Metabolic syndrome and its individual components with mortality among patients with coronary heart disease

International Journal of Cardiology 224 (2016) 8–14

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Metabolic syndrome and its individual components with mortality among patients with coronary heart disease☆ Qian Chen a,b,1, Yuan Zhang c,1, Ding Ding a,1, Dan Li a,1, Min Xia a,1, Xinrui Li a,1, Yunou Yang a,1, Qing Li a,1, Gang Hu b,⁎,1, Wenhua Ling a,⁎,1 a Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-sen University, No. 74 Zhongshan Road 2, Guangzhou, Guangdong 510080, China b Chronic Disease Epidemiology Laboratory, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808, USA c Department of Cardiology, General Hospital of Guangzhou Military Command of People's Liberation Army, Guangdong 510010, China

a r t i c l e

i n f o

Article history: Received 9 May 2016 Received in revised form 19 August 2016 Accepted 20 August 2016 Available online 22 August 2016 Keywords: Coronary heart disease Metabolic syndrome All-cause mortality Cardiovascular mortality Cohort study

a b s t r a c t Background: The metabolic syndrome (MetS) and its metabolic risk factors appear to promote the development of atherosclerotic cardiovascular disease. The aim of this study was to examine the association of MetS and its individual components with all-cause and cardiovascular mortality among patients with coronary heart disease (CHD). Methods: We performed a prospective, hospital-based cohort among 3599 CHD patients in China. Cox proportional hazards regression models were used to estimate the association of MetS and its components at baseline with risk of mortality. Results: During a mean follow-up period of 4.9 years, 308 deaths were identified, 200 of which were due to cardiovascular disease. Compared with patients without MetS, patients with MetS according to the AHA/NHLBI statement had a 1.26-fold higher risk (95% CI, 1.01–1.59) of all-cause mortality and a 1.41-fold higher risk (1.06–1.87) of cardiovascular mortality. Patients with increasing numbers of components of MetS had a gradually increased risk for all-cause and cardiovascular mortality (P b 0.05). When each component of MetS was considered as a dichotomized variable separately, only low high-density lipoprotein cholesterol (HDL-C) and elevated fasting blood glucose (FBG) were associated with all-cause and cardiovascular mortality. After using restricted cubic splines, we found a U-shaped association of HDL-C, body mass index and blood pressure, a positive association of FBG, and no association of triglycerides with the risks of all-cause and cardiovascular mortality. Conclusions: MetS is a risk factor for all-cause and cardiovascular mortality among CHD patients. It is very important to control metabolic components in a reasonable control range. © 2016 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Metabolic syndrome (MetS) is a constellation of cardiometabolic risk factors, including hyperglycemia, abdominal obesity, dyslipidemia and elevated blood pressure (BP). It has been proposed that MetS is a powerful determinant of type 2 diabetes and cardiovascular disease (CVD) in the general population [1,2]. Coronary heart disease (CHD) is one of the leading causes of death worldwide [3]. Patients with CHD are more likely to have MetS and its individual components than the general population [4–7]. It has been ☆ This study was supported by the State Key Program of National Natural Science Foundation of China (Grant 81130052) and Qian Chen is supported by International Program for Ph.D. Candidates, Sun Yat-Sen University. ⁎ Corresponding authors. E-mail addresses: [email protected] (G. Hu), [email protected] (W. Ling). 1 This author takes responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.

http://dx.doi.org/10.1016/j.ijcard.2016.08.324 0167-5273/© 2016 Elsevier Ireland Ltd. All rights reserved.

shown that about 45% patients with CHD have MetS [8], about 35% are obese, more than 20% report diabetes, more than 50% have hypertension, and almost 60% have dyslipidemia [9]. Several studies have assessed the associations of MetS and its individual components with the risk of mortality among patients with CHD, but the results are inconsistent. Several studies provided supportive information of positive associations [6,10,11] while other studies have reported no associations [8,12] between MetS and long-term mortality among patients with CHD. Some but not all studies have found that low high-density lipoprotein cholesterol (HDL-C), hyperglycemia, and elevated triglycerides (TG) have a positive association with increased risks of all-cause and CVD mortality among patients with CHD [13–15]. Moreover, the relationship of body mass index (BMI) and BP with the risk of mortality among CHD patients is complicated and unclear. Some studies showed the “paradoxical” decrease in all-cause mortality with increased BMI in patients after percutaneous coronary intervention [10,12]. However, some epidemiological studies have found positive associations, U-

Q. Chen et al. / International Journal of Cardiology 224 (2016) 8–14

shaped associations, or no associations of BMI and BP with the risks of all-cause and CVD mortality among CHD patients [10,16–20]. Since Mets and its individual components are more common in CHD patients, and their associations with mortality are inconsistent, compared with the general population, more studies with large sample sizes of CHD patients are needed to assess this complicated association. The aim of the present study was to evaluate the associations of MetS and its individual components with the risks of all-cause and CVD mortality among Chinese patients with CHD. 2. Methods 2.1. Study population We have conducted a prospective, hospital-based cohort, the Guangdong Coronary Artery Disease Cohort (GCADC). Details of the GCADC study have been published previously [13]. Using the same selection, criteria and ascertainment of CHD, we first recruited 1984 patients during 2008–2011 [13], and then further included 1615 patients via electronic medical records during 2013–2014. Totally, we recruited 3599 successive inpatients admitted to the Cardiology Department of three superior specialty hospitals in Guangdong (Guangzhou Military General Hospital, Sun Yat-Sen Memorial Hospital, and First Affiliated Hospital of Sun Yat-Sen University) between October 2008 and December 2011 and diagnosed as CAD [International Classification of Diseases (ICD)-10 codes I20-I25] according to World Health Organization 1999/2000 guidelines [21,22]. The present study included 3351 CAD patients aged 40 years or older after excluding participants with incomplete data at baseline (n = 248). Informed consent was obtained from each of the first recruited patients from the GCADC study. We did not obtain informed consent from those additional participants involved in the present study because we used anonymized data compiled from electronic medical records. The study plan for the first recruited patients and analysis plan for the whole patients were approved by the Sun Yat-Sen University Ethics Committee, and all clinical investigations were conducted according to the principles expressed in the Declaration of Helsinki. 2.2. Measurements In the GCADC study, every patient's general information of examination date, birth date, gender, address, education level, marital status, leisure-time physical activity, smoking habits, alcohol consumption, history of diseases and use of medication before admission was ascertained by a standardized questionnaire through a face-to-face interview [13] or electronic medical records. We classified smoking habits and alcohol consumption into three groups: never, past, or current. Current smoking was defined as regularly at least one cigarette per day and lasting for more than 6 months before the study, and current alcohol drinking was defined as drinking any type of alcoholic beverage at least once a week and lasting for half a year before the study. Acute coronary syndrome was defined as the occurrence of any of unstable angina pectoris, ST-segment elevation myocardial infarction, and non-ST-segment elevation myocardial infarction within 3 months. Clinical characteristics, clinical test results, and treatment of all participants were extracted from an electronic case record system. At admission, trained nurses measured height, weight and BP using a standard protocol [23]. BMI was defined as the weight in kilograms divided by the square of height in meters. A venous blood specimen was drawn in the next morning after hospital admission with at least 12 h fasting. Lipids and fasting blood glucose (FBG) were determined by standard methods. Total cholesterol, TG, and HDL-C levels were determined using enzymatic methods, and low-density lipoprotein cholesterol level was calculated using the Friedewald equation. 2.3. Definition of the metabolic syndrome MetS was determined using the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) scientific statement [24]. We utilized BMI instead of waist circumference because waist circumference was not measured at baseline. The subjects were considered to have MetS if they had 3 or more of the following components: obesity (BMI ≥ 28 kg/m2), elevated TG (≥1.7 mmol/L), reduced HDL-C (b1.03 mmol/L in men and b1.30 mmol/L in women), elevated BP (≥130 mm Hg systolic blood pressure (SBP) or ≥85 mm Hg diastolic blood pressure (DBP) or using antihypertensive drug treatment in a patient with a history of hypertension), and elevated FBG (≥5.6 mmol/L or on drug treatment for elevated glucose). In addition, we used restricted cubic splines in Cox models to find the best control range of each individual component of Mets with the lower risk of all-cause and cardiovascular mortality. Then we developed modified AHA/NHLBI criteria to define Mets which required the presence of at least 3 of the following: BMI b 18.5 or ≥28 kg/m2; HDLC b 1.03 or ≥1.55 mmol/L in men and b1.30 or ≥1.55 mmol/L in women, BP b 130/85 or ≥160/100 mm Hg SBP/DBP, TG ≥ 1.7 mmol/L and FBG ≥ 5.6 mmol/L or on drug treatment for elevated glucose. 2.4. Prospective follow-up Follow-up information was obtained from hospital medical records of readmission, telephone contacts with patients or their immediate family members, and death registration

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at the Guangdong Provincial Center for Disease Control and Prevention. Follow-up of each cohort patients continued until the date of death or September 30, 2015. The ICD codes were used to identify the cause of death, and the ICD codes I00–I99 were classified as CVD deaths.

2.5. Statistical analyses Differences in risk factors by sex were tested by the general linear model after adjustment for age for continuous variables and Chi-square analysis for categorical variables. Cox proportional hazards models were performed to estimate the associations between different levels of each component of MetS at baseline and the risk of allcause and cardiovascular mortality. The analyses were adjusted for age and sex, and further for education, marital status, smoking status, alcohol drinking, leisure-time physical activity, BMI, SBP, TG, HDL-C, types of CHD, FBG, use of antihypertensive medications, use of glucose-lowering medications, use of lipid-lowering medications, and use of antiplatelet medications, other than the variables in the analysis. We also used the cox proportional hazard models to estimate the association of the MetS and the increasing number of the metabolic components with the risks of all-cause and cardiovascular mortality by different definitions after adjustment for age, gender, marital status, education, leisure-time physical activity, types of CHD, smoking status, alcohol drinking, use of antiplatelet medications, and use of lipidlowering medications. In addition, we used restricted cubic splines in Cox models to test whether there was a dose–response or non-linear association of each component of Mets (HDL-C, BMI, SBP, DBP, TG, and FBG) as a continuous variable with the risks of all-cause and CVD mortality. Statistical significance was considered to be P b 0.05. All statistical analyses were performed using PASW for Windows, version 20.0 (IBM SPSS Inc., Chicago, IL) and SAS for Windows, version 9.4 (SAS Institute, Cary, NC).

Table 1 Baseline characteristics of patients with coronary heart disease. Characteristic

Men

Women

No. of participants Age (y) Body mass index (kg/m2) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Fasting blood glucose (mmol/L) High-density lipoprotein cholesterol (mmol/L) Low-density lipoprotein cholesterol (mmol/L) Triglycerides (mmol/L) Total cholesterol (mmol/L) Married (%) Years of education (%) ≤9 10–12 ≥ 13 Smoking (%) Never Past Current Alcohol drinking (%) Never Past Current Leisure-time physical activity (%) None ≤30 min/day N30 min/day No data Type of coronary artery disease (%) Acute coronary syndrome Chronic coronary artery disease History of diseases (%) Hypertension Diabetes Dyslipidemia Use of medication before admission (%) Antihypertensive drugs Anti-diabetic drugs Lipid-lowering drugs Anti-platelet drugs

2113 62.2 (0.24) 24.0 (0.07) 134 (0.48) 78.1 (0.28) 6.51 (0.06) 1.08 (0.01) 2.91 (0.02) 1.82 (0.03) 4.62 (0.03) 78.5

1238 67.1 (0.31) 24.2 (0.10) 137 (0.63) 77.9 (0.36) 6.71 (0.08) 1.24 (0.01) 3.11(0.03) 1.90 (0.04) 5.06 (0.03) 75.6

P value

62.6 17.7 19.7

75.2 13.2 11.7

41.4 14.5 44.1

95.4 1.5 3.1

74.9 6.8 18.3

98.8 0.2 1.0

19.0 11.0 22.6 47.5

13.5 10.9 22.9 52.7

61.7 38.3

48.5 51.5

75.4 21.4 18.9

79.3 27.1 20.6

0.010 b0.001 0.24

45.6 15.2 16.8 10.9

58.6 20.0 14.3 10.9

b0.001 b0.001 0.062 0.95

b0.001 0.096 b0.001 0.72 0.044 b0.001 b0.001 0.124 b0.001 0.056 b0.001

b0.001

b0.001

0.001

b0.001

Data are mean (standard error) or percentage; all continuous variables are adjusted for age, except for age.

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Q. Chen et al. / International Journal of Cardiology 224 (2016) 8–14

3. Results 3.1. Baseline characteristics of participants The baseline demographic and clinical characteristics of the study population by gender were presented in Table 1. The mean age was 62.2 years in men and was 67.1 years in women. Since the interactions between sex and MetS status according to the AHA/NHLBI statement on the risks of all-cause and cardiovascular mortality were not significant, data for men and women were combined in the analyses. 3.2. Associations of metabolic components with mortality During a mean follow-up of 4.9 years, 308 deaths were recorded, 200 of which were due to CVD. There was a U-shaped association of HDL-C and BMI with the risks of all-cause and CVD mortality, a positive association of FBG with the risks of all-cause and CVD mortality, no association of BP and the risks of mortality, and no association of triglycerides with the risks of CVD mortality (Table 2). The multivariable-adjusted (age, sex, marital status, education, smoking, alcohol consumption, leisure-time physical activity, types of CHD, HDL-C, TG, FBG, SBP, BMI, use of antihypertensive medications, use of glucose-lowering medications, use of lipid-lowering medications, and use of antiplatelet medications, other than the variable in the analysis) hazard ratios (HRs) associated with different levels of

HDL-C (b 1.03, 1.03–1.55 [reference group], ≥ 1.55 mmol/L) in men were 1.94 (95% confidence interval [CI], 1.43–2.65), 1.00, and 2.04 (95% CI, 1.20–3.48) for all-cause mortality, and 2.52 (95% CI, 1.70– 3.73), 1.00, and 2.76 (95% CI, 1.45–5.28) for CVD mortality, respectively. Women with a lower HDL-C (b1.03 mmol/L) were at a higher risk of allcause mortality compared with women with a higher HDL-C (1.30– 1.55 mmol/L). The multivariable-adjusted HRs associated with different levels of BMI (b 18.5, 18.5–23.9 [reference group], 24–27.9, ≥28 kg/m2) were 1.59 (95% CI, 1.05–2.39), 1.00, 0.81 (95% CI, 0.63–1.06), and 1.04 (95% CI, 0.70–1.53) for all-cause mortality, and 1.79 (95% CI, 1.09– 2.96), 1.00, 0.81 (95% CI, 0.58–1.12), and 1.09 (95% CI, 0.67–1.76) for CVD mortality, respectively. The multivariable-adjusted HRs associated with different levels of BP (b130/85, 130–139/85–89, 140–159/90–99 [reference group], and ≥ 160/100 mm Hg) were 1.12 (95% CI, 0.84– 1.50), 0.76 (95% CI, 0.53–1.09), 1.00, and 1.03 (0.73–1.44) for all-cause mortality, and 1.11 (95% CI, 0.78–1.58), 0.71 (95% CI, 0.45–1.12), 1.00, and 0.95 (95% CI, 0.62–1.45) for CVD mortality, respectively. After using restricted cubic splines to test whether there was a dose– response or non-linear association of each component of Mets (HDL-C, BMI, SBP, DBP, TG, FBG) with the risks of all-cause and CVD mortality (Supplementary Fig. 1), we chose the best ranges for each of above variables. The association between each dichotomized component and the risks of all-cause and CVD mortality is presented in Table 3. High HDLC and normal glucose but not non-obese (b 28 kg/m2), normal BP

Table 2 Hazard ratios for all-cause and cardiovascular mortality according to different levels of HDL cholesterol, fasting blood glucose, body mass index, blood pressure and triglycerides among patients with coronary heart disease. Variable

No. of participants

No. of death

Person-years

Hazard ratios (95% confidence intervals) All-cause mortality

HDL cholesterol (mmol/L) Men (n = 2113) b1.03 1.03–1.55 ≥1.55 P for difference Women (n = 1238) b1.03 1.03–1.30 1.30–1.55 ≥1.55 P for difference Fasting blood glucose (mmol/L) b5.6 5.6–7.0 ≥7.0 P for difference BMI (kg/m2) b18.5 18.5–23.9 24–27.9 ≥28 P for difference Blood pressure (mm Hg) b130/85 130–139/85–89 140–159/90–99 ≥160/100 P for difference Triglycerides (mmol/L) b1.70 1.70–2.24 ≥2.25 P for difference

CVD mortality Model 2

Model 1a

Model 2b

1.87 (1.39–2.52) 1.00 1.80 (1.07–3.03) b0.001

1.94 (1.43–2.65) 1.00 2.04 (1.20–3.48) b0.001

2.49 (1.70–3.63) 1.00 2.31 (1.23–4.33) b0.001

2.52 (1.70–3.73) 1.00 2.76 (1.45–5.28) b0.001

1521 2255 1390 1014

2.15 (1.15–4.01) 1.76 (0.96–3.23) 1.00 1.41 (0.68–2.92) 0.094

2.47 (1.28–4.77) 1.64 (0.88–3.07) 1.00 1.25 (0.59–2.67) 0.038

1.69 (0.78–3.63) 1.29 (0.61–2.74) 1.00 1.32 (0.55–3.17) 0.597

1.71 (0.75–3.90) 1.07 (0.49–2.35) 1.00 1.37 (0.54–3.49) 0.471

74 53 73

7934 4137 4389

1.00 1.44 (1.09–1.89) 1.61 (1.23–2.09) 0.001

1.00 1.35 (1.02–1.79) 1.38 (1.04–1.83) 0.042

1.00 1.38 (0.97–1.97) 1.80 (1.30–2.49) 0.002

1.00 1.26 (0.88–1.80) 1.55 (1.10–2.19) 0.046

29 156 91 32

20 100 59 21

660 7745 6179 1877

1.64 (1.10–2.44) 1.00 0.79 (0.61–1.03) 1.09 (0.74–1.60) 0.008

1.59 (1.05–2.39) 1.00 0.81 (0.63–1.06) 1.04 (0.70–1.53) 0.028

1.78 (0.10–2.90) 1.00 0.81 (0.58–1.11) 1.14 (0.71–1.83) 0.022

1.79 (1.09–2.96) 1.00 0.81 (0.58–1.12) 1.09 (0.67–1.76) 0.033

1244 646 927 534

118 47 84 59

79 29 56 36

6115 3236 4491 2620

1.25 (0.94–1.66) 0.82 (0.57–1.17) 1.00 1.16 (0.83–1.61) 0.078

1.12 (0.84–1.50) 0.76 (0.53–1.09) 1.00 1.03 (0.73–1.44) 0.178

1.25 (0.89–1.77) 0.76 (0.49–1.19) 1.00 1.06 (0.90–1.61) 0.136

1.11 (0.78–1.58) 0.71 (0.45–1.12) 1.00 0.95 (0.62–1.45) 0.245

1965 625 761

206 53 49

130 36 34

9500 3110 3852

1.00 0.92 (0.68–1.25) 0.78 (0.57–1.07) 0.305

1.00 0.88 (0.64–1.20) 0.65 (0.47–0.90) 0.035

1.00 1.02 (0.70–1.47) 0.90 (0.61–1.31) 0.831

1.00 0.99 (0.68–1.45) 0.74 (0.50–1.11) 0.32

Total

CVD

Model 1

1005 981 127

117 69 18

88 39 13

4899 4796 587

305 450 276 207

34 41 14 15

19 21 10 10

1579 845 927

118 87 103

143 1583 1241 384

a

b

HDL indicates high-density lipoprotein; CVD, cardiovascular disease; and BMI, body mass index. a Adjusted for age and gender, except for HDL cholesterol (only adjusted for age). b Adjusted for model 1 covariates plus marital status, education, smoking, alcohol consumption, leisure-time physical activity, types of coronary artery disease, HDL cholesterol, triglycerides, fasting blood glucose, systolic blood pressure, body mass index, use of antihypertensive medications, use of glucose-lowering medications, use of lipid-lowering medications, and use of antiplatelet medications, other than the variable in the analysis.

Q. Chen et al. / International Journal of Cardiology 224 (2016) 8–14

(b 130/85 mm Hg), and low TG (b 1.7 mmol/L) using the AHA/NHLBI definition were significantly associated with reduced risks of all-cause and CVD mortality. When we used the modified definition, abnormal HDL-C level (b 1.03 or ≥ 1.55 mmol/L in men, b1.30 or ≥ 1.55 mmol/L in women), and abnormal BMI (b 18.5 or ≥28 kg/m2) were significantly, and abnormal BP (b 130/85 or ≥160/100 SBP/DBP mm Hg) was marginally significantly associated with increased risks of all-cause and CVD mortality.

3.3. Associations of MetS with mortality Table 4 presented multivariable-adjusted HRs for all-cause and CVD mortality associated with MetS according to different criteria, and numbers of individual components. Compared with patients without MetS, patients with MetS according to the AHA/NHLBI definition had a 1.26-fold higher risk (95% CI, 1.01–1.59) of all-cause mortality and a 1.41-fold higher risk (95% CI, 1.06–1.87) of CVD mortality. CHD patients with 2–5 of metabolic components had multivariable-adjusted HRs of 1.65–1.73 for all-cause mortality and 1.77–2.15 for CVD mortality compared with those with 0–1 of metabolic components. When we used the modified criteria, the multivariable-adjusted HRs of all-cause and CVD mortality for patients with MetS compared to those without MetS increased to 1.53 (95% CI, 1.22–1.92) and 1.58 (95% CI, 1.19–2.10), respectively. There was a positive association of the numbers of metabolic components with the risks of all-cause and CVD mortality. When we excluded triglycerides from the MetS, only included HDL-C, FBG and BP in the MetS, or only included HDL-C, FBG and BMI in the MetS, a graded positive association of the numbers of metabolic components with the risks of all-cause and CVD mortality was still present.

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4. Discussion To the best of our knowledge, the present study is the first to investigate the association of MetS and its individual components with the risks of all-cause and CVD mortality among CHD patients in China. CHD patients with the MetS have an increased risk of death from all causes and CVD. When using the AHA/NHLBI criteria, only high FBG and low HDL-C were associated with increased risks of all-cause and CVD mortality. After using restricted cubic splines, we found a Ushaped association of HDL-C, BMI and BP with the risks of all-cause and CVD mortality, a positive association of FBG with the risks of allcause and CVD mortality, and no association of triglycerides with the risks of all-cause and CVD mortality. The association of MetS with an increased risk of mortality has been confirmed in the general population. Lakka et al. [25] found greater risks of death from all causes as well as CVD for those with MetS in middleaged men in Finland. Hu et al. [5] showed that non-diabetic persons with MetS had an increased risk of all-cause and CVD death in Europe. In the United States, CHD, CVD, and all-cause mortality were also higher in adults with MetS than in those without MetS [26]. However, in highrisk populations, this association was under contradictory [12,15,27,28]. Our investigation is in line with the concept that MetS is associated with increased risks of all-cause and CVD mortality among Chinese patients with CHD after adjustment for major CVD risk factors. Although the current criteria [24,29,30] for clinical prognosis of these metabolic components of MetS have been modified over time, it is still unknown whether the current criteria for each risk component of MetS still carry the same prediction value in the setting of CHD. As for CHD patients who are under particular conditions, it was necessary to control metabolic components in a reasonable control range. We used restricted cubic splines to develop a HR curve to evaluate full-range associations of each metabolic component with the risk of all-cause and CVD mortality among CHD patients. We found U-

Table 3 Hazard ratios for all-cause and cardiovascular mortality according to different levels of HDL cholesterol, fasting blood glucose, body mass index, blood pressure and triglycerides among patients with coronary heart disease. No. of participants

AHA/NHLBI definition for components of metabolic syndrome HDL cholesterol (mmol/L) ≥1.03 in men, ≥1.30 in women b1.03 in men, b1.30 in women Fasting blood glucose (mmol/L) b5.6 ≥5.6 and use of glucose-lowering medications BMI (kg/m2) b28 ≥28 Blood pressure (mm Hg) b130/85 ≥130/85 and use of antihypertensive medications Triglycerides (mmol/L) b1.70 ≥1.70 Modified definition for components of metabolic syndrome HDL cholesterol (mmol/L) 1.03–1.55 in men, 1.30–1.55 in women b1.03 or ≥1.55 in men, b1.30 or ≥1.55 in women BMI (kg/m2) 18.5–27.9 b18.5 or ≥28 Blood pressure (mm Hg) 130–159/85–99 b130/85 or ≥160/100

No. of death Total

CVD

1591 1760

116 192

72 128

1467 1884

106 202

2967 384

Person-years

Hazard ratios (95% confidence intervals)a All-cause mortality

CVD mortality

7786 8674

1.00 1.67 (1.31–2.14)

1.00 1.69 (1.25–2.30)

64 136

7385 9076

1.00 1.34 (1.03–1.74)

1.00 1.47 (1.06–2.04)

276 32

179 21

14,584 1877

1.00 1.09 (0.75–1.59)

1.00 1.14 (0.71–1.80)

804 2547

57 251

39 161

3926 12,535

1.00 1.06 (0.79–1.44)

1.00 1.03 (0.71–1.48)

1965 1386

206 102

130 70

9499 6961

1.00 0.75 (0.58–0.97)

1.00 0.86 (0.63–1.17)

1257 2094

83 225

49 151

6186 10,274

1.00 1.70 (1.31–2.20)

1.00 1.89 (1.36–2.62)

2824 527

247 61

159 41

13,923 2537

1.00 1.34 (1.01–1.78)

1.00 1.46 (1.03–2.07)

1573 1778

131 177

85 115

7726 8734

1.00 1.21 (0.96–1.52)

1.00 1.20 (0.90–1.59)

HDL indicates high-density lipoprotein; CVD, cardiovascular disease; and BMI, body mass index. a Adjusted for age, gender, marital status, education, smoking, alcohol consumption, leisure-time physical activity, types of coronary artery disease, HDL cholesterol, triglycerides, fasting blood glucose, systolic blood pressure, body mass index, use of antihypertensive medications, use of glucose-lowering medications, use of lipid-lowering medications, and use of antiplatelet medications, other than the variable in the analysis.

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Q. Chen et al. / International Journal of Cardiology 224 (2016) 8–14

shape associations of HDL-C, BMI and BP with the risks of all-cause and CVD mortality, a positive association of FBG with the risks of all-cause and CVD mortality, and no association of triglycerides with the risks of all-cause and CVD mortality. The GCADC study has already found that impaired fasting glucose (fasting glucose, 5.6– 6.9 mmol/L), newly diagnosed diabetes (fasting glucose, ≥ 7.0 mmol/ L), and known diabetes were associated with higher risks of all-cause and CVD mortality among Chinese CAD patients when comparing with patients with normal FBG (b5.6 mmol/L) [13]. Our present analysis confirmed the similar associations. Moreover, the J-shaped association between FBG at baseline and the risk of all-cause and CVD death displayed by spline spots, was consistent with the Collaborative analysis Of Diagnostic criteria in Europe (DECODE) study. A collaborative prospective study of 22 cohorts in Europe showed the J-shaped relations between baseline glucose and all-cause, CVD, and non-CVD mortality [31]. The cut point of increasing risk was below diabetic threshold, even for the impaired fasting glucose threshold, which was in concordance with American Diabetes Association criteria for impaired fasting glucose [32]. The possible cardiotoxicity of hyperglycemia inducing electrophysiological alterations, abolishing ischemia preconditioning, increasing activation of thrombosis, amplifying inflammation, and worsening endothelial dysfunction [33] may partly explain our results.

There was a lack of agreement on the associations of BMI and HDL-C with the risks of all-cause and CVD mortality among CHD patients. Previous studies have indicated the association of low level of HDL-C with increased risks of mortality in many conditions. But whether higher HDL-C level is a predictor of higher risks of all-cause and CVD mortality still remains controversial. Although some researchers suggested that therapies of raising HDL-C were in high demand for the secondary prevention of CAD, Angeloni et al. showed that the protective role of HDL-C was lost in a large European cohort of CHD patients undergoing surgical revascularization with coronary artery bypass grafting [33]. In the present study, CHD patients with low (b1.03 mmol/L in men and b1.30 mmol/L in women) and high (≥ 1.55 mmol/L) levels of HDL-C have increased risks of all-cause and CVD mortality. We supported that higher HDL-C levels might be harmful for CHD patients, and thus combined the low (b 1.03 mmol/L in men and b 1.30 mmol/L in women) and high (≥1.55 mmol/L) levels of HDL-C as abnormal HDL-C of MetS. Potential mechanisms of this association among CHD patients are unclear. One major explanation is that HDL functionality may be impaired with CVD [34]. Under particular conditions, HDL would lose its protective functions (antioxidant, anti-inflammation, anti-apoptotic, ameliorate endothelial dysfunction) and gain dysfunction, which might contribute to inflammatory processes that promote CVD in patients with atherosclerosis.

Table 4 Association of different definitions of the metabolic syndrome with the risk of all-cause and cardiovascular mortality among patients with coronary heart disease. Definition of the metabolic syndrome

AHA/NHLBI definition for clinical diagnosis of MetS MetS No Yes Components of MetS ≤1 of components 2 3 4 5 P for trend Modified definition of MetS MetS No Yes Components of MetS ≤1 of components 2 3 4 5 P for trend Modified definition of MetS (excluding triglycerides) ≤1 of components 2 3 4 P for trend Modified definition of MetS (HDL-C, fasting blood glucose and blood pressure) 0 1 2 3 P for trend Modified definition of MetS (HDL-C, fasting blood glucose and BMI) 0 1 2 3 P for trend

No. of participants

No. of death Total

CVD

1857 1494

154 154

95 105

784 1073 902 508 84

50 104 96 51 7

1906 1445

Person-years

Hazard ratios (95% confidence intervals)a All-cause mortality

CVD mortality

9092 7369

1.00 1.26 (1.01–1.59)

1.00 1.41 (1.06–1.87)

28 67 67 34 4

3892 5200 4426 2529 413

1.00 1.65 (1.17–2.32) 1.73 (1.23–2.44) 1.73 (1.16–2.57) 1.69 (0.76–3.76) 0.021

1.00 1.87 (1.20–2.91) 2.15 (1.38–3.36) 2.06 (1.24–3.43) 1.77 (0.61–5.12) 0.016

152 156

98 102

9403 7058

1.00 1.53 (1.22–1.92)

1.00 1.58 (1.19–2.10)

812 1094 981 409 55

52 100 103 46 7

25 73 64 35 3

4040 5363 4766 2017 276

1.00 1.62 (1.15–2.27) 2.05 (1.46–2.88) 1.98 (1.32–2.97) 2.68 (1.20–5.96) b0.001

1.00 2.46 (1.56–3.90) 2.72 (1.71–4.35) 3.17 (1.88–5.35) 2.45 (0.73–8.24) b0.001

1140 1351 749 111

68 126 96 18

37 89 61 13

5698 6632 3602 529

1.00 1.72 (1.27–2.31) 2.30 (1.67–3.15) 2.96 (1.74–5.02) b0.001

1.00 2.24 (1.52–3.30) 2.69 (1.78–4.06) 3.93 (2.06–7.50) b0.001

280 1022 1413 636

17 68 133 90

9 40 91 60

1412 5085 6892 3072

1.00 1.26 (0.74–2.15) 1.92 (1.15–3.20) 2.74 (1.62–4.63) b0.001

1.00 1.43 (0.69–2.97) 2.48 (1.25–4.95) 3.47 (1.71–7.05) b0.001

480 1446 1216 209

24 108 148 28

11 68 103 18

2434 7150 5894 984

1.00 1.73 (1.11–2.70) 2.79 (1.80–4.31) 3.19 (1.83–5.56) b0.001

1.00 2.41 (1.27–4.57) 4.32 (2.31–8.09) 4.57 (2.13–9.78) b0.001

CVD indicates cardiovascular disease; HDL-C, high-density lipoprotein cholesterol; BMI, body mass index; and MetS, metabolic syndrome. a Adjusted for age, gender, marital status, education, smoking, alcohol consumption, leisure-time physical activity, type of coronary artery disease, use of lipid-lowering medications, and use of antiplatelet medications.

Q. Chen et al. / International Journal of Cardiology 224 (2016) 8–14

A systematic review of 40 studies with 250,152 CAD patients has shown that patients with a low BMI (b20 kg/m2) had a higher relative risk (RR) for all-cause (RR, 1.37; 95% CI, 1.32–1.43) and CVD (RR, 1.45; 95% CI, 1.16–1.81) mortality while overweight (25– 29.9 kg/m2) had the lowest risk for all-cause and CVD mortality compared with patients with normal BMI [35]. In the present study, we found that CHD patients with underweight (b 18.5 kg/m2) were at the highest risks of all-cause and CVD mortality. Unlike the “obesity paradox” [35], our results showed that patients with obesity (≥ 28 kg/m2) appeared to be at the increased risk of mortality, though the HRs were not significant. The conclusion of “the lower the BP, the lower the risk” cannot be reached at present. Previous epidemiology studies supported that a low BP might be beneficial to adverse outcomes. Messerli et al. found a J-shaped relationship between DBP and all-cause mortality among CAD patients, with the higher risk occurring at DBP below 70 to 80 mm Hg [36]. Besides, in a large clinical trial (Ongoing Telmisartan Along and in combination with Ramipril Global Endpoint Trial), a J-sharped (nadir around 130 mm Hg) association between in-treatment SBP and cardiovascular death [37] was found. There is uncertainty about the appropriate BP target for CHD patients. In the present study, both low BP (SBP b 130 mm Hg and DBP b 85 mm Hg) and high BP (SBP ≥ 160 mm Hg or DBP ≥ 100 mm Hg) seemed to be associated with increased risks of all-cause and CVD mortality among CHD patients. Hypertriglyceridemia was less important than expected. Although prior studies have shown that higher TG was a predictor of adverse outcomes [14,38], the current study did not observe any associations between elevated triglycerides and a higher risk of death. We hypothesize that this might be related to the use of cholesterol-lowering medications in the CHD population because using cholesterol-lowering medication would tend to attenuate the association between dyslipidemia and mortality. There are several limitations in the present study. Some new markers might play a potential role in prognostic evaluation. An analysis in eastern India [39] showed that the prevalence of highly sensitive C reactive protein, homocysteine, lipoprotein a, and uric acid in acute coronary syndrome patients with no or minimal traditional risk factors was high. Lang et al. [40] have found that elevated mean platelet volume was associated with major cardiac outcomes among patients with ST-elevation myocardial infarction after percutaneous coronary intervention. However, data of these novel factors were unavailable at baseline in most of our enrolled patients; we could not evaluate the prognostic value of these markers in the present study. Second, selection bias may occur owing to enrolled participants from hospitals where in-patients may have a more severe disease status. However, we recruited both acute and chronic CHD patients, and some of them were electively admitted patients with mild status, which might reduce the bias. Third, although our analyses adjusted for an extensive set of CVD confounding factors, residual confounding due to the measurement error in the assessment of confounding factors or unmeasured factors for all CHD patients cannot be excluded. As mentioned earlier, we used BMI instead of waist circumference because our study did not have data on waist circumference. We used a cut-off value based on data from the Chinese representative samples to minimize the impact on the risk specificity of central obesity. Last, we only measured the components of MetS at baseline and did not further measure them during follow-up. Based on the limitations above, our findings may need to be further confirmed by RCTs or one large cohort with CHD patients. In conclusion, MetS is associated with increased risks of allcause and CVD mortality among Chinese patients with CHD. It is important to control metabolic components in a reasonable control range, especially for glucose, HDL cholesterol, and blood pressure. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ijcard.2016.08.324.

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Conflict of interests The authors declare that there is no conflict of interests regarding the publication of this paper. Acknowledgments This work was supported by the National Natural Science Foundation of China [grant number 81130052]. Qian Chen is supported by International Program for Ph.D. Candidates, Sun Yat-Sen University. References [1] Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. (1988/12/01 ed1988). p. 1595–607. [2] A.D. Liese, E.J. Mayer-Davis, S.M. Haffner, Development of the multiple metabolic syndrome: an epidemiologic perspective, Epidemiol. Rev. 20 (1998) 157–172. [3] GBD 2013 Mortality and Causes of Death Collaborators, Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013, Lancet 385 (2015) 117–171. [4] E.S. Ford, W.H. Giles, A.H. Mokdad, Increasing prevalence of the metabolic syndrome among U.S. adults, Diabetes Care 27 (2004) 2444–2449. [5] G. Hu, Q. Qiao, J. Tuomilehto, et al., Prevalence of the metabolic syndrome and its relation to all-cause and cardiovascular mortality in nondiabetic European men and women, Arch. Intern. Med. 164 (2004) 1066–1076. [6] C.A. Daly, P. Hildebrandt, M. Bertrand, et al., Adverse prognosis associated with the metabolic syndrome in established coronary artery disease: data from the EUROPA trial, Heart 93 (2007) 1406–1411. [7] S.V. Arnold, K.J. Lipska, Y. Li, et al., The reliability and prognosis of in-hospital diagnosis of metabolic syndrome in the setting of acute myocardial infarction, J. Am. Coll. Cardiol. 62 (2013) 704–708. [8] J.L. Petersen, E. Yow, W. AlJaroudi, et al., Metabolic syndrome is not associated with increased mortality or cardiovascular risk in nondiabetic patients with a new diagnosis of coronary artery disease, Circ. Cardiovasc. Qual. Outcomes 3 (2010) 165–172. [9] EUROASPIRE I and II Group, Clinical reality of coronary prevention guidelines: a comparison of EUROASPIRE I and II in nine countries. European Action on Secondary Prevention by Intervention to Reduce Events, Lancet 357 (2001) 995–1001. [10] P.K. Bundhun, Z.J. Wu, M.H. Chen, Impact of modifiable cardiovascular risk factors on mortality after percutaneous coronary intervention: a systematic review and metaanalysis of 100 studies, Med. (Baltimore) 94 (2015) e2313. [11] A. Nigam, M.G. Bourassa, A. Fortier, et al., The metabolic syndrome and its components and the long-term risk of death in patients with coronary heart disease, Am. Heart J. 151 (2006) 514–521. [12] K.B. Won, B.K. Kim, H.J. Chang, et al., Metabolic syndrome does not impact long-term survival in patients with acute myocardial infarction after successful percutaneous coronary intervention with drug-eluting stents, Catheter. Cardiovasc. Interv. 83 (2014) 713–720. [13] D. Ding, J. Qiu, X. Li, et al., Hyperglycemia and mortality among patients with coronary artery disease, Diabetes Care 37 (2014) 546–554. [14] J. Liu, F.F. Zeng, Z.M. Liu, et al., Effects of blood triglycerides on cardiovascular and all-cause mortality: a systematic review and meta-analysis of 61 prospective studies, Lipids Health Dis. 12 (2013) 159. [15] D.J. Maron, W.E. Boden, J.A. Spertus, et al., Impact of metabolic syndrome and diabetes on prognosis and outcomes with early percutaneous coronary intervention in the COURAGE (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation) trial, J. Am. Coll. Cardiol. 58 (2011) 131–137. [16] H.S. Gurm, P.L. Whitlow, K.E. Kip, The impact of body mass index on short- and longterm outcomes inpatients undergoing coronary revascularization. Insights from the bypass angioplasty revascularization investigation (BARI), J. Am. Coll. Cardiol. 39 (2002) 834–840. [17] O. Angeras, P. Albertsson, K. Karason, et al., Evidence for obesity paradox in patients with acute coronary syndromes: a report from the Swedish Coronary Angiography and Angioplasty Registry, Eur. Heart J. 34 (2013) 345–353. [18] Y. Arbel, O. Havakuk, A. Halkin, et al., Relation of metabolic syndrome with longterm mortality in acute and stable coronary disease, Am. J. Cardiol. 115 (2015) 283–287. [19] P. Verdecchia, F. Angeli, C. Cavallini, et al., The optimal blood pressure target for patients with coronary artery disease, Curr. Cardiol. Rep. 12 (2010) 302–306. [20] Z.J. Wang, Y.J. Zhou, B.Z. Galper, et al., Association of body mass index with mortality and cardiovascular events for patients with coronary artery disease: a systematic review and meta-analysis, Heart 101 (2015) 1631–1638. [21] R.J. Gibbons, K. Chatterjee, J. Daley, et al., ACC/AHA/ACP-ASIM guidelines for the management of patients with chronic stable angina: executive summary and recommendations. A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Management of Patients with Chronic Stable Angina), Circulation 99 (1999) 2829–2848. [22] E. Braunwald, E.M. Antman, J.W. Beasley, et al., ACC/AHA guidelines for the management of patients with unstable angina and non-ST-segment elevation myocardial infarction: executive summary and recommendations. A report of the American

14

[23]

[24]

[25] [26]

[27] [28] [29]

[30]

[31]

Q. Chen et al. / International Journal of Cardiology 224 (2016) 8–14 College of Cardiology/American Heart Association task force on practice guidelines (committee on the management of patients with unstable angina), Circulation 102 (2000) 1193–1209. WHO MONICA Project Principal Investigators (Ed.), The World Health Organization MONICA Project (monitoring trends and determinants in cardiovascular disease): a major international collaboration, J. Clin. Epidemiol. 41 (1988) 105–114. S.M. Grundy, J.I. Cleeman, S.R. Daniels, et al., Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement, Circulation 112 (2005) 2735–2752. H.M. Lakka, D.E. Laaksonen, T.A. Lakka, et al., The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men, JAMA 288 (2002) 2709–2716. S. Malik, N.D. Wong, S.S. Franklin, et al., Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults, Circulation 110 (2004) 1245–1250. E. Angeloni, G. Melina, U. Benedetto, et al., Metabolic syndrome affects midterm outcome after coronary artery bypass grafting, Ann. Thorac. Surg. 93 (2012) 537–544. G. Levantesi, A. Macchia, R. Marfisi, et al., Metabolic syndrome and risk of cardiovascular events after myocardial infarction, J. Am. Coll. Cardiol. 46 (2005) 277–283. K.G. Alberti, P.Z. Zimmet, Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation, Diabet. Med. 15 (1998) 539–553. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III), JAMA 285 (2001) 2486–2497. Is the current definition for diabetes relevant to mortality risk from all causes and cardiovascular and noncardiovascular diseases? Diabetes Care 26 (2003) 688–696.

[32] S.M. Grundy, B. Hansen, S.C. Smith Jr., J.I. Cleeman, et al., Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management, Circulation 109 (2004) 551–556. [33] E. Angeloni, F. Paneni, U. Landmesser, et al., Lack of protective role of HDL-C in patients with coronary artery disease undergoing elective coronary artery bypass grafting, Eur. Heart J. 34 (2013) 3557–3562. [34] R.S. Rosenson, H.B. Brewer Jr., B.J. Ansell, et al., Dysfunctional HDL and atherosclerotic cardiovascular disease, Nat. Rev. Cardiol. 13 (2016) 48–60. [35] A. Romero-Corral, V.M. Montori, V.K. Somers, et al., Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies, Lancet 368 (2006) 666–678. [36] F.H. Messerli, G. Mancia, C.R. Conti, et al., Dogma disputed: can aggressively lowering blood pressure in hypertensive patients with coronary artery disease be dangerous? Ann. Intern. Med. 144 (2006) 884–893. [37] P. Sleight, J. Redon, P. Verdecchia, et al., Prognostic value of blood pressure in patients with high vascular risk in the Ongoing Telmisartan Alone and in combination with Ramipril Global Endpoint Trial study, J. Hypertens. 27 (2009) 1360–1369. [38] P. Cullen, Evidence that triglycerides are an independent coronary heart disease risk factor, Am. J. Cardiol. 86 (2000) 943–949. [39] S. Mukherjee, K. Manna, S. Datta, Prevalence of novel risk factors in patients of acute coronary syndrome in eastern India: a detailed analysis, Int. Cardiovasc. Forum J. 4 (2015) 14–18. [40] L.-G. Lang, L. Hong, Z.-J. Li, et al., Prognostic value of postprocedural mean platelet volume on one-year major cardiac outcomes in ST-elevation myocardial infarction after percutaneous coronary intervention, Int. Cardiovasc. Forum J. 3 (2015) 10–13.