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Waist Circumference and CardiometabolicRisk

A Consensus Statement from Shaping Americas Health: Association for

Weight Management and Obesity Prevention; NAASO, The ObesitySociety; the American Society for Nutrition; and the American DiabetesAssociation

SAMUELKLEIN, MD1

DAVIDB. ALLISON, PHD2

STEVENB. HEYMSFIELD, MD3

DAVIDE. KELLEY, MD4

RUDOLPHL. LEIBEL, MD5

CATHYNONAS, MS, RD, CDE6

RICHARD KAHN, PHD7

O

besity is an important risk factor forcardiometabolic diseases, including

diabetes, hypertension, dyslipide-mia, and coronary heart disease (CHD).Several leading national and internationalinstitutions, including the World HealthOrganization (WHO) and the NationalInstitutes of Health, have provided guide-lines for classifying weight status based onBMI (1,2). Data from epidemiologicalstudies demonstrate a direct correlationbetween BMI andthe risk of medical com-

plications and mortality rate (e.g., 3,4).Men and women who have a BMI 30

kg/m2

are considered obese and are gen-erally at higher risk for adverse healthevents than are those who are consideredoverweight (BMI between 25.0 and 29.9kg/m2) or lean (BMI between 18.5 and24.9 kg/m2). Therefore, BMI has becomethe gold standard for identifying pa-tients at increased risk for adiposity-related adverse health outcomes.

Body fat distribution is also an impor-

tant risk factor for obesity-related dis-eases. Excess abdominal fat (also knownas central or upper-body fat) is associatedwith an increased risk of cardiometabolicdisease. However, precise measurementof abdominal fat content requires the useof expensive radiological imaging tech-niques. Therefore, waist circumference

(WC) is often used as a surrogate markerof abdominal fat mass, because WC cor-relates with abdominal fat mass (subcuta-neous and intra-abdominal) (5) and isassociated with cardiometabolic diseaserisk (6). Men and women who have waistcircumferences greater than 40 inches(102 cm) and 35 inches (88 cm), respec-tively, are considered to be at increasedrisk for cardiometabolic disease (7).These cut points were derived from a re-gression curve that identified the waistcircumference values associated with aBMI 30 kg/m2 in primarily Caucasian

men and women living in north Glasgow(8).

An expert panel, organized by the Na-tional Heart, Lung and Blood Institute,has recommended that WC be measuredas part of the initial assessment and beused to monitor the efficacy of weight losstherapy in overweight and obese patientswho have a BMI 35 kg/m2 (7). How-ever, measurement of WC has not beenwidely adopted in clinical practice, andthe anatomical, metabolic, and clinicalimplications of WC data can be confus-

ing. Therefore, Shaping Americas Health:Association for Weight Management andObesity Prevention; NAASO: The ObesitySociety; and the American Diabetes Asso-ciation convened a panel, comprised ofmembers with expertise in obesity man-agement, obesity-related epidemiology,adipose tissue metabolic pathophysiol-ogy, statistics, and nutrition science to re-view the published scientific literatureand hear presentations from other expertsin these fields. The Consensus Panel metfrom December 17 to 20, 2006, in Wash-

From the

1

Division of Geriatrics and Nutritional Science, Center for Human Nutrition, Washington Uni-versity School of Medicine, St.Louis, Missouri; the2Clinical Nutrition Research Unit, Universityof Alabamaat Birmingham, Birmingham, Alabama; the 3Clinical Research Department, Metabolism, Merck Pharmaceu-tical Company, Rahway, New Jersey; the 4Obesity and Nutrition Research Center, University of Pittsburgh,Pittsburgh, Pennsylvania; the 5Naomi Berrie Diabetes Center, Columbia University, New York, New York;the 6Obesity and Diabetes Programs, North General Hospital, New York, New York; and the 7AmericanDiabetes Association, Alexandria, Virginia.

Address correspondence and reprint requests to Samuel Klein, MD, Washington University School ofMedicine, 660 South Euclid Ave., Campus Box 8031, St. Louis, MO 63110. E-mail: [email protected].

Approved for publication 7 March 2007.D.B.A. has received research grants from Frito-Lay and OMP; has served as a consultant to Kraft Foods,

Pfizer, Bristol-Myers Squibb, and Bio Era; and has received financial support from Lilly, Pfizer, MerckPharmaceutical Company, Unilever, Coca-Cola, General Mills, International Life Sciences Institute, Glaxo-SmithKline, OMP, Jansen Pharmaceuticals, and Frito-Lay. S.K. has received research grants from Sanofi-

Aventis, Merck, and Takeda for clinical trials; has served as a consultant to Sanofi-Aventis, AmylinPharmaceuticals, EnteroMedics, Dannon-Yakult, and Merck Pharmaceutical Company. S.B.H. is an em-ployee of Merck Pharmaceutical Company. D.E.K. has received research grants from Novartis Pharmaceu-

ticals, Sanofi-Aventis, and Pfizer; has served as a consultant/advisor to Novartis Pharmaceuticals, Sanofi-Aventis, Pfizer, Merck Pharmaceutical Company, and GlaxoSmithKline; and has been on speakers bureausfor Novartis Pharmaceuticals, Sanofi-Aventis, and Merck Pharmaceutical Company. R.L.L. has receivedresearch grants from GlaxoSmithKline and has been a consultant/advisor to Amylin Pharmaceuticals, MerckPharmaceutical Company, Arisaph Pharmaceuticals, and Genaera Corporation. C.N. has been a consultant/advisor to Amylin Pharmaceuticals, GlaxoSmithKline, and Slim Fast.

Abbreviations:CHD, coronary heart disease; CT, computed tomography; IAAT, intra-abdominal adi-pose tissue; MRI, magnetic resonance imaging; NHANES III, National Health and Nutrition ExaminationSurvey III; SAAT, subcutaneous abdominal adipose tissue; WC, waist circumference; WHO, World HealthOrganization.

A table elsewhere in this issue shows conventional and Systeme International (SI) units and conversionfactors for many substances.

DOI: 10.2337/dc07-9921 2007 by NAASO and the American Diabetes Association.The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby

marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

R e v i e w s / C o m m e n t a r i e s / A D A S t a t e m e n t s

C O N S E N S U S S T A T E M E N T

DIABETESCARE, VOLUME 30, NUMBER6, JUNE2007 1647


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changes in abdominal adipose tissue masshas not been established. Nonetheless,the precision of WC measurement is highat any given landmark. Even self-measurement can be highly reproducible

when performed by properly trained sub-jects, although self-measurement resultsin an underestimation of true WC. Mea-surement of WC cannot determine the in-dividual contributions of SAAT and IAATto abdominal girth, which require imag-ing by MRI or CT. The value of these scan-ning techniques in clinical practice hasnot been determined.

QUESTION 2: What are thebiological mechanisms responsiblefor the association between waistcircumference and metabolic and

cardiometabolic risk?It is not known whether the storage of anabsolute or relative excess amount of tri-glycerides in abdominal fat depots is di-rectly responsible for increased diseaserisk or whether such deposition is simplyassociated with other processes that causerisk, or both. In addition, WC values pro-vide a measure of both SAAT and IAATmasses. Therefore, the relationship be-tween WC and cardiometabolic risk can-not determine whether risk is associatedwith SAAT, IAAT, or both.

The mechanism(s) responsible for the

relationship between excess abdominalfat distribution and cardiometabolic dis-ease is not known, but several hypotheseshave been proposed. One of the earliesthypotheses that implicated IAAT as a met-abolic risk factor suggested that activationof the central nervous systemadrenalaxis by environmental stressors causedboth the preferential deposition of adi-pose tissue in the trunk and the cardio-va s c ula r a nd me ta b olic dis orde rsassociated with that deposition (22).More recently, it has been suggested that a

limited ability of subcutaneous fat depotsto store excess energy results in over-flow of chemical energy to IAAT and ec-topic sites, such as liver and skeletalmuscle. Excessive ectopic fat accumula-

tion then causes metabolic dysfunction inthose organs. In fact, increased intrahe-patic fat is associated with dyslipidemiaand hepatic insulin resistance (23), andincreased intramyocellular fat is associ-ated with skeletal muscle insulin resis-tance (24). In this paradigm, IAAT isprimarily a marker of the magnitude ofoverflow of fatty acids from subcutaneousdepots. Therefore,increased WC could be adiscernible marker of a system-wide im-pairment in energy storage regulation, inwhich an increase in IAAT reflects a re-duced capacity for energy storage in other

adipose tissues. A third hypothesis pro-poses a direct effect of omental and mesen-teric adipose tissue depots on insulinresistance, lipoprotein metabolism, andblood pressure. Metabolic products ofomental and mesenteric adipose tissue de-pots are released into the portal vein, whichprovides direct delivery to the liver. Lipoly-sis of omentalandmesenteric adiposetissuetriglycerides release free fatty acids that caninduce hepatic insulin resistance andprovide substrate for lipoprotein synthesisand neutral lipid storage in hepatocytes. Inaddition, specific proteins and hormones

produced by omental and mesenteric adi-pose tissue, such as inflammatory adipo-kines, angiotensinogen, and cortisol(generated by local activity of 11-hydrox-ysteroid dehydrogenase), can also contrib-ute to cardiometabolic disease. A fourthhypothesis is that genes that predispose topreferential deposition of fat in abdominaldepots independently cause cardiometa-bolic disease.

These hypotheses are not mutuallyexclusive, and it is possible that all, andother unknown mechanisms, are in-

volved in the association between abdom-inal fat mass and adverse metabolicconsequences.

QUESTION 3: What is the power ofwaist circumference to predictadverse cardiometabolic outcomes?How does the predictive power ofwaist circumference compare withthat of BMI? Does waistcircumference measurement inaddition to BMI improvepredictability?The importance of WC in predicting car-diometabolic risk factors (e.g., elevatedblood pressure, dyslipidemia, and hyper-glycemia) and adverse outcomes (e.g., di-abetes, CHD, and death rate) has beenexamined in many large epidemiologicalstudies (7,24 33). Specific relative risksbetween WC and these outcomes vary,

depending on the population sampledand the outcome measured. The relation-ship between WC and clinical outcome isconsistently strong for diabetes risk, andWC is a stronger predictor of diabetesthan is BMI. The relative risk of develop-ing diabetes between subjects in the high-est and lowest categories of reported WCoften exceeds 10 and remains statisticallysignificant after adjusting for BMI. Thesedata demonstrate that WC can identifypersons who are at greater cardiometa-bolic risk than those identified by BMIalone. Values for WC are also consistently

related to the risk of developing CHD,and the relative risk of developing CHDbetween subjects in the highest and low-est categories of WC ranges from 1.5 to2.5 and remains statistically significant af-ter adjusting for BMI. Values for WC areusually strongly associated with all-causeand selected cause-specific mortalityrates. Data from several studies supportthe notion that WC is an important pre-dictor of diabetes, CHD, and mortalityrate, independent of traditional clinicaltests, such as blood pressure, blood glu-cose, and lipoproteins (7,26). However,

there is not yet a compelling body of evi-dence demonstrating that WC providesclinically meaningful information that isindependent of well-known cardiometa-bolic risk factors.

The relationships between WC andhealth outcomes are affected by demo-graphic variables, including sex, race/ethnicity, and age. WC is an importantpredictor of health outcomes in men andwomen; Caucasians, African Americans,Asians, and Hispanics; and adults of allage-groups. In fact, the relationship be-

Table 2Relationships among waist circumference, BMI, and adipose tissue compartments inmen and women

Men Women

BMI

Waist

circumference BMI

Waist

circumference

Total adipose tissue 0.82 0.87 0.91 0.87Percent body fat 0.70 0.79 0.86 0.82Total subcutaneous

adipose tissue0.82 0.83 0.91 0.86

Total intra-abdominaladipose tissue

0.59 0.79 0.69 0.77

Data are correlation coefficients. Adapted from reference 18.

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tween WC and health outcome changesmuch less with increasing age than doesthe relationship between BMI and healthoutcome (31). However, it is not knownwhether WC can provide a better assess-ment of health risk in one sex, racial/ethnic group, or age category thananother.

Theshapeof therelationship betweenWC and health outcomes (e.g., linear,monotonic, step-function, or U-shaped)influences the WC value that can mostefficiently distinguish between normaland abnormal and serve as a basis forconsidering clinical action. Data frommost studies suggest that the shape of therelationship between WC and health out-come lends itself to identifying clinicallymeaningful cut point values because riskoften accelerates monotonically above,and can be relatively flat below, a specific

WC value. Optimum WC cut points willlikely vary according to the populationstudied, the health outcome of interest,and demographic factors.

Data from most clinical weight lossand exercise training trials have shownthat reductions in WC occur concomi-tantly with reductions in obesity-relatedcardiometabolic risk factors and disease.However, these results do not prove thatthe reduction in WC was responsible forthe beneficial effect on health outcome.Additional studies are needed to evaluatethe effect of decreasing WC on cardio-

metabolic outcomes.

QUESTION 4: Should waistcircumference be measured inclinical practice?The panel concluded that determiningwhether waist circumference should bemeasured in clinical practice depends onthe responses to the following four keyquestions:

1. Can waist circumference be reli-ably measured? Answer:Yes.

Health care personnel and even pa-tients themselves, who are given appro-

priate training in technique, can providehighly reproducible measurements ofWC in men and women. However, it isnot know whether measurement of oneanatomical site is a better indicator of car-diometabolic risk than measurement atother sites.

2. Does waist circumference provide:a) good prediction of diabetes, CHD, andmortality rate? Answer:Yes; b) incremen-tal value in predicting diabetes, CHD, andmortality rate above and beyond that pro-vided by BMI? Answer:Yes; c) sufficient

incremental value in these predictionsabove and beyond that offered by BMIand commonly evaluated cardiometa-bolic risk factors, such as blood glucoseconcentration, lipid profile and bloodpressure? Answer:Uncertain.

Data from many large populationstudies have found waist circumference tobe a strong correlate of clinical outcome,particularly diabetes, and to be indepen-dent of BMI. In addition, data from a lim-ited number of studies demonstrates thatWC remains a predictor of diabetes,CHD, and mortality rate, even after ad-justing for BMI and several other cardio-metabolic risk factors. Additional studiesare needed to confirm that WC remainsan independent predictor of risk.

3. Do the current definitions used todetermine a high WC identify a nontrivialnumber of patients who are at increased

cardiometabolic risk, but who would nototherwise be identified by having a BMI25 kg/m2 and an assessment of com-monly evaluatedcardiometabolic risk fac-tors? Answer:Yes.

The recommended WC thresholdsfor increased cardiometabolic risk in men(40 inches [102 cm]) and women (35inches [88 cm]) were derived from WCvalues that correlated with a BMI 30kg/m2 (2). The National Health and Nu-trition Examination Survey III (NHANESIII) found that about 14% of women andabout 1% of men had a high WC but a

normal BMI (18.524.9 kg/m

2

) (36). Inaddition, 70% of women who wereoverweight (BMI 25.029.9 kg/m2) ha daWC 35 inches and 25% of men whowere overweight had a WC 40 inches.An estimate based on data available fromthe WHO Monica Project, conducted inmore than 32,000 men and women fromEurope, Australia, and New Zealand, sug-gest that about 10% of participants whohad BMI values 30 kg/m2 had a WCabove therecommendedcut points for in-creased risk (36). It is not known whatportion of subjects who had a large WC

would have been identified as having in-creased cardiometabolic risk based onfindings from a standard medical evalua-tion. Therefore, the optimal WC criterianeeded to identify patients at increasedrisk of metabolic disease, who would oth-erwise not be identifiedby evaluating BMIand/or other standard cardiometabolicrisk factors, is not known and will likelyrequire adjustments based on BMI, sex,age, and race/ethnicity.

4. Would assessment of WC in pa-tients who have a BMI 25 kg/m2 affect

clinical management if NHLBI obesitytreatment guidelines are followed? An-swer:Probably not.

Measurement of WC in clinical prac-tice is not trivial, because providing thisassessment competes for the limited timeavailable in a busy office practice and re-quires specific training to ensure that re-liable data are obtained. Therefore, waistcircumference should only be measured ifit can provide additional information thatinfluences patient management. Based onNHANES III data, 99.9% of men and98.4% of women would have received thesame treatment recommendations pro-posed by the NHLBI Expert Panel by eval-uating BMI and other cardiovascular riskfactors, without an assessment of WC(37). However, it is likely that differentWC cut point values could provide moreuseful clinical information. For example,

an analysis of data obtained from theNHANES III and the Canadian HeartHealth Surveys found that BMI-specificWC cut points provided a better indicatorof cardiometabolic risk than the recom-mended WC thresholds (35). For nor-mal-weight (BMI 18.524.9 kg/m2),overweight (BMI 25.029.9 kg/m2), classI obesity (BMI 30.034.9 kg/m2), andclass II/class III obesity (BMI 35.0 kg/m2), the optimal WC cut points were 87,98, 109, and 124 cm in men and 79, 92,103, and 115 cm in women, respectively.Therefore, it is possible that WC measure-

ment could be an effective clinical tool foridentifying metabolically obese, leanpatients who might benefit from lifestyletherapy but would not have been consid-ered for treatment because of a normalBMI. Waist circumference could alsoidentify metabolically normal, obesesubjects who do not require aggressiveobesity therapy because they do not havea marked increase in cardiometabolicrisk.

CONCLUSIONSWaist circumference provides a unique

indicator of body fat distribution, whichcan identify patients who are at increasedrisk for obesity-related cardiometabolicdisease, above and beyond the measure-ment of BMI. However, the current WCcut points recommended to determinehealth risk (2) were derived by regressionfrom an obese BMI and are unlikely toaffect clinical management when BMI andotherobesity-related cardiometabolic riskfactors are already being determined.Therefore, the clinical usefulness of mea-suring WC, when risk is based on the cur-

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rently accepted guidelines, is limited.However, WC measurement can some-times provide additional information tohelp the clinician determine which pa-tients should be evaluated for the pres-ence of cardiometabolic risk factors, suchas dyslipidemia, and hyperglycemia. Inaddition, measuring WC can be useful inmonitoring a patients response to dietand exercise treatment because regularaerobic exercise can cause a reduction inboth WC and cardiometabolic risk, with-out a change in BMI (38). Further studiesareneeded to establish WC cutpoints thatcan assess cardiometabolic risk, not ade-quately captured by BMI and routine clin-ical assessments. Selection of the mostappropriate WC values will be complexbecause they are likely influenced by sex,race/ethnicity, age, BMI, and other fac-tors. Nonetheless, it should be possible to

determine more useful WC cut pointsthan are currently recommended, bycarefully reviewing published data andreevaluating datasets available from exist-ing population studies. These additionalanalyses will define the future role of WCmeasurement in clinical practice.

Acknowledgments This conference wassupportedin part by an educational grant fromthe Campbell Soup Company.

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