We tested the hypothesis that cardiometabolic syndrome (CMS) is associated with subclinical atherosclerosis in men and that moderate-to-high levels of cardiorespiratory fitness (fitness) attenuate this relation. Our study population (n = 2,107 men) participated in a health screening program that included measures of coronary artery calcification (CAC) and carotid artery intima-media thickness (CIMT) as surrogate markers of subclinical atherosclerosis. The prevalence of subclinical atherosclerosis was defined as a CAC score >0 and a mean CIMT more than the seventy-fifth percentile. Fitness was directly measured through peak oxygen consumption during cardiopulmonary exercise testing to volitional fatigue/exhaustion. The presence of CMS was defined as having ≥3 relevant risk factors based on the Adult Treatment Panel III report (ATP-III) criteria. After adjusting for confounding variables, participants with CMS demonstrated a higher odds ratio (OR) of having a positive CAC (OR 1.41, 95% confidence interval [CI] 1.05 to 1.89) and CIMT (OR 1.70, 95% CI 1.14 to 2.52) compared with those without CMS. Upper levels of fitness were associated with a lower prevalence of CAC (OR 0.69, 95% CI 0.55 to 0.88) and CIMT (OR 0.53, 95% CI 0.40 to 0.71) compared with lower fitness. In the joint analysis, unfit participants with CMS were 1.47 times (95% CI 1.09 to 1.96 for CAC) and 2.35 times (95% CI 1.70 to 3.26 for CIMT) more likely to exhibit these indexes of subclinical atherosclerosis compared with fit participants without CMS. Fit participants with CMS had ORs for the prevalence of CAC (OR 1.12; 95% CI 0.85 to 1.47) and CIMT (OR 1.06; 95% CI 0.74 to 1.53) that were similar to those of the fit cohort without CMS. In conclusion, our findings demonstrate that CMS is associated with an increased risk of subclinical atherosclerosis but that high fitness appears to attenuate these associations in men.
Although cardiorespiratory fitness appears to attenuate the effects of cardiometabolic syndrome (CMS) on cardiovascular mortality, the underlying mechanisms remain unclear. Because previous studies have suggested that moderate-to-high fitness is associated with a lower prevalence of subclinical atherosclerosis, we tested the hypothesis that CMS is associated with an increased risk of subclinical atherosclerosis, but that fitness attenuates these associations.
Methods
Men who underwent a general health examination at Samsung Medical Center, Seoul, South Korea, from January 2010 to December 2010, were eligible for this cross-sectional study. Among these participants, we analyzed 2,107 men (age 53 ± 1 year, range 40 to 78 years) who had no known history of coronary heart disease, all of whom had measures of coronary artery calcification (CAC), cardiometabolic risk factor profiling, and fitness (VO 2peak ) determined by treadmill exercise testing with direct cardiopulmonary gas analysis. A subset of this population (n = 1,943) underwent an additional assessment of carotid artery intima-media thickness (CIMT). Information regarding cigarette smoking was obtained by a self-reported questionnaire. Indexes of subclinical atherosclerosis included the CAC score and CIMT. Diabetes was defined as a fasting glucose level of ≥126 mg/dl and/or self-reported by participants. Hypertension was categorized as a blood pressure at rest of ≥140/90 mm Hg and/or self-reported by participants. Written informed consent was obtained from all participants before undergoing the health screening program, and the study was approved by the medical center institutional review board.
Body mass index was calculated as weight (kg) divided by height squared (m 2 ). Waist girth was measured in the standing position using a standard tape measure at the level of the umbilicus. Blood pressure at rest was obtained in the seated position after ≥5 minutes of quiet rest using an automated sphygmomanometer (Dinamap PRO 100; GE healthcare, Milwaukee, Wisconsin). Blood samples were collected after a 12-hour overnight fast and analyzed by the hospital Clinical Medicine Laboratory. Total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and serum triglycerides were analyzed by enzymatic colorimetric and liquid selective detergent methods, respectively, using a Hitachi 7600 analyzer (Hitachi Co., Tokyo, Japan). Fasting glucose levels were determined using the Hexokinase, UV method (Hitachi-7600; Hitachi Co.). High-sensitivity C-reactive protein (CRP) was measured using a CRP (II) Latax X2 turbidimetric method (Hitachi Co.). Inter- and intra-assay coefficients of variation were <5% for all blood variables.
The presence of CMS was defined as having ≥3 of the following risk factors: waist girth >90 cm, blood pressure >130/85 mm Hg, high-density lipoprotein cholesterol <40 mg/dl, triglycerides >150 mg/dl, and glucose >100 mg/dl based on the National Cholesterol Education Program’s adult treatment panel III criteria and WHO Asia-Pacific obesity criteria for waist circumference.
CAC was measured using the multidetector computed tomography system, Brilliance 40 (Phillips Medical Systems, Cleveland, Ohio) or VCT LightSpeed 64 (GE Healthcare, Milwaukee, Wisconsin). The total CAC score was computed by summing the CAC scores of all foci in the epicardial coronary system and quantitated using the Agatston score. The prevalence of subclinical atherosclerosis was defined as dichotomous variables by CAC with an Agatston score >0 as previously reported.
The common CIMT was also used as a marker of subclinical carotid atherosclerosis. Carotid artery ultrasound imaging was performed using a high-resolution B-mode ultrasound system (Logiq 7; GE Medical System, Milwaukee, Wisconsin) with a 5 to 13 MHz linear array transducer. CIMT was measured in the supine position as the distance between the leading edge of the lumen-intima interface and the foremost border of the media-adventitia interface of the far wall of the carotid artery. The CIMT was obtained 10 mm proximal to the carotid bifurcation. The overall maximal CIMT was defined as the mean of the maximal intima-media thickness and averaged for the left and right sides. The prevalence of subclinical atherosclerosis was defined as a mean CIMT more than the seventy-fifth percentile for each age group.
Participants underwent peak or symptom-limited cardiopulmonary exercise testing using the conventional Bruce treadmill protocol. The peak heart rate was obtained through 12-lead ECGs (Q-4500, Quinton Cardiology Systems, Bothell, Washington) and defined as the highest value achieved during exercise testing. The percentage of age-predicted maximal heart rate was calculated as peak heart rate/(220 − age) × 100. Fitness was directly measured by VO 2peak during progressive testing to volitional fatigue (Jaeger Oxycon Delta; Erich Jaeger, Hoechberg, Germany) and defined as the highest or peak attained oxygen consumption, expressed as ml/kg/min, recorded during the test, and classified by tertiles of age-specific values. Fitness was categorized by fit (middle and upper tertiles) and unfit (lower tertile) as previously described.
Data are presented as mean ± SD and as proportions for categorical variables. CRP and CAC were expressed as median and interquartile ranges because these were not normal distributions. For 2 group comparisons by the presence of CMS, variables were assessed using an independent t test and chi-square tests for continuous and categorical variables, respectively. The CRP and CAC values were evaluated using a nonparametric t test (Mann-Whitney test). To determine the associations of CMS components (3 groups: 0, 1 to 2, and ≥3 risk factors) and fitness (3 groups; lower, middle, and higher) with subclinical atherosclerosis (CAC and CIMT), odds ratios (ORs) and 95% confidence intervals (CIs) from multivariate logistic regression models were calculated after adjusting for age, CRP, cigarette smoking, hypertension, and diabetes. Participants were divided into 4 groups based on CMS (with and without CMS) and fitness levels (fit and unfit) to determine the joint associations of CMS and fitness on subclinical atherosclerosis. All analyses were conducted using the SPSS 22.0 (SPSS, Armonk, New York), and statistical significance was set at p <0.05.
Results
Table 1 presents a comparison of participants with and without the CMS. Participants with CMS had more cardiovascular disease risk factors, lower peak heart rate, and VO 2peak than participants without CMS. Participants with CMS had significantly higher CAC scores and CIMT than those without CMS (p <0.05).
| Variable | Cardiometabolic syndrome | p – value | |
|---|---|---|---|
| No (n = 1453) | Yes (n = 654) | ||
| Age (years) | 53 ± 6 | 53 ± 6 | 0.722 |
| Body mass index (kg/m 2 ) | 24.2 ± 2.3 | 26.3 ± 2.4 | <0.001 |
| Waist girth (cm) | 85.4 ± 6.3 | 92.2 ± 6.3 | <0.001 |
| Current smoker | 18.8% | 21.1% | 0.215 |
| Hypertension | 7.2% | 35.9% | <0.001 |
| Diabetes mellitus | 9.3% | 22.3% | <0.001 |
| Systolic blood pressure (mmHg) | 116 ± 14 | 130 ± 16 | <0.001 |
| Diastolic blood pressure (mmHg) | 75 ± 9 | 84 ± 10 | <0.001 |
| Total cholesterol (mg/dl) | 197 ± 35 | 203 ± 38 | <0.001 |
| High-density lipoprotein cholesterol (mg/dl) | 51 ± 12 | 43 ± 10 | <0.001 |
| Low-density lipoprotein cholesterol (mg/dl) | 124 ± 30 | 127 ± 34 | 0.065 |
| Triglycerides (mg/dl) | 130 ± 66 | 208 ± 102 | <0.001 |
| Glucose (mg/dl) | 99 ± 20 | 112 ± 27 | <0.001 |
| C-reactive protein (mg/dl) | 0.06 (0.03-0.12) | 0.09 (0.05-0.16) | 0.039 |
| Coronary artery calcification (Agatston units) | 2 (0-52) | 6 (0-73) | 0.035 |
| Carotid artery intima media thickness (mm) ∗ | 0.63 ± 0.14 | 0.65 ± 0.15 | 0.011 |
| Peak heart rate (beats/min) | 152 ± 12 | 150± 13 | <0.001 |
| Age-predicted maximal heart rate (%) | 92 ± 6 | 91 ± 7 | 0.066 |
| Peak respiratory exchange ratio | 1.10 ± 0.08 | 1.11 ± 0.08 | 0.127 |
| Peak oxygen consumption (ml/kg/min) | 31.8 ± 4.5 | 29.9 ± 4.1 | <0.001 |
Table 2 lists the ORs and 95% CI of the CMS components with prevalence of subclinical atherosclerosis. The prevalence of CAC and CIMT were directly associated with increasing numbers of CMS components (p <0.05). After adjusting for age, CRP, smoking, hypertension, diabetes, and peak oxygen consumption, participants with CMS demonstrated a higher prevalence of CAC and CIMT compared with those without CMS. Table 3 presents the ORs of fitness in relation to the prevalence of subclinical atherosclerosis. Upper fitness was associated with a lower prevalence of CAC and CIMT compared with lower fitness after adjusting for potential confounding variables, including CMS components. In addition, each 1 metabolic equivalent (3.5 ml/kg/min) increment in fitness was associated with a 10% and 19% lower prevalence of CAC and CIMT after adjusting for risk factors (model 2).
| Variables | n | Prevalence n (%) | Unadjusted OR (95% CI) | Model 1 OR (95% CI) | Model 2 OR (95% CI) |
|---|---|---|---|---|---|
| CAC score (>0) | |||||
| Metabolic risk factor (0) | 416 | 193 (46.5%) | 1 (ref) | 1 (ref) | 1 (ref) |
| Metabolic risk factor (1-2) | 1037 | 604 (58.2%) | 1.61 (1.28-2.03) | 1.45 (1.13-1.85) | 1.40 (1.10-1.79) |
| Metabolic risk factor (≥3, CMS) | 654 | 391 (59.8%) | 1.72 (1.34-2.20) | 1.52 (1.14-2.03) | 1.41 (1.05-1.89) |
| CIMT (>75 th percentile) | |||||
| Metabolic risk factor ( 0 ) | 381 | 46 (12.1%) | 1 (ref) | 1 (ref) | 1 (ref) |
| Metabolic risk factor (1-2) | 953 | 181 (19.0%) | 1.71 (1.21-2.42) | 1.61 (1.13-2.29) | 1.53 (1.07-2.18) |
| Metabolic risk factor (≥3, CMS) | 609 | 140 (23.0%) | 2.17 (1.52-3.12) | 1.91 (1.29-2.83) | 1.70 (1.14-2.52) |
| Variables | n | Prevalence n (%) | Unadjusted OR (95% CI) | Model 1 OR (95% CI) | Model 2 OR (95% CI) |
|---|---|---|---|---|---|
| CAC score (>0) | |||||
| Lower fitness | 713 | 450 (63.1%) | 1 (ref) | 1 (ref) | 1 (ref) |
| Middle fitness | 688 | 378 (54.9%) | 0.72 (0.58-0.89) | 0.74 (0.59-0.93) | 0.75 (0.60-0.95) |
| Upper fitness | 706 | 360 (51.0%) | 0.61 (0.49-0.75) | 0.67 (0.53-0.84) | 0.69 (0.55-0.88) |
| Continuous variable (1 MET) | 0.76 (0.71-0.82) | 0.89 (0.82-0.96) | 0.90 (0.83-0.98) | ||
| CIMT (>75 th percentile) | |||||
| Lower fitness | 658 | 174 (26.4%) | 1 (ref) | 1 (ref) | 1 (ref) |
| Middle fitness | 622 | 96 (15.4%) | 0.51 (0.38-0.67) | 0.52 (0.40-0.69) | 0.54 (0.41-0.71) |
| Upper fitness | 663 | 97 (14.6%) | 0.48 (0.36-0.63) | 0.51 (0.39-0.68) | 0.53 (0.40-0.71) |
| Continuous variable (1 MET) | 0.80 (0.74-0.88) | 0.79 (0.72-0.88) | 0.81 (0.73-0.90) | ||
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