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Circulation. 1996;93:1809-1817

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(Circulation. 1996;93:1809-1817.)
© 1996 American Heart Association, Inc.


Articles

Insulin Sensitivity and Atherosclerosis

George Howard, DrPH; Daniel H. O'Leary, MD; Daniel Zaccaro, MS; Steve Haffner, MD; Marian Rewers, MD, PhD; Richard Hamman, MD, DrPH; Joe V. Selby, MD, MPH; Mohammed F. Saad, MD; Peter Savage, MD; Richard Bergman, PhD; for the IRAS Investigators

From the Department of Public Health Sciences, Bowman Gray School of Medicine of Wake Forest University (G.H., D.Z.), Winston-Salem, NC; Department of Radiology, Tufts-New England Medical Center (D.H.O.), Boston, Mass; Division of Clinical Epidemiology, University of Texas at San Antonio (S.H.); Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center (M.R., R.H.), Denver; Division of Research, Kaiser Permanente (J.V.S.), Oakland, Calif; Division of Diabetes, Hypertension, and Nutrition, Department of Medicine, University of Southern California Medical Center (M.F.S.), Los Angeles; Division of Epidemiology and Clinical Applications, National Heart, Lung, and Blood Institute (P.S.), Bethesda, Md; and Department of Physiology and Biophysics, University of Southern California School of Medicine (R.B.), Los Angeles.

Correspondence to George Howard, DrPH, Department of Public Health Sciences, Bowman Gray School of Medicine of Wake Forest University, Medical Center Blvd, Winston Salem, NC 27157-1063. E-mail howard@phs.bgsm.wfu.edu.


*    Abstract
up arrowTop
*Abstract
down arrowIntroduction
down arrowMethods
down arrowResults
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
Background Reduced insulin sensitivity has been proposed as an important risk factor in the development of atherosclerosis. However, insulin sensitivity is related to many other cardiovascular risk factors, including plasma insulin levels, and it is unclear whether an independent role of insulin sensitivity exists. Large epidemiological studies that measure insulin sensitivity directly have not been conducted.

Methods and Results The Insulin Resistance Atherosclerosis Study (IRAS) evaluated insulin sensitivity (SI) by the frequently sampled intravenous glucose tolerance test with analysis by the minimal model of Bergman. IRAS measured intimal-medial thickness (IMT) of the carotid artery as an index of atherosclerosis by use of noninvasive B-mode ultrasonography. These measures, as well as factors that may potentially confound or mediate the relationship between insulin sensitivity and atherosclerosis, were available in relation to 398 black, 457 Hispanic, and 542 non-Hispanic white IRAS participants. There was a significant negative association between SI and the IMT of the carotid artery both in Hispanics and in non-Hispanic whites. This effect was reduced but not totally explained by adjustment for traditional cardiovascular disease risk factors, glucose tolerance, measures of adiposity, and fasting insulin levels. There was no association between SI and the IMT of the carotid artery in blacks. The association between SI and the IMT was stronger for the internal carotid artery than for the common carotid artery in all ethnic groups.

Conclusions Higher levels of insulin sensitivity are associated with less atherosclerosis in Hispanics and non-Hispanic whites but not in blacks. This effect is partially mediated by traditional cardiovascular risk factors.


Key Words: atherosclerosis • diabetes mellitus • insulin • carotid arteries


*    Introduction
up arrowTop
up arrowAbstract
*Introduction
down arrowMethods
down arrowResults
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
One large, cross-sectional study has established an association of fasting insulin levels and atherosclerosis,1 and at least two relatively small studies have shown a relationship of low SI to atherosclerosis.2 3 Low SI in this context can be defined as a relative inability of insulin to enhance glucose disposal. Insulin resistance is thought to promote atherosclerosis, in part through associated metabolic abnormalities, eg, hypertension, hyperglycemia, hyperinsulinemia, and dyslipidemia. It is important to measure insulin resistance directly and to focus future interventions on this underlying defect rather than to treat and monitor each associated abnormality separately. In fact, some drugs that effectively lower blood pressure (thiazides, ß-blockers), hyperglycemia (insulin), or lipid levels (nicotinic acid) may actually increase insulin resistance and worsen long-term outcomes. The IRAS directly measured insulin resistance in generally healthy adults and related it to subclinical atherosclerosis, with control for the levels of associated metabolic abnormalities.

Direct assessment of SI is expensive and time consuming, which makes studies of associations of SI with atherosclerosis in larger cohorts a difficult task. SI is correlated with both fasting insulin and 2-hour insulin levels after a glucose load4 5 and other "traditional" cardiovascular risk factors previously shown to cluster with SI in the insulin-resistance syndrome (Syndrome X).6 This correlation between SI and other factors related to the development of atherosclerosis makes assessment of the independent role of SI a challenge that requires a substantial sample size.

The relationship between SI and atherosclerosis may differ by ethnic group. Non-Hispanic whites are more insulin sensitive than Hispanics7 8 and blacks,8 and yet carotid wall thickness is similar or thinner in Hispanics than in non-Hispanic whites.9 SI has been shown to be related to lower blood pressure in whites but not in blacks in some10 but not all studies.11 Thus, it is possible that the relationship between SI and atherosclerosis may differ in various ethnic groups.

The IRAS is the first large epidemiological study to assess both SI and atherosclerosis directly. The study evaluated a large (1600+) triethnic (black, Hispanic, and non-Hispanic white) cohort in four US locations. The present report describes the relationship between SI and atherosclerosis as defined by the IMT of the ICA and CCA assessed by B-mode ultrasound. We hypothesized that a negative relationship exists between SI and atherosclerosis and that this relationship may be mediated by the other cardiovascular risk factors that make up the insulin-resistance syndrome, such as elevated blood pressure, larger body adiposity, and lower HDL levels. In addition, we evaluated whether the association of SI and atherosclerosis is mediated through circulating insulin.


*    Methods
up arrowTop
up arrowAbstract
up arrowIntroduction
*Methods
down arrowResults
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
The IRAS is the first large epidemiological study conducted to examine the relationship between insulin levels and SI with measures of atherosclerosis and prevalent cardiovascular disease. The study recruited a triethnic population of 1625 subjects and was conducted at four clinical centers. The San Antonio, Tex, and San Luis Valley, Colo, centers recruited Hispanics and non-Hispanic whites from two ongoing population-based studies (the San Antonio Heart Study12 and the San Luis Valley Diabetes Study,13 respectively). The Los Angeles and Oakland, Calif, centers recruited non-Hispanic whites and blacks from Kaiser Permanente, a nonprofit HMO. Recruitment was tailored to yield approximately equal numbers of participants by ethnicity, sex, and glucose tolerance categories (NIDDM, impaired glucose tolerance, and normal). Persons with impaired glucose tolerance were the most difficult to find; hence, sampling strategies were focused on methods that would maximize the number of these participants. The San Antonio and San Luis centers drew random samples from participant lists from their respective ongoing studies, which resulted in selection of a disproportionate number of participants with previously documented impaired glucose tolerance. The Oakland and Los Angeles centers enriched their sample of persons with impaired glucose tolerance by oversampling from lists of nondiabetic persons with elevated levels of fasting plasma glucose (ie, 6.1 to 7.2 mmol/L). A total of 3416 potential participants were contacted to obtain the final sample of 1625, for an overall recruitment rate of 48%. The most common reason for exclusion at the screening interview was recent use of corticosteroids (n=101). Other reasons for exclusion included insulin treatment in the previous 5 years, severe limitation of caloric intake (<3360 kJ), decompensated congestive heart failure, decompensated emphysema or chronic lung disease, unstable angina, current treatment for cancer (other than skin cancer), seizure disorder or epilepsy, pregnancy, cognitive or psychological dysfunction (interviewer assessed), or other serious illnesses. The IRAS examination required two visits conducted approximately 1 week apart, each of which lasted approximately 4 hours. The oral glucose tolerance test and ultrasound examination were conducted during the first visit, and the FSIGT was performed during the second visit. Patients were asked to fast for 12 hours before each visit. Further details of the IRAS study and the recruitment process are available elsewhere.14

This report includes only 1397 subjects because (1) the ultrasound machines were transferred from the IRAS to another NHLBI-funded project for approximately the final 2 months of patient evaluation, which resulted in deletion of 111 participants from analysis, and (2) some subjects failed to complete the FSIGT evaluation, which resulted in deletion of an additional 117 participants from analysis.

B-mode real-time ultrasound was used to assess the IMT of the carotid artery wall by use of a protocol identical to that used in the Cardiovascular Health Study.15 Briefly, a bilateral assessment of the wall thickness was made in the ICA and CCA. For the ICA, the sonographer sought the site of maximal IMT thickness in the region between the dilatation of the carotid bulb and the ICA 1 cm distal to the tip of the flow divider. For the ICA, three images were obtained (bilaterally) at the site of maximal thickness at different interrogation angles (proximal, lateral, and anterior). For the CCA, bilateral images were obtained 1 cm proximal to the dilatation of the carotid bulb at a single (lateral) angle.

Ultrasound images were recorded on videotape and transferred to a central reading facility (D.H.O., principal investigator) for measurement of the IMT. For each of the eight available images, the maximal IMT was taken over a 1-cm segment of the arterial wall distant from the skin surface ("far wall"). Two summary measures were calculated: (1) the mean of the six ICA sites and (2) the mean of the two CCA sites. To allow equal weighting of the left and right arteries in the presence of missing data, the mean value of the available measures on the left ICA and the mean value of the available measures on the right ICA were calculated, and then the mean of these two means was used in analysis. This approach is identical or similar to that used to provide an index of atherosclerosis in other epidemiological studies15 16 17 18 19 and clinical trials.20 21 22

SI was assessed by an insulin-enhanced, FSIGT (12 samples)23 24 with minimal model analysis.25 From the minimal model, insulin sensitivity is expressed as parameter SI. In the IRAS, FSIGTs were performed with insulin injection (0.03 U/kg). The patterns of insulin and glucose levels during this test were assayed by our central laboratory. These insulin and glucose values were then used to estimate the parameters of the minimal model. This model is composed of two differential equations that are implemented on the digital computer. The overall model has four parameters that are estimated from the FSIGT; it has been documented previously that the ratio of two of these parameters (p3/p2) is an accurate SI measure, which is correlated with measures obtained with the more difficult glucose clamp procedure.25 Specifically, glucose (0.3 g/kg) and insulin (0.03 U/kg) were injected intravenously at 0 and 20 minutes, respectively. Blood samples were collected at 0, 2, 4, 8, 19, 22, 30, 40, 50, 70, 100, and 180 minutes for determination of glucose and insulin levels. This modified protocol has been proved to be a valid and reliable index of SI compared with the gold standard euglycemic clamp method, both overall (r=.62) and in subsets of persons with normal (r=.53) or impaired glucose tolerance (r=.48); however, its reliability is marginally lower among diabetic subjects (r=.41).26

Linear regression was used to estimate the relation between SI and IMT. Early in the analysis, it became apparent that there were clear ethnic differences in the SI/IMT relationship verified by examining interaction terms and that the mean IMT for participants with an SI of zero was not adequately described by the simple linear relation between SI and IMT (verified by examination of regression residuals and by polynomial regression). To address the ethnic differences in the SI/IMT relation, separate linear models were fit for each of the three ethnic groups. The SI for approximately 15% of IRAS participants was estimated to be zero. Most of these individuals were known diabetics or had diabetic glucose tolerance tests at the IRAS exam. To address the nonlinearity at SI=0, we used the model:

where I is an indicator variable for SI=0 (I=1 if SI=0, I=0 otherwise), {varepsilon} is the regression error term, and ßk is the estimated regression parameter to describe the relation between SI and IMT. Given this parameterization, ß1 should be interpreted as the regression slope that describes the relation of SI and IMT among those participants with a nonzero SI value. The ß2 parameter should be interpreted as the difference between the mean IMT for participants with a 0 value for SI and the IMT expected (for SI=0) from the linear extrapolation of this relation among participants with nonzero values of SI. Whereas the primary analysis was performed for the entire IRAS cohort, confirmatory models for analysis of the diabetic and nondiabetic subgroups were also performed (see data in "Appendix").

The goal of the analysis was to assess the relation of SI and IMT and to evaluate the impact of potential confounding or mediating variables on this relation. As such, a statistical modeling approach was used in which the SI/IMT relation was first estimated after adjustment for demographic factors only. Additional potential confounders, suggested as a potential mechanism for SI, were added to this model in a stepwise manner (the order of which was determined a priori) to evaluate the potential mediating effect of these variables on the SI/IMT relation. Six models were considered. The basic model included demographic variables of age, clinical center, and sex. The second model (model 2) evaluated the SI/IMT relation after adjustment for the demographic variables plus the well-established cardiovascular risk factors of HDL cholesterol level, LDL cholesterol level, smoking status (current smoker, past smoker, or never smoker), and hypertension (systolic blood pressure >=140, diastolic blood pressure >=90, or current use of hypertensive medications). The third model (model 3) adjusted for demographic factors, established risk factors, and glucose tolerance status categorized by use of the World Heath Organization criteria27 (normal, impaired, or diabetic). The fourth model (model 4) considered the relation of SI and IMT after control for demographic factors, cardiovascular disease risk factors, glucose tolerance status, and adiposity as indexed by body mass index and waist-hip ratio. The fifth model (model 5) adjusted for all factors in model 4 and added the fasting insulin level. Finally, model 6 adjusted for all factors in model 5 and added the 2-hour insulin level; hence, this final model adjusted for demographic factors, cardiovascular risk factors, glucose tolerance status, adiposity measures, and fasting and 2-hour insulin levels.

There were clearly significant (P<=.05) interactions between SI and ethnicity noted in many models, which indicated that the SI/IMT relation differed substantially among the three ethnic groups. This interaction was not present for other demographic factors such as sex (P>.1). Because of these SI-by-ethnicity interactions, separate models fit for each of the ethnic groups are presented herein. To provide comparable models across ethnic groups, the model with an indicator variable for SI=0 (described above) was used for all analyses regardless of the statistical significance of the indicator variable.

Because the distribution of SI is right skewed (skewness=2.8), there was some concern that individuals with high SI values could exert undue influence (leverage) on the estimated SI/IMT relation. A number of analyses were conducted to ensure this was not the case, including analysis of the relation of IMT with the log of SI, deletion of the 10 most highly leveraged points (approximately 1% of the sample), and deletion of the 10 highest SI values (again, approximately 1% of the sample). Each of these alternative analyses provided results that did not differ substantially from the primary analysis (data not shown).

To compare the independent predictive value of fasting insulin levels and 2-hour insulin levels after a glucose challenge with the predictive value of SI, models that related both fasting and 2-hour insulin levels with carotid artery wall thickness were fit after demographic adjustment for each ethnic group. Because neither fasting nor 2-hour insulin levels proved to be significantly related to IMT in the demographic model, other models were not considered.


*    Results
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
*Results
down arrowDiscussion
down arrowAppendix 1
down arrowReferences
 
A description of the IRAS cohort available for the present analysis is provided in Table 1Down. Non-Hispanic white participants were more insulin sensitive and had lower body adiposity than their black or Hispanic counterparts. Black participants had higher blood pressure and lipid levels and were more likely to have been categorized as hypertensive or diabetic than either the Hispanic or non-Hispanic white participants. The highest rate of smoking was among the Hispanic participants. There were substantial ethnic differences in the mean IMT, with blacks having generally thicker carotid artery walls. Many of these differences reflect established population differences.28 We caution against making ethnic comparisons, because these differences are not adjusted for clinical center (and as such may be confounded by geography) and are of marginal importance in that analyses were performed separately for each ethnic group.


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Table 1. Descriptive Statistics for Variables Included in Regression Models for All IRAS Participants and All IRAS Participants Stratified by Ethnicity

Because the multiple metabolic abnormalities associated with diabetes could alter the relation between SI and IMT, the SI/IMT relation was examined separately within the nondiabetic (normal plus impaired glucose tolerance) and diabetic IRAS subgroups (data shown in "Appendix"; none of the coefficients for the SI=0 terms were significant, and these were omitted from the "Appendix"). Differences in the SI/IMT relation between diabetics and nondiabetics were tested via an SI-by-diabetes interaction, which proved to be significant (0.01<P<.05) only for the CCA in blacks in the demographic model (model 1). In this case, there was a statistically nonsignificant negative association between SI and CCA IMT in nondiabetic participants and a statistically nonsignificant positive association between SI and CCA IMT in diabetic participants. This single significant difference between diabetics and nondiabetics in the association between SI and IMT does not substantially affect the interpretation (because both trends were statistically nonsignificant) and could have occurred by chance alone (the interaction was of borderline significance, and a substantial number of interactions were tested, which increased the chance of spurious findings). Because there was little evidence that the SI/IMT relation differs between diabetics and nondiabetics, the emphasis of the present report is on the combined analysis.

As shown in Table 2Down and Fig 1Down, after adjustment for demographic factors (model 1), the average ICA IMT in both Hispanic and non-Hispanic white participants was {approx}30 µm thinner in association with a 1-U increase in SI (P<=.003) among those participants with nonzero SI values. The magnitude of this effect was reduced by {approx}20%, to {approx}23 µm, by statistical adjustment for major cardiovascular risk factors (model 2). The magnitude of the association between ICA IMT and SI was similar after this adjustment for non-Hispanic whites and Hispanics, and the relation remained significant for non-Hispanic whites (P=.012) and Hispanics (P=.050). Statistical adjustment for glucose tolerance status reduced the magnitude of the association by an additional 20%, to {approx}17 µm per unit difference in SI, which reduced the significance of the association for both non-Hispanic whites (P=.072) and Hispanics (P=.162). Additional statistical adjustment for adiposity (model 4), fasting insulin level (model 5), and 2-hour insulin level (model 6) had a very small effect on the estimated magnitude of association and statistical significance of the SI/ICA-IMT relation. As seen in Fig 1Down, for black participants, the relation was nonsignificant (P>.5) in the unanticipated direction that a thicker ICA IMT was associated with higher SI values in all models.


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Table 2. Estimated Regression Coefficient for SI That Predicted IMT in Models With Increasing Control for Demographic and Risk Factor Variables: All IRAS Participants



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Figure 1. Estimated difference (with 95% CI) in mean ICA IMT difference per unit difference in SI, shown by ethnic group for selected models. Solid line indicates black (Afr American) participants; short, dashed line, Hispanic participants; long, dashed line, non-Hispanic white participants (NonHisp Wh); BMI, body mass index; and WHR, waist-to-hip ratio.

For non-Hispanic whites, there was significant evidence (in all models except model 1, in which there was marginally significant evidence) that the average ICA IMT was {approx}110 µm thinner among those participants with a zero SI value than would be expected from trend on the basis of those participants with a nonzero SI value. This implied that after control for demographic factors (model 1), the average ICA IMT for non-Hispanic white participants with a zero SI was similar to that for participants with an SI of 3.2 (SI-zero coefficient/ßSI=-96.7/-30.1). For both blacks and Hispanics, there was no evidence (P>.05) that the average ICA IMT for participants with a zero SI value differed from the trend established among the participants with a nonzero SI value (P>.4).

In the CCA, the average IMT was approximately 10 µm thinner for each unit increase in SI in all three ethnic groups after control for demographic factors (see model 1 in Table 2Up and Fig 2Down), a difference that proved significant (in non-Hispanic whites) or marginally significant (in blacks or Hispanics). Adjustment for major cardiovascular risk factors (model 2) had a relatively minor impact on the magnitude of the association for the Hispanic and non-Hispanic white participants but accounted for nearly all of the association in blacks. The association between SI and CCA IMT remained significant for non-Hispanic whites after adjustment for these cardiovascular risk factors (P=.022); however, the association for Hispanics became nonsignificant (P=.256). Adjustment for glucose tolerance status, adiposity, and fasting and 2-hour insulin levels (models 3, 4, 5, and 6) accounted for most of the remaining observed association for Hispanics (P>.6). For non-Hispanic whites, adjustment for glucose tolerance status marginally reduced the magnitude of the association (P=.064). Additional adjustment for adiposity (model 4), fasting insulin level (model 5), and 2-hour insulin level (model 6) reduced the magnitude of the association to {approx}7 µm per unit difference in SI, a difference that was not statistically significant (P>.18). For the CCA IMT, participants with a zero SI differed little from the trend established among those with a nonzero SI.



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Figure 2. Estimated difference (with 95% CI) in mean CCA IMT difference per unit difference in SI, shown by ethnic group for selected models. Solid line indicates black (Afr American) participants; short, dashed line, Hispanic participants; long, dashed line, non-Hispanic white participants (NonHisp Wh); BMI, body mass index; and WHR, waist-to-hip ratio.

In Table 3Down, the relation between fasting and 2-hour insulin levels with IMT is shown. None of the models indicated a relation between insulin levels and IMT in either the CCA or ICA, and other models were not considered. Because insulin levels do not have a linear relation with glucose over the entire range of glucose tolerance from normal to diabetic, linear regression techniques may not describe the relation between insulin levels and IMT optimally. To address this concern, the relation between fasting and 2-hour insulin levels with IMT was estimated for diabetics and nondiabetics separately. Among the 24 models considered (separately for fasting and 2-hour insulin levels among two diabetes status strata, three ethnic group strata, and the CCA and ICA walls), there was a significant association (P=.03) between the 2-hour insulin level and IMT only for the CCA bed of diabetic Hispanic participants. These additional analyses failed to support the hypothesis of a link between insulin levels and IMT because they lacked a consistent pattern of significance, there was a lack of any significant finding in nondiabetics (in whom an association was more anticipated), and it was likely that this single finding was a spurious result of the relatively large number of statistical tests performed.


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Table 3. Estimated Regression Coefficient for Fasting and 2-Hour Insulin Levels in Prediction of IMT in Model 11 (All IRAS Participants)


*    Discussion
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
*Discussion
down arrowAppendix 1
down arrowReferences
 
These results indicate that for non-Hispanic whites and Hispanics, higher SI is associated with thinner IMT of the carotid artery wall. The association between decreased SI and carotid wall thickness (an indicator of atherosclerosis) is dependent in part on traditional cardiovascular risk factors, such as dyslipidemia, hypertension, and smoking, as might be predicted by studies of the insulin-resistance syndrome.6 However, the association between decreased SI and carotid wall thickness remains significant in non-Hispanic whites (and is of similar magnitude in Hispanics) even after adjustment for traditional cardiovascular risk factors, which suggests that insulin resistance may have an independent effect on atherogenesis.

The magnitude of this association in Hispanic and non-Hispanic whites is relatively large. A difference in SI equivalent to the interquartile difference (75th percentile minus 25th percentile, 2.21-0.41=1.8 min-1·µU-1 · mL-1) was associated with an estimated difference in mean ICA IMT of {approx}55 µm after adjustment for demographic factors and 32 µm after adjustment for other major cardiovascular risk factors (adiposity and fasting and 2-hour insulin levels). This contrasts with the reported difference of {approx}60 µm to 70 µm between persons with and without prevalent heart disease, hypertension, or smoking.29 30 In the IRAS data, a 60-µm difference was also seen between hypertensives and normotensives, and a difference of 90 µm was seen between current smokers and nonsmokers, after adjustment for age, ethnicity, sex, and clinic (data not shown). Therefore, moderate differences in SI were associated with differences in IMT nearly as large as those associated with many of the traditional cardiovascular risk factors.

For Hispanic and non-Hispanic white participants, statistical adjustment for a number of covariates did move the statistical relations from significance (P<=.05) to nonsignificance (P>.05) in each group. However, the consistency of the magnitude of the association for Hispanics and non-Hispanic whites across the spectrum of models considered is striking (Fig 1Up). This similarity offers an internal replication of the results. Combining the Hispanic and non-Hispanic white groups may be justified, because it has been reported that the predominant ethnic admixture of Hispanics is white.31 32 The combining of these groups is also supported by the lack of statistical evidence of an SI-by-ethnicity interaction between Hispanics and non-Hispanic whites (P>.5). When these two groups are combined, the association between SI and ICA IMT is highly significant in the most basic model with adjustment for demographic factors (regression coefficient=-28.4, P<=.0001) and remains significant up to and including the model with adjustment for demographic factors, traditional risk factors, diabetes status, and measures of adiposity (model 4; regression coefficient=-18.3, P=.028). With additional adjustment for fasting and 2-hour insulin levels (model 6), the magnitude of the SI/IMT relation is reduced marginally (regression coefficient=-17.4) and the relation becomes marginally significant (P=.058). Hence, even with adjustment for a wide range of factors that may potentially mediate the effect of SI, the magnitude of the SI/IMT relation is reduced by only 39% and marginal significance is maintained. Thus, these data suggest the observed association of increased SI with decreased IMT in the model with only demographic adjustment is not entirely mediated by associations of SI with traditional cardiovascular disease risk factors and insulin levels in Hispanics and non-Hispanic whites.

In another group of whites, Laakso and coworkers2 also reported an association between greater SI and less atherosclerosis in a case-control study of 43 normoglycemic Finns.2 In that study, the SI of 30 participants with thick CCA IMT as measured by B-mode ultrasound was contrasted with 13 control participants with thin IMT. The study by Laakso and coworkers did not adjust for cardiovascular risk factors, adiposity, or insulin levels; hence, it is most comparable to the demographic model (model 1) reported in the present study. In model 1, we found a significant (P<=.0001) association between CCA IMT and SI among non-Hispanic whites, which is consistent with the findings of Laakso et al.2 CCA IMT was also significantly correlated with SI measured by the euglycemic clamp in 25 Swedish men considered to be at high risk of atherosclerosis and 23 Swedish men considered to be at low risk of atherosclerosis.3 By stratifying for risk of atherosclerosis, this report3 "adjusted" for major cardiovascular risk factors and is most comparable to our model after adjustment for cardiovascular risk factors (model 2). We found that the association between CCA IMT and SI remained significant (P=.022) in non-Hispanic whites after adjustment for demographic and cardiovascular risk factors. The current report confirms and extends earlier findings by examination of the association between SI and IMT in larger samples from three ethnic groups before and after adjustment for additional potential confounders.

It has been suggested that higher insulin levels (either by themselves or as a reflection of higher levels of insulin resistance) are related to the development of atherosclerosis both through a direct effect on the arterial wall and indirectly through their effects on lipids and blood pressure.33 A direct mechanism for the atherogenicity of insulin could involve its ability to stimulate both lipid synthesis in arterial tissue and proliferation of arterial smooth muscle cells. Alternatively, insulin and insulin resistance have been shown to be related to a clustering of major cardiovascular risk factors that are part of the insulin-resistance syndrome that includes hypertension and dyslipidemia.6 Although our analysis showed a substantial relation for SI with IMT among non-Hispanic whites and Hispanics, we failed to document a notable relation of either fasting or 2-hour insulin levels with IMT. These data suggest that the relation of SI with atherosclerosis is stronger than that between insulin measures and atherosclerosis.

Control for lipids, hypertension, and obesity, each of which is a factor in the insulin-resistance syndrome, substantially reduced the estimated impact of SI, which suggests that these factors may be intermediate factors in the relation between SI and IMT. However, even with further adjustment for fasting and 2-hour insulin levels, approximately half of the SI/IMT relation remained unexplained. It is possible that control for hypertension, HDL cholesterol levels, LDL cholesterol levels, smoking, and glucose tolerance status provided an inadequate control for the factors in the insulin-resistance syndrome. These factors, as well as fasting and 2-hour insulin levels, are measured with error. More precise measurement and modeling may account for an additional portion of the estimated SI/IMT relation. Other risk factors, including plasma fibrinogen and plasminogen activator inhibitor-1, have been shown to be associated with insulin resistance and may contribute to the residual SI/IMT association. Alternatively, a more direct effect of SI on the development of atherosclerosis may be operative. Hence, we suggest that insulin resistance is related to the development of atherosclerosis in Hispanics and non-Hispanic whites not only through its association with factors in the insulin resistance syndrome, but also through some other mechanism.

The strength of the SI/ICA-IMT association in both Hispanics and non-Hispanic whites contrasts with that observed for blacks. For the black IRAS participants, the estimated association exists nonsignificantly in the unanticipated direction (Fig 1Up; Table 2Up). Whereas the association of SI and IMT for blacks did not differ significantly from zero (P>.5), it did differ significantly from that observed for Hispanics and non-Hispanic whites (P<.05). This difference between Hispanics/non-Hispanic whites and blacks in the association of SI and IMT is consistent with a similar difference observed in blacks and non-Hispanic whites in the association of SI and blood pressure.10 34 It has been suggested that SI and glucose tolerance status are less associated in blacks, as up to 50% of blacks with NIDDM remain insulin sensitive.34 35 In the IRAS, control for hypertension did not substantially modify the SI/IMT relation in blacks. Therefore, the mechanism for the ethnic difference in the SI/IMT relation remains unexplained.

A sizable proportion of the IRAS participants had an SI value of zero: 16% of blacks, 16% of Hispanics, and 15% of non-Hispanic whites. Most of the zero SI values were observed in diabetic participants who did not require insulin (diabetics who required insulin were excluded from the IRAS because they would respond differently to the insulin and glucose challenges used in the FSIGT). There was a tendency for the average IMT of these participants to be thinner than the IMT that would be expected on the basis of the trend estimated among the participants with a nonzero SI, although it reached statistical significance in less than half of the models considered. The underlying reasons for this finding could include at least two possibilities. First, the IRAS recruitment process could have resulted in the selection of resistant subjects who, for other, unmeasured reasons, were relatively protected from atherosclerosis. For example, the IRAS excluded all NIDDM subjects who had ever used insulin. Patients with established diabetes who have not required insulin therapy may have less severe disease and be at lower biological risk for atherosclerotic complications than their insulin-using counterparts. Similarly, persons with both low SI and NIDDM may have particularly severe atherosclerosis that would lead to early mortality or severe morbidity. The IRAS may have excluded this group by the obvious selective mortality and by exclusion of patients with unstable angina and congestive heart disease. Second, it is possible that there exists a subset of subjects who are truly very insulin resistant (as estimated by a zero SI) and who have an unknown protective mechanism to deter the development of atherosclerosis. The relatively frequent occurrence of a zero SI, particularly among diabetic participants, also has several possible explanations. These estimates may reflect an inability of the FSIGT protocol to fully stimulate insulin-sensitive tissues in some subjects. It is possible that some subjects would show no discernible response to the dose of insulin used in the FSIGT (0.03 U/kg or {approx}2 U over 3 hours) or would have an SI that is actually very close to zero at the level of insulinemia achieved during the test. Also, the frequent occurrence of a zero SI could have resulted from a failure of the analysis program (MINMOD) to achieve numerical convergence at an appropriate point on the estimation surface. A substudy is currently under way within the IRAS to further understand the factors that underlie an estimate of a zero SI. In the present report, the effect of these zero-SI participants has been removed statistically from the estimation of the relation between the measured SI and IMT among those participants with nonzero SI values by the introduction of the indicator variable for SI=0.

There were also notable differences in the SI/IMT relation between the ICA and CCA beds. These differences may reflect differences in the likelihood of atherosclerotic development at the two sites or differences in the IRAS scanning protocol between the two beds. It has been noted that development of atherosclerosis tends to begin in the region of the carotid bifurcation and then to extend in either direction (distal or proximal) to other sites.36 Therefore, in the relatively young IRAS cohort, increased IMT associated with the development of atherosclerosis is more likely to be observed in the internal carotid images, including the bifurcation region, than in the common carotid images, proximal to the dilatation of the carotid bulb. The idea that a thickened IMT associated with atherosclerosis is more likely to be observed in the ICA than the CCA is further strengthened by the IRAS scanning protocol. The ICA images are taken at the point of maximal intimal-medial thickening, whereas the CCA images were taken at a fixed point below the dilatation of the carotid bulb. Because there are established correlations between IMT at different sites within the carotid artery bed,37 the similar pattern observed in these analyses between the ICA and CCA was expected. However, the ultrasound protocol used in the ICA compared with the CCA should have higher accuracy, because a larger number of images were averaged, and it may be more likely to reflect atherosclerotic thickening, because it more actively sought "maximal thickening."

The present study has several limitations. First, the SI/IMT relation was estimated in a cross-sectional manner, and therefore causation of the protective effect of increased sensitivity cannot be addressed directly. Clearly, it is important to confirm these cross-sectional relations in a longitudinal study. Second, attempts to collect a sufficient number of IRAS participants across the spectrum of glucose tolerance did not permit the IRAS to be a strictly population-based study. We believe this is a minor concern, because the IRAS population was drawn from existing population-based studies (San Antonio Heart Study and San Luis Valley Diabetes Study) or from HMO populations (Oakland and Los Angeles, Calif), so that the population was basically representative of the general population, and the focus of the present report is on the relationship between factors measured in the study participants, rather than a description of the distribution of the factors in the general population. We also assume that cross-sectional analyses will tend to underestimate the magnitude of associations between risk factors and atherosclerosis, as did those analyses presented here, because those individuals most at risk will not be available for recruitment ("survivor" bias). Finally, we cannot rule out that there may have been misclassification of conventional cardiovascular risk factors, which would lead to an underestimation of their effect, or that other relevant confounders (eg, plasminogen activator inhibitor-1, sex hormone–binding globulin, and others) were not considered.

In conclusion, data from the initial IRAS examination indicate an inverse association between SI and atherosclerosis as assessed by measures of carotid wall thickness in Hispanics and non-Hispanic whites. This association is reduced but not completely eliminated by confounding factors, including HDL, LDL, smoking, hypertension, glucose tolerance status, body mass index, waist-hip ratio, and fasting insulin; this suggests that the association is mediated in part by the relationship of diminished SI with several established cardiovascular disease risk factors. For unknown reasons, this relationship of SI with atherosclerosis was not seen in black subjects, a finding reminiscent of the lack of association of SI with blood pressure in blacks in some studies. Longitudinal studies will be necessary to further clarify these relationships.


*    Selected Abbreviations and Acronyms
 
CCA = common carotid artery
FSIGT = frequently sampled intravenous glucose tolerance test
ICA = internal carotid artery
IMT = intimal-medial thickness
IRAS = Insulin Resistance and Atherosclerosis Study
NIDDM = non–insulin-dependent diabetes mellitus
SI = insulin sensitivity


*    Acknowledgments
 
This work was supported by NHLBI grants HL47887, HL47889, HL47890, HL47892, and HL47902 and by the General Clinical Research Centers Program (National Center for Research Resources GCRC, M01 RR431, M01 RR01346).


*    Appendix 1
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
up arrowDiscussion
*Appendix 1
down arrowReferences
 


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Table APPENDIX. Estimated Regression Coefficient for SI That Predicted IMT in Models With Increasing Control for Demographic and Risk Factor Variables: Nondiabetic and Diabetic IRAS Participants

Received October 24, 1995; revision received January 18, 1996; accepted January 22, 1996.


*    References
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
up arrowDiscussion
up arrowAppendix 1
*References
 
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