1. Lynch CM, Sexton DJ, Hession M, Morrison JJ. Obesity and mode of delivery in primigravid and multigravid women. Am J Perinatol. 2008;25:163–167.[PubMed]
2. Rooney B, Schauberger C. Excess pregnancy weight gain and long-term obesity: one decade later. Obstet Gynecol. 2002;100:245–252.[PubMed]
3. de Boo HA, Harding JE. The developmental origins of adult disease (Barker) hypothesis. Aust N Z J Obstet Gynaecol. 2006;46:4–14.[PubMed]
4. Barker DJP. Fetal and infant origins of adult disease. BMJ. 1990;301:1111.[PMC free article][PubMed]
5. Whitaker RC. Predicting preschooler obesity at birth: the role of maternal obesity in early pregnancy. Pediatrics. 2004;114:e29–e36.[PubMed]
6. Oken E, Gillman MW. Fetal origins of obesity. Obesity Res. 2003;11:496–506.[PubMed]
7. Gallagher D, Heymsfield SB, Heo M, et al. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000;72:694–701.[PubMed]
8. Fain JN. Release of interleukins and other inflammatory cytokines by human adipose tissue is enhanced in obesity and primarily due to the nonfat cells. Vitam Horm. 2006;74:443–477.[PubMed]
9. Kershaw EE, Flier JS. Adipose tissue as an endocrine organ. J Clin Endocrinol Metab. 2004;89:2548–2556.[PubMed]
10. Kim SY, Dietz PM, England L, et al. Trends in pre-pregnancy obesity in nine states, 1993–2003. Obesity. 2007;15:986–993.[PubMed]
11. Committee on the Impact of Pregnancy Weight on Maternal and Child Health, National Research Council, authors. Influence of Pregnancy Weight on Maternal and Child Health: Workshop Report. Washington, DC: The National Academies Press; 2007.
12. Brawarsky P, Stotland NE, Jackson RA, et al. Pre-pregnancy and pregnancy-related factors and the risk of excessive or inadequate gestational weight gain. Int J Gynaecol Obstet. 2005;91:125–131.[PubMed]
13. Keppel KG, Taffel SM. Medical advice on maternal weight gain and actual weight gain. Results from the 1988 National Maternal and Infant Health Survey. Am J Public Health. 1993;83:1100–1103.[PubMed]
14. Oken E, Taveras EM, Popoola FA, et al. Television, walking, and diet: associations with postpartum weight retention. Am J Prevent Med. 2007;32:305–311.[PMC free article][PubMed]
15. Villamor E, Cnattingius S. Interpregnancy weight change and risk of adverse pregnancy outcomes: a population-based study. Lancet. 2006;368:1164–1170.[PubMed]
16. Chu SY, Kim SY, Lau C, et al. Maternal obesity and risk of stillbirth: a metaanalysis. Am J Obstet Gynecol. 2007;197:223–228.[PubMed]
17. Weiss JL, Malone FD, Emig D, et al. Obesity, obstetric complications and cesarean delivery rate-a population-based screening study. Am J Obstet Gynecol. 2004;190:1091–1097.[PubMed]
18. O’Brien TE, Ray JG, Chan WS. Maternal body mass index and the risk of preeclampsia: a systematic overview. Epidemiology. 2003;14:368–374.[PubMed]
19. Chu SY, Kim SY, Schmid CH, et al. Maternal obesity and risk of cesarean delivery: a meta-analysis. Obstet Rev. 2007;8:385–394.[PubMed]
20. Ehrenberg HM, Dierker L, Milluzzi C, Mercer BM. Prevalence of maternal obesity in an urban center. Am J Obstet Gynecol. 2002;187:1189–1193.[PubMed]
21. Carroll CS , Sr, Magann EF, Chauhan SP, et al. Vaginal birth after cesarean section versus elective repeat cesarean delivery: weight-based outcomes. Am J Obstet Gynecol. 2003;188:1516–1520.[PubMed]
22. Durnwald C, Ehrenberg H, Mercer B. The impact of maternal obesity and weight gain on VBAC success. Am J Obstet Gynecol. 2003;189:S205.
23. Soens MA, Birnbach DJ, Ranasinghe JS, van Zundert A. Obstetric anesthesia for the obese and morbidly obese patient: an ounce of prevention is worth more than a pound of treatment. Acta Anaesthesiol Scand. 2008;52:6–19.[PubMed]
24. Vahratian A, Zhang J, Troendle JF, et al. Maternal pre-pregnancy overweight and obesity and the pattern of labor progression in term nulliparous women. Obstet Gynecol. 2004;104:943–951.[PubMed]
25. Nuthalapaty FS, Rouse DJ, Owen J. The association of maternal weight with cesarean risk, labor duration, and cervical dilation rate during labor induction. Obstet Gynecol. 2004;103:452–456.[PubMed]
26. Denison FC, Price J, Graham C, et al. Maternal obesity, length of gestation, risk of postdates pregnancy and spontaneous onset of labour at term. BJOG. 2008;115:720–725.[PMC free article][PubMed]
27. Ehrenberg H, Mercer B, Catalano P. The influence of obesity and diabetes on the prevalence of macrosomia. Am J Obstet Gynecol. 2004;191:964–968.[PubMed]
28. Anath CV, Wen SW. Trends in fetal growth among singleton gestations in the United States and Canada, 1985 through 1998. Semin Perinatol. 2002;26:260–267.[PubMed]
29. Ørskou J, Kesmodel U, Henriksen TB, Secher NJ. An increasing proportion of infants weigh more than 4000 grams at birth. Acta Obstet Gynaecol Scand. 2001;80:931–936.[PubMed]
30. Surkan PJ, Hsieh CC, Johansson AL, et al. Reasons for increasing trends in large for gestational age births. Obstet Gynecol. 2004;104:720–726.[PubMed]
31. Sewell MF, Huston-Presley L, Super DM, Catalano P. Increased neonatal fat mass, not lean body mass, is associated with maternal obesity. Am J Obstet Gynecol. 2006;195:1100–1103.[PubMed]
32. Hull HR, Dinger MK, Knehans AW, et al. Impact of maternal body mass index on neonate birthweight and body composition. Am J Obstet Gynecol. 2008;198:416.e1–416.e6.[PubMed]
33. Catalano PM, Ehrenberg HM. The short- and long-term implications of maternal obesity on the mother and her offspring. BJOG. 2006;113:1126–1133.[PubMed]
34. Waller DK, Mills JL, Simpson JP, et al. Are obese women at higher risk for producing malformed offspring? Am J Obstet Gynecol. 1994;170:541–548.[PubMed]
35. Watkins ML, Rasmussen SA, Honein MA, et al. Maternal obesity and risk for birth defects. Pediatrics. 2003;111:1152–1158.[PubMed]
36. Rasmussen SA, Chu SY, Kim SY, et al. Maternal obesity and risk of neural tube defects: a meta-analysis. Am J Obstet Gynecol. 2008;198:611–619.[PubMed]
37. Hedderson MM, Williams MA, Holt VL, et al. Body mass index and weight gain prior to pregnancy and risk of gestational diabetes mellitus. Am J Obstet Gynecol. 2008;198:409.e1–409.e7.[PMC free article][PubMed]
38. Chu SY, Callaghan WM, Kim SY, et al. Maternal obesity and risk of gestational diabetes mellitus. Diabetes Care. 2007;30:2070–2076.[PubMed]
39. Radaelli T, Varastehpour A, Catalano P, Hauguelde Mouzon S. Gestational diabetes induces placental genes for chronic stress and inflammatory pathways. Diabetes. 2003;52:2951–2958.[PubMed]
40. Yogev Y, Langer O. Pregnancy outcome in obese and morbidly obese gestational diabetic women. Eur J Obstet Gynaecol Reprod Biol. 2008;137:21–26.[PubMed]
41. Catalano PM, Thomas A, Huston-Presley L, Amini SB. Increased fetal adiposity: a very sensitive marker of abnormal in utero development. Am J Obstet Gynecol. 2003;189:1698–1704.[PubMed]
42. Gillman MW, Rifas-Shiman S, Berkey CS, et al. Maternal gestational diabetes, birth weight, and adolescent obesity. Pediatrics. 2003;111:e221–e226.[PubMed]
43. Honda K. Factors underlying variation in receipt of physician advice on diet and exercise: applications of the behavioral model of health care utilization. Am J Health Promot. 2004;18:370–377.[PubMed]
44. Power ML, Cogswell ME, Schulkin J. Obesity prevention and treatment practices of U.S. obstetrician-gynecologists. Obstet Gynecol. 2006;108:961–968.[PubMed]
There is a worldwide growing trend in obesity, partly because more people are eating high-calorie diets and are less physically active. Obesity greatly increases the risk of developing cardiovascular disease (CVD),1 type 2 diabetes, hypertension, and dyslipidemia and leads to increased mortality. Obesity is a common problem in older men. Approximately 50% of men over 50 years of age are overweight, and body weight tends to increase with age (1). The Korean National Health and Nutrition Surveys reported an increase in prevalence of obesity in South Korea from 1995 to 2001, and an age-related increase in prevalence of obesity in Korean adults in 2001 (2).
Prostatic hyperplasia is another prevalent problem among older men, and it has received more attention as the average human lifespan increases. Although the prevalence of prostatic hyperplasia depends on definition (3), Ekman (4) reported that 40% of men in their 70s have clinical prostatic hyperplasia, and 80% have structural prostatic hyperplasia. In South Korea, prevalence of clinical prostatic hyperplasia was reported to be from 10.6% to 31% in men over 50 years of age, with an age-related increase (5,6).
There is insufficient research on risk factors for prostatic hyperplasia, especially the role of obesity, and the results of the existing studies are inconsistent. Some investigators have reported that obesity may influence prostatic enlargement by raising estrogen concentration and may worsen urinary obstructive symptoms by increasing activity of sympathetic nervous systems (7,8,9,10,11), whereas others have observed no such relationships (12,13,14,15). Hammarsten and Hogstedt (16) concluded that obesity-related metabolic diseases, such as type 2 diabetes, hypertension, and dyslipidemia, were associated with prostatic hyperplasia. However, it is not known whether obesity without overt metabolic diseases raises the risk of prostatic hyperplasia, because previous studies have not excluded the effect of overt obesity-related metabolic diseases. Therefore, this study examined the effect of obesity on prostate volume in men over 40 years of age without overt obesity-related metabolic diseases.
Research Methods and Procedures
We studied 146 men over 40 years of age without overt obesity-related metabolic diseases, such as hypertension, impaired fasting glucose, diabetes, dyslipidemia, or CVD. Written informed consent was obtained from each subject before enrollment in this study. The study was approved by the Institutional Review Board of the Medical Research Institute, Pusan National University, and was performed in accordance with the principles of the Declaration of Helsinki.
In all, 416 men over 40 years of age visited the Nutrition Obesity and Metabolism Center, Pusan National University Hospital, for transrectal ultrasonography between March 2001 and April 2002. Transrectal ultrasonography is regarded as an accurate and reproducible method for determining prostatic volume (17,18,19,20,21).
Prostatic hyperplasia was defined as a prostatic volume >20 mL, which is commonly used as one parameter of clinical benign prostatic hyperplasia criteria (22,23). We surveyed subjects’ current and previous diseases and smoking, drinking, and exercise habits and performed routine blood, lipid, and liver function tests, transrectal ultrasonography, and an electrocardiogram. In addition, plasma fasting glucose, serum prostate specific antigen (PSA), total testosterone, and dehydroepiandrosterone sulfate (DHEA-S) levels were measured.
Smoking status was divided into three categories: current smoker, ex-smoker, and non-smoker. A registered dietitian determined subjects’ daily average nutrition intake of energy, proteins, fats, carbohydrates, and alcohol for 3 months using a Semi-Quantitative Food Frequency Questionnaire. Alcohol consumption habit was divided into two categories, based on 30 grams of pure alcohol per day. The subjects were asked whether they exercised regularly at a moderate intensity that left them feeling slightly out of breath and sweating. Regular exercise was defined as more than three times per week.
Patients using 5α-reductase inhibitors, antihypertensive, antidiabetic, or lipid-lowering medication, or who had been treated for coronary heart disease or ischemic stroke were excluded. Subjects with abnormal fasting glucose (≥110 mg/dL) underwent a second fasting glucose test on another day, and those with a consistent abnormal glucose level were excluded. Subjects with a high fasting cholesterol level (total cholesterol ≥ 200 mg/dL), confirmed high blood pressure (according to the recommendation of the Joint National Committee) (7), or evidence of ischemia on electrocardiogram were excluded.
In all, we excluded 270 patients with one or more exclusion criteria: dyslipidemia (225), hypertension (97), impaired fasting glucose or diabetes (46), CVD (8), taking 5-αreductase inhibitors (12), suspected prostate cancer by transrectal ultrasonography (7), previous prostate surgery (3), or BMI <18.5 kg/m2 (1). A total of 146 men were included in this study. The 146 subjects were divided into three groups according to BMI: normal (18.5 to 22.9 kg/m2), overweight (23 to 24.9 kg/m2), and obese (≥25 kg/m2). They were also categorized into two groups by waist circumference: normal waist (≤90 cm) and central obesity (>90 cm). Classification of the subgroups was based on the Asia-Pacific criteria of obesity (24).
The same urologist, who did not have information about the aim of the study, estimated prostate volume using transrectal ultrasonography (SA-8800; Medison Co., Ltd., Seoul, Korea). The volume of the prostate was calculated by elliptical volume measurement (π/6 × transverse × anteroposterior × cephalocaudal diameter). The BMI was calculated as weight (kilograms) divided by height squared (meters squared). Waist circumference was measured at the narrowest point between the lowest rib and the uppermost lateral border of the right iliac crest. Height and weight were measured by a registered nurse.
Blood samples were collected from the antecubital vein after at least 8 hours of fasting. Total cholesterol and liver function parameters were measured using enzymatic methods with a Hitachi 7600 chemical auto-analyzer (Hitachi Co., Ltd., Tokyo, Japan). Glucose was measured by the glucose oxidase method using a Synchron LX20 (Beckman Coulter, Inc., Fullerton, CA). Serum total testosterone was measured using a commercial radioimmunoassay (RIA; Coat-A-Count Total Testosterone, Diagnostic Products Corp., Los Angeles, CA). The Coat-A-Count procedure is a solid-phase RIA, based on a testosterone-specific antibody immobilized to the wall of a polypropylene tube. 125I-labeled testosterone competes for antibody sites for a fixed time with testosterone in the subject's sample. The Coat-a-Count Total Testosterone kit was adapted for serum measurements as per Disease Prevention and Control research protocols. The lower limit of detection was 0.14 nM. The mean intra- and inter-assay coefficients of variation were 3.9% and 2.5%, respectively. Plasma level of DHEA-S was also determined by a commercial RIA (Coat-A-Count DHEA-SO4; Diagnostic Products Corp.). The lower limit of detection was 5 μg/dL. The mean intra- and inter-assay coefficient of variation values were 4.7% and 8.3%, respectively. PSA was measured using a chemiluminescence method (Modular Analytics E 170; Roche Diagnostics, Indianapolis, IN). Because hormone concentrations vary during the day, blood was sampled at the same time (between 9:00 am and 10:00 am).
Statistical analyses were performed using the SPSS statistical package (SPSS for Windows 10.0; SPSS, Chicago, IL). ANOVA with Scheffé's post hoc test was used to determine the statistical significance of the differences in age, blood pressure, fasting glucose, total cholesterol, daily energy, protein, fat, and carbohydrate intake between groups. The χ2 test was used to determine the statistical significance of differences in smoking status, exercise habits, and alcohol consumption between groups. The significance of differences in prostate volume, serum total testosterone, and DHEA-S among groups based on BMI was examined using ANOVA with Scheffé's post hoc test and among groups based on waist circumference with a two-sample Student's t test. The correlations among prostate volume and age, obesity, total testosterone, and DHEA-S were determined using the Pearson correlation coefficient. The correlations among prostate volume and alcohol intake, smoking, and exercise habits were determined using the Spearman correlation coefficient. After adjusting for age, the correlations between prostate volume and BMI and waist circumference were determined using partial correlation coefficients. The correlation between prostate volume and total testosterone level was determined using a partial correlation coefficient adjusted for age, BMI, and waist circumference. Odds ratios (ORs) were calculated using binary logistic regression analysis to evaluate the associations between obesity indices and prostatic hyperplasia, which was defined as a prostate volume >20 mL, after adjusting for age, testosterone level, fasting glucose level, total cholesterol level, systolic and diastolic blood pressure, total energy intake, alcohol intake, smoking status, exercise, and BMI category or abdominal circumference categories for each other categorical subgroup. p < 0.05 was considered statistically significant. All statistical tests were two-sided.
The age distribution of the 146 subjects was as follows: 60, 56, 29, and 1 were in their 40s (41%), 50s (38%), 60s (20%), and 70s (1%), respectively. There was no significant difference in the average age across the normal (52.1 ± 9.2 years), overweight (51.5 ± 7.6 years), and obese (52.2 ± 7.4 years) groups. Systolic blood pressure, total cholesterol, fasting glucose level, daily carbohydrate, fat intake, exercise, smoking, and drinking did not differ across the normal, overweight, and obese groups, but daily energy and protein intake were significantly greater in the obese group than in the normal group, and diastolic blood pressure was significantly greater in the obese group than in the overweight group (Table 1). There were no significant differences in age, blood pressure, total cholesterol, fasting glucose level, energy, carbohydrate, protein, and fat intake, exercise, smoking, and drinking between the normal waist and central obesity groups (Table 2).
|Age (years)||52.1 ± 9.2||51.5 ± 7.6||52.2 ± 7.4||52.0 ± 8.1|
|SBP (mm Hg)||115.8 ± 12.6||115.3 ± 11.5||120.1 ± 11.2||117.4 ± 11.9|
|DBP (mm Hg)||74.4 ± 6.9||72.1 ± 6.7*||75.8 ± 6.8*||74.4 ± 6.9|
|Fasting glucose (mg/dL)||85.4 ± 9.6||87.4 ± 9.7||84.4 ± 8.7||85.5 ± 9.3|
|Total cholesterol (mg/dL)||171.7 ± 18.1||180.2 ± 18.2||174.0 ± 16.4||174.8 ± 17.7|
|Total energy (kcal)||1975.9 ± 478.2*||2192.8 ± 391.5||2244.2 ± 409.3*||2138.9 ± 443.4|
|Protein (%)||14.6 ± 1.6*||14.9 ± 1.6||15.5 ± 1.4*||15.0 ± 1.5|
|Fat (%)||19.2 ± 6.7||18.3 ± 4.1||20.8 ± 4.5||19.6 ± 5.3|
|Carbohydrate (%)||66.2 ± 7.5||66.8 ± 5.5||63.6 ± 5.7||65.3 ± 6.4|
|≥30 g/d||19 (38.0)||18 (47.3)||25 (43.1)||62 (42.5)|
|<30 g/d||31 (62.0)||20 (52.7)||33 (56.9)||84 (57.5)|
|Current smoker||22 (44.0)||11 (28.9)||25 (43.1)||58 (39.7)|
|Ex-smoker||12 (24.0)||12 (31.6)||18 (31.1)||42 (28.8)|
|Nonsmoker||16 (32.0)||15 (39.5)||15 (25.8)||46 (31.5)|
|Yes||27 (54.0)||15 (39.5)||28 (48.3)||70 (47.9)|
|No||23 (46.0)||23 (60.5)||30 (51.7)||76 (52.1)|
|Age||52.2 ± 8.2||51.0 ± 7.5|
|SBP (mm Hg)||116.7 ± 12.3||119.8 ± 10.1|
|DBP (mm Hg)||74.0 ± 7.1||75.8 ± 6.2|
|Fasting glucose (mg/dL)||85.6 ± 9.7||85.1 ± 7.5|
|Total cholesterol (mg/dL)||175.9 ± 18.0||171.0 ± 16.1|
|Total energy (kcal)||2098.3 ± 446.1||2295.8 ± 402.2|
|Protein (%)||14.9 ± 1.5||15.6 ± 1.5|
|Fat (%)||19.3 ± 5.5||20.7 ± 4.5|
|Carbohydrate (%)||65.7 ± 6.6||63.6 ± 5.8|
|≥30 g/d||41 (35.3)||19 (63.3)|
|<30 g/d||75 (64.7)||11 (36.7)|
|Current smoker||45 (39.0)||13 (43.3)|
|Ex-smoker||32 (27.6)||10 (33.3)|
|Nonsmoker||39 (33.4)||7 (23.4)|
|Yes||55 (47.4)||13 (43.3)|
|No||61 (52.6)||17 (56.7)|
The prostate volume was 18.8 ± 5.0, 21.8 ± 7.2, and 21.8 ± 5.6 mL in the normal, overweight, and obese groups, respectively. There was a significant difference between the normal and obese groups (p = 0.03; Table 3) but not between the normal and overweight or overweight and obese groups. Prostate volume was 20.0 ± 6.0 mL in the normal waist and 23.7 ± 5.3 mL in the central obesity group, and this difference was significant (p = 0.002; Table 4).
|Prostate volume (mL)||18.8 ± 5.0*||21.8 ± 7.2||21.8 ± 5.6*||20.8 ± 6.0|
|Testosterone (nM)||22.3 ± 7.4†||19.8 ± 4.0||17.1 ± 5.0†||19.6 ± 6.1|
|DHEA-S (μg/dL)||180.8 ± 99.2||194.1 ± 97.4||220.7 ± 120.3||200.1 ± 108.4|
|Prostate volume (mL)||20.0 ± 6.0||23.7 ± 5.3*||20.8 ± 6.0|
|Testosterone (nM)||20.1 ± 6.4||17.5 ± 4.5†||19.6 ± 6.1|
|DHEA-S (μg/dL)||192.7 ± 104.8||228.9 ± 118.8||200.1 ± 108.4|
Serum Total Testosterone and DHEA-S
Serum testosterone levels were 22.3 ± 7.4, 19.8 ± 4.0, and 17.1 ± 5.0 nM in the normal, overweight, and obese groups, respectively, and the testosterone concentration was significantly lower in the obese group than in the normal group (p = 0.001; Table 3). In addition, serum testosterone levels were 20.1 ± 6.4 and 17.5 ± 4.5 nM in the normal waist and central obesity groups, respectively, and this difference was significant (p = 0.04; Table 4). The obese and central obesity groups had significantly lower serum testosterone concentrations and higher prostate volumes. There was no significant difference in the DHEA-S concentration between groups.
Association Between Prostate Volume and Obesity
The relationships between prostate volume and age, obesity index, testosterone, and lifestyle factors were tested. Age, BMI, and waist circumference were significantly correlated with prostate volume. There was no correlation between testosterone and prostate volume adjusted for age, BMI, and waist circumference (p = 0.80). The correlation coefficients of age, BMI, and waist circumference were 0.193, 0.245, and 0.251, respectively (p < 0.05). After adjusting for age, prostate volume was also positively correlated with BMI and waist circumference (partial correlation coefficients 0.270 and 0.265, respectively; p < 0.01; data not shown). Based on binary logistic regression analysis, the adjusted ORs of prostatic hyperplasia are shown in Table 5. Total testosterone level (adjusted OR = 1.23, p = 0.08; data not shown) and BMI categories did not affect prostatic hyperplasia, but waist circumference >90 cm was an independent factor associated with prostatic hyperplasia (OR = 3.37, 95% CI: 1.08 to 10.5). Relative to men with both low BMI (18.5 to 22.9 kg/m2) and normal waist circumference, those with high BMI (≥25 kg/m2) and central obesity were at significantly increased risk of prostatic hyperplasia (OR = 4.88, p = 0.008).
|Normal (18.5 to 22.9)||1|
|Overweight (23 to 24.9)||0.186||1, 93||0.73 to 5.09|
|Obese (≥25)||0.382||1, 62||0.55 to 4.80|
|>90 cm||0.037||3, 37||1.08 to 10.5|
|Combined obesity indices of BMI and waist circumference†|
|Normal BMI and waist circumference ≤90 cm (N = 50)||1|
|Overweight BMI and waist circumference ≤90 cm (N = 37)||0.222||1.85||0.69 to 4.95|
|Obese BMI and waist circumference ≤90 cm (N = 29)||0.526||1.43||0.47 to 4.36|
|Obese BMI and waist circumference >90 cm (N = 30)||0.008||4.88||1.52 to 15.6|
Obesity has strongly reproducible effects on the susceptibility to adult human diseases, is widely recognized as a risk factor for chronic diseases, and is associated with increased mortality. Prostatic hyperplasia is also a prevalent problem among men, and its incidence is expected to increase as the human lifespan is prolonged. However, there are few studies of risk factors for prostatic hyperplasia. Therefore, it would be meaningful to study the association between prostate volume and obesity.
It is not clear what causes prostatic hyperplasia, but aging may be the most important factor (25). Lee et al. (26) observed that age was the most significant risk factor for prostatic hyperplasia, and Berry et al. (27) also found that only patients over 30 years of age had prostatic hyperplasia and that the incidence was proportional to their age. It has not been proven that aging itself causes prostatic hyperplasia, but aging may result in prostatic hyperplasia through the synergistic stimulation of androgen and estrogen (28,29). We also found a positive correlation between prostate volume and age, and there was no significant difference in mean age across the subgroups in the study.
It is unclear whether there is an association between prostatic hyperplasia and smoking (12,15,30,31,32,33,34), drinking alcohol (13,14,15,30,31,35), and dietary intake (15,36). Our study found no significant difference in these factors across the subgroups and no significant correlation with prostate volume. Although the mechanism of action is unclear, physical activity consistently shows inhibitory effects on prostatic hyperplasia (15,37). We observed that physical activity had no significant effects on prostate volume.
Soygur et al. (7) reported that, in men younger than 60 years of age with a lower than calculated ideal body weight, the average weights of prostatectomy specimens were smaller than in those of the same age group who were 140% or more over their ideal body weight (46 vs. 60 grams, p < 0.01). These results indicated that obesity was a risk factor for prostatic enlargement. Daniell (8) also observed that adenoma weight increased with obesity in transurethral prostatectomy patients. In our study, prostate volume was positively correlated with BMI, waist circumference, and age (p < 0.05), and the correlations between prostate volume and obesity indices (BMI and waist circumference) were stronger after adjusting for age (p < 0.01; data not shown). In addition, prostate volume was significantly greater in men with BMI > 25 kg/m2 than in those with BMI < 23 kg/m2, and men with a waist circumference >90 vs. ≤90 cm. Giovannucci et al. (9) consistently found that, after adjustment for age and BMI, waist circumference was related to surgery for prostatic hyperplasia (OR = 2.38 for those with a waist circumference ≥109 cm relative to those with a waist circumference <89 cm). In our study, obesity index and BMI were positively associated with prostate volume but, when prostatic hyperplasia was defined as prostate volume >20 mL, binary logistic analyses showed that central obesity, not BMI, was related to prostatic hyperplasia. Roehrborn and Claus (38) and Meigs et al. (15) indicated that serum testosterone levels were unrelated to prostate volume. Soygur et al. (7) also reported that prostate volume was related only to the degree of obesity and not to testosterone, DHEA, or DHEA-S concentrations. We found that obese or centrally obese men had lower testosterone concentrations and greater prostate volumes. In other words, obese men usually have an estrogen/testosterone imbalance, with a higher estrogen and lower testosterone level (39,40), which may influence prostate volume. However, testosterone level was not correlated with prostate volume and had no effect on prostatic hyperplasia in our study.
Prostatic hyperplasia patients often have obesity-related metabolic diseases, such as type 2 diabetes, hypertension, and CVD, and vice versa (15,41). Prostate volume increases with fasting glucose level and hyperinsulinemia-related metabolic diseases such as obesity, diabetes, hypertension, and dyslipidemia. Perhaps hyperinsulinemia affects prostate growth directly and activates the sympathetic nervous system indirectly (16). We did not include overt obesity-related diseases, such as diabetes, impaired fasting glucose, hypertension, or dyslipidemia, but fasting glucose, blood pressure, and total cholesterol levels of the study subjects were included in the analysis, so we evaluated the direct effect of obesity on prostate volume.
No definite criteria for clinically diagnosed prostatic hyperplasia have been established, although prostate volume >20 mL, international prostate gland symptom score >7, and peak urinary flow rate <15 mL/s are commonly used (23). We studied only the relationship between obesity and prostate volume based on transrectal ultrasonography and not the relationships between obesity and clinical symptoms of urinary dysfunction with prostatic hyperplasia. This could be a limitation of our study. Small sample size, especially of centrally obese men, was another limitation.
In conclusion, BMI and waist circumference were positively correlated with prostate volume when the effects of overt obesity-related metabolic disease were excluded. Prostate volume was significantly greater in men with BMI ≥25 kg/m2 than in those with BMI <23 kg/m2 and in men with waist circumference >90 cm vs. ≤90 cm. Waist circumference >90 cm was an independent risk factor for prostatic hyperplasia. We suggest that central obesity is an important risk factor for prostatic hyperplasia.
This work was supported by Pusan Kyeungnam Society for the Study of Obesity Grant 2004-01.