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The Metabolic Syndrome and Total and Cardiovascular Disease Mortality in Middle-aged Men
Hanna-Maaria Lakka, MD, PhD;
David E. Laaksonen, MD, MPH;
Timo A. Lakka, MD, PhD;
Leo K. Niskanen, MD, PhD;
Esko Kumpusalo, MD, PhD;
Jaakko Tuomilehto, MD, PhD;
Jukka T. Salonen, MD, PhD
JAMA. 2002;288:2709-2716.
ABSTRACT
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Context The metabolic syndrome, a concurrence of disturbed glucose and insulin metabolism, overweight and abdominal fat distribution, mild dyslipidemia, and hypertension, is associated with subsequent development of type 2 diabetes mellitus and cardiovascular disease (CVD). Despite its high prevalence, little is known of the prospective association of the metabolic syndrome with cardiovascular and overall mortality.
Objective To assess the association of the metabolic syndrome with cardiovascular and overall mortality using recently proposed definitions and factor analysis.
Design, Setting, and Participants The Kuopio Ischaemic Heart Disease Risk Factor Study, a population-based, prospective cohort study of 1209 Finnish men aged 42 to 60 years at baseline (1984-1989) who were initially without CVD, cancer, or diabetes. Follow-up continued through December 1998.
Main Outcome Measures Death due to coronary heart disease (CHD), CVD, and any cause among men with vs without the metabolic syndrome, using 4 definitions based on the National Cholesterol Education Program (NCEP) and the World Health Organization (WHO).
Results The prevalence of the metabolic syndrome ranged from 8.8% to 14.3%, depending on the definition. There were 109 deaths during the approximately 11.4-year follow-up, of which 46 and 27 were due to CVD and CHD, respectively. Men with the metabolic syndrome as defined by the NCEP were 2.9 (95% confidence interval [CI], 1.2-7.2) to 4.2 (95% CI, 1.6-10.8) times more likely and, as defined by the WHO, 2.9 (95% CI, 1.2-6.8) to 3.3 (95% CI, 1.4-7.7) times more likely to die of CHD after adjustment for conventional cardiovascular risk factors. The metabolic syndrome as defined by the WHO was associated with 2.6 (95% CI, 1.4-5.1) to 3.0 (95% CI, 1.5-5.7) times higher CVD mortality and 1.9 (95% CI, 1.2-3.0) to 2.1 (95% CI, 1.3-3.3) times higher all-cause mortality. The NCEP definition less consistently predicted CVD and all-cause mortality. Factor analysis using 13 variables associated with metabolic or cardiovascular risk yielded a metabolic syndrome factor that explained 18% of total variance. Men with loadings on the metabolic factor in the highest quarter were 3.6 (95% CI, 1.7-7.9), 3.2 (95% CI, 1.7-5.8), and 2.3 (95% CI, 1.5-3.4) times more likely to die of CHD, CVD, and any cause, respectively.
Conclusions Cardiovascular disease and all-cause mortality are increased in men with the metabolic syndrome, even in the absence of baseline CVD and diabetes. Early identification, treatment, and prevention of the metabolic syndrome present a major challenge for health care professionals facing an epidemic of overweight and sedentary lifestyle.
INTRODUCTION
The metabolic syndrome, a concurrence of disturbed glucose and insulin metabolism, overweight and abdominal fat distribution, mild dyslipidemia, and hypertension, is most important because of its association with subsequent development of type 2 diabetes mellitus and cardiovascular disease (CVD).1-2 The syndrome is characterized by insulin resistance and is also known as the insulin resistance syndrome. The pathogenesis of the syndrome has multiple origins, but obesity and sedentary lifestyle coupled with diet and still largely unknown genetic factors clearly interact to produce the syndrome.1-3
Despite abundant research on the subject, definitions of the metabolic syndrome and the various cutoffs for its components have varied widely.1-2 To aid in the research and clinical application of the metabolic syndrome, the World Health Organization (WHO) consultation for the classification of diabetes and its complications4 and the National Cholesterol Education Program (NCEP) expert panel5 have recently published definitions.
Because of the epidemic of overweight and sedentary lifestyle worldwide,6 the metabolic syndrome is becoming increasingly common. According to the NCEP definition, roughly one third of middle-aged men and women in the United States have the metabolic syndrome.7 Knowledge of the impact of the metabolic syndrome according to standard definitions on cardiovascular and overall mortality in the general population is crucial for developing public health policy and clinical guidelines for its prevention and treatment. In the Botnia study,8 cardiovascular and overall mortality was higher in 35- to 70-year-old persons with a family history of type 2 diabetes who had the metabolic syndrome as defined by the WHO. Cardiovascular disease and diabetes were present already at baseline in a third of the cohort. Furthermore, no statistical adjustment was made for these diseases. Cardiovascular disease and diabetes are well-defined clinical entities with a high mortality rate and require aggressive intervention.9-11 The importance of the metabolic syndrome from a clinical and public health perspective may be greatest in its earlier stages, before development of CVD or diabetes. Although the association of the metabolic syndrome with CVD is well described,2, 12-13 the methods and definitions used in these studies are variable. To our knowledge, there are no published data of these associations in prospective population-based cohorts using standard definitions.
We assessed the association of the metabolic syndrome based on definitions by the NCEP and WHO with cardiovascular and overall mortality during an 11-year follow-up in a population-based cohort of middle-aged Finnish men who did not have CVD or diabetes at baseline. As a complementary statistical approach, we also assessed mortality associated with the metabolic syndrome using factor analysis.
METHODS
The Kuopio Ischaemic Heart Disease Risk Factor Study is a prospective population-based study14 that comprised a random age-stratified sample of 2682 men living in eastern Finland who were aged 42, 48, 54, or 60 years at baseline between 1984 and 1989. The University of Kuopio Research Ethics Committee approved the study. All participants gave their written informed consent. For the present study, 1123 men with a history of CVD, cancer, or diabetes at baseline were excluded. Men with missing data on waist circumference (n = 274) or biochemical measures included in the definition of the metabolic syndrome (n = 76) were also excluded, leaving 1209 men for the analyses.
Assessment of Components of the Metabolic Syndrome
Blood pressure was measured with a random-zero mercury 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 hours 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 trichloroacetic acid. Insulin was measured with a radioimmunoassay kit (Novo Nordisk, Bagsvaerd, Denmark) from serum samples stored at -80°C.15 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. Measurement of fibrinogen and white blood cell (WBC) count has been described previously.15
Metabolic Syndrome
The metabolic syndrome as defined by the NCEP was 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 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 (Table 1). Use of waist girth of more than 94 cm was suggested for men genetically susceptible to insulin resistance.5 In keeping with the clinically oriented NCEP recommendations, the cutoff for HDL cholesterol was rounded off in SI units (<1.0 mmol/L [39 mg/dL]).16 Because blood glucose was measured, the corresponding cutoff for elevated blood glucose, 101 mg/dL (5.6 mmol/L4), was used.
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Table 1. Modified NCEP and WHO Definitions of the Metabolic Syndrome in Men*
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The metabolic syndrome for men according to the WHO definition was modified for epidemiological studies16 in part as proposed by the European Group for the Study of Insulin Resistance17 and defined as hyperinsulinemia or elevated fasting glycemia and at least 2 of the following: abdominal obesity, dyslipidemia, or hypertension (Table 1).4 Insulin resistance was estimated as hyperinsulinemia based on fasting insulin levels in the upper fourth.17 Impaired fasting glycemia was defined as fasting blood glucose of 101 to 109 mg/dL (5.6-6.0 mmol/L).4 Diabetes was defined as blood glucose of at least 110 mg/dL (6.1 mmol/L) or a clinical diagnosis of diabetes with dietary, oral, or insulin treatment.4 Men with diabetes at baseline were excluded.
As suggested by the European Group for the Study of Insulin Resistance, hypertension was defined at a lower level than the original WHO definition for consistency with the WHO–International Society of Hypertension and Sixth Joint National Committee recommendations,17-19 and microalbuminuria was not included in the definition.17 The original WHO cutoff for HDL cholesterol was maintained. Abdominal obesity was defined according to the original WHO definition4 (waist-hip ratio >0.90 or BMI  30) and the European Group for the Study of Insulin Resistance recommendation (waist girth 94 cm).17 These modifications of the WHO definition have been recently validated, as have been the NCEP definitions.16
Other Assessments
Maximal oxygen consumption was measured directly with respiratory gas exchange analysis during a graded symptom-limited maximal exercise test on a cycle ergometer.20 Assessment of medical history and medications, family history of diseases, smoking,21 and alcohol consumption22 has been described previously.
Ascertainment of All-Cause, CVD, and Coronary Heart Disease Deaths
Deaths were ascertained by computer linkage to the national death registry using the Finnish social security number. No patients were lost to follow-up. All deaths that occurred between study entry (March 1984 to December 1989) and December 1998 were included. Deaths with the International Classification of Diseases, Ninth Revision (ICD-9) codes 390 to 459 were classified as CVD deaths. Deaths coded as coronary heart disease (CHD) (410-414) or stroke (430-436) were all validated according to the international criteria adopted by the WHO Monitoring of Trends and Determinants of Cardiovascular Disease (MONICA) project.23-25 The province of Kuopio participated in the multinational MONICA project between 1982 and 1992,24 during which CHD deaths were determined by the coronary registry group of the Finnish MONICA center (FINMONICA).24 Data on fatal coronary events between January 1993 and December 1998 were obtained by computer linkage to the national hospital discharge registry. An internist (T.A.L.) collected diagnostic information from hospitals and classified them using identical diagnostic criteria.26
Statistical Analysis
The associations of relevant variables with cardiovascular and all-cause mortality were assessed with univariate Cox proportional hazards regression models. Associations of the NCEP and WHO definitions of the metabolic syndrome with CHD, cardiovascular, and overall mortality were analyzed with forced Cox proportional hazards regression models, with adjustment for age (model 1); age, examination year, LDL cholesterol, smoking, and family history of CHD (model 2); and age, examination year, LDL cholesterol, smoking, alcohol intake, socioeconomic status, family history of CHD, and WBC and fibrinogen concentrations (model 3). As an alternative approach, factor analysis was carried out using components of or variables related to the metabolic syndrome and other risk factors. The intercorrelations of these variables were assessed using partial correlation analysis adjusting for age. Principal component analysis was used to extract the initial factors. Only factors with eigen values of more than 1.0 were retained in the analysis. The initial factors were then subjected to Varimax rotation to facilitate their interpretation. Cutoffs for loading varying from 0.20 to 0.40 have been recommended for the interpretation of factors.27-29 For interpretation, we considered variables with loadings of at least 0.40 on a factor to be heavily loaded on that factor, and variables with loadings of 0.30 to 0.39 to be moderately loaded. The metabolic syndrome factor thus obtained was dichotomized such that men in the highest fourth were considered to have the metabolic syndrome. The dichotomized factor was entered with age and the other factors yielded by the factor analysis into Cox proportional hazards regression models with cardiovascular and all-cause death as dependent variables. Triglyceride and insulin concentrations and alcohol intake were corrected for skewing using log transformation but are presented using untransformed values. Significance was considered to be P<.05. All statistical analyses were performed with SPSS version 11.0 (SPSS Inc, Chicago, Ill).
RESULTS
The median follow-up for survivors was 11.6 years (range of follow-up, 9.1-13.7 years). There were 109 deaths during follow-up. Of these, there were 46 CVD deaths, 27 of which were due to CHD. In univariate Cox proportional hazards regression analyses, blood pressure, BMI, waist circumference, smoking, and alcohol intake were associated with a higher mortality from CHD, CVD, and any cause during the follow-up (Table 2). Although blood glucose and serum insulin levels were associated with cardiovascular and all-cause mortality, dyslipidemia was not.
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Table 2. Baseline Characteristics of All Men Without Initial CVD, Cancer, and Diabetes, and Those Who Died of CHD, CVD, and Any Cause During Follow-up*
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The Metabolic Syndrome and CHD, CVD, and Overall Mortality
The Kaplan-Meier estimate of overall survival at 13.7 years of follow-up for men with vs without the metabolic syndrome was 79% (95% confidence interval [CI], 61%-89%) vs 90% (95% CI, 87%-92%) for the NCEP definition with a waist cutoff of 102 cm; 83% (95% CI, 71%-90%) vs 90% (95% CI, 87% 92%) for the NCEP definition with a waist cutoff of 94 cm; 84% (95% CI, 79%-89%) vs 90% (95% CI, 87%-92%) for the WHO definition based on the waist-hip ratio; and 83% (95% CI, 75%-89%) vs 90% (95% CI, 87%-92%) for the WHO definition with a waist cutoff of 94 cm.
In age-adjusted Cox proportional hazards regression analyses (model 1), the metabolic syndrome was associated with a 2.4- to 3.4-fold higher mortality from CHD (Table 3). The NCEP definition with a waist cutoff of 102 cm appeared to have an especially high risk for CHD mortality, but the 95% CIs overlap widely with those of the other definitions. After taking into account the conventional cardiovascular risk factors, LDL cholesterol, smoking, and family history of CHD in addition to examination year (model 2), the relative risks (RRs) of the metabolic syndrome for CHD mortality increased to 2.9 to 4.2. Further adjustment for WBC and fibrinogen levels and alcohol consumption (model 3) had little effect on the RRs for the NCEP definitions but increased the RRs of the WHO definitions to 3.3 to 4.2.
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Table 3. Relative Risk of Death From CHD, CVD, and Any Cause During the 11-Year Follow-up*
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In age-adjusted analyses, the metabolic syndrome was associated with a 2.5- to 2.8-fold greater risk of death from any cardiovascular cause, except for the NCEP definitions of the metabolic syndrome, in which the association did not reach statistical significance. Adjusting further for conventional risk factors (model 2) increased the RRs for all definitions of the metabolic syndrome somewhat, but the NCEP definition with a waist cutoff of 94 cm was still not significantly associated with CVD mortality. The RRs for the WHO definitions appeared to be higher than those for the NCEP definitions and were significant in all models.
In Cox proportional hazards regression analyses adjusting only for age, men with the metabolic syndrome as defined by the WHO had a 1.9- to 2.1-fold higher overall mortality risk of any cause, whereas the associations for the NCEP definitions only tended toward significance. The RR attenuated somewhat for overall compared with CHD mortality, but the absolute percentage difference in mortality between men with and without the metabolic syndrome as defined by the WHO (based on waist-hip ratio) increased as the cause of death was expanded (unadjusted absolute percentage differences in actual deaths for CHD, 3%; for CVD, 5%; for any cause, 7%). All definitions were associated with all-cause mortality after taking into account other risk factors (most importantly smoking, model 2). Including fibrinogen and WBC levels and alcohol consumption (model 3) weakened the associations such that only the WHO definitions were significantly associated with increased overall mortality.
The Metabolic Syndrome and Mortality in Normoglycemic Men
We also repeated analyses in normoglycemic men, excluding those with impaired fasting glycemia (n = 38) at baseline. The associations of the metabolic syndrome with CVD and CHD mortality were similar to those shown in Table 3, except that the NCEP definition with a waist cutoff of 94 cm also predicted CHD mortality with borderline significance (model 3: RR, 2.84 [95% CI, 0.99-8.13]). The associations with overall mortality were also similar, except that NCEP definitions not only predicted overall mortality when adjusting for smoking and conventional cardiovascular risk factors, but also when adjusting further for other risk factors (model 3: RR, 2.03 [95% CI, 1.08-3.81] for NCEP with a waist cutoff of 102 cm; RR, 1.71 [95% CI, 0.98-2.97] for NCEP with a waist cutoff of 94 cm).
Factor Analysis
The age-adjusted intercorrelations of variables included in the definitions of the metabolic syndrome were in general strong (data available upon request from author). Alcohol intake, smoking, WBC count, and fibrinogen levels were not only intercorrelated but also correlated with many variables included in the definition of the metabolic syndrome. For factor analyses, we used age-adjusted variables to generate factors independent of age, although unadjusted variables generated very similar factors. Use of 13 variables associated with insulin resistance and CVD yielded 4 factors explaining 54% of the total variance both before and after rotation (Table 4). The factor with the highest variance (21% before rotation, 18% after rotation) had strong loadings by variables included in the definitions of the metabolic syndrome and was therefore termed the metabolic syndrome factor. The second factor, with high loading by smoking, fibrinogen levels, and WBCs, explained 14% of the variance both before and after rotation. The third factor had high loading by alcohol, HDL, and triglycerides and quite high loading by blood pressure. The fourth factor had high loadings for LDL cholesterol and family history of ischemic heart disease. We also used an 11-variable model without WBCs and fibrinogen and a 15-variable model, which included physical activity and maximal oxygen consumption. The factors generated were otherwise similar to the model shown but, in the 11-factor model, both smoking and alcohol loaded heavily on the second factor.
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Table 4. Loadings of 13 Age-Adjusted Variables on the 4 Factors Rotated and Extracted With Factor Analysis*
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The Metabolic Syndrome Factor and Mortality
The unadjusted Kaplan-Meier hazard curves for the metabolic syndrome factor dichotomized according to the upper quartile and CHD, CVD, and all-cause mortality are shown in Figure 1. The estimated percentage surviving at 13.7 years of follow-up for those with the metabolic syndrome by factor analysis vs those without was 94% (95% CI, 91%-97%) vs 98% (95% CI, 96%-99%) for CHD survival; 91% (95% CI, 87%-94%) vs 97% (95% CI, 94%-98%) for CVD survival; 82% (95% CI, 76%-87%) vs 92% (95% CI, 89%-94%) for overall survival.
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Figure. Unadjusted Kaplan-Meier Hazard Curves
RR indicates relative risk; CI, confidence interval. Curves for men with vs without the metabolic syndrome based on factor analysis (men in the highest quarter of the distribution of the metabolic syndrome factor were considered to have the metabolic syndrome). Median follow-up (range) for survivors was 11.6 (9.1-13.7) years. Relative risks were determined by age-adjusted Cox proportional hazards regression analysis.
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In Cox proportional hazards regression analyses after adjustment for age, year of examination, and the 3 other factors, men with loadings on the metabolic syndrome factor in the highest quarter had an increased mortality from CHD, CVD, and all causes (RR, 3.61 [95% CI, 1.65-7.90]; 3.18 [95% CI, 1.73-5.81]; and 2.25 [95% CI, 1.51-3.35], respectively). The RR attenuated somewhat for overall compared with CHD mortality, but the absolute percentage difference in mortality during follow-up between men with and without the metabolic syndrome as defined by factor analysis increased as the cause of death was expanded (4%, unadjusted absolute percentage differences for CHD; 6% for CVD; and 8% for all-cause mortality). When categorizing by tertiles, the RR for overall mortality seemed to be graded (RR, 1.48 [95% CI, 0.86-2.54] for the middle third and 2.19 [95% CI, 1.32-3.62] for the upper third relative to the lower third). When categorized by quartiles, however, the increase in all-cause mortality was limited to the highest quarter (RR, 0.91 [95% CI, 0.47-1.73] for the second fourth; 1.00 [95% CI, 0.53-1.88] for the third fourth; and 2.18 [95% CI, 1.29-3.70] for the highest fourth relative to the lowest fourth). Results for the 11- and 15-variable factor analyses were similar.
COMMENT
To our knowledge, this is the first prospective population-based cohort study reporting the association of the metabolic syndrome using recently proposed definitions with cardiovascular and overall mortality. The increased mortality found in this study was independent of other important and potentially confounding factors such as smoking, alcohol consumption, and serum LDL cholesterol levels. Although we cannot exclude the possibility that subsequent diabetes may explain some of the increased mortality, the association of the metabolic syndrome with cardiovascular and overall mortality persisted even when excluding men with impaired fasting glycemia.
The prevalence of the metabolic syndrome at baseline in this cohort in which men with diabetes or CVD were excluded was quite low, 9% to 14% depending on the definition. We have previously reported a prevalence ranging from 11% (NCEP with waist >102 cm) to 21% (WHO with adiposity based on waist-hip ratio) in this same middle-aged cohort with diabetes excluded but CVD included.16 These data are still much lower than the alarming roughly 30% prevalence of the metabolic syndrome (NCEP with waist >102 cm) reported for 40- to 59-year-old men in the Third National Health and Nutrition Examination Survey.7 However, the same disturbing trends of increasing overall and abdominal obesity that are occurring globally6 are also occurring in Finland.30-31 It is likely that as the prevalence of the metabolic syndrome increases, so will the disease burden imposed by its consequences, including type 2 diabetes mellitus and CVD.
The highest risk (3.0-to 4.3-fold) associated with the metabolic syndrome was for CHD mortality. Risk attenuated progressively for cardiovascular and overall mortality, indicating that the impact on overall mortality was mediated mainly by CVD and especially CHD. Overall mortality was also increased in men with the metabolic syndrome, even though cardiovascular deaths made up less than half of the cases of all-cause mortality. Furthermore, the absolute percentage difference in mortality continued to increase as the cause of death was expanded from CHD to all-cause. In the Botnia study,8 cardiovascular and overall mortality was higher in 35- to 70-year-old individuals with a family history of type 2 diabetes who had the metabolic syndrome as defined by the WHO. Because no statistical adjustment was made, the excess mortality may have been explained by a prevalence of CVD that was already 3-fold higher at baseline in individuals with the metabolic syndrome. Because CVD and diabetes were already present at baseline in one third of the cohort, data from the Botnia study8 demonstrate that the metabolic syndrome also entails a high risk in individuals with a family history of diabetes and late-stage manifestations of the metabolic syndrome (ie, diabetes and CVD). Our findings demonstrate a clearly increased mortality for men with the metabolic syndrome even in its earlier phases, before development of CVD or diabetes.
In men with the metabolic syndrome as defined by the NCEP, cardiovascular and overall mortality was more consistently increased when using a waist cutoff of 102 cm than when using a waist cutoff of 94 cm. The differences in risk between the WHO definitions based on waist-hip ratio and waist were more subtle and overlapped widely. Cardiovascular and overall mortality were overall slightly higher with the WHO definitions than the NCEP definition using a waist cutoff of 102 cm, in addition to being consistently statistically significant regardless of adjustment for other factors. We have previously found that the WHO definition of the metabolic syndrome with adiposity based on the waist-hip ratio detected more cases (67%) of diabetes during follow-up, whereas the NCEP definitions missed most cases of diabetes, especially when using a waist cutoff of 102 cm.16 The NCEP definitions can nonetheless be easily implemented clinically and would define persons at increased risk for all-cause and CVD mortality.
As a complementary approach, factor analysis was performed using components of the metabolic syndrome and important confounding and cardiovascular risk factors. Factor analysis has been used to reduce intercorrelated variables into a smaller set of underlying uncorrelated factors that can be used to explain complex underlying physiological phenomena and is well suited for analyses pertaining to the metabolic syndrome.29, 32-33 Factor analysis generated a principal factor explaining 18% of the total variance that had moderate-to-heavy loadings by all the core components of the metabolic syndrome. Although previous studies have generated factors with differences at least in part related to the variables entered into the analyses, the factor explaining the greatest variance has consistently had heavy loadings by measures of adiposity and fat distribution, insulin, and glucose.32-35
Men with loadings on the metabolic syndrome factor in the upper fourth were 2.3, 3.2, and 3.6 times more likely to die of any cause, CVD, and CHD, respectively, than other men after adjustment for age and the other factors. These results agree well with the multivariate analyses using the NCEP and WHO definitions of the metabolic syndrome. An increased risk for coronary or cardiovascular events during follow-up in middle-aged and elderly men with high loadings on the metabolic factor has previously been shown.33, 35 To our knowledge, there have been no previous reports showing increased cardiovascular or overall mortality with the metabolic syndrome using factor analysis.
Recent evidence from the Finnish Diabetes Prevention Study and US Diabetes Prevention Program suggests that even modest lifestyle interventions can have a major impact in decreasing the risk for diabetes in glucose-intolerant individuals.36-37 Physical activity,38 weight loss,6 and diet39-41 favorably affect components of the metabolic syndrome at least in the relatively short term. Men engaging in regular moderate and especially vigorous leisure-time physical activity were less likely to develop the metabolic syndrome during follow-up in the Kuopio Ischaemic Heart Disease Risk Factor Study cohort.42 However, no randomized controlled trials showing that lifestyle interventions can prevent the metabolic syndrome itself currently exist. The long-term effectiveness of such interventions clinically and at the population level in the treatment and prevention of the metabolic syndrome and its consequences warrant further research.
The strengths of this study include its longitudinal population-based design, reliable assessment of causes of death, detailed assessment of metabolic and cardiovascular risk factors, and exclusion of diabetes and CVD at baseline. A major limitation is the absence of women, elderly individuals, and other races from the cohort. Also, there was a limited number of CHD deaths, even though the follow-up time was relatively long.
Middle-aged men with the metabolic syndrome as defined by the NCEP and WHO have an increased cardiovascular and overall mortality, even when initially without diabetes and CVD. Factor analysis confirmed these findings. The threat to public health posed by the metabolic syndrome will continue to grow as the metabolic syndrome becomes more common. Early identification, treatment, and prevention of the metabolic syndrome present a major challenge for physicians and public health policy makers facing an epidemic of overweight and sedentary lifestyle.
AUTHOR INFORMATION
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Author Contributions: Drs H.-M. Lakka and Laaksonen contributed equally to this manuscript as first authors.
Study concept and design: H.-M. Lakka, Laaksonen, T. Lakka, Niskanen, Kumpusalo, Salonen.
Acquisition of data: T. Lakka, Tuomilehto, Salonen.
Analysis and interpretation of data: H.-M. Lakka, Laaksonen, T. Lakka, Niskanen, Salonen.
Drafting of the manuscript: H.-M. Lakka, Laaksonen, T. Lakka, Niskanen, Salonen.
Critical revision of the manuscript for important intellectual content: H.-M. Lakka, Laaksonen, T. Lakka, Niskanen, Kumpusalo, Tuomilehto, Salonen.
Statistical expertise: H.-M. Lakka, Laaksonen, T. Lakka, Salonen.
Obtained funding: H.-M. Lakka, T. Lakka, Niskanen, Salonen.
Administrative, technical, or material support: Tuomilehto, Salonen.
Study supervision: T. Lakka, Niskanen, Kumpusalo, Tuomilehto, Salonen.
Funding/Support: The Kuopio Ischaemic Heart Disease Risk Factor Study was supported by grants 41471, 1041086, and 2041022 from the Academy of Finland; 167/722/96, 157/722/97, and 156/722/98 from the Ministry of Education of Finland; HL44199 from the National Heart, Lung, and Blood Institute of the United States; and the city of Kuopio. Dr H.-M. Lakka was supported by grants from University of Kuopio, the Finnish Cultural Foundation of Northern Savo, and the Yrjö Jahnsson Foundation and Dr T. Lakka was supported by grants from the Academy of Finland, the Yrjö Jahnsson Foundation, and the University of Kuopio.
Acknowledgment: We thank the staff of the Research Institute of Public Health, University of Kuopio, and Kuopio Research Institute of Exercise Medicine for data collection in the Kuopio Ischaemic Heart Disease Risk Factor Study.
Corresponding Author and Reprints: Hanna-Maaria Lakka, MD, PhD, Pennington Biomedical Research Center, Louisiana State University, 6400 Perkins Rd, Baton Rouge, LA 70808-4124 (e-mail: lakkah{at}pbrc.edu).
Author Affiliations: Research Institute of Public Health (Drs H.-M. Lakka, T. Lakka, and Salonen), Department of Public Health and General Practice (Drs H.-M. Lakka, Kumpusalo, and Salonen), and Department of Physiology (Dr Laaksonen), University of Kuopio, Finland; Pennington Biomedical Research Center, Louisiana State University, Baton Rouge (Drs H.-M. Lakka and T. Lakka); Department of Medicine, Kuopio University Hospital, Finland (Drs Laaksonen and Niskanen); Kuopio Research Institute of Exercise Medicine, Finland (Dr T. Lakka); Inner Savo Health Center, Suonenjoki, Finland (Dr Salonen); General Practice, Kuopio University Hospital, Finland (Dr Kumpusalo); Department of Public Health, University of Helsinki, Finland (Dr Tuomilehto); and Department of Epidemiology and Health Promotion, National Public Health Institute, Helsinki, Finland (Dr Tuomilehto).
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