Epidemiology/Health Services/Psychosocial Research
O R I G I N A L
A R T I C L E
Joint Distribution of Non-HDL and LDL
Cholesterol and Coronary Heart Disease
Risk Prediction Among Individuals With
and Without Diabetes
JIAN LIU, MD, PHD1
CHRISTOPHER SEMPOS, PHD2
RICHARD P. DONAHUE, PHD3
JOAN DORN, PHD3
MAURIZIO TREVISAN, MD, MS3
SCOTT M. GRUNDY, MD, PHD4
OBJECTIVE — To assess coronary heart disease (CHD) risk within levels of the joint distribution of non-HDL and LDL cholesterol among individuals with and without diabetes.
RESEARCH DESIGN AND METHODS — We used four publicly available data sets for
this pooled post hoc analysis and confined the eligible subjects to white individuals aged ⱖ30
years and free of CHD at baseline (12,660 men and 6,721 women). Diabetes status was defined
as either “reported by physician-diagnosed and on medication” or having a fasting glucose level
ⱖ126 mg/dl at the baseline examination. The primary end point was CHD death. Within
diabetes categories, risk was assessed based on lipid levels (in mg/dl): non-HDL ⬍130 and LDL
⬍100 (group 1); non-HDL ⬍130 and LDL ⱖ100 (group 2); non-HDL ⱖ130 and LDL ⬍100
(group 3); and non-HDL ⱖ130 and LDL ⱖ100 (group 4). Group 1 within those without diabetes
was the overall reference group.
RESULTS — Of the subjects studied, ⬃6% of men and 4% of women were defined as having
diabetes. A total of 773 CHD deaths occurred during the average 13 years of follow-up time. A
Cox proportional hazard model was used to estimate the relative risk (RR) of CHD death. Those
with diabetes had a 200% higher RR than those without diabetes. In a multivariate model, CHD
risk in those with diabetes did not increase with increasing LDL, whereas it did increase with
increasing non-HDL: RR (95% confidence interval) for group 1: 5.7 (2.0 –16.8); group 2: 5.7
(1.6 –20.7); group 3: 7.2 (2.6 –19.8); and group 4: 7.1 (3.7–13.6).
CONCLUSIONS — Non-HDL is a stronger predictor of CHD death among those with diabetes than LDL and should be given more consideration in the clinical approach to risk reduction
among diabetic patients.
Diabetes Care 28:1916 –1921, 2005
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
From 1Brock University, Ontario, Canada; the 2National Institutes of Health, Bethesda, Maryland; the 3State
University of New York at Buffalo, Buffalo, New York; and the 4University of Texas Southwestern Medical
Center at Dallas, Dallas, Texas.
Address correspondence and reprint requests to Jian Liu, MD, PhD, Community Health Sciences, Faculty
of Applied Health Sciences, Brock University, St. Catharines, ON L2S 3A1, Canada. E-mail: [email protected].
Received for publication 24 February 2005 and accepted in revised form 11 May 2005.
S.M.G. has received honoraria from Pfizer, Sankyo, Schering Plough, Fournier, Bristol-Myers Squibb, and
AstraZeneca and honoraria and grant support from Merk, Abbott, and Kos.
Additional information for this article can be found in an online appendix at http://care.
diabetesjournals.org.
Abbreviations: ADA, American Diabetes Association; ATP III, Adult Treatment Panel III; CHD, coronary
heart disease; CVD, cardiovascular disease; FCS, Framingham Cohort Study; FOS, Framingham Offspring
Study; LRCF, Lipid Research Clinics Prevalence Follow-up Study; MRFIT, Multiple Risk Factors Intervention
Trial.
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion
factors for many substances.
© 2005 by the American Diabetes Association.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby
marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1916
P
atients with diabetes have more than
a 200% greater risk of cardiovascular diseases (CVDs) than nondiabetic individuals (1). Growing evidence
suggests that dyslipidemia contributes
significantly to the excess risk of CVD (2).
Retrospective subgroup analysis and
prospective studies have shown that lipid-lowering therapy can slow the progression of atherosclerosis and decrease the
risk for cardiovascular events in patients
with diabetes (3).
Common characteristic features of diabetic dyslipidemia are the elevation of
plasma triglycerides and triglyceride-rich
VLDL cholesterol, reduced HDL cholesterol, and an increased number of small
dense LDL cholesterol particles (2). Based
on epidemiology studies linking diabetic
dyslipidemia to coronary heart disease
(CHD), together with preliminary evidence from the major statin trials, the
American Diabetes Association (ADA) has
updated guidelines that outline the priorities for the treatment of dyslipidemia
among patients with diabetes (4). The National Cholesterol Education Program
Adult Treatment Panel III (ATP III) defined diabetes as a CHD risk equivalent
with an LDL treatment goal of ⬍100
mg/dl (5). Although patients are divided
into risk categories according to their levels of LDL, HDL cholesterol, and triglycerides, both the ADA and the ATP III
guidelines emphasized that LDL lowering
remains the top priority for lipid lowering, and non-HDL is the secondary goal of
treatment when the triglyceride level is
⬎200 mg/dl.
Because diabetic patients typically
have an increase in atherogenic triglyceride-rich lipoprotein VLDL levels, there is
a suggestion that non-HDL cholesterol,
which is defined as the difference between
total and HDL cholesterol, may be more
appropriate as the therapeutic target in
patients with diabetes than LDL cholesterol (2). The rationale for this recommendation is that: 1) non-HDL cholesterol
DIABETES CARE, VOLUME 28, NUMBER 8, AUGUST 2005
Liu and Associates
includes all potential athergenic lipoproteins, including LDL, VLDL, and its remnants; 2) estimates of LDL by Friedewald
formula (6) become increasingly inaccurate
as triglyceride levels increase (7); and therefore, 3) using LDL alone as the therapeutic
target may not be sensitive enough to manage dyslipidemia among those diabetic
patients.
To address this question, we used
four publicly available data sets, including the Framingham Cohort Study (FCS),
the Framingham Offspring Study (FOS),
the Lipid Research Clinics Prevalence Follow-up Study (LRCF), and the Multiple
Risk Factors Intervention Trials (MRFIT)
Usual Care Group, to evaluate the role of
the joint distribution of non-HDL and
LDL cholesterol as predictors of CHD
death risk among individuals with and
without diabetes.
RESEARCH DESIGN AND
METHODS — The data sets used in
this study are all prospective cohort studies designed to study CVD and its risk
factors. We confined our consideration to
white men and women because of a limited number of blacks and other minorities, and we focused on participants aged
ⱖ30 and free of CHD at baseline. The
details of each of the following studies, in
terms of study design and data collection,
have been described elsewhere: FCS (8),
FOS (9), LRCF (10), and MRFIT (11). A
brief summary of each study is shown in
online appendix 2 (available from http://
care.diabetesjournals.org). Although
each study used different questionnaires,
similar questions were asked to assess
each participant’s lifestyle factors and
health outcomes. Diabetes status was defined as either “reported by physiciandiagnosed and on medication” or having a
fasting glucose level ⱖ126 mg/dl at the
baseline examination based on the ADA’s
new definition of diabetes (12).
Laboratory procedures
The glucose and lipid profile were determined from fresh plasma after overnight
fast (ⱖ9 h). Glucose level was determined
using either the techniques described by
Cooper (13) or those of Bathelmai and
Czok (14), but they were comparable. Total cholesterol was assayed by the AbellKendall method (15) in the FCS and FOS
and by a Technicon AutoAnalyzer in the
LRCF and MRFIT. The values of total cholesterol in the LRCF and MRFIT were
DIABETES CARE, VOLUME 28, NUMBER 8, AUGUST 2005
standardized to the Abell-Kendall
method. HDL cholesterol in all studies
was assayed by manganese-heparin precipitation. Triglycerides were measured
using the serum automated LedererKessler method (16) in the FCS and FOS,
but a calibration adjustment was applied
to the measurements in the lipid study to
match the average levels obtained by the
Lipid Standardization Laboratory (17). In
the LRCF and MRFIT, a preparation of an
isopropanol extract of plasma was treated
with a zerolite mixture to remove phospholipids, glucose, and bilirubin, and
then plasma triglyceride levels were estimated fluorimetrically. All methods of triglyceride measurement are comparable
because they were all standardized to the
Lipid Research Clinics methods. LDL
cholesterol in the FCS and FOS was estimated indirectly by use of the Friedewald
formula when triglycerides were ⬍400
mg/dl (6) and was estimated directly for
triglycerides ⱖ400 mg/dl after ultracentrifugation of plasma and measurement of
cholesterol in the bottom fraction (plasma
density ⬍1.006). In the LRCF, LDL cholesterol was determined by ultracentrifugation. The level of LDL cholesterol in the
MRFIT was estimated indirectly using the
Friedwald formula when triglycerides
were ⬍300 mg/dl and estimated directly
by ultracentrifugation for triglycerides
ⱖ300 mg/dl. Non-HDL cholesterol is defined as the difference between total and
HDL cholesterol.
Ascertainment of CHD
In the FCS and FOS, the end point diagnoses were based on a review of medical
records by a committee of the FCS investigators. The diagnosis of CHD included
fatal and nonfatal myocardial infarction,
sudden cardiovascular death, and acute
coronary insufficiency (8). In the LRCF,
each participant’s vital status was followed prospectively to provide data on
subsequent mortality. The protocol included annual mail and telephone contact
with participants, but there was no clinical reexamination or assessment of morbidity. When a death was discovered, a
copy of the death certificate was obtained,
and the attending physician and next of
kin were interviewed. Two members of a
panel of five cardiologists, blinded to the
participant’s identity and baseline characteristics, coded the cause of death as
CHD, CVD (which included CHD), or
“other.” Disagreements between the two
cardiologists were settled by the entire
panel (18). In the MRFIT, the vital status
of each man was checked by clinical center staff during the trial and at the termination of active intervention in February
1982. Then, vital status was determined
from the National Death Index and Social
Security Administration. Cause-specific
death rates are based on coding of death
certificates by trained nosologists, using
the ICD-9 (19). Two nosologists independently coded each death certificate, and a
third nosologist adjudicated any disagreement (20). Using the ICD-9, deaths from
CHD were denoted by codes 402, 410 –
414, and 429.2 (21).
Assessment of other potential
confounding factors
Age at baseline was calculated by the date
of birth and the date of exam when
plasma lipoproteins were measured for
each cohort. Smoking status was defined
as current cigarette smokers and noncurrent smokers based on self-report from
the baseline questionnaire. BMI was calculated as the ratio of weight (in kilograms) to height (in meters squared)
measured at the baseline examination.
Systolic blood pressure (in mmHg) was
the average of two readings at the baseline
examination.
Statistical analysis
Follow-up time was calculated as the difference between the date of end point and
the date of blood draw from each cohort.
The end point was defined as either death
from CHD or end of study, which varies
from cohort to cohort. Means and proportions were calculated for the CHD risk
factors at baseline based on diabetes status. Student’s t tests and ␹2 tests were
used for comparisons of means and the
proportions. Because of the limited number of individuals with diabetes in each
cohort, only pooled analyses were performed. Based on ATP III guidelines, individuals with diabetes are defined as a
CHD risk equivalent, and the therapeutic
goal for dyslipidemia management is set
as an LDL cholesterol level ⬍100 mg/dl.
For non-HDL cholesterol, the cut points
are 30 mg/dl higher than that for LDL
cholesterol to account for the VLDL cholesterol fraction. Therefore, we divided
the distributions of these two lipid parameters in the following way: LDL cholesterol: ⬍100, 100 –129, and ⱖ130 mg/dl;
and non-HDL cholesterol: ⬍130, 130 –
1917
Non-HDL and LDL cholesterol and CHD
Table 1—Baseline characteristics of participants by study sources and sex
FCS
n*
Current smokers (%)
Diabetes (%)
Age (years)
Total cholesterol (mg/dl)
HDL cholesterol (mg/dl)
LDL (mg/dl)†
Triglycerides (mg/dl)
VLDL cholesterol (mg/dl)
Non-HDL cholesterol (mg/dl)
Systolic blood pressure (mmHg)
BMI (kg/m2)
FOS
LRC R
LRC H L
MRFIT-UC
Pooled
Men
Women
Men
Women
Men
Women
Men
Women
Men
Men
Women
978
57.4
12.2
60
219
46
142
133
31
173
140
22
1,377
32.6
10.1
60
241
57
155
116
28
183
136
21
1,715
29.2
5.8
42
209
44
137
125
27
165
128
27
1,724
17.3
2.1
41
199
58
124
81
18
141
120
25
2,359
35.0
2.8
46
207
46
138
138
23
161
126
26
2,149
29.3
2.2
48
207
59
132
110
16
148
122
25
1,883
38.5
5.8
46
241
43
157
242
42
198
128
27
1,471
36.4
5.2
49
250
57
167
172
26
193
126
26
5,725
61.1
5.7
46
241
42
160
197
39
199
137
27
12,660
48.2
5.7
47
229
43
151
178
34
185
133
27
6,721
28.5
4.4
49
221
58
142
117
21
163
126
24
Data are mean values. Non-HDL cholesterol ⫽ total ⫺ HDL. *No missing values in terms of age, total cholesterol, HDL, LDL, triglycerides, and non-HDL. †FCS and
FOS: Friedewald formula (LDL ⫽ total cholesterol ⫺ HDL ⫺ triglycerides/5) when triglycerides ⬍400 mg/dl and direct measurement when triglycerides ⱖ400
mg/dl; LRC random and LRC high lipids: direct measurement; MRFIT: Friedewald formula (LDL ⫽ total cholesterol ⫺ HDL ⫺ triglycerides/5) when triglycerides
⬍300 mg/dl and direct measurement when triglycerides ⱖ300 mg/dl. LRC R, Lipid Research Clinics Program Follow-up Study Random Sample; LRC H L, Lipid
Research Clinics Program Follow-up Study Random Hyperlipdemia Sample; MRFIT-UC, MRFIT Usual Care Group.
159, and ⱖ160 mg/dl. For other lipid
parameters, we followed the recommendations of the ATP III guidelines as follows: total cholesterol: ⬍200, 200 –239,
and ⱖ240 mg/dl; HDL cholesterol: ⱖ60,
40 –59, and ⬍40 mg/dl; triglycerides:
⬍150, 150 –199, and ⱖ200 mg/dl. The
risk of CHD death within each level of the
various lipid parameters was estimated
for individuals with and without diabetes.
The lowest category of each lipid parameter from those without diabetes, except
for HDL cholesterol, where the highest
from those without diabetes was used,
was used as the reference group. As a result, five indicator variables were created
for each individual in the data set. For
example, the reference group for LDL
cholesterol was individuals with LDL
⬍100 (mg/dl) and without diabetes, and
the five indicator variables were: 1) LDL
100 –129 and without diabetes (1 ⫽ yes,
0 ⫽ no); 2) LDL ⱖ130 and without diabetes (1 ⫽ yes, 0 ⫽ no); 3) LDL ⬍100 and
with diabetes (1 ⫽ yes, 0 ⫽ no); 4) LDL
100 –129 and with diabetes (1 ⫽ yes, 0 ⫽
no); and 5) LDL ⱖ130 with diabetes (1 ⫽
yes, 0 ⫽ no). For the joint distribution of
non-HDL and LDL cholesterol, four
groups were created based on lipid levels
(in mg/dl): 1) non-HDL ⬍130 and LDL
⬍100; 2) non-HDL ⬍130 and LDL
ⱖ100; 3) non-HDL ⱖ130 and LDL ⬍100;
and 4) non-HDL ⱖ130 and LDL ⱖ100.
Group 1 within those without diabetes was the overall reference group, and
seven indicator variables were created.
1918
Cox proportional hazards models were
used in three approaches to estimate the
relative risk (RR) of CHD death for nonHDL and LDL with adjustment for age,
cohort study, current smoking status,
BMI, systolic blood pressure, and sex
(when applicable). First, both non-HDL
and LDL were added into the model as
continuous variables, and their impacts
on CHD death were estimated by diabetes
status and by sex. Second, non-HDL and
LDL were retained as continuous variables, and diabetes status was included as
well as interaction terms between diabetes
status and non-HDL and between diabetes status and LDL. Finally, the RRs for
grouped non-HDL, LDL, and other lipids
were estimated. We also conducted receiver operating characteristic analyses
and compared the c-statistics for the overall predictive value of non-HDL and LDL
as a continuous variable separately as well
as the category variables separately in the
model, with adjustment for the covariates
mentioned above (22). All analyses were
performed using SAS statistical software,
version 8.2 (SAS Institute, Cary, NC).
RESULTS — There were 12,660 men
and 6,721 women from the four cohorts
included in this analysis (Table 1). The
proportion of individuals with diabetes is
higher in the FCS than in the other cohorts. Overall, ⬃6% of men and ⬃4% of
women were categorized as having diabetes status.
Overall, individuals with diabetes
were older and were more likely to be
male; to have higher levels of total, VLDL,
and non-HDL cholesterol and triglycerides; to have lower levels of HDL cholesterol; to have higher levels of systolic
blood pressure; and to have a larger BMI
(Table 2). Except for current smoking status and LDL cholesterol levels, all differences between individuals with and
without diabetes were statistically
significant.
During the average ⬃13 years of follow-up, 114 CHD deaths occurred in
1,018 individuals with diabetes, and
there were 659 CHD deaths among the
18,363 individuals without diabetes.
Non-HDL and LDL were initially considered in the Cox regression model as continuous variables and examined by
diabetes status with adjustment for age,
sex, study, BMI, systolic blood pressure,
and current smoking status. Among those
without diabetes, each increase by 1
mg/dl of non-HDL cholesterol was associated with a 5% increased risk for CHD
death (95% CI 1.001–1.008, P ⬍ 0,001),
and every 1-mg/dl increase of LDL cholesterol was associated with a 4% increased risk for CHD death (1.001–
1.008, P ⫽ 0.02). These results were
nearly identical among those with diabetes. When stratified by sex and diabetic
status, both men and women had similar
RRs for CHD from non-HDL and LDL.
These latter findings reached statistical
significance only for non-HDL among
men (P ⫽ 0.005 for those with diabetes
DIABETES CARE, VOLUME 28, NUMBER 8, AUGUST 2005
Liu and Associates
Table 2—Comparison of selected variables at baseline by diabetes status
n
Men (%)
Current smokers (%)
Age (years)
Total cholesterol (mg/dl)
LDL cholesterol (mg/dl)
VLDL cholesterol (mg/dl)
HDL cholesterol (mg/dl)
Non-HDL cholesterol (mg/dl)
Triglycerides (mg/dl)
Systolic blood pressure (mmHg)
BMI (kg/m2)
With diabetes
Without diabetes
P
1,018
70.7
39.3
53.4
237.8
148.6
45.6
43.6
194.1
254.1
141.4
27.3
18,363
65.0
41.5
47.1
225.3
148.0
28.7
48.6
176.7
151.4
129.4
25.8
0.002
0.17
⬍0.001
⬍0.001
0.68
⬍0.001
⬍0.001
⬍0.001
⬍0.001
⬍0.001
⬍0.001
and P ⫽ 0.02 for those without diabetes)
and for LDL among those without diabetes (P ⫽ 0.02). There was no evidence of
an interaction between diabetic status and
lipid level; the RR estimates were ⬃1.0 for
the interaction terms (P ⬎ 0.5). Overall,
the c-statistics from ROC analysis for nonHDL and LDL was similar (0.799 vs.
0.796 as continuous variables; 0.798
vs. 0.797 using the cut points previously
described).
When LDL, non-HDL, and other lipid
measurements were considered as categorical variables as described above (see
RESEARCH DESIGN AND METHODS), all lipid parameters were strongly positively associated with the risk for CHD death among
individuals with and without diabetes,
except for HDL cholesterol, which was
negatively associated with the risk for
CHD death (Table 3). The associations
were stronger among individuals with diabetes; generally, the RRs for individuals
with diabetes were ⬃200% higher than
that for individuals without diabetes in
corresponding lipid levels.
The risk for CHD death for the joint
distribution of non-HDL and LDL cholesterol by diabetes status is shown in Fig. 1
(see online Appendix 1 for the RR estimates and 95% CIs for each cell). Compared with the reference group (without
diabetes with non-HDL ⬍130 mg/dl and
LDL ⬍100 mg/dl), the RR (95% CI) for
CHD death among those with diabetes
did not increase with increasing level of
LDL, whereas it did increase with increasing level of non-HDL: group 1: 5.7 (2.0 –
16.8); group 2: 5.7 (1.6 –20.7); group 3:
7.2 (2.6 –19.8); and group 4: 7.1 (3.7–
13.6). Among those without diabetes, the
risk for CHD death increased with higher
DIABETES CARE, VOLUME 28, NUMBER 8, AUGUST 2005
levels for both non-HDL and LDL cholesterol: group 2: 3.3 (1.6 – 6.7); group 3:
2.3 (0.9 –5.4); and group 4: 3.8 (2.0 –
7.1).
CONCLUSIONS — The results from
this pooled prospective cohort confirmed
that diabetes status is a strong risk factor
for CHD death. Our results indicate that
the categorical 130 mg/dl cutoff point for
non-HDL appears to be a better predictor
of the risk for CHD death than the 100
mg/dl cutoff point for LDL among those
with diabetes, and it may serve as a useful
clinical tool. The failure of the ROC analyses to find one lipid parameter superior
to another may not be surprising because
the interpretation of the RRs is, at least in
part, dependent on the measurement
scale, the cut points used, and the manner
in which the variables are modeled (23).
Several other studies have shown that
the level of non-HDL cholesterol was a
stronger predictor of CHD or CVD risk
among patients with diabetes. In the
Health Professionals’ Follow-up Study
(24), non-HDL cholesterol was a strong
predictor of CVD in 746 diabetic men
aged 46 – 81 years during a 6-year followup. The RR for the highest quartile of nonHDL cholesterol was significantly higher
than that for LDL cholesterol: 2.34 (95%
CI 1.26 – 4.43) vs. 1.74 (0.99 –3.06). In a
Finish cohort study (25), 1,059 middleaged men and women with type 2 diabetes were followed for 7 years, and it was
found that higher levels of non-HDL cholesterol were independently associated
with a twofold increase in the risk for
CHD death or morbidity, although there
Table 3—Relative risk of coronary heart disease mortality for various levels of lipids measured at baseline by diabetes status, pooled analysis
n
CHD
LDL cholesterol (mg/dl)
⬍100
100–129
ⱖ130
Non-HDL cholesterol (mg/dl)
⬍130
130–159
ⱖ160
Total cholesterol (mg/dl)
⬍200
200–239
ⱖ240
HDL cholesterol (mg/dl)
ⱖ60
40–59
⬍40
Triglycerides (mg/dl)
⬍150
150–199
ⱖ200
Without diabetes
With diabetes
18,363
659
1,018
114
1.00
1.73 (1.07–2.81)
3.02 (1.93–4.72)
4.63 (2.21–9.70)
2.93 (1.53–5.61)
5.94 (3.64–9.69)
1.00
0.95 (0.65–1.39)
2.11 (1.52–2.91)
2.73 (1.27–5.87)
2.73 (1.60–4.66)
3.68 (2.51–5.39)
1.00
2.02 (1.58–2.60)
2.43 (1.90–3.11)
3.10 (1.97–4.88)
3.52 (2.41–5.14)
4.41 (3.07–6.32)
1.00
1.81 (1.40–2.35)
2.59 (1.97–3.41)
1.94 (1.00–3.76)
3.42 (2.35–4.96)
4.65 (3.24–6.67)
1.00
1.26 (1.03–1.54)
1.34 (1.10–1.63)
1.80 (1.34–2.44)
3.22 (2.14–4.85)
2.27 (1.61–3.19)
Data are RR (95% CI). RR from proportional hazard model adjusted for age, sex, systolic blood pressure, BMI,
current smoking, and study sources.
1919
Non-HDL and LDL cholesterol and CHD
Figure 1— RR of CHD mortality for joint distribution of non-HDL and LDL cholesterol measured
at baseline by diabetes status (pooled analysis). RR are from proportional hazard model adjusted
for age, sex, systolic blood pressure, BMI, current smoking, and study sources.
was no direct comparison between LDL
and non-HDL cholesterol for the predictive values of CHD. In the Strong Heart
Study cohort (26) of 2,108 AmericanIndian men and women aged 45–74 years
with diabetes, the hazard ratios for the
highest tertile of non-HDL cholesterol were
higher than those for LDL cholesterol
among both diabetic men and women, although the CIs were overlapping.
This is among the first studies to evaluate the predictive value of the joint distribution of non-HDL and LDL
cholesterol among individuals with and
without diabetes, although two of the
three studies mentioned above performed
some comparisons between LDL and
non-HDL cholesterol. According to ATP
III guidelines, for patients with diabetes,
the goal for LDL cholesterol–lowering
therapy is an LDL cholesterol level ⬍100
mg/dl. For a baseline LDL cholesterol
⬍100 mg/dl among those with diabetes,
no further LDL cholesterol–lowering
therapy was recommended. Evidence
from the subgroup analysis of patients
with diabetes from the Heart Protection
Study (HPS) trial indicated that even
among those diabetic patients with very
low LDL cholesterol (⬍116 mg/dl) at entry, a marginally significant risk reduction
of CHD event was observed with LDL
cholesterol–lowering therapy (simvastain) (27). This suggested that the goal for
LDL cholesterol therapy among patients
with diabetes can be set even lower than
1920
currently recommended (28). Our results
further suggest that non-HDL might be a
better primary target for lipid reduction
than LDL among patients with diabetes.
The potential value of using non-HDL as
the dyslipidemia management tool
among patients with diabetes needs to be
further investigated.
There are several reasons why the
level of non-HDL may be superior to that
of LDL in CHD risk prediction among individuals with diabetes (29). First, nonHDL cholesterol contains all potential
atherogenic lipoproteins, including
VLDL, intermediate-density lipoprotein,
and LDL, whereas LDL cholesterol does
not. The characterized dyslipidemia
among diabetic individuals is elevated triglyceride-rich lipoproteins (VLDL and intermediate-density lipoprotein) and
decreased HDL. The use of LDL alone will
ignore the contribution of those triglyceride-rich lipoproteins in the development
of CHD. Second, in the clinical lipoprotein analysis, the level of LDL cholesterol
is usually estimated using Friedewald’s
formula, based on the measurements of
total and HDL cholesterol and triglycerides, which is used to estimate the value of
VLDL cholesterol. However, the estimation of LDL by this formula becomes progressively less accurate as the triglyceride
level increases, and the formula is no
longer considered accurate enough for
use when triglyceride levels reach 400
mg/dl. Because of elevated triglyceride
levels in patients with diabetes, the level
of LDL estimated by this formula is likely
to be unreliable. In contrast, the level of
non-HDL can be easily calculated from
the difference between the levels of total
and HDL cholesterol. In addition, there is
no assumption about the composition of
VLDL particles; thus, the non-HDL level
can be calculated in the nonfasting state
or in the setting of hypertriglyceridemia.
Among the main limitations of this
study are that it is a post hoc analysis
based on the new ADA definition of diabetes applied to this pooled cohort and
also that only ⬃11% of population met
the ATP III goal for an LDL level ⬍100
mg/dl, whereas 15% of the population experienced a non-HDL level ⬍130 mg/dl.
Thus, the results from this analysis may
not be generalizable to the general population. However, the ATP III recommendations for screening and treatment were
established for those with an elevated absolute risk of CHD, which the majority of
participants in this analysis would most
likely meet by today’s standards. There
was no information for us to distinguish
type 2 from type 1 diabetes, although the
majority of these adults likely had type 2
diabetes, given its much higher prevalence in the general population (1). There
are several significant strengths to this investigation, including the large sample
size from this pooled cohort and also that
each of the studies included was originally designed to examine the etiologies
of CHD risk and that our end point (CHD
death) was well documented.
In conclusion, these results suggest
that non-HDL cholesterol level is a stronger predictor of CHD death than LDL
cholesterol among those with diabetes,
and they further suggest that VLDL cholesterol (and/or VLDL triglyceride) may
play a critical role in the development of
CHD among those with diabetes. These
findings should be considered in the clinical approach to risk reduction among diabetic patients.
Acknowledgments — T h e F r a m i n g h a m
Heart Study, LRCF, and MRFIT are conducted
and supported by the National Heart, Lung,
and Blood Institute (NHLBI) in collaboration
with the study investigators.
This article was prepared using a limitedaccess dataset obtained from the NHLBI and
does not necessarily reflect the opinions or
views of the individual studies or the NHLBI.
DIABETES CARE, VOLUME 28, NUMBER 8, AUGUST 2005
Liu and Associates
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