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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arch Neurol. Author manuscript; available in PMC 2010 October 14.
Published in final edited form as:
PMCID: PMC2954671

Insulin Resistance and Risk of Ischemic Stroke among Non-Diabetic Individuals from the Northern Manhattan Study



To determine the association between insulin resistance and risk of first ischemic stroke in a large multiethnic, stroke-free cohort without diagnosis of diabetes.

Research Design and Methods

A cohort of 1,509 non-diabetic participants from the Northern Manhattan Study (mean age 68±10 years; 64% women; 59% Hispanics) was analyzed for insulin sensitivity, expressed by the Homeostatic Model Assessment of Insulin Sensitivity (HOMA index = [fasting insulin (µU/ml]×[fasting glucose (mmol/L)] ÷ 22.5). Insulin resistance (IR) was defined by a HOMA-IR index in the top quartile (Q4). Cox proportional hazard models were used to determine the effect of HOMA-IR on the risk of incident ischemic stroke (IS), myocardial infarction (MI), vascular death, and combined outcomes (IS, MI, or vascular death).


The mean HOMA-IR was 2.3 ± 2.1, and Q4 was ≥2.8. During a mean follow-up of 8.5 years, vascular events occurred among 180 subjects; 46 had fatal or non-fatal ischemic stroke, 45 had fatal or non-fatal MI, and 121 died of vascular causes. The top quartile of the HOMA-IR vs. <Q4 significantly predicted the risk of ischemic stroke only [adjusted HR 2.83; 95% CI 1.34–5.99], but not other vascular events. This effect was independent of sex, race-ethnicity, traditional vascular risk factors as well of the metabolic syndrome and its components.


Insulin resistance estimated by the homeostatic model assessment is a marker of increased risk of incident stroke among non-diabetic individuals. Our findings emphasize the need to better characterize individuals at increased risk of stroke, and the potential role for primary preventive therapies targeted at insulin resistance.

Keywords: insulin resistance, incident ischemic stroke, vascular disease, cohort, prospective, population-based


Insulin resistance is a metabolic disorder characterized by diminished tissue sensitivity to insulin that originates from environmental factors such as a sedentary lifestyle, central obesity, and genetic predisposition [1]. Insulin resistance is a pivotal pathophysiologic contributor to the increased risk of cardiovascular disease (CVD) [25]. Whether insulin resistance predicts ischemic stroke is still a matter of debate [4,610]. We have yet to clarify whether insulin resistance is a risk factor for incident ischemic stroke in the general population after accounting for traditional vascular and metabolic risk factors. The gold standard for direct measurement of insulin sensitivity and secretion are the euglycemic hyperinsulinemic clamp methods, which are cumbersome and not suitable for epidemiological studies. The homeostasis model assessment (HOMA) is a widely used clinical and epidemiological tool for indirect estimates of insulin sensitivity and insulin secretion [11,12].

The aim of our study was to determine whether baseline insulin resistance estimated by the homeostasis model assessment increases risk of incident ischemic stroke, myocardial infarction (MI), and vascular death in a large, multiethnic, population-based stroke-free cohort without a diagnosis of diabetes. We have previously observed that impaired fasting glucose and the metabolic syndrome are powerful predictors of incident ischemic stroke [13,14]. The current study extends these results to the predictive effect of insulin resistance.

Research Design and Methods


The Northern Manhattan Study (NOMAS) is a prospective, population-based, cohort study of stroke incidence, risk factors, and prognosis in a multiethnic urban community. Methodology for the NOMAS study has been extensively described [15,16]. A total of 3,298 stroke-free individuals were enrolled in NOMAS between 1993 and 2001. After exclusion of individuals with previously-diagnosed diabetes or fasting glucose ≥126 mg/dl (n=705;21%), previous MI (n=244;7%), those who did not have blood samples available for fasting insulin and glucose analysis (n=1464;44%), and race-ethnicity other than Black, White, or Hispanic (n=79;%), a sample of 1,509 stroke-free individuals was included in this study.

Annual Prospective Follow-Up and Outcome Classification

Subjects were screened annually by telephone to determine any change in vital status, detect neurologic and cardiac symptoms and events, review interval hospitalizations, risk factor status, medications, and changes in functional status. Persons with positive telephone interview screens were examined in-person by the study neurologists and cardiologists. Incident ischemic stroke was the primary outcome. The secondary outcomes were incident MI, vascular death, and any vascular event, defined as incident ischemic stroke, MI, or vascular death combined. Follow-up procedures and outcome classifications were detailed previously [13,14].

Exposure Classification

Baseline blood samples, drawn after at least 12 hours of fasting, were assayed for insulin level by Immulite 2000 analyzer (Diagnostic Products Corporation, Los Angeles, CA) with manufacturer’s reagents and a solid-phase, two-site, chemiluminescent enzyme-labeled immunometric assay [11,12]. The HOMA-IR index was calculated as: fasting insulin (μU/ml)×fasting glucose (mmol/L)/ 22.5.

Covariate Definitions

Race and ethnicity were defined by self-identification based on a series of interview questions modeled after the US census [15]. The race-ethnic categorizations included Hispanic, non-Hispanic white and non-Hispanic black. Individuals of other race-ethnicity were excluded from the analyses. Hypertension was defined as a self-reported history of hypertension or a measured systolic blood pressure ≥140 or diastolic blood pressure ≥90. Smoking was categorized as non-, former, and current smoker (within one year). Moderate alcohol use was defined as current drinking of >1 drink per month and ≤2 drinks per day. Moderate to heavy physical activity level was defined as engaging in the recreational activities in a typical 14-day period. Waist circumference, LDL cholesterol, HDL cholesterol, systolic and diastolic blood pressure were examined as continuous variables. Metabolic syndrome was defined by the Third Report of the National Cholesterol Education Program: Adult Treatment Panel (NCEP ATP) III [17].

Statistical Analyses

The HOMA-IR index was examined continuously and as quartiles in order to investigate a potential dose-response relationship or a threshold effect with vascular outcomes. The prevalence of sociodemographic characteristics (age, sex, race-ethnicity, and education), traditional vascular risk factors, and other baseline variables was stratified by the HOMA-IR status at the cut-off level of the top quartile of the HOMA-IR distribution (Q4 = 2.8 or defined as the insulin resistance group).

Person-time of follow-up was accrued from the baseline to the end of the follow-up period (January of 2008), the time of outcome event, death or loss to follow-up, whichever came first. Cox proportional hazard models were used to determine the effect of insulin resistance on the risk of incident ischemic stroke as a primary outcome and on the risk of MI, vascular death, and any vascular event as secondary outcomes. Univariate age-adjusted Cox models were conducted (model 1) as well as multivariate adjusted models controlling for sociodemographic factors (age, sex race-ethnicity, high school completion; model 2), sociodemographic factors and metabolic syndrome (model 3), and sociodemographic factors, and risk factors including waist circumference, systolic and diastolic blood pressure, moderate alcohol consumption, HDL, moderate to heavy physical activity, and current/former smoking (model 4). Lastly, the two interaction terms, sex by HOMA-IR and race-ethnicity by HOMA-IR, were added to model 4 to examine potential effect modification by sex and race-ethnicity. Statistical analyses were conducted with SAS version 9.1 (SAS Institute, Cary, NC).

In addition, we examined the potential for selection bias which can result from the use of a subset of the overall study population if inclusion is jointly affected by both IR and risk of cardiovascular events. The study population analyzed in this study (n=1,509) represented a sub-sample of the full NOMAS cohort (N=3,298) with available information on HOMA and meeting all inclusion criteria. The potential for selection bias was examined by fitting logistic regression models using the observation indicators as response and follow-up times, uncensoring indicators as well as risk factors as covariates. Based on this result, we conducted an inverse probability weighting method which adjusts potential selection bias of standard Cox regression parameter estimates by weighting each record in the risk set by the inverse of the probability of observation [18].


Among 1,509 individuals free of stroke, MI and diagnosis of diabetes, the mean age was 68±11 years, 36% were male, 59% Hispanic, 21% Black, 21% White. The mean HOMA-IR index was 2.3±2.1. A value of 2.8 was a cut point value of the top quartile of the HOMA-IR index distribution (the insulin resistance group). The percentage of individuals in the top quartile of HOMA-IR was similar for men (23%) and women (26%), but varied across race-ethnic groups (15% for Whites, 22% for Blacks, and 30% for Hispanics, p<0.05). A HOMA-IR value greater than 3 was present in 23% of subjects (13% White, 18%, Black, 69% Hispanics; p<0.05).

Vascular risk factor characteristics stratified by insulin resistance (HOMA-IR Q4 and Q1–3) are presented in Table 1. Individuals in the top quartile of HOMA-IR were younger, more likely to be Hispanic, had higher blood pressure, waist circumference, BMI, triglycerides, fasting glucose, and lower HDL cholesterol. They were less likely to be moderate alcohol users and to be physically active. Table 2 presents baseline characteristics stratified by sex. Women were older and had greater BMI and LDL, while men were predominately smokers, moderate alcohol users and had higher diastolic blood pressure and waist circumference. While more women used statins, the overall use of statins was low. There was no difference in use of antiplatelets agents.

Table 1
Vascular Risk Factor Profile of the Study Population
Table 2
Vascular Risk Factor Profile Stratified by Sex

Overall, 35% of subjects had metabolic syndrome (61% of those in the top HOMA-IR quartile, and 27% in the first 3 quartiles). The proportion of individuals in the top quartile of HOMA-IR was greater among those with the metabolic syndrome (43% vs. 15% without the metabolic syndrome). In addition, the proportion of those in the top quartile of HOMA was also greater among individuals with each component of the metabolic syndrome (p<0.05), particularly for elevated fasting glucose (60% vs.23% without elevated glucose) and waist circumference (40% vs. 15% without elevated waist circumference) (data not shown).

During a mean follow-up of 8.5 years, 180 participants experienced one or more symptomatic vascular events. We observed 46 cases of fatal or non-fatal ischemic stroke, 45 fatal or non-fatal MI, and 121 vascular deaths. The incidence rate (per 1000 person years) of ischemic stroke was 3.5, myocardial infarction 3.5, and combined vascular events 14.0.

Preliminary analyses using HOMA-IR as a continuous variable did not indicate a significant association with risk of ischemic stroke (age-adjusted RR=1.04; 95% CI,0.90–1.19) or combined vascular events (age-adjusted RR=1.03; 95% CI,0.97–1.10). Analyses of HOMA-IR quartiles also did not show a dose-response relationship (shown in Table 3 for ischemic stroke only). After adjustment for covariates, a clear dose-response relationship was not apparent for ischemic stroke (model 4, trend test p-value = 0.08) or for other events (e.g. for combined vascular events in model 4, trend test p-value=0.74, data not shown). A threshold effect was observed among individuals in the 4th quartile of HOMA-IR where an elevated risk for ischemic stroke (HOMA-IR Q4 vs. Q1 age-adjusted RR=3.11; 95%CI,1.25–7.76) and for combined vascular events (HOMA-IR Q4 vs. Q1 age-adjusted RR=1.35; 95%CI,0.91–2.00, data not shown) was observed.

Table 3
The relation between HOMA-IR quartiles and risk of ischemic stroke, MI, vascular death, and combined vascular events.

The HOMA-IR Q4 vs. Q1–3 was associated with a significant 2.5 fold increased risk of ischemic stroke in the age-adjusted analysis (RR 2.47; 95%CI,.28–4.77) (Table 3). The association persisted in a model controlling for sociodemographic factors and metabolic syndrome (model 3: multivariate-adjusted RR=2.43; 95%CI,1.21–4.91); and in the model controlling for vascular risk factors (model 4: multivariate-adjusted RR 2.83; 95%CI,1.34–5.99).

The association between insulin resistance and risk of MI and vascular death as secondary outcomes (Table 3) was not significant (model 4: multivariate-adjusted RR for MI=1.77; 95%CI,0.88–3.58; for vascular death RR=1.10; 95%CI,0.69–1.74), suggesting that the effect of insulin resistance may not be as strong for MI and vascular death as for ischemic stroke risk.

The association between insulin resistance and risk of combined vascular events (Table 3) showed that individuals in the top quartile of HOMA-IR had a 45% increased risk of vascular events in the age-adjusted model (RR 1.45, 95%CI,.04–2.03). This association persisted after controlling for demographic factors, but was attenuated and no longer significant after controlling for metabolic syndrome status (model 3: RR=1.37; 95%CI,0.96–1.96) or after adjustment for vascular risk factors (model 4: RR=1.25, 95%CI,0.86–1.82).

Effect modification by sex was suggested for the association between HOMA-IR and ischemic stroke (an interaction term between the HOMA-IR Q4 and sex was significant in the multivariate-adjusted model, p<0.05). A significant association between insulin resistance and risk of ischemic stroke was observed among men (HOMA-IR Q4 vs. Q1–3 in model 4: multivariate-adjusted RR 10.86; 95%CI,3.04–38.82), but not among women (model 4: multivariate-adjusted RR 1.27, 95%CI,0.41–3.92) (data not shown). No effect modification by race-ethnicity was observed.

To test for potential inclusion bias of standard Cox regression parameter estimates, we have conducted the analysis by weighting each record in the stroke risk set by the inverse of the probability of observation, suggested that even after correcting for potential bias due to inclusion of those with available HOMA, the conclusions remained unchanged, as the association between insulin resistance (HOMA Q4) and risk of ischemic stroke remained statistically significant.


In this multiethnic, prospective, population-based cohort study of non-diabetic individuals, we report that insulin resistance estimated by a homeostasis model assessment in the fourth quartile (vs. quartiles 1–3) is associated with a 2.8-fold increased risk of first ischemic stroke, but not with other vascular events. Adjustment for established cardiovascular risk factors including glucose level, obesity and the metabolic syndrome did not attenuate the association with ischemic stroke. We also observed a stronger association between insulin resistance and first ischemic stroke among men than women, but not among any specific race-ethnic groups. Potential effect modification of this relationship by sex and race-ethnicity deserves further exploration in larger ethnically-diverse prospective cohorts.

There are several possible reasons for the stronger effect of insulin resistance on the risk of ischemic stoke than MI in current study in comparison to the other studies. First, race-ethnic disparities in the different effect of insulin resistance on the risk of stroke or MI may be one of the possible explanations. Our population-based study is comprised of predominately Hispanics in comparison to the predominately white population of the Framingham Offspring Study and the MESA [6,7]. Hispanics and Blacks in our population are at particularly greater risk of stroke than whites [19], have higher prevalence of the metabolic syndrome and a greater effect of the metabolic syndrome on the risk of stroke than MI compared to whites [16]. Hispanics and blacks also had the higher prevalence of insulin resistance than whites in this study, which might have had a greater effect on the risk of stroke than MI. Current study however, had limited power to explore predictive effect modification of insulin resistance by race-ethnicity. Second, we have excluded individuals with previous history of MI which may be another explanation for the smaller predictive effect of insulin resistance on incident MI compared to other studies which included individuals with prevalent MI. Third, insulin resistance has been associated with subclinical atherosclerosis and therefore may be more likely linked to ischemic stroke due to small or large vessel atherosclerosis than due to cardioembolism. Small and large vessel atherosclerotic strokes were more frequent ischemic stroke subtypes among Hispanics than whites in our previous study [19]. Lastly, insulin resistance is associated with hypertension, hypertriglyceridemia and low HDL (as noted in Table 1) which may be more closely and specifically linked to ischemic stroke than MI. This may be especially important in Blacks and Hispanics. Since insulin resistance drives high triglycerides and low HDL, insulin resistance may have a relatively greater effect on stroke than MI given that LDL cholesterol is less strongly related to stroke. In addition, HDL levels are lower in men than women which also might have contributed to the stroke sex-specific differential effect of insulin resistance in our study.

The risk of incident ischemic stroke in our population (adjusted HR of 2.8) is higher than reported in other population-based studies even after adjusting for the metabolic syndrome. In large population-based studies for nondiabetic patients in the highest 20th to 30th percentile of insulin resistance, the adjusted HR of stroke ranged between 1.5 and 2.6, but in most studies this effect was lost after adjusting for components of the metabolic syndrome [2,4,6,20,21]. Although a resistance to insulin action may provide the unifying mechanism of the metabolic syndrome, the results of our study suggest that the metabolic syndrome (as defined by the NCEP ATPIII) may not capture all the vascular risk associated with insulin resistance raising the possibility that other pathways influenced by insulin resistance such as inflammation may be important [22].

We have observed a greater effect of insulin resistance on risk of first ischemic stroke among men then women, although the prevalence of insulin resistance was similar. Reasons for the sex-specific differential effect remain unclear. Complex interactions between insulin resistance and sex-specific vascular risk factor profiles (e.g. smoking or higher blood pressure in men) [23,24], sex differences in insulin action [25], and its biologic effects on atherosclerotic process [26] may have accounted for the observed difference in the risk of stroke between men and women.

The strengths of our study include a prospective population-based design with thorough case ascertainment, confirmation of diagnosis, a well-documented baseline exposure, and comprehensive prospectively-collected data on established risk factors for cardiovascular disease. Our aggressive follow-up strategies resulted in less than 1% loss to follow-up. Study participants were seen in person at both study entry and follow-up, when possible, to document outcome events. The inclusion of a large multi-ethnic, elderly, heterogeneous cohort with similar geographic access to the medical center is generalizable to other multi-ethnic urban populations and allows for more valid comparisons across race-ethnic categories. However, the power to detect effect modification by race-ethnicity may be limited in the current study. Additional limitations include the potential for residual confounding, the one-time exposure measurement, and the limited statistical power of the stroke analysis. Interpretation of our results therefore must be taken with caution. Due to the lack of a dose-response relation and the possibility of chance findings, further exploration with larger datasets and more endpoints is necessary. It is likely that because of a small number of endpoints we did not observed an effect of HOMA-IR on MI. Another possible explanation may be the fact that HOMA-IR is a relatively blunt instrument for estimating reduced sensitivity to insulin although in general, HOMA-IR values correlate reasonably well with clamp-derived “gold-standard” values [27].

Our study provides evidence that insulin resistance as measured by HOMA is independently associated with an increased risk of first ischemic stroke. Insulin resistance may be a novel therapeutic target for stroke prevention. Clinical trials such as IRIS (Insulin Resistance Intervention after Stroke Trial) among stroke and TIA patients, and VA-HIT (Veterans Affairs High-Density Lipoprotein Cholesterol Intervention Trial) among patients with coronary heart disease have shown improved insulin sensitivity and beta-cell function after treatment with certain classes of drugs such as a PPARγ (peroxisome proliferator activated receptor y) agonist or cholesterol lowering drugs [5,20]. In addition to secondary stroke prevention, future studies are needed to determine if the treatment of insulin resistance can reduce the risk of incident stroke and cardiovascular disease.


Financial Disclosure: None reported.


1. Kendall DM, Harmel AP. The metabolic syndrome, type 2 diabetes, and cardiovascular disease: understanding the role of insulin resistance. Am J Manag Care. 2002;8(20 Suppl):S635–S653. [PubMed]
2. Pyorala M, Miettinen H, Laakso M, Pyorala K. Hyperinsulinemia and the risk of stroke in healthy middle-aged men: The 22-year follow-up results of the Helsinki Policemen study. Stroke. 1998;29:1860–1866. [PubMed]
3. Stamler J, Vaccaro O, Neaton JD, Wentworth D. Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care. 1993;16(2):434–444. [PubMed]
4. Folsom AR, Rasmussen ML, Chambless LE, Howard G, Cooper LS, Schmidt MI, Heiss G. Prospective associations of fasting insulin, body fat distribution, and diabetes with risk of ischemic stroke. The Atherosclerosis Risk in Communities (ARIC) study investigators. Diabetes Care. 1999;22:1077–1083. [PubMed]
5. Robins SJ, Collins D, McNamara JR, Bloomfield HE. Body weight, plasma insulin, and coronary events with gemfibrozil in the Veterans Affairs High-Density Lipoprotein Intervention Trial (VA-HIT) Atherosclerosis. 2008;196(2):849–855. [PubMed]
6. Rutter MK, Wilson PW, Sullivan LM, Fox CS, D'Agostino RB, Sr, Meigs JB. Use of alternative thresholds defining insulin resistance to predict incident type 2 diabetes mellitus and cardiovascular disease. Circulation. 2008;117(8):1003–1009. [PMC free article] [PubMed]
7. Bertoni AG, Wong ND, Shea S, Ma S, Liu K, Preethi S, Jacobs DR, Jr, Wu C, Saad MF, Szklo M. Insulin resistance, metabolic syndrome, and subclinical atherosclerosis: the Multi-Ethnic Study of Atherosclerosis (MESA) Diabetes Care. 2007;30(11):2951–2956. [PubMed]
8. Matsumoto K, Miyake S, Yano M, Ueki Y, Miyazaki A, Hirao K, Tominaga Y. Insulin resistance and classic risk factors in type 2 diabetic patients with different subtypes of ischemic stroke. Diabetes Care. 1999;22(7):1191–1195. [PubMed]
9. Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Meigs JB, Bonadonna RC, Muggeo M. Insulin resistance as estimated by homeostasis model assessment predicts incident symptomatic cardiovascular disease in caucasian subjects from the general population: the Bruneck study. Diabetes Care. 2007;30(2):318–324. [PubMed]
10. Jeppesen J, Hansen TW, Rasmussen S, Ibsen H, Torp-Pedersen C, Madsbad S. Insulin resistance, the metabolic syndrome, and risk of incident cardiovascular disease: a population-based study. J Am Coll Cardiol. 2007 May 29;49(21):2112–2119. [PubMed]
11. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412–419. [PubMed]
12. Haffner SM, Miettinen H, Stern MP. The homeostasis model in the San Antonio Heart study. Diabetes Care. 1997;20:1087–1092. [PubMed]
13. Boden-Albala B, Sacco RL, Lee HS, Grahame-Clarke C, Rundek T, Elkind MV, Wright C, Giardina EG, Di Tullio MR, Homma S, Paik MC. Metabolic syndrome and ischemic stroke risk: Northern Manhattan Study. Stroke. 2008;39(1):30–35. [PMC free article] [PubMed]
14. Boden-Albala B, Cammack S, Chong J, Wang C, Wright C, Rundek T, Elkind MS, Paik MC, Sacco RL. Diabetes, Fasting Glucose Levels, and Risk of Ischemic Stroke and Vascular Events: Findings from the Northern Manhattan Study (NOMAS) Diabetes Care. 2008;31(6):1132–1137. [PubMed]
15. Sacco RL, Boden-Albala B, Abel G, Lin IF, Elkind M, Hauser WA, Paik MC, Shea S. Race-ethnic disparities in the impact of stroke risk factors: the Northern Manhattan stroke study. Stroke. 2001;32:1725–1731. [PubMed]
16. Kargman DE, Sacco RL, Boden-Albala B, Paik MC, Hauser WA, Shea S. Validity of telephone interview data for vascular disease risk factors in a racially mixed urban community: the Northern Manhattan Stroke Study. Neuroepidemiology. 1999;18:174–184. [PubMed]
17. Expert panel on detection, evaluation and treatment of high cholesterol in adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on the detection, evaluation, and treatment of high blood cholesterol in adults (ATP III) JAMA. 2001;2001:2486–2497. [PubMed]
18. Wang CY, Chen HY. Augmented Inverse Probability Weighted Estimator for Cox Regression Missing Covariate Regression. Biometrics. 2001;57:414–419. [PubMed]
19. White H, Boden-Albala B, Wang C, Elkind MS, Rundek T, Wright CB, Sacco RL. Ischemic stroke subtype incidence among whites, blacks, and Hispanics: the Northern Manhattan Study. Circulation. 2005;111(10):1327–1331. [PubMed]
20. Kernan WN, Inzucchi SE, Viscoli CM, Brass LM, Bravata DM, Shulman GI, McVeety JC, Horwitz RI. Impaired insulin sensitivity among nondiabetic patients with a recent TIA or ischemic stroke. Neurology. 2003;13(60(9)):1447–1451. [PubMed]
21. Lakka H-M, Lakka TA, Tuomilehto J, Sivenius J, Salonen JT. Hyperinsulinemia and the risk of cardiovascular death and acute coronary and cerebrovascular events in men. Arch Intern Med. 2000;160:1160–1168. [PubMed]
22. Festa A, D'Agostino R, Jr, Howard G, Mykkanen L, Tracy RP, Haffner SM. Chronic subclinical inflammation as part of the insulin resistance syndrome: the Insulin Resistance Atherosclerosis Study (IRAS) Circulation. 2000;102(1):42–47. [PubMed]
23. Bennet AM, Brismar K, Hallqvist J, Reuterwall C, De Faire U. The risk of myocardial infarction is enhanced by a synergistic interaction between serum insulin and smoking. Eur J Endocrinol. 2002;147(5):641–647. [PubMed]
24. Nishizawa H, Shimomura I, Kishida K, Maeda N, Kuriyama H, Nagaretani H, Matsuda M, Kondo H, Furuyama N, Kihara S, Nakamura T, Tochino Y, Funahashi T, Matsuzawa Y. Androgens decrease plasma adiponectin, an insulin-sensitizing adipocyte-derived protein. Diabetes. 2002;51:2734–2741. [PubMed]
25. Blaak E. Sex differences in the control of glucose homeostasis. Curr Opin Clin Nutr Metab Care. 2008;11(4):500–504. [PubMed]
26. Rundek T, Arif H, Boden-Albala B, Elkind MS, Paik MC, Sacco RL. Carotid plaque, a subclinical precursor of vascular events: the Northern Manhattan Study. Neurology. 2008;70(14):1200–1207. [PMC free article] [PubMed]
27. Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, Monauni T, Muggeo M. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: Studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care. 2000;23:57–63. [PubMed]