Published online before print December 24, 2008, doi: 10.1161/STROKEAHA.108.518878
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Stroke. 2009;40:337.)
© 2009 American Heart Association, Inc.
Original Contributions |
Comparison of Definitions of Metabolic Syndrome in Relation to the Risk of Developing Stroke and Coronary Heart Disease in Finnish and Swedish Cohorts
From the Department of Public Health (Q.Q., J.T.), University of Helsinki, Helsinki, Finland; the Department of Health Promotion and Chronic Disease Prevention (Q.Q., T.L., P.J., J.T.), National Public Health Institute, Helsinki, Finland; the Department of Public Health/Geriatrics (B.Z.), Uppsala University Hospital, Uppsala, Sweden; and the Department of Public Health and Clinical Medicine (B.S., M.E.), University of Umeå, Umeå, Sweden.
Correspondence to Qing Qiao, MD, PhD, Department of Public Health, University of Helsinki, PL41, Mannerheimintie 172, FIN-00014 Helsinki, Finland. E-mail qing.qiao{at}ktl.fi
 |
Abstract |
|---|
 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Background and Purpose— The purpose of this study was to compare definitions of metabolic syndrome with regard to their prediction of stroke and coronary heart disease incidence.
Methods— The study comprises 4041 men and 3812 women of 6 Finnish and Swedish cohorts aged 25 to 74 years at baseline. Hazard ratio was estimated applying Cox regression analyses adjusting for cohort, cholesterol, and smoking and using age as a time scale. A paired homogeneity test was performed to compare the differences.
Results— A total of 113 (47) ischemic and 43 (15) hemorrhagic stroke and 235 (50) coronary heart disease events were accumulated in men (women). Hazard ratios (95% CIs) for ischemic stroke in men were 1.59 (1.09 to 2.32), 1.52 (1.01 to 2.28), 1.16 (0.77 to 1.74), and 1.27 (0.87 to 1.86), respectively, for the World Health Organization, National Cholesterol Education Program, National Cholesterol Education Program revised, and the International Diabetes Federation definitions of metabolic syndrome, and in women 2.20 (1.15 to 4.19), 2.68 (1.47 to 4.87), 2.31 (1.27 to 4.20), and 1.91 (1.05 to 3.49), respectively. The corresponding hazard ratios (95% CIs) for coronary heart disease were 1.57 (1.21 to 2.04), 1.51 (1.15 to 1.99), 1.63 (1.25 to 2.13), and 1.46 (1.12 to 1.89) in men and 1.32 (0.69 to 2.51), 1.54 (0.85 to 2.79), 1.81 (1.02 to 3.21), and 2.47 (1.37 to 4.45) in women. None of the definitions of metabolic syndrome predicted hemorrhagic stroke. There was no difference between definitions of metabolic syndrome and between a full definition and its individual components.
Conclusions— Metabolic syndrome as well as its individual components predicted the incidence of the ischemic stroke and the coronary heart disease equally well and should be treated equally as well.
Key Words: metabolic syndrome • stroke • coronary heart disease • definitions
|
Introduction |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
There are different definitions of metabolic syndrome (MetSyn), and there seems little doubt on the ability of MetSyn to predict coronary heart disease (CHD),1–3 but whether all definitions predict cardiovascular disease (CVD) risk equally well is still unclear. Studies have also noticed that the CVD risk of a full definition of the syndrome was not different from that of some of its single components.4–7 Among the numerous studies about MetSyn, fewer have evaluated the impact of the syndrome on stroke and compared different definitions. The risk of stroke and CHD in relation to a full definition of MetSyn as well as its single component is estimated and compared in the Finnish and the Swedish cohorts.
|
Subjects and Methods |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Study Population
The study population comprises 4041 men and 3812 women of 2 Finnish and 4 Swedish cohorts aged 25 to 74 years at baseline and followed for 4 to 21 years. Except for the Uppsala Longitudinal Study of Adult Men (ULSAM) all other studies8,9 have been carried out following the standard World Health Organization (WHO) MONICA procedures.10 Individuals participating in the MONICA studies were randomly drawn from national population register. ULSAM is a population-based cohort study of diabetes and cardiovascular disease in men recruited originally in 1970 to 1973 and re-examined in 1991 to 1995 in Sweden.11,12 The data collected in the 1991 to 1995 examination were considered as baseline in the current data analysis. Individuals included in this article are those who were at baseline survey free of CVD either self-reported CVD or identified from a register as having CHD or stroke; free of previously diagnosed diabetes; and had all other covariates required for the current data analysis.
Definition of Metabolic Syndrome
Four different definitions of MetSyn were studied and their actual definitions used in this article are described subsequently. Because data on urinary protein excretion and on insulin resistance under the hyperinsulinemic and euglycemic conditions are not available, the WHO definitions of MetSyn used in the present study are modified. Because lipid-lowering drugs were seldom used before 1994 and were not available in most of the cohorts, the "treatment" for dyslipidemia was not taken into account in the definition.
Individuals with fasting plasma glucose (FPG) 
6.1 mmol/L and/or 2-hour plasma glucose 7.8 mmol/L and/or insulin resistance were considered to have WHO MetSyn13 if they, in addition, had 2 or more of the following other components: (1) central obesity (waist-to-hip ratio >0.90 in men, >0.85 in women) and/or body mass index >30 kg/m2; (2) hypertension, arterial blood pressure 140/90 mm Hg, or use of antihypertensive drugs; and (3) plasma triglycerides 1.7 mmol/L and/or plasma high-density lipoprotein cholesterol <0.9 mmol/L in men and <1.0 mmol/L in women. Insulin resistance was defined by the top quartile of the fasting insulin concentration among nondiabetic individuals in the background population. Because the insulin measurements were not standardized between studies, the quartile cutoff points were calculated separately for each individual cohort and separately for men and women.
The National Cholesterol Education Program (NCEP) definition does not have any prerequisite; a diagnosis can be made if a person has 3 or more of the 5 components of: (1) waist circumference >102 cm in men and >88 cm in women; (2) FPG 6.1 mmol/L; (3) hypertension, arterial blood pressure 130/85 mm Hg, or use of antihypertensive drugs; (4) plasma triglycerides 1.7 mmol/L; and (5) plasma high-density lipoprotein cholesterol <1.03 mmol/L in men and <1.29 mmol/L in women.14,15
In the revised NCEP definition, the cutoff value of the FPG was lowered from 6.1 mmol/L to 5.6 mmol/L according to a report of the National Heart, Lung, and Blood Institute/American Heart Association.16
According to the International Diabetes Federation (IDF) definition a person can be defined as having MetSyn if he or she has central obesity (defined as waist circumference 94 cm for men and 80 cm for women in Europids) plus any 2 of the following 4 components: (1) plasma triglyceride 1.7 mmol/L; (2) plasma high-density lipoprotein cholesterol <1.03 mmol/L in males and <1.29 mmol/L in females; (3) systolic blood pressure 130 or diastolic blood pressure 85 mm Hg or treatment of previously diagnosed hypertension; and (4) FPG 5.6 mmol/L.17
Ascertainment of Follow-Up Events of Stroke and Coronary Heart Disease
Stroke and CHD events were ascertained through computerized record linkage of the unique national identification numbers of the survey participants to the national Death Registry and the national Hospital Discharge Registry in both Finnish and Swedish studies. Only the first-ever event was counted. International Classification of Diseases, 9th Revision (10th Revision), was used for the classification of either the fatal or the nonfatal events: Codes: 410 to 414 (I20 to I25) for fatal CHD; 410 to 411 (I21 to I22, I24) for nonfatal acute myocardial infarction; 430 to 438 (I60 to I69) for fatal cerebrovascular diseases, and 430 to 434, 436 (I60 to I66) for nonfatal stroke. The stroke events were further classified into subtypes of ischemic (codes 433, 434, 436, I63 to I64), hemorrhagic (codes 430 to 431, I60 to I61), and unclassified stroke. Because the number of the unclassified is low, they were not included in the subtype analysis. The first nonfatal myocardial infarction and the first fatal CHD events constitute the incident CHD events, whereas incident stroke events consist of the first nonfatal stroke events and the first fatal cerebrovascular events after the baseline survey. Subjects with a self-reported history of CVD or ascertained from the registers as having CHD or stroke before the baseline survey were excluded from the data analysis.
Statistical Analysis
SPSS for Windows (Version 15.0.1) was used for calculating means and proportions. Cox proportional hazard model analyses were performed using R 2.6.1 Programme adjusting for cohort, total cholesterol, and smoking using age as a time scale. Hazard ratios (95% CIs) for CHD or stroke incidence in relation to MetSyn of different definitions and single risk factor components of these definitions were estimated. The assumption of the proportionality was examined in each fitted Cox model for each explanatory variable as well as for the whole model as indicated by a global test. There was no statistical evidence showing that the assumption of the proportionality did not hold.
Homogeneity tests were made to test the null hypothesis that the multivariate adjusted β coefficients (effect size) for CHD or stroke incidence in relation to MetSyn by different definitions were not statistically different from each other using the program written by John Fox (Car package in R 2.6.1 program). The hypothesis will be rejected if the probability value of the test is <5%, and the test will indicate that the predicted events or β coefficients are different with different definitions. Both paired and global tests were performed. The paired comparison has been made for any 2 full definitions of the syndrome and also for a full definition versus its single individual components when the 2 being tested are in the same model.
|
Results |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
The baseline characteristics of the cohorts and the follow-up information are shown in Table 1. The occurrence of the CHD events was higher in men than in women in all cohorts studied, but this is not the case for stroke. In men, the majority of the events came from the ULSAM91-95 study because the study participants were on average 18 years older than other participants.
|
Prevalence of MetSyn of different definitions and their individual components were higher in men than in women except for low high-density lipoprotein and obesity indices for which different definitions for men and women have been used (Table 2). In men, a full definition of MetSyn, elevated blood glucose, high blood pressure, and dyslipidemia all significantly predicted the incident CHD events, but none of the obesity indices did (Table 3). In women, the significant risk predictors of the CHD events are MetSyn of the NCEP revised and the IDF definitions, low high-density lipoprotein, and high blood pressure; the hazard ratios for various obesity indices were also high, but the statistical significance was reached only by the WHO obesity. Neither a full definition nor its single component predicted hemorrhagic stroke except for elevated blood pressure in both men and women (Table 4). However, MetSyn of different definitions and most of their individual components significantly predicted the occurrence of the ischemic stroke, particularly in women (Table 4).
|
|
|
There was no difference among the 4 definitions of MetSyn in men, but the IDF definition was better than the NCEP and the WHO definitions in women with regard to the prediction of the CHD incidence (Table 3). All 4 were equally well in prediction of ischemic stroke. A full definition of the syndrome did not perform better than most of its individual components (Tables 3 and 4
).
In addition to cohorts, smoking and total cholesterol, a further adjustment for education (1 to 9, 10 to 12, and >12 school years), and leisure time physical activity (sedentary, moderate, and intensive) was also made in the data analysis. Hazard ratios for various estimates were not changed much, but the CIs became wider compared with the estimates without adjustment for education and physical activity. This is because the information is missing for approximately 400 people.
The hazard ratios corresponding to a 1-SD increase in linear form of the body mass index and waist circumference and in triglycerides were higher in women than in men for both incident CHD and ischemic stroke (Table 5). Elevated blood pressure and high blood glucose levels predicted ischemic stroke in both men and women, but predicted the CHD incidence only in men but not in women.
|
|
Discussion |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Our current collaborative data analysis shows that all 4 definitions of MetSyn predicted the incidence of CHD equally well in men, but the IDF definition performed better than others in women. There was also no difference among the 4 definitions with regard to the prediction of ischemic stroke. The presence of MetSyn seemed not increase the risk of hemorrhagic stroke. Most of the individual components of MetSyn predicted the incidence of the CHD and ischemic stroke as equally well as its full definition.
Meta-analyses based on published prospective studies that have evaluated the association of the modified WHO definition or the original NCEP definition with the risk of CVD have left little doubt about the contribution of clustering of risk factors to the increased CVD risk.1–3,18 A recent meta-analysis based on data of 17 population-based studies that applied the original NCEP definition showed that the CVD risk increased in the presence of MetSyn of the NCEP definition in most studies with an overall hazard ratio of 1.6 (95% CI, 1.5 to 1.8).3 Three recent population-based studies, including the IDF definition of MetSyn in Danes,19 Swedes,6 and in American Indians,20 showed that the relative increase in CVD risk related to MetSyn was lower for the IDF criteria than for the NCEP or the WHO criteria, but there was no formal statistical test applied. Population-based studies that have formally tested the differences between definitions of MetSyn are still rare. Nevertheless, it is practically important to know the differences to understand the underlying causes of the clustering and to make a uniform definition worldwide. We have previously reported that the prediction of CVD mortality was stronger in European men diagnosed by the WHO definition than in those diagnosed by the IDF definition (P=0.03), but there was no difference between the IDF and the NCEP or the NCEP and the WHO, whereas in women, the IDF conveyed a slightly higher risk than NCEP revised definitions.4 In the current study, the hazard ratio for the CHD incidence was slightly lower in men for the IDF definition than for the NCEP or the WHO definitions, but they did not differ statistically, whereas in women, the IDF definition was significantly better than the NCEP or the WHO definition. However, the IDF definition labeled more people with the syndrome than others and thus requires more efforts or resource for intervention. Whether the intervention targeting people labeled as having MetSyn is cost-effective is unclear and requires further investigation. It needs also to be borne in mind that a modified rather than an original WHO definition was compared. Microalbuminuria has been found to increase the risk of vascular disease in patients with diabetes with MetSyn,21 but a population-based Finnish study found that WHO MetSyn, which includes microalbuminuria in the definition, was not better than other definitions with regard to the prediction of the incidence of stroke.22
Population-based studies investigating the impact of MetSyn on stroke events are still rare. One study among nondiabetic American whites and blacks aged 45 to 64 years found that the NCEP definition conveyed a similar risk for incident ischemic stroke as that for incident CHD,23 but in another study among elderly American whites and blacks, the NCEP revised definition was not a risk predictor for stroke but was for CHD.24 A modified WHO definition of MetSyn has been reported to increase the incidence of ischemic stroke in middle-aged Finnish men.25 Another Finnish study among the elderly reported recently that principally all definitions studied predicted incident stroke events when only age and gender were adjusted, but the model prediction could be improved after simultaneously fitting the model with all components of each corresponding definition, and the prediction for impaired glucose tolerance alone was as strong as that for its full definitions.22 Population-based studies revealed that a revised NCEP definition using South Asian criteria for high waist circumference was a risk predictor for either ischemic or hemorrhagic stroke in Chinese26 and in Japanese men, but not for hemorrhagic stroke in Japanese women.27 There are, however, limitations with the previous reports; the sample size is relatively small, there are no data for women alone, and moreover, none of the previous studies have formally compared the effect sizes between 2 definitions and between a full definition and its single individual component of the same definition. Our collaborative data analysis of the large population-based cohorts provides a unique opportunity to investigate the subtype of stroke and its relationship to the cluster of the risk factors separately for men and women and to compare effect sizes between the different definitions of MetSyn and between a full definition and its individual components applying a formal paired as well as global homogeneity test. We found that all 4 definitions studied predict the ischemic stroke equally well. However, none of the definitions of MetSyn or of their single individual factors predicted hemorrhagic stroke except for high blood pressure. This can be explained by the different underlying causes of ischemic and hemorrhagic stroke; the former is mainly a consequence of atherosclerosis and the latter mainly caused by elevated blood pressure and cerebral aneurysms. However, taking into account the low number of hemorrhagic stroke events, the interpretation of the finding requires caution and the study question needs to be further investigated.
Studies have also shown that individual MetSyn components predicted the CVD risk by a similar magnitude as that of the actual syndrome.4–6 A hyperinsulinemic-euglycemic clamp study showed that approximately one third of the subjects who did not meet the NCEP criteria for MetSyn were insulin-resistant.28 Importantly, these subjects were not significantly different from those meeting the NCEP criteria in regard to the prevalence of impaired fasting glycaemia, impaired glucose tolerance, glucose disposal rates, and lipoprotein subclass composition (increased very-low-density lipoprotein size and large very-low-density lipoprotein concentration and decreased large high-density lipoprotein particles and high-density lipoprotein size).28 Recently, Hanefeld and coworkers showed that in people with type 2 diabetes, the cluster of diabetes with hypertension seemed more strongly associated with the concurrence of cardiovascular events than other clusters of MetSyn.29 MetSyn comprises heterogeneous clusters of individual components or traits. Different approaches should be used to treat different traits even in the absence of a full definition of MetSyn.
The strengths of the study include its population-based study design, which have applied the standard MONICA survey procedures,10 and its complete follow-up using national registers; the high quality of data collection for both demographic and event data according to the quality assessment reports of the MONICA study (www.ktl.fi/publications/monica/coreqa/table10.htm; www.ktl.fi/publications/monica/strokeqa/table16.htm); and the standard 2-hour, 75-g oral glucose tolerance test for diagnosing diabetes. However, our study has also certain limitations, including using a modified WHO definition for MetSyn and pooling all cohorts together in the data analysis to increase the statistical power. Although we have a relatively large sample size and relatively long follow-up, the stroke events are still low. This is because most of the cohorts recruited mainly middle-aged people and the stroke events are relatively lower in the middle-aged than in the elderly population. This has hampered the data analysis in subgroups due to the low statistical power. However, this power problem will always be met if one intends to study stroke subtype in the middle-aged population. We have disclosed all details about the definition of MetSyn. To minimize the discrepancies between cohorts in anthropometric and laboratory measures, we have used cohort-specific values of the study variables and taken cohort as the covariate in all pooled data analyses. Therefore, it is very unlikely that these technical limitations will bias our results and lead to a misinterpretation of our results. We also ran the data analysis by excluding the data from the ULSAM91-95 cohort to check whether the outcome in men has been driven by this elderly cohort from which the majority of the events came. After removing the ULSAM91-95 cohort from the data analysis, the estimates did not change substantially but the CI became wider.
In conclusion, both a full definition of MetSyn and its single individual components predicted the development of ischemic stroke and CHD equally well. Intervention for CVDs should target not only MetSyn, but also its individual factors even in the absence of a full definition of the syndrome.
|
Acknowledgments |
|---|
Source of Funding
The data analysis has been supported by the Academy Finland (project 118492).
Disclosures
None.
Received February 29, 2008; revision received June 26, 2008; accepted July 2, 2008.
|
References |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
1. Ford ES. Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: a summary of the evidence Diabetes Care. 2005; 28: 1769–1778.
2. Galassi A, Reynolds K, He J. Metabolic syndrome and risk of cardiovascular disease: a meta-analysis. Am J Med. 2006; 119: 812–819.[CrossRef][Medline] [Order article via Infotrieve]
3. Qiao Q, Gao WG, Zhang L, Nyamdorj R, Tuomilehto J. Metabolic syndrome and cardiovascular disease. Annals of Clinical Biochemistry. 2007; 44: 232–263.
4. The DECODE Study Group. Comparison of different definitions of the metabolic syndrome in relation to cardiovascular mortality in European men and women. Diabetologia. 2006; 49: 2837–2846.[CrossRef][Medline] [Order article via Infotrieve]
5. Lawlor DA, Smith GD, Ebrahim S. Does the new International Diabetes Federation definition of the metabolic syndrome predict CHD any more strongly than older definitions? Findings from the British Women’s Heart and Health Study. Diabetologia. 2006; 49: 41–48.[CrossRef][Medline] [Order article via Infotrieve]
6. Nilsson PM, Engstrom G, Hedblad B. The metabolic syndrome and incidence of cardiovascular disease in non-diabetic subjects—a population-based study comparing three different definitions. Diabet Med. 2007; 24: 464–472.[CrossRef][Medline] [Order article via Infotrieve]
7. Chien KL, Hsu HC, Sung FC, Su TC, Chen MF, Lee YT. Metabolic syndrome as a risk factor for coronary heart disease and stroke: an 11-year prospective cohort in Taiwan community. Atherosclerosis. 2007; 194: 214–221.[CrossRef][Medline] [Order article via Infotrieve]
8. Vartiainen E, Puska P, Jousilahti P, Korhonen HJ, Tuomilehto J, Nissinen A. Twenty-year trends in coronary risk factors in north Karelia and in other areas of Finland. Int J Epidemiol. 1994; 23: 495–504.
9. Stegmayr B, Lundberg V, Asplund K. The events registration and survey procedures in the Northern Sweden MONICA Project. Scand J Public Health Suppl. 2003; 61: 9–17.[Medline] [Order article via Infotrieve]
10. WHO MONICA Project Principal Investigators. The World Health Organization MONICA Project (monitoring trends and determinants in cardiovascular disease): a major international collaboration. WHO MONICA Project Principal Investigators. J Clin Epidemiol. 1988; 41: 105–114.[CrossRef][Medline] [Order article via Infotrieve]
11. Zethelius B, Johnston N, Venge P. Troponin I as a predictor of coronary heart disease and mortality in 70-year-old men: a community-based cohort study. Circulation. 2006; 113: 1071–1078.
12. Sundstrom J, Riserus U, Byberg L, Zethelius B, Lithell H, Lind L. Clinical value of the metabolic syndrome for long term prediction of total and cardiovascular mortality: prospective, population based cohort study. BMJ. 2006; 332: 878–882.
13. WHO Consultation. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. Geneva: World Health Organization; 1999. Report No 99.2.
14. Adult Treatment Panel III. 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) final report. Circulation. 2002; 106: 3143–3421.
15. Expert Panel on Detection Evaluation, and Treatment of High Blood Cholesterol in Adults,. 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. 2001; 285: 2486–2497.
16. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Arterioscler Thromb Vasc Biol. 2004; 24: e13–18.
17. Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabetic Medicine. 2006; 23: 469–480.[CrossRef][Medline] [Order article via Infotrieve]
18. Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, Montori VM. Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol. 2007; 49: 403–414.
19. Jeppesen J, Hansen TW, Rasmussen S, Ibsen H, Torp-Pedersen C, Madsbad S. Insulin resistance, the metabolic syndrome, and risk of incident cardiovascular disease: a population-based study. J Am Coll Cardiol. 2007; 49: 2112–2119.
20. de Simone G, Devereux RB, Chinali M, Best LG, Lee ET, Galloway JM, Resnick HE. Prognostic impact of metabolic syndrome by different definitions in a population with high prevalence of obesity and diabetes: the Strong Heart Study. Diabetes Care. 2007; 30: 1851–1856.
21. Gimeno-Orna JA, Molinero-Herguedas E, Lou-Arnal LM, Boned-Juliani B, Labrador-Fuster T, Guiu-Campos M. Microalbuminuria accounts for the increased vascular disease risk in diabetic patients with metabolic syndrome [in Spanish]. Rev Esp Cardiol. 2007; 60: 1202–1205.[CrossRef][Medline] [Order article via Infotrieve]
22. Wang J, Ruotsalainen S, Moilanen L, Lepisto P, Laakso M, Kuusisto J. The metabolic syndrome predicts incident stroke: a 14-year follow-up study in elderly people in Finland. Stroke. 2008; 39: 1078–1083.
23. McNeill AM, Rosamond WD, Girman CJ, Golden SH, Schmidt MI, East HE, Ballantyne CM, Heiss G. The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care. 2005; 28: 385–390.
24. McNeill AM, Katz R, Girman CJ, Rosamond WD, Wagenknecht LE, Barzilay JI, Tracy RP, Savage PJ, Jackson SA. Metabolic syndrome and cardiovascular disease in older people: the Cardiovascular Health Study. J Am Geriatr Soc. 2006; 54: 1317–1324.[CrossRef][Medline] [Order article via Infotrieve]
25. Kurl S, Laukkanen JA, Niskanen L, Laaksonen D, Sivenius J, Nyyssonen K, Salonen JT. Metabolic syndrome and the risk of stroke in middle-aged men. Stroke. 2006; 37: 806–811.
26. Liu J, Grundy SM, Wang W, Smith JSC, Lena Vega G, Wu Z, Zeng Z, Wang W, Zhao D. Ten-year risk of cardiovascular incidence related to diabetes, prediabetes, and the metabolic syndrome. Am Heart J. 2007; 153: 552–558.[CrossRef][Medline] [Order article via Infotrieve]
27. Ninomiya T, Kubo M, Doi Y, Yonemoto K, Tanizaki Y, Rahman M, Arima H, Tsuryuya K, Iida M, Kiyohara Y. Impact of metabolic syndrome on the development of cardiovascular disease in a general Japanese population: the Hisayama study. Stroke. 2007; 38: 2063–2069.
28. Liao Y, Kwon S, Shaughnessy S, Wallace P, Hutto A, Jenkins AJ, Klein RL, Garvey WT. Critical evaluation of Adult Treatment Panel III criteria in identifying insulin resistance with dyslipidemia. Diabetes Care. 2004; 27: 978–983.
29. Hanefeld M, Koehler C, Gallo S, Benke I, Ott P. Impact of the individual components of the metabolic syndrome and their different combinations on the prevalence of atherosclerotic vascular disease in type 2 diabetes: the Diabetes in Germany (DIG) study. Cardiovasc Diabetol. 2007; 6: 13.[CrossRef][Medline] [Order article via Infotrieve]
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||