery disease (CAD) independent of other cardiovascular risk factors.

RESEARCH DESIGN AND METHODS—We studied 1,482 women and men, age 40–69 years old, African American (28%), Hispanic (34%), or non-Hispanic white (38%), with normal (45%), impaired (23%), or diabetic (32%) glucose tolerance. CAD defined as confirmed past myocardial infarction, coronary artery bypass graft, coronary angioplasty, or presence of a major Q-wave was found in 91 participants.

RESULTS—The odds ratio (OR) for CAD was greatest among individuals in the two lowest quintiles of Si (2.4, 95% CI 1.0–5.6 and 4.7, 2.1–10.7) compared with the highest Si quintile. After adjusting for demographic and cardiovascular risk factors, a decrement from the 75th to 25th percentile in Si was associated with a 56% increase in CAD (P = 0.028). Similar increments in fasting or 2-h insulin levels were associated with, respectively, only 15 (NS) and 3% (NS) increases in CAD. The association between Si and CAD was partially mediated by insulin, HDL cholesterol and triglyceride levels, hypertension, diabetes, and obesity, but not LDL cholesterol or cigarette smoking.

CONCLUSIONS—Low Si is associated with CAD independently of and stronger than plasma insulin levels. Part of the association is accounted for by dyslipidemia, hypertension, diabetes, and obesity.

Abbreviations: CAD, coronary artery disease • ECG, electrocardiogram • FSIGT, frequently sampled intravenous glucose tolerance test • HOMA, homeostasis model assessment • IGT, impaired glucose tolerance • IRAS, Insulin Resistance Atherosclerosis Study


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 
Low insulin sensitivity underlies the metabolic syndrome that includes central obesity, dyslipidemia, hyperglycemia, hypertension, impaired fibrinolysis, and atherosclerosis (1,2). However, measurement of insulin sensitivity is technically difficult, and only a few relatively small studies (3–5) have demonstrated a strong association between insulin sensitivity measured directly and coronary artery disease (CAD). On the other hand, hyperinsulinemia (a marker of low insulin sensitivity) has been related to CAD in numerous prospective (6–12) and cross-sectional studies (13). Insulinemia is generally inversely related to insulin sensitivity, but the relationship is not linear (14), and it is usually absent in diabetic individuals (15,16) who account for a significant proportion of people with low insulin sensitivity. The Insulin Resistance Atherosclerosis Study (IRAS) (17) and others (18,19) have previously shown that low insulin sensitivity is associated with atherosclerosis, defined by the intima-media thickening of the carotid arteries. In this study, we test the hypothesis that low insulin sensitivity is also cross-sectionally associated with clinical CAD, independent of insulin levels and other cardiovascular risk factors.


   RESEARCH DESIGN AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
RESULTS
 CONCLUSIONS
 References
 
The design of IRAS, a four-center epidemiological study exploring relationships among insulin sensitivity, insulin levels, cardiovascular risk factors, and cardiovascular disease across a broad range of glucose tolerance, has been previously published (20). Briefly, IRAS evaluated 1,624 women and men aged 40–69 years, representing normal (44%), impaired (23%), and diabetic glucose tolerance (33%). Of the 479 diabetic patients included in this report, 294 were previously diagnosed (average duration of diabetes 6.9 ± 6.4 years). Of those, 73% were taking oral hypoglycemic agents, whereas the remaining were treated with diet alone. Individuals with impaired glucose tolerance (IGT) and type 2 diabetes were over-sampled to achieve sufficient statistical power in these subgroups. Nondiabetic IRAS participants had, however, fasting blood glucose levels similar to those in nondiabetic individuals of the same ethnic group in the general population (20). IRAS clinics in Oakland and Los Angeles, California, studied non-Hispanic whites and African Americans recruited from Kaiser Permanente health maintenance organizations. The centers in San Antonio, Texas and San Luis Valley, Colorado recruited non-Hispanic whites and Hispanics from ongoing population-based studies (21,22). Race and ethnicity were assessed by self-report using the U.S. census definitions; African-Americans comprised 29%, Hispanics 34%, and non-Hispanic whites 37% of the study participants. Exclusion criteria included insulin treatment in the past 5 years, fasting glucose >=16.7 mmol/l [300 mg/dl], unstable angina, decompensated congestive heart failure, or serious illness within the past month. All study protocols were approved by institutional review boards, and informed consent was obtained from all participants.

Measurement of glucose tolerance, insulin, and insulin sensitivity
An oral glucose tolerance test with glucose tolerance classification according to the WHO criteria (23) and a frequently sampled intravenous glucose tolerance test (FSIGT) were performed on two separate days 2–28 days apart. Participants were asked to refrain from heavy exercise and alcohol consumption for 24 h and fast for 12 h before each visit and abstain from smoking the morning of examination. Plasma glucose was measured with the glucose oxidase method on an automated autoanalyzer (Yellow Springs Equipment). Plasma insulin levels were measured using the dextran-charcoal radioimmunoassay method (24).

Insulin sensitivity was assessed by the FSIGT with minimal model analysis (25). Glucose (0.3 g/kg in 50% solution) was injected through an intravenous catheter at 0 min, and regular human insulin (0.03 U/kg) was injected at 20 min. Blood was collected at -5, 2, 4, 8, 19, 22, 30, 40, 50, 70, 100, and 180 min for insulin and glucose determination. Si was calculated by mathematical modeling (MINMOD, version 3.0, 1994). The injection of insulin was necessary to ensure adequate plasma insulin levels for accurate computation of insulin sensitivity in a diabetic person (26). This version of the FSIGT was validated by comparison with the hyperinsulinemic-euglycemic clamp (27).

Definition of CAD
CAD was defined conservatively as past myocardial infarction, coronary artery bypass graft, or percutaneous transluminal coronary angioplasty only if confirmed by review of medical records or a major Q-wave on IRAS examination electrocardiogram (ECG). The IRAS Events Committee (M.R., S.H., and J.S.) reviewed using standard criteria (28) all events reported to occur before the IRAS examination. Myocardial infarction was confirmed in 39 (72%) of 54, coronary artery bypass graft in 19 of 21, and percutaneous transluminal coronary angioplasty in 7 of 9 of case subjects. Standard, resting 12-lead ECG was performed using the MAC/PC electrocardiograph (Marquette Electronics, Milwaukee, WI). ECG tracings were read centrally using NOVACODE ECG software and the Minnesota Code (29) and revealed a major Q-wave (Minnesota code 1.1–1.2, except for 1.28) in 59 of the participants. Of the 1,482 IRAS participants who completed FSIGT, 91 (47 nondiabetic and 44 diabetic participants) had at least one of these events and were classified as case subjects.

Other measurements
Resting systolic and diastolic blood pressure were measured three times, and the second and third measurements were averaged. Hypertension was defined as systolic blood pressure >=140 or diastolic blood pressure >=90 mmHg or if they were currently taking antihypertensive medication. BMI was used as an estimate of overall adiposity. The waist-to-hip ratio was used as an estimate of body fat distribution. Cigarette smoking was categorized into "none," "past," or "current" using a standard questionnaire. Plasma HDL and LDL cholesterol were measured in fresh fasting plasma using the ß-quantification according to the Lipid Research Clinics. Triglycerides were measured by enzymatic method in a glycerol blanked assay (Hitachi Autoanalyzer).

Statistical analysis
All analyses were performed in SAS version 6.08 statistical package (SAS Institute, Cary, NC) using Student’s t test and {chi}2 test for univariate comparisons and logistic regression to estimate the relationship between Si and CAD, controlling for potential confounders and effect modifiers.

The Si was estimated to be 0 for 231 of the 298 participants in the lowest Si quintile. In all logistic regression models shown, an indicator variable was included for individuals with Si = 0, as previously described (17), but it was statistically not significant (P > 0.05).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
CONCLUSIONS
 References
 
This report includes 91% (1,482 of 1,624) of the study participants who completed the FSIGT. Univariate comparison of the characteristics of the 91 case subjects and 1,391 control subjects studied (Table 1) confirmed known associations between CAD and type 2 diabetes, male sex, older age, central obesity (higher waist-to-hip ratio), dyslipidemia (low HDL cholesterol and high triglycerides), hypertension, and cigarette smoking. Case subjects had significantly lower Si levels than control subjects. Fasting insulin levels were only on the borderline of being higher among case subjects than control subjects. There was no difference in the levels of 2-h insulin between case subjects and control subjects.


View this table:
[in this window]
[in a new window]
  		Table 1— Univariate comparison of the levels of selected cardiovascular risk factors among IRAS participants with and without confirmed CAD

 
To explore the linearity of the relationship between Si and the CAD, the ORs of CAD were estimated by quintiles of the Si distribution, adjusting for age, sex, ethnicity, and clinic (Fig. 1). Adjusted CAD ORs for quintiles of fasting and 2-h insulin levels were included for comparison. The quintile of highest Si or lowest fasting insulin or 2-h insulin levels served as the reference. The ORs for CAD were greatest among individuals in the second lowest Si quintile (OR = 4.7, 95% CI 2.1–10.7), followed by those with the lowest Si (2.4, 1.0–5.6). The ORs were nearly identical when the analysis was stratified by diabetic status. For instance, the ORs for CAD in nondiabetic participants were greatest among individuals in second lowest Si quintile (OR = 4.7), followed by those with the lowest Si (OR = 2.5).



View larger version (11K):
[in this window]
[in a new window]
  		Figure 1— OR for CAD by Si quintiles (0–0.24, 0.25–0.83, 0.84–1.44, 1.45–2.67, and 2.68–19.4 x 10-4 min · µU-1 · ml-1), quintiles of fasting insulin (179–1,830, 129–178, 93–128, 65–92, and 7–64 pmol/l), and quintiles of 2-h insulin levels (1,048–6,458, 674–1,047, 453–573, 237–451, and 214–236 pmol/l), adjusted for age, sex, ethnicity, and clinic. Individuals in the fifth quintile (highest Si, lowest fasting, or 2-h insulin levels) served as the reference group, IRAS 1992–1995.

 
After adjustment for demographic factors CAD (Table 2, model 1a), an interquartile decrement from the 75th to 25th percentile in Si (2.21 to 0.41 x 10-4 min · µU-1 · ml-1) was associated with a 91% increase in CAD (P = 0.001). Similar interquartile differences in fasting insulin (from 60 to 132 pmol/l) (model 1b) or 2-h insulin levels (from 216 to 816 pmol/l) (model 1c) were associated with, respectively, only 34% (P = 0.034) and 16% (NS) increases in CAD. A simultaneous estimation of the effects of Si, fasting, and 2-h insulin (model 1d) indicated that only Si was significantly and independently associated with CAD (OR = 1.84, P < 0.006).


View this table:
[in this window]
[in a new window]
  		Table 2— OR for CAD associated with a difference between the 75th and 25th percentile in Si adjusted for demographic variables and conventional cardiovascular risk factors, IRAS 1992–1995

 
Because nearly a one-half of the case subjects had type 2 diabetes, which is known to increase the risk of CAD, we carried the analyses also stratified by diabetic status. The results were virtually identical for diabetic and nondiabetic participants, and the interaction between the effects of Si and diabetes was nonsignificant (P > 0.9) in all of the models. In further analyses, we combined diabetic and nondiabetic participants.

Adjustment for HDL and LDL cholesterol levels, triglycerides, smoking, and hypertension attenuated the independent association between CAD and Si (model 2a) and removed any association between CAD and fasting (model 2b) or 2-h insulin levels (model 2c). Models 2d, 2e, and 2f further suggested that Si, rather than fasting or 2-h insulin levels, was the independent determinant of CAD. The decrease in the CAD ORs with adjustment for cardiovascular disease risk factors, from 1.91 for (model 1a) to 1.56 (model 2a), was consistent with the likely scenario that some of these factors could mediate the association between Si and CAD. A stepwise addition of these risk factors to model 1a (data not shown) indicated that HDL cholesterol levels or closely correlated triglyceride levels and hypertension, but not LDL cholesterol and cigarette smoking, might mediate the effect of Si.

Further adjustment for diabetes status (model 3) and obesity (model 4) removed most of the remaining association between Si and CAD. One may, however, argue that this could be a case of over adjustment, because the vast majority of participants with low Si were diabetic and/or obese. After adjustment for all covariates (model 5), insulin levels did not have any effect on CAD, but the interquartile decrement in Si was still associated with a 29% increase in the odds of CAD. Although not statistically significant, this finding may suggest that additional factors not included in these analyses may also play a role in the association between low Si and CAD.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
References
 
This is the largest epidemiological study to date that has assessed directly insulin sensitivity and related it to fasting and postload insulin levels, traditional cardiovascular risk factors, and CAD. Our findings of an association between low insulin sensitivity and CAD, largely independent of the effects of major cardiovascular risk factors, are consistent with previous studies that used fasting insulin levels as a marker of insulin sensitivity (6–13). In contrast to some of these previous studies (8,9,30), the association between Si and CAD was highly significant and independent of the effects of lipids, hypertension, and cigarette smoking. These results are also consistent with the previously reported (17–19) association between low Si and carotid artery wall thickness, which is an index of atherosclerosis. A comparison of the intima-media thickness of the internal carotid arteries in the IRAS CAD case subjects and control subjects (Fig. 2), confirmed that the most insulin-resistant CAD case subjects had the most extensive carotid atherosclerosis. Thus, low insulin sensitivity is associated with both subclinical carotid atherosclerosis and clinical CAD.



View larger version (14K):
[in this window]
[in a new window]
  		Figure 2— Mean internal carotid artery intima-media wall thickness among CAD case (n = 91) and control (n = 1,391) subjects by quintiles of insulin sensitivity (Si, adjusting for age, sex, ethnicity, and clinic); IRAS 1992–1995.

 
The association between Si and carotid wall thickness (17) or CAD (current report) was independent of and much stronger than the associations with fasting or 2-h insulin levels. The exact contribution of the proposed atherogenic effect of insulin (13) to the association between insulin resistance and CAD is difficult to quantify in this cross-sectional analysis but appears to be relatively small (Table 2, model 1a versus 1d). This is consistent with the variable and generally weak associations between insulin levels and CAD reported previously (30). On the other hand, our data confirm that hypertension (31), dyslipidemia (32), and diabetes (acting through hyperglycemia or other risk factors [33,34]) mediate a significant part of the association between low Si and CAD.

This study is the first to measure insulin sensitivity directly in a large population of people with normal, impaired, or diabetic glucose tolerance. Whereas it is more difficult to measure Si than fasting insulinemia, the interpretation of Si (effectiveness of insulin on glucose kinetics) is easier than that of fasting insulin levels. Fasting insulin levels increase with insulin resistance but to a variable extent limited by the pancreas’ ability to secrete insulin and modified by ambient glycemia and insulin clearance. Therefore, fasting insulinemia is a less useful marker of insulin sensitivity in individuals with diabetes, impaired insulin secretion (e.g., a large proportion of individuals with IGT [15]), some forms of hyperinsulinemia (e.g., insulinoma), and disorders of insulin clearance (e.g., cirrhosis). The major advantage of the IRAS protocol was the ability to measure insulin sensitivity in individuals with diabetes who are at a two- to fourfold increased risk of CAD (12,35). They have typically been excluded from previous studies (6–11), yet diabetes affects, in the U.S., 6–14% of people aged 30–64 years and 18–32% of those over 64 years (36).

Despite the advantages of the minimal model analysis in assessment of insulin sensitivity, the method resulted in a "zero Si" estimate in ~16% of IRAS participants (in 2% of those with normal, 13% with impaired, and 36% of those with diabetic glucose tolerance). "Zero insulin sensitivity" is a difficult concept to accept; however, we have demonstrated that IRAS participants with Si = 0 had more features of the metabolic syndrome than other insulin-resistant IRAS participants with Si >0 (37). The phenomenon has been recently explained (38) as an artifact of a single compartment glucose distribution assumption underlying the minimal model estimation of Si, which does not include insulin action on hepatic glucose metabolism. A more exact two-compartment modeling is not suitable for field studies due to complexity and use of a radiolabeled tracer. However, allowing Si to assume apparently negative values could partly correct the deviation and improve the correlation with euglycemic clamp derived measure of insulin sensitivity (39). When we recalculated Si, allowing negative values, the rank of Si values was virtually unchanged. The ORs for CAD by quintile of such calculated Si (data not shown) looked nearly identical to those shown in Fig. 1, which were calculated using traditional Si values. This could be expected because Si estimates from the two-compartment model correlate perfectly with the one-compartment model Si estimates (38). Therefore, whereas the minimal model systematically underestimated insulin sensitivity, compared with the euglycemic clamp or a two-compartment model, it provided a dependable, cost-efficient, and minimally invasive way to measure insulin sensitivity in a large free-living population.

The present study has several limitations. First, the relation between Si, insulin levels, and CAD were assessed cross-sectionally, and the proposed role of low insulin sensitivity as one of the causes of CAD needs to be confirmed in longitudinal studies. The IRAS cohort is being followed prospectively with major cardiovascular disease end points ascertained through annual participant interviews and committee review of medical records of reported fatal and nonfatal events. A 10-year follow-up of the study cohort will be completed in 2005.

Second, the IRAS cohort is not strictly population based. The study participants were drawn from two existing population-based epidemiological studies and from two health maintenance organization populations; however, individuals with IGT and diabetes were over-sampled by design. On the other hand, demanding protocol and specific exclusion criteria removed from the study population individuals with the most severe diabetes or CAD. Less than expected carotid artery atherosclerosis among the most insulin-resistant IRAS participants reported previously (17) and lower than expected CAD prevalence found in the current study in that group could be due to a "survivor bias." This could occur if individuals with the most severe CAD have died, elected not to participate, or were excluded. This potential selection bias would tend to underestimate the true association between Si and CAD.

Third, the study population included Hispanic and non-Hispanic whites as well as African Americans, but relatively few end points in each of these subgroups limited our ability to detect any ethnic differences in the relation between low Si and CAD. There were no clear interactions between Si and ethnicity (P > 0.4, data not shown), and the present analyses were adjusted for, but not stratified by, ethnicity.

Fourth, there could have been some misclassification of the CAD status using the study criteria. Only 91 participants with most severe clinical or ECG manifestations of CAD were classified as "case subjects," whereas obviously many more had some degree of CAD but were classified as "control subjects." More precise procedures to document CAD, such as coronary angiography or electron beam tomography for coronary calcification, were too invasive or expensive for this large study. Our definition of CAD most likely underestimated the true associations between CAD and risk factors, including Si. Recently, a study of just 13 case subjects with arteriographically documented CAD and 10 control subjects (3) found a significant difference in their insulin sensitivity, consistent with that reported here.

Fifth, the minimal model measurement of insulin sensitivity is technically difficult in clinical practice. In search for a simpler solution, we substituted Si with the homeostasis model assessment (HOMA) measurement of insulin sensitivity that can be derived from the FSIGT (39). In none of the models, except for the simplest model 1a, was HOMA associated with CAD. Although easier to obtain than Si, the HOMA estimate of insulin sensitivity appears to be insufficiently precise for studies of IRAS size.

Finally, Si and insulin levels display significant variability, partially related to precision of measurements and partially due to acute day-to-day and diurnal changes (40). The interclass correlation for Si measured twice within 1 week in 58 IRAS participants was 0.67 compared with 0.76 for fasting insulin. Thus, it is unlikely that we measured Si with more precision than fasting insulin levels and that this could account for the stronger association of CAD with Si than with fasting insulin. We confirmed that by using the average of two fasting insulin measurements (on the oral glucose tolerance test day and on the FSIGT day) instead of a single measurement in alternative models 1, 2, and 5. Although some of the ORs for fasting insulin increased slightly, the ORs for Si and the associated P values virtually did not change. We did not estimate the reproducibility of 2-h insulin levels in IRAS, but they may vary by >30% in normal subjects studied 48 h apart (41), which is comparable with the reproducibility of Si and fasting insulin. Therefore, differential measurement precision of Si and insulin levels is unlikely to explain the apparent independence and greater strength of the association between Si and CAD compared with that between insulin levels and CAD.

In middle-aged women and men representative of the three major U.S. ethnic groups and including individuals with normal, impaired, and diabetic glucose tolerance, we found that CAD was cross-sectionally associated with low insulin sensitivity. This association was independent of and stronger than that between CAD and fasting or postload insulin levels. Dyslipidemia, hypertension, diabetes, obesity, and fat centrality explained part of the association between low insulin sensitivity and CAD.


   Acknowledgments
 
This study was supported by the National Heart, Lung, and Blood Institute Awards U01-HL-47887, HL-47889, HL-47890, HL-47892, and HL-47902. In addition, the Los Angeles center was supported by grant M01-RR-43 from the National Center for Research Resources/National Institutes of Health.

The authors would like to thank the women and men who participated in this study. We would also like to acknowledge the valuable contributions of additional IRAS investigators, clinical, and technical staff.


   Footnotes
 
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

Received for publication September 1, 2003. Accepted for publication December 1, 2003.


   References
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 CONCLUSIONS
 References
 

  1. Reaven GM: Role of insulin resistance in human disease. Diabetes 37:326–337, 1988
  2. DeFronzo RA, Ferrannini E: Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 14:173–194, 1991[Abstract]
  3. Young MH, Jeng CY, Sheu WH, Shieh SM, Fuh MM, Chen YD, Reaven GM: Insulin resistance, glucose intolerance, hyperinsulinemia and dyslipidemia in patients with angiographically demonstrated coronary artery disease. Am J Cardiol 72:458–460, 1993[Medline]
  4. Shinozaki K, Suzuki M, Ikebuchi M, Hara Y, Harano Y: Demonstration of insulin resistance in coronary artery disease documented with angiography. Diabetes Care 19:1–7, 1996[Abstract]
  5. Bressler P, Bailey SR, Matsuda M, DeFronzo RA: Insulin resistance and coronary artery disease. Diabetologia 39:1345–1350, 1996[Medline]
  6. Welborn TA, Wearne K: Coronary heart disease incidence and cardiovascular mortality in Busselton with reference to glucose and insulin concentrations. Diabetes Care 2:154–160, 1979[Abstract]
  7. Pyörälä M, Miettinen H, Laakso M, Pyörälä K: Hyperinsulinemia predicts coronary heart disease risk in healthy middle-aged men: the 22-year follow-up results of the Helsinki Policemen Study. Circulation 98:398–404, 1998[Abstract/Free Full Text]
  8. Eschwege E, Ducimetiere P, Thibult N, Richard JL, Claude JR, Rosselin GE: Coronary heart disease mortality in relation with diabetes, blood glucose and plasma insulin levels: the Paris prospective study 10 years later. Horm Metab Res 15 (Suppl.):41–45, 1985
  9. Yarnell JWG, Sweetnam PM, Marks V, Teale JD, Bolton CH: Insulin in ischaemic heart disease: are associations explained by triglyceride concentrations: the Caerpholly prospective study. Br Heart J 171:293–296, 1994
  10. Perry IJ, Wannamethee SG, Whincup PH, Shaper AG, Walker MK, Alberti KGMM: Serum insulin and incident coronary heart disease in middle-aged British men. Am J Epidemiol 144:224–234, 1996[Abstract/Free Full Text]
  11. Després J-P, Lamarche B, Mauriège P, Cantin B, Dagenais GR, Moorjani S, Lupien PJ: Hyperinsulinemia as an independent risk factor for ischemic heart disease. N Engl J Med 334:952–957, 1996[Abstract/Free Full Text]
  12. Folsom AR, Liao F, Szklo M, Smith R, Stevens J, Eckfeldt JH: A prospective study of coronary heart disease in relation to fasting insulin, glucose, and diabetes. Diabetes Care 20:935–942, 1997[Abstract]
  13. Stout RW: Insulin and atheroma: 20-year perspective. Diabetes Care 13:631–655, 1990[Abstract]
  14. Kahn SSE, Prigeon RL, McCulloch DK, Boyko EJ, Bergman RN, Schwartz MW, Neifing JL, Ward WK, Beard JC, Palmer JP, Porte D Jr: Quantification of the relationship between insulin sensitivity and ß-cell function in human subjects: evidence for a hyperbolic function. Diabetes 42:1663–1672, 1993[Abstract]
  15. Laakso M: How good a marker is insulin level for insulin resistance? Am J Epidemiol 137:959–965, 1993[Abstract/Free Full Text]
  16. Ludvik B, Nolan JJ, Baloga J, Sacks D, Olefsky J: Effect of obesity on insulin resistance in normal subjects and patients with NIDDM. Diabetes 44:1121–1125, 1995[Abstract]
  17. Howard G, O’Leary DH, Zaccaro D, Haffner S, Rewers M, Hamman R, Selby JV, Saad MF, Savage PJ, Bergman R: Insulin sensitivity and atherosclerosis. Circulation 93:1809–1817, 1996[Abstract/Free Full Text]
  18. Watarai T, Yamasaki Y, Ikeda M, Kubota M, Kodama M, Tsujino T, Kishimoto M, Kawamori R, Hori M: Insulin resistance contributes to carotid arterial wall thickness in patients with non-insulin-dependent-diabetes mellitus. Endocr J 46:629–638, 1999[Medline]
  19. Wohlin M, Sundstrom J, Arnlov J, Andren B, Zethelius B, Lind L: Impaired insulin sensitivity is an independent predictor of common carotid intima-media thickness in a population sample of elderly men. Atherosclerosis 170:181–185, 2003[Medline]
  20. Wagenknecht LE, Mayer EJ, Rewers MR, Haffner S, Selby J, Borok GM, Henkin L, Howard G, Savage PJ, Saad MF, Bergman RN, Hamman R: The Insulin Resistance Atherosclerosis Study (IRAS): Objectives, design, and recruitment results. Ann Epidemiol 5:464–472, 1995[Medline]
  21. Stern MP, Rosenthal M, Haffner SM, Hazuda HP, Franco LJ: Sex differences in the effects of sociocultural status on diabetes and cardiovascular risk factors in Mexican Americans: the San Antonio Heart Study. Am J Epidemiol 120:834–851, 1984[Abstract/Free Full Text]
  22. Hamman RF, Marshall JA, Baxter J, Kahn LB, Mayer EJ, Orleans M, Murphy JR, Lezotte DC: Methods and prevalence of non-insulin dependent diabetes mellitus in a biethnic Colorado population: the San Luis Valley Diabetes Study. Am J Epidemiol 129:295–311, 1989[Abstract/Free Full Text]
  23. World Health Organization: Diabetes Mellitus: Report of a WHO Study Group. Geneva, World Health Org., 1985 (Tech. Rep. Ser., no. 727)
  24. Herbert V, Lau K, Gottlieb C, Bleicher S: Coated charcoal immunoassay of insulin. J Endocrinol Metab 25:1375–1384, 1965[Medline]
  25. Bergman RN, Finegood DT, Ader M: Assessment of insulin sensitivity in vivo. Endocr Rev 6:45–86, 1985[Medline]
  26. Welch S, Gebhart SSP, Bergman RN, Phillips LS: Minimal model analysis of intravenous glucose tolerance derived insulin sensitivity in diabetic subjects. J Endocrinol Metab 71:1508–1518, 1990[Abstract]
  27. Saad MF, Anderson RL, Laws A, Watanabe RM, Kades WW, Chen Y-DI, Sands RE, Pei D, Savage PJ, Bergman RN: A comparison between the minimal model and glucose clamp in the assessment of insulin sensitivity across the spectrum of glucose tolerance. Diabetes 43:1114–1121, 1994[Abstract]
  28. The ARIC Investigators: The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. Am J Epidemiol 129:687–702, 1989[Abstract/Free Full Text]
  29. Prineas RJ, Crow RS, Blackburn H: The Minnesota Code: Manual of Electrographic Findings. Boston, John Wright-PGS, 1982
  30. Wingard DL, Ferrara A, Barrett-Connor EL: Is insulin really a heart disease risk factor? Diabetes Care 18:1299–1304, 1995[Medline]
  31. Ferrannini E, Buzzigoli G, Bonadonna R, Giorco MA, Oleggini M, Graziadei L, Pedrinnelli R, Brandi L, Bevilacqua S: Insulin resistance in essential hypertension. N Engl J Med 317:350–357, 1987[Abstract]
  32. Orchard TJ, Becker DJ, Bates M, Kuller LH, Drash AL: Plasma insulin and lipoprotein concentrations: an atherogenic association? Am J Epidemiol 118:326–337, 1983[Abstract/Free Full Text]
  33. Barrett-Connor E: Does hyperglycemia really cause coronary heart disease? Diabetes Care 20:1620–1623, 1997[Medline]
  34. Lehto S, Rönnemaa T, Haffner SM, Pyörälä K, Kallio V, Laakso M: Dyslipidemia and hyperglycemia predict coronary heart disease events in middle-aged patients with NIDDM. Diabetes 46:1354–1359, 1997[Abstract]
  35. Wingard DL, Barrett-Connor E: Heart disease and diabetes. In Diabetes in America. Ed 2. Bethesda, MD, NIH, NIDDK, 1995, p. 429–548 (NIH publ. no. 95–1468)
  36. King H, Rewers M, for WHO Ad Hoc Diabetes Reporting Group: Global estimates for prevalence of diabetes and impaired glucose tolerance in adults. Diabetes Care 16:157–177, 1993[Abstract]
  37. Haffner SM, D’Agostino R Jr, Festa A, Bergman RN, Mykkanen L, Karter A, Saad MF, Wagenknecht LE: Low insulin sensitivity (SI = 0) in diabetic and nondiabetic subjects in the insulin resistance atherosclerosis study: is it associated with components of the metabolic syndrome and nontraditional risk factors? Diabetes Care 26:2796–2803, 2003[Abstract/Free Full Text]
  38. Ni T-C, Ader M, Bergman RN: Reassessment of glucose effectiveness and insulin sensitivity from minimal model analysis: the effect of single compartment glucose distribution assumption. Diabetes 46:1813–1821, 1997[Abstract]
  39. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner R: Homeostasis model assessment: insulin resistance and ß-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419, 1985[Medline]
  40. Van Cauter E, Polonsky KS, Scheen AJ: Roles of circadian rhythmicity and sleep in human glucose regulation. Endocr Rev 18:716–738, 1997[Abstract/Free Full Text]
  41. Olefsky JM, Reaven GM: Insulin and glucose responses to identical oral glucose tolerance test performed 48 hours apart. Diabetes 23:449–453, 1974[Medline]

Add to CiteULike CiteULike   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
 Eur Heart JHome page
D. J. Betteridge, R. A. DeFronzo, and R. J. Chilton
PROactive: time for a critical appraisal
Eur. Heart J., April 2, 2008; 29(8): 969 - 983.
[Abstract] [Full Text] [PDF]

Home page
 Arch NeurolHome page
N. M. Lalic, J. Maric, M. Svetel, A. Jotic, E. Stefanova, K. Lalic, N. Dragasevic, T. Milicic, L. Lukic, and V. S. Kostic
Glucose Homeostasis in Huntington Disease: Abnormalities in Insulin Sensitivity and Early-Phase Insulin Secretion
Arch Neurol, April 1, 2008; 65(4): 476 - 480.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
F. E. Hirai, S. E. Moss, B. E.K. Klein, and R. Klein
Relationship of Glycemic Control, Exogenous Insulin, and C-Peptide Levels to Ischemic Heart Disease Mortality Over a 16-Year Period in People With Older-Onset Diabetes: The Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR)
Diabetes Care, March 1, 2008; 31(3): 493 - 497.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
C. Beysen, E. J. Murphy, T. McLaughlin, T. Riiff, C. Lamendola, H. C. Turner, M. Awada, S. M. Turner, G. Reaven, and M. K. Hellerstein
Whole-Body Glycolysis Measured by the Deuterated-Glucose Disposal Test Correlates Highly With Insulin Resistance In Vivo
Diabetes Care, May 1, 2007; 30(5): 1143 - 1149.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
E. Esteve, A. Castro, A. Lopez-Bermejo, J. Vendrell, W. Ricart, and J.-M. Fernandez-Real
Serum Interleukin-6 Correlates With Endothelial Dysfunction in Healthy Men Independently of Insulin Sensitivity
Diabetes Care, April 1, 2007; 30(4): 939 - 945.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
the Metascreen Writing Committee
The Metabolic Syndrome Is a Risk Indicator of Microvascular and Macrovascular Complications in Diabetes: Results from Metascreen, a multicenter diabetes clinic-based survey
Diabetes Care, December 1, 2006; 29(12): 2701 - 2707.
[Abstract] [Full Text] [PDF]

Home page
 Arch Intern MedHome page
C.-H. Tseng
Exogenous Insulin Use and Hypertension in Adult Patients With Type 2 Diabetes Mellitus.
Arch Intern Med, June 12, 2006; 166(11): 1184 - 1189.
[Abstract] [Full Text] [PDF]

Home page
 CirculationHome page
P. W.F. Wilson, R. B. D'Agostino, H. Parise, L. Sullivan, and J. B. Meigs
Metabolic Syndrome as a Precursor of Cardiovascular Disease and Type 2 Diabetes Mellitus
Circulation, November 15, 2005; 112(20): 3066 - 3072.
[Abstract] [Full Text] [PDF]

Home page
 ANGIOLOGYHome page
A. Veiraiah
Hyperglycemia, Lipoprotein Glycation, and Vascular Disease
Angiology, July 1, 2005; 56(4): 431 - 438.
[Abstract] [PDF]

Home page
 CirculationHome page
M.R. Langenfeld, T. Forst, C. Hohberg, P. Kann, G. Lubben, T. Konrad, S.D. Fullert, C. Sachara, and A. Pfutzner
Pioglitazone Decreases Carotid Intima-Media Thickness Independently of Glycemic Control in Patients With Type 2 Diabetes Mellitus: Results From a Controlled Randomized Study
Circulation, May 17, 2005; 111(19): 2525 - 2531.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Endocrinol. Metab.Home page
C. K. Sites, G. D. L'Hommedieu, M. J. Toth, M. Brochu, B. C. Cooper, and P. A. Fairhurst
The Effect of Hormone Replacement Therapy on Body Composition, Body Fat Distribution, and Insulin Sensitivity in Menopausal Women: A Randomized, Double-Blind, Placebo-Controlled Trial
J. Clin. Endocrinol. Metab., May 1, 2005; 90(5): 2701 - 2707.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Endocrinol. Metab.Home page
A. M. Poynten, S. K. Gan, A. D. Kriketos, L. V. Campbell, and D. J. Chisholm
Circulating Fatty Acids, Non-High Density Lipoprotein Cholesterol, and Insulin-Infused Fat Oxidation Acutely Influence Whole Body Insulin Sensitivity in Nondiabetic Men
J. Clin. Endocrinol. Metab., February 1, 2005; 90(2): 1035 - 1040.
[Abstract] [Full Text] [PDF]

Home page
 Arterioscler. Thromb. Vasc. Bio.Home page
S. B. Seidelmann, C. De Luca, R. L. Leibel, J. L. Breslow, A. R. Tall, and C. L. Welch
Quantitative Trait Locus Mapping of Genetic Modifiers of Metabolic Syndrome and Atherosclerosis in Low-Density Lipoprotein Receptor-Deficient Mice: Identification of a Locus for Metabolic Syndrome and Increased Atherosclerosis on Chromosome 4
Arterioscler. Thromb. Vasc. Biol., January 1, 2005; 25(1): 204 - 210.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Rewers, M.
Right arrow Articles by Savage, P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Rewers, M.
Right arrow Articles by Savage, P.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Diabetes Diabetes Care Clinical Diabetes Diabetes Spectrum