Body Size and Prostate Cancer

Epidemiologic Reviews Copyright © 2001 by the Johns Hopkins University Bloomberg School of Public Health All rights reserved Vol. 23, No. 1 Printed i...
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Epidemiologic Reviews Copyright © 2001 by the Johns Hopkins University Bloomberg School of Public Health All rights reserved

Vol. 23, No. 1 Printed in U.S.A.

Body Size and Prostate Cancer

Abraham M. Nomura


which BMI is also a measure of body build or body proportion. Lastly, BMI reflects both body fatness and lean body mass. Another point to consider in epidemiologic studies is the source of the data regarding weight and height. Although self-reported weight and height are generally highly correlated with measured weight and height, the magnitude of the correlations can vary across studies (2). Furthermore, high correlations do not necessarily reflect accuracy, because systematic differences between self-reported and measured values may exist in spite of the strength of the correlations. Biases in self-reported weight and height have been documented (14, 15). Men tend to under-report their weight when they are obese and over-report it when they are underweight. In recent years, the distribution of body fat has received more attention as an important dimension in studying the relation between obesity and health. Persons with excess fat stored mainly on the upper body (male or android obesity) have been shown to have an increased risk for total mortality, cancer, and cardiovascular disease (16-18). Waist circumference or the ratio of waist to hip circumferences have been used to estimate upper body fat (8). However, there are problems in using circumferences as indices of adipose tissue distribution because standard definitions of the circumferences are not always followed. The "waist" circumference has been variously defined as the umbilicus, the lower margin of the ribs, the iliac crests, and at the level of the smallest circumference on the torso below the sternum. Similarly, the "hip" circumference has been set at the iliac crests, the anterior iliac spines, the greater trochanter of the femur bone, or the maximum posterior protrusion of the buttocks (2). There may be appreciable differences among circumferences measured at these locations, and these bony landmarks may be difficult to identify in obese persons. In addition to BMI and body fat distribution, another measure of human obesity that is of interest is abdominal visceral fat. Its amount is important in determining whether obesity has major or minor health implications in an individual (19). As with estimating upper body fat, a waist circumference measurement can provide reasonable mean values of abdominal visceral fat for a group, but it is not accurate for a given individual (8). A computed tomography scan or magnetic resonance imaging is needed to measure abdominal visceral fat accurately. Besides obesity, height or stature is another measurement used to evaluate body size in relation to health. Adult height or stature is determined primarily by two components, heredity (parental stature) and nutritional intake during the

Anthropometry is the branch of anthropology that deals with the comparative measurements of the human body and its associated parts. It is the most widely utilized and least expensive method of assessing human body composition. In epidemiologic and clinical studies, it is mainly used to calculate body fatness and fat-free mass in groups and individuals (1). Anthropometric measurements to estimate obesity include weight, weight in relation to height, skinfold thicknesses, and circumference measurements of the trunk and limbs (2). Body fatness reflects the interaction of human growth and development with the environment under the influence of a person's genotype. Studies in twins, other biologic relatives, and relatives by adoption show that about 25 percent of the variance in percent body fat is attributed to genetic factors after adjustment for age and gender differences (3). Inheritability is estimated to be as high as 30—40 percent for factors such as adipose tissue distribution, resting metabolic rate, lipoprotein lipase activity, and basal rates of lipolysis (4). At the same time, the rising prevalence of obesity in the United States and the secular trend toward increasing obesity present clear evidence of the environmental influences on adiposity (5-7). Investigations of the relation between body size and prostate cancer have focused mainly on weight and measurements of obesity, such as the body mass index (BMI). The BMI, which is defined as body weight in kilograms (kg) divided by the square of the height in meters (m2), is a surrogate for body fat content (8). It is highly correlated with percent body fat determined hydrostatically by total body submersion (9). This index has been commonly used since it has frequently been shown that persons with a high body mass relative to stature have high mortality rates (10-12). In spite of its popularity, there are limitations of BMI as an objective measure of obesity, as pointed out by Garn et al. (13). Firstly, the assumption that the BMI is independent of stature is not entirely true for adults and especially not true for children. Secondly, persons with short legs for their height have higher BMI values, which indicates the extent to

Received for publication August 29, 2000, and accepted for publication February 2, 2001. Abbreviation: BMI, body mass index. From the Japan-Hawaii Cancer Study, Kuakini Medical Center, 347 North Kuakini Street, Honolulu, HI 96817 (e-mail: [email protected]). (Reprint requests to Dr. Abraham M. Y. Nomura at this address).


Body Size and Prostate Cancer

developmental period (20). As such, height is a potentially important marker of the effects that early nutrition may have on human carcinogenesis. BODY SIZE AND PROSTATE CANCER

A number of studies have been done to assess the relation of body size to prostate cancer. These investigations have usually used anthropometric measurements in describing their findings. Table 1 summarizes the results from 12 casecontrol studies which were conducted from 1986 to 1999 (21-32). The investigations were done in Greece, the United States, Sweden, Canada, South Africa, and Italy; 10 of them reported no significant association between prostate cancer and various measurements, including weight, height, BMI, waist/hip ratio, waist circumference, and triceps skinfold thickness. The number of cases in these studies ranged from 120 to 1,655. The sources of controls was variable as there were seven studies with population controls, two with hospital or clinic controls, and one with neighborhood controls.


Six of the 10 studies collected interview data, three examined the study participants, and one obtained questionnaire data. In the two studies that reported a positive association (23, 32), the odds ratios were 1.9 and 3.9, respectively, based on the BMI in the highest quantile group. Gronberg et al. (23) identified 406 prostate cancer cases from the Swedish Twin Registry, and used the same registry to select 1,218 unrelated controls who completed the same questionnaire. Talamini et al. (32) interviewed 166 cases and 202 hospital controls in northern Italy and found that 68 cases, compared with 44 controls, had a BMI of 28 or greater. In many case-control studies the analysis depended upon self-reported anthropometric measurements, which may have limitations as pointed out earlier. Some patients may have lost weight because of their disease, which could limit the validity of measuring weight at time of examination in casecontrol studies. Cohort studies, in which the participants were examined for their anthropometric measurements before they were subsequently diagnosed with prostate cancer, have an obvious advantage over case-control studies in this regard.

TABLE 1. Summary of results from case-control studies of anthropometry and prostate cancer Study (reference no.), year, location

No. of subjects




Hsiehetal. (21), 1999, Athens, Greece

320 cases; 246 hospital controls

BMI*, height

No significant differences

Interview data

Demark-Wahnefried et al. (22), 1997, North Carolina

159 cases; 156 urology clinic controls

BMI Waist/hip ratio Triceps skinfold Weight Height

OR* = 0.9 (NS*) OR = 1.0(NS) OR = 0.9 (NS) OR = 0.9 (NS) OR = 1.1 (NS)

Examination data

Gronberg et al. (23), 1996, Sweden

406 cases; 1,218 controls


OR = 1.9 (p = 0.002)

Questionnaire data; cases and unrelated controls are in twin registry

Ghadirian et al. (24), 1996, Montreal, Canada

232 cases; 231 population controls



Interview data

Rohan et al. (25), 1995, Ontario, Canada

207 cases; 207 population controls


OR = 1.1 (NS)

Interview data

Whittemore et al. (26), 1995, United States; Canada

1,655 multiethnic cases; 1,645 population controls

BMI, waist circumference, weight, height

No significant differences

Interview data; mean values for cases and controls were reported

Andersson et al. (27), 1995, Sweden

256 cases; 252 population controls

BMI Weight Height

OR = 0.8 (NS) OR = 1.1 (NS) OR = 1.4(NS)

Examination data

Gann et al. (28), 1994, United States

120 physician cases; 120 physician controls


No significant difference

Questionnaire data; mean values for cases and controls were reported

Walker et al. (29), 1992, South Africa

166 cases; 166 neighborhood controls

BMI, weight, height

No significant differences

Examination data; mean values were reported

West et al. (30), 1991, Utah

358 cases; 679 population controls


Calculated OR = 1.0 (NS)

Interview data

Koloneletal. (31), 1988, Hawaii

452 cases; 899 population controls

BMI, weight, height

No significant differences

Interview data; mean values were reported

Talamini et al. (32), 1986, northern Italy

166 cases; 202 hospital controls


OR = 3.9 (p= 0.006)

Interview data; no differences in height between cases and controls

* BMI = body mass index; OR = odds ratio for the highest quantile; NS = not significant.

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Table 2 presents a review of the data from 11 cohort studies published from 1984 to 2000 (33-43). The results are mixed. Five of the reports suggested that there was a positive association of prostate cancer with either body mass index, lean body mass, weight, or percent desirable weight (36, 37, 40, 41, 43). The findings with regard to height will be discussed below. The six studies that showed no association reported on either BMI, lean body mass, weight, waistto-hip ratio, or triceps skinfold thickness (33-35, 38, 39, 42). Five (34-37, 41) of the 11 investigations examined the subjects for their anthropometric measurements. Three of these studies (36, 37, 41) found a positive association with either body weight or BMI (relative risk = 1.3-2.2). Two (36, 43) of the 11 studies had death, instead of incident prostate cancer cases, as the outcome. They both found positive associations with the percent desirable weight or other measures of obesity. This suggests that severity of disease may be an important factor, since the majority of cases with prostate cancer do not die from their disease.


The findings for height are even more uncertain than the findings of the other anthropometric measurements in the cohort studies. Three (36, 38, 40) of the nine studies in table 2 that included height reported a positive association. The relative risks ranged from 1.3 to 1.8 in these investigations. Of the five studies that examined their subjects, just one (36) showed a positive relation. Two (36, 38) of the three positive studies had death or advanced disease as the outcome. However, these findings are tempered by the fact that six of the other cohort studies reported no association. Furthermore, none of the six case-control studies in table 1 that reported on height found any association. Because lean body mass has also been correlated with BMI, researchers examined the association of the former with prostate cancer in three of the studies listed in table 2. Andersson et al. (36) found a positive association (relative risk = 1.3), while the other two groups of researchers (33, 35) reported that there was no relation between lean body mass and prostate cancer risk. Earlier, it was observed that

Summary of results from cohort studies of anthropometry and prostate cancer

Study (reference no.), year, location

No. of subjects




Shuuman et al. (33), 2000, The Netherlands

58,279 men; 681 cases

BMI* LBM* Height

RR* = 0.9 (NS*) RR = 1 0 (NS) RR= 1.0 (NS)

Questionnaire data; no association for advanced cases; BMI at age 20 years had positive association (RR = 1.3)

Habel et al. (34), 2000, California

70,712 men; 2,079 cases

BMI Weight Height

RR = 0 9 (NS) RR = 1.1 (NS) RR = 1.1 (NS)

Examination data

Lund Nilsen and Vatten (35), 1999, Norway

22,248 men; 642 cases

BMI LBM Weight Height


= = = =

1.0 1.1 1.0 1.2

(NS) (NS) (NS) (NS)

Examination data; suggestion of weak positive association with height

Andersson et al. (36), 1997, Sweden

135,006 men; 708 deaths

BMI LBM Weight Height

RR= RR = RR = RR =

1.4 1.3 1.3 1.3

(p = (p = (p = (p =

Veierod et al. (37), 1997, Norway

25,708 men; 72 cases

BMI Height

RR = 2.2 (p = 0.02) RR = 1.2 (NS)

Examination data

Giovannucci et al. (38), 1997, United States

47,781 professional men; 1,369 cases

BMI Waist/hip ratio Height

RR = 0.9 (NS) RR = 1.0(NS) RR = 1.4 (NS)

Questionnaire data; positive association with height (RR = 1.7) in advanced cases

Cerhan et al. (39), 1997, Iowa

1,050 men, 71 cases

BMI Weight Height

RR = 1.5 (p= 010) RR = 1.6 (p= 0.20) RR = 1.1 (p = 0.80)

Interview data

Le Marchand et al. (40), 1994, Hawaii

20,316 multiethnic men, 198 cases

BMI Weight Height

RR = 0.7 (NS) RR = 0.9 (NS) RR = 1.8 (p = 0.01)

Chyou etal. (41), 1994, Hawaii

7,840 Japanese men; 306 cases

Weight BMI Height Triceps skinfold

RR = 1.5 (p = 0.008) No significant difference No significant difference No significant difference

Mills et al. (42), 1989, California

14,000 Seventh Day Adventists; 180 cases


RR = 1.2(NS)

Mailed questionnaire data

Snowdon et al. (43), 1984, California

6,763 Seventh Day Adventists; 84 deaths

Percent, desirable weight

RR = 2.4 (p< 0.01)

Questionnaire data

0.04) 0.002) 0.002) 0.04)

Examination data; 2,368 incident cases also show positive, but weak associations

Interview data

Examination data

' ! BMI = body mass index; LBM = lean body mass; RR = relative risk for the highest quantile; NS = not significant.

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Body Size and Prostate Cancer

the area of muscle in the arm, but not the area of fat in the arm, was positively related to prostate cancer risk (44). However, this finding has yet to be replicated by other researchers. Overall, the results on BMI are inconsistent. In addition, this index is related to both lean body mass and body fat, which leads to limitations in the interpretation of results associated with this index. Although the distribution of body fat is also an important consideration, only three studies (22, 26, 38) in tables 1 and 2 combined have included measurements in waist circumference or waist-to-hip ratios. They have reported no association of these measurements with prostate cancer. Data are also sparse in assessing whether childhood or infant obesity is more important than adult obesity in relation to prostate cancer. One preliminary study of birth weight followed 366 men and found that high birth weight was associated with prostate cancer in 21 cases (45). However, in another report, obesity at age 10 years, assessed in 33,326 men, was found to be inversely related to the risk of advanced and metastatic prostate cancer (38). BIOLOGIC MECHANISMS

If obesity is related to prostate cancer, then the biologic pathways are likely to be complex. Obesity has effects on the hypothalamic-pituitary-adrenocortical/thyroid/gonadal axis, as well as on growth hormones, gut hormones, the pancreas, and the sympathetic nervous system in humans (46). It is associated with numerous endocrine changes such as increased estrogen and decreased testosterone levels (47, 48). Obesity leads to lowered sex hormonebinding globulin, which could increase unbound testosterone levels. Researchers have suspected that testosterone is related to prostate cancer risk, but the association has not been established (49). Obesity is also related to insulin resistance and hyperinsulinemia (50). The syndrome of insulin resistance, or syndrome X, consists of the frequent association of abdominal obesity, hyperinsulinemia, hypertension, dyslipidemia, and accelerated atherosclerosis in the same individual (51). However, no reports have been found on the association between insulin resistance and prostate cancer. Insulin-like growth factors have mitogenic properties and stimulate the growth of normal and tumor cells in the prostate gland (52). Recent studies support the presence of a positive association of insulin-like growth factor-1 with prostate cancer risk (53, 54). Insulin-like growth factor-1 has been positively related to height in children (55), but not in adults (54, 56). Energy intake, BMI, and physical activity affect blood levels of insulin-like growth factors and insulin-like growth factor binding proteins, but their relations are complex and still need to be disentangled (57). The association between insulin-like growth factors and prostate cancer is covered in greater depth in a separate review in this special issue of Epidemiologic Reviews. The cloning of the Lep gene responsible for obesity in the ob/ob mouse in 1994 led to much interest in the pathophysiology of obesity (58). Leptin, the protein product of the adipocyte-specific ob gene, is believed to have a role in Epidemiol Rev Vol. 23, No. 1, 2001


weight regulation and energy expenditure (59). In humans, the place of leptin in the pathogenesis of obesity is unclear. Most obese persons do not have any abnormality in the coding sequence for leptin (60). The production of leptin is increased by insulin and glucocorticoids (61), but the 24hour profiles of circulating leptin are not correlated with insulin levels (62). It has a circadian rhythm, with serum leptin levels being lowest around noon to mid-afternoon and highest between midnight and early-morning hours. Because of these complexities in the physiology of leptin, it is not surprising that no association was found in a preliminary study of serum leptin in 43 prostate cancer cases and 48 controls (63). FUTURE RESEARCH

Inexpensive and uninvasive methods to assess adiposity need to be developed to advance our knowledge on the association of obesity with prostate cancer. The BMI has been commonly used, but it has apparent shortcomings in estimating obesity. Bioelectric impedance analysis, as an uninvasive method to estimate percent body fat and lean body mass (64), deserves consideration, although it has limitations in assessing body fat in severe obesity (65). Little attention has been paid to the association of adolescent obesity or body fat distribution with prostate cancer. More information is needed on the possible role of hormones, insulin-like growth factors, and leptin in relation to obesity and prostate cancer risk. Future epidemiologic studies to determine whether body size (obesity) affects prostate cancer risk should include as many of the following features as possible: 1. They should preferably be cohort studies instead of case-control studies, unless the case-control studies have valid data on anthropometric measurements predating the diagnosis of prostate cancer. 2. The participants should be measured according to established standards, and at least height, weight, waist-tohip ratio, and skinfold thicknesses should be included in the study. More current anthropometric techniques to measure body fat distribution should be considered. 3. Because of the importance of severity of disease in prostate cancer research, prostate cancer incidence, stage of disease at time of diagnosis, and mortality outcomes should be recorded on participants in cohort studies. However, the problem of competing causes of death and possible information bias in recording the underlying cause of death should be considered in using prostate cancer mortality as the outcome (66). 4. Blood samples should be collected at the time of anthropometric measurements in cohort studies to enable investigators to measure biomarkers that could be helpful in determining whether obesity or related factors are associated with prostate cancer risk. 5. Family history of prostate cancer and relevant gene markers should be included in the study to enable the investigators to assess gene-environment interactions in relation to body size and prostate cancer.




This work was supported by grants R01 CA 33644 and R01 CA 54281 from the National Cancer Institute, National Institutes of Health.

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REFERENCES 1. Lukaski HC. Methods for the assessment of human body composition: traditional and new. Am J Clin Nutr 1987;46: 537-56. 2. Heymsfield SB, Allison DB, Wang ZM, et al. Evaluation of total and regional body composition. In: Bray GA, Bouchard C, James WPT, eds. Handbook of obesity. New York, NY: Marcel Dekker, 1998:41-77. 3. Bouchard C, Bray GA, Hubbard VS. Basic and clinical aspects of regional fat distribution. Am J Clin Nutr 1990;52: 946-50. 4. Rosenbaum M, Leibel RL, Hirsch J. Obesity. N Engl J Med 1997;337:396-407. 5. Mokdad AH, Serdula MK, Dietz WH, et al. The spread of the obesity epidemic in the United States, 1991-1998. JAMA 1999;282:1519-22. 6. Wickelgren I. Obesity: how big a problem? Science 1998; 280:1364-7. 7. Grundy SM. Multifactorial causation or obesity: implications for prevention. Am J Clin Nutr 1998;67(suppl):563S-72S. 8. Bray GA, Bouchard C, James WPT. Definitions and proposed current classification of obesity. In: Bray GA, Bouchard C, James WPT, eds. Handbook of obesity. New York, NY: Marcel Dekker, 1998:31^0. 9. Revicki DA, Israel RG. Relationship between body mass indices and measures of body adiposity. Am J Public Health 1986;76:992-4. 10. Calle EE, Thun MJ, Petrelli JM, et al. Body-mass index and mortality in a prospective cohort of US adults. N Engl J Med 1999;341:1097-105. 11. Stevens J, Cai J, Pamuk ER, et al. The effect of age on the association between body mass index and mortality. N Engl JMed 1998;338:l-7. 12. Lee IM, Manson JE, Hennekens CH, et al. Body weight and mortality: a 27-year follow-up of middle-aged men. JAMA 1993:270:2823-8. 13. Garn SM, Leonard WR, Hawthorne VM. Three limitations of the body mass index. Am J Clin Nutr 1986;44:996-7. 14. Bowman RL, DeLucia JL. Accuracy of self-reported intake: a meta-analysis. Behav Ther 1992;23:6637-58. 15. Cameron R, Evers SE. Self-reported issues in obesity and weight management: state-of-the-art and future directions. Behav Assess 1990;12:91-106. 16. Folsom AR, Kushi LH, Anderson KE, et al. Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women's Health Study. Arch Intern Med 2000;160:2117-28. 17. Schapira DV, Kumar NB, Lyman GH, et al. Upper-body fat distribution and endometrial cancer risk. JAMA 1991 ;266: 1808-11. 18. Lapidus L, Bengtsson C, Larsson B, et al. Distribution of adipose tissue and risk of cardiovascular disease and death: a 12-year follow-up of participants in the population study of women in Gothenburg, Sweden. Br Med J (Clin Res Ed) 1984;289:1257-61. 19. Bjorntop P. Adipose-tissue in obesity. In: Hitsch J, Van Itallie TB, eds. Recent advances in obesity research. 4th ed. London, England: John Libbey, 1985:163-70. 20. Albanes D, Jones DY, Schartzkin A, et al. Adult stature and risk of cancer. Cancer Res 1988;48:1658-62. 21. Hsieh CC, Thanos A, Mitropoulos D, et al. Risk factors for

25. 26.

27. 28. 29. 30.

31. 32. 33. 34. 35. 36.

37. 38. 39.

40. 41.

42. 43.

prostate cancer: a case-control study in Greece. Int J Cancer 1999;80:699-703. Demark-Wahnefried W, Conaway MR, Robertson CN, et al. Anthropometric risk factors for prostate cancer. Nutr Cancer 1997;28:302-7. Gronberg H, Damber L, Damber JE. Total food consumption and body mass index in relation to prostate cancer risk: a case-control study in Sweden with prospectively collected exposure data. J Urol 1996;155:969-74. Ghadirian P, Lacroix A, Maisonneuve P, et al. Nutritional factors and prostate cancer: a case-control study of French Canadians in Montreal, Canada. Cancer Causes Control 1996;7:428-36. Rohan TE, Howe GR, Burch JD, et al. Dietary factors and risk of prostate cancer: a case-control study in Ontario, Canada. Cancer Causes Control 1995 ;6:145-54. Whittemore AS, Kolonel LN, Wu AH, et al. Prostate cancer in relation to diet, physical activity, and body size in blacks, whites, and Asians in the United States and Canada. J Natl Cancer Inst 1995;87:652-61. Andersson SO, Baron J, Wolk A, et al. Early life risk factors for prostate cancer: a population-based case-control study in Sweden. Cancer Epidemiol Biomarkers Prev 1995;4:187-92. Gann PH, Hennekens CH, Sacks FM, et al. Prospective study of plasma fatty acids and risk of prostate cancer. J Natl Cancer Inst 1994;86:281-6. Walker ARP, Walker BF, Tsotetsi NG, et al. Case-control study of prostate cancer in black patients in Soweto, South Africa. Br J Cancer 1992;65:438^1. West DW, Slattery ML, Robison LM, et al. Adult dietary intake and prostate cancer risk in Utah: a case-control study with special emphasis on aggressive tumors. Cancer Causes Control 1991;2:85-94. Kolonel LN, Yoshizawa CN, Hankin JH. Diet and prostatic cancer: a case-control study in Hawaii. Am J Epidemiol 1988;127:999-1012. Talamini R, La Vecchia C, Decarli A, et al. Nutrition, social factors and prostatic cancer in a northern Italian population. Br J Cancer 1986;53:817-21. Schuurman AG, Goldbohm RA, Dorant E, et al. Anthropometry in relation to prostate cancer risk in the Netherlands cohort study. Am J Epidemiol 2000;151:541-9. Habel LA, Van Den Eeden SK, Friedman GD. Body size, age at shaving initiation, and prostate cancer in a large multiracial cohort. Prostate 2000;43:136-43. Lund Nilsen TI, Vatten LJ. Anthropometry and prostate cancer risk: a prospective study of 22,248 Norwegian men. Cancer Causes Control 1999; 10:269-75. Andersson SO, Wolk A, Bergstrom R, et al. Body size and prostate cancer: a 20-year follow-up study among 135,006 Swedish construction workers. J Natl Cancer Inst 1997;89: 385-9. Veierod MB, Laake P, Thelle DS. Dietary fat intake and risk of prostate cancer: a prospective study of 25,708 Norwegian men. Int J Cancer 1997;73:634-38. Giovannucci E, Rimm EB, Stampfer MJ, et al. Height, body weight, and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 1997;6:557-63. Cerhan JR, Tomer JC, Lynch CF, et al. Association of smoking, body mass, and physical activity with risk of prostate cancer in the Iowa 65+ Rural Health Study (United States). Cancer Causes Control 1997;8:229-38. Le Marchand L, Kolonel LN, Wilkens LR, et al. Animal fat consumption and prostate cancer: a prospective study in Hawaii. Epidemiology 1994;5:276-82. Chyou PH, Nomura AMY, Stemmermann GN. A prospective study of weight, body mass index and other anthropometric measurements in relation to site-specific cancers. Int J Cancer 1994;57:313-17. Mills PK, Beeson L, Phillips RL, et al. Cohort study of diet, lifestyle, and prostate cancer in Adventist men. Cancer 1989; 64:598-604. Snowdon DA, Phillips RL, Choi W. Diet, obesity, and risk of Epidemiol Rev Vol. 23, No. 1, 2001

Body Size and Prostate Cancer fatal prostate cancer. Am J Epidemiol 1984;120:244-50. 44. Severson RK, Grove JS, Nomura AMY, et al. Body mass and prostatic cancer: a prospective study. BMJ 1988;297:713-15. 45. Tibblin G, Eriksson M, Cnattingius S, et al. High birth weight as a predictor of prostate cancer risk. Epidemiology 1995;6:423-4. 46. Drent ML. Effects of obesity on endocrine function. In: Bray GA, Bouchard C, James WPT, eds. Handbook of obesity. New York, NY: Marcel Dekker, 1998:753-73. 47. Zumoff B. Hormonal abnormalities in obesity. Acta Med ScandSuppl 1988;723:153-60. 48. Pasquali R, Casimirri F, Cantobelli S, et al. Effects of obesity and body fat distribution on sex hormones and insulin in men. Metabolism 1991;40:101^l. 49. Nomura AMY, Kolonel LN. Prostate cancer: a current perspective. Am J Epidemiol 1991; 13:200-27. 50. Bjorntorp P. Metabolic implications of body fat distribution. Diabetes Care 1991; 14:1132-43. 51. Garber AJ. Diabetes mellitus. In Stein JH, ed. Internal medicine. St. Louis, MO: Mosby, 1998:1851-74. 52. Cohen P, Peehl DM, Rosenfeld RG. The IGF axis in the prostate. Horm Metab Res 1994;26:81-4 53. Wolk A, Mantzoros CS, Andersson SO, et al. Insulin-like growth factor 1 and prostate cancer risk: a population-based, case-control study. J Natl Cancer Inst 1998;90:911-15. 54. Chan JM, Stampfer MJ, Giovannucci E, et al. Plasma insulinlike growth factor-I and prostate cancer risk: a prospective study. Science 1998;279:563-6. 55. Juul A, Bang P, Hertel NT, et al. Serum insulin-like growth factor-I in 1030 healthy children, adolescents, and adults: relation to age, sex, stage of puberty, testicular size, and body mass index. J Clin Endocrinol Metab 1994;78:744-52.

Epidemiol Rev Vol. 23, No. 1, 2001


56. Ma J, Pollak MN, Giovannucci E, et al. Prospective study of colorectal cancer risk in men and plasma levels of insulinlike growth factor (IGF)-I and IGF-binding protein-3. J Natl Cancer Inst 1999;91:620-5. 57. Yu H, Rohan T. Role of the insulin-like growth factor family in cancer development and progression. J Natl Cancer Inst 2000;92:1472-89. 58. Havel PJ. Leptin production and action: relevance to energy balance in humans. Am J Clin Nutr 1998;67:355-6. 59. Luke AH, Rotimi CN, Cooper RS, et al. Leptin and body composition of Nigerians, Jamaicans, and US blacks. Am J Clin Nutr 1998;67:391-6. 60. Considine RV, Considine EL, Williams CJ, et al. Evidence against either a premature stop codon or the absence of obese gene mRNA in human obesity. J Clin Invest 1995;95:2986-8. 61. Leibowitz SF, Hoebel BG. Behavioral neuroscience of obesity. In: Bray GA, Bouchard C, James WPT, eds. Handbook of obesity. New York, NY: Marcel Dekker, 1998:313-58. 62. Fruhbeck G, Jebb SA, Prentice AM. Leptin: physiology and pathophysiology. Clin Physiol 1998;18:399-419. 63. Lagiou P, Signorello LB, Trichopoulos D, et al. Leptin in relation to prostate cancer and benign prostatic hyperplasia. Int J Cancer 1998;76:25-8. 64. Segal KR, Loan MV, Fitzgerald PI, et al. Lean body mass estimation by bioelectrical impedance analysis: a four-site cross-validation study. Am J Clin Nutr 1988;47:7-14. 65. Deurenberg P. Limitations of the bioelectrical impedance method for the assessment of body fat in severe obesity. Am J Clin Nutr 1996;64(suppl):449S-52S. 66. Newschaffer CJ, Otani K, McDonald MK, et al. Causes of death in elderly prostate cancer patients and in a comparison nonprostate cancer cohort. J Natl Cancer Inst 2000; 92:613-21.