Critical Reflection

Goodwills

Reading12.pdf

Home >Psychology homework help >Critical Reflection

T o c s 1 o

F H U B a t M H G p ‡ L

QUARTERLY FOCUS ISSUE: PREVENTION/OUTCOMES

Metabolic Syndrome

The Metabolic Syndrome and Cardiovascular Risk A Systematic Review and Meta-Analysis

Salvatore Mottillo, BSC,*† Kristian B. Filion, PHD,*‡§ Jacques Genest, MD,� Lawrence Joseph, PHD,‡§ Louise Pilote, MD, MPH, PHD,‡§¶ Paul Poirier, MD, PHD,†† Stéphane Rinfret, MD, MSC,‡‡ Ernesto L. Schiffrin, MD, PHD,** Mark J. Eisenberg, MD, MPH*‡

Montreal and Sainte-Foy, Quebec, Canada

Objectives We sought to conduct a systematic review and meta-analysis of the cardiovascular risk associated with the met- abolic syndrome as defined by the 2001 National Cholesterol Education Program (NCEP) and 2004 revised Na- tional Cholesterol Education Program (rNCEP) definitions.

Background Numerous studies have investigated the cardiovascular risk associated with the NCEP and rNCEP definitions of the metabolic syndrome. There is debate regarding the prognostic significance of the metabolic syndrome for cardiovascular outcomes.

Methods We searched the Cochrane Library, EMBASE, and Medline databases through June 2009 for prospective observa- tional studies investigating the cardiovascular effects of the metabolic syndrome. Two reviewers extracted data, which were aggregated using random-effects models.

Results We identified 87 studies, which included 951,083 patients (NCEP: 63 studies, 497,651 patients; rNCEP: 33 studies, 453,432 patients). There was little variation between the cardiovascular risk associated with NCEP and rNCEP definitions. When both definitions were pooled, the metabolic syndrome was associated with an in- creased risk of cardiovascular disease (CVD) (relative risk [RR]: 2.35; 95% confidence interval [CI]: 2.02 to 2.73), CVD mortality (RR: 2.40; 95% CI: 1.87 to 3.08), all-cause mortality (RR: 1.58; 95% CI: 1.39 to 1.78), myocardial infarction (RR: 1.99; 95% CI: 1.61 to 2.46), and stroke (RR: 2.27; 95% CI: 1.80 to 2.85). Patients with the meta- bolic syndrome, but without diabetes, maintained a high cardiovascular risk.

Conclusions The metabolic syndrome is associated with a 2-fold increase in cardiovascular outcomes and a 1.5-fold increase in all-cause mortality. Studies are needed to investigate whether or not the prognostic significance of the meta- bolic syndrome exceeds the risk associated with the sum of its individual components. Furthermore, studies are needed to elucidate the mechanisms by which the metabolic syndrome increases cardiovascular risk. (J Am Coll Cardiol 2010;56:1113–32) © 2010 by the American College of Cardiology Foundation

ublished by Elsevier Inc. doi:10.1016/j.jacc.2010.05.034

P t o A u s

w n R G f R F J i F

he metabolic syndrome affects approximately one-quarter f North Americans and has become a leading health oncern due to its link to cardiovascular disease (1). Ever ince the metabolic syndrome was described by Reaven in 988 (2), a number of definitions have been published by rganizations including the National Cholesterol Education

rom the *Divisions of Cardiology and Clinical Epidemiology, Jewish General ospital/McGill University, Montreal, Quebec, Canada; †Faculty of Medicine, niversity of Montreal, Montreal, Quebec, Canada; ‡Department of Epidemiology, iostatistics and Occupational Health, McGill University, Montreal, Quebec, Can- da; §Division of Clinical Epidemiology, McGill University Health Center, Mon- real, Quebec, Canada; �Division of Cardiology, McGill University Health Center,

ontreal, Quebec, Canada; ¶Division of Internal Medicine, McGill University ealth Center, Montreal, Quebec, Canada; **Division of Internal Medicine, Jewish eneral Hospital, Montreal, Quebec, Canada; ††Faculty of Pharmacy, Laval Hos-

ital, Quebec Heart and Lung Institute, Sainte-Foy, Quebec, Canada; and the

‡Clinical and Interventional Cardiology, Multidisciplinary Cardiology Department, aval Hospital, Quebec Heart and Lung Institute, Sainte-Foy, Quebec, Canada. This a

rogram (NCEP) (3), the International Diabetes Federa- ion (4), and the World Health Organization (5), among thers. Of these, the 2001 Third Report of the NCEP’s dult Treatment Panel has emerged as the most widely sed definition, primarily because it provides a relatively imple approach for diagnosing the metabolic syndrome by

ork is supported by the Canadian Institutes of Health Research (CIHR grant umber 82918). Mr. Mottillo is supported by a Canadian Cardiovascular Outcomes esearch Team (CCORT) summer studentship funded through a CIHR Team rant in Cardiovascular Outcomes Research. Dr. Genest is on the Speakers’ Bureau

or Merck and AstraZeneca. Dr. Joseph is a Chercheur-National of the Fonds de la echerche en Santé du Québec (FRSQ). Dr. Pilote is a Chercheur-National of the RSQ. Dr. Poirier is a Senior Physician-Scientist of the FRSQ. Dr. Rinfret is a

unior Physician-Scientist of the FRSQ. Dr. Schiffrin holds a Canada Research Chair n Vascular and Hypertension Research. Dr. Eisenberg is a Chercheur-National of the RSQ. All other authors have reported that they have no relationships to disclose.

Manuscript received February 11, 2010; revised manuscript received May 10, 2010,

ccepted May 13, 2010.

c f g d h

c t A m s i s b t m i i s r o o c a g a

D t t m v b

A C s s a i S s e o a d c t c m n D d m t d t s p p w d s i M n m m m v a t t D i s 9 u f r e e m t N s r o

1114 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

employing easily measurable risk factors (3,6). Specifically, the NCEP defines the metabolic syndrome as having 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumference: men �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density lipo- protein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) systemic hypertension (�130/ �85 mm Hg); and 5) elevated fasting glucose (�110 mg/dl). In 2004, this NCEP definition was revised (rNCEP) by lowering the threshold for fasting glucose to �100 mg/dl in concordance with American Diabetes Association criteria for impaired fasting glu-

ose (7). Also, thresholds for central obesity were lowered rom strictly �102 cm in men and 88 cm in women to reater than or equal to these values. Finally, the rNCEP efinition includes patients being treated for dyslipidemia, yperglycemia, or systemic hypertension. The value of the metabolic syndrome as a predictor of

ardiovascular risk has been met with much debate. In 2005, he American Diabetes Association and the European ssociation for the Study of Diabetes issued a joint state- ent summarizing the issues surrounding the metabolic

yndrome (8). In this statement, they underscore the need to dentify the cardiovascular risk associated with the metabolic yndrome. A large number of observational studies have een carried out to investigate this risk, and there is a need o synthesize the results of these studies. Two previous eta-analyses investigating the metabolic syndrome only

ncluded studies published prior to 2005 and did not nvestigate the rNCEP definition (9,10). Since then, 71 tudies have been published that used the NCEP and NCEP definitions to investigate the cardiovascular effects f the metabolic syndrome. Thus, our objective was to carry ut a systematic review and meta-analysis to estimate the ardiovascular risk associated with the metabolic syndrome ccording to the NCEP and rNCEP definitions in the eneral population and the subpopulations of men, women, nd patients without type 2 diabetes mellitus.

ethods

ata sources and searches. We systematically searched he Cochrane Library, EMBASE, and Medline databases hrough June 2009 using the following key words: all-cause ortality, cardiovascular risk, cardiovascular disease, cardio-

ascular mortality, fatal myocardial infarction (MI), meta-

Abbreviations and Acronyms

BMI � body mass index

CI � confidence interval

CVD � cardiovascular disease

HDL � high-density lipoprotein

HR � hazard ratio

LDL � low-density lipoprotein

MI � myocardial infarction

NCEP � National Cholesterol Education Program

rNCEP � revised National Cholesterol Education Program

RR � relative risk

olic syndrome, National Cholesterol Education Program w

dult Treatment Panel III, nonfatal MI, revised National holesterol Education Program Adult Treatment Panel III,

troke, and syndrome X. References from published pro- pective studies, relevant reviews, and previous meta- nalyses were hand searched for additional studies not dentified in the database search. tudy selection. Eligible studies: 1) were prospective, ob- ervational studies; 2) stratified patients based on the pres- nce or absence of the metabolic syndrome using the NCEP r rNCEP definitions; 3) reported cardiovascular outcomes nd/or all-cause mortality; 4) reported outcomes as count ata, or as relative risk (RR) or hazard ratio (HR) with a orresponding measure of variance; and 5) were published in he English language. Studies investigating more than 1 ardiovascular outcome or more than 1 definition of the etabolic syndrome were also eligible for inclusion. Studies

ot meeting these criteria were excluded. ata extraction. Two reviewers independently extracted

ata using standardized data extraction forms. Disagree- ents were resolved by consensus or, when necessary, by a

hird reviewer. Reviewers extracted information on study esign, including the duration of follow-up, the setting, and he number of participants with and without the metabolic yndrome according to each definition. Extracted baseline articipant characteristics included age, sex, mean blood ressure, body mass index (BMI), cholesterol, triglycerides, aist circumference, and the prevalence of cardiovascular isease (CVD), type 2 diabetes mellitus, systemic hyperten- ion, obesity, and smoking. Reviewers extracted the follow- ng outcomes: all-cause mortality, CVD, CVD mortality,

I, and stroke. Outcomes data presented as count data, onadjusted risk estimates (RR or HR) with corresponding easures of variance, or multivariable adjusted risk esti- ates were extracted for participants with and without the etabolic syndrome. The variables included in the multi-

ariable models were also extracted. In addition, when vailable, outcomes were extracted for different subpopula- ions, which included men, women, and patients without ype 2 diabetes mellitus.

ata synthesis and analysis. We synthesized the results of ncluded studies using random-effects meta-analyses, and ynthesized results are presented as RRs with corresponding 5% confidence intervals (CIs). Heterogeneity was assessed sing I2 statistics. We only conducted these meta-analyses or studies that reported outcomes as count data; studies that eported outcomes as risk estimates only (HR and RR) were xcluded from these analyses. In the general population, we stimated the cardiovascular risk associated with the NCEP, odified NCEP, the rNCEP, and modified rNCEP defini-

ions of the metabolic syndrome separately. The modified CEP and modified rNCEP definitions typically used mea-

urements of BMI (typically, BMI �30 kg/m2 or BMI anging from �25 to 27 kg/m2 for Asian populations) instead f waist circumference to define central obesity.

We also assessed the cardiovascular risk when all definitions

ere pooled. With the pooled definitions, we determined the

r p c 2 o o

o e a a s p l T s a f w

S p l t r i i s N s d

o t s

s f T t t w t m 2 c f f s p s p

a 5 ( ( r s ( d s 1

1115JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

isk in the general population, in men, in women, and in atients without type 2 diabetes mellitus. Pooled analyses were onducted for the following 5 outcomes: 1) all-cause mortality; ) CVD; 3) CVD mortality; 4) MI; and 5) stroke. For each utcome, a meta-analysis was performed to summarize the verall effects across all relevant studies.

We reported risk estimates (HR and RR) in tables as part f our systematic review. We classified nonadjusted risk stimates and risk estimates adjusting exclusively for age nd/or sex as “least adjusted.” In contrast, risk estimates djusting for any cardiovascular risk factor (i.e., smoking tatus, low-density lipoprotein [LDL] cholesterol, and hysical activity) were classified as “most adjusted.” The

ength of follow-up varied considerably between studies. herefore, we conducted a sensitivity analysis in which we

tratified studies using the median length of follow-up. In ddition, funnel plots were constructed and visually assessed or the possible presence of publication bias. All analyses ere conducted using MIX software version 1.7 (11,12).

esults

earch results and study inclusion. A total of 3,162 otentially relevant studies were identified in our initial

iterature search (Fig. 1). After screening the abstracts of hese studies, the full-length papers of 189 studies were etrieved and assessed for eligibility. Of the retrieved stud- es, a total of 87 met our inclusion criteria and were included n our systematic review (Tables 1 to 5). The remaining 102 tudies were excluded either because they did not use the CEP or rNCEP definitions of the metabolic syndrome to

tratify patients (n � 68), they used a cross-sectional study

Figure 1 Flow Diagram of Studies Included in the Systematic R

NCEP � National Cholesterol Education Program; rNCEP � revised National Chole

esign (n � 31), or they did not report any cardiovascular m

utcomes (n � 3). No additional studies were identified hrough our hand search of references from published tudies, relevant reviews, and previous meta-analyses.

All included studies were published since 2002, had ample sizes ranging from 76 to 124,513 patients, and had ollow-up durations ranging from 1.0 to 32.7 years (Online ables 1 to 4). The prevalence of the metabolic syndrome in

hese studies ranged from 1% in a study of women without ype 2 diabetes mellitus (13) and 78% in a study of patients ith type 2 diabetes mellitus (14). There were also varia-

ions in the mean values for each of the 5 components of the etabolic syndrome: 1) BMI ranged from 22 to 33 kg/m2;

) fasting glucose ranged from 82 to 196 mg/dl; 3) HDL holesterol ranged from 37 to 64 mg/dl; 4) triglycerides ranged rom 88 to 199 mg/dl; and 5) systolic blood pressure ranged rom 117 to 174 mm Hg. Many studies followed specific ubpopulations, accounting for much of the variability. In articular, several studies reported outcomes for men (28 tudies; n � 172,548), women (24 studies; n � 164,768), and articipants without diabetes (17 studies; n � 172,367). Of the 87 studies (n � 951,083) included in our system-

tic review, 43 reported all-cause mortality data (n � 36,864) (Table 1), 19 reported CVD (n � 116,202) Table 2), 38 reported CVD mortality (n � 407,350) Table 3), 12 reported MI (n � 29,470) (Table 4), and 26 eported stroke (n � 126,633) (Table 5). A total of 38 tudies investigated the NCEP definition (n � 345,560) Online Table 1), and 26 studies investigated the rNCEP efinition (n � 433,808) (Online Table 2). In addition, 25 tudies investigated the modified NCEP definition (n � 52,091) (Online Table 3), and 7 studies investigated the

Education Program.

eview

sterol

odified rNCEP definition (n � 19,624) (Online Table 4).

1116 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

etS Studies Reporting the Incidence of All-Cause MortalityTable 1 MetS Studies Reporting the Incidence of All-Cause Mortality

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up

(yrs) Effect

Measure

Risk of All-Cause Mortality† (95% CI)

All-Cause Mortality (%)

Least Adjusted Most Adjusted MetS Group

Non-MetS Group

NCEP definition‡ Benetos et al., 2008 (33) Pts without CVD 84,730 9.6 4.7§ HR — 1.63 (1.38–1.93) — — Butler et al., 2006 (14) General population 3,035 38.5 6.0� RR 1.02 (0.85–1.22) — 14.5 14.2

Men 1,473 — 6.0� RR — — 15.9 19.0 Women 1,562 — 6.0� RR — — 13.4 9.0 Pts with T2DM 461 77.9 6.0� RR 0.71 (0.48–1.06) — 18.1 25.5 Pts without T2DM 2,562 31.6 6.0� RR 0.95 (0.76–1.17) — 12.9 13.6

Dekker et al., 2005 (34) Men 615 19.0 11.0� HR 1.98 (1.28–3.05) — — — Women 749 25.8 11.0� HR 1.18 (0.72–1.94) — — —

Guize et al., 2007 (35) General population 60,754 10.3 3.6§ HR — 1.79 (1.35–2.38) — — Hillier et al., 2005 (36) Elderly women with no T2DM 921 27.1 12.2§ HR — 1.30 (1.00–1.70) — — Hong et al., 2007 (37) Pts with atherosclerosis 14,699 — 9.0§ RR — 1.39 (1.22–1.58) 9.6 5.9

Men with atherosclerosis 6,389 32.4 9.0§ RR — 1.57 (1.31–1.89) 10.2 8.0 Women with atherosclerosis 8,310 29.1 9.0§ RR — 1.22 (1.02–1.47) 9.2 4.3

Hunt et al., 2004 (28) General population 2,107 9.4 12.7§ HR 1.47 (1.13–1.92) — — — Subjects with CVD 1,947 — 12.7§ HR 1.06 (0.71–1.58) — — —

Katzmarzyk et al., 2005 (38) Nonobese men 7,505 4.7 10.0§ RR — 0.92 (0.53–1.60) 3.98 2.24 Overweight men 9,048 19.8 10.2§ RR — — 3.52 2.21 Obese men 2,620 61.1 10.2§ RR — — 3.44 2.45

Katzmarzyk et al., 2006 (39) Men 20,789 19.7 11.0§ RR 1.46 (1.23–1.74) 1.36 (1.14–1.62) 4.5 2.7 Lakka et al., 2002 (40) Middle-aged men 707 15.0 12.0¶ RR 1.67 (0.95–2.92) 1.67 (0.91–3.08) — — Langenberg et al., 2006 (41) General population 2,118 — 20.0� HR — 1.43 (1.24–1.65) 71.5 58.8

Men 977 16.9 20.0� HR — 1.44 (1.18–1.76) 74.5 65.8 Women 1,141 15.1 20.0� HR — 1.46 (1.19–1.80) 68.6 53.0

Mancia et al., 2007 (42) General population 2,013 16.2 12.3� HR 2.39 (1.79–3.18) 1.37 (1.02–1.84) 20.2 9.2 Marroquin et al., 2004 (43) Women with CAD 147 42.2 3.5¶ HR — 4.93 (1.02–23.76) 14.5 2.11

Women without CAD 362 34.5 3.5¶ HR — 1.41 (0.32–6.32) 3.2 3.5 Women with T2DM without CAD 340 30.3 3.5¶ RR 2.20 (0.60–8.04) — 7.8 3.5

Monami et al., 2008 (44) Pts with T2DM 1,716 67.1 4.7§ HR 1.36 (1.10–1.69) — — — Pannier et al., 2008 (45) Normotensive pts 34,577 4.5 4.7§ HR — 1.09 (0.68–1.75) — —

Hypertensive pts 26,447 17.7 4.7§ HR — 1.40 (1.13–1.74) — — Ramkumar et al., 2007 (46) Pts with moderate CKD 710 48.9 9.0� HR — 1.40 (1.01–1.94) — — Sundstrom et al., 2006 (47) 70-year-old men 1,221 24.1 32.7� HR 1.58 (1.24–2.01) 1.26 (0.95–1.66) — — Takeno et al., 2008 (48) Pts with AMI 461 37.3 1.5¶ HR — 1.27 (0.54–3.04) — — Wang et al., 2007 (49) Elderly without T2DM 1,025 42.7 13.5¶ HR 1.13 (0.93–1.37) 1.08 (0.89–1.31) — —

Elderly men without T2DM — — 13.5¶ HR — 1.08 (0.82–1.42) — — Elderly women without T2DM — — 13.5¶ HR — 1.08 (0.83–1.40) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 42.6 3.2¶ HR 1.45 (1.17–1.80) 1.43 (1.14–1.78) — — Zambon et al., 2009 (51) Elderly 2,910 39.0 4.4§ HR 1.30 (1.11–1.54) — — —

Elderly men 1,174 25.6 4.4§ HR 1.26 (0.99–1.60) — — — Elderly women 1,736 48.1 4.4§ HR 1.33 (1.06–1.68) — — —

Modified NCEP definition# Chen et al., 2006 (52) Pts with renal disease and ACS 76 76.3 18.1§ RR 2.82 (0.72–11.09) — 31.4 11.1 Feinberg et al., 2007 (53) Pts with ACS, without T2DM 1,060 33.9 1.0� HR — 1.96 (1.18–3.24) 8.9 4.6 Kasai et al., 2006 (54) Pts who underwent PCI 748 42.5 12.0§ HR — 1.34 (0.88–2.05) 13.5 10.5 Levantesi et al., 2005 (55) Pts post-MI 8,245 37.0 3.5� RR 1.15 (0.99–1.33) 1.29 (1.10–1.51) 8.5 7.4 Malik et al., 2004 (56) General population 4,576 37.1 13.3§ HR — 1.40 (1.19–1.66) — —

Subjects with T2DM 4,056 29.0 13.3§ HR — 1.17 (0.96–1.42) — — Nigam et al., 2006 (57) General population 24,358 13.5 12.6§ HR 1.23 (1.16–1.29) 1.21 (1.14–1.29) — — Sundstrom et al., 2006 (47) 50-year-old-men 2,322 17.4 32.7� HR 1.67 (1.45–1.93) 1.36 (1.17–1.58) — —

70-year-old-men 1,221 23.1 32.7� HR 1.52 (1.19–1.94) 1.20 (0.90–1.59) — — Thomas et al., 2007 (58) General population 2,863 17.5 8.5§ RR 3.03 (2.00–4.59) — 7.0 2.3

Revised NCEP definition** Benetos et al., 2008 (33) Pts without CVD 84,730 16.5 4.7§ HR — 1.32 (1.13–1.53) — — Davis et al., 2007 (59) Subjects with type 1 diabetes 127 41.7 11.0§ HR — 0.74 (0.32–1.74) — — Guize et al., 2007 (35) General population 60,754 17.7 3.6§ HR — 1.46 (1.14–1.88) — — Hildrum et al., 2009 (60) Age 40–59 yrs 3,789 28.0 7.9§ HR 2.06 (1.35–3.13) 2.14 (1.40–3.29) — —

Age 60–74 yrs 1,973 47.0 7.9§ HR 1.10 (0.90–1.36) 1.14 (0.92–1.41) — — Age 75–89 yrs 986 57.0 7.9§ HR 1.05 (0.88–1.25) 1.05 (0.87–1.26) — —

Huang et al., 2008 (61) Men 58,771 — 8.0� RR 2.09 (1.90–2.30) 1.21 (1.09–1.34) 4.7 2.3 Women 65,742 — 8.0� RR 4.33 (3.85–4.88) 1.30 (1.12–1.49) 4.4 4.1 Pts without T2DM without CVD 117,045 — 8.0� RR — 1.04 (0.94–1.15) 3.1 1.4

Kajimoto et al., 2008 (62) Pts with T2DM who underwent CABG 274 65.3 10.5§ HR 0.84 (0.56–1.27) — — — Pts without T2DM who underwent CABG 909 40.9 10.5§ HR 1.34 (1.03–1.74) — — —

Katzmarzyk et al., 2006 (39) Men 20,789 26.9 11.0§ RR 1.41 (1.21–1.67) 1.31 (1.11–1.54) 4.2 2.6 Lee et al., 2008 (63) Men 2,787 24.3 14.1§ HR 3.20 (2.50–4.10) 1.40 (1.10–1.80) 16.8 6.3

Women 2,912 21.4 14.1§ HR 5.00 (3.50–6.90) 1.80 (1.30–2.60) 11.7 2.7

(continued on next page)

S c T a c ( b r I m ( t b t w m r 9 1 m C 4 1 F w

e 2 1 f

w a w ( 8 C 3 i s i 9 n a S p s f w f

* a h l ¶ r

c � myo i

1117JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

ome studies investigated more than 1 cardiovascular out- ome or more than 1 definition of the metabolic syndrome. he metabolic syndrome and cardiovascular risk. The

ssociation between the metabolic syndrome and cardiovas- ular risk was similar for the NCEP and rNCEP definitions Table 6). Specifically, the metabolic syndrome as defined y the NCEP definition was associated with an increase in isk for all-cause mortality (RR: 1.54; 95% CI: 1.29 to 1.84; 2 � 84%; 95% CI: 73% to 91%) similar to that of the etabolic syndrome as defined by the rNCEP definition

RR: 1.63; 95% CI: 1.30 to 2.04; I2 � 95%; 95% CI: 92% o 97%). There was also little variation in cardiovascular risk etween the modified NCEP and modified rNCEP defini- ions compared with the original NCEP definition. Overall, hen studies investigating all definitions were pooled, the etabolic syndrome was associated with an increase in the

isk for CVD (RR: 2.35; 95% CI: 2.02 to 2.73; I2 � 64%; 5% CI: 39% to 79%), CVD mortality (RR: 2.40; 95% CI: .87 to 3.08; I2 � 81%; 95% CI: 72% to 88%), all-cause ortality (RR: 1.58; 95% CI: 1.39 to 1.78; I2 � 89%; 95% I: 85% to 92%), MI (RR: 1.99; 95% CI: 1.61 to 2.46; I2 � 0%; 95% CI: 0% to 73%), and stroke (RR: 2.27; 95% CI: .80 to 2.85; I2 � 88%; 95% CI: 82% to 91%) (Table 6, igs. 2 to 6). The point estimates for cardiovascular risk

ontinuedTable 1 Continued

First Author, Year (Ref. #)* Population n Me

Lopes et al., 2008 (64) Pts with CAD 589 Pts with CAD with T2DM — Pts with CAD without T2DM —

Mozaffarian et al., 2008 (65) Elderly 4,258 Noto et al., 2008 (66) General population 685

Men — Women —

Saito et al., 2009 (67) Men 12,412 Women 21,639

Simons et al., 2007 (68) Elderly men 1,233 Elderly women 1,572

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 Pts with CV risk factor without T2DM 2,472

Wen et al., 2008 (69) Elderly men 5,761 Elderly women 4,786

Modified revised NCEP definition# Hsu et al., 2008 (70) Men 4,888

Women 6,170 Kasai et al., 2008 (71) Pts without T2DM who underwent PCI 450 Niwa et al., 2007 (72) Men 914

Women 1,262 Tanomsup et al., 2007 (73) Men 2,545 Wang et al., 2007 (49) Elderly without T2DM 1,025

Elderly men without T2DM 648 Elderly women without T2DM 377

Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and djusting for any cardiovascular risk factor or component of the metabolic syndrome (i.e., smoking aving 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumferen

ipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); and 4) hypertension (�130 Median follow-up. #The modified NCEP and modified revised NCEP definitions use measurements evised NCEP definition uses a lower cutoff for elevated fasting glucose of �100 mg/dl.

ACS � acute coronary syndrome; AMI � acute myocardial infarction; BMI � body mass index ardiovascular; CVD � cardiovascular disease; HR � hazard ratio; MetS � metabolic syndrome; MI ntervention; Pts � patients; RR � relative risk; T2DM � type 2 diabetes mellitus.

ere consistently higher in women compared with men, (

specially for all-cause mortality (RR: 1.86; 95% CI: 1.37 to .52; I2 � 91%; 95% CI: 85% to 94% for women vs. RR: .42; 95% CI: 1.16 to 1.74; I2 � 90%; 95% CI: 81% to 94% or men).

A small number of studies reported outcomes for patients ithout type 2 diabetes mellitus. However, even in the

bsence of type 2 diabetes mellitus, the metabolic syndrome as still associated with an increased risk of CVD mortality

RR: 1.75; 95% CI: 1.19 to 2.58; I2 � 68%; 95% CI: 8% to 9%), MI (RR: 1.62; 95% CI: 1.31 to 2.01; I2 � 0%; 95% I: 0% to 90%), and stroke (RR: 1.86; 95% CI: 1.10 to .17; I2 � 89%; 95% CI: 56% to 97%). The confidence nterval for our assessment of the effect of the metabolic yndrome on all-cause mortality in this subpopulation was nconclusive (RR: 1.32; 95% CI: 0.65 to 2.67; I2 � 87%; 5% CI: 47% to 97%). Finally, there were an insufficient umber of studies investigating patients with type 2 diabetes vailable to pool these data. ensitivity analyses. In sensitivity analyses, we assessed the otential impact of follow-up duration on our results. These ensitivity analyses showed that studies with longer ollow-up times had risk estimates that were similar to those ith shorter follow-up times. Specifically, in studies with a

ollow-up time that was longer than the median duration

Follow-Up (yrs)

Effect Measure

Risk of All-Cause Mortality† (95% CI)

All-Cause Mortality (%)

Least Adjusted Most Adjusted MetS Group

Non-MetS Group

2.0� HR — 2.50 (1.15–5.47) — — 2.0� HR — 1.06 (0.38–2.91) — — 2.0� HR — 3.57 (1.38–9.19) — —

15.0� HR 1.31 (1.19–1.43) 1.22 (1.11–1.34) 53.1 47.9 15.0� HR — 1.00 (0.81–1.24) 25.6 23.7 15.0� HR — 0.95 (0.61–1.47) 18.8 19.6 15.0� HR — 1.04 (0.82–1.32) 28.0 28.2 12.3� HR 1.07 (0.94–1.23) 1.06 (0.92–1.23) — — 12.3� HR 1.23 (1.05–1.44) 1.22 (1.03–1.43) — — 16.0� HR 1.60 (1.37–1.86) 1.53 (1.30–1.79) 66.7 52.8 16.0� HR 1.43 (1.23–1.67) 1.35 (1.15–1.59) 51.3 39.4

3.2¶ HR 1.43 (1.15–1.78) 1.40 (1.12–1.75) — — 3.2¶ HR 1.36 (1.05–1.76) 1.34 (1.03–1.74) — — 8.0� RR 1.24 (1.08–1.42) 1.18 (1.02–1.36) — — 8.0� RR 1.27 (1.05–1.54) 1.15 (0.94–1.40) — —

4.7§ HR 1.05 (0.87–1.28) — — — 4.7§ HR 1.46 (1.19–1.80) — — — 12§ HR 0.90 (0.45–1.79) 0.88 (0.42–1.85) — —

12.5§ HR 1.05 (0.60–1.82) 1.13 (0.64–1.98) 17.1 15.3 12.5§ HR 1.24 (0.39–3.95) 1.31 (0.41–4.18) 13.6 6.2 17.0� HR — 1.60 (1.23–2.09) — — 13.5¶ HR 1.10 (0.91–1.33) 1.08 (0.88–1.28) — — 13.5¶ HR — 1.05 (0.80–1.37) — — 13.5¶ HR — 1.09 (0.83–1.43) — —

imates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates terol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as n �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density m Hg); and 5) elevated fasting glucose (�110 mg/dl). §Mean follow-up. �Maximum follow-up.

typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The

� coronary artery bypass graft; CAD � coronary artery disease; CI � confidence interval; CV � cardial infarction; NCEP � National Cholesterol Education Program; PCI � percutaneous coronary

tS (%)

52.3 — —

35.0 22.9 12.4 31.5 — —

31.1 34.1 50.1 —

45.6 54.4

22.0 28.0 28.7

9.0 1.7

19.3 51.3 — —

risk est , choles ce: me /�85 m of BMI (

; CABG

12.3 years), the risk for CVD mortality associated with the

m 8 w ( t

a a f 9 c 2

* a h l f N

1118 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

etabolic syndrome (RR: 2.62; 95% CI: 1.56 to 4.38; I2 � 8%; 95% CI: 80% to 93%) was similar to the risk in studies ith a follow-up time shorter than the median duration

RR: 2.23; 95% CI: 1.74 to 2.86; I2 � 65%; 95% CI: 30% o 82%).

Some studies also reported outcomes for patient popula-

etS Studies Reporting the Incidence of CVDTable 2 MetS Studies Reporting the Incidence of CVD

First Author, Year (Ref. #)* Population n MetS (%)

NCEP definition‡

Andreadis et al., 2007 (74) Pts with hypertension 1,007 42.1

Dekker et al., 2005 (34) Men 615 19.0

Women 749 25.8

Jeppesen et al., 2007 (75) General population 2,135 19.2

Resnick et al., 2003 (76) American Indians without T2DM

2,283 35.0

Sattar et al., 2008 (77) Elderly (age 70–82 yrs) without T2DM

4,812 27.7

Elderly (age 60–79 yrs) men without T2DM

2,737 27.2

Wilson et al., 2005 (78) Men 1,549 22.5

Women 1,774 14.9

Modified NCEP definition#

Guzder et al., 2006 (79) Pts with T2DM 428 82.5

Hwang et al., 2009 (80) Men 1,761 21.7

Women 674 11.4

Kokubo et al., 2008 (81) Men 2,492 18.0

Elderly men — —

Women 2,840 20.7

Elderly women — —

Ninomiya et al., 2007 (82) Men 1,050 20.6

Women 1,402 29.9

Schillaci et al., 2004 (83) Hypertensive pts 1,742 34.0

Song et al. 2007 (84) Women with BMI �25 kg/m2

13,526 4.3

Women with BMI 25–29.9 kg/m2

7,834 14.1

Women with BMI �30 kg/m2

4,266 31.4

Takeuchi et al., 2005 (85) Men 780 25.3

Worm et al., 2009 (86) HIV-infected pts 23,202 4.4

Revised NCEP definition**

Ingelsson et al., 2007 (87) Pts without T2DM 1,830 31.8

Liu et al., 2007 (88) General population 30,378 18.2

Meigs et al., 2007 (89) Pts without insulin resistance

2,104 16.2

Pts with insulin resistance

699 63.0

Vaccarino et al., 2008 (90) Women received CA angiography

652 60.0

Wand et al., 2007 (91) HIV-infected pts 881 8.5

ipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85 ollow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (ty CEP definition uses a lower cutoff for elevated fasting glucose of �100 mg/dl. CA � coronary artery; HIV � human immunodeficiency virus; other abbreviations as in Table 1.

ions with cardiovascular risk factors (systemic hypertension, t

therosclerosis, or a history of CVD). Our sensitivity nalysis showed that studies of subjects without these risk actors had risk estimates for CVD mortality (RR: 2.36; 5% CI: 1.79 to 3.1; I2 � 84%; 95% CI: 75% to 89%) onsistent with those obtained in our primary analysis (RR: .40; 95% CI: 1.87 to 3.08; I2 � 81%; 95% CI: 72%

-Up s)

Effect Measure

Risk of CVD† (95% CI) CVD (%)

Least Adjusted Most Adjusted MetS Group

Non-MetS Group

§ HR 1.75 (1.15–2.66) — 11.8 8.1

� HR 1.91 (1.31–2.79) 1.64 (1.11–2.44) — —

� HR 1.68 (1.11–2.55) 1.17 (0.73–1.87) — —

§ HR — 1.86 (1.39–2.45) — —

¶ HR 1.35 (1.13–1.62) 1.11 (0.79–1.56) — —

¶ HR 1.07 (0.86–1.32) — — —

¶ HR 1.27 (1.04–1.56) — — —

� RR 2.88 (1.99–4.16) — 17.9 4.9

� RR 2.25 (1.31–3.88) — 7.7 2.6

¶ HR 1.27 (0.72–2.23) 2.05 (1.13–3.74) — —

¶ RR 2.02 (1.38–2.95) — 10.0 4.9

¶ RR 5.17 (2.59–10.31) — 15.6 3.0

HR 1.70 (1.23–2.34) 1.75 (1.27–2.41) 12.3 6.5

HR 1.67 (1.16–2.40) 1.73 (1.20–2.48) — —

HR 1.93 (1.35–2.77) 1.90 (1.31–2.77) 9.5 3.2

HR 1.78 (1.19–2.66) 1.70 (1.12–2.59) — —

� HR 1.93 (1.38–2.70) 1.86 (1.32–2.62) 23.2 13.0

� HR 1.68 (1.22–2.33) 1.70 (1.22–2.36) 17.0 7.9

¶ HR — 1.73 (1.25–2.38) — —

§ RR 2.58 (1.88–3.53) 2.40 (1.71–3.37) 7.9 2.2

§ RR 2.92 (2.24–3.79) — 7.1 2.4

§ RR 2.32 (1.71–3.15) — 6.1 2.6

� HR — 2.23 (1.14–4.34) 11.7 6.7

§ RR 2.89 (2.34–3.59) 0.94 (0.69–1.27) — —

¶ RR 2.08 (1.47–2.93) — 10.2 4.9

� HR — 2.01 (1.73–2.33) — —

¶ RR 1.40 (1.00–2.10) 1.30 (0.90–1.90) 10.6 6.1

¶ RR 2.01 (1.28–3.15) — 17.1 8.5

§ RR 2.44 (1.51–3.92) 1.81 (1.10–2.99) — —

� HR — 2.56 (0.86–7.60) — —

imates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates terol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as n �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density ); and 5) elevated fasting glucose (�110 mg/dl). §Median follow-up. �Maximum follow-up. ¶Mean BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised

Follow (yr

2.1

11.0

9.4

7.8

3.2

7.0

8.0

4.2

8.7

—

14.0

4.1

10.0

6.0

5.1

7.2

10.0

12.0

5.9

3.0

risk est , choles ce: me

mm Hg pically,

o 88%).

O e b d p d s

2 a p c t o

m m v r o m r w d v

b d n I i m

1119JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

Funnel plots suggest that mild publication bias may be resent (data not shown).

iscussion

ur systematic review and meta-analysis was designed to stimate the cardiovascular risk associated with the meta- olic syndrome as defined by the NCEP and rNCEP efinitions. Our literature search was designed to include all rospective studies investigating the NCEP and rNCEP efinitions, thereby allowing us to include a large number of tudies (87 studies; n � 951,083).

Overall, the metabolic syndrome was associated with a -fold increase in risk of CVD, CVD mortality, and stroke, nd a 1.5-fold increase in risk of all-cause mortality. Thus, atients with the metabolic syndrome were at higher risk for ardiovascular outcomes than for all-cause mortality, al- hough these patients were at elevated risk for either

Figure 2 The Metabolic Syndrome and the Relative Risk for All

I2 � 89%; 95% confidence interval (CI): 85% to 92%. ACS � acute coronary syndro MI � myocardial infarction; PCI � percutaneous coronary intervention; Pts � patie

utcome compared with those without this syndrome. The h

etabolic syndrome was also associated with an approxi- ate 2-fold increase in risk for MI. There was little

ariation in cardiovascular risk between the NCEP and NCEP definitions, which principally differ in their thresh- ld for impaired fasting glucose (�110 mg/dl vs. �100 g/dl, respectively). The modified NCEP and modified

NCEP definitions also showed little variation compared ith the original NCEP definition; these definitions only iffer in their measurement of central obesity (use of BMI ersus waist circumference, respectively).

The pathophysiological mechanism by which the meta- olic syndrome increases cardiovascular risk remains under ebate (15). Earlier definitions by the World Health Orga- ization (5) and the European Group for the Study of nsulin Resistance (16) emphasize the independent role of nsulin resistance as the underlying component of the

etabolic syndrome. Insulin resistance progresses toward

e Mortality

AD � coronary artery disease; MetS � metabolic syndrome; R � relative risk; T2DM � type 2 diabetes mellitus.

-Caus

me; C nts; R

yperinsulinemia and hyperglycemia, thus triggering pe-

MetS Studies Reporting the Incidence of CVD MortalityTable 3 MetS Studies Reporting the Incidence of CVD Mortality

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of CVD Mortality† (95% CI) CVD Mortality (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group

NCEP definition‡ Benetos et al., 2008 (33) Pts without CVD 84,730 9.6 4.7§ HR — 2.05 (1.28–3.28) — — Butler et al., 2006 (14) General population 3,035 38.5 6.0� RR 1.37 (0.98–1.92) — 5.13 3.75

Men 1,473 — 6.0� — — — 6.2 5.5 Women 1,562 — 6.0� — — — 4.4 1.9 Pts with T2DM 461 77.9 6.0� RR 0.77 (0.38–1.53) — 7.5 9.8 Pts without T2DM 2,562 31.6 6.0� RR 1.19 (0.79–1.81) — 4.1 3.4

DECODE study, 2007 (92) Men without T2DM age 50–69 yrs 2,790 26.5 10.0� RR 1.48 (1.02–2.14) — 5.55 3.75 Dekker et al., 2005 (34) Men 615 19.0 11.0� HR 2.25 (1.16–4.34) — — —

Women 749 25.8 11.0� HR 0.76 (0.32–1.83) — — — Hillier et al., 2005 (36) Elderly women with no T2DM 921 27.1 12.2§ HR — 1.60 (1.10–2.30) — — Hunt et al., 2004 (28) General population 2,107 9.4 12.7§ HR 2.53 (1.74–3.67) — — —

Subjects with CVD 1,947 — 12.7§ HR 2.01 (1.13–3.57) — — — Katzmarzyk et al., 2005 (38) Nonobese men 7,505 4.7 10.2§ RR 3.74 (1.68–8.32) 1.60 (0.71–3.61) 1.99 0.53

Overweight men 9,048 19.8 10.2§ RR 2.14 (1.35–3.41) — 1.51 0.7 Obese men 2,620 61.1 10.2§ RR 1.33 (0.67–2.63) — 1.56 1.18

Katzmarzyk et al., 2006 (39) Men 20,789 19.7 11.4§ RR 2.03 (1.54–2.69) 1.79 (1.35–2.37) 1.93 0.8 Lakka et al., 2002 (40) Men 707 15.0 11.6§ RR 2.08 (0.93–4.65) 2.27 (0.96–5.36) — — Langenberg et al., 2006 (41) General population 2,118 — 20.0� HR — 1.50 (1.23–1.83) 38.0 29.1

Men 977 16.9 20.0� HR — 1.28 (0.95–1.71) 32.7 33.7 Women 1,141 15.1 20.0� HR — 1.18 (1.38–2.39) 43.0 25.3

Maggi et al., 2006 (93) Men 1,359 31.4 4.0� HR 3.35 (1.35–8.30) 1.12 (1.09–1.16) — — Women 1,724 59.5 4.0� HR 1.06 (0.63–1.39) 0.82 (0.56–1.19) — —

Mancia et al., 2007 (42) General population 2,013 16.2 12.3� HR 3.27 (1.97–5.41) 1.71 (1.02–2.85) 7.3 2.4 Monami et al., 2008 (44) Pts with T2DM 1,716 67.1 4.7§ HR 1.82 (1.24–2.68) — — — Solymoss et al., 2009 (94) Pts with �50% stenosis of CA 876 53.0 12.6§ HR 1.43 (0.97–2.11) 1.42 (0.96–2.10) — — Sundstrom et al., 2006 (47) 70-year-old men 1,221 24.1 32.7� HR 2.01 (1.41–2.85) 1.43 (0.95–2.17) — — Wang et al., 2007 (49) Elderly without T2DM 1,025 42.7 13.5¶ HR 1.43 (1.12–1.84) 1.35 (1.05–1.74) — —

Elderly men without T2DM — — 13.5¶ HR — 1.43 (1.00–2.03) — — Elderly women without T2DM — — 13.5¶ HR — 1.27 (0.89–1.82) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 42.6 3.2¶ HR 1.71 (1.31–2.24) 1.65 (1.25–2.17) — — Zambon et al., 2009 (51) Elderly 2,910 39.0 4.4§ HR 1.36 (1.03–1.78) — — —

Elderly men 1,174 25.6 4.4§ HR 1.51 (0.98–2.33) — — — Elderly women 1,736 48.1 4.4§ HR 1.27 (0.90–1.79) — — —

(continued on next page)

1 1

2 0

M ottillo

et al.

JACC Vol.56,No.14,2010

The M

etabolic Syndrom

e and

C ardiovascular

R isk

Septem ber28,2010:1113–32

ContinuedTable 3 Continued

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of CVD Mortality† (95% CI) CVD Mortality (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group

Modified NCEP definition# Chen et al., 2006 (52) Pts with renal disease and ACS 76 73.7 18.2§ — — — 24.0 0.0 de Simone et al., 2007 (95) Hypertensive subjects 8,243 19.3 10.0� HR — 1.73 (1.38–2.17) — — Kasai et al., 2006 (54) Pts who underwent PCI 748 28.7 12§ RR 2.70 (1.28–5.70) — 6.3 2.3 Malik et al., 2004 (56) General population 4,576 37.1 13.3§ HR — 1.82 (1.40–2.37) — —

Subjects with T2DM 4,056 29.0 13.3§ HR — 1.65 (1.10–2.47) — — Nigam et al., 2006 (57) General population 24,358 13.5 12.6§ HR 1.26 (1.19–1.35) 1.22 (1.14–1.31) — — Nakatani et al., 2007 (96) Japanese pts with AMI 3,858 42.7 2.0¶ HR — 1.08 (0.62–1.90) — — Sundstrom et al., 2006 (47) 50-year-old men 2,322 17.4 32.7� HR 2.21 (1.82–2.68) 1.59 (1.29–1.95) — —

70-year-old men 1,221 23.1 32.7� HR 2.11 (1.49–3.00) 1.55 (1.02–2.35) — — Thomas et al., 2007 (58) General population 2,863 17.5 8.5§ RR 6.12 (2.99–12.51) — 3.4 0.6

Revised NCEP definition** Benetos et al., 2008 (33) Pts without CVD 84,730 16.5 4.7§ HR — 1.64 (1.08–2.50) — — Davis et al., 2007 (59) Subjects with type 1 diabetes 127 41.7 11.0§ HR 1.37 (0.40–4.74) — — — Hildrum et al., 2009 (60) Age 40–59 yrs 3,789 28.0 7.9§ HR 3.97 (2.00–7.88) 3.95 (1.96–7.97) — —

Age 60–74 yrs 1,973 47.0 7.9§ HR 1.07 (0.82–1.39) 1.09 (0.83–1.43) — — Age 75–89 yrs 986 57.0 7.9§ HR 1.12 (0.90–1.40) 1.11 (0.89–1.39) — —

Huang et al., 2008 (61) Men 58,771 — 8.0� RR 3.17 (2.56–3.93) 1.77 (1.40–2.24) 1.2 0.4 Women 65,742 — 8.0� RR 7.46 (5.55–10.02) 1.69 (1.19–2.42) 1.0 0.1 Pts without T2DM and CVD 117,045 — 8.0� RR — 1.68 (1.32–2.16) 0.7 0.2

Hunt et al., 2007 (97) Men without T2DM 1,940 15.6 15.5§ RR 3.38 (1.95–5.85) — 5.1 1.5 Women without T2DM 2,532 19.4 15.5§ RR 1.81 (1.17–2.81) — 7.2 4.0

Kajimoto et al., 2008 (62) Nondiabetic pts who had CABG 909 40.9 10.5§ HR 2.31 (1.36–3.92) — — — Diabetic pts who had CABG 274 65.3 10.5§ HR 0.75 (0.41–1.36) — — —

Katzmarzyk et al., 2006 (39) Men 20,789 26.9 11.4§ RR 1.89 (1.44–2.47) 1.67 (1.27–2.19) 1.7 0.8 Lee et al., 2008 (63) Men 2,787 24.3 14.1§ HR 6.70 (4.30–10.40) 3.00 (1.90–4.80) 8.1 1.4

Women 2,912 21.4 14.1§ HR 7.40 (4.00–13.80) 2.10 (1.10–4.00) 4.3 0.7 Mozaffarian et al., 2008 (65) Elderly 4,258 35.0 15.0� RR 1.51 (1.29–1.76) — — — Noto et al., 2008 (66) General population 685 22.9 15.0� HR 1.33 (0.96–1.83) — 10.6 7.8

Men — 12.4 15.0� HR 1.45 (0.83–2.52) — 11.8 7.6 Women — 31.5 15.0� HR 1.31 (0.88–1.93) — 10.2 7.9

Saito et al., 2009 (67) Men 12,412 — 12.3¶ HR 1.61 (1.16–2.23) 1.41 (0.99–2.02) — — Women 21,639 — 12.3¶ HR 1.46 (1.00–2.13) 1.44 (0.98–2.11) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 50.1 3.2¶ HR 1.69 (1.28–2.22) 1.61 (1.22–2.14) — — Pts with CV factor without T2DM 2,472 — 3.2¶ HR 1.55 (1.12–2.14) 1.49 (1.07–2.08) — —

Wen et al., 2008 (69) Elderly men 5,761 45.6 8.0� RR 1.70 (1.28–2.23) 1.45 (1.07–1.96) — — Elderly women 4,786 54.4 8.0� RR 1.86 (1.21–2.84) 1.66 (1.05–2.60) — —

Modified revised NCEP definition# Espinola-Klein et al., 2007 (98) Pts with CAD 811 43.0 6.7¶ HR — 2.50 (1.60–3.80) 18.4 7.4 Hsu et al., 2008 (70) Men 4,888 22.0 4.7§ HR — 1.40 (0.96–2.04) — —

Women 6,170 28.0 4.7§ HR — 1.85 (1.25–2.73) — — Niwa et al., 2007 (72) Men 914 9.0 12.5§ HR 1.67 (0.65–4.34) 1.84 (0.68–4.96) 6.1 3.7

Women 1,262 1.7 12.5§ HR 1.12 (0.15–8.39) 1.31 (0.17–9.96) 4.5 2.03 Wang et al., 2007 (49) Elderly without T2DM 1,025 51.3 13.5¶ HR 1.37 (1.07–1.77) 1.31 (1.02–1.69) — —

Elderly men without T2DM 648 — 13.5¶ HR — 1.32 (0.93–1.87) — — Elderly women without T2DM 377 — 13.5¶ HR — 1.29 (0.89–1.87) — —

*Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and risk estimates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates adjusting for any cardiovascular risk factor or component of the metabolic syndrome (i.e., smoking, cholesterol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as having 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumference: men �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density lipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85 mm Hg); and 5) elevated fasting glucose (�110 mg/dl). §Mean follow-up. �Maximum follow-up. ¶Median follow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised NCEP definition uses a lower cutoff for elevated fasting glucose of � 100 mg/dl.

Abbreviations as in Tables 1 and 2.

1 1

2 1

JACC Vol.

56, No.

14, 2010

M ottillo

et al.

Septem ber

28, 2010:1113–32

The M

etabolic Syndrom

e and

C ardiovascular

R isk

MetS Studies Reporting the Incidence of MITable 4 MetS Studies Reporting the Incidence of MI

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of MI† (95% CI) MI (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group

NCEP definition‡

Butler et al., 2006 (14) General population 3,035 38.5 6.0§ HR — 1.51 (1.12–2.05) 9.1 5.7

Men 1,473 — 6.0§ HR — — 12.1 8.1

Women 1,562 — 6.0§ HR — — 6.8 3.1

Pts with T2DM 461 77.9 6.0§ RR 0.95 (0.52–1.74) — 11.1 11.8

Pts without T2DM 2,562 31.6 6.0§ RR 1.51 (1.11–2.04) — 8.2 5.4

Girman et al., 2004 (99) Pts without T2DM 1,991 20.6 5.4¶� HR 1.49 (1.21–1.83) — — —

Pts without T2DM 3,188 46.0 5.0§ HR 1.49 (0.99–2.25) — — —

Holvoet et al., 2004 (100) Elderly 3,033 37.8 5.0§ RR 1.91 (1.35–2.72) 1.97 (1.35–2.86) 5.6 2.9

Solymoss et al., 2009 (94) Pts with �50% stenosis of CA 204 53.0 12.6¶ HR 2.36 (1.00–5.57) 2.25 (0.93–5.43) — —

Takeno et al., 2008 (48) Pts with AMI 461 37.3 1.5� HR — 0.84 (0.23–2.70) — —

Thorn et al., 2009 (101) Pts with type 1 diabetes 2,474 — 5.7� HR 2.61 (1.90–3.59) 1.85 (1.32–2.59) — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 42.6 3.2� HR 1.54 (1.16–2.04) 1.61 (1.21–2.15) — —

Modified NCEP definition#

Chen et al., 2006 (52) Pts with renal disease and ACS 76 76.3 18.1¶ HR — — 16.0 0.0

Kasai et al., 2006 (54) Pts who underwent PCI 748 28.7 12¶ RR 1.35 (0.70–2.61) — 5.4 4.0

Kokubo et al., 2008 (81) Men 2,492 18.0 — HR 2.09 (1.30–3.37) 2.12 (1.31–3.43) 5.8 2.6

Women 2,840 20.7 — HR 2.68 (1.41–5.10) 2.77 (1.44–5.32) 3.6 0.8

Revised NCEP definition**

Nilsson et al., 2007 (102) Pts without T2DM 5,047 20.7 10.7¶ RR 1.99 (1.47–2.69) — 5.8 2.9

Men without T2DM 3,008 26.0 10.7¶ RR 1.87 (1.30–2.67) — 8.7 4.6

Women without T2DM 2,039 17.0 10.7¶ RR 1.48 (0.82–2.68) — 2.7 1.8

Noto et al., 2008 (66) General population 685 22.9 15.0§ HR — 1.91 (1.28–2.83) 7.5 3.9

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 50.1 3.2� HR 1.60 (1.20–2.14) 1.68 (1.25–2.26) — —

Pts with CV factor without T2DM 2,472 — 3.2� HR 1.57 (1.12–2.20) 1.65 (1.16–2.34) — —

*Studies are listed by category and then alphabetically by author. †Nonadjusted risk estimates and risk estimates adjusting exclusively for age and/or sex were classified as “least adjusted.” Risk estimates adjusting for any cardiovascular risk factor or component of the metabolic syndrome (i.e., smoking, cholesterol, obesity) were classified as “most adjusted.” ‡The NCEP defines the metabolic syndrome as having 3 or more of the following 5 cardiovascular risk factors: 1) central obesity (waist circumference: men �102 cm; women �88 cm); 2) elevated triglycerides (�150 mg/dl); 3) diminished high-density lipoprotein (HDL) cholesterol (men �40 mg/dl; women �50 mg/dl); 4) hypertension (�130/�85 mm Hg); and 5) elevated fasting glucose (�110 mg/dl). §Maximum follow-up. �Median follow-up. ¶Mean follow-up. #The modified NCEP and modified revised NCEP definitions use measurements of BMI (typically BMI �30 kg/m2 or BMI �27 kg/m2 in Asian populations) to define central obesity. **The revised NCEP definition uses a lower cutoff for elevated fasting glucose of �100 mg/dl.

Abbreviations as in Tables 1 and 2.

1 1

2 2

M ottillo

et al.

JACC Vol.56,No.14,2010

The M

etabolic Syndrom

e and

C ardiovascular

R isk

Septem ber28,2010:1113–32

r p l v c i c ( ( s c t d s t

a o i c i t i t t t

d w p h l n w s a m r p c i d e a a i c c s r

1123JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

ipheral vasoconstriction and sodium retention. Hepatic roduction of very low-density lipoprotein also increases,

eading to hypertriglyceridemia, low HDL cholesterol, ele- ated apolipoprotein B, elevated small LDL cholesterol, and onsequently, atherosclerosis. As a result of these lipid mbalances, individuals with the metabolic syndrome typi- ally exhibit a prothrombotic and proinflammatory state 15,17). More recent definitions by the NCEP (3), rNCEP 7), and the International Diabetes Federation (4) empha- ize central obesity as the underlying component. Adipo- ytes secrete mediators including TNF-�, leptin, adiponec- in, and resistin, which lead to insulin resistance. In these efinitions, it is postulated that central obesity causes ystemic hypertension and dyslipidemia independently and hrough the induction of insulin resistance.

Regardless of which definition is used, insulin resistance nd central obesity are postulated to be the key components f the metabolic syndrome, and both lead to glucose ntolerance and dysglycemia. Consequently, even a small hange in the fasting glucose threshold may have an mportant impact on the associated cardiovascular risk. For his reason, there has been considerable debate over the mpact of lowering the fasting glucose threshold from �110 o �100 mg/dl. We therefore carried out a meta-analysis of he cardiovascular risk associated with the rNCEP defini-

Figure 3 The Metabolic Syndrome and the Relative Risk for CV

I2 � 64%; 95% CI: 39% to 79%. BMI � body mass index; CVD � cardiovascular d

ion in addition to the original NCEP definition. s

Previous meta-analyses showed that the metabolic syn- rome was associated with higher cardiovascular risk in omen relative to men (9,10). In our meta-analysis, the oint estimates for cardiovascular risk were consistently igher in women compared with men. However, patient-

evel data are needed to confirm this finding. The mecha- isms explaining a potentially higher cardiovascular risk in omen with the metabolic syndrome are unclear; however,

everal theories have been postulated (18 –20). First, central diposity tends to be more pronounced in women post- enopause than in men, and thus may be linked to a higher

isk of cardiovascular disease (18). Second, the cholesterol rofile is different in women compared with men. HDL holesterol decreases post-menopause and LDL cholesterol ncreases post-menopause, with LDL particles becoming enser, and therefore, more atherogenic (19). Third, there is vidence that elevated triglycerides are more highly associ- ted with coronary artery disease in women than in men. In meta-analysis, it was shown that an increase in triglycer-

des of 18 mg/dl was associated with a 76% increased ardiovascular risk in women compared with a 32% in- reased risk in men (20). Finally, several studies have uggested a number of other unique risk factors that may be esponsible for a stronger association between the metabolic

; other abbreviations as in Figure 2.

isease

yndrome and cardiovascular risk in women. These risk

MetS Studies Reporting the Incidence of StrokeTable 5 MetS Studies Reporting the Incidence of Stroke

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of Stroke† (95% CI) Stroke (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group

NCEP definition‡

Boden-Albala et al., 2007 (103) General population 3,297 44.0 6.4§ HR — 1.50 (1.10–2.20) — —

Men 1,220 38.0 6.4§ HR — 1.10 (0.60–1.90) — —

Women 2,077 48.0 6.4§ HR — 2.00 (1.30–3.10) — —

Hsia et al., 2003 (104) Women with angiographic disease 397 61.2 2.8§ RR 1.90 (0.52–6.91) — 3.7 1.9

McNeill et al., 2005 (105) Men 6,881 23.7 11.0§ RR 1.28 (0.87–1.89) — 2.2 1.7

Women 5,208 22.7 11.0§ RR 5.45 (3.92–7.59) — 7.4 1.4

Qiao et al., 2009 (106) Men without CAD and T2DM 4,041 — 21.0� HR 1.30 (0.92–1.83) — — —

Women without CAD and T2DM 3,812 — 21.0� HR 2.30 (1.36–1.90) — — —

Solymoss et al., 2009 (94) Pts with �50% stenosis of CA 876 53.0 12.6§ HR 1.67 (1.18–2.37) 1.68 (1.18–2.39) — —

Thorn et al., 2009 (101) Pts with type 1 diabetes 2,474 — 5.7¶ HR 1.94 (1.25–3.02) 1.51 (0.94–2.44) — —

Vlek et al., 2008 (107) Hypertensive pts without T2DM 1,815 42.7 3.9§ HR 1.36 (0.85–2.16) — — —

Wang et al., 2008 (108) Elderly without T2DM 991 42.1 13.8¶ HR 1.62 (1.17–2.24) — — —

Wassink et al.,2008 (50) Pts with CV risk factor 3,196 42.6 3.2¶ HR 1.66 (1.10–2.49) 1.73 (1.13–2.65) — —

Modified NCEP definition#

Chen et al. 2006 (109) Men 725 45.5 10.4§ HR 5.80 (2.00–16.50) — 9.1 1.0

Women 831 58.7 10.4§ HR 2.50 (0.70–8.40) — 7.7 0.7

Chien et al., 2007 (110) General population 3,507 24.2 9.0¶ HR — 2.05 (1.45–2.91) — —

Hwang et al., 2009 (80) Men 1,761 21.7 8.7§ RR 1.35 (0.80–2.25) — 5.0 3.7

Women 674 11.4 8.7§ RR 4.98 (2.23–11.13) — 11.7 2.4

Iso et al., 2007 (111) Men 3,813 — 18.3¶ HR 1.90 (1.30–2.80) 2.00 (1.30–3.10) — —

Women 5,646 — 18.3¶ HR 1.40 (1.00–2.10) 1.50 (1.00–2.30) — —

Kokubo et al., 2008 (81) Men 2,492 18.0 — HR 1.52 (0.99–2.34) 1.58 (1.02–2.43) 6.5 4.0

Women 2,840 20.7 — HR 1.70 (1.09–2.64) 1.62 (1.02–2.58) 6.0 2.5

Koren-Morag et al., 2005 (112) Pts with CAD without T2DM 10,784 34.3 8.1� RR 1.44 (1.18–1.76) — 4.3 3.0

Men with CAD without T2DM 8,844 — 8.1� RR 1.31 (1.05–1.64) — 4.2 3.2

Women with CAD without T2DM 1,903 — 8.1� RR 2.09 (1.28–3.42) — 4.8 2.3

Kurl et al., 2006 (113) Men without T2DM 1,264 9.0 14.3§ RR 2.00 (1.01–3.95) 2.39 (1.17–4.89) — —

Ninomiya et al., 2007 (82) Men 1,050 20.6 14.0� HR 2.04 (1.33–3.14) 1.92 (1.23–2.98) 14.4 7.6

Women 1,402 29.9 14.0� HR 1.43 (0.99–2.08) 1.50 (1.03–2.19) 11.9 6.6

Song et al., 2007 (84) Women with BMI �25 kg/m2 13,256 4.3 10.0¶ RR 1.35 (0.74–2.45) 1.24 (0.64–2.39) 2.1 1.0

Women with BMI 25–29.9 kg/m2 7,834 4.3 10.0¶ RR 2.07 (1.23–3.47) — 1.7 0.8

Women with BMI �30 kg/m2 4,266 4.3 10.0¶ RR 1.79 (0.96–3.32) — 1.3 0.8

Takahashi et al., 2007 (13) Women without T2DM 726 1.1 6.4§ RR — 23.1 (2.7–19.6) — —

Takeuchi et al., 2005 (85) Men 780 25.3 6.0� RR — 1.61 (1.26–2.06) — —

Wannamethee et al., 2005 (114) Men 5,228 25.5 20.0� RR 1.51 (1.20–1.91) — 7.6 5.0

(continued on next page)

1 1

2 4

M ottillo

et al.

JACC Vol.56,No.14,2010

The M

etabolic Syndrom

e and

C ardiovascular

R isk

Septem ber28,2010:1113–32

ContinuedTable 5 Continued

First Author, Year (Ref. #)* Population n MetS (%) Follow-Up (yrs) Effect Measure

Risk of Stroke† (95% CI) Stroke (%)

Least Adjusted Most Adjusted MetS Group Non-MetS Group

Revised NCEP definition**

Nilsson et al., 2008 (102) Pts without T2DM 5,047 20.7 10.7§ RR 2.47 (1.83–3.34) — 6.4 2.6

Men without T2DM 3,008 26.0 10.7§ RR 2.10 (1.39–3.18) — 7.0 3.3

Women without T2DM 2,039 17.0 10.7§ RR 2.71 (1.75–4.19) — 5.9 2.2

Noto et al., 2008 (66) General population 685 22.9 15.0� HR 1.44 (0.94–2.19) — 6.8 3.5

Qiao et al., 2009 (106) Men without CAD and T2DM 4,041 — 21.0� HR 1.13 (0.81–1.58) — — —

Women without CAD and T2DM 3,812 — 21.0� HR 2.08 (1.24–3.51) — — —

Rodriguez-Colon et al., 2009 (115) General population 14,993 39.0 9.0� RR 2.45 (1.96–3.08) 2.24 (1.78–2.82) 3.2 1.3

Men 6,732 39.0 9.0� RR 1.98 (1.47–2.67) 2.11 (1.56–2.85) 3.7 1.9

Women 8,261 39.0 9.0� RR 3.27 (2.29–4.67) 2.41 (1.69–3.49) 2.9 1.1

Simons et al., 2007 (68) Elderly men 1,233 31.1 16.0� HR 1.43 (1.07–1.92) 1.31 (0.96–1.77) 70.1 15.8

Elderly women 1,572 34.1 16.0� HR 1.53 (1.17–2.01) 1.37 (1.04–1.82) 17.0 12.2

Wang et al., 2008 (108) Elderly without T2DM 991 50.8 13.8¶ HR 1.52 (1.10–2.11) — — —

Wassink et al., 2008 (50) Pts with CV risk factor 3,196 50.1 3.2¶ HR 1.75 (1.15–2.66) 1.77 (1.14–2.75) — —

Pts with CV factor without T2DM 2,472 — 3.2¶ HR 1.88 (1.18–2.99) 1.96 (1.21–3.18) — —

Wild et al., 2009 (116) General population 762 34.7 15.0� RR 2.61 (1.52–4.48) — 4.2 11.0

Modified revised NCEP definition#

Chen et al., 2006 (109) Men 709 48.6 10.4§ HR 8.20 (2.00–34.30) — 8.9 0.7

Women 850 57.3 10.4§ HR 2.60 (0.60–11.30) — 6.8 0.6

Abbreviations as in Tables 1 and 2.

1 1

2 5

JACC Vol.

56, No.

14, 2010

M ottillo

et al.

Septem ber

28, 2010:1113–32

The M

etabolic Syndrom

e and

C ardiovascular

R isk

f c

m i s c p d o m a 1 1 f w 2 w t M m

g m i e c c a N s ( ( s m n p ( w g r o 1 O s T r t w s

t c p cm

a ry

o f

th e

C a rd

io va

sc u la

r R

is k

A ss

o c ia

te d

W it

h th

e M

e tS

* a b le

6 S

u m

m a ry

o f

th e

C a rd

io va

sc u la

r R

is k

A ss

o c ia

te d

W it

h th

e M

e tS

P o p u la

ti o n

C V D

M o rt

a lit

y A

ll- C

a u se

M o rt

a lit

y M

I S

tr o k e

N o .

o f

P o p

A rm

s† N

o .

o f

P ts

R R

(9 5 %

C I)

N o .

o f

P o p

A rm

s† N

o .

o f

P ts

R R

(9 5 %

C I)

N o .

o f

P o p

A rm

s† N

o .

o f

P ts

R R

(9 5 %

C I)

N o .

o f

P o p

A rm

s† N

o .

o f

P ts

R R

(9 5

% C

N o .

o f

P o p

A rm

s† N

o .

o f

P ts

R R

(9 5

% C

ll M

e tS

d e fi n it io

n s

1 6

4 5

,2 5

1 2

.3 5

(2 .0

2 –2

.7 3

) 1

9 6

7 ,3

6 5

2 .4

0 (1

.8 7

–3 .0

8 )

2 3

9 0

,7 8

8 1

.5 8

(1 .3

9 –1

.7 8

) 8

1 7

,9 1

8 1

.9 9

(1 .6

1 –2

.4 6

) 2

2 9

0 ,1

6 6

2 .2

7 (1

.8 0

–2 .8

5 )

C E P

d e fi n it io

n ‡

3 4

,1 5

6 2

.5 1

(1 .3

8 –4

.5 5

) 8

4 9

,9 1

8 1

.8 5

(1 .4

2 –2

.4 1

) 1

0 6

2 ,3

3 6

1 .5

4 (1

.2 9

–1 .8

4 )

2 6

,0 6

8 1

.6 9

(1 .3

7 –2

.0 8

) 3

1 2

,4 8

6 2

.4 3

(0 .7

7 –7

.6 8

)

o d ifi

e d

N C E P

d e fi n it io

n §

1 0

3 6

,4 6

2 2

.4 4

(2 .0

3 –2

.9 2

) 3

3 ,6

6 7

4 .2

8 (2

.2 5

–8 .1

4 )

5 1

2 ,9

7 2

1 .7

4 (1

.1 3

–2 .6

8 )

4 6

,1 4

9 2

.4 9

(1 .4

1 –4

.4 2

) 1

3 5

3 ,4

1 3

2 .0

3 (1

.6 4

–2 .5

0 )

C E P

d e fi n it io

n �

3 4

,6 3

3 1

.9 3

(1 .5

6 –2

.4 0

) 6

3 1

,5 9

2 2

.9 1

(1 .8

5 –4

.5 8

) 7

3 4

,1 0

3 1

.6 3

(1 .3

0 –2

.0 4

) 2

5 ,7

0 1

1 .9

7 (1

.4 9

–2 .6

1 )

8 2

5 ,8

2 3

2 .9

2 (1

.9 4

–4 .3

9 )

o d ifi

e d

rN C E P

d e fi n it io

n §

0 0

— 3

2 ,9

7 7

2 .3

7 (1

.6 6

–3 .3

8 )

2 2

,1 6

6 1

.3 2

(0 .7

4 –2

.3 5

) 0

0 —

0 0

—

e n ¶

5 7

,3 5

3 2

.1 4

(1 .6

2 –2

.8 3

) 7

3 0

,4 8

1 1

.9 4

(1 .2

0 –3

.1 4

) 7

3 3

,3 4

6 1

.4 2

(1 .1

6 –1

.7 4

) 2

4 ,5

3 1

2 .0

1 (1

.5 2

–2 .6

7 )

1 0

3 6

,9 8

5 2

.0 0

(1 .3

8 –2

.8 8

)

o m

e n ¶

7 3

2 ,2

5 8

2 .8

7 (2

.4 0

–3 .4

3 )

5 8

,1 8

5 2

.5 5

(1 .4

1 –4

.6 0

) 9

1 6

,1 7

9 1

.8 6

(1 .3

7 –2

.5 2

) 2

5 ,8

4 8

2 .5

7 (0

.8 7

–7 .5

7 )

1 3

5 1

,7 2

2 2

.5 9

(1 .9

4 –3

.4 6

)

ts w

it h o u t

T2 D

M ¶

1 1

,8 3

0 —

4 9

,8 2

4 1

.7 5

(1 .1

9 –2

.5 8

) 2

3 ,6

2 2

1 .3

2 (0

.6 5

–2 .6

7 )

3 7

,6 0

9 1

.6 2

(1 .3

1 –2

.0 1

) 2

1 5

,8 3

1 1

.8 6

(1 .1

0 –3

.1 7

)

R R

s p ro

vi d e d

a re

p o o le

d e st

im a te

s u si

n g

ra n d o m

-e ff

e ct

s m

o d e lin

g .†

Th e

n u m

b e r o f p o p u la

ti o n

a rm

s (P

o p

A rm

s) re

fe rs

to a ll

th e

d if fe

re n t p o p u la

ti o n

su b g ro

u p s

fo r w

h ic

h st

u d ie

s re

p o rt

e d

ri sk

e st

im a te

s. ‡

Th e

N C E P

d e fi n e s

th e

m e ta

b o lic

sy n d ro

m e

a s

h a vi

n g

3 o r m

o re

e fo

llo w

in g

5 ca

rd io

va sc

u la

r ri sk

fa ct

o rs

:1 ) ce

n tr

a lo

b e si

ty (w

a is

t ci

rc u m

fe re

n ce

:m e n

� 1

0 2

cm ;w

o m

e n

� 8

8 cm

); 2

) e le

va te

d tr

ig ly

ce ri d e s

(� 1

5 0

m g /d

l) ;3

) d im

in is

h e d

h ig

h -d

e n si

ty lip

o p ro

te in

(H D

L) ch

o le

st e ro

l( m

e n

� 4

0 m

g /d

l; w

o m

e n

� 5

0 m

g /d

l) ;4

) h yp

e rt

e n si

o n

3 0

/� 8

5 m

m H

g );

a n d

5 )

e le

va te

d fa

st in

g g lu

co se

(� 1

1 0

m g /d

l) . §

Th e

m o d ifi

e d

N C E P

a n d

m o d ifi

e d

re vi

se d

N C E P

d e fi n it io

n s

u se

m e a su

re m

e n ts

o f

B M

I (t

yp ic

a lly

B M

I �

3 0

k g /m

2 o r

B M

I �

2 7

k g /m

2 in

A si

a n

p o p u la

ti o n s)

to d e fi n e

ce n tr

a l o b e si

ty .

�T h e

re vi

se d

N C E P

n it io

n u se

s a

lo w

e r cu

to ff

fo r e le

va te

d fa

st in

g g lu

co se

o f

� 1

0 0

m g /d

l. ¶

W e

e va

lu a te

d th

e re

la ti ve

ri sk

o f C V D

,C V D

m o rt

a lit

y, a ll-

ca u se

m o rt

a lit

y, M

I, a n d

st ro

k e

in m

e n

w it h

th e

m e ta

b o lic

sy n d ro

m e ,w

o m

e n

w it h

th e

m e ta

b o lic

sy n d ro

m e ,a

n d

p a ti e n ts

w it h o u t ty

p e

2 d ia

b e te

s lit

u s,

b u t

w it h

th e

m e ta

b o lic

sy n d ro

m e .

� co

n fi d e n ce

in te

rv a l;

rN C E P

� re

vi se

d N

a ti o n a l C h o le

st e ro

l E d u ca

ti o n

P ro

g ra

m ; P

o p

� p o p u la

ti o n ; o th

e r

a b b re

vi a ti o n s

a s

in Ta

b le

1 .

1126 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

actors include polycystic ovary syndrome (21), hormonal ontraceptive use (22–24), and gestational diabetes (25).

Our results also suggest that the metabolic syndrome aintains its prognostic value for cardiovascular outcomes

n the absence of type 2 diabetes mellitus. Some experts have uggested that the reason the metabolic syndrome is asso- iated with an increase in cardiovascular risk is because most atients with the metabolic syndrome also have type 2 iabetes mellitus (8). However, after synthesizing the results f studies conducted in patients without type 2 diabetes ellitus, the metabolic syndrome remained associated with high cardiovascular risk, ranging from RR: 1.62 (95% CI: .31 to 2.01; I2 � 0%; 95% CI: 0% to 90%) for MI, to RR: .86 (95% CI: 1.10 to 3.17; I2 � 89; 95% CI: 56% to 97%) or stroke. The risk for all-cause mortality in patients ithout type 2 diabetes mellitus (RR: 1.32; 95% CI: 0.65 to .67; I2 � 87; 95% CI: 47% to 97%) was accompanied by a ide and therefore inconclusive confidence interval because

his analysis involved only 2 studies (n � 3,622 patients). ore studies are needed to confirm whether or not the etabolic syndrome is prognostic in this population. Our systematic review allowed us to identify an important

ap in the literature. The prognostic importance of the etabolic syndrome, compared with that of the sum of its

ndividual components (obesity, systemic hypertension, el- vated fasting glucose, elevated triglycerides, and low HDL holesterol), has repeatedly been challenged (8,26,27). In a ohort study of 2,815 patients, the risk of CVD mortality ssociated with the metabolic syndrome as defined by the CEP definition (HR: 2.53; 95% CI: 1.74 to 3.67) was

imilar to the risk associated with impaired fasting glucose HR: 2.87; 95% CI: 1.96 to 4.20) and systemic hypertension HR: 1.71; 95% CI: 1.15 to 2.54) (28). Furthermore, in a ystematic review of 7 clinical trials (n � 3,459), the etabolic syndrome as defined by the NCEP definition was

o longer an independent predictor of atherosclerotic plaque rogression after adjustment for its individual components 29). Despite these studies, there remains debate as to hether or not the metabolic syndrome provides a syner- istic effect that increases its association with cardiovascular isk. Of the 87 studies included in our systematic review, nly 5 reported risk estimates that were adjusted for at least component of the metabolic syndrome (Online Table 5). f these 5 studies, 3 adjusted for obesity, 3 adjusted for

ystemic hypertension, and 1 adjusted for fasting glucose. here is a need for prospective studies that investigate the

isk associated with the metabolic syndrome independent of he risk of its individual components in order to establish hether or not the metabolic syndrome adds any prognostic

ignificance. Our results allow us to confirm the strong association of

he 2001 NCEP definition of the metabolic syndrome with ardiovascular risk. Furthermore, to our knowledge, no revious meta-analyses have been conducted to establish the ardiovascular risk associated with the 2004 rNCEP defi-

nition. We recommend that health care workers use theSu m T A N M rN M M W P

* Th

e o f th

(� 1

d e fi

m e l C I

1127JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

Figure 4 The Metabolic Syndrome and the Relative Risk for CVD Mortality

I2 � 81%; 95% CI: 72% to 88%. Abbreviations as in Figure 2.

Figure 5 The Metabolic Syndrome and the Relative Risk for MI

I2 � 40%; 95% CI: 0% to 73%. Abbreviations as in Figure 2.

m p a t p b ( P c c ( a c i t n l l fi o

b e c f a f a p S p s t c p T o H o

1128 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

etabolic syndrome as a diagnostic tool for identifying atients who are at risk for cardiovascular events. There is n urgent need to develop and implement prevention and reatment strategies, such as lifestyle programs, diets, and harmacotherapies to reduce the prevalence of the meta- olic syndrome and its associated cardiovascular risk 30,31). revious studies. Two previous meta-analyses, which in- luded studies published prior to 2005, investigated the ardiovascular risk associated with the metabolic syndrome 9,10). An additional 71 studies investigating the NCEP nd rNCEP definitions have been published since the onduct of these meta-analyses, and these studies were ncluded in our meta-analysis (32). We also established he cardiovascular risk associated with the rNCEP defi- ition of the metabolic syndrome, which was only re-

eased in 2004 (7). Finally, we confirmed that there was ittle variation in cardiovascular risk between the modi- ed NCEP and rNCEP definitions compared with the

Figure 6 The Metabolic Syndrome and the Relative Risk for Str

I2 � 88%; 95% CI: 82% to 91%. Abbreviations as in Figures 2 and 3.

riginal NCEP definition. v

The 2 previous meta-analyses concluded that the meta- olic syndrome nearly doubled the risk of cardiovascular vents. We obtained consistently higher point estimates for ardiovascular outcomes (RR �2) and showed that the risk or CVD, CVD mortality, and stroke exceeds that of ll-cause mortality. However, there remains a need for uture studies to investigate the cardiovascular risk associ- ted with the metabolic syndrome after its individual com- onents have been adjusted for. tudy limitations. Our meta-analysis has a number of otential limitations. The inclusion of observational cohort tudies in our meta-analysis presented challenges beyond hose typically encountered in meta-analyses of randomized ontrolled trials. First, of the 87 studies included in our aper, only 34 studies reported count data that we pooled. he remaining 53 studies only reported risk estimates (RR r HR), which were not included in our pooled analyses. owever, we included these 53 studies in tables as part of

ur systematic review. Second, the length of follow-up

oke

aried considerably between studies. However, in a sensi-

t f t w g i t p u w c a s o a b a a d a m t s o p p b v c l a e p e o

T r i i m m o p d a d o s s s c m i

v m e

A T M

R D E M Q

1129JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

ivity analysis, we stratified studies by the length of ollow-up and found that studies with longer follow-up imes had risk estimates that were similar to those in studies ith shorter follow-up times. There was also some hetero- eneity in baseline patient characteristics, such as the nclusion of patients with atherosclerosis, systemic hyper- ension, or a history of CVD. Due to the presence of otential heterogeneity between studies, data were analyzed sing random-effects models, which incorporate both ithin- and between-study variability. In addition, we

onducted a sensitivity analysis in which we restricted our nalyses to studies of subjects without systemic hyperten- ion, atherosclerosis, or cardiovascular disease. The results f these analyses are consistent with those of our primary nalysis. A third potential limitation was the limited num- er of studies available to estimate the cardiovascular risk ssociated with the metabolic syndrome in our subgroup nalyses of men, women, and patients without type 2 iabetes mellitus. We could not conduct meta-regression nalyses to estimate the effect of these covariates on the etabolic syndrome– cardiovascular risk association since

he number of studies investigating these subgroups was mall. A fourth limitation includes the inherent assumptions f meta-analysis. We were limited to data reported in ublished articles and did not have access to individual atient-level data. Access to patient-level data would have een particularly helpful for our subgroup analyses. Fifth, isual assessment of funnel plots suggests that mild publi- ation bias may be present. Publication bias is an inherent imitation to virtually all meta-analyses. Finally, our meta- nalysis was limited to studies published in English. How- ver, �5% of studies identified in our literature search were ublished in a language other than English, and their xclusion is unlikely to substantially affect the conclusions of ur meta-analysis.

onclusions

he metabolic syndrome is associated with a 2-fold increase in isk for CVD, CVD mortality, MI, and stroke, and a 1.5-fold ncrease in risk for all-cause mortality. There is little variation n risk between the NCEP and rNCEP definitions of the

etabolic syndrome. There is also little variation in risk for the odified NCEP and rNCEP definitions compared with the

riginal NCEP definition. In addition, our results indicate that atients with the metabolic syndrome, but without type 2 iabetes mellitus, are still at high risk for CVD mortality, MI, nd stroke. We therefore suggest that the metabolic syndrome oes not require type 2 diabetes mellitus in its definition in rder to be closely associated with cardiovascular risk. Our ystematic review identified an important gap in the literature; tudies are needed to investigate whether or not the prognostic ignificance of the metabolic syndrome exceeds the risk asso- iated with the sum of its individual components. We recom- end that health care workers use the metabolic syndrome to

dentify patients who are at particularly high risk for cardio-

ascular complications. The prevention and reduction of the etabolic syndrome is essential to reduce cardiovascular dis-

ase and to extend life in the adult population.

cknowledgments he authors would like to thank Tara Dourian, Yevgeniya izina, and Susan Wakil for their help with data abstraction.

eprint requests and correspondence: Dr. Mark J. Eisenberg, epartment of Medicine, Divisions of Cardiology and Clinical pidemiology, Sir Mortimer B. Davis Jewish General Hospital, cGill University, 3755 Cote Ste Catherine, Suite H-421.1, Montreal, uebec H3T 1E2, Canada. E-mail: [email protected].

EFERENCES

1. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA 2002;287:356 –9.

2. Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 1988;37:1595– 607.

3. Executive Summary of The Third Report of The National Choles- terol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285:2486 –97.

4. International Diabetes Federation. The IDF Consensus Worldwide Definition of the Metabolic Syndrome. Brussels, Belgium: Interna- tional Diabetes Federation; 2006.

5. WHO Consultation. Definition, diagnosis and classification of dia- betes mellitus and its complications. Geneva, Switzerland: World Health Organization; 1999:31–3.

6. Moebus S, Hanisch J, Neuhäuser M, Aidelsburger P, Wasem J, Jöckel K. Assessing the prevalence of the Metabolic Syndrome according to NCEP ATP III in Germany: feasibility and quality aspects of a two step approach in 1550 randomly selected primary health care practices. Ger Med Sci 2006;4:Doc07.

7. 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. Circulation 2004;109:433– 8.

8. Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2005;28:2289 –304.

9. Gami AS, Witt BJ, Howard DE, et al. 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: 403–14.

10. Galassi A, Reynolds K, He J. Metabolic syndrome and risk of cardiovascular disease: a meta-analysis. Am J Med 2006;119:812–9.

11. Bax L, Yu LM, Ikeda N, Tsuruta H, Moons KG. Development and validation of MIX: comprehensive free software for meta-analysis of causal research data. BMC Med Res Methodol 2006;6:50.

12. Bax L, Yu LM, Ikeda N, Tsuruta H, Moons KG. MIX: compre- hensive free software for meta-analysis of causal research data [computer program]. Version 1.7. 2008.

13. Takahashi K, Bokura H, Kobayashi S, Iijima K, Nagai A, Yamaguchi S. Metabolic syndrome increases the risk of ischemic stroke in women. Intern Med 2007;46:643– 8.

14. Butler J, Rodondi N, Zhu Y, et al. Metabolic syndrome and the risk of cardiovascular disease in older adults. J Am Coll Cardiol 2006;47: 1595– 602.

15. Alberti KG, Eckel RH, Grundy SM, 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 Asso- ciation; World Heart Federation; International Atherosclerosis So-

ciety; and International Association for the Study of Obesity. Circu- lation 2009;120:1640 –5.

mailto:[email protected]

1130 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

16. Ferrannini E, Natali A, Bell P, Cavallo-Perin P, Lalic N, Mingrone G, European Group for the Study of Insulin Resistance (EGIR). Insulin resistance and hypersecretion in obesity. J Clin Invest 1997; 100:1166 –73.

17. Onat A, Can G, Hergenc G, Yazici M, Karabulut A, Albayrak S. Serum apolipoprotein B predicts dyslipidemia, metabolic syndrome and, in women, hypertension and diabetes, independent of markers of central obesity and inflammation. Int J Obes (Lond) 2007;31: 1119 –25.

18. Donato GB, Fuchs SC, Oppermann K, Bastos C, Spritzer PM. Association between menopause status and central adiposity mea- sured at different cutoffs of waist circumference and waist-to-hip ratio. Menopause 2006;13:280 –5.

19. Blake GJ, Otvos JD, Rifai N, Ridker PM. Low-density lipoprotein particle concentration and size as determined by nuclear magnetic resonance spectroscopy as predictors of cardiovascular disease in women. Circulation 2002;106:1930 –7.

20. Hokanson JE, Austin MA. Plasma triglyceride level is a risk factor for cardiovascular disease independent of high-density lipoprotein cho- lesterol level: a meta-analysis of population-based prospective studies. J Cardiovasc Risk 1996;3:213–9.

21. Legro RS. Polycystic ovary syndrome and cardiovascular disease: a premature association? Endocr Rev 2003;24:302–12.

22. Anderson GL, Limacher M, Assaf AR, et al. Effects of conjugated equine estrogen in postmenopausal women with hysterectomy: the Women’s Health Initiative randomized controlled trial. JAMA 2004; 291:1701–12.

23. Hsia J, Langer RD, Manson JE, et al. Conjugated equine estrogens and coronary heart disease: the Women’s Health Initiative. Arch Intern Med 2006;166:357– 65.

24. Manson JE, Hsia J, Johnson KC, et al. Estrogen plus progestin and the risk of coronary heart disease. N Engl J Med 2003;349:523–34.

25. Carr DB, Utzschneider KM, Hull RL, et al. Gestational diabetes mellitus increases the risk of cardiovascular disease in women with a family history of type 2 diabetes. Diabetes Care 2006;29:2078 – 83.

26. Grundy SM. Metabolic syndrome: a multiplex cardiovascular risk factor. J Clin Endocrinol Metab 2007;92:399 – 404.

27. Johnson LW, Weinstock RS. The metabolic syndrome: concepts and controversy. Mayo Clin Proc 2006;81:1615–20.

28. Hunt KJ, Resendez RG, Williams K, Haffner SM, Stern MP. National Cholesterol Education Program versus World Health Or- ganization metabolic syndrome in relation to all-cause and cardio- vascular mortality in the San Antonio Heart Study. Circulation 2004;110:1251–7.

29. Bayturan O, Tuzcu EM, Lavoie A, et al. The metabolic syndrome, its component risk factors, and progression of coronary atherosclerosis. Arch Intern Med 2010;170:478 – 84.

30. Poirier P, Despres JP. Waist circumference, visceral obesity, and cardiovascular risk. J Cardiopulm Rehabil 2003;23:161–9.

31. Drolet B, Simard C, Poirier P. Impact of weight-loss medications on the cardiovascular system: focus on current and future anti-obesity drugs. Am J Cardiovasc Drugs 2007;7:273– 88.

32. Shojania KG, Sampson M, Ansari MT, Ji J, Doucette S, Moher D. How quickly do systematic reviews go out of date? A survival analysis. Ann Intern Med 2007;147:224 –33.

33. Benetos A, Thomas F, Pannier B, Bean K, Jego B, Guize L. All-cause and cardiovascular mortality using the different definitions of metabolic syndrome. Am J Cardiol 2008;102:188 –91.

34. Dekker JM, Girman C, Rhodes T, et al. Metabolic syndrome and 10-year cardiovascular disease risk in the Hoorn Study. Circulation 2005;112:666 –73.

35. Guize L, Thomas F, Pannier B, Bean K, Jego B, Benetos A. All-cause mortality associated with specific combinations of the metabolic syndrome according to recent definitions. Diabetes Care 2007;30:2381–7.

36. Hillier TA, Rizzo JH, Pedula KL, et al. Increased mortality associ- ated with the metabolic syndrome in older women with diabetes. Diabetes Care 2005;28:2258 – 60.

37. Hong Y, Jin X, Mo J, et al. Metabolic syndrome, its preeminent clusters, incident coronary heart disease and all-cause mortality— results of prospective analysis for the Atherosclerosis Risk in Com-

munities study. J Intern Med 2007;262:113–22.

38. Katzmarzyk PT, Church TS, Janssen I, Ross R, Blair SN. Metabolic syndrome, obesity, and mortality: impact of cardiorespiratory fitness. Diabetes Care 2005;28:391–7.

39. Katzmarzyk PT, Janssen I, Ross R, Church TS, Blair SN. The importance of waist circumference in the definition of metabolic syndrome: prospective analyses of mortality in men. Diabetes Care 2006;29:404 –9.

40. Lakka HM, Laaksonen DE, Lakka TA, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle- aged men. JAMA 2002;288:2709 –16.

41. Langenberg C, Bergstrom J, Scheidt-Nave C, Pfeilschifter J, Barrett- Connor E. Cardiovascular death and the metabolic syndrome: role of adiposity-signaling hormones and inflammatory markers. Diabetes Care 2006;29:1363–9.

42. Mancia G, Bombelli M, Corrao G, et al. Metabolic syndrome in the Pressioni Arteriose Monitorate E Loro Associazioni (PAMELA) study: daily life blood pressure, cardiac damage, and prognosis. Hypertension 2007;49:40 –7.

43. Marroquin OC, Kip KE, Kelley DE, et al. Metabolic syndrome modifies the cardiovascular risk associated with angiographic coro- nary artery disease in women: a report from the Women’s Ischemia Syndrome Evaluation. Circulation 2004;109:714 –21.

44. Monami M, Lamanna C, Balzi D, et al. Metabolic syndrome and cardiovascular mortality in older type 2 diabetic patients: a longitu- dinal study. J Gerontol A Biol Sci Med Sci 2008;63:646 –9.

45. Pannier B, Thomas F, Bean K, Jego B, Benetos A, Guize L. The metabolic syndrome: similar deleterious impact on all-cause mortality in hypertensive and normotensive subjects. J Hypertens 2008;26: 1223– 8.

46. Ramkumar N, Murtaugh MA, Cheung AK, Beddhu S. Lack of synergistic effects of metabolic syndrome and plasma fibrinogen on coronary events and mortality in moderate CKD. Am J Kidney Dis 2007;49:356 – 64.

47. 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 – 82.

48. Takeno M, Yasuda S, Otsuka Y, et al. Impact of metabolic syndrome on the long-term survival of patients with acute myocardial infarc- tion: potential association with C-reactive protein. Circ J 2008;72: 415–9.

49. Wang J, Ruotsalainen S, Moilanen L, Lepisto P, Laakso M, Kuusisto J. The metabolic syndrome predicts cardiovascular mortality: a 13-year follow-up study in elderly non-diabetic Finns. Eur Heart J 2007;28:857– 64.

50. Wassink AM, van der Graaf Y, Olijhoek JK, Visseren FL. Metabolic syndrome and the risk of new vascular events and all-cause mortality in patients with coronary artery disease, cerebrovascular disease, peripheral arterial disease or abdominal aortic aneurysm. Eur Heart J 2008;29:213–23.

51. Zambon S, Zanoni S, Romanato G, et al. Metabolic syndrome and all-cause and cardiovascular mortality in an Italian elderly population: the Progetto Veneto Anziani Pro.V.A. Study. Diabetes Care 2009; 32:153–9.

52. Chen HH, Wu CJ, Chen YC, Tsai CS, Lin FJ, Yeh HI. Metabolic syndrome is associated with severe coronary artery disease and poor cardiac outcome in end-stage renal disease patients with acute coronary syndrome. Coron Artery Dis 2006;17:593– 6.

53. Feinberg MS, Schwartz R, Tanne D, et al. Impact of the metabolic syndrome on the clinical outcomes of non-clinically diagnosed diabetic patients with acute coronary syndrome. Am J Cardiol 2007;99:667–72.

54. Kasai T, Miyauchi K, Kurata T, et al. Prognostic value of the metabolic syndrome for long-term outcomes in patients undergoing percutaneous coronary intervention. Circ J 2006;70:1531–7.

55. Levantesi G, Macchia A, Marfisi R, et al. Metabolic syndrome and risk of cardiovascular events after myocardial infarction. J Am Coll Cardiol 2005;46:277– 83.

56. Malik S, Wong ND, Franklin SS, et al. Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults. Circulation 2004;110: 1245–50.

57. Nigam A, Bourassa MG, Fortier A, Guertin MC, Tardif JC. The

metabolic syndrome and its components and the long-term risk of

1131JACC Vol. 56, No. 14, 2010 Mottillo et al. September 28, 2010:1113–32 The Metabolic Syndrome and Cardiovascular Risk

death in patients with coronary heart disease. Am Heart J 2006;151: 514 –21.

58. Thomas GN, Schooling CM, McGhee SM, et al. Metabolic syn- drome increases all-cause and vascular mortality: the Hong Kong Cardiovascular Risk Factor Study. Clin Endocrinol (Oxf) 2007;66: 666 –71.

59. Davis TM, Bruce DG, Davis WA. Prevalence and prognostic implications of the metabolic syndrome in community-based patients with type 1 diabetes: the Fremantle Diabetes Study. Diabetes Res Clin Pract 2007;78:412–7.

60. Hildrum B, Mykletun A, Dahl AA, Midthjell K. Metabolic syn- drome and risk of mortality in middle-aged versus elderly individuals: the Nord-Trondelag Health Study (HUNT). Diabetologia 2009;52: 583–90.

61. Huang KC, Lee LT, Chen CY, Sung PK. All-cause and cardiovas- cular disease mortality increased with metabolic syndrome in Tai- wanese. Obesity (Silver Spring) 2008;16:684 –9.

62. Kajimoto K, Kasai T, Miyauchi K, et al. Metabolic syndrome predicts 10-year mortality in non-diabetic patients following coronary artery bypass surgery. Circ J 2008;72:1481– 6.

63. Lee J, Heng D, Ma S, Chew SK, Hughes K, Tai ES. The metabolic syndrome and mortality: the Singapore Cardiovascular Cohort Study. Clin Endocrinol (Oxf) 2008;69:225–30.

64. Lopes NH, Paulitsch FS, Pereira AC, et al. Impact of metabolic syndrome on the outcome of patients with stable coronary artery disease: 2-year follow-up of the MASS II study. Coron Artery Dis 2008;19:383– 8.

65. Mozaffarian D, Kamineni A, Prineas RJ, Siscovick DS. Metabolic syndrome and mortality in older adults: the Cardiovascular Health Study. Arch Intern Med 2008;168:969 –78.

66. Noto D, Barbagallo CM, Cefalu AB, et al. The metabolic syndrome predicts cardiovascular events in subjects with normal fasting glucose: results of a 15 years follow-up in a Mediterranean population. Atherosclerosis 2008;197:147–53.

67. Saito I, Iso H, Kokubo Y, Inoue M, Tsugane S. Metabolic syndrome and all-cause and cardiovascular disease mortality: Japan Public Health Center-based Prospective JPHC Study. Circ J 2009;73: 878 – 84.

68. Simons LA, Simons J, Friedlander Y, McCallum J. Does a diagnosis of the metabolic syndrome provide additional prediction of cardio- vascular disease and total mortality in the elderly? The Dubbo Study. Med J Aust 2007;186:400 –3.

69. Wen CJ, Lee YS, Lin WY, et al. The metabolic syndrome increases cardiovascular mortality in Taiwanese elderly. Eur J Clin Invest 2008;38:469 –75.

70. Hsu PF, Chuang SY, Cheng HM, Tsai ST, Chou P, Chen CH. Clinical significance of the metabolic syndrome in the absence of established hypertension and diabetes: a community-based study. Diabetes Res Clin Pract 2008;79:461–7.

71. Kasai T, Miyauchi K, Kurata T, et al. Impact of metabolic syndrome among patients with and without diabetes mellitus on long-term outcomes after percutaneous coronary intervention. Hypertens Res 2008;31:235– 41.

72. Niwa Y, Ishikawa S, Gotoh T, Kayaba K, Nakamura Y, Kajii E. Metabolic syndrome mortality in a population-based cohort study: Jichi Medical School (JMS) Cohort Study. J Epidemiol 2007;17: 203–9.

73. Tanomsup S, Aekplakorn W, Sritara P, et al. A comparison of components of two definitions of the metabolic syndrome related to cardiovascular disease and all-cause mortality in a cohort study in Thailand. Diabetes Care 2007;30:2138 – 40.

74. Andreadis EA, Tsourous GI, Tzavara CK, et al. Metabolic syndrome and incident cardiovascular morbidity and mortality in a Mediterra- nean hypertensive population. Am J Hypertens 2007;20:558 – 64.

75. 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;49:2112–9.

76. Resnick HE, Jones K, Ruotolo G, et al. Insulin resistance, the metabolic syndrome, and risk of incident cardiovascular disease in nondiabetic american indians: the Strong Heart Study. Diabetes Care

2003;26:861–7.

77. Sattar N, McConnachie A, Shaper AG, et al. Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Out- come data from two prospective studies. Lancet 2008;371:1927–35.

78. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation 2005;112:3066 –72.

79. Guzder RN, Gatling W, Mullee MA, Byrne CD. Impact of metabolic syndrome criteria on cardiovascular disease risk in people with newly diagnosed type 2 diabetes. Diabetologia 2006;49:49 –55.

80. Hwang YC, Jee JH, Oh EY, et al. Metabolic syndrome as a predictor of cardiovascular diseases and type 2 diabetes in Koreans. Int J Cardiol 2009;134:313–21.

81. Kokubo Y, Okamura T, Yoshimasa Y, et al. Impact of metabolic syndrome components on the incidence of cardiovascular disease in a general urban Japanese population: the Suita study. Hypertens Res 2008;31:2027–35.

82. Ninomiya T, Kubo M, Doi Y, et al. Impact of metabolic syndrome on the development of cardiovascular disease in a general Japanese population: the Hisayama study. Stroke 2007;38:2063–9.

83. Schillaci G, Pirro M, Vaudo G, et al. Prognostic value of the metabolic syndrome in essential hypertension. J Am Coll Cardiol 2004;43:1817–22.

84. Song Y, Manson JE, Meigs JB, Ridker PM, Buring JE, Liu S. Comparison of usefulness of body mass index versus metabolic risk factors in predicting 10-year risk of cardiovascular events in women. Am J Cardiol 2007;100:1654 – 8.

85. Takeuchi H, Saitoh S, Takagi S, et al. Metabolic syndrome and cardiac disease in Japanese men: applicability of the concept of metabolic syndrome defined by the National Cholesterol Education Program-Adult Treatment Panel III to Japanese men—the Tanno and Sobetsu Study. Hypertens Res 2005;28:203– 8.

86. Worm SW, De Wit S, Weber R, et al. Diabetes mellitus, preexisting coronary heart disease, and the risk of subsequent coronary heart disease events in patients infected with human immunodeficiency virus: the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D Study). Circulation 2009;119:805–11.

87. Ingelsson E, Sullivan LM, Murabito JM, et al. Prevalence and prognostic impact of subclinical cardiovascular disease in individ- uals with the metabolic syndrome and diabetes. Diabetes 2007; 56:1718 –26.

88. Liu J, Grundy SM, Wang W, et al. Ten-year risk of cardiovascular incidence related to diabetes, prediabetes, and the metabolic syn- drome. Am Heart J 2007;153:552– 8.

89. Meigs JB, Rutter MK, Sullivan LM, Fox CS, D’Agostino RB Sr., Wilson PW. Impact of insulin resistance on risk of type 2 diabetes and cardiovascular disease in people with metabolic syndrome. Diabetes Care 2007;30:1219 –25.

90. Vaccarino V, McClure C, Johnson BD, et al. Depression, the metabolic syndrome and cardiovascular risk. Psychosom Med 2008; 70:40 – 8.

91. Wand H, Calmy A, Carey DL, et al. Metabolic syndrome, cardio- vascular disease and type 2 diabetes mellitus after initiation of antiretroviral therapy in HIV infection. AIDS 2007;21:2445–53.

92. Does diagnosis of the metabolic syndrome detect further men at high risk of cardiovascular death beyond those identified by a conventional cardiovascular risk score? The DECODE study. Eur J Cardiovasc Prev Rehabil 2007;14:192–9.

93. Maggi S, Noale M, Gallina P, et al. Metabolic syndrome, diabetes, and cardiovascular disease in an elderly Caucasian cohort: the Italian Longitudinal Study on Aging. J Gerontol A Biol Sci Med Sci 2006;61:505–10.

94. Solymoss BC, Bourassa MG, Marcil M, Levesque S, Varga S, Campeau L. Long-term rates of cardiovascular events in patients with the metabolic syndrome according to severity of coronary- angiographic alterations. Coron Artery Dis 2009;20:1– 8.

95. de Simone G, Olsen MH, Wachtell K, et al. Clusters of metabolic risk factors predict cardiovascular events in hypertension with target- organ damage: the LIFE study. J Hum Hypertens 2007;21:625–32.

96. Nakatani D, Sakata Y, Sato H, et al. Clinical impact of metabolic syndrome and its additive effect with smoking on subsequent cardiac events after acute myocardial infarction. Am J Cardiol 2007;99: 885–9.

97. Hunt KJ, Williams K, Hazuda HP, Stern MP, Haffner SM. The

metabolic syndrome and the impact of diabetes on coronary heart

K y P

1132 Mottillo et al. JACC Vol. 56, No. 14, 2010 The Metabolic Syndrome and Cardiovascular Risk September 28, 2010:1113–32

disease mortality in women and men: the San Antonio Heart Study. Ann Epidemiol 2007;17:870 –7.

98. Espinola-Klein C, Rupprecht HJ, Bickel C, et al. Impact of meta- bolic syndrome on atherosclerotic burden and cardiovascular progno- sis. Am J Cardiol 2007;99:1623– 8.

99. Girman CJ, Rhodes T, Mercuri M, et al. The metabolic syndrome and risk of major coronary events in the Scandinavian Simvastatin Survival Study (4S) and the Air Force/Texas Coronary Atheroscle- rosis Prevention Study (AFCAPS/TexCAPS). Am J Cardiol 2004; 93:136 – 41.

00. Holvoet P, Kritchevsky SB, Tracy RP, et al. The metabolic syn- drome, circulating oxidized LDL, and risk of myocardial infarction in well-functioning elderly people in the health, aging, and body composition cohort. Diabetes 2004;53:1068 –73.

01. Thorn LM, Forsblom C, Waden J, et al. Metabolic syndrome as a risk factor for cardiovascular disease, mortality, and progression of diabetic nephropathy in type 1 diabetes. Diabetes Care 2009;32: 950 –2.

02. 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 –72.

03. Boden-Albala B, Sacco RL, Lee HS, et al. Metabolic syndrome and ischemic stroke risk: Northern Manhattan Study. Stroke 2008;39: 30 –5.

04. Hsia J, Bittner V, Tripputi M, Howard BV. Metabolic syndrome and coronary angiographic disease progression: the Women’s Angio- graphic Vitamin & Estrogen trial. Am Heart J 2003;146:439 – 45.

05. McNeill AM, Rosamond WD, Girman CJ, et al. The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 2005;28: 385–90.

06. Qiao Q, Laatikainen T, Zethelius B, et al. Comparison of definitions of metabolic syndrome in relation to the risk of developing stroke and coronary heart disease in Finnish and Swedish cohorts. Stroke 2009;40:337– 43.

07. Vlek AL, van der Graaf Y, Spiering W, Visseren FL. Effect of metabolic syndrome or type II diabetes mellitus on the occurrence of recurrent vascular events in hypertensive patients. J Hum Hypertens

2008;22:358 – 65. F

08. 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 – 83.

09. Chen HJ, Bai CH, Yeh WT, Chiu HC, Pan WH. Influence of metabolic syndrome and general obesity on the risk of ischemic stroke. Stroke 2006;37:1060 – 4.

10. 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 –21.

11. Iso H, Sato S, Kitamura A, et al. Metabolic syndrome and the risk of ischemic heart disease and stroke among Japanese men and women. Stroke 2007;38:1744 –51.

12. Koren-Morag N, Goldbourt U, Tanne D. Relation between the metabolic syndrome and ischemic stroke or transient ischemic attack: a prospective cohort study in patients with atherosclerotic cardiovas- cular disease. Stroke 2005;36:1366 –71.

13. Kurl S, Laukkanen JA, Niskanen L, et al. Metabolic syndrome and the risk of stroke in middle-aged men. Stroke 2006;37:806 –11.

14. Wannamethee SG, Shaper AG, Lennon L, Morris RW. Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Arch Intern Med 2005;165:2644 –50.

15. Rodriguez-Colon SM, Mo J, Duan Y, et al. Metabolic syndrome clusters and the risk of incident stroke: the atherosclerosis risk in communities (ARIC) study. Stroke 2009;40:200 –5.

16. Wild SH, Byrne CD, Tzoulaki I, et al. Metabolic syndrome, haemostatic and inflammatory markers, cerebrovascular and periph- eral arterial disease: the Edinburgh Artery Study. Atherosclerosis 2009;203:604 –9.

ey Words: cardiovascular disease y cardiovascular risk y meta-analysis metabolic syndrome y mortality y National Cholesterol Education

rogram.

APPENDIX

or supplementary tables, please see the online version of this article.

The Metabolic Syndrome and Cardiovascular Risk

Methods

Data sources and searches
Study selection
Data extraction
Data synthesis and analysis

Results

Search results and study inclusion
The metabolic syndrome and cardiovascular risk
Sensitivity analyses

Discussion

Previous studies
Study limitations

Conclusions
Acknowledgments
REFERENCES
APPENDIX