CETP genotypes, multiple linear regression analysis with dummy variables for categorical and interaction
terms was applied. In order to improve statistical power, data from men and women were analyzed to-
gether, including a dummy variable for gender into the regression model. A core model with gender, age, BMI,
CETP TaqIB genotypes, and a set of variables for tobacco smoking and alcohol consumption, was first
identified using forward and backward procedures. The selection criterion for choosing the core model was the
following: a variable or interaction term was retained into the model if the global term was statistically sig-
nificant P B 0.05. Regression diagnostics analysis of residuals, influence of outliers and colinearity were
employed to check the assumptions and to assess the
Table 2 CETP TaqIB polymorphisms in the population by gender
a
Women All
Men n
n n
Genotypes 117 41.3
B1B1 222 43.2
105 45.5 100 43.3
223 43.4 123 43.5
B1B2 69 13.4
26 11.3 B2B2
43 15.2 514
283 100.0 Total
231 100.0
100.0 Allele frequency
B2 Allele 0.329
0.351 0.369
0.329–0.398 0.286–0.372
95 C.I. 0.322–0.380
a
Differences by gender across CETPTaqIB polymorphisms were nonsignificant. Chi square P value = 0.332.
Table 1 Demographic, biochemical and life-style characteristics of the popula-
tion Men n = 231
Women n = 283 Mean SD
P Mean SD
0.102 Age years
35.7 10.4 37.4 10.1
Body mass index B
0.001 23.9 4.2
26.4 4.8 kgm
2
5.3 1.0 Total-C mmoll
4.9 0.9 B
0.001 3.1 0.8
3.5 0.9 LDL-C mmoll
B 0.001
1.1 0.3 HDL-C mmoll
1.4 0.3 B
0.001 Triglycerides
B 0.001
1.3 1.2 1.1 0.7
mmoll B
0.001 127.2 15.9
Systolic blood 117.5 17.7
presure mmHg
0.017 73.8 11.6
70.7 12.4 Diastolic blood
presure mmHg
44.6 0.998
44.6 Current smokers
Past smokers 0.002
25.7 12.9
B 0.001
Alcohol users 88.9
59.9 Physical exercise
36.5 61.7
Sedentary Moderate
32.7 39.6
5.6 0.005
23.9 High
74.3 Daily walkers
71.9 0.872
Education 0.0
Non-schooling 0.0
26.8 34.7
Primary 29.6
Secondary 31.4
University short 19.6
32.3 cycle
University long 9.8
16.1 0.002
cycle Marital status
66.7 52.1
Married 41.8
30.8 Single
2.5 6.3
Divorced 0.016
P value in the comparison between men and women. Student’s test for comparison of means, and Chi square tests for percentages.
accuracy of computations. Once the core model was identified for the total sample, separate models with the
same variables were computed for men and women. Finally, additional life-style variables physical activity,
marital status and educational level were included into the core model defined in the previous stage. A variable
or interaction term was maintained in the final regres- sion model as independent term or as control variable
on the basis of statistical significance P B 0.05 or P B 0.20, respectively. All analyses were done using the
Statistical Package for Social Sciences SPSS, version 8.0 for windows.
4. Results
The main characteristics age, BMI, lipid levels, blood pressure, tobacco smoking, alcohol consumption,
physical activity, education, and marital status of the study subjects 231 men and 283 women are shown in
Table 1. The CETP TaqIB genotype could be deter- mined unequivocally in all of them. Genotypes and
allele frequencies of this polymorphism are shown in Table 2. The genotype distribution did not differ for
men and women P = 0.332 and no deviation from the Hardy – Weinberg
equilibrium was
observed P =
0.410. The calculated B2 allele frequencies were 0.351 95 CI: 0.322 – 0.380. The allele frequency of the B2
allele was significantly lower than that reported by Kauma et al. [20] in Finland, who detected an allele
frequency for B2 = 0.436, with a calculated 95 CI of 0.406 – 0.466; and also statistically different from those
in an average population from 11 areas of Europe [18]. In this case, the reported allele frequency for B2 was
0.440 95 CI, 0.416 – 0.464.
Table 3 shows plasma lipid levels by CETP TaqIB genotypes and gender in the study participants. Only
HDL-C levels differed statistically between the three TaqIB genotypes P B 0.05 in both men and women.
B2 carriers had significantly higher HDL-C levels as compared with B1B1 homozygotes. This allele effect
was present in both genders P trend B 0.001 and P trend = 0.002, in men and women, respectively. No
statistically significant associations were observed be- tween other lipid variables and the CETP TaqIB poly-
morphism. After Bonferroni corrections, compared with the B1B1 genotype, the mean HDL-C level in men
was 5.8 P \ 0.05 and 20.6 P B 0.05 higher in the B1B2 and B2B2 genotype, respectively. In women these
increases were 5.3 P \ 0.05 and 13.5 P B 0.05. To assess the influence of covariates on this association,
we examined the distribution of BMI, age, tobacco smoking, alcohol consumption, physical activity, mari-
tal status and education across CETP TaqIB polymor- phism. No statistically significant differences for any of
these variables across genotypes were observed data not shown.
To investigate the influence of the measured environ- mental factors and the CETP TaqIB polymorphism on
HDL-C levels, we carried out multivariate modeling with dummy variables as described in Section 2. Table
4 presents the results of the core model with age, BMI, tobacco smoking and alcohol consumption as indepen-
dent variables for all subjects, and for men and women separately. From the various fitted models, a continu-
ous variable cigday was the most statistically signifi- cant indicator P = 0.003 of tobacco smoking related
Table 3 Plasma lipid levels by CETPTaqIB genotypes and gender in the total sample
B1B2 B1B1
B2B2 n = 26
n = 100 n = 105
Men Women
P Trend n = 117
n = 123 n = 43
P Mean SD
Mean SD Mean SD
0.217 4.96 0.80
5.39 1.19 0.239
5.26 0.96 Men
Total-C mmoll 0.242
0.387 4.90 0.83
5.01 1.02 4.74 0.91
Women Men
3.44 0.82 3.63 0.89
LDL-C mmoll 3.18 0.70
0.067 0.219
0.577 0.104
2.96 0.59 3.19 0.27
3.14 0.68 Women
Men 1.02 0.26b
1.08 0.24b HDL-C mmoll
1.23 0.16a,c 0.004
0.001 0.008
0.002 Women
1.33 0.30b 1.40 0.27b
1.51 0.25a,c Men
1.86 1.65 1.47 1.16
Triglycerides mmoll 1.30 0.85
0.418 0.339
Women 0.88 0.48
0.95 0.58 0.79 0.33
0.279 0.526
Men 38.6 9.63
Age years 0.823
36.0 10.13 0.219
38.0 11.64 0.658
0.168 35.2 11.81
37.3 10.41 34.2 9.70
Women P value obtained in the ANOVA test for the global comparison between genotypes. a, b, c: P values obtained in the Bonferroni post-hoc test:
a: PB0.05 compared with B1B1 genotype; b: PB0.05 compared with B2B2 genotype; c: PB0.05 compared with B1B2 genotype. Table 4
Effect of CETPTaqIB genotype, alcohol consumption, tobacco smoking and BMI on plasma HDL-C levels multiple linear regression analysis in the total population and by gender
a
All n = 514 Men n = 231
Women n = 283 BSE
P P
BSE P
BSE B
0.001 B
0.001 1.834 0.084
1.834 0.126 Constant
B 0.001
1.578 0.133 0.009
0.002 B
0.001 CETPTaqIB
genotype −
0.184 0.390 B
0.001 B1B1
− 0.204 0.058
− 0.165 0.053
0.001 0.002
0.050 −
0.104 0.051 0.002
− 0.187 0.059
B 0.001
− 0.140 0.390
B1B2 reference
reference B2B2
reference 0.022 0.011
0.040 0.018 0.009
0.276 Alcohol intake
0.016 0.015 0.049
gday 0.048
− 0.017 0.047
0.003 Tobacco smoking
− 0.018 0.008
0.035 −
0.019 0.009 cigday
− 0.016 0.004
B 0.001
B 0.001
− 0.014 0.002
BMI Kgm
2
0.002 −
0.013 0.003 0.002 0.002
0.332 0.861
0.002 0.002 Age years
0.338 0.001 0.001
Gender B
0.001 B
0.001 Male
− 0.297 0.030
reference Female
R
2
of the model B
0.001 0.147
B 0.001
0.143 0.376
B 0.001
a
Dependent variable: HDL-C mmoll; B = regression coefficient. SE = standard error; Regression coefficients for alcohol intake and tobacco smoking corresponded to the square-root transformed variables.
Table 5 Mean plasma HDL-C according to CETPTaqIB genotype, stratified by tobacco smoking, alcohol consumption and gender
Non smokers Smokers
Alcohol users Non-users
Mean SD n
n Mean SD
n Mean SD
n Mean SD
Men CETPTaqIB genotype
1.04 0.25 48
1.00 0.25 93
1.05 0.25 13
0.85 0.23 B1B1
57 1.10 0.27
46 1.05 0.23
89 54
1.08 0.26 B1B2
11 1.07 0.15
17 B2B2
1.24 0.18 9
1.19 0.16 24
1.23 0.16 2
1.18 0.17 0.030
0.107 0.016
0.098 P
0.009 0.053
0.006 P trend
0.046 Women
CETPTaqIB genotype 1.33 0.25
48 1.32 0.28
B1B1 68
69 1.34 0.27
49 1.33 0.27
1.41 0.26 60
1.38 0.29 75
23 1.41 0.26
B1B2 48
1.40 0.29 1.52 0.28
18 1.49 0.23
27 B2B2
1.53 0.27 25
16 1.48 0.21
0.040 0.105
0.023 P
0.294 P trend
0.012 0.045
0.006 0.113
P values obtained in the ANOVA test for the global comparison between genotypes.
to HDL-C in the total sample. For alcohol consump- tion, also a continuous variable square root of daily
ethanol intake in gday was better than the categorical variables created as described in Section 2. Interest-
ingly, when type of alcoholic beverages was further explored beer, red wine, white wine or hard liquor,
red wine consumption was the most positive and statis- tically associated with HDL-C levels P B 0.001, while
beer consumption presented a negative regression co- efficient P \ 0.05. In this core model, when the whole
group was examined, we found that BMI, age, CETP TaqIB polymorphism, total alcohol consumption g
day and tobacco smoking cigday, were statistically significant predictors of HDL-C levels, explaining
37.6 adjusted r
2
= 0.376; P B 0.001 of the variance.
After adjusting for age, BMI, tobacco smoking and alcohol consumption, TaqIB polymorphism was inde-
pendently associated P B 0.001 with plasma HDL-C levels, and was able to explain 5.8 of the variance in
the HDL-C in the population. Considering B2B2 indi- viduals as reference, B1B2 subjects showed a mean
decrease of HDL-C levels of − 0.140 mmoll P B 0.001, and B1B1 subjects a mean decrease of − 0.184
mmolL P B 0.001. This effect was comparable to the gender effect, which lowers HDL-C by − 0.297 mmoll
P B 0.001 in men, compared with women P B 0.001. When first order interaction terms between the poly-
morphism and environmental variables tobacco and alcohol were tested, no statistically significant terms
P = 0.715 for tobacco smoking and P = 0.455 for alco- hol consumption; see Table 5 for HDL-C and TaqIB
genotype by smoking and alcohol drinking status were found, and they were not included in the previously
reported core model. In the separated analysis for men and women Table 4, the CETP TaqIB polymorphism
was also independently associated with HDL-C levels in both men and women P B 0.01.
When additional life-style variables physical activity, education and marital status were added to the core
model Table 6, CETP TaqIB polymorphism also re- mained independently and consistently as judged by
regression coefficients associated with HDL-C levels P B 0.001. Educational level was strongly associated
with HDL-C P = 0.005. Individuals with higher edu- cation university as reference presented the highest
HDL-C. Marital status was also independently and statistically associated with HDL-C P = 0.048. Physi-
cal exercise did not enter into the final model either as a three-level variable sedentary, moderate and high,
or as a dichotomized variable sedentary or active. Daily walking was associated with a mean increase of
0.047 mmoll in HDL-C without reaching statistical significance P = 0.126. With regard to tobacco smok-
ing, the introduction into the core model of educational level and marital status, there was an important change
in its statistical significance from P = 0.003, to P = 0.070. A similar trend was observed for alcohol con-
sumption from P = 0.040 to P = 0.317. Finally, when separate models for men and women were computed
results not shown, the effect of CETP TaqIB poly- morphism on HDL-C levels, controlling for alcohol,
tobacco, physical activity, education and marital status, remained statistically significant in both genders.
5. Discussion
