A L A R T I C L E

Obesity, Fat Distribution,and Weight Gain as RiskFactors for Clinical Diabetesin Men

JUNE M. CHAN

ERIC B. RIMM, SCD

GRAHAM A. COLDITZ, MD

MEIR J. STAMPFER, MD

WALTER C. WILLETT, MD

OBJECTIVE — To investigate the relation between obesity, fat distribution, andweight gain through adulthood and the risk of non-insulin-dependent diabetes melli-tus (NIDDM).

RESEARCH DESIGN AND METHODS— We analyzed data from a cohortof 51,529 U.S. male health professionals, 40-75 years of age in 1986, who completedbiennial questionnaires sent out in 1986, 1988, 1990, and 1992. During 5 years offollow-up (1987-1992), 272 cases of NIDDM were diagnosed among men without ahistory of diabetes, heart disease, and cancer in 1986 and who provided completehealth information. Relative risks (RRs) associated with different anthropometric mea-sures were calculated controlling for age, and multivariate RRs were calculated con-trolling for smoking, family history of diabetes, and age.

RESULTS— We found a strong positive association between overall obesity asmeasured by body mass index (BMI) and risk of diabetes. Men with a BMI of ^35kg/m2 had a multivariate RR of 42.1 (95% confidence interval [CI] 22.0-80.6) com-pared with men with a BMI <23.0 kg/m2. BMI at age 21 and absolute weight gainthroughout adulthood were also significant independent risk factors for diabetes. Fatdistribution, measured by waist-to-hip ratio (WHR), was a good predictor of diabetesonly among the top 5%, while waist circumference was positively associated with therisk of diabetes among the top 20% of the cohort.

CONCLUSIONS — These data suggest that waist circumference may be a betterindicator than WHR of the relationship between abdominal adiposity and risk ofdiabetes. Although early obesity, absolute weight gain throughout adulthood, and waistcircumference were good predictors of diabetes, attained BMI was the dominant riskfactor for NIDDM; even men of average relative weight had significantly elevated RRs.

From the Department of Epidemiology (E.B.R., M.J.S., W.C.W.) and the Department of Nutri-tion (J.M.C., E.B.R., M.J.S., W.C.W.), Harvard School of Public Health; and the CharmingLaboratory (G.A.C., M.J.S., W.C.W.), Department of Medicine, Brigham and Women's Hospitaland Harvard Medical School, Boston, Massachusetts.

Address correspondence and reprint requests to Eric B. Rimm, ScD, Department of Nutrition,Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115.

Received for publication 6 December 1993 and accepted in revised form 7 April 1994.NIDDM, non-insulin-dependent diabetes mellitus; BMI, body mass index; WHR, waist-to-hip

ratio; RR, relative risk; CI, confidence interval.

R isk of non-insulin-dependent dia-betes mellitus (NIDDM) has beenstrongly associated with obesity (. 1--

18). Metabolic studies suggest that obe-sity is accompanied by a reduced numberof insulin receptors as well as insulin re-sistance (19-22). This alteration in glu-cose metabolism is, however, reversiblewith weight loss (23-24). Thus, it iswidely accepted that obesity is causallyrelated to NIDDM (6). Other studies alsosuggest that abdominal obesity specifi-cally increases the risk of diabetes(19,21,25-27).

In the Nurses' Health Study, astrong quantitative relationship was ob-served between body mass index (BMI) (ameasure of obesity) and the risk of diabe-tes among women (1). Even women witha BMI between 23 and 24 kg/m\ which isless than the population average, had arisk of diabetes 3.6 times that of womenwith BMIs <22 kg/m2. It was also sug-gested that the amount of weight gainedsince early adulthood significantly con-tributed to the risk of acquiring diabetesin later life.

Previous studies have found BMIand fat distribution to be independentrisk factors for diabetes in men. I lowever,the emphasis put on weight distributionas a strong predictor for diabetes, inde-pendent of BMI, may be misplaced be-cause the statistical control for BMI hasbeen incomplete in many studies. Thepresent investigation prospectively exam-ined finely divided strata of BMI andwaist-to-hip ratio (WHR) (a measure offat distribution) to determine more pre-cisely at what levels the risk of diabetes isincreased in a large cohort of U.S. men.Absolute weight gain since early adult-hood was also examined as a potentialrisk factor for diabetes.

RESEARCH DESIGN ANDMETHODS— The Health Profession-als' Follow-up Study began in 1986 as aprospective study, primarily investigatingthe risk factors for cardiovascular diseaseand cancer. The cohort was comprised of

DlABt-TliS CARE, VOLUME 1 7 , NUMBER 9 , SEPTEMBER 1 9 9 4 961

Obesity, fat distribution, and diabetes

51,529 males, 40-75 years of age, whocompleted a six-page baseline question-naire in 1986. The cohort includes menfrom six different health occupations:dentists, veterinarians, osteopaths, podi-atrists, optometrists, and pharmacists.Further details of the cohort and fol-low-up techniques can be found else-where (28).

We obtained information fromthe 1986 baseline questionnaire on cur-rent height and weight, medical history,past and present smoking habits, familyhistory of various diseases, heart diseaserisk factors, weight at age 21, and weightchange in the past 5 years. Biennial ques-tionnaires sent out in 1988, 1990, and1992 were used to update exposure infor-mation and to ascertain newly diagnosedcases of diabetes.

Family history of diabetes was ob-tained by a brief follow-up questionnairesent out in 1987. In addition, we includedpaper tape measures to assist the men inself-reporting their waist and hip circum-ferences. Men were asked to take mea-surements while standing and to avoidmeasuring over bulky clothing. Theywere instructed to measure their waists atthe umbilicus and to take their hip mea-surement as the largest circumference be-tween the waist and thighs; illustrationswere included with the directions. Be-cause the 1987 questionnaire was notpart of the usual biennial mailings, we didnot use extensive follow-up procedures(29) to increase our follow-up rate to>65%. In 1990, Rimm et al. (30) foundself-measured waist, hip, and weightmeasurements to be reasonably validwhen compared with standardized mea-surements by a technician in a subset ofthis cohort. The crude Pearson correla-tion between self-reported waist circum-ferences and the average of two techni-cian-measured waist circumferences was0.95 for men; the analogous correlationfor hip circumference was 0.88. The dif-ferences in mean circumference (techni-cian measured minus self-measured)were 0.36 inches for waist and —0.78inches for hips. Self-reported and mea-

sured weights were strongly correlated (r= 0.97, mean difference -2.34 lbs). Thecorrelation between self- and technician-measured WHRs was 0.69 with a meandifference of 0.027. After adjusting for ageand BMI and correcting for random with-in-person variability from daily or sea-sonal fluctuations, the correlation forWHRwas 0.62. Although not validated inthis population, self-reporting by middle-aged men of weight in early adulthoodhas also been shown to be moderately ac-curate (r = 0.80) (31). Weight and heightwere reported in pounds and inches andwere converted to metric units to calcu-late BMI. In this cohort, waist and hipcircumferences were correlated withheight. Thus, to investigate the associa-tions of these measures independent ofheight, we calculated height-adjustedwaist and hip circumferences as the resid-uals using separate least-squares regres-sion models with height as the indepen-dent variable and the circumferencemeasure as the dependent variable. Tomake the residuals interpretable, weadded the population mean circumfer-ence to each of the residuals. This proce-dure removed variation in waist or hipcircumferences due to height.

Population for analysisAmong the 51,529 men in the Health Pro-fessionals' Study, 44,018 had providedcomplete medical history informationand were free of diabetes, coronary heartdisease, and cancer in 1986. Of these,15,496 did not provide complete waistand hip circumference measurements,and an additional 539 did not providecomplete weight or height information in1986 and were excluded from the studypopulation. The remaining 27,983 mencomprised the population for analysis.

We confirmed a diagnosis of dia-betes from information collected from asupplementary questionnaire, which wassent to those participants who indicatedhaving a new diagnosis of diabetes on the1988, 1990, or 1992 questionnaire. Weclassified a person as having incidentNIDDM if he met one of the following

criteria: 1) he reported one or more clas-sic symptoms (thirst, polyuria, weightloss, hunger, or pruritus), plus fastingplasma glucose at least 140 mg/dl or ran-dom plasma glucose at least 200 mg/dl; or2) at least two elevated plasma glucoseconcentrations on different occasions(fasting at least 140 mg/dl and/or randomat least 200 mg/dl and/or concentration atleast 200 mg/dl after ^ 2 hours on oralglucose tolerance testing) in the absenceof symptoms; or 3) treatment with hypo-glycemic medication (insulin or oral hy-poglycemic agent). These criteria were inaccordance with those of the National Di-abetes Data Group (32). After exclusions,we confirmed 272 new cases of NIDDMfrom the 290 subjects who reported dia-betes and returned a supplementaryquestionnaire.

The validity of self-reported dia-betes using the same supplementaryquestionnaire has been studied in theNurses' Health Study. Medical recordswere obtained from 62 women, who wereselected at random, reporting diabetesand classified as definite NIDDM by asupplementary questionnaire. Sixty-oneof the 62 women classified as havingNIDDM by questionnaire response wereconfirmed by medical record review (1).

Data analysisWe used BMI (kg/m2) as a measure of rel-ative weight. The range of BMI was di-vided into nine categories with wholenumber cutoff points. Participants con-tributed person-months of follow-uptime starting from the return of the 1987questionnaire until the date of diabetesdiagnosis, date of death, or until 31 Jan-uary 1992.

In this study, incidence rates werecalculated by dividing the number of in-cident cases by the number of total per-son-years of follow-up for each categoryof BMI. Relative risks (RRs) were thencomputed by dividing the incidence ratesfor a specific category by the incidencerate of the lowest category, adjusting forage in each model (33). To distinguishbetween the effects of early BMI and cur-

962 DIABETES CARE, VOLUME 17, NIMBER 9, SEPTEMBER 1994

Chan and Associates

rent BMI, we classified men jointly by rel-ative weight at age 21 and categories ofweight gain since age 21. To adjust forother risk factors, we used multiple logis-tic regression to generate odds ratios as anestimate of RR. Multivariate logistic re-gression models were used to examineBMI and other anthropometric measuresin relation to risk of diabetes after control-ling for age, smoking, and family historyof diabetes.

RESULTS— Risk of diabetes in-creased continuously with increasing lev-els of BMI. Men with a BMI of 25.0-26.9kg/m2 had a risk 2.2 times (95% confi-dence interval (CI) 1.3-3.8) greater thanmen with a BMI <23.0 kg/m2 after ad-justing for age, family history, and smok-ing habits. Risk rose markedly for menwith a BMI 2:29 kg/m2. As expected, themen in the highest category, BMI >35.0kg/m2, had the highest RR (multivariateRR = 42.1, 95% CI 22.0-80.6) (Table 1).

When WHR was added to thestandard model (controlling for familyhistory, age, and smoking), the RRs asso-ciated with nine categories of BMI wereonly modestly attenuated. For example,men in the highest category of BMI had amultivariate RR of 42.1 (95% CI 22.0-80.6) before and 31.7 (95% CI 16.2-62.0) after controlling for WHR (Table 1).

To examine the relation betweenearly adult obesity and diabetes risk, BMIat age 21 was calculated. The age-ad-justed RR for men with a BMI 2:27.0kg/m2 at age 21 was 2.9 (95% CI 2.0-4.2). BMI at age 21 was moderately cor-related with current BMI (r = 0.61).When the model was modified to controlfor weight gain since age 21, age, familyhistory, and smoking habits, the risk as-sociated with BMI at age 21 increased.Compared with men in the lowest quin-tile, men with a BMI between 23.0 and24.9 kg/m2 at age 21 had an increasedrisk of 1.5 (95% CI 1.1-2.2), and menwith a BMI >27.0 kg/m2 at age 21 had anRR of 6.4 (95% CI 4.3-9.5) (Table 2).

Absolute weight gain throughoutadulthood was also examined. Men who

ST ST1 D

III5' 5' TOo o ?d

a. E. CI

c < -S . su •3 2 . ^£!. Su 2=»

re" n £ •

2, ^ is^ % i70 < 7i

S 5«i %o £?3 O

era a-ro 3=• ui

< in

•3 O

< £ pT % p: ^ £ r ' m

rrf' ro?a s-3.

yearsases

g3

ro (V

o

II—I

bo

3U l

Ul

3

ryjbo

o ^Ul OJ

ON

'P NJ

bo oOJ

NJOJ

r~ ui4^ Ui

b

Ul"4^0000

NJ OJ

2 ?o S

00OJ004 *

NJ4

?NJ4 *

NJOJ <-"

^ b

.0-:

OU

IS J

ed, for

3"ro

307Tr»C L, or cun

ro3

0king

AU l

15-2

-

O

IVNJUlOgare

ro

D-su

moke

CL, form

ro

UIS

0roC L

r currei

3oki

era

AU l

" H5-24

**

IVNJU ln

era'su

roro

day)

su3

U l

^—N

NJVO

U l

00

bo

11—'ON~vl

UlUl

. • ^

9°30.7

v—s

OJ1—1

ON2-6

NJ

ON

3.8-1

NJ

b

ON

OJ

NJI—1

U l

NJ

OJ

1—1

1

NJv-^

[s

NJ1—>(22.0-8

0ON

001—1

1

OJU l

OJ

bo(8.5-2

NJOJ

NJON

VO

H-'

h->-42.

U l^s

U l0

(34. 6-7

4^

OJ00

NJ--J

NJI—1

NJ

^,427

OJ

1—'

0

"OJU lI—1

CO

0

NJ

.0-30

OJ.0-32.

' O

ubOJ4.9

IVu

BM

;tego

ON

so

a

so

Ol

DIABKTHS CARE, VOLUME 17, NUMBER 9, SEPTEMBER 1994 963

Obesity, fat distribution, and diabetes

Table 2—BMI at age 21 and risk of diabetes among a cohort of 27,338 U.S. men age 40-75years in 1986 and followed for 5 years

Range (kg/m2)

BMI at age 21<21.021.0-22.923.0-24.925.0-26.927.04-

Weight gain since age 21Loss 34-Loss 2-gain 2Gain 3-5Gain 6-7Gain 8-9Gain 10-14Gain 154-

Person-years

29,08536,89133,64917,7758,357

9,88526,26122,78712,98711,62120,96424,019

Cases

6950554448

41914172948

141

Age-adjusted RR(95% CD

1.00.6 (0.4-0.9)0.8 (0.6-1.2)1.2 (0.8-1.8)2.9 (2.0-4.2)

0.5 (0.2-1.5)1.0

0.8(0.4-1.6)1.7(0.9-3.1)3.0(1.8-5.2)2.6(1.5-4.3)6.5 (4.4-9.6)

Multivariate RR(95% CI)

1.01.0(0.7-1.4)1.5(1.1-2.2)2.5 (1.7-3.8)6.4 (4.3-9.5)

0.3(0.1-0.8)1.0

0.9 (0.5-1.8)1.9(1.0-3.7)3.5 (2.0-6.3)3.4 (2.0-5.8)8.9 (5.5-14.7)

Analysis includes 27,338 participants (266 cases) with complete information on BMl at age 21. MultivariateRR model for BMI at age 21 controls for age in 5-year intervals, family history, smoking status (never smoked,formerly smoked, or currently smoking <15,15-24, or S25 cigarettes/day), and seven categories of weightchange since age 21. Multivariate RR model for weight gain since age 21 controls for age, family history,smoking status (never smoked, formerly smoked, or currently smoking < 15,15-24, or S25 cigarettes/day),and quintiles of BMI at age 21.

had gained 6-7 kg since age 21 had anincreased multivariate RR of diabetes (RR= 1.9, 95% CI 1.0-3.7) compared withmen with an absolute weight change <2kg after controlling for age, smoking,family history, and BMI at age 21. Amodel was also constructed including ter-tiles of BMI at age 21 and weight gainsince age 21, controlling for age, familyhistory, and smoking. Across the range ofBMI, absolute weight gain was positivelyassociated with the risk of diabetes. Riskincreased within each tertile of weightgain as well as within each category ofBMI at age 21 (Fig. 1; Table 2).

Recent weight gain was stronglyassociated with the risk of diabetes. Infor-mation was available on weight gained inthe 5 years before 1986 for 259 of the 272NIDDM cases. After controlling for BMIin 1981, family history, age, and smokinghabits, men who had gained >13.6 kg(the equivalent of ^30 lbs) had a risk 4.5times that of men who were within 4.5 kgof their 1981 weight (95% CI 2.4-8.2)(Table 3). The positive association be-

tween weight gain in the last 5 years andrisk of diabetes was not appreciably mod-ified by BMI in 1981.

We examined the waist-to-hipcircumference ratio and the independentassociation of waist and hip circumfer-ences and height with the risk of diabetesusing three different models: controllingfor age only; controlling for age, smoking,and family history of diabetes; and con-trolling for age, smoking, family history ofdiabetes, and BMI in 1986 (Table 4). Weexamined the RRs associated with height-adjusted hip circumference and bothcrude and height-adjusted waist circum-ference. Compared with men with a WHR<0.90, men with a WHR >0.99 (top20%) had a multivariate RR of 4.0 (95%CI 2.5-6.2). However, after further con-trolling for current BMI, the multivariateRR was markedly attenuated, RR = 1.7(95% CI 1.1-2.7).

To investigate further the effect offat distribution on men in the highestquintile of WHR, the group was subdi-vided into the top 10-20%, top 5-10%,

and top 5%. Compared with men in thelowest quintile of WHR, men in the top5% of WHR had a multivariate RR of 5.2(95% CI 3.1-8.6) and a RRof 2.0 (95% CI1.2-3.5) after further control for BMI.WHR, independent of BMI, maintained asignificant positive association to the riskof diabetes only among the top 5%. Thus,the RR of diabetes among men in the topquintile (top 20%) of WHR, observedoriginally in Table 4, is primarily attribut-able to the top quarter of that group (thetop 5% of the cohort).

Men with a crude waist circumfer-ence >40.0 inches (top 20%) had a mul-tivariate RR of 10.8 (95% CI 6.2-18.7),but this was reduced to 3.5 (95% CI 1.7-7.0) after control for BMI. Men in thehighest quintile of height-adjusted waistcircumference had a multivariate RR of9.8 (95% CI 5.6-17.0) and 3.1 (95% CI1.4-6.6) after adding BMI to the model.Hip circumference was positively associ-ated with risk of diabetes in the multiva-riate model (RR = 7.3,95% CI 4.4-12.0);however, after control for BMI in 1986,hip circumference was not a significantrisk factor. No association between heightand risk of diabetes was observed. How-ever, absolute weight was found to be in-dependently correlated to risk of diabetesfor the highest quintile group, even aftercontrolling for current relative weight,age, smoking, and family history (RR =2.1, 95% CI 1.0-4.4 for men weighing198-307 lbs). Overall, current BMI pre-vailed as the strongest predictor of diabe-tes when included together in a modelwith hip circumference, height measure-ments, or WHR.

The WHR, which is associatedwith diabetes, is commonly used as anindicator of abdominal fat. Waist circum-ference, because it is a single measure-ment, contributes less error than WHR,and, particularly when adjusted forheight, may be a more direct measure ofabdominal fat. The RRs associated withabdominal adiposity were examinedmore closely by subdividing the top 20%of waist measurement into quartiles. Theincidence rate associated with each quar-

964 DIABETES CARE, VOLUME 17, NUMBER 9, SEPTEMBER 1994

Chan and Associates

<5 kg 5 -10 kg 11+ kgWeight change since age 21

24+ kg/m2

22-23 kg/m2

<22 kg/m2 Body MassIndex at age 21

Figure 1—The RR increases shown within each tertile of weight gain and within each category of BMI

at age 21.

tile of the top 20% was compared withthat of men in the lowest quintile of thewhole cohort. There was no substantialdifference between the risk of diabetes as-sociated with crude waist measurementsand that associated with height-adjustedwaist measurements. Increased RRs wereseen for each quartile group within thetop 20% even in multivariate models ad-justed for BMI. Men with a height-ad-justed waist measurement >43.8 inches(top 5%) had a multivariate RR of 18.6(95% CI 10.4-33.3) compared with menwith a waist measurement <34.75 inch-

es; risk was attenuated after further con-trolling for BMI (RR = 4.3, 95% CI 1.9-10.1).

We calculated RRs of diabetes forBMI and WHR within strata of age (Table5). After controlling for WHR and otherconfounders, we found that men age40-49 with a BMI >35 kg/m2 had a RR ofdiabetes of 77.4 (95% CI 25.2-247.0);men aged ^60 in the same category ofBMI had a much lower RR (RR = 14.9,95% CI 4.3-52.1). Conversely, older menin the top quintile of WHR had a muchhigher RR than younger men.

The association of family historywith diabetes incidence was examinedprospectively. Men who had fathers,mothers, or a sibling with a history of di-abetes were considered to have a positivefamily history of diabetes. Controlling forcurrent relative weight of the participant,age, and smoking, men with a family his-tory of diabetes had an elevated RR of 2.3(95% CI 1.8-3.0) compared with menwithout a family history of diabetes.

Excluded from the population foranalysis were 15,496 men who did notprovide complete waist and hip circum-ference measurements. To explore thepossibility that the remaining study pop-ulation differed in their relation betweenBMI and risk of diabetes, we calculatedthe multivariate RR for BMI limited tothose 15,496 men who did not reportcomplete waist or hip circumference in-formation. After excluding those menwith heart disease or cancer in 1986, 182cases of NIDDM occurred among thisgroup. Among this subset, risk for diabe-tes associated with nine categories of BMIwas very similar to those of the originalpopulation for analysis. Men with a BMI>35.0 kg/m2 had a RR of 34.9 (95% CI12.6-97.0).

We considered the possibility thatdiagnostic bias may account for the rela-tionship observed between BMI and therisk of diabetes. It is possible that physi-cians, aware of the associations betweenobesity and diabetes, may be more likelyto diagnose diabetes in assymptomatic

Table 3—Weight change between 1981 and 1986 among men who self-reported anthropometric measurements

Weight change1981-1986(kg)

Lost 4.5 +Lost 4.5-gain 4.5Gain 4.5-13.6Gain 13.6+

Cases

1010525

4

BMI <28 kg/m2

Person-years

5,77289,10413,947

868

in 1981

Age-adjusted RR(95% CI)

1.5 (0.8-2.9)1.0

1.7(1.1-2.6)4.6(1.8-11.3)

Cases

155833

9

BMI >28 kg/m2

Person-years

3,3268,5262,901

328

in 1981

Age-adjusted RR(95% CI)

0.7(0.4-1.2)1.0

1.8(1.2-2.8)4.8 (2.5-9.2)

RR (95% CDadjusted forBMI in 1981

0.8(0.5-1.2)1.0

1.7(1.2-2.3)4.5 (2.4-8.2)

Analysis includes 27,159 participants (259 cases) with complete information on BMI in 1981/weight change; uneven cutoff points caused by conversion frompounds to kilograms. RR adjusted for age in 5-year intervals, family history, smoking status (never smoked, formerly smoked, or currently smoking < n , l i 24,or >25 cigarettes/day), and deciles of BMI in 1981.

DIABETES CARE, VOLUME 17, NUMBER 9, SEPTEMBER 1994 965

Obesity, fat distribution, and diabetes

Table 4—Waist, hips, height, and WHR in 1986 as risk factors for diabetes

Waist (crude)Range (inches)CasesModel 1: across ageModel 2: without BMlModel 3: with BMl

Waist (height-adjusted)Range (inches)CasesModel 1: across ageModel 2: without BMlModel 3: with BMl

Hips (height-adjusted)Range (inches)CasesModel 1: across ageModel 2: without BMlModel 3: with BMl

HeightRange (inches)CasesModel 1: across ageModel 2: without BMlModel 3: with BMl

WHRRangeCasesModel 1: across ageModel 2: without BMlModel 3: with BMl

1

29.4-34.5141.01.01.0

26.9-34.5141.01.01.0

28.1-37.7171.01.01.0

41-68711.01.01.0

<0.90241.01.01.0

2

34.6-36.026

2.0(1.0-3.8)1.9(1.0-3.7)1.7 (0.9-3.3)

34.6-36.221

1.37 (0.7-2.7)1.3 (0.7-2.7)1.2 (0.6-2.4)

37.7-39.026

1.5 (0.8-2.7)1.5 (0.8-2.7)1.3 (0.7-2.4)

69-7075

1.0(0.7-1.4)1.0(0.7-1.4)1.1 (0.8-1.5)

0.90-0.9224

0.9 (0.5-1.6)0.9 (0.5-1.6)0.8(0.4-1.4)

Quintiles

3

36.1-38.038

2.2(1.2-4.1)2.2(1.2-4.1)1.7 (0.8-3.3)

36.3-37.932

1.9(1.0-3.7)2.0(1.0-3.7)1.5 (0.7-3.0)

39.0-40.139

2.1 (1.2-3.6)2.0(1.1-3.6)1.3 (0.7-2.5)

70-7141

1.1 (0.8-1.7)1.2 (0.8-1.7)1.3 (0.9-1.9)

0.93-0.9546

1.9(1.1-3.1)1.8(1.1-3.0)1.3 (0.8-2.2)

4

38.1-40.039

3.3(1.8-6.0)3.2 (1.7-5.8)1.9 (0.9-3.9)

37.9-40.147

2.9 (1.6-5.2)2.8(1.5-5.1)1.7 (0.8-3.5)

40.1-41.755

30.0(1.8-5.0)2.9(1.7-5.1)1.4(0.7-2.7)

71-7235

1.0(0.7-1.6)1.1 (0.7-1.6)1.1 (0.7-1.6)

0.96-0.9868

2.5(1.6-4.1)2.5 (1.5-3.9)1.4(0.9-2.4)

5

40.1-69.0155

12.0 (7.8-18.4)10.8 (6.2-18.7)3.5 (1.7-7.0)

40.2-68.3158

11.0(7.1-17.0)9.8 (5.6-17.0)3.1 (1.4-6.6)

41.7-64.4135

7.7(5.1-11.8)7.3 (4.4-12.0)1.5(0.7-2.9)

73-9150

1.2(0.8-1.7)1.2(0.9-1.8)1.3(0.9-1.8)

0.99+110

4.6 (3.0-7.0)4.0 (2.5-6.2)1.7 ((1.1-2.7)

Data are RR (95% Cl). Model 1, RR across age-groups; Model 2, RR controlling for age in 5-year intervals, family history, and smoking status (never smoked, formerlysmoked, or currently smoking < 15,15-24, or >25 cigarettes/day); Model 3, RR controlling for age in 5-year intervals, family history, smoking status (never smoked,formerly smoked, or currently smoking <15, 15-24, or ^25 cigarettes/day), and nine categories of BMl in 1986. Height-adjusted waist and hips models 2 and 3control for height using residual analysis.

fatter men. However, when we only in-cluded the 175 cases with symptomaticdiabetes, the RR associated with a BMl>35 kg/m2 compared with a BMl <23kg/m2 (RR = 46.6, 95% Cl 21.4-101.6)was actually higher than when assymp-tomatic cases were included.

When men who reported canceror heart disease at baseline were addedback to the population for analysis, theresults were not appreciably differentfrom those presented above.

C O N C L U S I O N S — We found an ex-tremely strong association between BMland risk of NIDDM. Increased risks wereseen for all BMl levels ^24.0 kg/m2, wellbelow the standard criteria for obesity.Thus, even men of average weight aresubstantially more likely to develop dia-betes than men with a BMl <23.0 kg/m2.The extremely strong RR for men with aBMl >29.0 kg/m2 combined with meta-bolic data and the effect of weight loss onglucose tolerance warrant the conclusion

that the relationship between obesity andrisk of diabetes is causal (6,19-22).

The validity of BMl as a measureof body fatness or adiposity has been as-sessed by comparison with densitometry.Correlation coefficients with percentbody fat have generally been between 0.6and 0.8 (34). However, the correlationwas >0.9 when compared with absolutefat mass adjusted for height, which ap-pears to be a stronger predictor of glucoseintolerance than percent body fat. To the

966 DIABETES CARE, VOLUME 17, NUMBER 9, SEPTEMBER 1994

Chan and Associates

Table 5—BMI, WHR, and risk of diabetes within age strata in 1986

nBMI

<23.023.0-23.924.0-24.925.0-26.927.0-28.929.0-30.931.0-32.933.0-34.9>35.0

WHR<0.900.90-0.920.93-0.950.96-0.980.99 +

40-49

49

1.00.5(0.1-2.7)0.9 (0.2-4.0)1.2(0.4-4.0)1.1(0.3-4.7)4.3(1.2-15.8)9.7 (2.5-36.7)

21.2 (5.4-82.9)77.4 (25.2-247.0)

1.00.6(0.2-1.6)1.0(0.4-2.7)0.6(0.2-1.7)0.9 (0.4-2.2)

Multivariate RR (95% Cl)

Age range (years)

50-59

97

1.01.8(0.3-10.6)2.9 (0.6-14.6)4.8(1.1-20.5)

13.3 (3.2-56.2)14.3 (3.3-63.2)23.0 (4.9-107.0)44.8(9.5-211.7)42.6(8.3-218.5)

1.01.2(0.5-3.1)1.3 (0.5-3.3)1.2 (0.5-2.9)2.3 (1.0-5.3)

60-75

126

1.00.9 (0.3-2.3)1.4(0.6-3.3)1.7 (0.8-3.5)2.6(1.2-5.6)4.2(1.9-9.5)7.2 (3.0-17.5)8.4 (2.9-24.7)

14.9(4.3-52.1)

1.00.6(0.2-1.8)1.7(0.7-4.1)2.2(1.0-5.1)1.8 (0.8-4.2)

Multivariate RR model for BMI controls for age in 5-year intervals, family history, smoking status (neversmoked, formerly smoked, or currently smoking <15, 15-24, or >25 cigarettes/day), and quintiles ofWHR. Multivariate RR model for WHR controls for age in 5-year intervals, family history, smoking status(never smoked, formerly smoked, or currently smoking <15, 15-24, or >25 cigarettes/day), and ninecategories of BMI in 1986.

extent that BMI is an imperfect measure-ment of adiposity, the extremely strongassociation between BMI and risk of dia-betes observed is an underestimate of thisassociation.

As stated in METHODS, in this co-hort, self-reported circumferences con-tain random error, especially when calcu-lating WHR, because this ratio hasreduced between-person variation andincludes error from both circumferencemeasurements. In our validation study,the correlation between the self-reportedand the average of two technician-mea-sured assessments, taken 7 months apart,was 0.62 for the WHR. A correlation of0.62 is comparable to that found betweenrepeat measures of blood pressure andcholesterol (35,36). Because the ratio ofself-reported circumference measureswill have more error than weight andheight, the RRs for circumferences will

tend to be underestimated to a greater de-gree than the RRs for BMI.

In this study, self-reported diabe-tes was confirmed by a supplementaryquestionnaire. However, because we didnot screen our population, 3-9% of themen may have undiagnosed NIDDM(37). Although, in this cohort, 78% of themen had seen their physician for routinephysicals within the first 2 years of fol-low-up. Underdiagnosis would have littleeffect on the RRs as long as the subset ofundiagnosed cases did not differ greatlyfrom the rest of the cases by levels of BMI.Among only symptomatic cases, the RRsof diabetes associated with levels of BMIwere not substantively different from therisks found among the complete casepopulation. Thus, underdiagnosis of as-symptomatic cases is not likely to havesignificantly influenced the observed as-sociation between obesity and risk of di-

abetes. Furthermore, when we removedthe cases diagnosed in the first 2 years offollow-up, the results were not apprecia-bly different from those presented.Among the 194 cases diagnosed between1989 and 1992, men with a BMI ==35kg/m2 had a multivariate RR of diabetes of53.9 (95% CI 24.3-119.5).

As indicated in Table 2 and Fig. 1,early obesity strongly predicts the risk ofdiabetes. Even men with a BMI between23.0 and 24.9 kg/m2 at age 21 had anincreased risk after controlling for age,smoking, family history, and weight gainsince age 21.

Similarly, overall absolute weightgain throughout adulthood was stronglyrelated to risk of diabetes, regardless ofBMI at age 21. Clearly, those who beganwith a higher BMI (>24 kg/m') andgained substantial weight, (>11.0 kg)had the highest RR (RR = 21.1, 95% CI8.5-52.3). However, the steady increasealong both axes shows that almost anyweight gained after adolescence is associ-ated with a higher risk of diabetes. Weobserved similar results in women in theNurses' Health Study (1). These data sug-gest that it may be equally important toattain a healthy weight earlier in life aswell as maintain it throughout adulthood.

Prior study of this cohort showedthat BMI increased with age up to ages60-65 and then decreased while averagewaist circumference increased continu-ously across all age-groups (38). This sug-gests a natural increase in adiposity withaging, as indicated by the increasing waistcircumferences accompanied by a de-crease in lean body mass after age 65.Other longitudinal studies have foundthat after age 65, men experience rapidloss of lean body mass (39,40). Age-related changes in body mass composi-tion may make BMI a less appropriate in-dicator of total obesity in older subjectsand could explain the observed reductionin magnitude of the risk of diabetes asso-ciated with BMI after age 60 (Table 5).

The data from this investigationimply that fat distribution, as measuredby WHR, may contribute to one's risk of

DlABETKS CARK, VOLUME 1 7 , NUMBER 9 , SEPTEMBER 1 9 9 4 967

Obesity, fat distribution, and diabetes

diabetes when analyzed separately fromother factors. However, after controllingfor relative weight, WHR was only a sig-nificant risk factor for diabetes and thenweakly among men in the top 5% with aWHR > 1.03.

Fat distribution has predicted di-abetes in several other studies. Althoughthis association has been more pro-nounced in women (2), a few studies haveemphasized the parallel importance inmen. Haffner et al. (7) found that WHRwas a better single screening measure forN1DDM than BMI and that upper bodyadiposity predicted diabetes even in leanmen and women. Ohlson et al. (8) alsofound that WHR was positively and sig-nificantly associated with NIDDM evenafter BMI was considered among men inthe top two tertiles of the study. This wasa 13.5-year prospective study of 792 54-year-old men in Goteborg, Sweden; how-ever, there were only 37 cases of diabetesconfirmed at the time of analysis (6). Cas-sano et al. (3) observed a 2.4 times greaterrisk (95% Cl 1.7-3.7) for men in the toptertile for the ratio of abdominal circum-ference to hip breadth compared withmen in the lowest tertile, after controllingfor BMI, cigarette smoking, and age after18 years of follow-up. These studies con-trolled for BMI in either quintile or tertilegroups. Hence, the stronger observed as-sociations between WHR and diabetesrisk may well be due to inadequate con-trol of BMI; the current study controlledfor BMI in nine categories.

Waist circumference (bothheight-adjusted and crude) was positivelyassociated with the risk of diabetes withineach quartile group of the top 20% ofwaist circumference, and the magnitudeof excess risk was stronger than withWHR after controlling for relative weight,height, smoking, family history, and age.Adjusting waist for height did not appre-ciably influence the magnitude of associ-ation with diabetes risk; because simplewaist measurements are easy to make,this may have practical importance inclinical settings. The increased risks of di-abetes associated with having a high

WHR and the increased risks observedamong men with large waist circumfer-ences may both be due to the metaboliccomplications of having high levels of ab-dominal adiposity. Because waist circum-ference has less measurement error thanWHR, it may be a better indicator of therelationship between abdominal adipos-ity and the risk of diabetes.

Further follow-up of the HealthProfessionals cohort would be necessaryto substantiate the current findings. It ispossible that as the cohort ages, somemeasure of abdominal adiposity mayemerge as an independently importantrisk factor for diabetes among leaner men.Metabolic data suggest that abdominaladiposity is associated with elevatedplasma levels of free fatty acids, insulininsensitivity, and impaired glucose toler-ance (19,21,25-27).

The results of this investigationshow that current BMI, early obesity, ab-solute weight gain throughout adulthood,and abdominal adiposity measured bywaist circumference are important inde-pendent risk factors for diabetes. Familyhistory and age are accepted risk factorsfor diabetes (1,11,41), but only weightchange is controllable. For incident dia-betes, the hypothesized importance ofweight distribution over general body sizemay be overemphasized. Fat distributionappears to be a modest independent riskfactor for diabetes among men in the top5% of WHR, but the strong RRs associ-ated with even moderate BMI levels sug-gest that overall obesity is the dominantrisk factor for diabetes. Thus, publichealth recommendations should primar-ily emphasize the prevention of overallobesity to reduce the occurrence ofNIDDM. Ideally, a lean weight should beattained early in life and maintainedthroughout adulthood.

Acknowledgments—This study was sup-ported by research grants HL-35464 and CA-55075 from the National Institutes of Healthand P30-DK-46200 from the Boston Obesity/Nutrition Research Center.

References

1. Colditz GA, Willett WC, Stampfer MJ,Manson JE, Hennekens CH, Arky RA,Speizer FE: Weight as a risk factor forclinical diabetes in women. Am J Epide-miol 132:501-513, 1990

2. Hartz AJ, Rupley DC, and Rimm AA: Theassociation of girth measurements withdisease in 32,856 women. Am] Epidemiol119:71-80, 1984

3. Cassano PA, Rosner B, Vokonas PS, WeissST: Obesity and body fat distribution inrelation to the incidence of non-insulin-dependent diabetes mellitus. Am] Epide-miol 136:1474-1486, 1992

4. Barrett-Connor E: Epidemiology, obesity,and non-insulin-dependent diabetes mel-litus. Epidemiol Rev 11:172-180, 1989

5. Seidell JC, Bakx JC, De Boer E, Deuren-berg P, Hautvast JGAJ: Fat distribution ofoverweight persons in relation to morbid-ity and subjective health. MJ Obes 9:363-374,1985

6. Ohlson LO, Larsson B, Bjorntorp P, Eriks-son J, Svardsudd K, Welin L, Tibblin G,Wilhelmsen L: Risk factors for type 2(non-insulin-dependent) diabetes melli-tus: thirteen and one-half years of fol-low-up of the participants in a study ofSwedish men born in 1913. Diabetologia31:798-805, 1988

7. Haffner SM, Mitchell BD, Stern MP, Ha-zuda HP, Patterson JK: Public health sig-nificance of upper body adiposity fornon-insulin- dependent diabetes mellitusin Mexican Americans. Intj Obes 16:177—84,1992

8. Ohlson LO, Larsson B, Svardsudd K, We-lin L, Eriksson H, Wilhelmsen L, Bjorn-torp P, Tibblin G: The influence of bodyfat distribution on the incidence of diabe-tes mellitus: 13.5 years of follow-up of theparticipants in the study of men born in1913. Diabetes 34:1055-1058, 1985

9. Fujimoto WY, Leonetti DL, BergstromRW, Shuman WP, Wahl PW: Cigarettesmoking, adiposity, non-insulin-depen-dent diabetes, and coronary heart diseasein Japanese-American men. Am] Med 89:761-771, 1990

10. Charles MA, Fontbonne A, Thibult N,Warnet JM, Rosselin GE, Eschwege E:Risk factors for NIDDM in white popula-

968 DIABETES CARE, VOLUME 17, NUMBER 9, SEPTEMBER 1994

Chan and Associates

tion: Paris prospective study. Diabetes 40:96-99, 1991

11. Mykkanen L, Laakso M, Uusitupa M,Pyorala K: Prevalence of diabetes and im-paired glucose tolerance in elderly sub-jects and their association with obesityand family history of diabetes. DiabetesCare 13:1099-1105, 1990

12. Dowse GK, Zimmet PZ, Gareeboo H, Al-berti K, Tuomilehto J, Finch CF, ChitsonP, Tulsidas H: Abdominal obesity andphysical inactivity as risk factors forNIDDM and impaired glucose tolerancein Indian, Creole, and Chinese Mauri-tians. Diabetes Care 14:271-282, 1991

13. Kaye SA, Folsom AR, Sprafka JM, PrineasRJ, Wallace RB: Increased incidence of di-abetes mellitus in relation to abdominaladiposity in older women. J Clin Epidemiol44:329-334, 1991

14. Stern MP, Gonzalez C, Mitchell BD, Vil-lalpando E, Haffner SM, Hazuda HP: Ge-netic and environmental determinants oftype II diabetes in Mexico City and SanAntonio. Diabetes 41:484-492, 1992

15. O'Dea K, White NG, and Sinclair AJ: Aninvestigation of nutrition-related risk fac-tors in an isolated Aboriginal communityin Northern Australia: advantages of a tra-ditionally orientated life-style. Med] Aust148:177-180,1988

16. KnowlerWC,PettittDJ,SaadMF, CharlesMA, Nelson RG, Howard BV, Bogardus C,Bennett PH: Obesity in the Pima Indians:its magnitude and relationship with dia-betes. Am] Clin Nutr 53:1543S-1551S,1991

17. Colditz GA, Manson JE, Stampfer MJ,Rosner B, Willett WC, Speizer FE: Dietand risk of clinical diabetes in women. AmJ Clin Nutr 55:1018-1023, 1992

18. Pi-Sunyer FX: Health implications of obe-sity. Am] Clin Nutr 53:1595S-1603S,1991

19. Fujioka S, Matsuzawa Y, Tokunaga K,Kawamoto T, Kobatake T, Keno Y, KotaniK, Yoshida S, Tarui S: Improvement ofglucose and lipid metabolism associatedwith selective reduction of intra-abdomi-nal visceral fat in premenopausal women

with visceral fat obesity, lnt J Obes 15:853-859, 1991

20. Deibert DC, and DeFronzo RA: Epineph-rine-induced insulin resistance in men. JClin Invest 65:717-721, 1980

21. Schutz Y and Tremblay A: Does lipid ox-idation differ in gynoid and android obesewomen? Int] Obes 16:67-69, 1992

22. OlefskyJM: Insulin resistance and insulinaction in vitro and in vivo perspective.Diabetes 30:148-162, 1981

23. Pedersen O, Hjollund E, Sorensen HS: In-sulin receptor binding and insulin actionin human fat cells, effects of obesity andfasting. Metabolism 31:884-895, 1982

24. Beck-Nielson H, Pederson O, LindkovHO: Normalization of insulin sensitivityand the cellular insulin binding duringtreatment of diabetics for one year. AdaEndocrinol 90:103-112, 1979

25. Kather M, Schroder F, Simon B, SchlierfG: Human fat cell adenylate cyclase: re-gional differences in hormone sensitivity.EurJ Clin Invest 7:595-597, 1977

26. Smith U, HammarstenJ, Bjorntorp P, KraiJG: Regional differences and effect ofweight reduction of human fat cell me-tabolism. Eur J Clin Invest 9:327-332,1979

27. DespresJ, Moorjani S, Lupien PJ, Trem-blay A, Nadeau A, Bouchard C: Regionaldistribution of body fat, plasma lipopro-teins, and cardiovascular disease. Arterio-sclerosis 10:497-511, 1990

28. Rimm EB, Giovannucci EL, Willett WC:Prospective study of alcohol consump-tion and risk of coronary disease in men.Lancet 338:464-468, 1991

29. Rimm EB, Stampfer MJ, Colditz GA, Gio-vannucci E, Willett WC: Effectiveness ofvarious mailing strategies among nonre-spondents in a prospective cohort study.Am J Epidemiol 131:1068-1071, 1990

30. Rimm EB, Stampfer MJ, Colditz GA,Chute CG, Litin LB, Willett WC: Validityof self-reported waist and hip circumfer-ences in men and women. Epidemiology1:466-473, 1990

31. Rhoads GG, Kagan A: The relation of cor-onary disease, stroke, and mortality to

weight in youth and in middle age. Lancet1:492-495, 1983

32. National Diabetes Data Group: Classifica-tion and diagnosis of diabetes mellitusand other categories of glucose intoler-ance. Diabetes 28:1039-1057, 1979

33. Kleinbaum DG, Kupper LL, MorgansternH: Epidemiologic Research: Principles and

Quantitative Methods. New York, Van

Norstrand Reinhold, 1982, p. 140-130,320-376

34. Spiegelman D, Israel RG, Bouchard C,Willett WC: Absolute fat mass, percentbody fat, and body-fat distribution: whichis the real determinant of blood pressureand serum glucose? Am J Clin Nutr !55:1033-1044, 1992

35. Rosner B, Hennekens C, Kass EH, MiallWE. Age specific correlations analysis oflongitudinal blood pressure data. Am JEpidemiol 106:306-313, 1977

36. Shekelle RB, Shryrock AM, Paul O: Diet,serum cholesterol, and death from coro-nary heart disease. N EnglJ Med 304:65-70,1981

37. Harris MI: Prevalence of non-insulin-dependent diabetes and impaired glucosetolerance. In Diabetes in America: DiabetesData. Vol. 6. National Diabetes DataGroup, Eds. Bethesda, MD, National In-stitutes of Health, 1985, p. 1-32 (DIMSpubl. no. PHS 85-1468)

38. Giovannucci E, Rimm EB, Chute CC,Kawachi I, Colditz GA, Stampfer MJ, Wil-litt WC: Obesity and benign prostatic hy-perlasia: a prospective study. Am] Epide-miol. In press

39. Borkan GA, Norris AG: Fat redistributionand the changing body dimensions of theadult male. Hum Bid 49:495-514, 1977

40. Flynn MA, Nolph GB, Baker AS, MartinWM, Krause G: Total body potassium inaging humans: a longitudinal study. AmJClin Nutr 50:713-717, 1989

41. Fujimoto WY, Leonetti DL, Newell-Mor-ris L, Shuman WP, Wahl PW: Relation-ship of absence or presence of a familyhistory of diabetes to body weight andbody fat distribution in type 2 diabetes.lnt J Obes 15:111-120, 1991

DIABHTES CARE, VOLUME 17, NUMBER 9, SEPTEMBER 1994 969