RACHEL BALLARD-BARBASH, CHRISTINE FRIEDENREICH, MARTHA ... week 8-2… · RACHEL BALLARD-BARBASH,...

22

An" explanation for the increasing incidence of cancers in devel-rr.-/oping countries has been the hypothesis that a chronic state ofpositive energy balance promotes tumor growth. (Tannenbauml940a,b) first explored this hypothesis in animal models and demon-strated that both increased calories and fat increased the occurrenceand number of breast cancer tumors in mice. Similarly, epidemiologicstudies in humans in the 1970s demonstrated that heavier women wereat increased risk of breast and endometrial cancer (De Waard et al.,1974;Blitzer e[ al., 1976). Other population-based studies in the early1980s suggested that risk increased with increasing weight for severalother cancer sites, specifically colon, prostate, gallbladder (amongwomen), and kidney (Lew and Garfinkel, 1979: Hartz et al., 1984;Garfinkel, 1986). Since then, numerous epidemiologic studies haveexamined the association of weight and other anthropometric meas-ures with cancer incidence and have explored potential biologicalmechanisms to explain observed associations. The majority of thesestudies have focused on breast, colon, endometrial, renal cell,esophageaUgastric, and prostate cancer; limited data are available onbody size associations with other cancer sites.

The aim of this review is to provide a comprehensive overview ofthe state of scientific evidence for.the association between obesity-related risk factors and cancer, with a focus on those cancers withsufficient evidence for review: those of the colon, rectum, esophagus/gastric cardia, renal cell, endometrium, ovary, breast, prostate, thyroid,lung, and head and neck. The specific objectives of this revieware to:

. Summarize the epidemiologic literature for the association betweencancer risk and obesity-related measures of weight or body massindex (BMI; defined most commonly as weight in kilograms [kg]divided by height in meters squared), fat deposition patterns (com-monly approximated by waist circumference or by the ratio of waist-to-hip circumferences [WHR] or by ratios of truncal to extremityskinfolds), and weight change;

. Highlight gaps in scientific knowledge for the association ofobesity-related factors and cancer risk;

. Identify the possible underlying biological mechanisms for theseassociations:

. Comment on areas for future research; and

. Estimate the public health impact of obesity on cancer risk at theinternational level.

Because of space limitations, the epidemiologic evidence on heightand cancer risk is not included in this review but has been well sum-marized in several previous reviews (Ballard-Barbash, 1999; Gunnelle t a l . . 2001) .

METHODS

A search was conducted on MEDLINE and PUBMED for all publi-cations on weight, body mass index, anthropometric factors, andspecific cancers in human populations and was supplemented by amanual search of all major relevant journals. The literature searchincluded all publications up to February 2003. Studies included in rhisreview focused on some aspect of anthropometric risk factors inrelation to cancer risk for the cancers noted above. Maior review

422

Obesity and Body Composition

RACHEL BALLARD-BARBASH, CHRISTINE FRIEDENREICH, MARTHA SLATTERY,AND INGER THUNE

papers or books were also identified and reviewed. Summary figuresof risk estimates for the highest compared to lowest quantile of BMIand the major cancer sites were generated. Because of the very largenumber of studies in breast cancer, studies with at least 100 caseseach of pre- and postmenopausal breast cancer cases are includedin the breast cancer figures. Because of differences in risk for colonand rectal cancer and the limited number of studies on rectal canceralone, only data on colon cancer were summarized in the coloncancer figure. Biological mechanisms potentially involved in theassociation between obesity and specific cancers were summaizedin a table. In addition, population attributable risks estimated forthe European Union by Bergstrom et al. (2001 ) were compared tocurrent estimates for the United States and summarized in a table. Asummary statement for each cancer site was developed following thecriteria for convincing, probable, possible, and no association assummarized in the 1997 World Cancer Research Fund and AmericanInstitue for Cancer Research (World Cancer Research Fund, 1997 )report on Food, Nutition and the Prevention of Concer: A GlobalPerspective.

METHODOLOGIC AND MEASUREMENT ISSUES

Existing methods for assessing the etiologic and prognostic influencesof energy balance and body size on cancer have limitations that shouldbe considered when evaluating the epidemiologic evidence and plan-ning future research. Briefly summarized, these limitations fall intothree areas: validity of exposure assessment, difficulty of comparisonsacross studies, and insufficient sample sizes to explore fully the manyfactors that relate to body size and fat mass and that could potentiallymodify observed associations.

The measurement of anthropometric indices is generally well stan-dardized and documented (Lohman et al., 1988; WHO, 1995). In fact,the standardization, accuracy, and reliability of these measures arebetter than for many other cancer-related exposures. Weight and heightare the most standardized measurements and least subject to variabil-ity. More recent investigations have used interviewers to measurevarious anthropometric indices from study participants, hence reduc-ing the possibility of random and systematic error. However, manystudies of cancer etiology have relied on self-reported weight andheight. Studies on self-reported height suggest a reasonable degree ofaccuracy with a bias in overreporting height that is somewhat greaterin men compared to women and that increases with age (Rowland,1990) or is limited to people over age 60 (Kuczmarski et a1., 2001),presumably due to age-related loss in height. Studies on self-reportedweight indicate the presence of significant misreporting at theextremes of weight, with heavier people underreporting and lighterpeople overreporting their weight (Rowland, 1990; Stevens et al.,1990; Must et al., 1993). Therefore, studies of chronic disease that relyon self-reported height and weight will underestimate the risk associ-ated with these measures (Gunnell et al., 2000). Nonetheless, com-pared to estimates of correlation between reported versus measuredassessment of other exposures, such as dietary intake, correlation coef-ficients between recalled and measured weight suggest that weight isrecalled with a reasonable degree of accuracy. For example, in oneU.S. study. correlations between reporled and measured weishts fbr

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elderly subjects asked to recall weight currently and from 4 and 28years previously were reponed to be 0.98 for current, 0.94 for 4-year,and 0.82 for 28-year recall (Stevens et al., 1990). Measurement ofskinfolds and circumferences is less reliable than the measurement ofweight and height (Lohman et al. , 1988; WHO,1995). However, rel i-ability is improved with standardization in measurement technique. Itis not feasible to obtain these anthropometric measures from self-report. Waist circumference is currently considered to be the most con-venient and simple measure of abdominal or central adiposity forepidemiologic research (WHO, 1995, 2000). Percent body fat can beestimated from bioelectric impedance but only has been reported inone study of cancer etiology (Lahmann, 2003). Bioelectric impedanceis currently the most promising field method for estimating bodycomposition in large epidemiologic studies because it is portable,inexpensive, easy to use, and highly precise. Issues related to use ofdifferent methods for estimating body composition for chronic diseaseepidemiology are well summaized by Baumgartner and colleagues( l99s).

Comparison across studies is difficult because most studies haveexamined risk by quantile distributions (most commonly tertile orquartile) for the BMI or other anthropometric measures used. As thedistribution of BMI varies across populations, these quantile groupsare not comparable across studies, making comparison difficult. Withincreasing interest in understanding the risk for many chronic diseasesby standard WHO BMI categories, investigators have begun toexamine risk by these categories: underweight as BMI of less than18.50, normal weight as BMI of 18.5G-24.99, overweight as BMI of25.00 or higher. This latter overweight category is further subdividedinto four categories: preobese, 25.00-29.99, obese class I,30.00-34.99; obese class II, 35.00-39.99; and obese class III, >40.00(WHO, 2000). More recent meta-analyses have the ability to examinerisk by these broad weight categories; however, analyses should notbe limited to these categories as risk may vary within them, depend-ing on the chronic diseases and the populations examined.

Research to date suggests often complex and varying associationsof body size with different cancer sites. Although cancer as a wholenow exceeds coronary artery disease as a cause of death in the UnitedStates population under age 85, the incidence of site-specific canceris much lower than diseases such as diabetes mellitus and coronaryartery disease, limiting the sample sizes of studies for less commoncancers. Therefore, delineation of the association of body size andcancer requires site-specific studies, which can often be done onlythrough multicollaborative efforts for less common cancers. Further-more, as more factors are identified as potentially influencing bodysize and cancer associations, delineation of the underlying mecha-nisms requires further subgroup analysis, thereby increasing samplesize requirements.

The "gold standard" technologies required, such as doubly-labeledwater for measuring energy expenditure or computenzed tomographyfor measuring body composition, are expensive, not easily portable,and, thus, not feasible for large samples. Therefore, it is not possibleto directly measure positive energy balance in large epidemiologicstudies of cancer risk or prognosis. In addition, although it is possibleto estimate energy balance from its components-energy intake andexpenditure-current methods to assess diet and physical activity relyon self-report of food intake and physical activity, a methodology withsubstantial reporting error. Consequently, because large epidemiologicstudies cannot measure energy balance through either doubly-labeledwater techniques or through accurate estimation of energy intake andcxpenditure from self-reports, the most valid measure of either per-sistent or recurrent states of positive energy balance is weight gainduring adult life. Given findings from clinical metabolic research ofcomplex interactions among different steroid hormones, such as sexsteroids and insulin, ranging from receptor cross-reactivity to postre-ceptor potentiation, statistical modeling methods that allow for thiscomplex interaction are needed and have not been used. In the future,statistical approaches for complex systems, including factor analysisand assessment of effect modification and interaction, may advanceunderstanding of the metabolic factors underlying body size andcancer associations.

Obesity, end Body Ccmposi t ion 423

COLORECTAL CANCER

Summary of F indings

Data from case-control and cohort studies provide convincing evi-dence of an approximately twofold increase in risk of colon canceramong men with a BMI of 30 or more. Risk estimates for men aremost commonly reported to be about 2. Among women, less exten-sive data provide evidence of a probably increased risk of colon cancerfrom a high BMI, with risk estimates usually between 1.0 and 1.5.Among obese women who are estrogen positive (defined as pre-menopausal or postmenopausal and taking hormone replacementtherapy [HRT]), a twofold increase in risk has been reported. Most ofthe literature has found no association between BMI and rectal cancer.Meta-analyses that provide a more quantitative statement of the asso-ciation across several studies have not been published.

Overview

Many aspects of the associations between body weight, obesity, andcolorectal cancer have been examined. Colorectal cancer has beenstudied by examining risk associated with colon and rectal cancerscombined, as well as for each site separately. Although many studieshave examined associations with colon cancer, few have consideredrectal cancer specifically. Additionally, unlike many cancers, associa-tions between body size and the precursor lesion, adenomatous polyps,have been reported. Several consistent differences in associations bygender, site, and location within the colon have been observed.Stronger associations have been observed for men than for women;for colon than for rectal cancer; and, within the colon, for distal thanfor proximal tumors.

Studies examining the associations between body size, obesity, andcolorectal cancer have used many different indicators of body size.Most studies have relied on BMI, usually from several years beforediagnosis. Few studies have used the current WHO criteria for over-weight (BMI 2 25) and obesity (BMI > 30), making comparisons andinterpretations across studies difficult. Most studies have categorizedBMI based on distribution in the population, and although the lowerlimit for the upper category of BMI is often near 30, at other times itis around 26. Limited data exist on waist and hip circumferences asindicators of fat pattern and its impact on colorectal cancer risk. Moststudies focus on adult BMI, with little information available on weightchange or early life body size as possible predictors of risk. Becauseof differences in reported associations for colon and rectal cancer, evi-dence for these sites is summarized separately.

Colon Cancer

Epidem io logyMany studies have evaluated associations between body size andcolon cancer, and reported associations have been fairly consistentacross case-control and cohort studies. Studies that have examinedassociations with obesity report slightly stronger associations thanthose for overweight. For men, most studies report significantincreased risk, with risk estimates of 2.0 or greater, although risk esti-mates range from 1.2 to 3.0 (Graham et al., 1978; West et al., 1989;Gerhardsson de Verdier et al., 1990 Le Marchand et al., 1992: I*eand Paffenberger, 1992a; Giovannucci et al., 1995; Caan et al., 1998;Singh et al., 1998; Schoen et al., 1999) (Figures 22-Ia and 22-lb).Most studies have adjusted for important confounding factors, includ-ing physical activity, dietary intake, and smoking, although somereport age-adjusted estimates of association only (Lund Nilsen andVatten, 2001). Associations observed for women are generally weakerthan those observed for men and are often not statistically significant.For women, risk estimates have generally ranged from 0.7 to 2.7(Poner and McMichael, 1983; Graham et al., 1988; Kune et al., 1990;Bostick et al., I994;Dietz et al., I995;Le Marchand et al., 1997; Mar-tinez et al., 1997; Caan et al., 1998; Singh et al., 1998; Ford,1999;Terry et al., 2001, 2002). Some studies report a similar twofoldincrease in risk of colon cancer for both men and women for thehighest BMI quantile examined (approximately 30) (West et al., 1989;

424

Figure 22-1. A, Summary of risk estimates andconfidence intervals from epidemiologic studies ofBMI and colon cancer in men. B, Summary of riskestimates and confidence intervals from epidemio-logic studies of BMI and colon cancer in women.

PART l l l : THE CAUSES OF CANCER

Cohort Studies: Population-Based

Lee and Pafienbarger (1992a), USA, n=290

Le Marchand er a/. ( l 997), USA, n=azl

Chyou elal. (1994), USA, n=289

Giovanntrci el ar. (1995), USA, n-203

Singh & Fraser (1998). USA, n=59

Ford (1999), 951, n=t04

Lund Nilsen and Vatten (2001), Norway, n=234

Case-Control Studies: Hospital-Based

Russo eral. (1998), ltaly, n=687

Case-Control Studies: Population-Based

Graham er a,. (1988), USA, n=205

Gerhardsson de Verdiet et al. (1990), Sweden, n=233

wesr elal. (1989). UsA. n=112

Kune et a/. (1990), Australia, n=388

Caan eral. (1998), uSA, n=1,095

A


Bostick elal. (1994), USA, n=212

Matlinez et al. (1997), USA, n=393

Singh & Fraser (1998), USA, n=83

Ford (1999) . USA. n=l l8

fe(ry et al. (2001). Sweden, n=29t

lund Nilsen and Vatten (2001). NoMay, n=277

fefty et al. (2t02). Canada, n=383

Iefi,J el al. (2002). Canada, premenopausal, n=118

Te(ry el al. (2002), Canada, postmenopausal, n=184

Casecontrol Studies: Population-Based

Wesl efa,. (1989), USA. n=119

Gratlam et al. (1988). USA, n=223

Gerhardsson de Vedie( el al. {1990}, Sweden. n=189

Kune et al. (1990), Ausrralia, n=327

Caal' et al. (1998), USA, n=888

Slatl.ery et al. (2003), USA, estroQeo+, n=301

slanery eral. (2003), usA, estrogen-, n=576

B

Ford, 1999). Few studies have included African Americans. The onestudy reporting associations for African Americans was limited to 99cases and reported no significant association between BMI and col-orectal cancer (Dales et al., 1979).

Some studies have had sufficiently large sample sizes such thatassociations for proximal and distal colon tumors could be consideredseparately. Stronger associations for distal tumors than proximaltumors are often seen (Dietz et al., 1995; Martinez et al., 1997: Caanet al., 1998), although the study by Le Marchand et al. (1997 ) showedstronger associations with proximal rather than distal tumors, and thestudy of women by Terry et al. (2001) did not observe a significantassociation for either proximal or distal tumors. [n a study by LeMarchand et al. (1992), the greatest risk associated with a high BMIwas observed for sigmoid tumors, which most studies include as partof the distal colon.

Some studies have examined waist-to-hip ratio and colon cancerrisk (Martinez et al., 19971' Caan et al., 1998; Russo et al., 1998;

Schoen et al., L999). Similar results have been observed from bothcase-control and cohort studies, and suggest that a higher WHRincreases risk of colon cancer.

Biologica l Mechanisms and Tumor Mutat ionsAssociations between body size and colon cancer risk may be modi-fied by several factors. Interactions between BMI, physical activity,and hormones appear to provide the most insight into possible bio-logical mechanisms. High levels of vigorous physical activity havebeen shown to modify the risk associated with obesity; for example,risk is not as markedly increased among obese men and women whoare physically active (Lee and Paffenberger, 1992a; Le Marchand etal.,1997: Slattery etal.,1997). Interactions between obesity and estro-gen or HRT may explain gender differences in risk associated withBMI (Teny et al., 2002). Studies have shown that being overweightor obese increases risk of colon cancer only among women who arepremenopausal (Terry et al., 2002). In another study that examined

Obesity and Body Composi t ion 425

lr'il

estrogen-positive women (defined as premenopausal or post-menopausal and taking HRT), risks associated with a high BMI weresimilar to associations observed in men, with risk estimates for a BMIof 30 or more being twofold greater than that of women who are lean(Slattery et al., 2003). However, women who were estrogen negative(defined as postmenopausal and not taking HRT) did not experienceincreased risk from being overweight or obese. In men it has beenobserved that, with advancing age, the risk associated with beingoverweight or obese declines (Slattery et al., 2003). This change inrisk over time could be the result of declining androgen levels thatoperate in a similar fashion as estrogen in regulating risk associatedwith obesity. These interactions between physical activity and BMI,and estrogen and BMI, suggest that at least one way BMI may influ-ence colorectal risk is through its influence on estrogen and on theinteraction between estrogen and insulin.

Evaluations of the association between BMI and colon cancerthat have examined specific tumor mutations have provided insightinto possible mechanisms of action and the role of body size in pos-sible specific disease pathways. The few published studies suggest thatBMI may be involved in several pathways. One study reported that anelevated BMI was associated with Ki-ras mutations in codons 12 and13 (Slattery et a1.,2001a). The BMI associations appeared to be morespecific for Ki-ras mutations in women than in men. BMI appeared tobe equally associated with tumors with and without p53 mutations(Slattery et al., 2002). Obesity was reported as being associated onlywith tumors that were stable (i.e., negative for microsatellite instabil-ity) in women, although in men, obesity was associated with bothstable and unstable tumors (Slatterv et al.. 2001b).

Rectal Cancer

The small number of studies that have examined associations betweenbody size and rectal cancer generally report results for few cases. Fromexisting data it appears that body size is not associated with rectalcancer among men or women (Graham et al., 1988; Gerhardsson deVerdier et al., 1990; Dietz et al., 1995; Le Marchand et al.,1991: Russoet al., 1998; Terry et al., 2001). In contrast, one study of womenreported reduced risk of rectal cancer among those with a BMI of morethan 25 relative to those with a BMI of less than 22 (Potter andMcMichael, 1986). Unlike colon cancer, studies of rectal cancer havenot evaluated interactions between BMI and other indicators of bodysize with diet and lifestyle factors. This lack of examination of inter-action is most probably because of the relatively limited number ofrectal cancer cases available for analysis, making studies of interac-tion imprecise and problematic. Evaluation of BMI and other indica-tors of body size with specific mutations in tumors have not beenreported.

Colorectal Adenomas

Studies evaluating the association between body size and the occur-rence of adenomas have examined associations by polyp size and type.Most studies of colorectal adenomas have examined BMI alone andhave observed similar associations as for colon cancer (Neugut et al.,1991; Shinchi et al., 1994: Davidow et al., 1996; Giovannucci et al.,1996). Some studies do not detect associations with adenomas andbody size (Terry et al., 2001,2002). In a study that included bothcancer and adenomas, an increased risk with a high BMI was observedfor large adenomas only, but not for colorectal tumors (Boutron-Ruaultetal.,2001). Most studies have observed a 1.5- to 2.5-fold increase inrisk of adenomas among the group with the highest BMI. A large WHRalso has been associated with adenomas, with stronger associationsbeing observed for larger adenomas (Kono et al., l99l; Shinchi et al.,1994; Kono et al., 1999). Similar to studies of rectal cancer, studiesof adenomas have been limited in terms of examining interactions withother diet and lifestyle factors, primarily because of small sample sizesavailable to examine interactions. One study by Martinez et al. (1999)observed no differences in risk for adenomas amons those with andwithout Ki-ras mutations.

ADENOCARCTNOMAS OF THE ESOPHAGUS (AE) ANDGASTRTC CARDTA (AC)


Data from case-control and cohort studies provide evidence of a prob-able and fairly consistent association of a twofold or greater increasedrisk of adenocarcinoma of the esophagus and gastric cardia from over-weight and obesity. Most studies have evaluated risk using a BMI ofaround 30 or more as the upper level of BMI, although some studiesuse a much lower BMI as the upper level. The increased risk associ-ated with obesity has been observed in both men and women. Meta-analyses that provide a more quantitative statement of the associationacross several studies have not been published.

Epidemiology

The incidence of adenocarcinoma of the esophagus and gastric cardiahas risen dramatically in the past two decades in developed nations(Li and Morbahan, 2000; Walther et al., 2001). For reasons not entirelyclear, body size and obesity are associated with AE and AC, with theincreases in the incidence of these diseases paralleling the increasesin obesity observed in Western cultures.

An important feature of the observed associations between AE andAC and body size is that they are limited to adenocarcinomas and gen-erally are not observed for squamous cell cancer or other histologicaltypes (Vaughan et al.,1995, Chow et al., 1998; Lagergren et al., 1999).However, one study reported a sixfold increased risk of squamous cellesophageal tumors and no increased risk of AE or AC adenocarcino-mas among individuals with a high BMI (Kabat et al., 1993).

In some studies, tumor location seems an important feature for AC,with associations stronger for tumors located more distally (Ji et a1.,1997). Associations have remained after adjustment for important con-founding factors, such as cigarette smoking and diet (Brown et al.,1995; Chow et al. , 1998; Wu et a1., 2001).

Most studies show stronger associations for AE than for AC (Figure22-2); risk estimates are inconsistent and range from the null to sixfoldor greater with BMIs of 27 or higher. The study by Lagergren et al.(1999) revealed that associations were stronger forAE (OR = 7.6;95VoC. I . , 3 .8-15.2) than for AC (OR = 2.3 ;95Vo C.1. , 1 .5-3.6) ; amongpeople with a BMI of more than 30, the odds ratio was 16.2 for AE(95Vo C.1., 6.341.4). In some instances, the reported BMI level atwhich a risk is observed is modest. For example, in one study of AEin British women, a sixfold increased risk was observed for a BMIhigher than 22.7 (Cheng et al., 2000). In the study by Chow et al.(1998), a three- to fourfold increase in risk of AE and a twofoldincrease in risk of AC was observed with a BMI of about 27.5 orgreater. Limited data support a dose-response effect, with higher BMIsresulting in higher risk. Wu et al. (2001) observed a significant dose-response, with risk increasing as BMI increased during all periods ofadult life (i.e., for BMI at ages 20, 40, and recent adult BMI). Weightgain of 46 pounds or more was shown to be as important a predictoras weight i tself (Ji et al. , 1997; Chow et al. , 1998).

Body size at young age and 20 years before diagnosis also appearto be important contributors to risk (Ji et al., 1997;Lagergren et al.,1999).In some studies, the risk estimates observed for body size atyounger ages are larger than those for recent body size. In the studyof British women reported by Cheng et al. (2000) BMI at age 20 yearsappeared to be an important contributor to risk. In addition, associa-tions have been reported as stronger for nonsmokers than smokers, andfor younger people (<59) than older people, and as similar for thosewith and without gastroesophageal reflux disease, for men and women,and for various levels of education (Lagergren et a1., 1999; Tretliet al., 1999).

Biological Mechanisms

The underlying biological mechanisms for the association betweenBMI and AE/AC are not clear. Although it has been proposed that themechanism involves esophageal reflux, limited data show that the risk

426 PART III: THE CAUSES OF CANCER

Gohorl Studies

Tretli & Robsahm (1999), Norway, males, n.94

Tretli & Robsahm (1999), Norway, females, n=25


Kabatelal. (1993), USA, males, n=121

Thang et al- (1996), USA, males and females, n=95

Gaius etal (2001), ltaly, Switzerland. tefiales, n=114

Inoue elal. (2002), Japan, females. n=365

Case0ontrol Studies: Population-Based

Btown et al. (1995), USA, males, n=l6l

Vaughan efal. (1995), USA, AE, males and fema,es, n=131

Vaughan eral 0995), USA, AC, males and females. n=164

Ji ela,. (1997), China, AC. males, n=]48

Ji e, al 0997), China, AC, females, n=37

cnow et al. (1998), USA, AE, males, n=244

chon et al. (1998), usA, AE, females, n=48

chow elal. (.|998), usA,Ac, males, n=223

Chow etal 0998), USA.AC, females, n=38

Figure 22-2. Summary of risk estimates and confi-dence intervals from epidemiologic studies of BMIand esophageal or gastric cardia adenocarc.inoma inmen and women.

associated with BMI is the same for those with and without sympto-matic reflux disease (Lagergren et al., 1999). Other hypotheses forobesity potentially increasing risk include effects of diabetes orinsulin-related mechanisms (Cheng et al., 2000), and the delay inesophageal motility associated with obesity (Li and Mobarhan, 2000).

RENAL CELL CANCERSummary of Findings

Data from case-control and cohort studies provide convincing evi-dence of a consistent association of increased risk of renal cell cancerfrom overweight and obesity that is greater in women than in men.Estimates from a meta-analysis that calculated risks for men andwomen combined suggest this increase in risk corresponds to a 36Voincrease for an overweight person and an 84Vo incrcase for an obeseperson (Bergstrom et al., 2001).

Epidemiology

Risk for renal cell cancer is increased in heavier men and womenin virtually all studies (Wynder et al., 1,974:McLaughlin et al., 1984,1992; Goodman et al. , 1986; Yu et al. , 1986; Asal et al. . 1988:Kadamini et al., 1989; Maclure and Willett. 1990; Partanen et al.,l99l; McCredie and Stewart, 1992; Benhamou et al., 1993; Finkleet al., 1993; Kreiger et al., 1993; Hiatt et al., 1994; Lindblad er al.,1994; Mellemgaard et al., 1994, 1995; Muscat et al., 1995; Chowet al., 1996, 2000; Boeing et al., 1997; Yuan et al., 1998). The oneexception is a hospital-based case-control study (Talamini et al., 1990)(Figures 22-3a and 22-3b). In contrast, no association between bodysize and tumors of the renal pelvis has been demonstrated (McCredieand Stewart, 1992; Chow et al., 2000). Most studies demonstrate alinear dose-response relationship between body weight or BMI andrenal cell cancer. However, the increase in relative risk appears to behigher for women than for men, perhaps best demonstrated in thelargest multicenter study that included men and women (Mellemgaard

Lagergren etal. (1999), Sweden.AE, males and females, n=]89 (RR=7.6)

Lagergren et at (1999), Sweden, AC, males and females, n=262

Cheng el r/. (2000). United Kingdom. AE, females, n=68 (RR=6 0)

Wu eI al. (2001), USA, AE, males and lemales. n=2'12

Wu ef ai (2001), USA, AC. males and females, n=266

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et al., 1995). In that study, the relative risk for women in the top quar-tile of BMI was 2.2 compared to a risk of 1.2 for men in the top quar-tile of BMI. A similar pattern was observed in the very obese group,with higher increases in risk observed for women compared with men.For very obese women with a BMI in the top 57o (>38.1), risk wasmarkedly increased to 3.6. In contrast, for a similar group of veryobese men, risk was 1.6. In a meta-analysis including I I studies, riskof incident renal cell cancer was increased by 67o and 7Vo for eachunit increase in BMI for men and women, respectively (Bergstrdmet a1.,2001). This increase in risk corresponds to a 367o increasein risk for an overweight person and an 84Vo tncrease for an obeseperson.

Data are limited on adult weight gain and renal cell cancer, and theyhave not been reported except for three studies. In a 1995 multicenterstudy, Mellemgaard et al. (1995) examined the slope and variability(coefficient of variation) of BMI, two measures that investigators haveconceptualized as representing the rate of weight gain and frequencyof weight fluctuations, respectively. In this study, the rate of weightchange appeared to be an independent predictor of risk for women butnot for men, though the coefficient of variation of BMI was not asso-ciated with renal cell cancer after adjustment for BMI in women. Oneother study. by Chow et al. (2000), examined the association of changein BMI over a period of 6 years and renal cell cancer risk in men andfound a non-statistically significant increased risk of 1.6 with anincrease in BMI of 2.5 units. Addit ional ly, Bergstrdm et al. (2001)observed that weight gain. especially among subjects with high BMIat age 20 (OR = 1.9, C.I. , 1.2-3.0), was associated with an increasedrenal cancer risk.

A number of other factors, including hypertension, diabetes melli-tus, and tobacco use, have been consistently associated with risk ofrenal cell cancer. Each of these factors is related to obesity: Obesityis positively and causally related to hypertension and diabetes melli-tus, and tobacco use is associated with leanness. A lirnited number ofstudies of obesity and renal cell cancer have adjusted for hyperten-sion and/or smoking (Kreiger et al. , 1993: Behnamou et al. , 1993;Mellemgaard et al. , 1994; Muscat et al. , 1995; Chow et al. , 1996,

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Cohort Studies

Hiatt et al. (1994), USA, n=163

Chow ela l (2000) , Sweden, n=759


Goodman e la l (1986) , USA, n=173

Benhamou e la l . (1993) , France, n=138

Muscat er a l ( '1995) . USA. n=543


McLaughlin et al. (1984), USA, n=310

Asal eta l ( r988) , USA, n=209

Maclure & Wi l le( (1990) , USA, n=135

McCredie & Stewart (1992), Ausrralla, n=307

McLaughlin et al.(1992), China, n=76

Kreiger era l (1993) , Canada. n=282

Lindblad et al. (1994). Sweden, n=207

Mellemgaard et al. (1994), Denmark, n=225

Chow e1r l (1996) . USA. n=27a

Yuan et at (1998) , USA, n=781

A

Cohort Studies

Finkle et al. (19€3), USA, n=161

Hia[ er al (1 99a), USA, n=88

Case4onhol Studies: Hospital-Based

Goodman et al. (1986), USA, n=71

Benhamou el at ('1993), France, n=58

Muscar elal (1995), USA. n=2a5

CaseControl Studies: Population.Based

McLaughlin eta,.0984), USA, n= 178

Asal et at. (1988), USA, n=100

Maclure & Wilbn (1990), USA, n=68

McCredie & Steilarl (1992), Australia, n=I73

McLaughlin el ar. (1992). China, n=58

KJeiget et al. (1993). Canada, n=181

Linduad efal (1994), Sweden. n=172

Mellemgaard elat (1994), Denmark, n=141

Chof/ et at. (1996), USA. n=1 63

Yuan et al. (1998). USA, n=a23

B

2000). However, none has fully explored potential interactions amongthese factors. Limited data suggesr that risk from obesity is higheramong heavier men and women with hypertension (Muscat et al.,1995) and who are nonsmokers (Chow et al., 2000). A limited numberof studies have found amphetamines, used in the treatment of obesityand other conditions, to be positively associated with renal cell cancer(Wolk et al., 1996).


The precise mechanisms by which higher body mass might influencerenal cell carcinogenesis are not clearly defined. Hormonal factors,particularly sex steroids, have been found to promote renal cell pro-liferation and growth by direct endocrine receptor-mediated effects(Ronchi et al., 1984), by regulation of receptor concentrations (Traish


Figure 22-3. A, Summary of risk estimates andconfidence intervals from epidemiologic studies ofBMI and renal cell cancer in women. B, Summaryof risk estimates and confidence intervals from epi-demiologic studies of BMI and renal cell cancer inmen.

et al., 1987), or through paracrine growth factors (Concolino et al.,1989). In a 1996 review on nutrition and renal cell cancer, Wolk et al.(1996) also proposed the hypothesis that the metabolic syndrome asso-ciated with upper body obesity, including hypertension, glucose intol-erance, increased levels of insulin-like growth factor (IGF), and inwomen, anovulation and increased androgen production, might resultin renal damage that would increase the susceptibility of the kidneyto other carcinogens.

ENDOMETRIAL CANCERSummary of Findings

Data from case-control and cohort studies provide convincing evi-dence of a consistent association of increased risk of endometrial

cancer from overweight and obesity with a doubling to tripling of riskobserved among obese women. The lifetime risk of being diagnosedwith endometrial cancer in the United States is about 3Vo, whereasthe cumulative risk increases to 97o to lj%o in obese women(Schottenfeld, 1995). Based on the prevalence of obesity (Flegal et al.,2002) and estimates of relative risk in U.S. women, excessive weightand a central pattern of fat distribution may account for ITVo to 467oof endometrial cancer incidence in postmenopausal women. Datasuggest that obesity may account for about 40Vo of the worldwidevariation in cumulative rates of endometrial cancer (IARC, 2002).Meta-analyses that provide a more quantitative statement of theassociation across several studies have not been published.

Epidemiology

Adenocarcinoma of the endometrium is the most common cancer ofthe female reproductive organs. International variation in endometrialcancer rates may represent differences in the distribution of knownrisk factors, which include obesity, hormone replacement therapy(HRT), ovarian dysfunction, diabetes mellitus, infertility, nulliparity,and tamoxifen use (Purdie et al., 2001). Comparisons of cumulativerates (ages 0-84) of endometrial cancer with reported data on theprevalence of obesity among women in developed and developingcountries suggest that obesity may account for about 40Vo of theworldwide variation in cumulative rates of endometrial cancer(Akhmedkhanov et al., 2001). Thus, a substantial portion of the inter-national variation in the incidence of endometrial cancer could beexplained by differences in the prevalence of obesity.

A consistent positive association between obesity and endometrialcancer risk has been observed in most cohort studies focusing onthis association (Ewertz et al., 1984:' Folsom et al., 1989, Tretliand Magnus, 1990; Le Marchand et al. , l99l; Moller et al. , 1994;Tcirnberg and Carstensen, 1994:'Teny et al., 1999; Jain et al., 2000;Furberg and Thune, 2003). Excess risk persists even after adjustmentfor several factors, such as parity, HRT, and smoking (Le Marchandet a l . . l99 l : Ja in e t a1. .2000) . Both Le Marchand et a l . (1991) and

428

Figure 22-4. Summary of risk estimates and con-fidence intervals from epidemiologic studies ofBMI and endometrial cancer.

PART l l l : THE CAUSES OF CANCER


Ewenz et al. (1984), Denmark. n=t t 5

Tretli & Magnus (1990). Norway, n=2,208

Le Marchand eta l - (1991) , USA, n=214

Malle( et al. (1994). Denmark, n=il 4

Ieffy et al- (1999), Sweden, n=133

)ain et al. (2000), canada, n=221


La Vecchia elal (1984), ltaly, Postmenopausal, n=283

La Vecchia el a/. (1 984). ltaly, Premenopausal, n=283

Koumantaki eral. (1989), Greece, n=83

Austin errl. (1991), USA. n=l68

Inoue e l a l (1994) , Japan, n=143

CaseControl Studies: Population-Based

Casagrande e( al. (1979), USA. n=150

Shu etal (1992), China. n=268

Br inron e la l (1992) , USA, n=405

Swanson e l a l (1993) , USA, n=405

Olson era l (1995) , USA, n=232

Sholl & Newcomb (1998), USA, n=723

Weiderpass et al. Qcf,q, Sweden, n=709 (RR=6.3)

Bea'd et al. (2000), USA. n=1 1 7

Xu (2002) , Chrna, n=497

Tdrnberg and Carstensen (1994) observed a stronger associationbetween body mass index and endometrial cancer risk with increasingage than have others (Furberg and Thune, 2003). In a study of 47,003women who were older than 55 years at entry and followed for 25years, Tornberg and Carstensen (1994) observed a threefold increasedrisk (RR =3.16; P < 0.0001) when comparing heavy to lean women(BMI 2 28 vs. BMI > 22).

Consistent with the observation from cohort studies, mosf case-control studies (Blitzer et al., 1976, La Vecchia et al., 1984, l99l',Lap idus et a l . , 1988; Aust in e t a l . , l99 l ; Shu et a l . , l99 l ; Br in tonet al. , 1992:Levi et al. , 1992; Shu et al. , 1992; Swanson et al. , 1993:Inoue et al. , 1994; Olson et al. , 1995; Baanders-van Halewyn et al. .1996; Kalandidi et al., 1996; Shoff and Newcomb et al., 1998) exceptthree (Koumantaki et al., 1989; Parslov et al., 2000; Beard et al., 2000)observed that women with a BMI of 25 or higher have a two- to three-fold increase in risk (Figure 224). High BMI was associated with aneven greater excess risk in a study in Hawaii that included Japanese,Caucasian, native Hawaiian, Filipino, and Chinese populations(Goodman etal. , l99l). Compared to lean women (BMI <21,.1), over-weight women (BMI > 27.3) had a fourfold increased risk (RR = 4.3,P < 0.0001). Another large, informative Swedish case-control studywith 709 endometrial cancer cases found an even larger increased riskof endometrial cancer with increasing weight (Weiderpass et al.,2000). Compared to lean women (BMI < 22.5), obese women (BMIof 3G-33.99) had a threefold increased r isk (OR =2.9, C.1., 2.0-4.0).and markedly obese women (BMI > 34) a sixfold increased risk (OR= 6.3, C.L, 4.2-9.5). The effect of BMI did not vary by age.menopause, or use of contraceptives. Thus, a linear increase in riskwith increasing BMI has been observed.

Weight gain during adulthood is especially interesting, and studiesshow a linear dose-response relationship between weight gain andendometrial cancer (Le Marchand et al., l99l; Shu et al., 1992,Swanson et al., 1993; Olson et al., 1995; Teny et al., 1999). Two ofthese studies did not adjust for young adult weight or BMI (Swansonet al., 1993; Olson et al., 1995). The studies that adjusted for youngadult or baseline weieht or BMI found differine results. [n two studies

=___-_{-

-

t

_-_--------{-----------t-

--|-

-------f-

that adjusted for either adolescent or early adult weight or BMI. theassociation between adult weight ,eain and endometrial cancerremained after adjustment (Le Marchand et al., 1991; Xu et a1.,2002).ln one other study, adjustment for baseline weight eliminated the asso-ciation between adult wei-eht gain and endometrial cancer (Teny et al.,1999).In one study in Shanghai. weight loss from ages 20 to 30 wasinversely associated with endometrial cancer risk (Xu et al., 2002).

The distribution of body fat, including such measures as skinfold(subscapular) and WHR, also has been examined in several studies(Folsom et al. , 1989; El l iott et al. . 19901 Austin. 1991 ; Schapira et al. ,l99 l ;Shu et a l . , 1992: Swanson et a l . . 1993) . Ev idence suggests thatfat distribution may be important in endometrial cancer, with upper-body obesity particularly increasing risk. A case-control study fromShanghai found that the distribution of subscapular skinfolds was abetter predictor for endometrial cancer risk than WHR, even afteradjustment for BMI (Shu et al., 1992).

Interaction between obesity and physical activity has been proposedas one explanation for the observation that some studies have observeda stronger positive association between obesity and endometrial cancerrisk in older than younger wolnen (Le Marchand et al., 1991: TOrn-berg and Carstensen. 1994). This finding is consistent with some pop-ulation evidence that older women are less active than younger women(IARC, 2002). Recently, the established link between diabetes andendometrial cancer risk suggests that hyperglycemia (Furberg andThune, 2003) and hyperinsulinemia (Weiderpass et al., 2000;Anderson et al., 2001) mav influence risk.


Changes in metabolism and hormonal activity that occur in obesitymay be importanl mechanisms that explain the biologically plausiblelink between increased endometrial cancer risk and obesity. Thenormal menstrual cycle reflects the complex balance between the pro-liferative actions of estrogen and the antiestrogenic and secretorytransforming actions of progesterone on the endometrium (Hale et al.,2002). A shift to a positive energy balance might contribute to an unfa-vorable sex hormone profile in women (Key et a1.,2001; Jasienskaet a l . , 2001) .

Among premenopausal women, obesity may induce a progesteronedeficiency during the luteal phase as a result of anovulatory cycles,amenorrhea, and irregular menstrual periods. This situation may leadto an increased proliferation and decreased desquamation of endome-trial cells. Among postmenopausal women, several lines of evidencesuggest that obesity is associated with increased lifetime exposure toestrogen that may also increase risk: increased aromatization of andro-gens (androstenedione) to estrone in adipose tissue (Key and Pike,I 98 8a; Zeleniuch-Jacquotte, 200 I ), increased secretion of androstene-dione in adrenal glands, and decreased sex hormone binding globulin(SHBG), resulting in an increase in bioavailable estradiol (free andalbumin bound). Therefore, through different mechanisms for pre- andpostmenopausal women, obesity alters sex steroid concentrationand metabolism in ways that increase endometrial cancer risk.

Experimental and epidemiological evidence suggest that insulin-likegrowth factor-l (IGF-I), a hormone with strong mitogenic and anti-apoptotic actions, may be important in endometrial carcinogenesis. Ahigh BMI may alter IGF-I blood levels, although this has not beenexamined in studies of endometrial cancer risk. In addition, energyrestriction is known to enhance DNA repair, moderate oxidativedamage to DNA, and reduce oncogene expression (Lipman et al., 1989).

Another possible biological mechanism is related to the establishedlink between diabetes and endometrial cancer (Furberg and Thune,2003) and the fact that obesity is associated with insulin resistance,hyperinsulinemia, and diabetes mellitus. Evidence is increasing thatinsulin is a growth factor for tumor formation (Yu and Rohan, 2000).The mechanisms underlying insulin-mediated neoplasia may includeenhanced DNA synthesis with resultant tumor cell growth, inhibitionof apoptosis, and an altered sex hormone milieu. Hence, in overweightand obese women, coexisting metabolic disturbances may act syner-gistically to facilitate malignant transformation of glandular endome-trial cells.


OVARIAN CANCER


The results from cohort and case-control studies do not indicateany clear association between overweight or obesity and epithelialovarian cancer risk. Several recent studies, however, suggest a possi-ble posit ive associat ion.

Epidemiology

Epithelial ovarian cancer incidence varies between countries andwithin countries and ethnic groups, but only a small percentage hasbeen attributed to family history. The majority of ovarian cancer issporadic, suggesting that part of the disease may be explained by mod-i fi able lifestyle-related factors.

In contrast to some cohort studies that found no association betweenolder adult obesity and ovarian cancer (Mgller et al., 1994; Tornberget a1., 1994; Mink et al., 1996; Fairfield et a1.,2002), two studies (Lewand Garfinkel,1979, Fairfield etal.,2002) have observed a direct asso-ciation between obesity at some ages and ovarian cancer incidence. Ina recent report from the Nurses Health Study with 402 cases of epithe-lial ovarian cancer (Fairfield et al., 2002), a twofold increase in pre-menopausal ovarian cancer risk was found among women with a BMIat age 18 of 25 or higher compared to a BMI less than 20. However,no association between recent BMI or adult weight change and ovariancancer risk was observed in this study.

An inconsistent association also has been observed in case-controlstudies (Figure 22-5). Only six of these studies (Casagrande et a1.,1979; CASH, 1987; Farrow et al. , 1989; Purdie et al. , 1995; Mori etal., 1998; Lubin et al., 2003) found a direct association, whereas otherstudies found no association (Shu et al., 1989; Hartge et al., 1989;Mink et al.,1996: Ness et al., 2000; Greggi et al., 2000; Lukanova etal., 2002) and some a negative association (Byers et al., 1983; Par-razzini et al., 1997; Riman et a1.,2001). One case-control study thatfound no association between BMI and ovarian cancer did observe astatistically significant increased risk with elevated WHR (Mink et al.,1996).


Several reproductive factors, including the number of pregnancies,early menarche, late menopause, and late first pregnancy, influenceovarian cancer risk and could potentially play a role in theobesity-ovarian cancer risk association. All of these factors except forthe number of pregnancies may increase risk. Thus, it is plausible thatobesity may influence ovarian cancer risk through changes in sexsteroids levels. However, at present the epidemiologic data have notestablished consistent direct association between overweisht orobesity and ovarian cancer.

BREAST CANCER

Summary of Findings

Extensive data from case-control and cohort studies provide convinc-ing evidence of a modest increased risk of postmenopausal breast cellcancer from overweight and obesity and a larger twofold increase inrisk for adult weight gain. Estimates from a meta-analysis of cohortstudies found gradual increases in risk of postmenopausal breastcancer to a BMI of 28, after which risk did not increase further. Therelative risk for a BMI of 28 compared with a BMI of less than 21was I .26 (van den Brandt et al., 2000). However, risk estimates varyby age at diagnosis, history of HRT, and estrogen receptor status ofthe tumor. Another meta-analysis found that this increased risk forpostmenopausal breast cancer corresponded to a I2Vo increase foran overweight woman and a 25Vo increase for an obese woman(Bergstrdm et al., 2001). Data show a stronger association for adultweight gain, with a doubling of risk among women who have neverused HRT and who gained over 20 kg from age 18 (Huang et al.,1997). A meta-analysis of cohort studies found an inverse association

430 PART l l l : THE CAUSES OF CANCER

Cohort Shdies: Poputation-Based

Mollet el al. (1994), Denmart, n=58

Tdrnberg & Cartensen (1994), Sweden, n=330

Mink er a/. (1996), USA, n=97

Faifield et al. (2002). USA, n=4OZ

Case'Control Studies: Hospital.Based

llton et al. (1988). Japan, n= 1 t0

Paraztini elal. (1997), ltaly, n=971

Mon et al. (1998), Japan, n=89

Gase'Control Studies: Population-Based

Faftw eI al. (19$1, USA. n=27t

Shu el a/. (1989), China, n=1 ?2

Pu'die et al. (19951, Australia, n=824

Ness eral. (2000), usA. n=767

Riman et a/. (2001), Sneden, AI histdogb types, n-.|93

Rirnan etar. (200'l), Sweden, Serous, n=l93 (RR=6.5)

Riman ef a/. (2001), Sweden, Mucinous, n=193

Lukanova etal.(20021, USA, Sweden, ltaty, n=122

Lubin etal (2003), lsrael. n=1,269

Figure 22-5. Summary of risk estimates and confi-dence intervals from epidemiologic studies of BMIand ovarian cancer.

between BMI and premenopausal breast cancer, with a relative risk of0.54 for women with a BMI higher than 3l compared with womenwith a BMI of less than zl (van den Brandt et a1.,2000). This esti-mate is consistent with the reduction in risk of 0.6 to 0.7 observed inmany studies and does not appear to be present for BMIs less than 2g.An extensive literature on breast cancer prognosis and survival sug-gests that women who are heavier at the time of diagnosis and galnw_eight following diagnosis experience a worse prognosis inespectiveof menopausal status at diagnosis.

Epidemiology

Animal model research in the 1930s first examined the hypothesisthat a positive energy balance increased risk for breast cancer(Tannenbaum, 1940a, 1940b). The epidemiological evidence onweight or BMI and breast cancer risk varies by menopausal status(Figures 224a and 224b), age at diagnosis, hormone r...pto, statusof the breast cancer, and exposure to exogenous estrogens. Becausestudies of breast cancer have used so many different BMI cutpointsthat are not consistent with current wHo criteria of overweight andobese, the following review uses the term heavier women rodescribe the upper BMI groups rather than the terms overweight andobese. The most informative studies have distinguished betweenpre- and postmenopausal breast cancer; examined the effect of weight,weight gain, and central body fat at various ages; and have examinedthe differential effects of endogenous and exogenous estrogens. withthe emergence of a possible lGF-mediated pathway fbr severalcancers, recent studies have also begun to explore the potentialinteractions of IGF with body size.

Most studies find that heavier women have a decreased risk ofpremenopausal breast cancer (Paffenbarger et al., l9g0; willett et al.,1985; Hislop et al., 1986; Le Marchand et al., lggga; London er al.,1989; Swanson et al., 1989; Tretli, l9g9; Bouchardy et al., 1990;Brinton et al, 1992 Harris et al., 1,992:pathak et al., rigz; vanen andKvinnsland, 1992; Tdrnberg and carstensen, 1994; Francheschi et al.,1996; Swanson er al., 1996: Huang et al., 1991; Chie et al., l99g;Coates et al., 1999; Peacock et al., 1999; Enger et al., 2000; Hallet a1.,2000; de vasconcelos et a1.,2001; Friedenreich et a1.,2002).other studies find no association between BMI and premenopausalbreast cancer (Hirose et aI. ,2001;Shu et al. , 2001; yob et a1.,20011.Relative risks of approximately 0.6 to 0.7 have been reported whether

weight or BMI is assessed at the time of diagnosis or at earlier timesduring childhood, adolescence, or adulthood (Hislop et al., l9g6;Kolonel et al., 1986; London er al., 1989; Brinton er al., lgg}). Earlystudies suggested that the protective effect among heavier women waslimited to early-stage disease due to poorer detection of small tumors(Willett et al., 1985; Swanson et al., 1989). However, subsequentstudies in these same groups suggest that detection bias does notexplain the increased risk for breast cancer observed among leanpremenopausal women (London et al., 1989; Brinton et al., 1992:swanson et al., 1996). A large case-control study of 1588 cases foundthat risk was increased about twofold among women who were talland thin compared with women who were heavy and short (swansonet al., l'996). A mera-analysis of seven cohorts comprising 723 inci-dent cases of invasive breast cancer in premenopausal women foundan inverse association between BMI and premenopausal breast cancer;the relative risk was 0.54 for women with a BMI higher than 3l com-pared to women with a BMI less than2l (van den Brandt et al., 2000).This estimate is consistent with the reduction in risk of 0.6 to 0.7observed in many studies and does not appear to be present for BMIsless than 28.

conversely, most studies have found that heavier women are atincreased risk of postmenopausal breast cancer (Valaoras et al., 1969;de Waard et al., 1974; Choi et al., 1978; paffenberger et al., l9g0;Kalish, 1984; Lubin et al. , 1985; Hislop er al. , 1986; Kolonel er al. ,1986; Le Marchand er al. , 1988a; Negri et al. , 1988; Tao et al. , lggg;Ingram et al., 1989; Tretli et al., 1989; Folsom et al., 1990; Hseihet al. , 1990;Parazzini et al. , 1990;Chu et al. , l99l;Harris etaI.,1992;Pathak et al., 1992; Sellers et al., 1992,2002; Radimer er al., 1993;Francheschi et al., 1996; Yong et al., 1996; Ziegler et al., 1996;Trentham-Dietz et al., 1997; Chie et al., 1998: Galanis er al., l99g;Magnusson et al. , 1998; Enger er al. , 2000; Hall er al. , 2000; Lamet al., 2000: Li et al., 2000: Trenrham-Dietz et al., 2000: Shu et al.,2001; Yoo et al., 2001; Friedenreich et al., 2002; Wenten et al., 20A2:Lahmann et al., 2003). A meta-analysis of seven cohorts comprising3208 cases of invasive postmenopausal breast cancer found gradualincreases in risk to a BMI of 28 after which risk did not increasefurther; the relative risk for a BMI of 28 compared with a BMI of lessthan2l was I .26 (van den Brandt et al., 2000). The majority of studieson BMI and breast cancer risk have adjusted for major breast cancerrisk factors, including reproductive factors. Few studies have exam-ined in detail the effect of confoundins or interactions with diet and

*::lri1:1+';' t i i, i i

Cohort Studies: Hospital.Based

Yoo el al. (2001), Japan, n=1,151

Cohorl Studies: Population-Based

LeMarchand el a,. (1988b), USA, age 30,49, n=149

LeMarchand et a/. (1988b). USA, aqe 45-49, n=141

Tretli (1989), Norway, n=5,1 22

Vatlen & Kvinnsland (1992), Norway. n=291

Huang el al (1991), USA, n= 1,000

Manjer et al. (2001), Sweden. n=112

Van Den Brandt et al. (20N\, Pooled analysis of I studies. n=3,208

Case.Control Studies: Hospital.Based

Hsieh elal. (1990). Intemational, n=3,993

Franceschi etal. (1996), ltaly, n=988

Chie et al. (1998), Taiwan, n=334

de Vasconcelos et a/. (2001 ). Brazil, n=1 77

Hirose et a/. (2001). Japan. no family history, n=861

Hirose e, a/. (2001), Japan, family history n=65


Hislop et al (1986), Canada, n=306

Chu er a l (1991) , USA. n=2.053

Brinton & Swanson (1 992), USA, n=41 4

Swanson etd l (1996) , USA, n=I ,588

Yong el al (1996), USA, n=226

Liegler et al. (1996), USA, n=421

Coales el al (1999), USA, n=1,590

Peacock etal (1999), USA, n=845

Enger etal. (2000), usA. n=400

Hall elal (2000). USA, 8lack. n=389

Hall et al. (2000), usA, whire, n =389

Shu eral. (2001), China, n=1,459

Friedenreich el al.(2002\, Canada, n=462

A

__+_-._|-

--|-

Cohoil Srudies: Hospital-Based

Yoo eta l (2001) , Japan, n=l ,154

Cohort Sludies: Population-Based

Le Marchand el a/. (1988a), USA, age 50-51, n=145

Le Marchand et at (1988a), USA, age 55-65, n=l 35

Tretli (1989). Norway. n=5,122

Sellers etal (19S2), USA, no family history n=469,

Sellers et al (1992), USA. family history, n=469.

Huang e l a l (1997) , USA, n=1.517

Manjer el a[ (2001), Sweden, n=112

Sellers et al (2002), USA, no family history, n=1.874

Sellers el al (2002), USA, family history, n=1.874

Lahmann et al. (2W31, Sweden. n=246

Van Den Erandt et al. (200fJ1, Pooled analysis of I studies, n=3,208

Case'Control Studies: Hospital-Based

Hsieh et a/. (1 990), International, n=3,993

Hams er al. (1992), USA, n=412

Francheschi el rt (1996), ltaly, n=988

Chie el al. (1998), Iaiwan. n=334

Lam et al. (2000), USA, n=529

de Vasconcelos elal (2001), Erazil, n=177

Hirose et al (2001), Japan. no lamily history. n=604

Hirose el al (2001 ), Japan, family history, n=44


Hislop et al (1986), Canada, n=306

Kolonel el al (1986). USA, Japanese, n=272

Kolonel el al (1986), tlSA, white, n=272

chu et al. (1991), usA, n=2.053

Erinton & Swanson (1992), USA, n=414

Yong ef al (1996), USA, n=226

Galanis ef a,. (1998), USA, n=292

Magnusson et at (1 998). Sweden, n=2,904

Enger er al (2000). USA, n=a00

Hall et al. (2000), USA, 8lack, n=3gl

Hall et al. (2000), USA, White, n=391

Li et al. (20001, usA, n=479

Trentham-Dieiz et al. (20M1,. USA, n=5,659

Shu e,a l (2001) . China, n=1.459

Wenten e la l (2m2), USA. Hispanic , n=315

Wenten et al (2002), USA, non-Hispanic White, n=372

Friedenreich et al. (20021, Canada, n=771

B

I

_--t-

--'|-

-_|-

_--+|-

-_.|-

-__t-

---l_

_.----|--

_--l--

-|-.

Figure 224. A, Summary of risk estimates and confidence intervals from epidemiologicstudies of BMI and breast cancer in premenopausal women (limited to studies with at least

100 cases). B, Summary of risk estimates and confidence intervals from epidemiologic studiesof BMI and breast cancer in postmenopausal women (limited to studies with at least 100 cases).


physical activity. only one study in vermont that had data on breastdensity from screening mammograms controlled for the effect ofbreast density (Lam et al., 2000). Because BMI is inversely related tobreast density, adjustment for breast density resulted in an increase inthe risk estimations at all levels of BMI; the oR increased from 1.9to 2.5 after adjustment for breast density among obese women.

when examined, risk estimates for the association between obesityand breast cancer vary by age at diagnosis, history of HRI estrogenreceptor status of the tumor, and possibly family history of breastcancer. Risk has been found to increase with age at diagnosis in somestudies that include a substantial number of postmenopausal womenolder than 65 years (Yong et al., 1996; van den Brandt et al., 2000;Friedenreich et al., 2002).In one study, risk estimates increased froml.l among women younger than 60 years to 1.8 among women olderthan 65 years (Yong et al., 1996).

The effect of exogenous estrogen or estrogen receptor status oftumors has been examined with stratified analyses in more recentstudies. In these studies, obesity-related risk has been higher amongwomen who have never used HRT (Huang et al., 1997 , Lam et al.,2000; Friedenreich et al., 2002; Lahmann et al., 2003). One of thelargest cohort studies in the United States found a statistically sig-nificant BMI and estrogen replacement interaction, with no increasein risk (RR of l.l) among all women bur an increase in risk (RR of1.6) among heavier women who had not used HRT (Huang et al.,1997). At least three studies have examined risk by BMI and estrogenreceptor status of the breast tumor (Enger et al., 2000; yoo et al., 2001;Sellers et al., 2002).In one U.S. study, risk for a BMI of 27 comparedwith a BMI of 22 was 2.4 for tumors that were both estrogen and pro-gesterone receptor positive (Enger et al., 2000). In another study, riskestimates were 2.0 and 2.2 for a BMI of 30.7 compared with a BMIof 23 for estrogen receptor positive and progesterone positive rumors,respectively (sellers et al., 2ooz). In both of these studies, obesity-related risk was not increased for estrogen and progesterone receptornegative tumors. In a Japanese study, risk did not vary by estrogenor progesterone status of the tumor (Yoo et al., 2001). However,the women in this study were lean; the upper quartile of BMI of 22 inthis study is lower than the lowest quartile of BMI in most U.S.studies.

Data are very limited on variation in BMl-related risk for post-menopausal breast cancer by family history. In several studies fromthe Iowa women's Health study, heavier postmenopausal women witha family history of breast cancer have a greater risk of deveropingbreast cancer than do heavier women without a family history (Sellerset al., 1992; Sellers et al., 2OO2).In one srudy in Japan, no differenceswere observed in associations of weight, BMI, or change in BMI byfamily history for premenopausal breast cancer, although somewhatstronger associations were seen for weight and change in BMI andpostmenopausal breast cancer among postmenopausal women with afamily history of breast cancer, confirming earlier results by Sellersand colleagues (Hirose et al., 20Ol). Only one study has examinedvariation in BMl-related risk for premenopausal breast cancer byfamily history of breast cancer (Swerdlow et al., 20021. rn that study,the inverse association commonly observed between BMI and breastcancer risk was only observed in women without a family history ofbreast cancer.

Weight or BMI at birth, during childhood, and early in adulthoodhave been examined relative to breast cancer. The data on birth weightand breast cancer are limited by a very small number of cases, withmost studies having fewer than 100 cases. Some studies find no asso-ciation (Le Marchand et al., 1988b; Ekbom et al., 1997). or a non-significant increased risk (Hilakivi-Clarke er al., 2001); others findan increase in risk with increasing birth weight for premenopausalbut not postmenopausal breast cancer (Berstein, 1988; Ekbom et al..1992 Michels et al., 1996; Sanderson et al., 1996; Innes et al., 2000)or a stronger increase in risk for premenopausal compared to post-menopausal breast cancer (De Stavola et al., 2000: Kaijser et al.,2001). In most studies, heavier weight or BMI during teenage andyoung adulthood (18-20 years) is associared with a l\vo to 30vodecrease in breast cancer risk for both pre- and postmenopausal breastcancer. This decreased risk is most often not statistically sisnificant

(Paffenbarger et al. , 1980; Wil lett et al. , 1985; London et al. , 1989;Folsom et al. , 1990; Lund et al. , 1990; Chu er al. , l99l:Brinton andSwanson. 1992; Sel lers et al. , 1992; Ursin et al. , 1995; Huang er al. ,1997:' Magnusson et al., 1998; Coates et al., 1999; Peacock et al.,1999, Enger e[ al., 2000; Hirose et al., 2001; de Vasconceloset al., 2001; Wenten et al., 2002). During the middle decades of life,the risk associated with BMI remains inverse for premenopausal breastcancer and increases with age for postmenopausal breast cancer.

lncreases in central adiposity have been associated with a L4- to2.O-fold increase in breast cancer risk among postmenopausal womenin most studies (Bal lard-Barbash et al. , 1990a; Folsom et al. , 1990:Schapira et al., 1990; Bruning et al., 1992a, 1992b; Sellers et al., 1992Ng, 1997; Shu et a1.,2001;Friedenreich et a1.,2002). However, notall studies show this association (den Tonkelaar et al., 1992: Petrek.1993; Lahmann et al., 2003). Data on cenrral adiposity and pre-menopausal breast cancer do not suggest a consistent associat ionbetween measures, such as waist circumference or WHR, and breastcancer risk (Francheschi et al., 1996; Mannisto et aI., 1996: Swansonet al. , t996; Ng et al. , 1997; Kaaks et al. , 1998; Huang et al. , 1999;Sonnenschein et al. ,1999; Hall et al. ,20001 Shu et al. , 2001: Frieden-reich et al., 2002). only five of these studies observed statisticallysignificant increases in risk (Mannisto et al., t996; Ng et al., 1997Sonnenschein et al. , 1999; Hall et al. , 2000; Shu et al. , 2001). Theassociation in postmenopausal women may be modified by a familyhistory of breast cancer and ovarian cancer. In the Iowa Women'sHealth Study, among women with elevated WHR, only women witha positive family history of breast cancer were at increased risk. Thecombination of a high WHR with a family history of breast andovarian cancer was associated with a more than fourfold increase inrisk of breast cancer (Folsom et al., 1990; Sellers et al., l9g3).

The most consistent body size predictor of postmenopausal breastcancer risk is adult weight gain (Lubin, 1985; Le Marchand et al.. 1988b;Ballard-Barbash, 1990b; Folsom et al., 1990; Brinron et al., l99Z:Radimer et al. , 1993; Barnes-Josiah et al. , 1995;Ziegler et al. , 1996;Huang et al., 1997; Magnusson et al., 1998; Jernstrdm and Barrett-Connor, 1999; Enger et al., 2000; Li er al., 2000; Trenrham-Dietzet a1.,2000; Shoff et a1.,2000; Hirose er al. , 2001: Shu et al. ,2001;Friedenreich et al., 2002: Wenten et al., 2002: Lahmann et al., 2003).This association has been seen in cohort studies that found no asso-ciation between BMI at baseline and subsequent development ofbreast cancer and that also adjusted for baseline BMI (Ballard-Barbashet al., 1990a: Folsom et al., 1990; Huang et al., 1997). Findings fromone of the largest cohort studies suggest that a doubling of risk wasassociated with a weight gain of more than 20kg after the age of l8years, but only among women who had never used postmenopausalHRT (Huang et al., 1997). Other studies have observed similar results,with increases in risk either limited to or much larger among womenwho have gained more weight and who have never used HRT com-pared to current users (Harris et al., 1992: Magnusson et al., 1998;Trentham-Dietz et al.. 2000: Friedenreich et al., 2002: Lahman et al.,2003). Consistent with findings for BMI and premenopausal breastcancer, weight gain appears to be associated with a reduced or no sig-nificant increased risk of premenopausal breast cancer in most studies(Le Marchand et al., 1988a; London et al., 1989; Brinton et al.. 1992..Huang et al. , 1997;Coates et al. , 1999; Peacock et al. , 1999: Hiroseet a1. ,2001;Shu et a I . ,2001; de Vasconcelos e t a1. ,2001;Fr iedenre ichet al., 2002, Wenten et al., 2002). However, a study by Wenten et al.(2002) in New Mexico found differences in risk for Hispanic com-pared to non-Hispanic white women. [n that study, no association wasfound between weight gain and risk of premenopausal breast canceramong non-Hispanic white women; in contrast, a non-statistically sig-nificant but nearly twofold increased risk was observed with more thanl4kg of weight gain among Hispanic white women.

The only study that has examined the effect of percent body fatmeasured by bioelectric impedance as well as several other measuresof body size, fat mass, and distribution found the strongest associationfor percent body fat, with a doubling of risk for women with a percenrbody fat of over 36Vo compared to women with a percent body fatof less than 27Vo. Similar to results reported for BMI and weightgain. risk for percent body fat was stronger among wornen who had

never used HRT. Amon-e women with a percent body fat of morethan 367c, the risk estimate among women who did not use HRTwas 3.4 compared to 1.0 amon_s women using HRT (Lahmann et al.,2003).

Breast Cancer Prognosis

Extensive data indicate that heavier women experience poorer survivaland increased likelihood of recurrence in most studies, irrespectiveof menopausal status and after adjustment for stage and treatment(Greenberg et al. , 1985: McNee et al. . 1987; Hebert et al. , 1988:Mohle-Boetani et al. , 1988; Lees et al. , 1989; Verrault et al. , 1989;Coates et al. , 1990; Tretl i et al. , 1990; Kyogoku er al. , 1990; Vanenet al. . l99l: Senie et al. , 1992; Giuffr ida et al. , 1992 Bastarracheaet al. , 19911'Zhang et al. , 1995: den Tonkelaar et al. , 1995: Maehleand Tretli, 1996). The effect of weight or BMI on prognosis appearsto be limited to or more pronounced among women with stage I andII disease (Verreault et al., 1989; Tretli and Magnus, 1990), estrogenreceptor and progesterone receptor positive status (Coates et al., 1990;Giuffrida et al., 1992: Maehle and Tretli, 1996), and negative nodes(Mohle-Boetani et al. . 1988; Newman et al. . l99l). The most preciserisk estimates for BMI and breast cancer prognosis are derived fromlarge population-based cohorts of breast cancer cases. In the largestcohort of more than 8000 women with breast cancer, risk varied bystage at diagnosis (Tretl i and Magnus, I990). Among women withstage I disease, women in the upper quintile of BMI had a 70Voincreased risk of dying from breast cancer. Among women with stageII disease, women in the upper quintile had a 407o increased risk. BMIwas not associated with risk among women with late stage III and IVdisease (Tretli and Magnus, 1990). In a subset of 1238 women fromthis cohort who had unilateral breast cancer treated with modifiedradical mastectomy and were followed for l5 years, the risk of dyingfrom breast cancer relative to BMI varied markedly by hormone recep-tor status (Maehle and Tretli, 1996). Although women with estrogenreceptor and progesterone receptor positive tumors had a 46Vo reducedrisk of dying from breast cancer, the risk within hormone receptorpositive and negative groups varied by BMI. Among women withhormone receptor positive tumors, obese women had a threefoldhigher risk of death than did thin women. Conversely, among womenwith hormone receptor negative tumors, thin women had a sixfoldhigher risk of death than did obese women, even afier adjustment forlymph node status, tumor diameter, and mean nuclear area. One studythat examined the association of BMI with distant recurrence anddeath found a 707o to SOVo increase in risk of both distant recurrenceand death among women with a BMI of 21.8 or greater (Goodwinet al., 2002a). This study also examined the association of fastinginsulin, IGF, and estradiol to these outcomes and found increased riskof distant recurrence and death among women with elevated insulin,but not with elevated IGF- l, IGF-II, and estradiol. A subsequent studyin this same sample found that the binding proteins of IGFBP-l andIGFBP-3 were inversely associated with risk of distant recurrence, butonly IGFBP-I was also inversely associated with risk of death(Goodwin et al., 2002b).

Weight gain is reported in the majority of women undergoingadjuvant therapy for breast cancer (Heasman et al., 1985; Goodwinet al., 1988,1999; Camoriano et al., 1990; Demark-Wahnefried, 1993).Weight gain associated with treatment is lowest among women notreceiving systemic therapy, intermediate among women receiving hor-monal therapy, and more pronounced among women receiving adju-vant chemotherapy and those who undergo menopause after diagnosisand treatment. To identify optimal interventions to prevent weight gainduring treatment, research has begun to examine whether changes inenergy intake and expenditure during and after treatment are associ-ated with weight gain (Demark-Wahnefried et al., 1993,2001: DeWaard et al., 1993). Although data on the association of post-diagnosis weight gain and prognosis are limited, the largest studyof 646 premenopausal women found that women who gained morethan 5.9kg were 1.5 times as likely to relapse and 1.6 times morelikely to die than women who gained less weight (Camoriano et al.,1990).

Obesity and Bodv Composi t ion 433


Ovar ian Hormone Metabol ismThe major focus of research on mechanisms underlying body size andbreast and endometrial cancer risk has been the effects of adiposityon endogenous hormonal, predominantly estrogen, metabolism;this research has been extensively reviewed (Kirschner et al., l98l;Key and Pike, 1988b; Bernstein and Ross, 1993; Key et al., 2001).Hypotheses have evolved from a focus on estrogen excess, to the com-bined effects of estrogen and progesterone, and most recently, toattempts to delineate factors defining bioavailability and eff-ects ofestrogens and androgens and their metabolites on specific end organs.Increases in overall and central adiposity have been associated withincreases in insulin, androgens, and triglycerides; decreases in SHBG;and increases in total and free estradiol (Evans et al., 1984; Haffneret al. . 1989; Kirschner et al. , 1990; Kaye et al. , l99l;Bruning et al. ,1992a, 1992b, Potischman et al., 1996). A number of these hormonalchanges increase the bioavailability of estradiol and its metabolitesand may also directly promote tumor growth.

The bioavailability of estradiol is dependent on the degree ofbinding and the strength of binding to several protein carriers. SHBGis the predominant protein carrier of estradiol and the percentage offree estradiol is generally inversely related to the level of SHBG.However, estradiol is also transported and bound, though less tightly,to albumin. Increases in free fatty acids, such as triglycerides, has beenreported to increase the level of free estradiol by displacing estradiolfrom SHBG where it is tightly bound, to albumin, where it is lesstightly bound. Therefore, both decreases in SHBG and increases intriglycerides may result in increases in free estradiol.

Key and Pike (1988a, 1988b) first proposed that the effect ofadiposity on the bioavailability of estrogen was modulated bymenopausal changes in estrogen and progesterone production, and soexplained the apparent contradictory findings for premenopausal andpostmenopausal breast cancer. Before menopause, ovarian estrogenproduction overwhelms changes in estrogen metabolism related to theoverall level of adiposity. Consequently, estradiol in ovulatory cyclesdoes not differ measurably in obese compared to lean women. In con-trast, estradiol levels are reduced in anovulatory cycles that are morefrequent in obese than lean premenopausal women. Conversely, obesepremenopausal women have been found to have markedly reducedprogesterone levels, both due to increased frequency of anovulationand decreased progesterone production in the luteal phase. With theonset of menopause, the decreased risk associated with premenopausalobesity declines over time. In postmenopausal women, the overall levelof adiposity results in increases in estrogenic activity by increases inestrogen production from androgens (Kirschner et al., 1981), decreasedestrogen-protein binding (Bruning, 1987) due to decreases in SHBG(Moore et al., 1987; Kaye et al., 1991; Bruning et al., 1992b) andincreases in triglycerides (Bruning et al., 1992b). Furthermore, the C-2hydroxy metabolite of estrogen has been proposed to be a less tumori-genic metabolite of estrogen, and C-2 versus l6-hydroxylation of estra-diol is reported to be decreased in obese women (Schneider et al., 1983).A well-designed study using contemporary, high-quality assays for sexsteroids found that the increases in estrone, estradiol, free estradiol, andalbumin-bound estradiol associated with increases in BMI were notpresent in premenopausal women but were statistically significantamong postmenopausal women (Potischman et a1.,1996).

lnsul in , Insul in- l ike Growth Factors,and Other HormonesInsulin, insulin-like growth factors, and binding proteins (BPs) maypromote hormone-dependent tumors through direct effects on tumorcells (Foekens et al., 1989; Yee et al., 1989; Turner et al., 1997), andthrough indirect effects on estrogens and possible interactions withestrogen at the estrogen receptor on breast cancer cells (Clayton et al.,1997; El-Tanani et al., 1997). A comprehensive review of epidemio-logical research by Yu and Rohan (2000) summarized the mitogenicand antiapoptotic actions of IGFs on various cancer cells, their syn-gergistic effects with other growth factors and steroids, and the asso-ciations of IGFs and binding proteins with cancer. The research on


breast cancer is briefly reviewed here. Five of seven studies that haveexamined the effect of IGF-I have found an increased risk of pre-menopausal breast cancer associated with increased IGF-I (peyratet al., 1993; Bruning et al.,1995; Del Giudice et al., 1998; Hankinsonet al., 1998; Toniolo et al., 2000). However, only one of these studies(Bruning et al., 1995) found a statistically significant increasedrisk. Three studies found no association between IGF-I and post-menopausal breast cancer (Bruning et al., 1995; Hankinson et al.,1998; Jernstr<im and Barrett-Connor, 1999), and one study found a dif-ference in mean IGF-I in cases and controls (Agurs-collins et al.,2000). C-peptide, a marker of hyperinsulinemia, has been associatedwith breast cancer risk in two studies (Bruning et al., I99Za; yanget al., 2001). One study that observed an increase risk of post-menopausal breast cancer with weight gain did not find that thisincreased risk was explained by levels of IGF-I, fasting insulin, proin-sulin, or C-peptide (Jernstrom and Barrett-Conner, 1999). Few otherstudies have examined whether insulin, IGF, or related growth factorsmight explain part of the increased risk associated with BMI, weightgain, or central body fat. Data on the association between IGF-I andBMI or fat mass are mixed (Yu and Rohan, 2000), with some studiesfinding no association (Kelly et al., 1990; Landin-wilhermsen er al.,1994; Goodman-Gruen et al., 1997; Janssen er al., 1998; Kaklamaniet al., 1999), some an inverse association (Colletti et al., l99l;Veldhuis et al., 1995; Marin et al., 1993; Maccario et al., 1999), andsome, particularly in lower BMI ranges, a positive association (IARC,2002). However, IGF-I is hypothesized to be associated with thedegree of muscle mass, and is related to the preservation of musclemass in animal studies. studies have not examined whether increasesin muscle mass also may explain the increased premenopausal breastcancer risk observed among tall and lean women.

Other Hormonal HypothesesAnimal studies have examined the effect of various other hormonalmeasures, such as growth hormone, or cortisol, on breast cancer devel-opment. These factors may vary by body weight, fat mass, or body fatdistribution, but studies in humans have not examined these as poten-tial mechanisms for weight-related breast cancer risk. one study hasexamined the association of leptin, a hormone that reflects total fatmass, with premenopausal breast cancer and found a non-significantlower level of leptin in cases compared to controls (Mantzoros et al.,1999). This finding is consistent with the inverse association betweenBMI and premenopausal breast cancer. No published studies haveexamined associations of leptin with postmenopausal breast cancer.circulating leptin is closely related to insulin levels and adiposity. Itincreases the amount of adipose tissue in the body (Bennett et al.,1997; Niskanen et al., 1997) by regulating food intake and energybalance (Larsson et al., 1998; van Aggel-Leijssen et al., 1999) andinteracting with other endocrine systems (Licino et ar., 1997:Haffneret al., 1997). Insulin increases leptin gene expression, stimulates leptinprotein production in rodents, and regulates leptin and SHBG proteinlevels in vivo and in vitro (Segal et al., 1996; Johannsson et al., 199g:Russell et al., 1998; Ho et al., 1999).

Other Mechanisms

with the recent emergence of studies suggesting that physical activitymay reduce risk of breast cancer, a limited number of analyses haveexamined the possibility of effect modification or interaction betweenphysical activity and various weight-related measures (Thune et al.,1997)- Although some studies have included physicar activity in alarge list of covariates within multivariate moders to adjust for con-founding, no analyses have reported whether effect modification byphysical activity is observed in risk estimates for weight-related mea-sures and breast cancer. Similarly, although diet has been proposedas a major mediator of the association of weight or BMI with post-menopausal breast cancer risk, no analyses have been designed toexamine this issue. The large error in self-reporting of energy, greaterin heavier compared to lighter individuals (Heitman, 1993, Subaret al., 2003), limits the ability to examine this issue with currentlyavailable data.

PROSTATE CANCER

Summary of Findings

Extensive data from cohort and case-control studies provide convinc-ing evidence of no association between body mass index and prostatecancer. Data on other anthropometric measures, such as abdominalobesity, muscle mass, or weight gain, are too limited to allow for anydefinitive conclusion.

Epidemiology

The association of BMI and incidence of prostate cancer has beenexamined in 33 studies conducted worldwide. Of these, l3 are cohortstudies (Figure 22-7) (Nomura et al., 1985; Severson et al., 1988;Mills et al., 1989; Chyou et al., 1994 Le Marchand er al., 1994;Thune and Lund, 1994; Andersson et al., 1997; Cerhan et al, 1997;Giovannucci et al., 1997; Lund Nilsen and Vatten, 1999; Clarkeand Whittemore, 2000; Habel et al., 2000; Putnam et al., 2000;Schuurman et al., 2000; Lee et aL.,2001). The remaining 20 are case-control studies (Wynder et al., l97l; Graham er al., 1983; Talaminiet al. , 1986; Ross et al. , 1987; Kolonel et al. , 1988; Yu et al. , 1988;Mettlin et al., 1989; West et al., l99l; Andersson et al.. 1995:Whittemore et al., 1995; Andersson et al., 1996; Gronberg et al., 1996;Ilic et al., 1996; Key et al., 1997: Demark-Wahnefried et al., 1997a:Hayes et al., 1999; Hsieh et al., 1999; Villeneuve et al., 1999; Bairatiet al., 2000: Hsing et al., 2000: Spitz et aI., 2000: Sharpe andSiemiatycki, 2001). Of these 33 incidence studies, seven observedan increased prostate cancer risk among men who were in the highestcategory of BMI (Thune and Lund, 1994; Grcinberg et al., 1996;Andersson et al., 1997; Key et al., 1997; Putnam et al., 2000; Spitzet al., 2000) or weight (Chyou et al., 1994) as compared to those inthe lowest category. In these seven studies, the increased risk wassmall, lUvo on average, across these categories of BMI, and the rangein risk estimates was from 0.5 to 4.4. T\e remaining studies found noassociation between obesity and increased prostate cancer risk.

Most epidemiological studies of obesity and prostate cancer haveused BMI as a measure of obesity. However, the ranges for BMI usedin these studies have not been standardized. Residualconfounding thatmight have concealed weak associations with anthropometry is a pos-sibility in these studies, particularly because several did not have a fullexamination of all possible confounding factors. Nonetheless, giventhe large number of studies conducted, the consistency of the results,the low magnitude of the association, and the limited evidence of adose-response effect, the lack of association between body mass indexand prostate cancer is convincing.

In addition to examining BMI, several of these investigationsevaluated the possible associations of weight with prostate cancerrisk. Consistently, no associations were found for increased risk withweight. It is possible, however, that other anthropometric measuresmay be more strongly associated with prostate cancer risk. Body massindex measures both lean body mass and adiposity. Other anthropo-metric measures of body fat distribution may be more strongly relatedto prostate cancer risk because this cancer is androgen-dependent, andlean body mass is related to androgen levels. Fewer studies have exam-ined lean body mass or abdominal adiposity, thereby timiting any con-clusive assessments of the associations. Severson et al. (1988) foundan increased prostate cancer risk in a Japanese population associatedwith the area of muscle in the arm and not with the fat in the arm. ANorwegian cohort study found no increased risk with lean body mass(Lund Nilsen and Vatten, 1999). Similarly, an American study foundno association with lean body mass or fat mass area as measured inthe arm (Clarke and Whittemore, 2000).

Weight gain throughout the lifetime and increased abdominaladiposity also are possible prostate cancer risk factors, although fewstudies have evaluated these variables. Schuurman et al. (2000) founda significant positive trend for increasing quantiles of BMI at age 20,but no increased risk for high weight gain from age 20 to time of inter-view. Hsing et al. (2000) found that abdominal adiposity, as measuredby WHR, increased prostate cancer risk in Chinese men. The observedincreased risk with WHR was independent of BMI, socioeconomic

Ftit:

::

Inodence Studies: Cohorl Studies

N{)rnura elal (1985), Severson etal {1988), USA, n=174

['ll l1, er r/. (1989), USA, n=180

t.ttyou et al. (,l99a), USA, n=306

I r. Marchand el al. (19941, USA, n=198

lhune E Lund (1994), Norway, n=220

Molle( et al. (1 994), Denmark, n=96

( , rovanf lucc i e l a t (1997) , USA, n=1,369

(.r{han elal. (1997), USA, n=71

Andersson et ai (1997), Sweden, n=2,368

l und Nilsen & Vatten (1999), No^,yay, n=642

t'utnan et al. (2000), usA, n=101

Schuurman el al (Z0m), Netherlands, n=6,8 1

llabel elal (2000), USA, n=2,0?9

tee e la l (2001) ,954, n=439


Ialamini el a/. (1986), ltaly, n= 166

Yu e la l . (1988) . USA, n=1,162

Menlin eral (1989), USA, n=371

Demark-Wahnefried etai (1997a). USA, n=l56

Spte et al. (2000), USA, n=103

{Jairari elal (2000). Canada, n=64


Andersson elal (1995), Sweden, n=256

Andersson elal (1996), Sweden, n=256

Gronberg el a/. (1996). Sweden, n=406

l\ey et al. {1997). United Kingdom, n=328

Hayes et al. (1999). USA, Blacks. n=449

Ha,les et al. (1999). USA, Whites, n=483

Vrlleneuve et a/ (1999), Canada. n-1,623

Hsing elal (2000), China, n=239

Sharpe and Siemiarycki (2001). Canada, n=399

status, physical activity, and dietary intake, including total calories.Though the associations with WHR were strong and consistent inthis study, additional empirical evidence is needed to confirm thisassociation.

Some effect modification by stage of disease may exist for obesityand prostate cancer. In the Health Professionals Follow-up Study,Giovannucci et al. (1991) observed a 58Vo increased risk among menwith metastatic prostate cancer for those in the highest quintile ofWHR, though no such increased risk was found for all stages ofprostate cancer combined. In this same study, preadult obesityappeared to protect against the occurrence of prostate cancer, andthese associations were particularly evident for metastatic disease(Giovannucci et al., 1991). Further effect modification may occurwith race. In a study in the United States with African American andwhite men, Hayes et al. (1999) found an increased risk of advancedprostate cancer among black men in the highest quartile of BMI at age25. No similarly increased risks were found for white men or for menwith less advanced prostate cancer for either race. Additional factorsthat may modify the effect of this putative association have not beenfully explored. One such factor is smoking. A case-control study inCanada found an interaction between smoking and BMI. Men withhigh BMI who were smokers were at increased risk as compared tononsmokers within the same BMI category (Sharpe and Siemiatycki,2001) .


Figure 22-7. Summary of risk estimates and confi-dence intervals from epidemiologic studies of BMIand prostate cancer.


Prostate cancer is a hormone-mediated cancer in that endogenoushormones regulate the growth and function of the prostate gland(Henderson et al., 1982), and administration of large quantities oftestosterone can induce prostate cancer in rodents (Noble, 1977). Menwho have high estrogen levels rarely develop prostate cancer (Glantz,1964). A Western lifestyle, charactenzed by a positive energy balanceas a result of high-energy intake and low activity levels, has consis-tently been implicated as a risk factor for prostate cancer in inter-national comparisons and experimental studies (Hebert et al., 1998;Bosland et al., 1999; Mukherjee et al.,1999). The evidence, however,from individual-level epidemiologic studies on the associationsbetween dietary intake, obesity, and physical activity and prostatecancer risk is weaker (Friedenreich and Thune, 2001; Schulman et al.,2001). Despite the lack of an association between BMI and pro-state cancer from epidemiologic studies, several studies of biologicalmarkers that are related to obesity suggest an association of thesemarkers with prostate cancer.

Leptin, an adipocyte-derived hormone that regulates satiety andenergy expenditure, has been shown to increase prostate cancer risk.It is suggested as a key link between a state of continual positiveenergy balance and the transition from premalignant lesions to overtprostate cancer (Stattin et al., 2001). In addition, higher serum insulin

436 PART ll l : THE CAUSES OF CANCER

levels increase prostate cancer risk independent of abdominal adipos-ity (Hsing et al., 2001). Despite these associations, it is unclearwhether the concomitant hormonal and metabolic changes that occurbecause of abdominal adiposity and insulin resistance are the biolog-ical mechanisms for the link between insulin and prostate cancer risk.

Two other biomarkers for prostate cancer risk that may be relatedto BMI and either fat or muscle mass have been identified from studiesin diverse populations: IGF-I (Mantzoros et al., 1997; Chan et al.,1998; Wolk et al., 1998) and serum testosterone (Shaneyfelt et al.,2000). A meta-analysis of published studies on hormonal predictors ofprostate cancer risk found that men with serum testosterone or IGF- Ilevels in the upper quartile of the population disrribution have anapproximately twofold higher prostate cancer risk (Shaneyfelt et al.,2000). Levels of dihydrotestosterone and estradiol were not found tohave as strong an association with prostate cancer risk (Shaneyfeltet al., 2000). Overall, exposure to endogenous androgenic hormonesappears to be positively associated with prostate cancer risk (Bosland,2000). A number of studies have explored the associations betweenvarious sex steroids and BMI in men (Glass, 1989; Kato et al., I99Z:Andersson et al., l99l;Demark-Wahnefried et al., 1997b Tymchuket al., 1998; Tamani et al., 200I; Sarma et al., 2002). However, howBMI may play a role in the association of these measures with prostatecancer is complex and not well understood.

THYROID CANCER

Summary of Findings

Data from case-control and cohort studies are suggestive of anincreased risk of thyroid cancer among heavier individuals (BMI cut-points not defined) that is present only for women. Estimates from ameta-analysis suggest a 20Vo increase in risk in women (Dal Masoet al., 2000).

Epidemiology

A meta-analysis (Dal Maso et al., 2000) summarized and reanalzyedevidence from the existing case-control studies on obesity and thyroidcancer (McTiernan et al., 1984; Preston-Martin et al., 1987; Ron et al.,1987;Linos et al. , 1989; Kolonel et al. , 1990; Francheschi et al. , l99l;Levi et al., 1991; Goodman et al., 1992; Glattre et al., 1993; preston-Martin et al., 1993; Wingren er al., 1993: Hallquist er al., 1994,D'Avanzo et al., 1995; Galanri er al., 1997; Negri er al., 1999). Theauthors reported that relative risks for the upper tertile of BMI at thetime of diagnosis was above unity for 9 of the 12 studies in women,with a relative risk overall for the highest compared to the lowesttertile of 1.2 (95Vo Cl, 1.0-1.4), P for trend of 0.04. The overall rela-tive risk for the highest compared to the lowest tertile in men was r.0,with a nonsignificant P for trend.

Similarly, in five case-control studies that have examined this factor,no association has been observed for thyroid cancer risk and BMIbetween the ages of 17 to 20 (McTiernan et al., 1984; presron-Martinet al., 1987; Linos et al., 1989; Preston-Martin et al., 1993; Wingrenet al., 1993). One case-control study of papillary thyroid cancer inwomen (Rossing et al., 2000), published after the Dal Maso (2000)meta-analysis, found that women who weighed 185 pounds or morehad a l.5-fold increased risk. Another case-control study in womenfound no association between BMI and thyroid cancer (Mack et al.,2002) but did observe a non-statistically significant increase in riskwith weight gain. The only cohort study to examine the associationbetween obesity and thyroid cancer risk found no statistically signifi-cant association with BMI at the baseline interview or with weishtgain since age 20 (Iribanen er al., 2001).


several mechanisms have been proposed for the modest associationobserved in many case-control studies in women. Most relate to poten-tial interactions between thyroid hormones and other steroid hor-

mones. Proposed mechanisms include increases in obesity-relatedpostmenopausal estrogen based on evidence that exogenous estrogensare weakly associated with thyroid cancer risk (La Vecchia et al., 1999;Negri et al., 1999).In addition, detection bias due to more frequentexamination of the thyroid gland because of screening for hypothy-roidism among heavier women may be a factor in countries, such asthe United States, where this practice may be more prevalent.

CANCERS OF THE LUNG AND THE HEAD AND NECK

Overview

An extensive literature exists on the commonly observed inverse asso-ciation between obesity and cancers of the lung and the head and neck.This literature was summarized in the 2002International Agency forResearch on Cancer (IARC) report on weight control and physicalactivity (IARC, 2002). In the past 10 years, studies examining theinverse association of obesity and these cancers have been designedto examine the extent of confounding by the effect of tobacco use orpreexisting disease that may result in weight loss.

Summary of Findings

Data from case-control and cohort studies suggest an inverse associ-ation between BMI and cancers of the lung and head and neck. Thisinverse association moves to the null after adjustment for confound-ing by tobacco use and, therefore, is not thought to be causal in nature.

Lung Cancer

The majority of cohort (Knekt et al., 1991; Lee and Paffenbarger,1992b: Chyou et al., 1994; Drinkard et al., 1995; Kark et al., 1995.Henley et al., 2002) and case-control studies (Kabat and Wynder,1992; Goodman and Wilkins, 1993; Kubik et al., 2N2: Olson et al.,2002) have found an inverse association between body size and lungcancer, although it is generally less striking after adjustment for poten-tial confounding by smoking status. In addition, several recent studieshave examined the association of BMI and lung cancer in subgroupssuch as current and nonsmokers (Rauscher et al., 2000; Henley et al.,2002) and found little association among never or former smokers. Astudy limited to never and former smokers in New York (Rauscher etal., 2000) found a doubling of risk for lung cancer among obese menand women that was not statistically significant. A cohort study fromthe American Cancer Society's Cancer Prevention Study II, whichexamined the effect of the potential for bias from tobacco use and pre-existing disease, also evaluated the role of weight and BMI amongnever smokers and found no association (Henley et al., 2002). Thisstudy showed a lessening in the observed association between BMIand lung cancer among the entire cohort after adjusting for preexist-ing disease and removing early follow-up as an additional method ofadjusting for preexisting disease. These findings are interpreted toindicate that leanness is unlikely to be a causal factor in the develop-ment of lung cancer. However, it is likely that the causal factors forlung cancer among never smokers are very different than causalfactors among current smokers. Therefore, it is not clear that analysesof associations between BMI and lung cancer among never smokerscan contribute much to understanding whether confounding bytobacco use explains the majority of the inverse association observedbetween BMI and lung cancer among smokers.

The only study that has examined the association of body fat dis-tribution by waist circumference and lung cancer risk found evidenceof a differential association between waist circumference and histo-logic subtypes of lung cancer (Olson et a1.,2002). In that study amongmiddle-aged lowa women, risk for small cell and squamous cell lungcancer was increased by threefold among women in the highest quin-tile of waist circumference; in contrast, no association was observedbetween waist circumference and adenocarcinoma of the lune.

T:lr.

':.: : :t . :

Head and Neck Cancers

Although tobacco and alcohol use account for more than 90Vo ofcancers of the head and neck in developing countries (IARC, 1986,1988), leanness also has been associated with increased risk of headand neck cancers in some case-control studies. No cohort studiesexamining this association have been published. Six case-controlstudies found an inverse association between weight and/or BMIand cancer of the oral cavity and pharynx (Mclaughlin et al., 1988;Marshall et al., 1992;; Day et al., 1993; Kabat et al., 1994, D' Avanzoet al., 1996; Francheschi et al., 2001) and one found a non-statisticallysignificant risk estimate of 1.5 among heavier women (Negri et al.,2000). Two other studies found weaker inverse associations betweenBMI and laryngeal cancer (Muscat and Wynder, 1992: D'Avanzoet al., 1996). Similar to findings for lung cancer, several studies foundeither no associat ion (Kabat et al. , 19941'Francheschi et aI. ,2001) orweaker associations (D'Avanzo et al., 1996) between BMI and oralcancer among never smokers compared to current smokers. Theseresults suggest that BMI is not causally related to risk of head andneck cancers. However, similar to lung cancer, the causal factors con-tributing to head and neck cancer among never smokers may be dif-ferent than those amons current or former smokers.

CANCER SITES WITH INSUFFICIENT EVIDENCEFOR CONCLUSIONS

Limited epidemiologic evidence exists on weight or BMI for a num-ber of other cancers, including leukemia, non-Hodgkin lymphoma,malignant melanoma, and testicular, pancreatic, bladder, and cervicalcancers. However, data for these and other cancer sites are toolimited to allow specific conclusions.to be made and are not summa-rized here due to space limitations. A summary of the evidence forseveral of these other cancer sites is provided in the February2002 IARC publication Weight Control and Phvsical Activirv (IARC,200D.

DATA ON CANCER MORTALIry

Because of space limitations and the difficulty of disentangling theeffect of screening and treatment from individual-based risk factors,such as obesity, when examining cancer mortality as an outcome, thisreview does not provide a detailed overview of the evidence on obesityand cancer mortality. However, a recent study from a large U.S.-basedcohort provides several new insights (Calle et al., 2003). In this study,the effect of obesity on cancer mortality was examined in a cohort ofmore than 900,000 adults who developed more than 57,000 cancers in16 years of follow-up. The study is unique in that it provided estimatesfor multiple cancers within one cohort and one report and had a muchlarger sample size than any other single report to date. Therefore,the study was able to provide estimates for multiple cancers, includingmore precise estimates for less common cancers, and examined theeffect of overweight and obesity among nonsmokers. The study foundthat BMI was associated with higher rates of death in both menand women for cancers of the esophagus, colon and rectum, liver,gallbladder, pancreas, kidney, non-Hodgkin lymphoma, and multiplemyeloma. BMI was also associated with higher rates of death fromcancers of the stomach and prostate in men and cancers of the breast,uterus, cervix, and ovary in women. Based on rates of overweight andobesity present in the United States in 1999 to 2000, the study esti-mated that l47o of cancer deaths in men and 20Vo of cancer deaths inwomen could be attributed to overweieht and obesitv.

FUTURE DIRECTIONS

Studies are needed that have sufficient power and complete data on anumber of factors to adequately control for all confounders of the asso-ciation between BMI and cancer, and to study subgroups postulated


to be at very low or high risk. In addition, more studies on weight andheight at an early age in life with a long follow-up are needed to clarifythe role of weight and weight gain throughout the life span. For somecancer sites, a number of studies corrected only for age, thus allow-ing uncontrolled confounding to influence the results. Important con-founders to consider include physical activity, other anthropometricfactors such as height, smoking status, dietary intake, and otherlifestyle factors. A full examination of all anthropometric risk factorsand cancer is also needed. For some cancer sites, such as breast cancer,additional measures such as body fat distribution, weight gain, andbody composition have been examined. However, for most cancersites, very few studies have considered any factor other than BMI.

Moreover, studies that examine a full range of possible effect mod-ifiers need to be conducted because relatively few investigations haveexamined risks within subgroups of the population defined on char-acteristics such as ethnic origin/race, other lifestyle risk factors (e.g.,physical activity, dietary intake, smoking status), HRT, genetic factors(e.g., family history of cancer or other comorbid diseases, such asdiabetes that may influence the health consequences of obesity), orother possible risk factors, such as breast density in the case of breastcancer. Studies that provide data specific to racial and ethnic groupsare increasingly important. At present, most of the data on obesity andcancer are based on population samples drawn from Europe, theUnited States, Canada, Australia, Japan, and China, and thereforehave largely included whites of European descent, Chinese, Japanese,and Hawaiians. Data are very limited for African-American men andwomen or those of North. Central. or South American Latina descentor for many populations in Asia and Africa. In addition, data on thesegroups are seldom reported separately even within large case-controlor cohort studies that may include these populations.

To clarify the extent to which anthropometric factors are risk factorsfor specific cancers, further research is needed to delineate the roleof site-specific biological mechanisms, particularly for endogenoushormones, insulin, insulin-related growth factors, leptin, cortisol,and related hormones that may influence the development of body fat,skeletal structure, and musculature and that may underlie observedassociations with cancer outcomes. Evidence is evolving rapidly aboutgenetic factors that may have particular importance in the metabolismof sex steroids and insulin or in the development of obesity. Futurestudies are needed to examine how specific genes predict underlyingmetabolic profiles and subsequent cancer risk.

An overview of the potential biological mechanisms that have beeneither hypothesized or examined as possible explanations for the asso-ciation of obesity with specific cancers is presented in Table 22-l.Tltisoverview demonstrates that many of these cancers are hypothesizedto be hormone based, either in terms of sex steroids or, more recently,in terms of insulin, leptin, or insulin-related growth factors. Althoughnot explored to any extent in humans, research in animal modelssuggest that factors such as cortisol or vitamin D may also explainsome of the risk associated with obesity. Using animal models,these mechanisms have largely been explored by studies of caloricrestriction rather than by studies of increases in energy expenditure(Hursting et al., 2003).

Two other areas of emerging research should be briefly noted. Withimproved detection and treatment, many people are living longerand healthier lives with cancer, and therefore, studies on the effect ofobesity on cancer prognosis are needed. At present, research in prog-nosis has been largely limited to breast cancer and should be extendedto other cancers. In addition, to achieve a better understanding of whatinterventions may reduce risk, studies of the effect of specific dietaryand exercise programs to control weight are needed, particularlystudies that can elucidate the effect of such interventions on underly-ing mechanisms that may influence carcinogenesis.

EXTENT OF THE OBESITY EPIDEMIC ANDMANAGEMENT STRATEGIES

The WHO 2000 report Obesity: Preventing and Managing the GlobalEpidemic is the most recent comprehensive source summarizing the


Table22-1. Biological Mechanisms Potentially Involved in the Association Between Obesity and Specific Cancers

Mechanism Explanation Cancer Sites

Altered endogenous estrogen levelsAltered endogenous androgen levelsAltered metabolic hormone levels

Interaction between sex steroid and metabolichormones

Altered nervous and immune system functioningIncreased cell numberPositive energy balanceConcentration of adverse factors in adipose tissueIncreased gastric reflux

Delayed esophageal transit time

Increased incidence of metabolic syndrome(hypertension, glucose intolerance, increasedIGF, and in women anovulation and increasedandrogens)

Higher estrogen, higher testosterone. and lower SHBGHigher estrogen, lower testosterone, and lower SHBGElevated leptin and insulin, increased IGF, higher

cholesterol

Greater sympathetic activity, immune system dysfunctionLarger pool of cells to undergo malignant transformationHigh dietary fat intake, Iower physical activityGreater concentration of growth factors or carcinogensIncreased intra-abdominal fat mass increases intra-

abdominal pressure and hence increases gastric refluxObesity leads to delayed esophageal transit time and

increased exposure timeContributes to renal damage and susceptibility to

other carcinogens

Breast, endometrial, renalProstateProstate, breast, endometrium, colon,

esophageal, gastricProstate, breast, endometrium, colon

Prostate, breastBreast, colon, theoretically relevant to allAllAl lEsophageal

Esophageal

Renal

IGF, insulin-like growth factor; SHBG, sex hormone binding globulin.

global epidemic of obesity. Within that report, the WHO MONICAstudy provides a full spectrum of data comparing rates of obesityworldwide for the period 1983-1986. At that time, the internationalprevalence of obesity, defined as a BMI of 30 and higher, rangedfrom 5Vo to 20Vo for men and l}Vo to 407o in women (WHO, 2000).The WHO 2000 report highlighted sgveral major features of theinternational patterns of body weight and associated health outcomes.For the first time, more people were classified as experiencing obesitythan were suffering from starvation in developing as well as devel-oped countries. The report also noted the rapidly increasing ratesof obesity in some Asian countries, such as Japan and China, wherethe prevalence of obesity traditionally had been very low. Similar topatterns observed in the United States, rates of obesity in other coun-tries are generally higher among women than men and in urban ascompared to rural communities. Although data on children are morelimited, evidence suggests that obesity is also increasing in childrenworldwide in developed and developing countries. In 2000, theWHO initiated a global strategy for preventing and controlling non-communicable diseases that includes a focus on combatting the world-wide rise in obesity through reducing unhealthy diets and physicalinactivity.

In the United States, the prevalence of obesity has changed dra-matically over the past 40 years. It was relatively stable at approxi-mately L}Vo for men and l5%o for women during the early 1960s tothe late 1970s. During the late 1980s and early t990s rates of obesityincreased, and the most current estimates from the 1999-2000National Health and Nutrition Examination Survey (NHANES) indi-cate that the prevalence of obesity has increas ed to 27 .5Vo for men and33.4Vo for women (Flegal eta1.,2002). Rates tend to increase with ageto about age 70; at later ages, they decline slightly. Rates are highestamong non-Hispanic black women who experience a 507o prevalenceof obesity.

When the prevalence of overweight, or a BMI of 25 and higher, isconsidered, about 65Vo of the U.S. adult population is affected. Of par-ticular concern are increases in rates of overweight among childrenand adolescents. Prevalence rates, which were approximately 57oduring the 1960s, have tripled to over I5Vo in 1999-2000 amongschool-aged children and adolescents. Rates rose by 10 percentagepoints or more between 1988 and 1994 and between 1999 and 2000for both Mexican American and non-Hispanic black adolescents(Ogden et al., 2002).

Estimating the consequences and cost of obesity internationally iscomplex because obesity and overweight are risk factors for multiplechronic diseases other than cancer, including non-insulin-dependentdiabetes mellitus, insulin resistance, gallbladder disease, hyperlipi-

demia, coronary heart disease, hypertension, osteoarthritis, sleepapnea, low-back pain, polycystic ovarian disease, impaired fertility,reproductive hormone abnormalities, surgical complications, andanesthesia complications. [nternational estimates of the economic costhave ranged from 2Vo to about 77o of national health care costs, withthe United States reporting the highest cost of 7Vo (WHO, 2000). In1990, this cost was estimated to be $45.8 billion dollars from the directcost of obesity-associated diseases and $23.3 billion from lost pro-ductivity (Wolf and Colditz, 1994).In an updated analysis, Wolf andColditz (1998) estimated the total U.S. direct cost attributable toobesity to be $99.2 billion, which represented 5.77o of the total U.S.national health expenditure that year.

A comprehensive overview of the treatment and prevention ofobesity is beyond the scope of this review. These issues are addressedin detail in the WHO 2000 report Obesity: Preventing and Managingthe Global Epidentic and other reviews (Kopelman, 2000). Advancesin the field of obesity, particularly in terms of the genetics of obesityand its implication for developing more targeted and effectivetreatment approaches, have been highlighted in issues of Science(February 2003) and Nature (April 2000). Preventing and controllingobesity requires comprehensive societal efforts and must target life-long health habits at the individual level. In addition, continuedresearch is needed to find better means of identifying individuals atrisk of developing obesity and its adverse consequences because oftheir genetic, familial, or other environmental risk factors. At present,with the rapid increase in obesity in developed and developing coun-tries among all age groups, including children, prevention has becomean urgent worldwide priority. lssues of particular concern in cancercontrol include the need to develop better strategies to facilitate theavoidance of weight gain during adult life and to identify whetherspecifi c interventions during treatment can alleviate treatment-relatedweight gain that has been identified to worsen breast cancer prog-nosis, but may also be an issue for other cancers. Key public healthrecommendations and strategies relevant to cancer are reviewed inthe2002IARC report onWeight Control cmd Ph,-sicalActiv,in (IARC,2002).

CONCLUSIONS AND POPULATIONATTRIBUTABLE RISK

At present, data provide convincing evidence of a positive associationof overweight and obesity with cancers of the colon (among men).renal cell, postmenopausal breast, endometrium, and probable evi-dence of a oosit ive associat ion with colon cancer (amons women).

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Obesity and Body Composi t ion 439Table 22-2. Popu lati on Attributabl e Rates (PAR in vc) f or weight-Relatedcancers for the European Union (EU) from 1982to 1996 and the unitedStates from 1999 to 2000

Men Women

Overweight Obese Overweight Obese

-----ry--l

t"J a

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USAColonKidneyEndometriumBreast (postmenopausal)

6.915.2

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7060504030201 0

overweight/obesity prevalence rates used: EU overweight and obesity rates were, respec-tively,35vo and l9va for men, and 50vo and l3vo for women. For the United States from1999 to 2000, the rates were increased to 6'lvc and 28vo for men and 62va and 33va fotwomen.*Source of RR and EU PARs is Bergstr<im et al. (2000).

adenocarcinoma of the esophagus and gastric cardia, and thyroidcancer (among women). on the other hand, epidemiologic studies donot demonstrate an association of weight or BMI with prostate cancerincidence. In addition, limited evidence does not suggest any consis-tent direct association between overweight or obesity and ovariancancer. The consistent inverse association between overweight orobesity and lung, and head and neck, cancers is reduced with adjust-ment for tobacco use; therefore, overweight and obesity are not con-sidered to be protective for these cancers. The inverse associationbetween overweight and obesity and premenopausal breast cancerpersists after adjustment for multiple potential confounding factors.Extensive data provide convincing evidence of a positive associationbetween overweight and obesity and adverse changes in breast cancerprognosis and mortality.

Estimates of the population attributable risk (PAR) of cancer dueto overweight and obesity have been summarized in the 2002 IARCreport and are modest for some cancers, such as colon and post-menopausal breast cancer. Approximately 9vo to llvo of these cancersare attributable to overweight or obesity. PAR estimates nre more sub-stantial for renal cell, esophageal, and endometrial cancer:25vo,37vo,and 39vo, respectively. However, these estimates were based on inter-national rates of overweight and obesity from the 1990s (IARC, z00z)and are higher in the United States today given the continued increasein the prevalence of overweight and obesity. Table 22-2 provides acomparison of PARs for five major weight-related cancers for theEuropean Union as estimared by Bergstrcim and colleagues (2000) andfor the united states based on rates of obesity and overweight fromthe 1999-2000 NHANES survey. The PARs estimated by Bergstrtimand colleagues (2001) were based on relative risk estimates from meta-analyses and from rates of obesity in European union countries from1982 to 1996. Because of increases in rates of overweight and obesityin the United Srates, PARs are higher for rhe united States than thoseestimated for the European union. Figure 22-8 shows the potentialfor substantial increases in PARs with increases in rates of over-weight/obesity and relative risk estimates of overweight/obesity withcancer. For example, in a country such as Japan, which has obesityrates of less than 3vo, the PAR for a cancer with a twofold increasedue to obesity, such as endometrial cancer, is less than3vo.T\e PAR estimate for obesity and endometrial cancer within theEuropean Union published by Bergstr0m and colleagues (2000) was22vo when the prevalence of obesity was l3vo for women within theEuropean Union. In contrast, in the United States, whose rate ofobesity in women is 33vo, the PAR for endometrial cancer is 33vo.Thepotential for marked increases in the PAR for obesity and weieht-

Overweight/Obesity Prevalence (%)

Figure 22-8. Population attributable risk (PAR) by overweight/obesityprevalence rates and levels of relative isk. Source: Population Attribut-able Risk (PAR) from Bergstrom et al., 2001 for renal cell cancer. UpdatedPAR estimates are based on NHANES 1999-2000 obesity prevalence.PARs are In US, EU males and OO US, EU females, respectively.-+ RR_1.5; -# RR_2.0; {- RR_3.0.

related cancers is further demonstrated in Figure 22-9, which demon-strates the relatively strong association between rates of obesity andendometrial cancer prevalence internationally. Similar associationscan be seen for other cancers as well. With the expectation that theepidemic of obesity is likely to continue, if not accelerate, in the nearterm, overweight and obesity will become increasingly importantcontributors to cancer risk internationally.

Acknowledgments

The authors would like to acknowledge the contributions of the followingpeople to this review: Anita Ambs, National Cancer Institute, for managing thedistribution of materials for the review and the development of figures; DavidTran, Scientific Consulting Group, for literature reviews; Darrell Anderson,Scientific Consulting Group, for development of summary tables, figures, andfinal preparation of the manuscript; and Anne Rodgers, for editing.

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Obesity Prevalence, 7o

Figure 22-9. Association between obesity prevalence (BMI > 30kg/m2)and endometrial cancer cumulative rates in selected countries.

MO PART ll l : THE CAUSES OF C,ANCER

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