Obesity and Coronary Artery Calcium in Diabetes:
The Coronary Artery Calcification
in Type 1 Diabetes (CACTI) Study
Ticiana C. Rodrigues, M.D.,1,2Adrienne M. Veyna, M.P.H.,1Michelle D. Haarhues, M.A.,1
Gregory L. Kinney, M.P.H.,1Marian Rewers, M.D., Ph.D.,1,3and Janet K. Snell-Bergeon, Ph.D.1
Background: The aim was to examine whether excess weight is associated with coronary artery calcium (CAC),
independent of metabolic parameters in adults with type 1 diabetes (T1D).
Methods: Subjects between 19 and 56 years of age with T1D (n=621) from the Coronary Artery Calcification in
Type 1 Diabetes study were classified as abnormal on four metabolic parameters: blood pressure ‡130/85mm
Hg or on antihypertensive treatment; high-density lipoprotein-cholesterol of <40mg/dL for men or <50mg/dL
for women; triglycerides of ‡150mg/dL; or C-reactive protein of ‡3lg/mL. Study participants with two or
more abnormal parameters were classified as metabolically abnormal. Weight categories by body mass index
were normal (<25kg/m2), overweight (25 to <30kg/m2), and obese (‡30kg/m2). CAC was measured at two
visits 6.0–0.5 years apart. Progression of CAC was defined as an increase in square root transformed CAC
volume of ‡2.5mm3or development of clinical coronary artery disease.
Results: Among subjects with T1D, 48% of normal, 61% of overweight, and 73% of obese participants were
classified as metabolically abnormal (P<0.0001). Overweight and obesity were independently associated with
presence of CAC, independent of presence of metabolically abnormal. Obesity but not overweight was asso-
ciated with CAC progression, independent of the other cardiovascular risk factors.
Conclusions: Although obesity is known to increase cardiovascular disease risk through inducing metabolic
abnormalities such as dyslipidemia, hypertension, and inflammation, it is also a strong predictor of subclinical
atherosclerosis progression in adults with T1D independent of these factors.
risk is mediated through the effects of obesity on hyperten-
sion, inflammation, dyslipidemia, and insulin resistance.
Furthermore, it is unclear if overweight and obesity increase
cardiovascular risk in the absence of metabolic abnormalities,
especially in patients who are already at high risk for CVD,
such as adults with type 1 diabetes (T1D). Adults with T1D
are no more likely to be overweight or obese than individuals
without diabetes, in contrast to patients with type 2 diabetes,
among whom obesity is prevalent. However, excess weight is
not an exclusive concern of patients with type 2 diabetes.
Patients with T1D who gained weight after insulin intensive
therapy had lower high-density lipoprotein (HDL) levels and
besity is an important risk factor for cardiovascular
disease (CVD), but it is unclear how much of this excess
higher low-density lipoprotein (LDL) levels and blood pres-
sure than patients who did not gain weight.1T1D subjects
with higher body mass index (BMI) have more CVD risk
factors than patients with lower BMI.2–4High normal weight
was associated with worse glycemic control, higher triglyc-
erides, and higher systolic blood pressure compared with
patients with lower BMI in a Japanese population of T1D.5
Several potential sources of excess weight in T1D patients
have been suggested, including insulin therapy, low physical
activity level, and increased food intake due to fear of hypo-
glycemia.6,7Obesity has been associated with an elevated
number of CVD risk factors, elevated risk of type 2 diabetes,
in the general population.8–10However, the association be-
tween excess weight and CVD among individuals with T1D
hasbeenlesswellstudiedandmay be animportantmodifiable
1Barbara Davis Center for Childhood Diabetes and3Colorado School of Public Health, Aurora, Colorado.
2Division of Endocrinology, Clinical Hospital of Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil.
DIABETES TECHNOLOGY & THERAPEUTICS
Volume 13, Number 10, 2011
ª Mary Ann Liebert, Inc.
risk factor in this high-risk group in an environment of in-
creasing obesity worldwide.
This study examined whether excess weight is associated
with the presence and progression of coronary artery calcium
metabolic parameters in adults with T1D.
Research Design and Methods
The Coronary Artery Calcification in Type 1 Diabetes
Study is a prospective cohort study designed to determine the
causes of accelerated development and progression of coro-
nary atherosclerosis in subjects with and without diabetes.
Participants (n=1,416) completed a baseline examination in
2000–2002 and were 19–56 years of age. The study assessed
the extent of CAC in 652 participants with T1D and 764 con-
trol subjects without diabetes mellitus as reported previous-
ly.11Only the 652 subjects with T1D were included in this
analysis, as there are likely different factors contributing to
metabolic abnormalities in the setting of diabetes mellitus. All
patients with diabetes had been diagnosed when younger
than 30 years, had been treated with insulin within 1 year of
diagnosis, and had disease duration of at least 4 years at en-
rollment. Of the 652 T1D individuals enrolled at baseline, 621
participants had data on CAC progression with a mean fol-
low-up 6.0–0.5 years later.
At the time of enrollment, all participants were asymp-
tomatic for coronary artery disease and had no history of
coronary artery bypass graft surgery, myocardial infarction,
coronary angioplasty, or unstable angina. The study protocol
was reviewed and approved by the Colorado Combined In-
stitutional ReviewBoard, and informed consent was obtained
from all participants before enrollment.
Participants’ height was measured to the nearest 0.1cm
using a stadiometer, and weight was measured to the nearest
0.1kg. BMI (in kg/m2) was calculated, and weight categories
by BMI were normal (<25kg/m2), overweight (between 25
and <30kg/m2), and obese (‡30kg/m2) for all subjects.10
Minimum waist and maximum hip measurements were
obtained in duplicate, and the results were averaged. The
average was used to calculate waist to hip ratio. Resting
systolic blood pressure and diastolic blood pressure were
measured three times after subjects had been seated for
5min, and the second and the third measurements were
averaged. Participants also completed standardized ques-
tionnaires, including medical history, medication inventory,
rose angina questionnaire to assess history of chest pain,
current and past smoking status, physical activity, food
frequency, and family medical history of diabetes, CVD, and
Participants were classified as abnormal on four metabolic
parameters: blood pressure ‡130/85mm Hg or current an-
tihypertensive treatment; HDL-cholesterol of <40mg/dL for
men or <50mg/dLfor women;triglycerides of ‡150mg/dL;
and C-reactive protein (CRP) of ‡3lg/mL (patients with
CRP ‡10lg/L were excluded). Study participants with two
or more abnormal parameters were classified as having
metabolic abnormality (MA).
After subjects fasted overnight for 12h, blood was col-
lected and centrifuged, and separated plasma was stored at
4?C until assayed. Total plasma cholesterol and triglyceride
levels were measured using standard enzymatic methods,
HDL-cholesterol was separated using dextran sulfate, and
LDL-cholesterol was calculated using the Friedewald for-
mula. High-performance liquid chromatography was used
to measure glycosylated hemoglobin (Variant II, Bio-Rad,
Hercules, CA). CRP was measured in the laboratory of Dr.
Russell Tracy at the University of Vermont (Colchester, VT)
with a BNII nephelometer from Dade Behring (Deerfield,
IL), using a particle-enhanced immunonepholemetric assay.
Urinary albumin was measured by radioimmunoassay, and
albumin excretion rate (AER) was determined by radioim-
munoassay; the results of two timed overnight urine col-
lections were averaged. Estimated glucose disposal rate
(eGDR) was estimated by a regression equation derived
from hyperinsulinemic euglycemic clamp studies on 24
subjects chosen to represent the full spectrum of insulin
resistance as represented by insulin resistance risk factors.12
ultrafast Imatron C-150XLP electron beam computer tomog-
raphy scanner (GE/Imatron, San Francisco, CA) to obtain two
sets of high-resolution, noncontrast, contiguous 3-mm tomo-
graphic images acquired at 100-ms exposure. Scanning started
from near the lower margin of bifurcation of the main
pulmonary artery withthe subject holding his orher breath for
35–40s and proceeded caudally. Calcified coronary artery le-
sions were identified as those with a minimum density of 130
Hounsfield units and a minimum area of three pixels
(1.03mm). A calcium score for each region was calculated by
multiplying the area by the density score (1 for 130–199, 2 for
200–299, 3 for 300–399, and 4 for >399 Hounsfield units). A
total CACscore inAgatstonunits was calculatedby adding up
scores for all slices separately for left main, left anterior des-
cending, circumflex, and right coronary arteries.13The calcium
volume score was determined by the workstation using a
standard algorithm. The scanner was recalibrated each day
with a phantom. Effective radiation dose for an electron beam
computer tomography sequence was 0.7–1.0mSV for men and
1.0–1.3mSV for women. A single technician obtained and
scored all electron beam computed tomography scans, and the
measured twice at the baseline and twice at a follow-up
6.0–0.5 years later and averaged at each visit.
Data are presented as arithmetic means and SDs for con-
tinuous variables, geometric means, and ranges for log-
transformed variables and as percentages for categorical
variables. The analysis of variance test was used for contin-
uous variables, and the v2test was used for categorical vari-
ables. The coronary calcium interpolated volume from each
scan was square root transformed to reduce the variance
across coronary calcium scores,14and the square root trans-
formed volumes were averaged for each visit. The difference
between mean square root transformed coronary calcium
992RODRIGUES ET AL.
volumes was calculated from the baseline visit to the follow-
up visit. Progression of coronary calcium was defined as an
increase in square root transformed coronary calcium volume
of ‡2.5mm3over the course of the two visits14or develop-
ment of clinical coronary artery disease between the baseline
and follow-up visit (myocardial infarction, coronary artery
bypass graft surgery, or coronary angioplasty). Triglycerides,
CRP, and AER were log transformed for these analyses.
Presence of CAC and CAC progression were used as de-
pendent variables in logistic regression models, and age, sex,
calcium volume score at baseline, AER, and presence of MA
were tested as independent variables. Additionally, we re-
placed weight category by waist or waist–hip ratio; because
they were highly correlated, each variable was included sepa-
at baseline, and presence of MA. We tested for interactions
between sex and waist and between sex and waist–hip ratio.
SAS version 9.2 (SAS Institute Inc., Cary, NC) was the
statistical program used to perform these analyses, and all
statistical tests were two sided, with P<0.05 considered sig-
The average age of the T1D subjects (n=621) was 36–9
years, and 47.7% (129 of 270) of normal, 60.6% (154 of 254) of
overweight, and 73.2% (71 of 97) of obese participants were
classified as MA (P<0.0001). The baseline characteristics of
study participants stratified by categories of weight and
presence of MA are given in Table 1. T1D normal weight
patients with MA were older and had lower HDL-cholesterol
levels, higher AER, and higher CAC score than T1D normal
weight patients without MA. Individuals who were over-
weight/obese and had MA had higher insulin dose and
higher AER levels than those without MA. Hypertension,
higher glycosylated hemoglobin, higher triglyceride levels,
and higher CRP levels were associated with MA in all groups
of T1D compared with those without MA. Patients with MA
had lower eGDR than patients without MA independently of
the weight categories. Hypertension was the most common
MA, as it was present in 269 subjects; CRP ‡3lg/dL was
present in 98 subjects, elevated triglycerides (‡150mg/dL)
were found in 70 subjects, and low HDL (<40mg/dL for men
and <50mg/dL for women) was present in 145 subjects. In
the entire group, 55 subjects taking angiotensin converting
enzyme inhibitors or angiotensin receptor blockers, and 133
were taking statin medication, at baseline.
Presence of CAC (CAC >0) was more prevalent among
those with excess weight in MA T1D than in MA T1D with
normal weight (Fig. 1). However, CAC progression was not
of MA status, in univariate analysis (Fig. 1).
Table 2 shows the odds for presence and progression of CAC
by metabolic status and weight category. Table 2 compares
those with normal weight with those who are obese. Over-
metabolic status, whereas obesity was associated with both
presence and progression of CAC independent of metabolic
Table 1. Characteristics of Patients According to Weight and the Presence of Metabolic Abnormality
Normal weight OverweightObese
SBP (mm Hg)
DBP (mm Hg)
Data are mean–SD values, percentages, or geometric means (interquartile interval).
aP<0.05,bP<0.0001 for metabolically abnormal versus metabolically normal.
AER, albumin excretion rate; CAC, coronary artery calcium; CRP, C-reactive protein; DBP, diastolic blood pressure; DDM, duration of
diabetes; eGDR, estimated glucose disposal rate (in mg/kg/min); GFR, glomerular filtration rate in the Modification of Diet in Renal Disease
equation; HDL, high-density lipoprotein; HTN, hypertension; INS, insulin; LDL, low-density lipoprotein; SBP, systolic blood pressure; SMK,
current smoking; TC, total cholesterol; TG, triglycerides; WHR, waist–hip ratio.
T1D, WEIGHT, AND CORONARY ARTERY CALCIUM 993
When we used waist circumference or waist–hip ratio,
replacing weight category, these markers were not associ-
ated with CAC progression in this sample of patients, and
we did not find interaction between sex and waist or waist–
Of note is that among the three groups, the change of the
weight over the 6 years was 1.97–5.5, 1.51–5.9, and
-0.06–11.20kg for normal weight, overweight, and obese,
respectively, with no difference among them (P=0.59).
Among the normal weight individuals only 54 subjects
changed from normal to overweight/obese, and this was not
associated with CAC progression. Thirty-four patients chan-
ged from overweight or obese to normal weight over 6 years,
and this weight reduction was not associated with protection
for CAC progression.
Additionally, we tested for the eGDR (a marker of insulin
resistance in T1D patients). Obesity and eGDR were predic-
tors of CAC progression (odds ratio 2.95 [95% confidence
interval 1.05–8.26], P=0.03; and odds ratio 0.06 [95% confi-
dence interval 0.006–0.60], P=0.02, respectively) in individ-
uals with MA. In individuals without MA, the association of
(odds ratio 2.14 [95% confidence interval 0.89–5.12], P=0.08)
when eGDR was added to the model.
Our data suggest that obesity predicts the presence as well
the progression of CAC, and overweight was associated with
the presence of atherosclerosis. Excess weight is not consid-
ered a typical feature of T1D, but we observed that it is fre-
quent among patients with T1D (56.7% were above normal
Several studies have shown that the aggregation of car-
diovascular risk factors in T1D subjects predicts the devel-
opment of micro- and macrovascular complications,2,3,15and
these studies showed that higher BMI is associated with more
clustering of risk factors, but they did not evaluate if the
presence of excess weight is an independent factor of the
presence of MA in association with vascular complications. In
weight group. P values are given for the difference among those with normal weight and obesity in MA and without MA
type 1 diabetes (T1D) subjects.
Presence of coronary artery calcium (CAC) >0 and progression of CAC by metabolic abnormity (MA) finding and
Table 2. Odds Ratios for Presence and Progression
of Coronary Artery Calcium Metabolic Status
and Weight Category
Presence of CAC (0vs. any CAC)
Progression of CAC*
The model was adjusted for age, sex, weight category, presence of
metabolic abnormality, and albumin excretion rate.
*Adjusted also for calcium volume score at baseline.
CAC, coronary artery calcium.
994 RODRIGUES ET AL.
this study, we observed higher prevalence of MA among the
subjects with overweight and obesity in adults with T1D.
Recently, in a study that evaluated 5,440 participants of the
National Health and Nutrition Examination Surveys 1999–
2004, the authors reported that among U.S. adults there is a
high prevalence of clustering of MA among normal weight
individuals and a high prevalence of overweight and obese
individuals who are metabolically healthy,10reinforcing the
role of obesity as heterogeneous and nonuniform in different
individuals. However,we haveshown obeseindividuals who
appear to be metabolically healthy are nevertheless at in-
creased risk for subclinical atherosclerosis.
Of note is that we observed the same prevalence of over-
weight and obesity in our sample as in the general U.S. adult
population of the same age (20–39 years) (56.7% of excess
weight in T1D vs. 57.5% in general population).16When the
that the presence of MA among normal weight individuals is
associated with older age and that the prevalence of the
metabolically healthy phenotype among obese individuals
decreased with increasing age.10T1D subjects with normal
weight and MA were older than normal weight T1D subjects
without MA, in concordance with the results of the general
As expected, the insulin dose was higher in excess weight
T1D subjects with MA compared with individuals with an
excess of weight and without MA. The association between
insulin resistance and excess weight in T1D and its effects on
the metabolic profile of these patients have been docu-
mented.1Although higher doses of insulin have been used in
obese patients, they had no better glycemic control than the
patients with lower doses. Worse insulin resistance (lower
eGDR) was associated with the presence of obesity.
There is some evidence that obesity is not associated with
an increased risk of future cardiovascular events among in-
dividuals without metabolic syndrome, but only in those
participants with MA.9,17,18In T1D, that appears to be dif-
ferent. Although we did not evaluate cardiovascular events,
we observed that overweight and obesity were associated
with the presence of atherosclerosis, assessed by CAC, and
obesity was associated with progression of CAC. These
finding were independent of the presence of MA or other
factors, including AER, a known hard-risk factor associated
with CVD in T1D. Overweight was associated with CAC
progression, but it was not independent of the presence of
the MA. These differences between the effect of overweight
and obesity on the progression of atherosclerosis could be
explained by data from the Diabetes Control and Com-
plications Trial, which showed that weight gain had no
homogeneous effect in all intensively treated group: patients
with excessive weight gain (fourth quartile of weight gain)
had an adverse lipid profile, higher blood pressure levels,
greater insulin requirements, and increased waist–hip ratio,
suggesting increased insulin resistance.1Our data show the
effect of obesity on the atherosclerosis process in a pro-
spective analysis. Although overweight was associated with
the presence of CAC, it may have a limited burden on the
evolution of atherosclerosis and may not be independent of
MA. Furthermore, subjects with higher weight gain in the
intensive treatment group during the Diabetes Control and
Complications Trial study had increased CRP,19a marker
associated with early atherosclerosis lesions.20Higher BMI is
associated with elevated levels of CRP;21in our sample CRP
levels were higher in the entire group of obese, indepen-
dently of the presence of MA.
Our data agree with the findings from the Pittsburgh Epi-
demiology of Diabetes Complications study cohort, which
showed that at baseline BMI (as a continuous variable) was
associated with the progression of CAC in T1D subjects.22We
evaluated excess weight as a categorical variable and believe
that this way it allows a better visualization of the impact of
obesity on the outcome and makes the interpretation of the
evaluated as a continuous variable, it still had the same as-
sociation with the outcomes (data not shown).
A possible limitation of our study is the very small group
with obesity but without MA (n=26), which did not allow for
observing the burden of obesity on CAC progression because
we had just 15 obese individuals with CAC progression.
In summary, T1D patients with excess weight and obesity
had higher odds for presence of subclinical atherosclerosis,
but only obesity was strongly associated with the progression
is known to increase CVD risk through inducing metabolic
abnormalities such as dyslipidemia, hypertension, and in-
flammation, it is also a strong predictor of subclinical ath-
erosclerosis progression in adults with T1D independent of
these factors. One possible explanation is the insulin resis-
pursued as one of the target treatments in T1D subjects, and
further studies with reduction or prevention of gain of weight
should be conducted to examine reduction/prevention of
macrovascular complication in T1D individuals.
T.C.R. wrote and edited the manuscript and contributed to
the discussion, G.K., A.M.V., and M.D.H. researched data,
and M.R. and J.K.S.-B. reviewed and edited the manuscript
and contributed to the discussion. Support for this study was
provided by grants RO1 HL61753 and RO1 HL079611 from
the National Heart, Lung and Blood Institute, National In-
stitutes of Health and by Diabetes Endocrinology Research
Center Clinical Investigation Core grant P30 DK57516. The
study was performed at the Adult General Clinical Research
Center at the University of Colorado Denver Anschutz
Medical Center supported by grant M01 RR000051 from the
National Institutes of Health, at the Barbara Davis Center for
Imaging Center in Denver. T.C.R. is the recipient of a grant
from Coordenac ¸a ˜o de Aperfeic ¸oamento de Pessoal de Nı ´vel
Superior of the Brazilian Government. J.K.S.-B. was sup-
ported by American Diabetes Association Junior Faculty
Author Disclosure Statement
The authors have nothing to disclose.
1. Purnell JQ, Hokanson JE, Marcovina SM, Steffes MW, Cleary
PA, Brunzell JD: Effect of excessive weight gain with in-
tensive therapy of type 1 diabetes on lipid levels and blood
pressure. JAMA 1998;280:140–146.
T1D, WEIGHT, AND CORONARY ARTERY CALCIUM995
2. Kilpatrick ES, Rigby AS, Atkin SL: Insulin resistance, the Download full-text
metabolic syndrome, and complication risk in type 1 dia-
betes. Diabetes Care 2007;30:707–712.
3. Pambianco G, Costacou T, Orchard TJ: The prediction of
major outcomes of type 1 diabetes: a 12-year prospective
evaluation of three separate definitions of the metabolic
syndrome and their components and estimated glucose
disposal rate. Diabetes Care 2007;30:1248–1254.
4. Laakso M, Pyorala K: Adverse effects of obesity on lipid and
lipoprotein levels in insulin-dependent and non–insulin-
dependent diabetes. Metabolism 1990;39:117–122.
5. Arai K, Yokoyama H, Okuguchi F, Yamazaki K, Takagi H,
Hirao K, Kobayashi M; Japan Diabetes Clinical Data Man-
agement Study Group: Association between body mass in-
dex and core components of metabolic syndrome in 1486
patients with type 1 diabetes mellitus in Japan (JDDM 13).
Endocr J 2008;55:1025–1032.
6. Carlson MG, Campbell PJ: Impact of obesity on insulin ac-
tion in NIDDM. Diabetes 1993;52:2623–2629.
7. Purnell JQ, Dev RK, Steffes MW, Cleary PA, Palmer JP,
Hirsch IB, Hokanson JE, Brunzell JD: Relationship of family
history of type 2 diabetes, hypoglycemia, and auto-
antibodies to weight gain and lipids with intensive and
conventional therapy in the Diabetes Control and Compli-
cations Trial. Diabetes 2003;52:2623–2629.
8. Marroquin OC, Kip KE, Kelley DE, Johnson BD, Kelsey SF,
Shaw LJ, Rogers WJ, Reis SE: Metabolic syndrome modifies
the cardiovascular risk associated with angiographic coronary
artery disease in women: a report from the Women’s Ische-
mia Syndrome Evaluation. Circulation 2004;109:706–713.
9. St-Pierre AC, Cantin B, Maurie `ge P, Bergeron J, Dagenais
GR, Despre ´s JP, Lamarche B: Insulin resistance syndrome,
body mass index and the risk of ischemic heart disease.
S, Wylie-Rosett J, Sowers MR: The obese without cardio-
metabolic risk factor clustering and the normal weight with
cardiometabolic risk factor clustering: prevalence and corre-
lates of 2 phenotypes among the US population (NHANES
1999–2004). Arch Intern Med 2008;168:1617–1624.
11. Dabelea D, Kinney G, Snell-Bergeon JK, Hokanson JE, Eckel
RH, Ehrlich J, Garg S, Hamman RF, Rewers M; Coronary
Artery Calcification in Type 1 Diabetes Study: Effect of type
1 diabetes on the gender difference in coronary artery cal-
cification: a role for insulin resistance? The Coronary Artery
Calcification in Type 1 Diabetes (CACTI) Study. Diabetes
12. Williams KV, Erbey JR, Becker D, Arslanian S, Orchard TJ:
Can clinical factors estimate insulin resistance in type 1 di-
abetes? Diabetes 2000;49:626–632.
13. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Via-
monte M Jr, Detrano R: Quantification of coronary artery
calcium using ultrafast computed tomography. J Am Coll
14. Hokanson JE, MacKenzie T, Kinney G, Snell-Bergeon JK,
Dabelea D, Ehrlich J, Eckel RH, Rewers M: Evaluating
changes in coronary artery calcium: an analytic method that
accounts for interscan variability. AJR Am J Roentgenol
15. Thorn LM, Forsblom C, Wade ´n J, Saraheimo M, Tolonen N,
Hietala K, Groop PH; Finnish Diabetic Nephropathy (Finn-
Diane) Study Group: The metabolic syndrome as a risk
factor for cardiovascular disease, mortality, and progression
of diabetic nephropathy in type 1 diabetes. Diabetes Care
16. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR,
Flegal KM: Prevalence of overweight and obesity among US
children, adolescents, and adults, 1999–2002. JAMA 2004;
17. Kip KE, Marroquin OC, Kelley DE, Johnson BD, Shaw LJ,
Bairey Merz CN, Sharaf BL, Pepine CJ, Sopko G, Reis SE;
Women’s Ischemia Syndrome Evaluation Investigators:
Clinical importance of obesity versus the metabolic syn-
drome in cardiovascular risk in women: a report from the
Women’s Ischemia Syndrome Evaluation (WISE) study.
18. Katzmarzyk PT, Janssen I, Ross R, Church TS, Blair SN: The
importance of waist circumference in the definition of met-
abolic syndrome: prospective analyses of mortality in men.
Diabetes Care 2006;29:404–409.
19. Schaumberg DA, Glynn RJ, Jenkins AJ, Lyons TJ, Rifai N,
Manson JE, Ridker PM, Nathan DM: Effect of intensive
glycemic control on levels of markers of inflammation in
type 1 diabetes mellitus in the Diabetes Control and Com-
plications Trial. Circulation 2005;111:2446–2453.
20. Hayaishi-Okano R, Yamasaki Y, Katakami N, Ohtoshi K,
Gorogawa S, Kuroda A, Matsuhisa M, Kosugi K, Nishi-
kawa N, Kajimoto Y, Hori M: Elevated C-reactive protein
associates with early-stage carotid atherosclerosis in young
subjects with type 1 diabetes. Diabetes Care 2002;25:1432–
21. Kilpatrick ES, Keevil BG, Jagger C, Spooner RJ, Small M:
Determinants of raised C-reactive protein concentration in
type 1 diabetes. QJM 2000;93:231–236.
22. Costacou T, Edmundowicz D, Prince C, Conway B, Orchard
TJ: Progression of coronary artery calcium in type 1 diabetes
mellitus. Am J Cardiol 2007;100:1543–1547.
Address correspondence to:
Janet K. Snell-Bergeon, Ph.D.
Barbara Davis Center for Childhood Diabetes
University of Colorado Denver
P.O. Box 6511, Mail Stop A-140
Aurora, CO 80045
996 RODRIGUES ET AL.