Hyperplastic Obesity Definition Essays

Obesity is a substantial public health crisis in the United States and in the rest of the industrialized world. The prevalence is increasing rapidly in numerous industrialized nations worldwide. This growing rate represents a pandemic that needs urgent attention if obesity’s potential toll on morbidity, mortality, and economics is to be avoided. Research into the complex physiology of obesity may aid in avoiding this impact. (See Pathophysiology and Etiology.)

The annual cost of managing obesity in the United States alone amounts to approximately $190.2 billion per year, or 20.6% of national health expenditures, according to a study. [11] Compared with a nonobese person, an obese person incurs $2741 more in medical costs (in 2005 dollars) annually. In addition, the annual cost of lost productivity due to obesity is approximately $73.1 billion, [12] and almost $121 billion is spent annually on weight-loss products and services. [13] (See Treatment and Medication.)

In a 2016 position statement, the American Association of Clinical Endocrinologists (AACE) and the American College of Endocrinology (ACE) proposed a new name for obesity, adiposity-based chronic disease (ABCD). The AACE/ACE did not introduce the name as an actual replacement for the term obesity but instead as a means of helping the medical community focus on the pathophysiologic impact of excess weight. [14]

For information on pediatric obesity, see Obesity in Children.

Measurements of obesity

Obesity represents a state of excess storage of body fat. Although similar, the term overweight is puristically defined as an excess of body weight for height. Normal, healthy men have a body fat percentage of 15-20%, while normal, healthy women have a percentage of approximately 25-30%. [15] However, because differences in weight among individuals are only partly the result of variations in body fat, body weight is a limited, although easily obtained, index of obesity.

The body mass index (BMI), also known as the Quetelet index, is used far more commonly than body fat percentage to define obesity. In general, BMI correlates closely with the degree of body fat in most settings; however, this correlation is weaker at low BMIs.

An individual’s BMI is calculated as weight/height2, with weight being in kilograms and height being in meters (otherwise, the equation is weight in pounds ´ 0.703/height in inches2). Online BMI calculators are available.

A person’s body fat percentage can be indirectly estimated by using the Deurenberg equation, as follows:

body fat percentage = 1.2(BMI) + 0.23(age) - 10.8(sex) - 5.4

with age being in years and sex being designated as 1 for males and 0 for females. This equation has a standard error of 4% and accounts for approximately 80% of the variation in body fat.

Although the BMI typically correlates closely with percentage body fat in a curvilinear fashion, some important caveats apply to its interpretation. In mesomorphic (muscular) persons, BMIs that usually indicate overweight or mild obesity may be spurious, whereas in some persons with sarcopenia (eg, elderly individuals and persons of Asian descent, particularly from South Asia), a typically normal BMI may conceal underlying excess adiposity characterized by an increased percentage of fat mass and reduced muscle mass.

In view of these limitations, some authorities advocate a definition of obesity based on percentage of body fat. For men, a percentage of body fat greater than 25% defines obesity, with 21-25% being borderline. For women, over 33% defines obesity, with 31-33% being borderline.

Other indices used to estimate the degree and distribution of obesity include the 4 standard skin thicknesses (ie, subscapular, triceps, biceps, suprailiac) and various anthropometric measures, of which waist and hip circumferences are the most important. Skinfold measurements are the least accurate means by which to assess obesity.

Dual-energy radiographic absorptiometry (DXA) scanning is used primarily by researchers to accurately measure body composition, particularly fat mass and fat-free mass. It has the additional advantage of measuring regional fat distribution. However, DXA scans cannot be used to distinguish between subcutaneous and visceral abdominal fat deposits.

The current standard techniques for measuring visceral fat volume are abdominal computed tomography (CT) scanning (at L4-L5) and magnetic resonance imaging (MRI) techniques. A simpler technique, using bioelectrical impedance, was recently introduced. [16] However, these methods are limited to clinical research.

Classification of obesity

Although several classifications and definitions for degrees of obesity are accepted, the most widely accepted classifications are those from the World Health Organization (WHO), based on BMI. The WHO designations include the following:

  • Grade 1 overweight (commonly and simply called overweight) - BMI of 25-29.9 kg/m 2

  • Grade 2 overweight (commonly called obesity) - BMI of 30-39.9 kg/m 2

  • Grade 3 overweight (commonly called severe or morbid obesity) - BMI greater than or equal to 40 kg/m 2

The cut-off for each grade varies according to an individual’s ethnic background. For example, a BMI of 23 kg/m2 or higher may define grade 1 overweight and 27.5 kg/m2 or higher may define grade 2 overweight (obesity) in many Asian populations, in which the risk was shown to be high and extremely high for grade 1 and 2 overweight at these levels, respectively. Other BMI cutoffs identified as potential public health action points in these populations are 32.5 and 37.5 kg/m2. [17]

The surgical literature often uses a different classification to recognize particularly severe obesity. The categories are as follows:

  • Severe obesity - BMI greater than 40 kg/m 2

  • Morbid obesity - BMI of 40-50 kg/m 2

  • Super obese - BMI greater than 50 kg/m 2

In children, a BMI above the 85th percentile (for age-matched and sex-matched control subjects) is commonly used to define overweight, and a BMI above the 95th percentile is commonly used to define obesity.

Comorbidities associated with obesity

Obesity is associated with a host of potential comorbidities that significantly increase the risk of morbidity and mortality in obese individuals. Although no cause-and-effect relationship has been clearly demonstrated for all of these comorbidities, amelioration of these conditions after substantial weight loss suggests that obesity probably plays an important role in their development. (See Presentation.)

Apart from total body fat mass, the following aspects of obesity have been associated with comorbidity:

  • Fat distribution

  • Waist circumference

  • Age of obesity onset

  • Intra-abdominal pressure

Fat distribution

Accumulating data suggest that regional fat distribution substantially affects the incidence of comorbidities associated with obesity. [3] Android obesity, in which adiposity is predominantly abdominal (including visceral and, to a lesser extent, subcutaneous), is strongly correlated with worsened metabolic and clinical consequences of obesity.

Waist circumference

The thresholds used in the National Cholesterol Education Program Adult Treatment Panel III definition of metabolic syndrome [18] state that significantly increased cardiovascular risk (metabolic central obesity) exists in men with waist circumferences of greater than 94 cm (37 in) and in women with waist circumferences of greater than 80 cm (31.5 in), as well as waist-to-hip ratios of greater than 0.95 in men and of greater than 0.8 in women. Circumferences of 102 cm (40 in) in men and 88 cm (35 in) in women indicate a markedly increased risk requiring urgent therapeutic intervention.

These thresholds are much lower in Asian populations. After analyzing survey results of Chinese, Malay, and Asian-Indian cohorts, Tan and colleagues concluded that a waist circumference of greater than 90 cm in men and of more than 80 cm in women were more appropriate criteria for metabolic central obesity in these ethnic groups. [19]

Age of obesity onset

An elevated BMI during adolescence (starting within the range currently considered normal) is strongly associated with the risk of developing obesity-related disorders later in life, independent of adult BMI. [20] Increases in BMI during early adulthood (age 25-40 y) are associated with a worse profile of biomarkers related to obesity than are BMI increases during later adulthood. [21] This is consistent with most emerging data regarding timing of changes in BMI and later health consequences.

Intra-abdominal pressure

Apart from the metabolic complications associated with obesity, a paradigm of increased intra-abdominal pressure has been recognized. This pressure effect is most apparent in the setting of marked obesity (BMI ≥ 50 kg/m2) and is espoused by bariatric surgeons. [22]

Findings from bariatric surgery and animal models suggest that this pressure elevation may play a role (potentially a major one) in the pathogenesis of comorbidities of obesity, such as the following [23] :

  • Pseudotumor cerebri

  • Lower-limb circulatory stasis

  • Ulcers

  • Dermatitis

  • Thrombophlebitis

  • Reflux esophagitis

  • Abdominal hernias

  • Possibly, hypertension and nephrotic syndrome


A study by Losina et al found that obesity with knee osteoarthritis resulted in the loss of a substantial number of quality-adjusted life years. The association was most notable among black and Hispanic women. [27]

Focal glomerulosclerosis

Some reports, including those by Adelman and colleagues and by Kasiske and Jennette, suggest an association between severe obesity and focal glomerulosclerosis. [28, 29, 30] This complication, in particular, improves substantially or resolves soon after bariatric surgery, well before clinically significant weight loss is achieved.

Pickwickian syndrome

The so-called Pickwickian syndrome is a combined syndrome of obesity-related hypoventilation [176] and sleep apnea. It is named after Charles Dickens’s novel The Pickwick Papers, which contains an obese character who falls asleep constantly during the day.

The hypoventilation in Pickwickian syndrome results from severe mechanical respiratory limitations to chest excursion, caused by severe obesity. The sleep apnea may be from obstructive and/or central mechanisms. Obstructive sleep apnea is common among men with collar size greater than 17 in (43 cm) and women with collar size greater than 16 in (41 cm).

Increased and decreased sleep duration

Sleep duration of less than 5 hours or more than 8 hours was associated with increased visceral and subcutaneous body fat, in a study of young African Americans and Hispanic Americans. [31] This association relates mostly to decreased leptin hormone and increased ghrelin hormone levels. [32]

Additional comorbidities

Overweight and obese individuals are at increased risk for the following health conditions:

  • Metabolic syndrome

  • Type 2 diabetes

  • Hypertension

  • Dyslipidemia

  • Coronary heart disease

  • Osteoarthritis

  • Stroke

  • Depression

  • Non-alcoholic fatty liver disease (NAFLD)

  • Infertility (women) and erectile dysfunction (men)

  • Risk of stillbirth [24, 25]

  • Gall bladder disease

  • Obstructive sleep apnea

  • Gastroesophageal reflux disease (GERD)

  • Some cancers (eg, endometrial, breast, and colon) [5, 6, 7]

  • Asthma

A study by Abdullah et al indicated that not only the severity of a patient’s obesity but its duration as well is associated with the individual’s risk of developing type 2 diabetes mellitus. Based on a more than four decade follow-up of 5132 participants in the Framingham Offspring Study, the investigators found a significant rise in type 2 diabetes risk as obese-years increased. [26]

A Korean study, by Evangelista et al, found a higher prevalence of general and abdominal obesity in persons with some stages of chronic kidney disease (CKD) than in those without CKD. The greatest prevalence of these forms of obesity was found in patients with stage 2 CKD. The investigators also reported that general and abdominal obesity were not associated with stage 4 or 5 CKD. [177]


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

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.


Subjects Characteristics

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 ± 9.251.5 ± 7.652.2 ± 7.452.0 ± 8.1
SBP (mm Hg)115.8 ± 12.6115.3 ± 11.5120.1 ± 11.2117.4 ± 11.9
DBP (mm Hg)74.4 ± 6.972.1 ± 6.7*75.8 ± 6.8*74.4 ± 6.9
Fasting glucose (mg/dL)85.4 ± 9.687.4 ± 9.784.4 ± 8.785.5 ± 9.3
Total cholesterol (mg/dL)171.7 ± 18.1180.2 ± 18.2174.0 ± 16.4174.8 ± 17.7
Nutrition uptake    
 Total energy (kcal)1975.9 ± 478.2*2192.8 ± 391.52244.2 ± 409.3*2138.9 ± 443.4
 Protein (%)14.6 ± 1.6*14.9 ± 1.615.5 ± 1.4*15.0 ± 1.5
 Fat (%)19.2 ± 6.718.3 ± 4.120.8 ± 4.519.6 ± 5.3
 Carbohydrate (%)66.2 ± 7.566.8 ± 5.563.6 ± 5.765.3 ± 6.4
Alcohol intake    
 ≥30 g/d19 (38.0)18 (47.3)25 (43.1)62 (42.5)
 <30 g/d31 (62.0)20 (52.7)33 (56.9)84 (57.5)
Smoking status    
 Current smoker22 (44.0)11 (28.9)25 (43.1)58 (39.7)
 Ex-smoker12 (24.0)12 (31.6)18 (31.1)42 (28.8)
 Nonsmoker16 (32.0)15 (39.5)15 (25.8)46 (31.5)
Regular exercise    
 Yes27 (54.0)15 (39.5)28 (48.3)70 (47.9)
 No23 (46.0)23 (60.5)30 (51.7)76 (52.1)
Age52.2 ± 8.251.0 ± 7.5
SBP (mm Hg)116.7 ± 12.3119.8 ± 10.1
DBP (mm Hg)74.0 ± 7.175.8 ± 6.2
Fasting glucose (mg/dL)85.6 ± 9.785.1 ± 7.5
Total cholesterol (mg/dL)175.9 ± 18.0171.0 ± 16.1
Nutrition uptake  
 Total energy (kcal)2098.3 ± 446.12295.8 ± 402.2
 Protein (%)14.9 ± 1.515.6 ± 1.5
 Fat (%)19.3 ± 5.520.7 ± 4.5
 Carbohydrate (%)65.7 ± 6.663.6 ± 5.8
Alcohol intake  
 ≥30 g/d41 (35.3)19 (63.3)
 <30 g/d75 (64.7)11 (36.7)
Smoking status  
 Current smoker45 (39.0)13 (43.3)
 Ex-smoker32 (27.6)10 (33.3)
 Nonsmoker39 (33.4)7 (23.4)
Regular exercise  
 Yes55 (47.4)13 (43.3)
 No61 (52.6)17 (56.7)

Prostate Volume

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 ± 7.221.8 ± 5.6*20.8 ± 6.0
Testosterone (nM)22.3 ± 7.4†19.8 ± 4.017.1 ± 5.0†19.6 ± 6.1
DHEA-S (μg/dL)180.8 ± 99.2194.1 ± 97.4220.7 ± 120.3200.1 ± 108.4
Prostate volume (mL)20.0 ± 6.023.7 ± 5.3*20.8 ± 6.0
Testosterone (nM)20.1 ± 6.417.5 ± 4.5†19.6 ± 6.1
DHEA-S (μg/dL)192.7 ± 104.8228.9 ± 118.8200.1 ± 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).

BMI (kg/m2)   
 Normal (18.5 to 22.9) 1 
 Overweight (23 to 24.9)0.1861, 930.73 to 5.09
 Obese (≥25)0.3821, 620.55 to 4.80
Waist circumference   
 ≤90 cm 1 
 >90 cm0.0373, 371.08 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)0.2221.850.69 to 4.95
 Obese BMI and waist circumference ≤90 cm (N = 29)0.5261.430.47 to 4.36
 Obese BMI and waist circumference >90 cm (N = 30)0.0084.881.52 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.


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