OBJECTIVE—Insulin resistance, associated metabolic abnormalities, and elevated homocysteine levels are risk factors for cardiovascular disease (CVD). We examined relationships between homocysteine levels and features of insulin resistance syndrome (IRS).

RESEARCH DESIGN AND METHODS—We measured clinical characteristics, plasma levels of fasting homocysteine, folate, B vitamins, creatinine, and fasting and 2-h insulin and glucose levels after a 75-g oral glucose tolerance test in 2,214 subjects without CVD at the fifth examination (1991–1995) of the Framingham Offspring Study. After excluding 203 subjects with diabetes, the remaining 2,011 subjects were categorized as having none, one, two, or all three of the phenotypes of IRS: impaired glucose tolerance, hypertension, and/or a central metabolic syndrome (two or more traits: obesity, dyslipidemia, or hyperinsulinemia). In addition, in 1,592 subjects attending the sixth examination (1995–1998), we measured the urine albumin/creatinine ratio (UACR). Age-, sex-, creatinine-, vitamin-, and UACR-adjusted mean homocysteine levels or proportions with homocysteine >14 μmol/l in each phenotypic category and differences between categories were assessed with regression models.

RESULTS—The mean age of the subjects was 54 years (range 28–82); 55% were women, 12.3% had hyperinsulinemia, and 15.9% had two or more of the IRS phenotypes. Adjusted mean homocysteine levels were higher comparing those with hyperinsulinemia (9.8 μmol/l) and those without (9.4 μmol/l, P = 0.04) and were higher among subjects with two or more IRS phenotypes (9.9 μmol/l) compared with those with 1 or no phenotype (9.3 μmol/l, P = 0.003). Mean UACR levels were also higher among subjects with two or more IRS phenotypes (7.2 mg/g) compared with those with 1 or no phenotype (5.5 mg/g, P = 0.007).

CONCLUSIONS—Hyperhomocysteinemia and abnormal urinary albumin excretion are both associated with hyperinsulinemia and may partially account for increased risk of CVD associated with insulin resistance. Because hyperhomocysteinemia and microalbuminuria also reflect endothelial injury, these observations also support the hypothesis that endothelial dysfunction is associated with expression of the IRS.

Insulin resistance is a fundamental abnormality in the pathogenesis of type 2 diabetes and may also play a role in the development of atherosclerotic cardiovascular disease (CVD) (1,2). Insulin resistance may be an expression of diffuse arterial endothelial dysfunction contributing to atherosclerosis (3), may lead directly to arterial damage through toxic effects of hyperinsulinemia (4), or may act indirectly through atherogenic effects of the constellation of risk factors associated with the insulin resistance syndrome (IRS) (5,6). Insulin resistance or hyperinsulinemia has been associated with CVD in some but not all studies, suggesting that previously unmeasured factors may be involved in the link between hyperinsulinemia and atherosclerosis (7,8,9,10,11,12). One potential factor may be variation in plasma levels of homocysteine.

Homocysteine is a sulfur-containing amino acid formed during the metabolism of methionine. Elevated levels of homocysteine are toxic to vascular endothelium (13), inducing endothelial dysfunction and contributing to development of atherosclerosis independent of standard CVD risk factors in diabetic (14,15,16,17) and nondiabetic subjects (18,19,20). Plasma levels of insulin seem to influence homocysteine metabolism, possibly through effects on glomerular filtration or by influencing activity of key enzymes in homocysteine metabolism, including 5,10-methylenetetrahydrofolate reductase (MTHFR) or cystathione β-synthase (CBS). (21,22,23,24,25) However, most data suggest that fasting homocysteine levels are similar in subjects with type 2 diabetes and nondiabetic control subjects (26,27,28,29,30).

Although insulin resistance (or hyperinsulinemia) and hyperhomocysteinemia may both be associated with endothelial dysfunction and CVD, associations between fasting levels of insulin and homocysteine in nondiabetic or prediabetic subjects are not well characterized. In this study, we assessed the relationship between hyperinsulinemia, phenotypes of IRS, and levels of fasting homocysteine in the population-based Framingham Offspring Study. In addition, we examined associations between hyperinsulinemia, levels of homocysteine, and renal function as measured by urinary albumin excretion.

Study population

Participants were subjects of the Framingham Offspring Study, a community-based observational study of risk factors for CVDs (31). From January 1991 through June 1995 (examination cycle 5), 3,799 participants fasted overnight and underwent a standardized clinical examination; those without diagnosed diabetes underwent an oral glucose tolerance test (OGTT). Diabetes was defined as a fasting plasma glucose level ≥7.0 mmol/l at any two previous examinations, use of hypoglycemic drug therapy at any examination, or as a current fasting plasma glucose level ≥7.0 mmol/l or 2-h postchallenge glucose level ≥11.1 mmol/l (32). Prevalent CVD (coronary heart disease, peripheral vascular disease, and stroke) was defined as described previously (33).

Of 3,799 participants, we excluded 385 with prevalent CVD, 162 missing fasting insulin levels, and 1,038 missing fasting homocysteine or vitamin levels. These levels were missing because homocysteine and vitamin sample collection began after examination cycle 5 was well underway. Subjects with missing data were younger than those for whom data were not missing (53 vs. 55 years, P = 0.002), but there was no difference in the distributions of sex or IRS phenotypes comparing subjects with and without study data. We further excluded 203 subjects with diabetes because diabetes is a consequence, not a feature, of IRS; a total of 2,011 subjects remained for the main analysis. An additional 419 subjects were missing levels of urine albumin/creatinine ratio (UACR), resulting in a total of 1,592 subjects for analyses that included UACR. There were no differences in age, plasma homocysteine level, or distributions of sex or IRS phenotypes comparing those with to those without UACR data.

Laboratory methods

The total fasting homocysteine concentration in plasma was determined by high-performance liquid chromatography with fluorometric detection (34); plasma folate was measured by a microbial assay (35,36); plasma pyridoxal 5′-phosphate (PLP) was measured by the tyrosine decarboxylase apoenzyme method (37); and plasma vitamin B12 was measured by radioimmunoassay (Quantaphase II; Bio-Rad, Hercules, CA). Coefficients of variation for these assays were 8% for homocysteine, 13% for folate, 16% for PLP, and 7% for vitamin B12. Total homocysteine was measured in specimens frozen for up to 4 years at –70°C; homocysteine levels are stable over time under these conditions (38). Fasting plasma glucose was measured in fresh specimens with a hexokinase reagent kit (A-gent Glucose Test; Abbott, South Pasadena, CA). Glucose assays were run in duplicate; the intra-assay coefficient of variation was <3%. Fasting plasma triglyceride and total cholesterol levels were measured enzymatically (39), and the HDL cholesterol fraction was measured after precipitation of LDLs and VLDLs with dextran sulfate magnesium (40). The Framingham laboratory participates in the lipoprotein cholesterol laboratory standardization program administered by the Centers for Disease Control and Prevention (Atlanta, GA). Fasting insulin was measured in EDTA plasma as total immunoreactive insulin (Coat-A-Count Insulin; Diagnostic Products, Los Angeles, CA) and calibrated to serum levels for reporting purposes. Cross-reactivity of this assay with proinsulin at midcurve is ∼40%; the intra- and interassay coefficient of variation ranged from 5.0 to 10.0% for concentrations reported here, and the lower limit of sensitivity was 8 pmol/l.

Urinary albumin excretion was assessed at examination 6 (1995–1998) by the UACR. Subjects provided a single-void, early morning “spot” urine sample. The urine albumin concentration was measured by immunoturbimetry (Tina-quant Albumin Assay; Roche Diagnostics, Indianapolis, IN) and the plasma and urine creatinine concentrations using a modified Jaffe method. Coefficients of variation were 7.2% for the urine albumin assay and 2.3% for the urine creatinine assay; the lower limit of detection was 3 mg/l for albumin and 2.0 mg/dl for creatinine. The UACR is a validated, reliable, single-sample measure of urinary albumin excretion that is highly correlated with albumin excretion rates assessed by 24-h urine collection (41,42,43). We classified subjects with a UACR <30 or ≥30 mg/g.

IRS phenotype definitions

Subjects were classified with each of three basic phenotypes of the IRS using combinations of individual traits, as described previously, and then further categorized with none, one, any two, or all three of the IRS phenotypes (5). The hypertension phenotype was defined as a blood pressure >140/90 mmHg on both of two measurements or report of use of antihypertensive medication (44). The impaired glucose tolerance (IGT) phenotype was defined as impaired fasting glucose (fasting plasma glucose level ≥6.1 and <7.0 mmol/l) or impaired glucose tolerance (2-h postchallenge glucose level ≥7.8 and <11.1 mmol/l) (32). The central metabolic syndrome phenotype was defined as the presence of at least two of three central traits: obesity (either overall or central obesity), dyslipidemia (either a low HDL cholesterol level or an elevated triglyceride level), or hyperinsulinemia. Overall obesity was defined as a BMI ≥27.8 kg/m2 in men or ≥27.3 kg/m2 in women (the National Health and Nutrition Examination Survey II 85th percentiles), corresponding to ∼120% ideal body weight (45). Central obesity was defined as a waist-to-hip ratio >1.0 in men or >0.9 in women, corresponding to >85th percentile in this population. Elevated triglyceride levels were defined as a fasting level ≥2.51 mmol/l, and low HDL cholesterol levels as ≤0.91 mmol/l in men or ≤1.16 mmol/l in women (46). Hyperinsulinemia was defined as a fasting insulin level exceeding the 90th percentile of its distribution among subjects with normal glucose tolerance (corresponding to a fasting serum insulin level >94 pmol/l). Elevated levels of fasting insulin serve as reasonably reliable single-sample measures of insulin resistance in nondiabetic populations as compared with insulin resistance assessed using clamp or minimal model methods (47,48,49).

Additional clinical characteristics assessed included cigarette smoking, defined as smoking at least one cigarette per day during the year before the examination; physical activity, assessed as a weighted sum of the proportion of a typical day spent sleeping and performing sedentary, slight, moderate, or heavy physical activities (50); and extent of regular alcohol use.

Statistical analysis

We log-transformed positively skewed levels of homocysteine, insulin, triglycerides, plasma creatinine, vitamin levels, and UACR to improve normality for regression modeling, correlations, and statistical testing. We then inverse-transformed logged means and SEs to report mean (SE) levels of these analytes. We used Student’s t test or the χ2 test to compare characteristics between men and women and those with or without study data and Spearman correlation coefficients to assess crude relationships between levels of log(homocysteine) and individual IRS traits. We used linear regression models to calculate least-squares mean log (homocysteine) levels and logistic regression models (51) to predict proportions with elevated homocysteine levels (defined as a plasma level >14 μmol/l, corresponding to a level previously associated with increased risk for CVD) (52) among the various IRS phenotype combinations. Nested regression models were adjusted for age, sex, plasma levels of creatinine, folate, vitamin B12, PLP, further adjusted for levels of UACR, and further adjusted for smoking, alcohol use, and physical activity. In alternative regression models, we adjusted levels of homocysteine for sex, vitamins, and creatinine clearance using the Cockcroft-Gault equation (53). All regression models included terms for each IRS phenotype or phenotype combination; in logistic regression models, the referent group included subjects with none or one of the IRS phenotypes, and in linear regression models, type 1 error in pairwise comparisons was controlled using Tukey’s test (54). The same approach was used to predict hyperinsulinemia, UACR levels, and proportions with UACR ≥30 mg/g. Analyses were performed using SAS (55). Statistical significance was defined as a two-tailed P value <0.05.

Framingham Offspring Study subjects are of mixed European Caucasian ethnicity; this study sample was middle-aged and comprised similar proportions of men and women (Table 1). Men had higher mean levels of homocysteine than women (10.4 vs. 8.8 μmol/l, P ≤ 0.0001), but the distribution of IRS phenotypes among men and women was similar (P = 0.2). There was no interaction by sex on the effect of IRS phenotype predicting homocysteine levels (P = 0.3 for first-order interaction terms); therefore, overall sex-adjusted results are presented.

In this nondiabetic population, 15.9% of subjects had at least two IRS phenotypes, and 6.6% had all three phenotypes (Table 1). The overall prevalence of hyperinsulinemia was 12.3%, and subjects with the central metabolic syndrome alone or in combination with other phenotypes had higher fasting insulin levels than those without the central metabolic syndrome phenotype (Table 2). Subjects with ≥2 phenotypes had significantly higher fasting insulin levels (76 pmol/l) compared with those with ≤1 phenotype (31 pmol/l, P < 0.0001).

Correlations between levels of individual IRS traits and homocysteine, in descending order of magnitude, were modest overall: waist-to-hip ratio r = 0.24 (P = 0.0001), systolic blood pressure r = 0.16 (P = 0.0001), BMI r = 0.12 (P = 0.0001), HDL cholesterol r = −0.11 (P = 0.0001), fasting glucose r = 0.11 (P = 0.0001), fasting insulin r = 0.07 (P = 0.001), diastolic blood pressure r = 0.07 (P = 0.001), fasting triglycerides r = 0.03 (P = 0.3), and 2-h postchallenge glucose r = 0.01 (P = 0.6). Fasting homocysteine was more strongly correlated with plasma creatinine (r = 0.27, P = 0.0001) than with UACR (r = −0.03, P = 0.3).

Associations between IRS phenotypes and homocysteine levels or proportions with elevated levels are shown in Table 3. Subjects with the hypertension phenotype alone had higher age-, sex-, creatinine-, and vitamin-adjusted mean homocysteine levels than those without any IRS phenotype (9.9 vs. 9.3 μmol/l, P = 0.01), but otherwise, there were no significant pairwise differences in mean levels across phenotypes. Groups of subjects with the hypertension phenotype alone, in combination with the central metabolic syndrome phenotype, or those with the central metabolic syndrome and IGT phenotype together had greater proportions with elevated homocysteine levels compared with those with no IRS phenotype (all P ≤ 0.05); groups with the central metabolic syndrome and IGT phenotypes together had greater proportions with an elevated homocysteine level than those with either phenotype in isolation (all P ≤ 0.02). Removal of terms for creatinine and vitamins from predicting models had a negligible effect on the results; alternative adjustment using the Cockcroft-Gault equation somewhat strengthened associations between more complete expression of the IRS and homocysteine levels (Table 3). Associations also remained significant after additional adjustment for UACR (Fig. 1); groups with two or three phenotypes of the IRS had greater proportions of subjects with elevated homocysteine levels compared with groups with none or one of the phenotypes (14.0 vs. 9.6%, P = 0.02), as well as higher mean homocysteine levels (9.9 vs. 9.3 μmol/l, P = 0.003). There was no interaction by category of UACR on the association between IRS phenotypes and homocysteine levels (P = 0.8 for first-order interaction term), and results were not different when models were further adjusted for cigarette smoking, alcohol use, and physical activity (not shown).

As an individual trait, hyperinsulinemia was weakly associated with variation in homocysteine levels. Subjects with a fasting insulin level >94 pmol/l had slightly higher adjusted mean homocysteine levels (9.8 μmol/l) compared with those below this threshold (9.4 μmol/l, P = 0.04). We also compared homocysteine levels in the 113 excluded subjects with type 2 diabetes and UACR data with levels in the 1,592 nondiabetic subjects. Adjusted levels were similar comparing diabetic (9.6 μmol/l) with nondiabetic subjects (9.4 μmol/l, P = 0.5).

Urinary albumin excretion was also related to combinations of IRS phenotypes (Table 2). Groups with all three phenotypes had higher age- and sex-adjusted UACRs than those with no phenotypes (8.5 vs. 5.3 mg/g, P = 0.03) as well as a greater proportion with UACR >30 mg/g (16.9 vs. 7.6%, P = 0.001). Overall, groups with two or three phenotypes of the IRS had higher mean UACRs than groups with none or one of the phenotypes (7.2 vs. 5.5 mg/g, P = 0.007) and a greater proportion with UACR >30 mg/g (15.5 vs. 8.4%, P = 0.0003). As an individual trait, groups with hyperinsulinemia tended to have a greater proportion of subjects with UACR >30 mg/g (13.2%) compared with those without hyperinsulinemia (9.1%, P = 0.07). Urinary albumin excretion was not significantly associated with variation in plasma homocysteine levels. Compared with subjects with UACR ≤30 mg/g, those with UACR ≥30 mg/g had similar multivariate-adjusted mean levels of homocysteine (9.4 vs. 9.7 μmol/l with UACR >30, P = 0.2) and proportions with elevated homocysteine levels (10.2 vs. 11.4%, P = 0.6).

Interest in associations between plasma homocysteine and insulin resistance has been spurred by the search for novel metabolic factors accounting for the disturbing excess burden of CVD in type 2 diabetes and IGT (56). Although elevated homocysteine levels increase risk for CVD in type 2 diabetes patients to a greater extent than among nondiabetic subjects (14), fasting levels of homocysteine per se do not seem to be different comparing subjects with type 2 diabetes to nondiabetic control subjects in our study and in others (26,27,28,29,30) but not in all studies (57). Similar homocysteine levels in diabetes could be due to methodological differences across studies in accounting for renal function. In type 2 diabetes, glomerular filtration rate varies substantially with duration of disease (58) and is a critical determinant of plasma homocysteine levels (59,60). Data are relatively sparse on variations in homocysteine levels among subjects at increased risk for type 2 diabetes or CVD.

In this analysis of nondiabetic participants without CVD in a large, community-based population study, we found positive associations between fasting levels of plasma homocysteine and some individual traits associated with insulin resistance. Elevated levels of fasting insulin were modestly but significantly associated with fasting homocysteine, even after adjustment for several important confounders. After grouping related traits into clinical phenotypes of the IRS, mean homocysteine levels or proportions with elevated levels were not dramatically different comparing groups with different phenotypes, although groups with two or more phenotypes had significantly higher levels and greater proportions of subjects with elevated levels than groups with only one or no IRS phenotypes. Our findings suggest that insulin resistance itself was modestly associated with elevated homocysteine levels; moreover, the co-occurrence of specific features of the IRS, especially hypertension and central obesity, was associated with more marked elevations in homocysteine levels.

We also found abnormal levels of urinary albumin excretion to be a feature of the IRS, confirming findings in some (61,62,63) but not all (64) epidemiological studies. Elevated UACR was also positively correlated with serum creatinine (59,65), but control for UACR and serum creatinine did not alter associations between IRS phenotypes and homocysteine levels. However, an important limitation of our study is that UACR and serum creatinine are probably not adequately sensitive markers of true glomerular filtration rate among subjects with normal renal function (59,60). Alternative adjustment for creatinine clearance using the Cockcroft-Gault equation did not weaken but actually slightly strengthened associations between IRS phenotypes and homocysteine levels; however, validity of this equation to adjust for renal function in populations different from that in which it was originally developed is questionable (66). Also, we measured UACR ∼4 years after assessment of homocysteine levels and IRS phenotypes, further attenuating its ability to adequately control for renal dysfunction. It is possible that valid control for true glomerular filtration rate would eliminate any association between homocysteine levels and insulin resistance. This result would suggest an alternative hypothesis that insulin resistance is associated with subtle abnormalities in renal function and that modest elevations in homocysteine levels reflect subclinical renal dysfunction. The recent demonstration that hyperhomocysteinemia predicts development of microalbuminuria supports this hypothesis (67).

Abnormal renal function in insulin resistance may be a consequence of diffuse subclinical vascular injury and endothelial dysfunction (68). Elevated plasma levels of homocysteine may contribute to endothelial dysfunction by diverse mechanisms, including accelerated generation of reactive oxygen species that directly damage endothelial cells, exposing the subendothelial matrix and creating a prothrombotic environment; by impairing nitric oxide-dependent vasodilatation; and by enhancing oxidation of LDL cholesterol. (13) These mechanisms lead to atherosclerosis of the large arteries and (alone or in combination with the atherogenic effects of hypertension, smoking, and hyperlipidemia) to the subsequent expression of clinical CVD (18,19,20). Insulin resistance has been proposed to arise from similar pathogenic mechanisms in the peripheral arteriolar and capillary beds, with endothelial dysfunction in skeletal muscle, liver, and adipose tissue, and the kidney giving rise to insulin resistance and to diverse features of the IRS (3,69). This hypothesis provides a plausible mechanism directly linking hyperhomocysteinemia with insulin resistance. However, the direction of causality in this association is not clear. Hyperhomocysteinemia can induce insulin resistance (13), leading to compensatory hyperinsulinemia, which may impair activity of the MTHFR and CBS enzymes, leading to accumulation of homocysteine in plasma (25). Therefore, insulin resistance and hyperhomocysteinemia may create a deleterious feedback loop, each promoting the development and propagation of the other. Whereas the cross-sectional nature of our analysis precludes assigning cause or effect to insulin resistance or hyperhomocysteinemia, the observation that homocysteine levels are elevated in proportion to the number of phenotypes of the IRS (reflecting progressively greater insulin resistance) is consistent with a dose-response relationship between insulin resistance and homocysteine levels.

Another limitation of our study includes the lack of direct measurement of insulin resistance. Although elevated fasting insulin levels are highly correlated with insulin resistance assessed using more direct measurements, especially among normal glucose-tolerant subjects (47,48), our approach may have produced some misclassification by insulin resistance status, which would weaken observed associations and produce an underestimate of the effect of insulin resistance on homocysteine levels. The few studies in which insulin resistance in nondiabetic subjects has been assessed directly have shown either moderate positive associations with homocysteine levels (21) or no association (21,70,71). We do not have data on postmethionine challenge plasma homocysteine levels; these may be higher in patients with type 2 diabetes than in nondiabetic control subjects (27). Postchallenge homocysteine levels might be more closely associated with insulin resistance than fasting levels, given that hyperinsulinemia may affect MTHFR and CBS activity (25); the influence on plasma homocysteine levels of activity of these enzymes is most apparent with methionine challenge (72). Also, we do not have data on genetic variation in MTHFR or CBS; variation in MTHFR has been associated with a greater degree of CVD in diabetes (73) and might modify the effect of insulin resistance or hyperinsulinemia on plasma levels of homocysteine.

In conclusion, we found modest associations between hyperinsulinemia, reflecting insulin resistance, and fasting levels of plasma homocysteine. Mean homocysteine levels, or the likelihood of clinically important elevations in homocysteine levels (52), were highest among subjects with fully expressed IRS (subjects with two or three of its component phenotypes). Elevated urinary albumin excretion was also a feature of the IRS, but control for renal function using UACR and serum creatinine did not weaken associations between insulin resistance and hyperhomocysteinemia. Our data suggest that clinically important hyperhomocysteinemia and subtly abnormal renal function are both features of the IRS, potentially accounting for some of the increased risk for CVD associated with insulin resistance. These observations are also consistent with the hypothesis that endothelial dysfunction is associated with expression of the IRS. Our findings may have implications for clinical prevention. In addition to regular physical exercise, diets or dietary supplements rich in folate and B vitamins may be beneficial for lowering plasma homocysteine levels, improving insulin sensitivity, and reducing risk for development of type 2 diabetes or CVD. Controlled clinical trials are required to demonstrate definitively an association between reduced homocysteine levels, improved insulin sensitivity, and prevention of CVD outcomes.

Figure 1—

Age-, sex-, plasma creatinine-, vitamin-, and urine albumin/creatinine ratio-adjusted proportions with elevated homocysteine levels (>14 μmol/l) according to IRS phenotype. HTN, hypertension phenotype; CMS, central metabolic syndrome phenotype (≥2 of obesity, dyslipidemia, or hyperinsulinemia); IGT, impaired glucose tolerance phenotype.

Figure 1—

Age-, sex-, plasma creatinine-, vitamin-, and urine albumin/creatinine ratio-adjusted proportions with elevated homocysteine levels (>14 μmol/l) according to IRS phenotype. HTN, hypertension phenotype; CMS, central metabolic syndrome phenotype (≥2 of obesity, dyslipidemia, or hyperinsulinemia); IGT, impaired glucose tolerance phenotype.

Table 1—

Study subject characteristics

n 2,011 
Women 54.7 
Age (years) 54 (28–82) 
Fasting plasma homocysteine (μmol/l) 9.5 (1.4) 
Homocysteine >14 μmol/l 10.2 
Folate (ng/ml) 5.6 (2.0) 
Vitamin B12 (pmol/l) 396.8 (1.7) 
PLP (nmol/l) 61.0 (1.8) 
Plasma creatinine (mg/dl) 1.0 (1.2) 
UACR* 5.7 (4.5) 
 <30 90.4 
 30–300 8.9 
 >300 0.7 
Hyperinsulinemia trait 12.3 
IRS phenotype  
 None 56.3 
 Hypertension 12.5 
 IGT 4.9 
 CMS 10.3 
 Hypertension and CMS 6.0 
 Impaired glucose tolerance and CMS 3.3 
 Hypertension, IGT, and CMS 6.6 
n 2,011 
Women 54.7 
Age (years) 54 (28–82) 
Fasting plasma homocysteine (μmol/l) 9.5 (1.4) 
Homocysteine >14 μmol/l 10.2 
Folate (ng/ml) 5.6 (2.0) 
Vitamin B12 (pmol/l) 396.8 (1.7) 
PLP (nmol/l) 61.0 (1.8) 
Plasma creatinine (mg/dl) 1.0 (1.2) 
UACR* 5.7 (4.5) 
 <30 90.4 
 30–300 8.9 
 >300 0.7 
Hyperinsulinemia trait 12.3 
IRS phenotype  
 None 56.3 
 Hypertension 12.5 
 IGT 4.9 
 CMS 10.3 
 Hypertension and CMS 6.0 
 Impaired glucose tolerance and CMS 3.3 
 Hypertension, IGT, and CMS 6.6 

Data are inverse transformations of log (mean), log (SD), or %.

*

A total of 1,592 subjects contributed UACR data;

>90th percentile fasting insulin in normal glucose tolerance. CMS, central metabolic syndrome.

Table 2—

Fasting insulin and urine albumin/creatinine levels by IRS phenotype

IRS phenotypes
NoneHTN onlyIGT onlyCMS onlyCMS and HTNCMS and IGTCMS, HTN, and IGT
n 1,133 252 99 208 120 67 132 
Mean fasting serum insulin (pmol/l) 26 (6.1) 6 35 (6.3)* 6 31 (6.5) 6 64 (6.3)* 6 83 (6.4)* 6 85 (6.6)* 6 67 (6.4)* 
Hyperinsulinemia 2.2 3.6 2.2 30.2* 50.1* 56.6* 37.0* 
Number with UACR 900 195 73 167 95 53 109 
Mean UACR (mg/g) 5.3 (1.1) 7.0 (1.1) 6.1 (1.2) 4.5 (1.1) 6.2 (1.1) 7.0 (1.2) 8.5 (1.2) 
UACR >30 mg/g 7.6 11.3 8.4 8.0 13.8 16.1 16.9§ 
IRS phenotypes
NoneHTN onlyIGT onlyCMS onlyCMS and HTNCMS and IGTCMS, HTN, and IGT
n 1,133 252 99 208 120 67 132 
Mean fasting serum insulin (pmol/l) 26 (6.1) 6 35 (6.3)* 6 31 (6.5) 6 64 (6.3)* 6 83 (6.4)* 6 85 (6.6)* 6 67 (6.4)* 
Hyperinsulinemia 2.2 3.6 2.2 30.2* 50.1* 56.6* 37.0* 
Number with UACR 900 195 73 167 95 53 109 
Mean UACR (mg/g) 5.3 (1.1) 7.0 (1.1) 6.1 (1.2) 4.5 (1.1) 6.2 (1.1) 7.0 (1.2) 8.5 (1.2) 
UACR >30 mg/g 7.6 11.3 8.4 8.0 13.8 16.1 16.9§ 

Data are inverse tranformations of log (mean), log (SD), or % adjusted for age and sex. HTN, hypertension; CMS, central metabolic syndrome (any two or all of obesity, dyslipidemia, or hyperinsulinemia). Hyperinsulinemia = fasting insulin >90th percentile in normal glucose tolerance. Pairwise statistical comparisons with subjects with no IRS phenoptypes as the reference group are shown for insulin and UACR; other pairwise comparisons are shown for UACR only

*

P < 0.0001;

P ≤ 0.05 compared with no IRS phenotypes;

P ≤ 0.05 compared with CMS only;

§

P < 0.001.

Table 3—

Plasma homocysteine levels by IRS phenotype

IRS phenotypes
NoneHTN onlyIGT onlyCMS onlyCMS and HTNCMS and IGTCMS, HTN, and IGT
n 1,133 252 99 208 120 67 132 
Mean homocysteine levels        
 Age- and sex-adjusted 9.3 10.2 9.4 9.4 9.8 9.9 9.7 
 Age-, sex-, creatinine-, and vitamin-adjusted 9.3 9.9 9.4 9.4 10.0 9.9 9.8 
 Sex-, vitamin-, and Cockcroft-Gault equation–adjusted 9.1 10.1§ 9.6 9.5 10.3§ 10.2* 10.2§ 
Percentage with homocysteine >14 μmol/l        
 Age- and sex-adjusted 8.8 14.2 7.9 8.3 13.8 17.6* 11.1 
 Age-, sex-, creatinine-, and vitamin-adjusted 8.9 12.6* 8.1 8.2 14* 17.9 13.2 
 Sex-, vitamin-, and Cockcroft-Gault equation–adjusted 8.0 13.4 8.5 9.3 17.0 20.2 16.6 
IRS phenotypes
NoneHTN onlyIGT onlyCMS onlyCMS and HTNCMS and IGTCMS, HTN, and IGT
n 1,133 252 99 208 120 67 132 
Mean homocysteine levels        
 Age- and sex-adjusted 9.3 10.2 9.4 9.4 9.8 9.9 9.7 
 Age-, sex-, creatinine-, and vitamin-adjusted 9.3 9.9 9.4 9.4 10.0 9.9 9.8 
 Sex-, vitamin-, and Cockcroft-Gault equation–adjusted 9.1 10.1§ 9.6 9.5 10.3§ 10.2* 10.2§ 
Percentage with homocysteine >14 μmol/l        
 Age- and sex-adjusted 8.8 14.2 7.9 8.3 13.8 17.6* 11.1 
 Age-, sex-, creatinine-, and vitamin-adjusted 8.9 12.6* 8.1 8.2 14* 17.9 13.2 
 Sex-, vitamin-, and Cockcroft-Gault equation–adjusted 8.0 13.4 8.5 9.3 17.0 20.2 16.6 

Data are inverse tranformations of log (mean), log (SD), or % adjusted as indicated (vitamins = folate, B12, and PLP levels). HTN, hypertension; CMS, central metabolic syndrome (any two or all of obesity, dyslipidemia, or hyperinsulinemia). Pairwise statistical comparisons are shown.

*

P ≤ 0.05 compared with no IRS phenotypes;

P < 0.01;

P < 0.001;

§

P < 0.0001;

P ≤ 0.05 compared with CMS only;

P ≤ 0.05 compared with IGT only.

This work was supported by a clinical research grant from the American Diabetes Association, a junior faculty development award from SmithKline Beecham, the Visiting Scientist Program (supported by ASTRA USA, Hoechst Marion Roussel, and Sevier Amerique), the U.S. Department of Agriculture under agreement no. 58-1950-9-001, and by a subcontract from the National Heart, Lung, and Blood Institute’s Framingham Heart Study, National Institutes of Health (NIH/NHLBI contract no. NO1-HC-38083). Roche Diagnostics generously donated assay reagents for measurement of urinary albumin and creatinine.

We thank Andrew Bostom, MD, MS, for helpful comments on an earlier version of this manuscript and Patricia Murphy-Sheehy, MPH, and Leslie Taylor for assistance with statistical analysis and manuscript preparation.

1.
Reaven GM: Role of insulin resistance in human disease.
Diabetes
37
:
1595
–1607,
1988
2.
Haffner SM, Valdez RA, Hazuda HP, Mitchell BD, Morales PA, Stern MP: Prospective analysis of the insulin resistance syndrome (syndrome X).
Diabetes
41
:
715
–722,
1992
3.
Pinkney JH, Stehouwer CD, Coppack SW, Yudkin JS: Endothelial dysfunction: cause of the insulin resistance syndrome.
Diabetes
46(Suppl. 2)
:
S9
–S13,
1997
4.
Stout RW: Insulin and atheroma: a 20-yr perspective.
Diabetes Care
13
:
631
–654,
1990
5.
Meigs JB, D’Agostino RB, Wilson PWF, Cupples LA, Nathan DM, Singer DE: Risk variable clustering in the insulin resistance syndrome: the Framingham Offspring Study.
Diabetes
46
:
1594
–1600,
1997
6.
Haffner SM, Stern MP, Hazuda HP, Mitchell BD, Patterson JK: Cardiovascular risk factors in confirmed prediabetic individuals. Does the clock for coronary heart disease start ticking before the onset of diabetes?
JAMA
263
:
2893
–2898,
1990
7.
Wingard DL, Barrett-Connor EL, Ferrara A: Is insulin really a heart disease risk factor?
Diabetes Care
18
:
1299
–1304,
1995
8.
Despres J-P, Lamarche B, Mauriege P, Cantin B, Dagenais GR, Moorjani S, Lupien P-J: Hyperinsulinemia as an independent risk factor for ischemic heart disease.
N Engl J Med
334
:
952
–957,
1996
9.
Pyorala M, Miettinen H, Laakso M, Pyorala 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
10.
Bonora E, Tessari R, Micciolo R, Zenere M, Targher G, Padovani R, Falezza G, Muggeo M: Intimal-medial thickness of the carotid artery in nondiabetic and NIDDM patients: relationship with insulin resistance.
Diabetes Care
20
:
627
–631,
1997
11.
Haffner SM, D’Agostino R, Mykkanen L, Hales CN, Savage PJ, Bergman RN, O’Leary D, Rewers M, Selby J, Tracy R, Saad MF: Proinsulin and insulin concentrations in relation to carotid wall thickness: Insulin Resistance Atherosclerosis Study.
Stroke
29
:
1498
–1503,
1998
12.
Rewers M, R D’Agostino J, Burke G, Zaccaro D, Selby J, Savage P: Coronary artery disease is associated with low insulin sensitivity independent of insulin levels and cardiovascular risk factors.
Diabetes
45(Suppl. 2)
:
52A
,
1996
13.
Welch GN, Loscalzo J: Homocysteine and atherothrombosis.
N Engl J Med
338
:
1042
–1050,
1998
14.
Hoogeveen EK, Kostense PJ, Beks PJ, Mackaay AJ, Jakobs C, Bouter LM, Heine RJ, Stehouwer CD: Hyperhomocysteinemia is associated with an increased risk of cardiovascular disease, especially in non-insulin-dependent diabetes mellitus: a population-based study.
Arterioscler Thromb Vasc Biol
18
:
133
–138,
1998
15.
Hoogeveen EK, Kostense PJ, Jakobs C, Dekker JM, Nijpels G, Heine RJ, Bouter LM, Stehouwer CD: Hyperhomocysteinemia increases risk of death, especially in type 2 diabetes: 5-year follow-up of the Hoorn Study.
Circulation
101
:
1506
–1511,
2000
16.
Okada E, Oida K, Tada H, Asazuma K, Eguchi K, Tohda G, Kosaka S, Takahashi S, Miyamori I: Hyperhomocysteinemia is a risk factor for coronary arteriosclerosis in Japanese patients with type 2 diabetes.
Diabetes Care
22
:
484
–490,
1999
17.
Stehouwer CD, Gall MA, Hougaard P, Jakobs C, Parving HH: Plasma homocysteine concentration predicts mortality in non-insulin-dependent diabetic patients with and without albuminuria.
Kidney Int
55
:
308
–314,
1999
18.
Boushey CJ, Beresford SA, Omenn GS, Motulsky AG: A quantitative assessment of plasma homocysteine as a risk factor for vascular disease: probable benefits of increasing folic acid intakes.
JAMA
274
:
1049
–1057,
1995
19.
Eikelboom JW, Lonn E, Genest J Jr, Hankey G, Yusuf S: Homocyst(e)ine and cardiovascular disease: a critical review of the epidemiologic evidence.
Ann Intern Med
131
:
363
–375,
1999
20.
Graham IM, Daly LE, Refsum HM, Robinson K, Brattstrom LE, Ueland PM, Palma-Reis RJ, Boers GH, Sheahan RG, Israelsson B, Uiterwaal CS, Meleady R, McMaster D, Verhoef P, Witteman J, Rubba P, Bellet H, Wautrecht JC, de Valk HW, Sales Luis AC, Parrot-Rouland FM, Tan KS, Higgins I, Garcon D, Andria G, et al: Plasma homocysteine as a risk factor for vascular disease: the European Concerted Action Project.
JAMA
277
:
1775
–1781,
1997
21.
Giltay EJ, Hoogeveen EK, Elbers JM, Gooren LJ, Asscheman H, Stehouwer CD: Insulin resistance is associated with elevated plasma total homocysteine levels in healthy, non-obese subjects.
Atherosclerosis
139
:
197
–198,
1998
22.
Jacobs RL, House JD, Brosnan ME, Brosnan JT: Effects of streptozotocin-induced diabetes and of insulin treatment on homocysteine metabolism in the rat.
Diabetes
47
:
1967
–1970,
1998
23.
Gallistl S, Sudi K, Mangge H, Erwa W, Borkenstein M: Insulin is an independent correlate of plasma homocysteine levels in obese children and adolescents.
Diabetes Care
23
:
1348
–1352,
2000
24.
Fonseca VA, Mudaliar S, Schmidt B, Fink LM, Kern PA, Henry RR: Plasma homocysteine concentrations are regulated by acute hyperinsulinemia in nondiabetic but not type 2 diabetic subjects.
Metabolism
47
:
686
–689,
1998
25.
Dicker-Brown A, Fonseca VA, Fink LM, Kern PA: The effect of glucose and insulin on the activity of enzymes in homocysteine metabolism (Abstract).
Diabetes
48(Suppl. 1)
:
A135
,
1999
26.
Drzewoski J, Czupryniak L, Chwatko G, Bald E: Total plasma homocysteine and insulin levels in type 2 diabetic patients with secondary failure to oral agents.
Diabetes Care
22
:
2097
–2099,
1999
27.
Munshi MN, Stone A, Fink L, Fonseca V: Hyperhomocysteinemia following a methionine load in patients with non-insulin-dependent diabetes mellitus and macrovascular disease.
Metabolism
45
:
133
–135,
1996
28.
Folsom AR, Nieto FJ, McGovern PG, Tsai MY, Malinow MR, Eckfeldt JH, Hess DL, Davis CE: Prospective study of coronary heart disease incidence in relation to fasting total homocysteine, related genetic polymorphisms, and B vitamins: the Atherosclerosis Risk in Communities (ARIC) study.
Circulation
98
:
204
–210,
1998
29.
Smulders YM, Rakic M, Slaats EH, Treskes M, Sijbrands EJ, Odekerken DA, Stehouwer CD, Silberbusch J: Fasting and postmethionine homocysteine levels in NIDDM: determinants and correlations with retinopathy, albuminuria, and cardiovascular disease.
Diabetes Care
22
:
125
–132,
1999
30.
Araki A, Sako Y, Ito H: Plasma homocysteine concentrations in Japanese patients with non-insulin-dependent diabetes mellitus: effect of parenteral methylcobalamin treatment.
Atherosclerosis
103
:
149
–157,
1993
31.
Kannel WB, Feinleib M, McNamara JR, Garrison RJ, Castelli WP: An investigation of coronary heart disease in families: the Framingham Offspring Study.
Am J Epidemiol
110
:
281
–290,
1979
32.
American Diabetes Association: Report of the Expert Committee on the diagnosis and classification of diabetes mellitus.
Diabetes
20
:
1183
–1197,
1997
33.
Cupples LA, D’Agostino RB: Section 34: Some risk factors related to the annual incidence of cardiovascular disease and death using pooled repeated biennial measurements: Framingham Heart Study, 30-year followup. In The Framingham Study: An Epidemiological Investigation of Cardiovascular Disease. Kannel W, Wolf P, Garrison R, Eds. Washington, DC, U.S. Dept. of Commerce, 1988
34.
Araki A, Sako Y: Determination of free and total homocysteine in human plasma by high-performance liquid chromatography with fluorescence detection.
J Chromatogr
422
:
43
–52,
1987
35.
Horne DW, Patterson D: Lactobacillus casei microbiological assay of folic acid derivatives in 96-well microtiter plates.
Clin Chem
34
:
2357
–2359,
1988
36.
Tamura T, Freeberg LE, Cornwell PE: Inhibition of EDTA of growth of Lactobacillus casei in the folate microbiological assay and its reversal by added manganese or iron.
Clin Chem
36
:
1993
,
1990
37.
Shin YS, Rasshofer R, Friedrich B, Endres W: Pyridoxal-5′-phosphate determination by a sensitive micromethod in human blood, urine and tissues; its relation to cystathioninuria in neuroblastoma and biliary atresia.
Clin Chim Acta
127
:
77
–85,
1983
38.
Ueland PM, Refsum H, Stabler SP, Malinow MR, Andersson A, Allen RH: Total homocysteine in plasma or serum: methods and clinical applications.
Clin Chem
39
:
1764
–1779,
1993
39.
McNamara JR, Schaefer EJ: Automated enzymatic standardized lipid analyses for plasma and lipid lipoprotein fractions.
Clin Chim Acta
166
:
1
–8,
1987
40.
Warnick GR, Benderson J, Albers JJ: Dextran sulfate-magnesium precipitation procedure for quantitation of high-density lipoprotein cholesterol.
Clin Chem
28
:
1379
–1382,
1982
41.
Nathan DM, Rosenbaum C, Protasowicki VD: Single-void urine samples can be used to estimate quantitative microalbuminuria.
Diabetes Care
10
:
414
–418,
1987
42.
Bakker AJ: Detection of microalbuminuria: receiver operating characteristic curve analysis favors albumin-to-creatinine ratio over albumin concentration.
Diabetes Care
22
:
307
–313,
1999
43.
Zelmanovitz T, Gross JL, Oliveira JR, Paggi A, Tatsch M, Azevedo MJ: The receiver operating characteristics curve in the evaluation of a random urine specimen as a screening test for diabetic nephropathy.
Diabetes Care
20
:
516
–519,
1997
44.
Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: The sixth report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.
Arch Intern Med
157
:
2413
–2446,
1997
45.
National Institutes of Health: Health implications of obesity.
Ann Intern Med
103
:
1073
–1077,
1985
46.
National Cholesterol Education Program:
Second Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel II)
. Washington, DC, U.S. Govt. Printing Office, 1993 (NIH publ. no. 93-3095)
47.
Anderson RL, Hamman RF, Savage PJ, Saad MF, Laws A, Kades WG, Sands RE, Cefalu W: Exploration of simple insulin sensitivity measures derived from frequently sampled intravenous glucose tolerance (FSIGT) tests: the Insulin Resistance Atherosclerosis Study.
Am J Epidemiol
142
:
724
–732,
1996
48.
Laakso M: How good a marker is insulin level for insulin resistance?
Am J Epidemiol
137
:
959
–965,
1993
49.
Howard G, Bergman R, Wagenknecht LE, Haffner SM, Savage PJ, Saad MF, Laws A, D’Agostino RB Jr: Ability of alternative indices of insulin sensitivity to predict cardiovascular risk: comparison with the “minimal model.” Insulin Resistance Atherosclerosis Study (IRAS) Investigators.
Ann Epidemiol
8
:
358
–369,
1998
50.
Kannel WB, Sorlie P: Some health benefits of physical activity: the Framingham Study.
Arch Intern Med
139
:
857
–861,
1979
51.
Lee J: Covariance adjustment of rates based on the multiple logistic regression model.
J Chron Dis
34
:
415
–426,
1981
52.
Selhub J, Jacques PF, Bostom AG, D’Agostino RB, Wilson PWF, Belanger AJ, O’Leary DH, Wolf PA, Schaefer EJ, Rosenberg IH: Association between plasma homocysteine concentrations and extracranial carotid artery stenosis.
N Engl J Med
332
:
286
–291,
1995
53.
Cockcroft DW, Gault MH: Prediction of creatinine clearance from serum creatinine.
Nephron
16
:
31
–41,
1976
54.
Kramer CY: Extension of multiple range tests to group means with unequal numbers of replications.
Biometrics
12
:
309
–310,
1956
55.
SAS Institute:
SAS/STAT Version 6 User’s Guide: Statistics
. Cary, NC, SAS Institute, 1989
56.
Savage PJ: Cardiovascular complications of diabetes mellitus: what we know and what we need to know about their prevention.
Ann Intern Med
124(1 Part 2):123–126, 1996
57.
Emoto M, Kanda H, Shoji T, Kawagishi T, Komatsu M, Mori K, Tahara H, Ishimura E, Inaba M, Okuno Y, Nishizawa Y: Impact of insulin resistance and nephropathy on homocysteine in type 2 diabetes.
Diabetes Care
24
:
533
–538,
2001
58.
Nelson RG, Bennett PH, Beck GJ, Tan M, Knowler WC, Mitch WE, Hirschman GH, Myers BD: Development and progression of renal disease in Pima Indians with non-insulin-dependent diabetes mellitus: Diabetic Renal Disease Study Group.
N Engl J Med
335
:
1636
–1642,
1996
59.
Wollesen F, Brattstrom L, Refsum H, Ueland PM, Berglund L, Berne C: Plasma total homocysteine and cysteine in relation to glomerular filtration rate in diabetes mellitus.
Kidney Int
55
:
1028
–1035,
1999
60.
Bostom AG, Kronenberg F, Jacques PF, Kuen E, Ritz E, Konig P, Kraatz G, Lhotta K, Mann JFE, Muller GA, Neyer U, Riegel W, Schwenger V, Riegler P, Selhub J: Proteinuria and plasma total homocysteine levels in chronic renal disease patients with a normal range serum creatinine: critical impact of true glomerular filtration rate.
Atherosclerosis.
In press
61.
Forsblom CM, Eriksson JG, Ekstrand AV, Teppo AM, Taskinen MR, Groop LC: Insulin resistance and abnormal albumin excretion in non-diabetic first-degree relatives of patients with NIDDM.
Diabetologia
38
:
363
–369,
1995
62.
Haffner SM, Gonzales C, Valdez RA, Mykkanen L, Hazuda HP, Mitchell BD, Monterrosa A, Stern MP: Is microalbuminuria part of the prediabetic state? The Mexico City Diabetes Study.
Diabetologia
36
:
1002
–1006,
1993
63.
Mykkanen L, Zaccaro DJ, Wagenknecht LE, Robbins DC, Gabriel M, Haffner SM: Microalbuminuria is associated with insulin resistance in nondiabetic subjects.
Diabetes
47
:
793
–800,
1998
64.
Jager A, Kostense PJ, Nijpels G, Heine RJ, Bouter LM, Stehouwer CD: Microalbuminuria is strongly associated with NIDDM and hypertension, but not with the insulin resistance syndrome: the Hoorn Study.
Diabetologia
41: 694–700, 1998
65.
Fujita H, Narita T, Ito S: Abnormality in urinary protein excretion in Japanese men with impaired glucose tolerance.
Diabetes Care
22
:
823
–826,
1999
66.
Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D: A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation: Modification of Diet in Renal Disease Study Group.
Ann Intern Med
130
:
461
–470,
1999
67.
Jager A, Kostense PJ, Nijpels G, Dekker JM, Heine RJ, Bouter LM, Donker AJ, Stehouwer CD: Serum homocysteine levels are associated with the development of (micro)albuminuria: the Hoorn study.
Arterioscler Thromb Vasc Biol
21
:
74
–81,
2001
68.
Deckert T, Feldt-Rasmussen B, Borch-Johnsen K, Jensen T, Kofoed-Enevoldsen A: Albuminuria reflects widespread vascular damage: the Steno hypothesis.
Diabetologia
32
:
219
–226,
1989
69.
Serne EH, Stehouwer CD, ter Maaten JC, ter Wee PM, Rauwerda JA, Donker AJ, Gans RO: Microvascular function relates to insulin sensitivity and blood pressure in normal subjects.
Circulation
99
:
896
–902,
1999
70.
Abbasi F, Facchini F, Humphreys MH, Reaven GM: Plasma homocysteine concentrations in healthy volunteers are not related to differences in insulin-mediated glucose disposal.
Atherosclerosis
146
:
175
–178,
1999
71.
Godsland IF, Rosankiewicz JR, Proudler AJ, Johnston DG: Plasma total homocysteine concentrations are unrelated to insulin sensitivity and components of the metabolic syndrome in healthy men.
J Clin Endocrinol Metab
86
:
719
–723,
2001
72.
Dudman NP, Wilcken DE, Wang J, Lynch JF, Macey D, Lundberg P: Disordered methionine/homocysteine metabolism in premature vascular disease: its occurrence, cofactor therapy, and enzymology.
Arterioscler Thromb
13
:
1253
–1260,
1993
73.
Arai K, Yamasaki Y, Kajimoto Y, Watada H, Umayahara Y, Kodama M, Sakamoto K, Hori M: Association of methylenetetrahydrofolate reductase gene polymorphism with carotid arterial wall thickening and myocardial infarction risk in NIDDM.
Diabetes
46
:
2102
–2104,
1997

Address correspondence and reprint requests to James B. Meigs, MD, MPH, General Medicine Division, Massachusetts General Hospital, 50 Staniford St., 9th Floor, Boston, MA 02114. E-mail: jmeigs@partners.org.

Received for publication 21 November 2000 and accepted in revised form 12 April 2001.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture.

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