The metabolic syndrome: prevalence in worldwide populations

Endocrinol Metab Clin N Am

33 (2004) 351–375

The metabolic syndrome: prevalence inworldwide populations

Adrian J. Cameron, MPH,Jonathan E. Shaw, MD, MRCP(UK), FRACP,

Paul Z. Zimmet, AO, MD, PhD, FRACP,FRCP, FACE, FAFPHM*

International Diabetes Institute, 250 Kooyong Road, Caulfield South 3162, Australia

The concept of the metabolic syndrome has now been in existence forseveral decades; however, it has only been since some agreement on definitionsof the syndrome was reached that it has been possible to compare theprevalence among populations worldwide. Just as the prevalence of theindividual components of the syndrome varies among populations, so doesthe prevalence of the metabolic syndrome itself. Differences in geneticbackground, diet, levels of physical activity, population age and sex structure,levels of over- and undernutrition, and body habitus all influence theprevalence of both themetabolic syndrome and its components. Regardless ofthe underlying genetic and environmental influences that mediate theprevalence of the metabolic syndrome, a higher prevalence will undoubtedlylead to undesirable outcomes such as cardiovascular disease.

Until the first broadly applicable definition of the metabolic syndrome wasproposed by the World Health Organization (WHO) in 1998 [1] and finalizedin 1999 [2], the definition varied from one study to the next. Just as theprevalence of component conditions such as obesity, hypertension, hypergly-cemia, and dyslipidemia is critically dependent on the definition, so is theprevalence of the syndrome as a whole. The measurement technique anddefinition of obesity used is particularly contentious given that alternativeobesity criteria for different populations have been proposed [3,4]. Thequestion of why a particular cut-point should be chosen is beyond the scope ofthis article but is critically relevant to prevalence statistics.Whether or not cut-points should be related to their relationships with a particular adverse

* Corresponding author.

E-mail address: [email protected] (P.Z. Zimmet).

0889-8529/04/$ - see front matter � 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.ecl.2004.03.005

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352 A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375

outcome, what particular health outcomes they should be related to, whetheror not the percentile of the population affected is important, whether or notthere are differences in the relationship between a cut-point and adverseoutcomes, and how often it is desirable to change diagnostic criteria are allimportant questions when deciding on a cut-point. Given the number ofcompeting priorities, it is not surprising that diagnostic criteria and cut-pointsare often chosen somewhat arbitrarily.

The definition of the metabolic syndrome, relying on individual cut-pointsfor up to five different abnormalities, is a greater challenge still. Althougha definition of the syndromemay be difficult to agree upon, it is important thatsuch a definition exists and is applied so that comparisons betweenpopulations of the prevalence of the syndrome and its relationship withvarious health outcomes can be made. A uniform definition would be ideal,but three definitions of the metabolic syndrome are currently in common use.Before presenting the figures for the prevalence of the metabolic syndromeworldwide, it is necessary to first describe the definitions used.

Definitions of the metabolic syndrome

Themetabolic syndrome is a clustering ofmetabolic abnormalities that hasbeen found to be associated with a risk of coronary heart disease, stroke, andcardiovascular mortality greater than that of its individual components [5].The syndrome itself has had a variety of names, such as the insulin resistancesyndrome, deadly quartet, syndrome X, syndrome X plus, among others. Theability to compare the prevalence of the metabolic syndrome both amongpopulations and over time, as well as the ability to identify the syndrome forprevention and treatment purposes, are twoobvious reasons that considerableimportance is placed on establishing a clear and unified definition. Whendebating the merits of a given definition, elements that require considerationinclude which components are to be included, what measures are used todefine those components selected, and what cut-points should be used for themeasures selected. Consideration needs to be given to the usefulness ofa definition of the metabolic syndrome in clinical practice, research, or both.

Before the initial publication of the WHO definition of the metabolicsyndrome in 1998, those describing the prevalence of the metabolic syndromeused their own definitions and measures of a component and their ownnumber and composition of the various components used to define thesyndrome.

The three most widely recognized recent attempts to define the metabolicsyndrome include the WHO report from 1999 [2], the European Group forthe Study of Insulin Resistance (EGIR), also in 1999 [6], and the definitionof the National Cholesterol Education Program Expert Panel on Detection,Evaluation, and Treatment of High Blood Cholesterol in Adults—otherwiseknown as the Adult Treatment Panel III (ATPIII)—in 2001 [7]. The original

353A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375

WHO recommendations were not designed to be an exact definition; rather,they were formulated as a working guideline, to be improved upon in thefuture, that would enable comparability between studies.

Following the publication of the WHO definition of the metabolicsyndrome in 1999, the EGIR proposed a modified version to be used innondiabetic subjects only, that would be simpler to use in epidemiologicstudies since it did not require a euglycemic clamp to measure insulinresistance, and with slightly modified cut-points for hypertension, triglycer-ides, high-density lipoprotein (HDL) cholesterol, and altered measures andcut-points for obesity [6]. The EGIR suggested that because the proposedWHO definition of the syndrome includes nonmetabolic features, a moreappropriate name would be the insulin resistance syndrome. Their newlyproposed definition focused more on the inclusion of insulin resistance as thecentral element, arguing that no evidence to the contrary had as yet beenpresented. To this end, they included the measurement of insulin resistance asthe key feature, without the requirement for a euglycemic clampmeasurementthatwas stipulated in the originalWHOdefinition. The requirement for one ofdiabetes or impaired glucose regulation (impaired glucose tolerance orimpaired fasting glycemia) as specified in theWHO definition was removed inthe EGIR proposal. Indeed, the EGIR definition was restricted to individualswho do not have diabetes because there is no simple way of measuring insulinresistance in individuals who have diabetes. Insulin resistance in the EGIRproposal was defined as the highest quartile of fasting insulin measurementswithin the relevant nondiabetic population (a universal cut-off point forinsulin measurement being impossible because of the different standards forassaying insulin). Insulin resistance has been suggested as a single and unit-ing cause for all of the components of the syndrome, and some studieshave implicated it in this role; however, this has not been confirmed in otherreports [8].

The ATPIII definition of the metabolic syndrome presented in 2001 wasdesigned to be more amenable to measurement in clinical practice. Themanagement of the metabolic syndrome according to ATPIII had a twofoldobjective: (1) to reduce the underlying causes (ie, obesity and physicalinactivity) and (2) to treat associated nonlipid and lipid risk factors.Reflecting the more clinical objectives of the ATPIII definition (to facilitatediagnosis and preventive interventions), no measurement of insulinresistance was included. The WHO, EGIR, and ATPIII definitions aresummarized in Box 1.

More recently, theAmericanCollege of Endocrinology (ACE) has releaseda position statement on what it refers to as the insulin resistance syndrome [9].In this document, a list of four factors described as ‘‘identifying abnormal-ities’’ of the syndrome are listed, including elevated triglycerides, reducedHDL cholesterol, elevated blood pressure, and elevated fasting and postloadglucose (Box 2). Obesity, together with the diagnosis of hypertension,gestational diabetes or cardiovascular disease (CVD), family history of


diabetes, hypertension or CVD, non-European ancestry, age greater than 40years, and a sedentary lifestyle are listed as factors that increase the likelihoodof the syndrome; however, these factors are not classified as identifyingelements themselves (with the exception of hypertension, which is included inboth lists).

Box 1. WHO, EGIR, and ATPIII definitions of the metabolicsyndrome

WHO 1999Diabetes or impaired fasting glycaemia or impaired glucose

tolerance or insulin resistance (under hyperinsulinemic andeuglycemic conditions, glucose uptake in lowest 25%) plus twoor more of the following:1. Obesity: body mass index >30 kg/m2 or waist:hip ratio

(WHR) >0.9 (male) or >0.85 (female)2. Dyslipidemia: triglycerides P 1.7 mmol/L or HDL

cholesterol <0.9 (male) or <1.0 (female) mmol/L3. Hypertension: blood pressure P 140/90 mm Hg4. Microalbuminuria: albumin excretion P 20 lg/min

EGIR 1999Insulin resistance (defined as hyperinsulinemia, top 25% of

fasting insulin values among the nondiabetic population)plus two or more of the following:1. Central obesity: waist circumference P 94 cm (male)

or P 80 cm (female)2. Dyslipidemia: triglycerides >2.0 mmol/L or

HDL cholesterol <1.03. Hypertension: blood pressure P 140/90 mm Hg

and/or medication4. Fasting plasma glucose P 6.1 mmol/L

ATPIII 2001Three or more of the following:

1. Central obesity: waist circumference >102 cm (male)or >88 cm (female)

2. Hypertriglyceridemia: triglycerides P 1.7 mmol/L3. Low HDL cholesterol: <1.0 mmol/L (male) or

<1.3 mmol/L (female)4. Hypertension: blood pressure P 135/85 mm Hg

or medication5. Fasting plasma glucose P 6.1 mmol/L


The list of four identifying abnormalities is described as a simple meansof identifying individuals who are likely to be insulin-resistant. Theseabnormalities are portrayed as not only the components of the insulinresistance syndrome but as a useful test for identifying individuals who havea greater probability of being insulin-resistant. The higher the number ofabnormalities in an individual and the more severe the magnitude of eachabnormality, the more likely an individual is insulin-resistant/hyperinsulin-emic. Each of the abnormalities is known to predict the development ofCVD or type 2 diabetes. The most obvious difference between this list ofabnormalities and the definitions of the metabolic syndrome describedearlier is the absence of obesity as a component of the syndrome in the ACEposition statement. Furthermore, hyperinsulinemia is excluded from thisdefinition, which is in line with the ATPIII definition but not the WHO orEGIR definitions.

Apart from the reality that measurement of plasma insulin values is notroutinely conducted in clinical practice, the arguments identified in the ACEposition statement for the exclusion of insulin values as a diagnostic toolinclude (1) the unstandardized nature of the insulin assay itself, makinginterlaboratory comparison difficult, and (2) the lack of evidence that anincrease in plasma insulin concentration by itself, in the absence of the otheridentifying abnormalities of the metabolic syndrome, can predict thedevelopment of CVD.

The proposed justification for the absence of obesity as a component ofthe ACE’s definition of insulin resistance syndrome is that obesity is ‘‘nota consequence of insulin resistance/hyperinsulinemia, but a physiologicalvariable that decreases insulin-medicated glucose disposal’’ [9]. Althoughemphasizing the role that the current obesity epidemic is playing in theincrease in incidence of both type 2 diabetes and the insulin resistance

Box 2. Identifying abnormalities of the insulin resistancesyndrome among individuals without type 2 diabetes

Triglycerides: >150 mg/dLHDL cholesterol

� Men: <40 mg/dL� Women: <50 mg/dL

Blood pressure: >130/85 mm HgGlucose

� Fasting: 110–125 mg/dL� 2-hour postglucose challenge: 140–200 mg/dL

Data from American College of Endocrinology Task Force on the InsulinResistance Syndrome. American College of Endocrinology Position Statement onthe Insulin Resistance Syndrome. Endocr Pract 2002;9:236–52.


syndrome, the ACE sees obesity as a contributory factor in the developmentof insulin resistance/hyperinsulinemia, rather than as a consequence ofabnormal insulin metabolism.

A thorough literature search for publications documenting the prevalenceof the metabolic syndrome according to any of the WHO, ATPIII, or EGIRcriteria was conducted. The prevalence of the metabolic syndrome inpopulations worldwide as reported in these studies can be found in Table 1.

Discussion

Despite attempts in recent years to reach an agreement on the definitionof the metabolic syndrome, it remains difficult to compare the prevalencespublished for different populations. The studies often differ with respect tostudy design, sample selection, the year that a study was conducted, theprecise definition of the metabolic syndrome used, and the age and sexstructure of the population itself. Despite these obstacles, it is still possibleto make some interesting inferences based on the information presented inTables 2–4.

Table 2, reporting the prevalence of the ATPIII definition of the metabolicsyndrome among various populations around the world, shows that even forthose studies involving participants within the same age range there is a widevariation in prevalence apparent in both men and women. Looking at thosestudies that include a population sample aged from 20 to 25 and upward, theprevalence varies from 8% (India) to 24% (United States) in men and from7% (France) to 46% (India) in women. Of particular interest are the twoIndian studies, which differed in their definition of obesity; one study [12] usedobesity criteria that were suitable for Indians, while the other [10] used thestandard ATPIII definition of obesity. Both studies used population-basedsamples within the same age range but reported prevalences of 13% in Jaipur[10] and 41% in Chennai [12]. The logical conclusion would be that much ofthe difference between these two studies is a result of the differing obesitycriteria. However, in reality the prevalence of obesity in the two study groupswas quite similar (31% versus 33%), despite the different definitions. Farlarger differences were observed between the two studies for the prevalence ofelevated triglycerides (46%versus 30%), hypertension (55%versus 39%), andelevated fasting plasma glucose (27% versus 5%), each of which was reportedas having used the same cut-points (those specified in the ATPIII criteria).Interestingly, a third Indian study [11], also from Chennai, reporteda metabolic syndrome prevalence of 11.2% (using EGIR criteria), whichwas much closer to the prevalence reported for Jaipur than the other Chennaistudy. Therefore, evenwithin the same ethnic population group it appears thatthere can be significant differences in the prevalence of both the individualfactors that constitute the metabolic syndrome and the metabolic syndromeitself.


The majority of the other studies that provided a prevalence of theATPIII definition of the metabolic syndrome are from populations ofpersons of European ancestry, with the exception of Mauritius, whichincludes three ethnic groups (Asian, Indian, Creole). The low prevalenceamong both men (11%) and women (15%) in this group cannot be attributedto the use of inappropriate obesity criteria, because the waist circumferencecut-points used were modified to those appropriate for an Asian population.

Even with obesity criteria adapted to those appropriate for an Asianpopulation, the prevalence of obesity in Mauritius is lower than in both theUnited States (38.6%) and Omani (24.6%) populations, both of which usedthe original ATPIII obesity criteria [15,38]. In each of the United States,Omani, and Mauritius populations, the prevalence of obesity is higheramong women, although the difference between the sexes is most striking inthe Oman and Mauritius studies (Oman: men = 4.7%, women = 44.3%;Mauritius: men = 8.6%, women = 27.8%). The prevalence of each of theother abnormalities in Mauritius (hypertension, 31.8%; elevated triglycer-ides, 25.9%; low HDL, 38.6%; elevated fasting glucose, 8.3%) was generallysomewhat lower than that observed in the three United States studies[38,39]. Therefore, the low prevalence in Mauritius appears to be the resultof a combination of lower prevalence of several of the components, ratherthan one particular component being less common.

An interesting demonstration of the effect of ethnicity on the metabolicsyndrome is a comparison of the prevalence of the metabolic syndrome asdefined by the ATPIII criteria among Finnish and Native American men[16,37]. Both studies involved subjects with comparable age ranges (42–60and 45–49, respectively), with the Finnish study showing a prevalence ofonly 14% compared with the prevalence in the Native American study of43.6%. Unfortunately, the prevalence of the individual components of themetabolic syndrome is not reported for the Native American study, soa clear idea of how the prevalence of the components differs between the twopopulations cannot be made. When looking at the data for both men andwomen in the 14 studies in Table 2, neither sex appears to have a clearlyhigher prevalence of the metabolic syndrome using the ATPIII definition.

The majority of the reports of the prevalence of the EGIR definition ofthe metabolic syndrome (Table 3) are taken from a comparative study ofEuropean populations undertaken by the EGIR themselves [27]. The mostnotable differences between the prevalence of the metabolic syndrome asdefined by the ATPIII and the EGIR definitions are that (1) among bothmen and women the prevalence is considerably lower using the EGIRdefinition and (2) the prevalence is consistently higher in men than womenusing the EGIR definition whereas no particular gender-specific trend wasobserved for the ATPIII definition. The only exception to the trend of malepredominance is in Mauritius [23], where the metabolic syndromeprevalence as defined by the EGIR definition is similar for men and women(9.0% and 10.2%, respectively).

Table 1

Prevalence of th

City,

country Ye

Prevalence

(%) (95% CI) Reference

Jaipur,

India

200 s

F)

Total = 12.8

(10.8–14.8)

M= 7.9

(6.7–9.1)

F = 17.5

(14.4–20.6)

Gupta

et al [10]

Chennai,

India

200 s

479;

e

783

and

e

e

ectively

n the

uals

F)

te

esponse

Total = 11.2

(9.4–13.3)

Middle-income

= 18.7 (15.1–22.9)

Lower-income

= 6.5 (4.8–8.7)

M= 12.9

F = 9.9

Deepa

et al [11]

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e metabolic syndrome in worldwide populations

ar

Definition of metabolic

syndrome Survey population

Age group, N,

response rate

3a ATPIII Randomly selected

population sample of

six clusters in the city

of Jaipur

Age: >20 year

N = 1091

(532 M, 559

Response rate:

60.6%

2a EGIR, but with obesity

defined as waisthip

ratio >0.9 (men) or

>0.85 (women) and

dyslipidemia defined

as total serum cholesterol

>5.2 mmol/L and/or

triglycerides >2.26 and/or

HDL\0.91

Urban; randomly

selected from

middle- and

lower-income areas

of Chennai

Age:>20 year

Lower-income

group, N =

middle-incom

group, N =

Response rates

were 91.4%

89.4% for th

middle- and

lower-incom

groups, resp

Final analysis

was based o

1070 individ

(464 M, 606

with comple

data (final r

rate: 76.5%)

Chennai,

India

1995 ATPIII, but with a modified

waist circumference

Randomly selected

cluster sample from

Age: 20–75 years

N = 475 (258

Total = 41.1

M= 36.4

F = 46.5

Ramachandran

et al [12]

T Unadjusted = 30.1

(29.2–31.0)

Age standardized

to SEGI world

population = 33.7

(32.8–34.6)

M= 42

F = 24

Azizi et al [13]

M s WHO= 13.6

ATPIII = 26.6

(age adjusted)

Aguilar-Salinas

et al [14]

N Total

age (standardized)

= 21

(crude = 17)

M age (standardized)

= 19.5

F age (standardized)

= 23.0

Al-Lawati

et al [15]

K

d

Total for EGIR

definition with

obesity defined

using WHR> 0.90

= 24.9

Laaksonen

et al [16]

(continued on next page)

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appropriate for Indians

(90 cm for males, 85 cm

for females)

Madras without

known diabetes

M, 217 F)

Response rate

not reported

ehran,

Islamic

Republic

of Iran

1999

–2001

ATPIII Randomly selected Age: >20 years

N = 9846

Response rate

unknown

exican

National

Study

1992–

1993

WHO and ATPIII Randomly selected

neighborhood blocks

in 417 cities using a

multistage sampling

procedure

Age: 20–69 year

N = 2158

Response

rate: 83%

izwa,

Oman

2001 ATPIII Randomly selected

cluster sampling, using

16 census enumeration

areas, of all Omanis in

the city of Nizwa who

were residents for more

than 6 months prior to

the survey date

Age: 20 years

N = 1419 (695

M, 724 F)

Response rate:

75.5%.

uopio,

Finland

1988–

1989

Four definitions of the metabolic

syndrome were used:

1. EGIR definition, but

with obesity defined using

the original WHO definition

(WHR > 0.90 or body

mass index of 30 kg/m2)

Randomly selected male

population stratified by

age (selected men were

42, 48, 54, or 60 years

old at recruitment)

living in eastern

Finland

Age: 42, 48, 54,

or 60 years ol

N = 1005

Response rate

not reported

Table 1 (continued

City,

country Yea

p, N,

rate

Prevalence


Total for EGIR

definition with

obesity defined

using waist

circumference of

94 cm = 21.1

Total for ATPIII

definition with

waist

circumference

of 102 cm = 13.7

Total for ATPIII

definition with

waist

circumference

of 94 cm = 20.5

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)

r



Age grou

response

2. EGIR definition with

obesity defined as waist

circumference of 94 cm

3. ATPIII definition with

the original definition of

obesity (waist circumference

of 102 cm)

4. ATPIII definition with an

altered definition of obesity

(waist circumference of 94 cm)

Despite the stipulation that

the EGIR definition should

only be applied to

non-diabetic subjects,

individuals with diabetes

were included in this study;

also, for the two definitions

of the metabolic syndrome

based on the EGIR definition,

the cut-point for triglycerides

was taken from the original

WHO definition (1.7 mmol/L)

rather than the EGIR

adaptation (2.0 mmol/L)

Tampere and

Pleksamaki,

ce

F

1993–1994 Three different definitions of

the metabolic syndrome

Randomly selected

through a city health

Tampere

Age: 40 or 45 years

103 M, 104 F

se rate: 80%

aki

6, 41, 46,

years

570 M, 578 F

Tampere

Definition 1:

M ¼ 16, F ¼ 12

Definition 2: 22

Pleksamaki

Definition 1:

M= 17, F = 8

Definition 2:

M= approximately

29, F = 19

Definition 3: M

= approximately

4, F = 2

Vanhala

et al [17]


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ntral

inland

were used:

1. Hypertriglyceridemia and/or

low HDL cholesterol as well as

insulin resistance (impaired

glucose tolerance, diabetes and/

or hyperinsulinemia defined as

fasting plasma insulin

13.0 mU/L)

2. Three or more of: (a) at least

one first-degree relative with

type 2 diabetes, obesity (body

mass index of 30 kg/m2), (b)

central obesity (WHR of 1.0 in

men and 0.88 in women), (c)

hypertension (diastolic blood

pressure of 95 mm Hg, systolic

blood pressure 160 mm Hg), (d)

triglyceride 1.7 mmol/L, (e)

HDL cholesterol\1.0 in men

and\1.2 in women, (f)

abnormal glucose metabolism

(impaired glucose tolerance or

diabetes), and (g)

hyperinsulinemia (defined as

fasting plasma insulin of

13.0 mU/L)

3. Hypertension, dyslipidemia,

and insulin resistance

(all as defined above)

survey in Tampere

(pregnant women and

foreigners were

excluded)

N ¼Respon

Pleksam

Age: 2

or 51

N =

Table 1 (continued)

City,

country Year

p, N,

rate

Prevalence


San Diego,

United States

(Filipina-

American

study)

1992–

199

9

ean

ups for

pina and

ian groups

.7 and 60.0

espectively)

(Filipina

) and 379

sian women)

Filipina women

= 34.3

Caucasian women

= 12.9

Araneta

et al [18]

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Age grou

response

9

ATPIII Women aged\70 years.

A group of community

dwelling self-defined

Filipina women were

recruited between 1995

and 1999 using

community groups,

advertising, and so

forth (ie, a nonrandom

sample). A comparison

group of non-Hispanic

Caucasian women were

recruited between

1992 and 1995 as part

of the Rancho

Bernado Heart and

Chronic Disease Study,

a community-based

longitudinal study. No

details were reported

regarding selection

procedures for this

comparison group.

Age: 50–6

years (m

age gro

the Fili

Caucas

were 59

years, r

N = 294

women

(Cauca

West of

Scotland

1989–1995 The ATPIII definition of the

metabolic syndrome was

The WOSCOPS

study was a clinical

The original cohort

was aged 45–64

aseline,

ean age

ears

6447.

Total = 26.2 Sattar

et al [19]

Z rs

sies

gypsies were

f whom

gypsies

d and 156

esponded

rate: 53%

for nongypsies

ies, respectively

Nongypsies

= 20 (12–27)

Gypsies = 4 (3–6)

Vozarova de

Courten

et al [20]


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Coronary

Prevention

Study

(WOSCOPS)

used, with the only

modification being the use

of body mass index rather

than waist circumference

(as waist circumference was

not measured in this study);

a body mass index of

28.8 kg/m2 was

reported as being

equivalent to a waist

circumference of 102 cm in

a regression analysis used

in a recent cross-sectional

survey cited

trial and included

6595 moderately

hyper-cholesterolemic

men (low-density

lipoprotein cholesterol

174 to 232 mg/dL;

triglycerides\530

mg/dL) who had no

history of myocardial

infarction; all

individuals who had

diabetes were excluded

(72 self-reported, 76

newly diagnosed)

years at b

with a m

of 55.2 y

N for this

analysis =

ate Klasy,

Southern

Slovakia

1998 The WHO definition of the

metabolic syndrome was used

with several modifications.

Microalbuminuria was defined

as albumin to creatinine ratio

>3.4 mg/mmoL (30 mg/g) and

dyslipidaemia was defined only

using hypertriglyceridemia rather

than low HDL as well as

hypertriglyceridemia. Insulin

resistance was defined as the upper

quartile of the distribution of

HOMA-IR (Homeostatis

Model Assessment–Insulin

Resistance) values, and impaired

glucose tolerance was not

included in the criteria

All inhabitants of the

town were invited to

participate; the town

is composed of a

population of

approximately 1800,

of whom 40%

are gypsies

Age: 30 yea

951 nongyp

and 550

invited, o

501 non-

responde

gypsies r

Response

and 28%

and gyps

Table 1 (continued)

City,

country Year

N,

te

Prevalence


Kobar and

Ramallah,

Occupied

Palestinian

Territories

1996–1998 65 years

00 rural

90 F], 492

2 F, 190 M])

te: 85%

for the

d rural

ties,

ly

Rural = 17

Urban = 17

Abdul-Rahim

et al [21]

Turkey

(national

study)

2000 rs or older

e of

000)

1.1 years

1166 F)

e rates were

in the cited

M= 27.0

F = 38.6

Onat

et al [22]

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Age group,

response ra

WHO; however, there

is no indication that

microalbuminuria

was measured

An urban and a rural

community were

selected, with eligibility

based on residence in

that area for at least

6 months and physical

ability to participate

Age: 30 to

N= 992 (5

[210 M, 2

urban [30

Response ra

and 59%

urban an

communi

respective

ATPIII Participants in the Turkish

Adult Risk Factor Study,

a prospective study

carried out periodically

since 1990 in seven

geographical regions of

Turkey; because HDL

measurements were not

performed up until the

1998 survey, the 2000

follow-up survey was

used as the baseline

survey

Age: 31 yea

at the tim

survey (2

Mean age: 5

N = 2296

(1130 M,

No respons

reported

reference

Australia

(AusDiab

national

1999–2000 EGIR, WHO, and

ATPIII, with the WHO

definition using an

Representative national

population from 42

randomly selected

7982 individuals

(3627 M, 4355 F)

aged over 35 years

e: 55.3%

WHO

Total = 20.9

(18.3–23.4)

M= 25.2

(22.1–28.3)

F = 16.7

(13.7–19.7)

ATPIII

Total = 18.3

(15.3–21.4)

M= 19.5

(16.7–22.3)

F = 17.2

(13.4–20.9)

EGIR

Total = 15.9

(13.9–17.9)

M= 18.6

(16.0–21.1)

F = 13.3

(10.7–16.0)

Unpublished

datab

M rs

698 F)

e: 80%

WHO

Total = 19.1

M= 20.9

F = 17.6

ATPIII

Total = 12.8

M= 10.6

F = 14.7

EGIR

Total = 9.6

M= 9.0

F = 10.2

Cameron

et al [23]


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study) albumin-to-creatinine

ratio of 2.5 in men and

3.5 in women to define

microalbuminuria

clusters in the six

states and the Northern

Territory of

Australia; only those

with complete data for

each of the components

of the metabolic

syndrome for each of

the three definitions

were used

Response rat

auritius 1987 WHO, ATPIII, and EGIR,

with waist circumference

cut-points adjusted to

those appropriate for an

Asian population (obesity

= 90 cm [M]

and 80 cm [F]

Representative national

study (individuals were

followed longitudinally

in 1992 and 1998, but

baseline data was

representative) using

cluster sampling

technique; all

individuals with known

diabetes at time of

survey were excluded

from the analysis

Age: >24 yea

N= 3171

(1473 M, 1

Response rat

Table 1 (con

City,

country

, Prevalence


Haute

Garonne,

southwest

France

ars

F)

: 67%

and

n

Total = 17.3

M= 23

F = 12

Marques-Vidal

et al [24]

Ireland ars

: 69.9%

WHO

Total = 21.0

(18.7–24.1)

M ¼ 24.6

F = 17.8

ATPIII

Total = 20.7

(19.1–24.4)

M= 21.8

F = 21.5

Villegas

et al [25]

Denmark

)

ate

the

paper

WHO

M= 38.0

F = 22.0

EGIR

M= 22.0

F = 16.0

Drivsholm

et al [26]

and Balkau

et al [27]

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tinued)

Year



Age group, N

response rate

ern

1994–

1997

WHO definition, but

microalbuminuria was

not measured; insulin

resistance was defined

as HOMA 3.8

Part of the MONICA

(MONitoring Project

an Cardiovascular

Disease) study, the

participants were all

from the Department of

Haute-Garonne,

selected based on age

and sex categories

from a polling list

Age: 35–64 ye

N = 1153

(597 M, 556

Response rate

for women

59% for me

2003a WHO and ATPIII Recruited from a

primary care setting

using stratified random

sampling

Age: 50–69 ye

N = 1018

Response rate

1997 WHO and EGIR;

microalbuminuria

was measured as

albumin-to-creatinine

ratio �30 mg/g

Glostrup 1936

population-based

cohort

Age: 60 years

N = 321

(M), 366 (F

No response r

reported in

comparison

England 1992 WHO and EGIR, Population-based Ely Age: 40–65 years

N = 484

(M), 631 (F)

No response rate

reported in the

comparison paper

WHO

M= 44.8

F = 33.90

EGIR

M= 17.9

F = 14.3

Balkau et al [27]

and Wareham

et al [28]

Eng Age: 40–75 years

N = 398

(M), 489 (F)

No response rate

reported in the

comparison paper

WHO

M= 12.6

F = 13.3

EGIR

M= 4.7

F = 3.9

Balkau et al [27]

and

Mohamed-Ali

et al [29]

Fra Age: 30–65 years

N = 2517

(M), 2562 (F)

No response rate

reported in the

comparison paper

WHO

M= 23.5

F = 9.6

EGIR

M= 16.4

F = 10.0

Balkau and

colleagues

[27,30]


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but no measure of

microalbuminuria available;

therefore, prevalence

reported will be an

underestimate

Study from Ely,

Cambridgeshire

land 1991 WHO and EGIR.

Microalbuminuria

measured as albumin

excretion rate �20 mg/min,

2 hours after an oral

glucose tolerance test.

No waist or hip

measurements taken, so

all obesity criteria are

based on body mass index

Population-based

Goodinge Study from

North London

nce 1996 WHO and EGIR.

Microalbuminuria

measured as spot

albuminuria �20 mg/L

or dipstick proteinuria.

No 2-hour plasma

glucose values were

available, therefore

prevalence reported will

be an underestimate

Volunteers recruited to

the D.E.S.I.R. study

in central-western

France

Table 1 (continued)

City

cou

, Prevalence


Ital

and

rs (F)

),

rate

the

n paper

WHO

M= 12.2

F = 5.1

EGIR

M= 8.7

F = 1.7

Balkau et al [27]

and Zavaroni

et al [31]

Ital ears

0–55

),

rate

the

n paper

WHO

M= 34.5

F = 18.0

EGIR

M= 24.6

F = 14.0

Balkau

et al [27] and

Zavaroni

et al [32]

Net ears

),

rate

the

n paper

WHO

M= 19.2

F = 7.6

EGIR

M= 13.3

F = 8.3

Balkau et al

[27] and

Lean

et al [33]

368

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al/Endocrin

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bClin

NAm

33(2004)351–375

,

ntry Year



Age group, N

response rate

y 1981 WHO and EGIR,

but no measure of

microalbuminuria

available; therefore,

prevalence reported will

be an underestimate.

No waist or hip

measurements taken, so

all obesity criteria are

based on body mass index

Participants recruited

from their workplace to

the Barilla Study in

Parma, Italy

Age: 22–73

years (M)

22–55 yea

N = 461 (M

268 (F)

No response

reported in

compariso

y 1995 WHO and EGIR;

microalbuminuria

measured a timed

albumin excretion

�20 mg/min

Participants recruited

from their workplace

to the Barilla Study

in Parma, Italy

Age: 40–81 y

(M) and 4

years (F)

N = 227 (M

145 (F)

No response

reported in

compariso

herlands 1995 WHO and EGIR,

but no measure of

microalbuminuria

available; no 2-hour

plasma glucose values

were available;


reported will be an

underestimate

Population-based

MORGEN

(Monitoring Project

on Risk Factors

for Chronic

Diseases) study

from Amsterdam,

Maastricht, and

Doetinchem in the

Netherlands

Age: 20–60 y

N = 696 (M

682 (F)

No response

reported in

compariso

Spain 1996 WHO and EGIR, Population-based

study from

sites in Spain

Age: 35–64 years

N = 906 (M),

1119 (F)

No response rate

reported in the

comparison paper

WHO

M= 25.5

F = 19.9

EGIR

M= 16.0

F = 15.4

Balkau et al

[27] and

Lorenzo

et al [34]

Swe tion-based

o Diet and

er Study from

o, Sweden

Age: 46–68

years

N = 2190 (M),

3106 (F)

No response rate

reported in the

comparison paper

WHO

M= 43.3

F = 26.3

EGIR

M= 23.6

F = 13.9

Balkau et al

[27] and

Hedblad

et al [35]

ted.

, Australia (presented at the Australian Diabetes Society meeting, Melbourne, 2003).

369

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net

al/Endocrin

olMeta

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NAm

33(2004)351–375

but no measure of

microalbuminuria

available; therefore,

prevalence reported

will be an

underestimate

VIVA

nine

den 1994 WHO and EGIR,

but no measure of

microalbuminuria

available; no 2-hour

plasma glucose

values were available;


reported will be an

underestimate

Popula

Malm

Canc

Malm

Abbreviations: F, female; M, male; WHR, waist:hip ratio.a Date of publication rather than date the study was conducb Data from the International Diabetes Institute, Melbourne


Table 2

Prevalence of the metabolic syndrome according to the ATPIII definition

Prevalence (%)

Country Age group (y) Reference Men Women

India >20 Gupta et al [10] 7.9 17.5

India 20–75 Deepa et al [12] 36.4a 46.5a

Iran >20 Azizi et al [13] 24 42

Mexico 20–69 Aguilar-Salinas

et al [14]

Total = 26.6

Oman >20 Al-Lawati et al [15] 19.5 23.0

Finland 42–60 Laaksonen et al [16] 13.7 —

Ireland 50–69 Villegas et al [25] 21.8 21.5

Scotland 45–64 Sattar et al [19] 26.2 —

Turkey >31 Onat et al [22] 27.0 38.6

Australia >24 Unpublished data 19.5 17.2

Mauritius >24 Cameron et al [23] 10.6a 14.7a

France 30–64 Balkau et al [36] 10 7

United States (Native Americans) 45–49 Resnick et al [37] 43.6 56.7

United States (Filipina Americans) 50–69 Araneta et al [18] — 34.3

United States >19 Ford et al [38] 24.2 23.5

United States 30–79 Meigs et al [39] 26.9 21.4

United States (Non-Hispanic white) 30–79 Meigs et al [39] 24.7 21.3

United States (Mexican American) 30–79 Meigs et al [39] 29.0 32.8

a Obesity criteria adjusted to waist circumference appropriate for an Indian population.

Table 3

Prevalence of the metabolic syndrome according to the EGIR definition

Prevalence (%)


India >20 Deepa et al [11] 12.9a 9.9a

Finland 42–60 Laaksonen et al [16] 21.1 –


Denmark 60 Balkau et al [27] 22.0 16.0

England 40–65 Balkau et al [27] 17.9 14.3

England 40–75 Balkau et al [27] 4.7b 3.9b

France 30–65 Balkau et al [27] 16.4 10.0

Italy 22–73 M, 22–55 F Balkau et al [27] 8.7b 1.7b

Italy 40–81 M, 40–55 F Balkau et al [27] 24.6 14.0

Netherlands 20–60 Balkau et al [27] 13.3 8.3

Spain 35–64 Balkau et al [27] 16.0 15.4

Sweden 46–68 Balkau et al [27] 23.6 13.9

Mauritius >24 Cameron et al [23] 9.0 10.2

Abbreviations: F, female, M, male.a Obesity defined as waisthip ratio >0.9 (M) or >0.85 (F) and dyslipidemia defined as total

serum cholesterol>5.2 mmol/L and/or triglycerides>2.26 mmol/L and/or HDL\0.91 mmol/L.b Obesity not included in the definition of the metabolic syndrome.


The variation seen between populations using the ATPIII definition isnot seen in the EGIR definition, with most prevalence figures fallingbetween 10% and 20% for men and 10% and 15% for women (excludingthose figures not based on a complete EGIR definition). The prevalence ofthe metabolic syndrome according to the EGIR definition cannot exceed25% because of the requirement of being in the top quartile of insulinresistance/insulinemia, which partly explains the lack of variation in theEGIR prevalence figures. The exceptions to the uniform prevalence of theEGIR metabolic syndrome are the baseline Barilla study from Italy [27], inwhich the prevalence is 8.7% for men and 1.7% for women, and theGoodinge study from England, in which the prevalence is only 4.7% in menand 3.9% in women [27]. Neither of these studies, however, had dataavailable for waist circumference or waist/hip ratio, resulting in theconsiderably lower prevalence observed. The results from the Indian study[11] are also not directly comparable because of the variation to the criteriafor obesity and dyslipidaemia.

Table 4 shows the prevalence of the metabolic syndrome as defined by theWHO definition [2]. As for Table 3, many of the results presented aresourced from the paper comparing the EGIR and WHO definitions in

Table 4

Prevalence of the metabolic syndrome according to the WHO definition

Prevalence (%)



Denmark 60 Balkau et al [27] 38.0 22.0

England 40–65 Balkau et al [27] >44.8 >33.9

England 40–75 Balkau et al [27] >12.6 >13.3

France 30–65 Balkau et al [27] >23.5 >9.6

France 35–64 Marques-Vidal et al [24] 23.0 12.0

Italy 22–73 M, 22–55 F Balkau et al [27] >12.2 >5.1

Italy 40–81 M, 40–55 F Balkau et al [27] 34.5 18.0

Netherlands 20–60 Balkau et al [27] >19.2 >7.6

Spain 35–64 Balkau et al [27] >25.5 >19.9

Sweden 46–68 Balkau et al [27] 43.3 26.3

Mauritius >24 Cameron et al [23] 20.9 17.6

Occupied Palestinian Territories 30–65 Abdul-Rahim et al [21] Total = 17

Ireland 50–69 Villegas et al [25] 24.6 17.8

United States 40–74 Ford et al [38] 41.3 32.7

United States 30–79 Meigs et al [39] 30.3 18.1

United States

(non-Hispanic white)

30–79 Meigs et al [39] 24.7 17.2

United States

(Mexican American)

30–79 Meigs et al [39] 32.0 28.3

Abbreviations: F, female; M, male.

A ‘‘greater than’’ sign (>) means that the figure is an underestimate because one or more

components of the metabolic syndrome were not measured (see metabolic syndrome definitions

for these studies earlier in this article).


European populations [27]. Because the WHO definition includes waist/hipratio as the measure of obesity, and this was not collected in either theGoodinge study or the Barilla baseline study, the prevalences reported forthese two studies are not directly comparable. In addition, the Goodingestudy excluded subjects who had known diabetes at the time of the survey.Because diabetes is included in the WHO criteria, this further reduces thereported prevalence.

The trend of a higher prevalence of the metabolic syndrome among menobserved using the EGIR definition is again in evidence when using theWHO definition. The only exception to this is the Goodinge study, whichdid not use exactly the same criteria as the other studies. In some cases, theprevalence of the metabolic syndrome in men is double or more that amongwomen. In the DESIR (Data from an Epidemiological Study on the InsulinResistance syndrome) study in France, the prevalence is 23.5% for men and9.6% for women, while in the MORGEN (Monitoring Project on RiskFactors for Chronic Diseases) study in the Netherlands, the prevalence is19.2% for men and 7.6% for women. Overall, the prevalence of themetabolic syndrome using the WHO definition appears to be higher thaneither the ATPIII or EGIR definitions, particularly among men. This isconfirmed by the two studies in which the same population group was usedto estimate the prevalence of all three definitions (Australia and Mauritius).In these analyses, the prevalence using the WHO definition is considerablyhigher than that using either the EGIR or ATPIII definitions, with theexception being women in the Australian study, in which the WHO andATPIII definitions have a comparable prevalence. In Mauritius, theprevalence of the metabolic syndrome among men is 10.6%, 9.0%, and20.9% for the ATPIII, EGIR, and WHO definitions, respectively, while forwomen the prevalence is 14.7%, 10.2%, and 17.6%, respectively. In theAustralian AusDiab study, the prevalence of the metabolic syndrome usingthe ATPIII, EGIR, and WHO definitions is 19.5%, 18.6%, and 25.2% formen, respectively, and 17.2%, 13.3% and 16.7% for women, respectively.

A consistent finding is the observation that the prevalence of themetabolic syndrome is highly age-dependent. This is demonstrated in theIranian population, in which the prevalence is less than 10% for both menand women in the 20- to 29-year age group, rising to 38% and 67% in the60- to 69-year age group for men and women, respectively [13]. Similarly,among a French population the prevalence rises from less than 5.6% in the30- to 39-year age group to 17.5% in the 60- to 64-year age group [36].

Although true differences in the prevalence of the metabolic syndromebetween populations may be due to lifestyle influences, genetic factors, andthe age and sex structures of the populations under study, other possiblereasons for the variation in prevalence observed in different studies includedifferences in the age groups selected for each study, the process of selectingparticipants, the methods of measurement, and the era in which each of thestudies was conducted (due to temporal changes in prevalence). The


Diabetes Atlas recently published by the International Diabetes Federationdemonstrates the difficulty involved in attempting to make meaningfulcomparisons between populations for parameters such as the prevalence ofdiabetic complications and the prevalence of impaired glucose tolerance[40]. Unlike diabetes, obesity, or hypertension, in which measurement ofonly a single parameter is required, the use of a specific definition of themetabolic syndrome means that several parameters must all be measured andall in the same way to estimate the prevalence of the metabolic syndrome. Ifdefined criteria for the metabolic syndrome can be agreed upon, over timemore studies will be conducted worldwide using standardized methods andcriteria for diagnosis of the syndrome, allowing a more thorough comparisonof the magnitude of the epidemic around the world. Prospective studiesevaluating the ability of the various definitions of the metabolic syndrome topredict future cardiovascular disease and other disease endpoints will bevaluable in determining which definition of the metabolic syndrome is mostuseful. Clinical and experimental studies investigating the mechanismsunderlying the metabolic syndrome will also help to refine the definition usedin clinical practice and epidemiologic studies.

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The metabolic syndrome: prevalence in worldwide populations

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