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Metabolic syndrome and the risk of sudden cardiac death in middle-aged men
International Journal of Cardiology 203 (2016) 792–797
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International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Metabolic syndrome and the risk of sudden cardiac death in middle-aged men☆ Sudhir Kurl a,⁎, David E. Laaksonen c, Sae Young Jae d, Timo H. Mäkikallio e, Francesco Zaccardi f, Jussi Kauhanen a, Kimmo Ronkainen a, Jari A. Laukkanen a,b a
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland Jyväskylä Central Hospital, Jyväskylä, Finland Institute of Clinical Medicine, Department of Medicine, Kuopio University Hospital, Kuopio, Finland d Department of Sports Informatics, College of Arts and Physical Education, University of Seoul, South Korea e Division of Cardiology, Department of Internal Medicine, University Hospital of Oulu, Oulu, Finland f Internal Medicine and Diabetes Care Unit, Policlinico Gemelli Hospital, Catholic University of Sacred Heart, Rome, Italy b c
a r t i c l e
i n f o
Article history: Received 12 March 2015 Received in revised form 7 October 2015 Accepted 27 October 2015 Available online 28 October 2015 Keywords: Metabolic syndrome Middle-aged men Sudden cardiac death
a b s t r a c t Background: Little is known about the relationship between metabolic syndrome and sudden cardiac death (SCD). We examined the association of metabolic syndrome, as defined by World Health Organization (WHO), International Diabetes Federation (IDF), National Cholesterol Education Program (NCEP) and American Heart Association (AHA) — IDF interim criteria, with incident SCD. We also assessed the association of a continuous metabolic risk score with SCD. Methods: A total of 1466 middle-aged men participating in a prospective population-based cohort study from eastern Finland with no history of coronary heart disease or diabetes at baseline were included. Results: During the average follow-up of 21 years 85 SCDs occurred. Men with the metabolic syndrome as defined by the WHO, NCEP, IDF and interim criteria had a 2.2–2.6 fold, increased risk for SCD, after adjusting for lifestyle and traditional cardiovascular risk factors not included in the metabolic syndrome definition (P b 0.001–0.011). A one-standard deviation increase in the metabolic risk score (composed of the sum of Z-scores for waist circumference, insulin, glucose, high-density lipoprotein (HDL) cholesterol, triglycerides, and blood pressure) was associated with a 1.68-fold higher (95% CI 1.33-2.11) risk of SCD. Even when adjusting further for systolic blood pressure, HDL cholesterol and body mass index, the association remained significant for the interim criteria and the metabolic risk score, but not for WHO, NCEP, or IDF definitions. Conclusions: Men with metabolic syndrome are at increased risk for SCD. Incident SCD associated with the IDF/ AHA interim criteria and metabolic risk clustering estimated by a score is not explained by obesity or traditional cardiovascular risk factors. Key messages: Men with metabolic syndrome are at increased risk for sudden cardiac death. Incident sudden cardiac death associated with metabolic risk clustering estimated by a score in not explained by obesity or traditional cardiovascular risk factors. Prevention of the metabolic syndrome may help reduce the health burden of SCD. © 2015 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Sudden cardiac death (SCD) accounts for one-half of all coronary heart disease (CHD)-related deaths. Since a majority of SCDs occur among the general segments of the population, the problem would require screening methods applicable to the general population. There continues to be interest in identifying clinically useful markers for SCD
☆ All the authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. ⁎ Corresponding author at: Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O. 1627, 70211 Kuopio, Finland. E-mail address: sudhir.kurl@uef.fi (S. Kurl).
http://dx.doi.org/10.1016/j.ijcard.2015.10.218 0167-5273/© 2015 Elsevier Ireland Ltd. All rights reserved.
among the general population. Epidemiological studies have shown that half of the victims of SCD have no physician-diagnosed CHD at the time of death [1–2]. Metabolic syndrome (MetS) is a common clinical condition with a prevalence varying from 10 to 40%, or even higher in older age groups, depending on the populations and definition of MetS [3–12]. A previous study found increased SCD risk for the metabolic syndrome based on the definitions of National Cholesterol Education Program III (NCEPATPIII) and International Diabetes Federation (IDF) with respect to SCD [3]. However, this previous study did not evaluate the risk of MetS for SCD based on World Health Organization (WHO) definition. Current definitions may also be criticized for the use of arbitrary dichotomous cut-offs for the features of the metabolic syndrome, even though
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risk factors such as blood pressure and high-density lipoprotein (HDL) cholesterol have continuous and dose-related associations with cardiovascular outcomes. Some researchers have therefore estimated metabolic risk as a continuous variable using the sum of the Z-scores of the individual metabolic risk factors [13,14]. The objective of the present investigation was to evaluate SCD risk for the MetS as defined by the WHO, NCEP, IDF and IDF/American Heart Association (AHA) interim criteria and a metabolic risk score in a population-based cohort of middle-aged men who did not have coronary heart disease or diabetes at baseline. 2. Research design and methods 2.1. Subjects This study group was subgroup of a random sample of 3433 men aged 42 to 60 years who resided in the town of Kuopio or its surrounding rural communities in eastern Finland. Of those invited, 2682 (83%) participated in the study. This Kuopio Ischemic Heart Disease Study (KIHD) was designed to investigate risk predictors for atherosclerotic cardiovascular outcomes in a population-based sample of men [7]. For the present study men with diabetes (n = 174) or CHD (n = 677) at baseline were excluded. Men with missing data (n = 615) on waist circumference or biochemical values included in the definition of the metabolic syndrome were excluded leaving 1466 for the analyses. 2.2. Assessment of components of the metabolic syndrome Blood pressure was measured with a random-zero sphygmomanometer. The mean of 6 measurements (3 while supine, 1 while standing, and 2 while sitting) of systolic and diastolic blood pressure was used. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Waist circumference was calculated as the average of 2 measurements taken after inspiration and expiration at the midpoint between the lowest rib and iliac crest. Waist-hip ratio was defined as waist girth/hip circumference measured at the trochanter major. Participants were asked to fast and to refrain from smoking for 12 h and to avoid alcohol intake for 3 days before blood sampling. Blood glucose was measured using a glucose dehydrogenase method after precipitation of proteins by tricholoracetic acid. Insulin was measured with a radioimmunoassay kit (Novo Nordisk, Bagsvaerd, Denmark) from the serum samples stored at –80 °C [7]. Because blood glucose was measured instead of plasma glucose, a blood glucose value of 5.6 mmol/L was considered to correspond to a plasma glucose level of 6.1 mmol/L [4], and a blood glucose value of 5.0 mol/L to correspond to a plasma glucose value of 5.6 mmol/L. Low-density lipoprotein (LDL) and high-density lipoprotein (HDL) fractions were separated from fresh serum by combined ultracentrifugation and precipitation. Lipoprotein fraction cholesterol and triglycerides were measured enzymatically [15]. 2.3. Metabolic syndrome As suggested by the European Group for the Study of Insulin Resistance, hypertension was defined at a lower level (at least 140/90 mm Hg or blood pressure medication) than the original WHO definition for consistency with the WHO-International Society of Hypertension and Sixth Joint National Committee recommendations [7,16–17], and microalbuminuria was not included in the definition [16]. The original WHO cut-off for serum HDL cholesterol was maintained. Abdominal obesity was defined according to the original WHO definition (waist-hip ratio N0.90 or BMI ≥30). The International Diabetes Federation consensus proposed a definition of MetS [18]. The MetS was defined as the presence of abdominal adiposity and two or more abnormalities of the following: elevated triglycerides (≥150 mg/dL or 1.7 mmol/L) or specific treatment for dyslipidemia, low HDL cholesterol (b40 mg/dL or 1.0 mmol/L for men), elevated fasting plasma glucose (≥100 mg/dL or 5.6 mmol/l) or antidiabetic treatment and elevated systolic or diastolic blood pressure (≥130/85 mm Hg) or antihypertensive medications. The MetS defined by the NCEP-ATPIII was the presence of 3 or more of the following: fasting plasma glucose of at least 110 mg/dL (6.1 mmol/L), serum triglycerides of at least 150.0 mg/dL (1.7 mmol/L), serum HDL cholesterol less than 40 mg/dL (1.04 mmol/L), blood pressure of at least 130/85 mm Hg, or waist girth of more than 102 cm. Use of waist girth of more than 94 cm was suggested for men genetically susceptible to insulin resistance [19]. In keeping with the clinically oriented NECP-ATPIII recommendations, the cut off for HDL cholesterol was rounded off in SI units (b1.0 mmol/L) [20]. The International Diabetes Federation consensus proposed a definition of MetS [18]. The MetS was defined as the presence of abdominal adiposity and two or more abnormalities of the following: elevated triglycerides (≥150 mg/dL or 1.7 mmol/L) or specific treatment for dyslipidemia, low HDL cholesterol (b40 mg/dL or 1.0 mmol/L for men), elevated fasting plasma glucose (≥100 mg/dL or 5.6 mmol/l) or antidiabetic treatment and elevated systolic or diastolic blood pressure (≥130/85 mm Hg) or antihypertensive medications. The IDF and AHA and several other organizations proposed an interim definition based on the presence of 3 or more of the following: fasting plasma glucose of at least 100 mg/dL (5.6 mmol/L), serum triglycerides of at least 150 mg/dL (1.7 mmol/L), serum HDL cholesterol less than 40 mg/dL (1.0 mmol/L), blood pressure of at least 130/ 85 mm Hg or blood pressure medication, or abdominal obesity using population-specific
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waist circumference [20]. A cut-off for waist of either 94 cm or 102 cm was suggested for europoid populations. For our study we used a cut-off of 94 cm. 2.4. Calculation of the metabolic risk score We calculated a continuous metabolic risk score (Metscore) similarly to previously published scores [21] using the sum of continuous Z-scores; waist circumference + insulin + glucose − HDL cholesterol + triglycerides + the average of SBP and DBP. A higher MetS score indicates a less favorable metabolic risk profile. 2.5. Assessment of risk factors Assessment of smoking, alcohol consumption, diet, socioeconomic status, medical history and medications and family history of diseases have been described previously [7,15,22]. 2.6. Classification of sudden cardiac death All deaths that occurred by the end of 2009 were checked from the hospital documents, wards of health centers and death certificates. Deaths were coded using to the Ninth International Classification of Diseases codes or the Tenth International Classification of Diseases codes. The sources of information were interviews, hospital documents, death certificates, autopsy reports and medico-legal reports [22]. There were no losses to follow-up. A death was determined SCD when it occurred either within 1 h after the onset of an abrupt change in symptoms or within 24 h after onset of an abrupt change in symptoms when autopsy data did not reveal a non-cardiac cause of sudden death. Sudden cardiac deaths that occurred out-of-hospital conditions were also defined based on hospital documents. Subjects who were successfully resuscitated from ventricular tachycardia (VT) or ventricular fibrillation (VF) were included in the definition of sudden cardiac arrest outcome. The deaths due to aortic aneurysm rupture, cardiac rupture or tamponade and pulmonary embolism, cancer or other non-cardiac co-morbidities were not included as SCD. The diagnostic classification of events was based on symptoms, electrocardiographic findings, cardiac enzyme elevations, autopsy findings (80%) and history of CHD together with the clinical and ECG findings of the paramedic staff. Thus, we have available all hospital documents including medical records, laboratory and ECG findings from hospital and paramedical staff and the use of medications and defibrillator. SCD cases were checked from deaths from cardiovascular causes and all available documents [22]. The documents related to the death were cross-checked in detail by two physicians. The independent event committee were blinded to clinical data performed classification of deaths. 2.7. Statistical analysis Skewed variable was normalized by taking the log, or in the case of conditioning leisure-time physical activity, by taking the square root. Comparisons of baseline variables between men who died suddenly during the follow-up and those who did not were made using the unpaired Student's t-test or chi-square test. Relative risks of WHO, NCEP and IDF definitions of the MetS with SCD were estimated using forced Cox proportional hazard regression models with adjustment for age and examination year (model 1); age, examination year, socio-economic status, smoking, alcohol consumption, and family history of CHD, dietary intake of saturated fats, and energy expenditure on leisure time physical activity (model 2). Relative hazards, adjusted for risk factors, were estimated as antilogarithms of coefficients from multivariate models. All tests for statistical significance were two-sided. The fit of the proportional-hazard models was examined by plotting the hazard functions in different categories of risk factors over time. The proportional hazard assumptions met indicated that the application of the models was appropriate. All statistical analyses were performed using the SPSS 20.0 Windows software.
3. Results 3.1. Baseline characteristics and follow-up events At the beginning of the follow-up, 15% out of 1381 men who did not suffer a SCD during the follow-up had the metabolic syndrome according to WHO definition, 8% had it according to the NCEP and IDF definitions, and 19% according to the IDF/AHA interim definition (Table 1). In men who died suddenly during the follow up (n = 85), the prevalence of the metabolic syndrome based on these definitions was about two-fold higher (p b 0.001–0.027). The metabolic risk score was also higher in men who died suddenly during the follow up (P = 0.001). When defining the metabolic syndrome at the top 20% of the metabolic risk score when classifying men with a MetSscore in the top 20% of the entire non-diabetic KIHD cohort (corresponding 18% in men without CHD or diabetes at baseline included in this study) as having the metabolic syndrome in our study population (corresponding to the
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Table 1 Characteristics of the 1466 middle-aged men without coronary heart disease or diabetes at baseline. Men who survived during the follow up Men who died suddenly during the follow Men who died suddenly out of (n = 1381) up (n = 85) hospital (n = 65) Age (years) Smokers (%) Alcohol consumption (g/week) Socioeconomic status (score) Family history of CHD‡ (%) Dietary saturated fat intake (energy-adjusted, g/d) Energy expenditure of §CLTPA Body mass index (kg/m2) Waist to hip ratio Waist girth (cm) Fasting serum glucose (umol/L) Fasting serum insulin (mU/L) Serum total cholesterol (mmol/L) LDLǁ cholesterol (mmol/L) HDLǁ cholesterol (mmol/L) Serum triglycerides (mmol/L) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Blood pressure medication (%) Metabolic risk score Metabolic syndrome (%) WHOb NCEPb IDFb IDF/AHAb Interim Metabolic risk score (top 20%)#
51.8 (5.8) 29 34 (7, 90) 11.2 (5.0) 45 45.9 [11]
53.8 (4.7) 41 39 (4, 123) 12.5 (4.7) 60 47.1 [10]
53.7 (5.1) 40 38 (4, 130) 12.8 (4.6) 55 47.9 [10]
85 (32, 194) 26.6 (3.3) 0.94 (0.06) 90.2 (9.3) 4.6 (0.5) 9.4 (7.2, 12.4) 5.8 (1.0) 3.9 (1.0) 1.3 (0.3) 1.08 (0.79, 1.52) 133 [16] 88 [10] 13 −0.33 (3.5)
70 (20, 166) 27.4 (4.0) 0.96 (0.05) 93.0 (10.5) 4.7 (0.5) 10.8 (8.1, 14.5) 5.9 (1.0) 4.1 (1.0) 1.3 (0.3) 1.01 (0.77, 1.75) 141 [16] 92 [10] 22 1.24 (3.9)
15 8 8 19 17
28 15 15 35 34
P-value* P-value† 0.003 0.020 0.82 0.026 0.009 0.31
0.018 0.075 0.83 0.020 0.14 0.18
69 (23, 130) 27.3 (4.1) 0.96 (0.05) 93.3 (10.9) 4.8 (0.6) 11.3 (8.6, 14.8) 5.9 (0.9) 4.1 1.2 0.98 (0.72, 1.64) 140 [16] 92 [10] 20 1.44 (3.97)
0.066 0.039 0.031 0.009 0.004 0.009 0.36 0.090 0.25 0.23 b0.001 0.001 0.016 b0.001
0.13 0.13 0.023 0.014 0.001 0.006 0.37 0.28 0.13 0.50 b0.001 0.007 0.14 b0.001
30 13 13 38 38
0.001 0.011 0.027 b0.001 b0.001
0.001 0.11 0.17 0.001 b0.001
Data are means, percentages, or medians (25th percentile, 75th percentile). *P-values are for the difference between men who died suddenly during the follow up and those who did not (Student's t-test or chi-square). †P-values are for the difference between men who did not die suddenly during the follow up and those who died suddenly out of hospital. ‡CHD denotes coronary heart disease. ǁCLTPA denotes conditioning leisure time physical activity. ǁLDL denotes low-density lipoprotein and HDL denotes high-density lipoprotein. bWHO denotes World Health Organization, NCEP National Cholesterol Education Program, IDF International Diabetes Federation and AHA American Heart Association. #Categorized by the top 20th percentile in the entire Kuopio Ischaemic Disease Study cohort, corresponding to the top 18% in these men without diabetes or ischemic heart disease at baseline.
top 18% in these men who died suddenly during the follow up (34% vs. 17%, P b 0.001, Table 1). Of the features of the metabolic syndrome, the most significant differences between men who died suddenly during the follow-up and those who did not were in SBP and DBP. Men who died suddenly during the follow up also had higher concentrations of serum insulin and glucose and a larger waist circumference and waist-to-hip ratio. There were no differences in dyslipidemia. Men who died suddenly were also older, smoked more, and more often had a family history of coronary heart disease and had a lower socioeconomic status (indicated by a higher score). The average follow-up time to death or the end of follow-up was 21.5 years (range 0.38–26.7 years). There were a total of 85 SCDs. A total of 65 SCDs (70.5%) occurred in out-of-hospital conditions.
3.2. The metabolic syndrome and risk of sudden cardiac death After adjustment for age, and examination year (model 1) the relative risk (RR) was 2.3–2.6 for SCD in men with metabolic syndrome according to WHO, NCEP, IDF and IDF/AHA interim definitions (Table 2). After adjustment for age, examination year, socio-economic status, smoking, alcohol consumption, family history of CHD LDL cholesterol concentrations, energy intake from saturated fats and energy expenditure of leisure time physical activity (model 2), the risk of SCD was still 2.2–2.6-fold higher among men with MetS according to these definitions (Table 2) than men without MetS. After further adjustment for traditional cardiovascular risk factors included in the definition of the metabolic syndrome (SBP and blood pressure medication as a marker of hypertension and HDL cholesterol) and BMI the association was attenuated (RR 1.46, 95% CI 0.83–2.57 for the WHO, RR 1.91, 95% CI 0.96–3.80 for the NCEP and RR 1.66, 95% CI 0.83–3.29 for the ID, and the IDF/AHA interim definition 2.56 (95% CI 1.63–4.01).
After adjustment for age and examination year (model 1), a one-SD increase in the MetSscore was associated with a 1.61-fold higher risk of SCD (95% CI 1.29–2.01). When classifying men with a MetSscore in the top 20% of the entire KIHD cohort (corresponding to 18% in men without coronary heart disease or diabetes at baseline included in this study) as having the metabolic syndrome, the RR was 2.04 (95% CI 1.20–3.47, Table 2). Further adjustment for socio-economic status, smoking, alcohol consumption, family history of CHD, LDL cholesterol concentrations, energy intake from saturated fats, and energy expenditure of leisure time physical activity (model 2) did not attenuate the associations (RR 1.68, 95% CI 1.33–2.11 for a one-SD change in the MetSscore; RR 2.83 (95% CI 1.78–4.50 for the categorized MetSscore). Even when adding traditional cardiovascular risk factors that are part of the definition of the metabolic syndrome (systolic blood pressure, blood pressure medication and HDL cholesterol) and BMI to model 2, the associations remained significant (RR 1.57, 95% CI 1.02–2.42 for a one-SD change in the MetSscore; RR 1.89 (95% CI 1.01–3.55 for the categorized MetSscore). When categorizing the metabolic syndrome by the top 15th percentile of the MetSscore, the results were similar. However, when defining the metabolic syndrome as middle-aged men in the top 10% of the MetSscore in the entire non-diabetic KIHD cohort (corresponding to 8.3% in men without CHD and diabetes and similar to the prevalence of the metabolic syndrome as defined by the NCEP and IDF), the association was weaker, and not significant when adding systolic blood pressure, blood pressure medication and BMI to model 2 (RR 1.45, 95% CI 0.69–3.03). Kaplan Meier curves are shown in the Fig. 1 based WHO definition. 3.3. The metabolic syndrome and risk of out-of-hospital sudden cardiac death After adjustment for age and examination year (model 1) the RR was 2.1–2.9 for OSCD in men with metabolic syndrome according to the
S. Kurl et al. / International Journal of Cardiology 203 (2016) 792–797 Table 2 Risk of sudden cardiac death according to metabolic syndrome in 1466 Middle-aged men with no prior ischemic heart disease or diabetes. Model 1 RR (95% CI)
Model 2 P value
RR (95% CI)
Risk for sudden cardiac death (85 cases) Metabolic syndrome WHO 2.30 (1.43–3.69) b0.001 2.34 (1.45–3.78) NCEP† 2.43 (1.34–4.42) 0.004 2.50 (1.36–4.58) IDF 2.36 (1.29–4.32) 0.006 2.20 (1.20–4.04) IDF/AHA interim 2.61 (1.67–4.09) b0.001 2.57 (1.63–4.06) Metabolic score 2.56 (1.63–4.01) b0.001 2.83 (1.78–4.50) (top 20%) Risk for out-of-hospital sudden cardiac death (60 cases) Metabolic syndrome WHO 2.50 (1.43–4.34) 0.001 2.52 (1.44–4.40) NCEP 2.13 (1.00–4.54) 0.049 2.22 (1.03–4.78) IDF 2.06 (0.96–4.40) 0.063 1.96 (0.91–4.2) IDF/AHA interim 2.94 (1.74–4.97) b0.001 2.89 (1.69–4.93) Metabolic risk score 3.08 (1.83–5.18) b0.001 3.35 (1.96–5.74) (top 20%)
P value
b0.001 0.003 0.011 b0.001 b0.001
0.001 0.041 0.087 b0.001 b0.001
Abbreviations are as in Table 1. Model 1: Adjusted for age and examination year. Model 2: Adjusted for age, examination year, socio-economic status, smoking, alcohol consumption, family history of coronary heart disease, LDL cholesterol concentrations, dietary intake of saturated fats, and energy expenditure of leisure time physical activity.
WHO, NCEP, IDF and IDF/AHA interim definitions (Table 2). After adjustment for age, examination year, socio-economic status, smoking, alcohol consumption, family history of CHD, LDL cholesterol concentrations, energy intake from saturated fats, and energy expenditure of leisure time physical activity (model 2), the risk of OSCD was 2.0–2.9-fold higher among men with MetS according to these definitions (Table 2) than men without MetS. The association was strongest for the IDF/ AHA definition and weaker for the NCEP and IDF definitions. After further adjustment for traditional cardiovascular risk factors included in the definition of the metabolic syndrome (systolic blood pressure, blood pressure medication as a marker of hypertension) and BMI the association was no longer significant for the WHO, NCEP and IDF definitions, but remained highly significant for the IDF/AHA interim definition (RR 2.36, 95% CI 1.26–4.42, P = 0.007). After adjustment for age and examination year (model 1), a one-SD increase in the MetSscore was associated with a 1.72-fold higher risk of OSCD (95% CI 1.32–2.24). When classifying men with a MetSscore in the
Fig. 1. Shows Kaplan Meier survival curves among men with and without metabolic syndrome based on the WHO definition.
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top 20% of middle-aged men in the entire KIHD population sample (top 19% in these men without CHD at baseline) as having the metabolic syndrome, the RR was 3.08 (95% CI 1.83–5.18, Table 2). Further adjustment for socio-economic status, smoking, alcohol consumption, family history of CHD, LDL cholesterol concentrations, energy intake from saturated fats, and energy expenditure of leisure time physical activity (model 2) did not attenuate the associations (RR 1.78, 95% CI 1.36–2.34 for a one-SD change in the MetSscore; RR 3.35 (95% CI 1.96–5.74 for the categorized MetSscore). Even when adding traditional cardiovascular risk factors that are part of the definition of the metabolic syndrome (systolic blood pressure, blood pressure medication and HDL cholesterol) and BMI to model 2, the associations remained significant (RR 1.84, 95% CI 1.11–3.04 for a one-SD change in the MetSscore; RR 2.59 (95% CI 1.34–5.39 for the categorized MetSscore). When categorizing the metabolic syndrome by the 15th percentile of the entire KIHD sample, the results were similar, but when using the 10th percentile cut-off, the association was not significant (RR 1.24, 95% CI 0.51–3.03). 4. Discussion In this prospective population-based cohort of middle-aged men without coronary heart disease or diabetes at baseline the MetS based on WHO, IDF and NCEP definitions was associated with a more than two-fold higher risk of SCD during the 21-year follow up, independently of major risk factors not included in the definition of the metabolic syndrome. The clustering of metabolic risk factors as estimated by a continuous metabolic risk score also predicted SCD during the follow-up. Even when adjusting further for BMI, HDL cholesterol, SBP and the use of blood pressure medication, the metabolic syndrome using the IDF/ AHA definition and the metabolic risk score was still associated with SCD, but the WHO, NCEP and IDF definitions were not. We formed the Metscore by using the sum of the Z-scores for waist circumference, concentrations of insulin, glucose, HDL cholesterol and triglycerides, and the average of systolic and diastolic blood pressure. This score is similar to those used in other studies to estimate clustering of metabolic risk, and avoid shortcomings of the metabolic syndrome defined by dichotomous variables based on arbitrary cut-offs to define the metabolic syndrome. When defining the metabolic syndrome as men in the top 20% of the Metscore in the entire non-diabetic KIHD cohort (corresponding to the top 18% in the men without CHD at baseline included in this study and similar to the prevalence of the MetS as defined by the WHO), the increased risk of SCD associated with this definition remained associated with SCD even after adjustment for potential confounding factors, BMI, and traditional cardiovascular risk factors, including blood pressure, blood pressure medication and HDL cholesterol. Findings remained similar when using the top 15%, but not when defining the MetS as the top 10% of the metabolic risk score (roughly corresponding to the prevalence of the NCEP and IDF definitions of the MetS). This may suggest that decreased statistical power related to the lower prevalence may partly explain why the NCEP and IDF definitions were not related to SCD after adjustment for blood pressure. This may also partly explain why the metabolic syndrome defined by the IDF/AHA interim criteria was also associated with SCD even after adjustment for classic CVD risk factors also included in the definition of the metabolic syndrome. Use of continuous variables for the features of the MetS may explain why the metabolic risk score predicted SCD better than the other definitions of the metabolic syndrome. It should be noted, however, that the metabolic risk score is well suited for epidemiological studies, but not for clinical use. If the metabolic risk score were to be adapted for clinical use, metabolic risk scores would by necessity be population-specific, because they are based on Zscores of risk factors at the population level. At the baseline in the 1980s prevalence of MetS varied from 10% to 22% depending upon the definition in the larger KIHD cohort of men without prevalent type 2 diabetes in our study. The prevalence of
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MetS is concordant with the lower range reported in various other European populations [7–8]. The increase in MetS seen globally is also occurring in Finland parallel to the increase in overweight and obesity [23,24], and currently the metabolic syndrome is considerably more common among middle-aged to older Finnish individuals [25]. In our cohort, the metabolic syndrome as defined by the NCEP and IDF had similar prevalences despite the differences in criteria, whereas in the United States, the IDF definition had a somewhat higher prevalence [26]. The IDF/AHA interim criteria using a lower 94 cm cut-off for abdominal obesity had a much higher prevalence (22%) than the NCEP definition (10%). In the United States, where obesity is much more prevalent, using a waist cutoff of 94 cm instead of 102 cm has little effect on the prevalence of the metabolic syndrome [20]. The prevalence of the metabolic syndrome in other countries will also depend on the population and the definition used. It is likely that as the prevalence of the MetS increases, so will the disease burden imposed by its consequences, such as type 2 diabetes and cardiovascular diseases (CVD). A previous study has shown that metabolic syndrome is associated with an increased risk of SCD independent of CHD risk factors [3]. However, this previous study did not take into consideration alcohol consumption, socioeconomic status and energy intake for saturated fats. Of the features of the metabolic syndrome included in the WHO, NCEP and IDF definitions and in the Metscore, blood pressure most significantly differed between men who died suddenly during the follow up and those who did not. The metabolic risk score predicted SCD even when adjusting for systolic blood pressure and blood pressure medication, however, indicating that the association of clustering of metabolic risk factors with SCD is not explained by high blood pressure alone. Glucose concentrations, insulin resistance as estimated by serum insulin concentrations were also higher and waist circumference larger in men who suffered SCD during the follow up, but dyslipidemia was not associated with SCD. Mechanisms related to hypertension and insulin resistance are therefore most likely to be the most important in the pathophysiology underlying the metabolic syndrome and incident SCD. Insulin resistance, inflammation and endothelial dysfunction are all interrelated pathophysiological processes that contribute to the development of hypertension, the metabolic syndrome and cardiovascular disease [27]. Our recent study has shown that elevated fasting plasma glucose is associated with an increased risk of SCD [28]. Secondly, insulin resistance has been linked with a pro-inflammatory state and the elevations of inflammatory markers [29]. It has been also shown that low-grade inflammation may increase the risk of metabolic syndrome, although some of the risk is mediated through obesity and factors related to insulin resistance [29] which contribute to an increased risk of SCD. SCD occurs shortly after the onset of symptoms, leaving little time for effective medical interventions. SCD in adults is mainly due to underlying CHD, and the most common electrophysiological mechanism of SCD is ventricular arrhythmias. Previous findings suggest that myocardial and electrical abnormalities are likely to influence the risk of SCD [30]. Other potential factors contributing to the increased risk of SCD observed in subjects with MetS include silent myocardial ischemia, plaque rupture, and abnormal cardiac repolarization [30]. Cardiac autonomic dysfunction has been linked to a pre-diabetic state [31–32]. Furthermore, hypertension leads to left ventricular hypertrophy (LVH) over time and LVH is an independent risk predictor for SCD [33]. 4.1. Strengths and limitations The strengths of this study include its prospective population-based design, with reliable data on various causes of diseases including assessment of causes of SCD, detailed assessment of MetS risk factors and exclusion of type 2 diabetes subjects at baseline. The definitions of MetS in clinical practice may provide a useful risk marker for SCD in general population. Our study emphasizes the importance of metabolic syndrome in a relatively homogenous middle-aged male population from
Eastern Finland. In addition to four main definitions of MetS we also tested the clustering of metabolic risk factors as a continuous variable using the metabolic risk score. A limitation is the absence of women and elderly from the cohort. Furthermore, the study design does not allow generalization to other ethnic groups. The follow-up studies may have been biased by the participants receiving advice on how to change their lifestyle when appropriate, as well as study findings also being reported to their physicians. The single assessment of MetS at baseline may lead to an underestimation, rather than an overestimation, of the prognostic significance of MetS. Although the prevention of metabolic abnormalities may reduce the risk of CVDs, we have limited evidence implicating a specific effect on SCD risk. Middle-aged men with the MetS as defined by the WHO, NCEP, IDF and IDF/AHA interim criteria have an increased risk for SCD. The IDF/AHA interim criteria and clustering of metabolic risk factors as estimated by a continuous score also predicts SCD independently of adiposity and traditional cardiovascular risk factors including blood pressure. MetS may provide a useful marker for SCD in the general population. The epidemic of overweight and sedentary lifestyle is an increasingly important problem facing public health policy makers and early identification, treatment and improved prevention of MetS presents a major challenge for health care professionals. Conflict of interest The authors report no relationships that could be construed as a conflict of interest. Relationship with industry and financial disclosure statement: none. References [1] D.P. Zipes, H.J. Wellens, Sudden cardiac death, Circulation 98 (1998) 2334–2351. [2] J.J. de Vreede-Swagemakers, A.P. Gorgels, W.I. Dubois-Arbouw, et al., Out-of-hospital cardiac arrest in the 1990s: a population-based study in the Maastricht area on incidence, characteristics and survival, J. Am. Coll. Cardiol. 30 (1997) 1500–1505. [3] J.P. Empana, P. Duciemetiere, B. Balkau, X. Jouven, Contribution of the metabolic syndrome to sudden death risk in asymptomatic men: the Paris prospective study I, Eur. Heart J. 28 (2007) 1149–1154. [4] B. Balkau, M.A. Charles, T. Drivsholm, et al., European Group For The Study Of Insulin Resistance (EGIR). Frequency of the WHO metabolic syndrome in European cohorts, and an alternative definition of an insulin resistance syndrome, Diabete Metab. 28 (2002) 364–376. [5] J.M. Dekker, C. Girman, T. Rhodes, et al., Metabolic syndrome and 10-year cardiovascular disease risk in the Hoorn Study, Circulation 112 (2005) 666–673. [6] E.S. Ford, W.H. Giles, W.H. Dietz, Prevalence of the metabolic syndrome among US adults: findings from the Third National Health and Nutrition Examination Survey, JAMA 287 (2002) 356–359. [7] 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. [8] G. Hu, Q. Qiao, J. Tuomilehto, B. Balkau, K. Borch-Johnsen, K. Pyorala, DECODE study group. 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. [9] 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. [10] H.E. Resnick, K. Jones, G. Ruotolo, et al., Strong Heart Study. Strong Heart Study. Insulin resistance, the metabolic syndrome, and risk of incident cardiovascular disease in nondiabetic American Indians: the Strong Heart Study, Diabetes Care 26 (2003) 861–867. [11] A.M. McNeill, W.D. Rosamond, C.J. Girman, et al., The metabolic syndrome and 11year risk of incident cardiovascular disease in the atherosclerosis risk in communities study, Diabetes Care 28 (2005) 385–390. [12] K.J. Hunt, R.G. Resendez, K. Williams, S.M. Haffner, M.P. Stern, San Antonio Heart Study National Cholesterol Education Program versus World Health Organization metabolic syndrome in relation to all-cause and cardiovascular mortality in the San Antonio Heart Study, Circulation 110 (2004) 1251–1257. [13] L.B. Andersen, M. Harro, L.B. Sardinha, et al., Physical activity and clustered cardiovascular risk in children: a cross-sectional study (the European Youth Heart Study), Lancet 368 (2006) 299–304. [14] J.C. Eisenmann, K.R. Laurson, K.D. DuBose, B.K. Smith, J.E. Donnelly, Construct validity of a continuous metabolic syndrome score in children, Diabetol. Metab. Syndr. 2 (2010 Jan 28) 8, http://dx.doi.org/10.1186/1758-5996-2-8. [15] J.T. Salonen, K. Nyyssönen, H. Korpela, J. Tuomilehto, R. Seppänen, R. Salonen, High stored iron levels are associated with excess risk of myocardial infarction in eastern Finnish men, Circulation 86 (1992) 803–811.
S. Kurl et al. / International Journal of Cardiology 203 (2016) 792–797 [16] B. Balkau, M.A. Charles, Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR), Diabet. Med. 16 (1999) 442–443. [17] The Sixth Report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure, Arch. Intern. Med. 157 (21) (1997) 2413–2446. [18] P. Zimmet, K.G. Alberti, R.M. Serrano, A new International Diabetes Federation (IDF) worldwide definition of the metabolic syndrome: the rationale and the results, Rev. Esp. Cardiol. 58 (2005) 1371–1376. [19] 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. [20] K.G. Alberti, R.H. Eckel, S.M. Grundy, et al., Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity, Circulation 120 (2009) 1640–1645. [21] U. Ekelund, S.A. Anderssen, K. Froberg, L.B. Sardinha, L.B. Andersen, S. Brage, et al., Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study, Diabetologia 50 (2007) 1832–1840. [22] S. Kurl, T.H. Mäkikallio, P. Rautaharju, V. Kiviniemi, J.A. Laukkanen, Duration of QRS complex in resting electrocardiogram is a predictor of sudden cardiac death in men, Circ. 125 (2012) 2588–2594. [23] Obesity, Preventing and managing the global epidemic: report of a WHO consultation. Geneva, Switzerland: World Health Organization, WHO Technical Report Series 894 (2000).
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International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Metabolic syndrome and the risk of sudden cardiac death in middle-aged men☆ Sudhir Kurl a,⁎, David E. Laaksonen c, Sae Young Jae d, Timo H. Mäkikallio e, Francesco Zaccardi f, Jussi Kauhanen a, Kimmo Ronkainen a, Jari A. Laukkanen a,b a
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland Jyväskylä Central Hospital, Jyväskylä, Finland Institute of Clinical Medicine, Department of Medicine, Kuopio University Hospital, Kuopio, Finland d Department of Sports Informatics, College of Arts and Physical Education, University of Seoul, South Korea e Division of Cardiology, Department of Internal Medicine, University Hospital of Oulu, Oulu, Finland f Internal Medicine and Diabetes Care Unit, Policlinico Gemelli Hospital, Catholic University of Sacred Heart, Rome, Italy b c
a r t i c l e
i n f o
Article history: Received 12 March 2015 Received in revised form 7 October 2015 Accepted 27 October 2015 Available online 28 October 2015 Keywords: Metabolic syndrome Middle-aged men Sudden cardiac death
a b s t r a c t Background: Little is known about the relationship between metabolic syndrome and sudden cardiac death (SCD). We examined the association of metabolic syndrome, as defined by World Health Organization (WHO), International Diabetes Federation (IDF), National Cholesterol Education Program (NCEP) and American Heart Association (AHA) — IDF interim criteria, with incident SCD. We also assessed the association of a continuous metabolic risk score with SCD. Methods: A total of 1466 middle-aged men participating in a prospective population-based cohort study from eastern Finland with no history of coronary heart disease or diabetes at baseline were included. Results: During the average follow-up of 21 years 85 SCDs occurred. Men with the metabolic syndrome as defined by the WHO, NCEP, IDF and interim criteria had a 2.2–2.6 fold, increased risk for SCD, after adjusting for lifestyle and traditional cardiovascular risk factors not included in the metabolic syndrome definition (P b 0.001–0.011). A one-standard deviation increase in the metabolic risk score (composed of the sum of Z-scores for waist circumference, insulin, glucose, high-density lipoprotein (HDL) cholesterol, triglycerides, and blood pressure) was associated with a 1.68-fold higher (95% CI 1.33-2.11) risk of SCD. Even when adjusting further for systolic blood pressure, HDL cholesterol and body mass index, the association remained significant for the interim criteria and the metabolic risk score, but not for WHO, NCEP, or IDF definitions. Conclusions: Men with metabolic syndrome are at increased risk for SCD. Incident SCD associated with the IDF/ AHA interim criteria and metabolic risk clustering estimated by a score is not explained by obesity or traditional cardiovascular risk factors. Key messages: Men with metabolic syndrome are at increased risk for sudden cardiac death. Incident sudden cardiac death associated with metabolic risk clustering estimated by a score in not explained by obesity or traditional cardiovascular risk factors. Prevention of the metabolic syndrome may help reduce the health burden of SCD. © 2015 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Sudden cardiac death (SCD) accounts for one-half of all coronary heart disease (CHD)-related deaths. Since a majority of SCDs occur among the general segments of the population, the problem would require screening methods applicable to the general population. There continues to be interest in identifying clinically useful markers for SCD
☆ All the authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. ⁎ Corresponding author at: Institute of Public Health and Clinical Nutrition, University of Eastern Finland, P.O. 1627, 70211 Kuopio, Finland. E-mail address: sudhir.kurl@uef.fi (S. Kurl).
http://dx.doi.org/10.1016/j.ijcard.2015.10.218 0167-5273/© 2015 Elsevier Ireland Ltd. All rights reserved.
among the general population. Epidemiological studies have shown that half of the victims of SCD have no physician-diagnosed CHD at the time of death [1–2]. Metabolic syndrome (MetS) is a common clinical condition with a prevalence varying from 10 to 40%, or even higher in older age groups, depending on the populations and definition of MetS [3–12]. A previous study found increased SCD risk for the metabolic syndrome based on the definitions of National Cholesterol Education Program III (NCEPATPIII) and International Diabetes Federation (IDF) with respect to SCD [3]. However, this previous study did not evaluate the risk of MetS for SCD based on World Health Organization (WHO) definition. Current definitions may also be criticized for the use of arbitrary dichotomous cut-offs for the features of the metabolic syndrome, even though
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risk factors such as blood pressure and high-density lipoprotein (HDL) cholesterol have continuous and dose-related associations with cardiovascular outcomes. Some researchers have therefore estimated metabolic risk as a continuous variable using the sum of the Z-scores of the individual metabolic risk factors [13,14]. The objective of the present investigation was to evaluate SCD risk for the MetS as defined by the WHO, NCEP, IDF and IDF/American Heart Association (AHA) interim criteria and a metabolic risk score in a population-based cohort of middle-aged men who did not have coronary heart disease or diabetes at baseline. 2. Research design and methods 2.1. Subjects This study group was subgroup of a random sample of 3433 men aged 42 to 60 years who resided in the town of Kuopio or its surrounding rural communities in eastern Finland. Of those invited, 2682 (83%) participated in the study. This Kuopio Ischemic Heart Disease Study (KIHD) was designed to investigate risk predictors for atherosclerotic cardiovascular outcomes in a population-based sample of men [7]. For the present study men with diabetes (n = 174) or CHD (n = 677) at baseline were excluded. Men with missing data (n = 615) on waist circumference or biochemical values included in the definition of the metabolic syndrome were excluded leaving 1466 for the analyses. 2.2. Assessment of components of the metabolic syndrome Blood pressure was measured with a random-zero sphygmomanometer. The mean of 6 measurements (3 while supine, 1 while standing, and 2 while sitting) of systolic and diastolic blood pressure was used. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Waist circumference was calculated as the average of 2 measurements taken after inspiration and expiration at the midpoint between the lowest rib and iliac crest. Waist-hip ratio was defined as waist girth/hip circumference measured at the trochanter major. Participants were asked to fast and to refrain from smoking for 12 h and to avoid alcohol intake for 3 days before blood sampling. Blood glucose was measured using a glucose dehydrogenase method after precipitation of proteins by tricholoracetic acid. Insulin was measured with a radioimmunoassay kit (Novo Nordisk, Bagsvaerd, Denmark) from the serum samples stored at –80 °C [7]. Because blood glucose was measured instead of plasma glucose, a blood glucose value of 5.6 mmol/L was considered to correspond to a plasma glucose level of 6.1 mmol/L [4], and a blood glucose value of 5.0 mol/L to correspond to a plasma glucose value of 5.6 mmol/L. Low-density lipoprotein (LDL) and high-density lipoprotein (HDL) fractions were separated from fresh serum by combined ultracentrifugation and precipitation. Lipoprotein fraction cholesterol and triglycerides were measured enzymatically [15]. 2.3. Metabolic syndrome As suggested by the European Group for the Study of Insulin Resistance, hypertension was defined at a lower level (at least 140/90 mm Hg or blood pressure medication) than the original WHO definition for consistency with the WHO-International Society of Hypertension and Sixth Joint National Committee recommendations [7,16–17], and microalbuminuria was not included in the definition [16]. The original WHO cut-off for serum HDL cholesterol was maintained. Abdominal obesity was defined according to the original WHO definition (waist-hip ratio N0.90 or BMI ≥30). The International Diabetes Federation consensus proposed a definition of MetS [18]. The MetS was defined as the presence of abdominal adiposity and two or more abnormalities of the following: elevated triglycerides (≥150 mg/dL or 1.7 mmol/L) or specific treatment for dyslipidemia, low HDL cholesterol (b40 mg/dL or 1.0 mmol/L for men), elevated fasting plasma glucose (≥100 mg/dL or 5.6 mmol/l) or antidiabetic treatment and elevated systolic or diastolic blood pressure (≥130/85 mm Hg) or antihypertensive medications. The MetS defined by the NCEP-ATPIII was the presence of 3 or more of the following: fasting plasma glucose of at least 110 mg/dL (6.1 mmol/L), serum triglycerides of at least 150.0 mg/dL (1.7 mmol/L), serum HDL cholesterol less than 40 mg/dL (1.04 mmol/L), blood pressure of at least 130/85 mm Hg, or waist girth of more than 102 cm. Use of waist girth of more than 94 cm was suggested for men genetically susceptible to insulin resistance [19]. In keeping with the clinically oriented NECP-ATPIII recommendations, the cut off for HDL cholesterol was rounded off in SI units (b1.0 mmol/L) [20]. The International Diabetes Federation consensus proposed a definition of MetS [18]. The MetS was defined as the presence of abdominal adiposity and two or more abnormalities of the following: elevated triglycerides (≥150 mg/dL or 1.7 mmol/L) or specific treatment for dyslipidemia, low HDL cholesterol (b40 mg/dL or 1.0 mmol/L for men), elevated fasting plasma glucose (≥100 mg/dL or 5.6 mmol/l) or antidiabetic treatment and elevated systolic or diastolic blood pressure (≥130/85 mm Hg) or antihypertensive medications. The IDF and AHA and several other organizations proposed an interim definition based on the presence of 3 or more of the following: fasting plasma glucose of at least 100 mg/dL (5.6 mmol/L), serum triglycerides of at least 150 mg/dL (1.7 mmol/L), serum HDL cholesterol less than 40 mg/dL (1.0 mmol/L), blood pressure of at least 130/ 85 mm Hg or blood pressure medication, or abdominal obesity using population-specific
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waist circumference [20]. A cut-off for waist of either 94 cm or 102 cm was suggested for europoid populations. For our study we used a cut-off of 94 cm. 2.4. Calculation of the metabolic risk score We calculated a continuous metabolic risk score (Metscore) similarly to previously published scores [21] using the sum of continuous Z-scores; waist circumference + insulin + glucose − HDL cholesterol + triglycerides + the average of SBP and DBP. A higher MetS score indicates a less favorable metabolic risk profile. 2.5. Assessment of risk factors Assessment of smoking, alcohol consumption, diet, socioeconomic status, medical history and medications and family history of diseases have been described previously [7,15,22]. 2.6. Classification of sudden cardiac death All deaths that occurred by the end of 2009 were checked from the hospital documents, wards of health centers and death certificates. Deaths were coded using to the Ninth International Classification of Diseases codes or the Tenth International Classification of Diseases codes. The sources of information were interviews, hospital documents, death certificates, autopsy reports and medico-legal reports [22]. There were no losses to follow-up. A death was determined SCD when it occurred either within 1 h after the onset of an abrupt change in symptoms or within 24 h after onset of an abrupt change in symptoms when autopsy data did not reveal a non-cardiac cause of sudden death. Sudden cardiac deaths that occurred out-of-hospital conditions were also defined based on hospital documents. Subjects who were successfully resuscitated from ventricular tachycardia (VT) or ventricular fibrillation (VF) were included in the definition of sudden cardiac arrest outcome. The deaths due to aortic aneurysm rupture, cardiac rupture or tamponade and pulmonary embolism, cancer or other non-cardiac co-morbidities were not included as SCD. The diagnostic classification of events was based on symptoms, electrocardiographic findings, cardiac enzyme elevations, autopsy findings (80%) and history of CHD together with the clinical and ECG findings of the paramedic staff. Thus, we have available all hospital documents including medical records, laboratory and ECG findings from hospital and paramedical staff and the use of medications and defibrillator. SCD cases were checked from deaths from cardiovascular causes and all available documents [22]. The documents related to the death were cross-checked in detail by two physicians. The independent event committee were blinded to clinical data performed classification of deaths. 2.7. Statistical analysis Skewed variable was normalized by taking the log, or in the case of conditioning leisure-time physical activity, by taking the square root. Comparisons of baseline variables between men who died suddenly during the follow-up and those who did not were made using the unpaired Student's t-test or chi-square test. Relative risks of WHO, NCEP and IDF definitions of the MetS with SCD were estimated using forced Cox proportional hazard regression models with adjustment for age and examination year (model 1); age, examination year, socio-economic status, smoking, alcohol consumption, and family history of CHD, dietary intake of saturated fats, and energy expenditure on leisure time physical activity (model 2). Relative hazards, adjusted for risk factors, were estimated as antilogarithms of coefficients from multivariate models. All tests for statistical significance were two-sided. The fit of the proportional-hazard models was examined by plotting the hazard functions in different categories of risk factors over time. The proportional hazard assumptions met indicated that the application of the models was appropriate. All statistical analyses were performed using the SPSS 20.0 Windows software.
3. Results 3.1. Baseline characteristics and follow-up events At the beginning of the follow-up, 15% out of 1381 men who did not suffer a SCD during the follow-up had the metabolic syndrome according to WHO definition, 8% had it according to the NCEP and IDF definitions, and 19% according to the IDF/AHA interim definition (Table 1). In men who died suddenly during the follow up (n = 85), the prevalence of the metabolic syndrome based on these definitions was about two-fold higher (p b 0.001–0.027). The metabolic risk score was also higher in men who died suddenly during the follow up (P = 0.001). When defining the metabolic syndrome at the top 20% of the metabolic risk score when classifying men with a MetSscore in the top 20% of the entire non-diabetic KIHD cohort (corresponding 18% in men without CHD or diabetes at baseline included in this study) as having the metabolic syndrome in our study population (corresponding to the
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Table 1 Characteristics of the 1466 middle-aged men without coronary heart disease or diabetes at baseline. Men who survived during the follow up Men who died suddenly during the follow Men who died suddenly out of (n = 1381) up (n = 85) hospital (n = 65) Age (years) Smokers (%) Alcohol consumption (g/week) Socioeconomic status (score) Family history of CHD‡ (%) Dietary saturated fat intake (energy-adjusted, g/d) Energy expenditure of §CLTPA Body mass index (kg/m2) Waist to hip ratio Waist girth (cm) Fasting serum glucose (umol/L) Fasting serum insulin (mU/L) Serum total cholesterol (mmol/L) LDLǁ cholesterol (mmol/L) HDLǁ cholesterol (mmol/L) Serum triglycerides (mmol/L) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Blood pressure medication (%) Metabolic risk score Metabolic syndrome (%) WHOb NCEPb IDFb IDF/AHAb Interim Metabolic risk score (top 20%)#
51.8 (5.8) 29 34 (7, 90) 11.2 (5.0) 45 45.9 [11]
53.8 (4.7) 41 39 (4, 123) 12.5 (4.7) 60 47.1 [10]
53.7 (5.1) 40 38 (4, 130) 12.8 (4.6) 55 47.9 [10]
85 (32, 194) 26.6 (3.3) 0.94 (0.06) 90.2 (9.3) 4.6 (0.5) 9.4 (7.2, 12.4) 5.8 (1.0) 3.9 (1.0) 1.3 (0.3) 1.08 (0.79, 1.52) 133 [16] 88 [10] 13 −0.33 (3.5)
70 (20, 166) 27.4 (4.0) 0.96 (0.05) 93.0 (10.5) 4.7 (0.5) 10.8 (8.1, 14.5) 5.9 (1.0) 4.1 (1.0) 1.3 (0.3) 1.01 (0.77, 1.75) 141 [16] 92 [10] 22 1.24 (3.9)
15 8 8 19 17
28 15 15 35 34
P-value* P-value† 0.003 0.020 0.82 0.026 0.009 0.31
0.018 0.075 0.83 0.020 0.14 0.18
69 (23, 130) 27.3 (4.1) 0.96 (0.05) 93.3 (10.9) 4.8 (0.6) 11.3 (8.6, 14.8) 5.9 (0.9) 4.1 1.2 0.98 (0.72, 1.64) 140 [16] 92 [10] 20 1.44 (3.97)
0.066 0.039 0.031 0.009 0.004 0.009 0.36 0.090 0.25 0.23 b0.001 0.001 0.016 b0.001
0.13 0.13 0.023 0.014 0.001 0.006 0.37 0.28 0.13 0.50 b0.001 0.007 0.14 b0.001
30 13 13 38 38
0.001 0.011 0.027 b0.001 b0.001
0.001 0.11 0.17 0.001 b0.001
Data are means, percentages, or medians (25th percentile, 75th percentile). *P-values are for the difference between men who died suddenly during the follow up and those who did not (Student's t-test or chi-square). †P-values are for the difference between men who did not die suddenly during the follow up and those who died suddenly out of hospital. ‡CHD denotes coronary heart disease. ǁCLTPA denotes conditioning leisure time physical activity. ǁLDL denotes low-density lipoprotein and HDL denotes high-density lipoprotein. bWHO denotes World Health Organization, NCEP National Cholesterol Education Program, IDF International Diabetes Federation and AHA American Heart Association. #Categorized by the top 20th percentile in the entire Kuopio Ischaemic Disease Study cohort, corresponding to the top 18% in these men without diabetes or ischemic heart disease at baseline.
top 18% in these men who died suddenly during the follow up (34% vs. 17%, P b 0.001, Table 1). Of the features of the metabolic syndrome, the most significant differences between men who died suddenly during the follow-up and those who did not were in SBP and DBP. Men who died suddenly during the follow up also had higher concentrations of serum insulin and glucose and a larger waist circumference and waist-to-hip ratio. There were no differences in dyslipidemia. Men who died suddenly were also older, smoked more, and more often had a family history of coronary heart disease and had a lower socioeconomic status (indicated by a higher score). The average follow-up time to death or the end of follow-up was 21.5 years (range 0.38–26.7 years). There were a total of 85 SCDs. A total of 65 SCDs (70.5%) occurred in out-of-hospital conditions.
3.2. The metabolic syndrome and risk of sudden cardiac death After adjustment for age, and examination year (model 1) the relative risk (RR) was 2.3–2.6 for SCD in men with metabolic syndrome according to WHO, NCEP, IDF and IDF/AHA interim definitions (Table 2). After adjustment for age, examination year, socio-economic status, smoking, alcohol consumption, family history of CHD LDL cholesterol concentrations, energy intake from saturated fats and energy expenditure of leisure time physical activity (model 2), the risk of SCD was still 2.2–2.6-fold higher among men with MetS according to these definitions (Table 2) than men without MetS. After further adjustment for traditional cardiovascular risk factors included in the definition of the metabolic syndrome (SBP and blood pressure medication as a marker of hypertension and HDL cholesterol) and BMI the association was attenuated (RR 1.46, 95% CI 0.83–2.57 for the WHO, RR 1.91, 95% CI 0.96–3.80 for the NCEP and RR 1.66, 95% CI 0.83–3.29 for the ID, and the IDF/AHA interim definition 2.56 (95% CI 1.63–4.01).
After adjustment for age and examination year (model 1), a one-SD increase in the MetSscore was associated with a 1.61-fold higher risk of SCD (95% CI 1.29–2.01). When classifying men with a MetSscore in the top 20% of the entire KIHD cohort (corresponding to 18% in men without coronary heart disease or diabetes at baseline included in this study) as having the metabolic syndrome, the RR was 2.04 (95% CI 1.20–3.47, Table 2). Further adjustment for socio-economic status, smoking, alcohol consumption, family history of CHD, LDL cholesterol concentrations, energy intake from saturated fats, and energy expenditure of leisure time physical activity (model 2) did not attenuate the associations (RR 1.68, 95% CI 1.33–2.11 for a one-SD change in the MetSscore; RR 2.83 (95% CI 1.78–4.50 for the categorized MetSscore). Even when adding traditional cardiovascular risk factors that are part of the definition of the metabolic syndrome (systolic blood pressure, blood pressure medication and HDL cholesterol) and BMI to model 2, the associations remained significant (RR 1.57, 95% CI 1.02–2.42 for a one-SD change in the MetSscore; RR 1.89 (95% CI 1.01–3.55 for the categorized MetSscore). When categorizing the metabolic syndrome by the top 15th percentile of the MetSscore, the results were similar. However, when defining the metabolic syndrome as middle-aged men in the top 10% of the MetSscore in the entire non-diabetic KIHD cohort (corresponding to 8.3% in men without CHD and diabetes and similar to the prevalence of the metabolic syndrome as defined by the NCEP and IDF), the association was weaker, and not significant when adding systolic blood pressure, blood pressure medication and BMI to model 2 (RR 1.45, 95% CI 0.69–3.03). Kaplan Meier curves are shown in the Fig. 1 based WHO definition. 3.3. The metabolic syndrome and risk of out-of-hospital sudden cardiac death After adjustment for age and examination year (model 1) the RR was 2.1–2.9 for OSCD in men with metabolic syndrome according to the
S. Kurl et al. / International Journal of Cardiology 203 (2016) 792–797 Table 2 Risk of sudden cardiac death according to metabolic syndrome in 1466 Middle-aged men with no prior ischemic heart disease or diabetes. Model 1 RR (95% CI)
Model 2 P value
RR (95% CI)
Risk for sudden cardiac death (85 cases) Metabolic syndrome WHO 2.30 (1.43–3.69) b0.001 2.34 (1.45–3.78) NCEP† 2.43 (1.34–4.42) 0.004 2.50 (1.36–4.58) IDF 2.36 (1.29–4.32) 0.006 2.20 (1.20–4.04) IDF/AHA interim 2.61 (1.67–4.09) b0.001 2.57 (1.63–4.06) Metabolic score 2.56 (1.63–4.01) b0.001 2.83 (1.78–4.50) (top 20%) Risk for out-of-hospital sudden cardiac death (60 cases) Metabolic syndrome WHO 2.50 (1.43–4.34) 0.001 2.52 (1.44–4.40) NCEP 2.13 (1.00–4.54) 0.049 2.22 (1.03–4.78) IDF 2.06 (0.96–4.40) 0.063 1.96 (0.91–4.2) IDF/AHA interim 2.94 (1.74–4.97) b0.001 2.89 (1.69–4.93) Metabolic risk score 3.08 (1.83–5.18) b0.001 3.35 (1.96–5.74) (top 20%)
P value
b0.001 0.003 0.011 b0.001 b0.001
0.001 0.041 0.087 b0.001 b0.001
Abbreviations are as in Table 1. Model 1: Adjusted for age and examination year. Model 2: Adjusted for age, examination year, socio-economic status, smoking, alcohol consumption, family history of coronary heart disease, LDL cholesterol concentrations, dietary intake of saturated fats, and energy expenditure of leisure time physical activity.
WHO, NCEP, IDF and IDF/AHA interim definitions (Table 2). After adjustment for age, examination year, socio-economic status, smoking, alcohol consumption, family history of CHD, LDL cholesterol concentrations, energy intake from saturated fats, and energy expenditure of leisure time physical activity (model 2), the risk of OSCD was 2.0–2.9-fold higher among men with MetS according to these definitions (Table 2) than men without MetS. The association was strongest for the IDF/ AHA definition and weaker for the NCEP and IDF definitions. After further adjustment for traditional cardiovascular risk factors included in the definition of the metabolic syndrome (systolic blood pressure, blood pressure medication as a marker of hypertension) and BMI the association was no longer significant for the WHO, NCEP and IDF definitions, but remained highly significant for the IDF/AHA interim definition (RR 2.36, 95% CI 1.26–4.42, P = 0.007). After adjustment for age and examination year (model 1), a one-SD increase in the MetSscore was associated with a 1.72-fold higher risk of OSCD (95% CI 1.32–2.24). When classifying men with a MetSscore in the
Fig. 1. Shows Kaplan Meier survival curves among men with and without metabolic syndrome based on the WHO definition.
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top 20% of middle-aged men in the entire KIHD population sample (top 19% in these men without CHD at baseline) as having the metabolic syndrome, the RR was 3.08 (95% CI 1.83–5.18, Table 2). Further adjustment for socio-economic status, smoking, alcohol consumption, family history of CHD, LDL cholesterol concentrations, energy intake from saturated fats, and energy expenditure of leisure time physical activity (model 2) did not attenuate the associations (RR 1.78, 95% CI 1.36–2.34 for a one-SD change in the MetSscore; RR 3.35 (95% CI 1.96–5.74 for the categorized MetSscore). Even when adding traditional cardiovascular risk factors that are part of the definition of the metabolic syndrome (systolic blood pressure, blood pressure medication and HDL cholesterol) and BMI to model 2, the associations remained significant (RR 1.84, 95% CI 1.11–3.04 for a one-SD change in the MetSscore; RR 2.59 (95% CI 1.34–5.39 for the categorized MetSscore). When categorizing the metabolic syndrome by the 15th percentile of the entire KIHD sample, the results were similar, but when using the 10th percentile cut-off, the association was not significant (RR 1.24, 95% CI 0.51–3.03). 4. Discussion In this prospective population-based cohort of middle-aged men without coronary heart disease or diabetes at baseline the MetS based on WHO, IDF and NCEP definitions was associated with a more than two-fold higher risk of SCD during the 21-year follow up, independently of major risk factors not included in the definition of the metabolic syndrome. The clustering of metabolic risk factors as estimated by a continuous metabolic risk score also predicted SCD during the follow-up. Even when adjusting further for BMI, HDL cholesterol, SBP and the use of blood pressure medication, the metabolic syndrome using the IDF/ AHA definition and the metabolic risk score was still associated with SCD, but the WHO, NCEP and IDF definitions were not. We formed the Metscore by using the sum of the Z-scores for waist circumference, concentrations of insulin, glucose, HDL cholesterol and triglycerides, and the average of systolic and diastolic blood pressure. This score is similar to those used in other studies to estimate clustering of metabolic risk, and avoid shortcomings of the metabolic syndrome defined by dichotomous variables based on arbitrary cut-offs to define the metabolic syndrome. When defining the metabolic syndrome as men in the top 20% of the Metscore in the entire non-diabetic KIHD cohort (corresponding to the top 18% in the men without CHD at baseline included in this study and similar to the prevalence of the MetS as defined by the WHO), the increased risk of SCD associated with this definition remained associated with SCD even after adjustment for potential confounding factors, BMI, and traditional cardiovascular risk factors, including blood pressure, blood pressure medication and HDL cholesterol. Findings remained similar when using the top 15%, but not when defining the MetS as the top 10% of the metabolic risk score (roughly corresponding to the prevalence of the NCEP and IDF definitions of the MetS). This may suggest that decreased statistical power related to the lower prevalence may partly explain why the NCEP and IDF definitions were not related to SCD after adjustment for blood pressure. This may also partly explain why the metabolic syndrome defined by the IDF/AHA interim criteria was also associated with SCD even after adjustment for classic CVD risk factors also included in the definition of the metabolic syndrome. Use of continuous variables for the features of the MetS may explain why the metabolic risk score predicted SCD better than the other definitions of the metabolic syndrome. It should be noted, however, that the metabolic risk score is well suited for epidemiological studies, but not for clinical use. If the metabolic risk score were to be adapted for clinical use, metabolic risk scores would by necessity be population-specific, because they are based on Zscores of risk factors at the population level. At the baseline in the 1980s prevalence of MetS varied from 10% to 22% depending upon the definition in the larger KIHD cohort of men without prevalent type 2 diabetes in our study. The prevalence of
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MetS is concordant with the lower range reported in various other European populations [7–8]. The increase in MetS seen globally is also occurring in Finland parallel to the increase in overweight and obesity [23,24], and currently the metabolic syndrome is considerably more common among middle-aged to older Finnish individuals [25]. In our cohort, the metabolic syndrome as defined by the NCEP and IDF had similar prevalences despite the differences in criteria, whereas in the United States, the IDF definition had a somewhat higher prevalence [26]. The IDF/AHA interim criteria using a lower 94 cm cut-off for abdominal obesity had a much higher prevalence (22%) than the NCEP definition (10%). In the United States, where obesity is much more prevalent, using a waist cutoff of 94 cm instead of 102 cm has little effect on the prevalence of the metabolic syndrome [20]. The prevalence of the metabolic syndrome in other countries will also depend on the population and the definition used. It is likely that as the prevalence of the MetS increases, so will the disease burden imposed by its consequences, such as type 2 diabetes and cardiovascular diseases (CVD). A previous study has shown that metabolic syndrome is associated with an increased risk of SCD independent of CHD risk factors [3]. However, this previous study did not take into consideration alcohol consumption, socioeconomic status and energy intake for saturated fats. Of the features of the metabolic syndrome included in the WHO, NCEP and IDF definitions and in the Metscore, blood pressure most significantly differed between men who died suddenly during the follow up and those who did not. The metabolic risk score predicted SCD even when adjusting for systolic blood pressure and blood pressure medication, however, indicating that the association of clustering of metabolic risk factors with SCD is not explained by high blood pressure alone. Glucose concentrations, insulin resistance as estimated by serum insulin concentrations were also higher and waist circumference larger in men who suffered SCD during the follow up, but dyslipidemia was not associated with SCD. Mechanisms related to hypertension and insulin resistance are therefore most likely to be the most important in the pathophysiology underlying the metabolic syndrome and incident SCD. Insulin resistance, inflammation and endothelial dysfunction are all interrelated pathophysiological processes that contribute to the development of hypertension, the metabolic syndrome and cardiovascular disease [27]. Our recent study has shown that elevated fasting plasma glucose is associated with an increased risk of SCD [28]. Secondly, insulin resistance has been linked with a pro-inflammatory state and the elevations of inflammatory markers [29]. It has been also shown that low-grade inflammation may increase the risk of metabolic syndrome, although some of the risk is mediated through obesity and factors related to insulin resistance [29] which contribute to an increased risk of SCD. SCD occurs shortly after the onset of symptoms, leaving little time for effective medical interventions. SCD in adults is mainly due to underlying CHD, and the most common electrophysiological mechanism of SCD is ventricular arrhythmias. Previous findings suggest that myocardial and electrical abnormalities are likely to influence the risk of SCD [30]. Other potential factors contributing to the increased risk of SCD observed in subjects with MetS include silent myocardial ischemia, plaque rupture, and abnormal cardiac repolarization [30]. Cardiac autonomic dysfunction has been linked to a pre-diabetic state [31–32]. Furthermore, hypertension leads to left ventricular hypertrophy (LVH) over time and LVH is an independent risk predictor for SCD [33]. 4.1. Strengths and limitations The strengths of this study include its prospective population-based design, with reliable data on various causes of diseases including assessment of causes of SCD, detailed assessment of MetS risk factors and exclusion of type 2 diabetes subjects at baseline. The definitions of MetS in clinical practice may provide a useful risk marker for SCD in general population. Our study emphasizes the importance of metabolic syndrome in a relatively homogenous middle-aged male population from
Eastern Finland. In addition to four main definitions of MetS we also tested the clustering of metabolic risk factors as a continuous variable using the metabolic risk score. A limitation is the absence of women and elderly from the cohort. Furthermore, the study design does not allow generalization to other ethnic groups. The follow-up studies may have been biased by the participants receiving advice on how to change their lifestyle when appropriate, as well as study findings also being reported to their physicians. The single assessment of MetS at baseline may lead to an underestimation, rather than an overestimation, of the prognostic significance of MetS. Although the prevention of metabolic abnormalities may reduce the risk of CVDs, we have limited evidence implicating a specific effect on SCD risk. Middle-aged men with the MetS as defined by the WHO, NCEP, IDF and IDF/AHA interim criteria have an increased risk for SCD. The IDF/AHA interim criteria and clustering of metabolic risk factors as estimated by a continuous score also predicts SCD independently of adiposity and traditional cardiovascular risk factors including blood pressure. MetS may provide a useful marker for SCD in the general population. The epidemic of overweight and sedentary lifestyle is an increasingly important problem facing public health policy makers and early identification, treatment and improved prevention of MetS presents a major challenge for health care professionals. Conflict of interest The authors report no relationships that could be construed as a conflict of interest. Relationship with industry and financial disclosure statement: none. References [1] D.P. Zipes, H.J. Wellens, Sudden cardiac death, Circulation 98 (1998) 2334–2351. [2] J.J. de Vreede-Swagemakers, A.P. Gorgels, W.I. Dubois-Arbouw, et al., Out-of-hospital cardiac arrest in the 1990s: a population-based study in the Maastricht area on incidence, characteristics and survival, J. Am. Coll. Cardiol. 30 (1997) 1500–1505. [3] J.P. Empana, P. Duciemetiere, B. Balkau, X. Jouven, Contribution of the metabolic syndrome to sudden death risk in asymptomatic men: the Paris prospective study I, Eur. Heart J. 28 (2007) 1149–1154. [4] B. Balkau, M.A. Charles, T. Drivsholm, et al., European Group For The Study Of Insulin Resistance (EGIR). Frequency of the WHO metabolic syndrome in European cohorts, and an alternative definition of an insulin resistance syndrome, Diabete Metab. 28 (2002) 364–376. [5] J.M. Dekker, C. Girman, T. Rhodes, et al., Metabolic syndrome and 10-year cardiovascular disease risk in the Hoorn Study, Circulation 112 (2005) 666–673. [6] E.S. Ford, W.H. Giles, W.H. Dietz, Prevalence of the metabolic syndrome among US adults: findings from the Third National Health and Nutrition Examination Survey, JAMA 287 (2002) 356–359. [7] 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. [8] G. Hu, Q. Qiao, J. Tuomilehto, B. Balkau, K. Borch-Johnsen, K. Pyorala, DECODE study group. 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. [9] 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. [10] H.E. Resnick, K. Jones, G. Ruotolo, et al., Strong Heart Study. Strong Heart Study. Insulin resistance, the metabolic syndrome, and risk of incident cardiovascular disease in nondiabetic American Indians: the Strong Heart Study, Diabetes Care 26 (2003) 861–867. [11] A.M. McNeill, W.D. Rosamond, C.J. Girman, et al., The metabolic syndrome and 11year risk of incident cardiovascular disease in the atherosclerosis risk in communities study, Diabetes Care 28 (2005) 385–390. [12] K.J. Hunt, R.G. Resendez, K. Williams, S.M. Haffner, M.P. Stern, San Antonio Heart Study National Cholesterol Education Program versus World Health Organization metabolic syndrome in relation to all-cause and cardiovascular mortality in the San Antonio Heart Study, Circulation 110 (2004) 1251–1257. [13] L.B. Andersen, M. Harro, L.B. Sardinha, et al., Physical activity and clustered cardiovascular risk in children: a cross-sectional study (the European Youth Heart Study), Lancet 368 (2006) 299–304. [14] J.C. Eisenmann, K.R. Laurson, K.D. DuBose, B.K. Smith, J.E. Donnelly, Construct validity of a continuous metabolic syndrome score in children, Diabetol. Metab. Syndr. 2 (2010 Jan 28) 8, http://dx.doi.org/10.1186/1758-5996-2-8. [15] J.T. Salonen, K. Nyyssönen, H. Korpela, J. Tuomilehto, R. Seppänen, R. Salonen, High stored iron levels are associated with excess risk of myocardial infarction in eastern Finnish men, Circulation 86 (1992) 803–811.
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