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
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
354 A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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
355A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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.
356 A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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.
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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
(%) (95% CI) Reference
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
Definition of metabolic
syndrome Survey population
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]
(continued on next page)
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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
(%) (95% CI) Reference
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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Definition of metabolic
syndrome Survey population
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]
(continued on next page)
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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
(%) (95% CI) Reference
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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Definition of metabolic
syndrome Survey population
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]
(continued on next page)
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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
(%) (95% CI) Reference
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]
366
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33(2004)351–375
tinued)
Year
Definition of metabolic
syndrome Survey population
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]
(continued on next page)
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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
(%) (95% CI) Reference
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
A.J.Camero
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al/Endocrin
olMeta
bClin
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33(2004)351–375
,
ntry Year
Definition of metabolic
syndrome Survey population
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;
therefore, prevalence
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
A.J.Camero
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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;
therefore, prevalence
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
370 A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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 (%)
Country Age group (y) Reference Men Women
India >20 Deepa et al [11] 12.9a 9.9a
Finland 42–60 Laaksonen et al [16] 21.1 –
Australia >24 Unpublished data 18.6 13.3
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.
371A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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 (%)
Country Age group (y) Reference Men Women
Australia >35 Unpublished data 25.2 16.7
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).
372 A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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
373A.J. Cameron et al / Endocrinol Metab Clin N Am 33 (2004) 351–375
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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