Cardiorespiratory fitness and sedentary activities are associated with adiposity in adolescents

Objective: To determine whether physical activity, sedentary activities, and/or cardiorespiratory fitness are related to waist circumference in adolescents, as previously reported in adults. Research Methods and Procedures: The study subjects were a representative sample of Spanish adolescents (N = 2859; 1357 boys, 1502 girls; age, 13 to 18.5 years), all of whom were involved in the AVENA (Food and Assessment of the Nutritional Status of Adolescents) study. BMI, waist circumference, pubertal maturation status, and cardiorespiratory fitness were measured in all. Leisure‐time physical activity, sedentary activities, active commuting to school, and socioeconomic status were assessed by self‐reported questionnaires. Results: No relationship was found between leisure‐time physical activity and BMI or waist circumference. In contrast, and in both boys and girls and after adjustment for confounding variables, cardiorespiratory fitness was found to be inversely associated with waist circumference and BMI, independent of sedentary activities or physical activity (p ≤ 0.001). The maximum oxygen consumption explained 13% of the variance in waist circumference in boys and 16% in girls. Sedentary activities were independently and directly related to waist circumference in both boys and girls (p ≤ 0.05) and to BMI in boys (p ≤ 0.05). Sedentary activities explained 10% of the variance in waist circumference in boys and 18% in girls. The BMI‐adjusted waist circumference was inversely correlated with cardiorespiratory fitness in overweight‐obese boys (p ≤ 0.05) and showed a trend toward significance in girls (p ≤ 0.1). Discussion: Both moderate to high levels of cardiorespiratory fitness and sedentary activities, but not physical activity, are associated with lower abdominal adiposity, as measured by waist circumference.     

Ethnic Differences in Visceral Adipose Tissue and Type 2 Diabetes: Filipino,African‐American,and White Women

Objective: To compare ethnic differences in visceral adipose tissue (VAT), assessed by computed tomography, and type 2 diabetes risk among 55‐ to 80‐year‐old Filipino, African‐American, and white women without known cardiovascular disease. Research Methods and Procedures: Subjects were participants in the Rancho Bernardo Study (n = 196), the Filipino Women's Health Study (n = 181), and the Health Assessment Study of African‐American Women (n = 193). Glucose and anthropometric measurements were assessed between 1995 and 2002. Results: African‐American women had significantly higher age‐adjusted BMI (29.7 kg/m²) and waist girth (88.1 cm) compared with Filipino (BMI, 25.5 kg/m²; waist girth, 81.9 cm) or white (BMI: 26.0 kg/m²; waist girth: 80.7 cm) women. However, VAT was significantly higher among Filipino (69.1 cm³) compared with white (62.3 cm³; p = 0.037) or African‐American (57.5 cm³, p < 0.001) women. VAT correlated better with BMI (r = 0.69) and waist (r = 0.77) in whites, compared with Filipino (r = 0.42; r = 0.59) or African‐American (r = 0.50; r = 0.56) women. Age‐adjusted type 2 diabetes prevalence was significantly higher in Filipinas (32.1%) than in white (5.8%) or African‐American (12.1%) women. Filipinas had higher type 2 diabetes risk compared with African Americans [adjusted odds ratio, 2.30; 95% confidence interval (CI), 1.09 to 4.86] or whites (adjusted odds ratio, 7.51; 95% CI, 2.51 to 22.5) after adjusting for age, VAT, exercise, education, and alcohol intake. Discussion: VAT was highest among Filipinas despite similar BMI and waist circumference as whites. BMI and waist circumference were weaker estimates of VAT in Filipino and African‐American women than in whites. Type 2 diabetes prevalence was highest among Filipino women at every level of VAT, but VAT did not explain their elevated type 2 diabetes risk.     

Effects of Obesity and Body Fat Distribution on Lipids and Lipoproteins in Nondiabetic American Indians: The Strong Heart Study

Objectives: To examine the relationship between obesity and lipoprotein profiles and compare the effects of total obesity and central adiposity on lipids/lipoproteins in American Indians. Research Methods and Procedures: Participants were 773 nondiabetic American Indian women and 739 men aged 45 to 74 years participating in the Strong Heart Study. Total obesity was estimated using body mass index (BMI). Central obesity was measured as waist circumference. Lipoprotein measures included triglycerides, high‐density lipoprotei in (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, apolipoprotein AI (apoAI), and apolipoprotein B (apoB). Partial and canonical correlation analyses were used to examine the associations between obesity and lipids/lipoproteins. Results: Women were more obese than men in Arizona (median BMI 32.1 vs. 29.2 kg/m²) and South Dakota and North Dakota (28.3 vs. 28.0 kg/m²), but there was no sex difference in waist circumference. Men had higher apoB and lower apoAI levels than did women. In women, when adjusted for center, gender, and age, BMI was significantly related to HDL cholesterol (r = ?0.24, p < 0.001). There was a significant but weak relation with apoAI (r = ?0.14 p < 0.001). Waist circumference was positively related to triglycerides (r = 0.14 p < 0.001) and negatively related to HDL cholesterol (r = ?0.23, p < 0.001) and apoAI (r = ?0.13, p < 0.001). In men, BMI was positively correlated with triglycerides (r = 0.30, p < 0.001) and negatively correlated with HDL cholesterol (r = ?0.35, p < 0.001) and apoAI (r = ?0.23, p < 0.001). Triglycerides increased with waist circumference (r = 0.30, p < 0.001) and HDL cholesterol decreased with waist circumference (r = ?0.36 p < 0.001). In both women and men there was an inverted U‐shaped relationship between obesity and waist with LDL cholesterol and apoB. In canonical correlation analysis, waist circumference received a greater weight (0.86) than did BMI (0.17) in women. However, the canonical weights were similar for waist (0.46) and BMI (0.56) in men. Only HDL cholesterol (?1.02) carried greater weight in women, whereas in men, triglycerides (0.50), and HDL cholesterol (?0.64) carried a large amount of weight. All the correlation coefficients between BMI, waist circumference, and the first canonical variable of lipids/lipoproteins or between the individual lipid/lipoprotein variables and the first canonical variable of obesity were smaller in women than in men. Triglycerides and HDL cholesterol showed clinically meaningful changes with BMI and waist circumference in men. All lipid/lipoprotein changes in women in relation to BMI and waist circumference were minimal. Discussion: The main lipoprotein abnormality related to obesity in American Indians was decreased HDL cholesterol, especially in men. Central adiposity was more associated with abnormal lipid/lipoprotein profiles than general obesity in women; both were equally important in men.     

Relationship of Neck Circumference to Cardiovascular Risk Factors

Objective: To determine a relationship between neck circumference (NC) and risk factors for coronary heart disease by evaluating the components of the metabolic syndrome. Research Methods and Procedures: The study group included 561 subjects (231 men and 330 women) who had no known major medical conditions and were not receiving any medication therapy. The subjects were those who attended a family health clinic for any reason between 1998 and December 2001. Main indicators studied included NC, waist circumference, waist‐to‐hip ratio, body mass index, blood pressure, and lipoprotein, glucose, and uric acid levels. Results: Pearson's correlation coefficients indicated a significant association between NC and body mass index (men, r = 0.71; women, r = 0.81; each, p < 0.0001), waist circumference (men, r = 0.75; women, r = 0.79; each, p < 0.0001), waist‐to‐hip ratio (men, r = 0.56; women, r = 0.63; each, p < 0.0001), total cholesterol (men, r = 0.50; women, r = 0.66; each, p < 0.0001), low‐density lipoprotein‐cholesterol (men, r = 0.42; women, r = 0.60; each, p < 0.0001), triglycerides (men, r = 0.48; women, r = 0.49; each, p < 0.0001), glucose (men, r = 0.21, p < 0.001; women, r = 0.44; p < 0.0001), uric acid (men, r = 0.50, p < 0.0001; women, r = 0.60, p < 0.001), and systolic (men, r = 0.53; women, r = 0.69; each, p < 0.0001), and diastolic (men, r = 0.55; women, r = 0.65; each, p < 0.0001) blood pressure. Discussion: Higher NC is correlated positively with the factors of the metabolic syndrome; therefore, it is likely to increase the risk of coronary heart disease.     

Accelerometry‐Measured Activity or Sedentary Time and Overweight in Rural Boys and Girls

Objective: The aim of this study was to examine the association between overweight and physical activity or sedentary time measured by accelerometry in rural boys and girls 7 to 19 years old. Research Methods and Procedures: A cross‐sectional study was conducted involving 130 girls and 99 boys in elementary, middle, and high school in rural Maryland. After weight, height, and body composition were measured, children wore an Actiwatch accelerometer for 6 days. Comparisons for activity counts were made between normal and overweight or at risk for overweight (at‐risk/overweight) participants (≥85th percentile of BMI). The associations between body composition and accelerometry‐defined activity levels (sedentary, light, moderate, and vigorous) were analyzed by age group for boys and girls. Results: Differences in total activity in counts per day or counts per minute were not observed between normal and at‐risk/overweight boys or girls in all age groups. No associations between measures of body composition and time spent in an activity level were seen in boys. Fat mass and percentage fat were positively correlated to time spent in sedentary activity (range r = 0.42 to 0.54, all p < 0.01) for girls. In contrast, fat mass and percentage fat were negatively related to time spent in light activity (range, r = ?0.40 to ?0.51, p < 0.05) for girls. Discussion: In girls, but not boys, greater body fat is associated with greater time spent being inactive, and lower levels of body fat are associated with more time spent in light activity. Physical activity interventions targeting inactive children in rural communities are warranted.     

Analysis of Obesity and Hyperinsulinemia in the Development of Metabolic Syndrome: San Antonio Heart Study

Objective: To use standardized cut‐offs of body mass index (BMI), waist circumference, waist‐to‐hip ratio, and fasting insulin levels to predict the development of metabolic disorders and metabolic syndrome. Research Methods and Procedures: We performed an 8‐year follow‐up study of 628 non‐Hispanic whites and 1340 Mexican Americans, ages 25 to 64 years, from the second cohort of the San Antonio Heart Study. We defined metabolic disorders as dyslipidemia (triglycerides ≥2.26 mM or high‐density lipoprotein <0.91 mM in men and <1.17 mM in women), hypertension (blood pressure ≥140/≥90 mm Hg, or receiving antihypertensive medications), and type 2 diabetes (fasting glucose ≥7.0 mM, 2‐hour test glucose ≥11.1 mM, or receiving anti‐diabetic medications). People with at least two metabolic disorders were defined as having metabolic syndrome. Results: High waist‐to‐hip ratio and fasting insulin levels were significant predictors of developing metabolic syndrome. High anthropometric indices remained significant predictors of metabolic syndrome after adjusting for fasting insulin. Waist circumference, BMI, and insulin had similar areas under the receiver operating characteristic curves (0.74 to 0.76). Further multivariate analyses combining these indices showed minimal increase in prediction. Of subjects who had a combination of high BMI (≥30 kg/m²) and high waist circumference (above “Action Level 2”), 32% developed metabolic syndrome, compared with 10% of subjects with both low BMI and low waist circumference. Discussion: These findings support the National Institutes of Health recommendations for reducing the risk of metabolic syndrome. Adjustment for baseline fasting insulin levels had only a small effect on the ability of anthropometric indices to predict the metabolic syndrome.     

High‐Sensitivity C‐Reactive Protein in Japanese Patients with Type 2 Diabetes

Objective: To assess the relationship between high‐sensitivity (HS) C‐reactive protein (CRP) and metabolic syndrome (MetS) or atherosclerosis and to assess effects of strict metabolic control on the degree of inflammation and MetS in patients with type 2 diabetes. Research Methods and Procedures: Four hundred thirteen patients with diabetes were enrolled in the cross‐sectional study. Of these 413 patients, 161 patients were further admitted for 2.4 ± 0.4 weeks (mean ± SD) to investigate the change in HS‐CRP or other parameters under strict metabolic control. Results: Log‐transformed HS‐CRP value (log HS‐CRP) was strongly correlated with BMI (r = 0.448, p < 0.01). Log HS‐CRP was also correlated with the presence of MetS or each component of MetS. Furthermore, a positive significant trend in HS‐CRP levels was shown with an increasing number of MetS components (p < 0.05). Log HS‐CRP showed a significant positive correlation with carotid artery intima‐media thickness (IMT) (r = 0.152, p < 0.01). In multiple step‐wise regression analysis, BMI, hemoglobin A_1c, right IMT, duration of diabetes, and triglyceride were selected as explanatory variables for log HS‐CRP (R² = 0.412). Under strict metabolic control, HS‐CRP was significantly (p < 0.01) lower, together with lower levels of other markers for MetS. The change in HS‐CRP was significantly correlated with the change in BMI (r = 0.161, p = 0.04). Discussion: In subjects with type 2 diabetes, HS‐CRP levels are related to MetS and subclinical atherosclerosis. Strict weight management and metabolic control were associated with a reduction in HS‐CRP levels, and changes in HS‐CRP were related to changes in weight, supporting the hypothesis that lifestyle modification reduces inflammation and the risk of CHD.     

Fasting Plasma Insulin Modulates Lipid Levels and Particle Sizes in 2‐ to 3‐Year‐Old Children

Objective: Obesity and hyperinsulinemia are associated with dyslipidemia in adults and older children, but little is known about these relationships in very young children. We examined the relation of fasting insulin to lipid levels and lipid particle size in young healthy children. Research Methods and Procedures: Analyses were performed on data from 491 healthy 2‐ and 3‐year old Hispanic children enrolled in a dietary study conducted in New York City, 1992–1995. Obesity measures included BMI, ponderal index, skinfold thickness, and waist circumference. Low‐density lipoprotein (LDL)‐ and high‐density lipoprotein (HDL)‐cholesterol particle size were measured by nuclear magnetic resonance. Results: Fasting insulin level was positively correlated with triglyceride levels (r = 0.24 for boys and r = 0.23 for girls; p < 0.001 for both) and inversely correlated with HDL‐cholesterol level in boys (r = ?0.20; p < 0.01). Higher fasting insulin level was also correlated with smaller mean HDL particle size in both boys (r = ?0.21; p < 0.001) and girls (r = ?0.14; p < 0.05) and smaller mean LDL particle size in boys (r = ?0.13; p < 0.05). The associations of fasting insulin level with triglyceride and HDL‐cholesterol levels and HDL and LDL particle size remained significant after multivariate regression adjustment for age, sex, and BMI or ponderal index. Discussion: Fasting insulin level is associated with relative dyslipidemia in healthy 2‐ and 3‐year‐old Hispanic children.     

Change in Vascular Adhesion Protein‐1 and Metabolic Phenotypes after Vertical Banded Gastroplasty for Morbid Obesity

Objective: The association between circulating vascular adhesion protein‐1 (VAP‐1) and metabolic phenotypes has been shown to be inconsistent. The current study explored whether the changes in serum VAP‐1 levels correlate with the changes in metabolic phenotypes after weight reduction surgery. Research Methods and Procedures: Clinical characteristics and serum VAP‐1 levels in 20 morbidly obese subjects (mean BMI 38.84 kg/m²) were measured before and after vertical banded gastroplasty. Results: Before surgery, serum VAP‐1 levels correlated positively with fasting plasma glucose (γ = 0.56, p = 0.01) and negatively with insulin levels (γ = ?0.51, p = 0.021). After surgery, the changes in serum VAP‐1 levels were negatively correlated with the changes in waist circumference (γ = ?0.57, p = 0.011), diastolic blood pressure (DBP) (γ = ?0.56, p = 0.015), and mean arterial pressure (γ = ?0.46, p = 0.055). In multivariate regression, serum VAP‐1 levels were negatively correlated with waist circumference (β = ?2.36, p = 0.014) and DBP (β = ?3.02, p = 0.017) after adjusting for age and gender. The change in DBP was negatively correlated with the change in VAP‐1 levels after adjusting for age, gender, and steady‐state plasma glucose. Discussion: The results suggest that VAP‐1 levels are correlated with fasting glucose and insulin levels in morbidly obese subjects. After surgery, the changes in VAP‐1 levels were associated with changes in visceral adiposity and DBP. Serum VAP‐1 might modulate DBP independently from the changes in insulin resistance in morbidly obese people.     

Plasma Leptin and Blood Pressure in Men: Graded Association Independent of Body Mass and Fat Pattern

Objective: The role of leptin in the association between body mass, central adiposity, and blood pressure (BP) is controversial. This study evaluated the relationship between leptin and BP in relation to body mass index (BMI) and fat distribution in a large sample of untreated male adults. Research Methods and Procedures: The study population was made up of 457 untreated male employees of the Olivetti factory in Naples. Plasma leptin, complete anthropometry, BP, and relevant biochemical variables were measured. Results: Log‐transformed plasma leptin levels were directly associated with BMI (r = 0.661, p < 0.001) and waist circumference (r = 0.630; p < 0.001). Leptin also correlated with systolic (r = 0.258) and diastolic (r = 0.277) BP (p < 0.001). The association between leptin and BP was maintained after accounting for age, BMI (or waist circumference), log‐insulin, and serum creatinine (p < 0.01); this association was stronger than that with BMI. Logistic regression analysis showed that an increased prevalence of hypertension (BP ≥ 140 and/or 90 mm Hg) was associated with high plasma leptin levels when controlling for age and waist circumference (odds ratio, 1.99; 95%CI, 1.06 to 3.72) or for age and BMI (odds ratio, 1.92; 95%CI, 1.02 to 3.61). Discussion: A graded positive relationship between plasma leptin levels and BP was observed in this sample of untreated male adults. This association was independent of age, BMI, abdominal adiposity, and fasting plasma insulin. Moreover, elevated plasma leptin concentrations were associated with greater probability of hypertension, again independently of potential confounders.     

An SNP in the Adiponectin Gene Is Associated with Decreased Serum Adiponectin Levels and Risk for Impaired Glucose Tolerance

Adiponectin is a plasma protein produced by the adipose tissue. Hypoadiponectinemia has been associated with insulin resistance and several components of the metabolic syndrome (MS): type 2 diabetes, obesity, and dyslipidemia. We investigated whether single nucleotide polymorphisms (SNPs) at positions 45 and 276 in the adiponectin gene were associated with features of the MS in 747 unrelated Spanish subjects. The G allele of SNP45 and the G/G genotype of SNP276 were associated with impaired glucose tolerance (p = 0.020 and 0.042, respectively). The G/G genotype for SNP276 was associated with lower serum adiponectin levels as compared with the G/T and T/T genotypes (G/G, 10.10 ± 0.24 μg/mL; G/T, 10.98 ± 0.32 μg/mL; T/T, 12.00 ± 0.92 μg/mL; p = 0.015) even after adjustment for sex, age, BMI, waist‐to‐hip ratio, homeostasis model assessment index, and the degree of glucose tolerance (p = 0.040). We found a significant negative association of circulating adiponectin levels with waist‐to‐hip ratio (r = ?0.42, p < 0.001), sagittal abdominal diameter (r = ?0.24, p < 0.001), triglycerides (r = ?0.32, p < 0.001), homeostasis model assessment index (r = ?0.14, p = 0.001), and uric acid (r = ?0.36, p < 0.001) and positive association with high‐density lipoprotein‐cholesterol (r = 0.41, p < 0.001). Our findings indicate that serum adiponectin levels are associated with several components of the MS. The SNP276 of the adiponectin gene may affect impaired glucose tolerance and hypoadiponectinemia.     

Skinfolds and coronary heart disease risk factors are more strongly associated with BMI than with the body adiposity index

Objective:

A recent, cross‐sectional analysis of adults found that the hip circumference divided by height^1.5 minus 18 (the body adiposity index, BAI) was strongly correlated (r = 0.79) with percent body fat determined by dual energy X‐ray absorptiometry. The BAI was proposed as a more accurate index of body fatness than BMI. We examined whether BAI was more strongly related, than was BMI and waist circumference, to skinfold thicknesses and levels of various risk factors for coronary heart disease.

Design and Methods:

Cross‐sectional analyses of adults (n = 14,263 for skinfold thickness; n=6291 for fasting lipid levels) in the National Health and Nutrition Examination Survey (NHANES) III, 1988‐1994.

Results:

As compared with BMI and waist circumference, we found that BAI was less strongly associated with the skinfold sum and with risk factor levels. For example, correlations with the skinfold sum were r = 0.79 (BMI) vs. r = 0.70 (BAI) among men, and r = 0.86 (BMI) vs. r = 0.79 (BAI) among women; p < 0.001 for the difference between each pair of correlations. An overall index of the 7 risk factors was also more strongly associated with BMI and waist circumference than BAI in analyses stratified by sex, race‐ethnicity and age. Multivariable analyses indicated that if BMI was known, BAI provided little additional information on risk factor levels.

Conclusions:

Based on the observed associations with risk factor levels and skinfold thicknesses, we conclude that BAI is unlikely to be a better index of adiposity than BMI.     

Cortisol,obesity, and the metabolic syndrome: A cross‐sectional study of obese subjects and review of the literature

Objective:

Circulating cortisol and psychosocial stress may contribute to the pathogenesis of obesity and metabolic syndrome (MS). To evaluate these relationships, a cross‐sectional study of 369 overweight and obese subjects and 60 healthy volunteers was performed and reviewed the previous literature.

Design and Methods:

Overweight and obese subjects had at least two other features of Cushing's syndrome. They underwent measurements representing cortisol dynamics (24 h urine cortisol excretion (UFC), bedtime salivary cortisol, 1 mg dexamethasone suppression test) and metabolic parameters (BMI, blood pressure (BP); fasting serum triglycerides, HDL, insulin, and glucose). Subjects also completed the Perceived Stress Scale (PSS). UFC, salivary cortisol, and weight from 60 healthy volunteers were analyzed.

Results:

No subject had Cushing's syndrome. UFC and dexamethasone responses were not associated with BMI or weight. However, salivary cortisol showed a trend to increase as BMI increased (P < 0.0001), and correlated with waist circumference (WC) in men (r_s = 0.28, P = 0.02) and systolic BP in women (r_s = 0.24, P = 0.0008). Post‐dexamethasone cortisol levels were weak to moderately correlated with fasting insulin (r_s = ?0.31, P = 0.01) and HOMA‐IR (r_s = ?0.31, P = 0.01) in men and systolic (r_s = 0.18, P = 0.02) and diastolic BP (r_s = 0.20, P = 0.009) in women. PSS results were higher in obese subjects than controls, but were not associated with cortisol or metabolic parameters. As expected, WC correlated with fasting insulin, HOMA‐IR, and systolic BP (adjusted for BMI and gender; P < 0.01). Literature showed inconsistent relationships between cortisol and metabolic parameters.

Conclusion:

Taken together, these data do not support a strong relationship between systemic cortisol or stress and obesity or MS.

     

Sedentary behavior, recreational physical activity, and 7-year weight gain among postmenopausal U.S. women

Objective: To assess the relationship among recreational physical activity (PA), non‐occupational sedentary behavior, and 7‐year weight gain among postmenopausal U.S. women 40 to 69 years old. Research Methods and Procedures: In 1992 and 1999, 18,583 healthy female participants from the Cancer Prevention Study II Nutrition Cohort completed questionnaires on anthropometric characteristics and lifestyle factors. The associations between recreational PA [in metabolic equivalent (MET) hours per week] and non‐occupational sedentary behavior (in hours per day) at baseline and risk for 7‐year weight gain (5 to 9 or ≥10 vs. ±4 pounds) were assessed using multivariate logistic regression analysis. Results: Neither PA nor sedentary behavior was associated with a 5‐ to 9‐pound weight gain. Among women who were not overweight at baseline (BMI <25.0), the odds of ≥10‐pound weight gain were 12% lower (odds ratio, 0.88; 95% confidence interval, 0.77 to 0.99) for those in the highest category of recreational PA (≥18 MET h/wk) compared with >0 to <4 MET h/wk; odds were 47% higher (odds ratio, 1.47; 95% confidence interval, 1.21 to 1.79) for non‐overweight women who reported ≥6 h/d of non‐occupational sedentary behavior compared with <3 h/d. Neither PA nor sedentary behavior were associated with risk of ≥10‐pound weight gain weight among women who were overweight at baseline (BMI ≥25.0). Discussion: Both recreational PA and non‐occupational sedentary behavior independently predicted risk of ≥10‐pound weight gain among postmenopausal women who were not overweight at baseline. Public health messages to prevent weight gain among normal‐weight postmenopausal women may need to focus on decreasing time spent in sedentary behaviors and increasing the amount of time spent on PA.     

Central obesity as a risk factor for prostatic hyperplasia

Objective: Obesity‐related metabolic diseases may influence prostatic hyperplasia. This study examined the impact of obesity on prostate volume in men without overt obesity‐related metabolic diseases. Research Methods and Procedures: We recruited 146 men over the age of 40 years who did not have overt obesity‐related diseases, such as diabetes, impaired fasting glucose, hypertension, or dyslipidemia. Transrectal ultrasonography was performed on all subjects. The subjects were divided into three groups according to their BMI: normal (18.5 to 22.9 kg/m²), overweight (23 to 24.9 kg/m²), and obese (≥25 kg/m²), and two groups according to their waist circumference: normal waist (≤90 cm) and central obesity (>90 cm). The classification of the subgroups was based on the Asia‐Pacific criteria of obesity. We compared the prostate volume among subgroups and assessed factors related to prostatic hyperplasia. Results: Mean 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, and was 20.0 ± 5.9 and 23.7 ± 5.3 mL in the normal waist and central obesity group, respectively. Prostate volume was significantly greater in the obese group than in the normal group (P = 0.03) and in the central obesity group compared with the normal waist group (P = 0.002). Prostate volume was positively correlated with BMI and waist circumference after adjustment for age. After adjusting for confounding factors, central obesity was an independent factor affecting prostatic hyperplasia, which was defined as a prostate volume >20 mL (odds ratio = 3.37, p = 0.037). 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 (odds ratio = 4.88, p = 0.008). However, those with high BMI (≥25 kg/m²) and normal waist circumference were not at significantly increased risk. Discussion: Prostate volume was greater in the obese and central obesity groups than in the normal group after patients with overt obesity‐related metabolic diseases were excluded. Although both BMI and waist circumference were positively correlated with prostate volume, central obesity was the only independent factor affecting prostate hyperplasia. We suggest that central obesity is an important risk factor for prostatic hyperplasia.     

Obesity‐related Comorbidities in Obese African Americans in an Outpatient Weight Loss Program

Objective: To identify, among obese African‐American enrollees in an outpatient weight loss program, differences between those with and without obesity‐related comorbidities (ORCMs). Research Methods and Procedures: Data were from 237 obese African Americans (BMI, 30 to 50 kg/m²; 90% women) who enrolled in a 10‐week lifestyle weight loss program. Analyses compared subgroups defined by ORCM status (from medical history) on baseline characteristics, program attendance, and postprogram weight change. Results: Most participants (76%) had one or more ORCMs. Those with versus without ORCMs, respectively, were older (mean age, 45.6 vs. 37.1 years; p < 0.001), were less educated (59.2% vs. 76.6% with >12 years; p = 0.031), were more likely to perceive a physical limitation affecting activity (22.2% vs. 1.8%; p < 0.001), and had higher waist circumference (mean, 113.7 vs. 106.9 cm; p < 0.001) but not BMI (38.3 vs. 37.0 kg/m²; p = 0.095). Logistic regression analyses confirmed the independence of these associations. Having ORCMs was not associated with class attendance or return for data collection after the 10‐week program. Postprogram weight change (n = 134) was unrelated to ORCMs, but better weight loss was seen among those without perceived physical limitations (1.9 vs. 0.4 kg in those without versus with limitations; p = 0.069). Conclusion: Data from this clinical sample of obese African Americans suggest that waist circumference is relevant to ORCM status at BMI levels up to 50 kg/m². Clear indications for tailoring of treatment based on ORCM status were not identified, although the possible influence of ORCM‐related activity limitations warrants further study.     

High‐density Lipoprotein Apolipoprotein A‐I Kinetics in Obesity

Objective: Low plasma concentrations of high‐density lipoprotein (HDL)‐cholesterol and apolipoprotein A‐I (apoA‐I) are independent predictors of coronary artery disease and are often associated with obesity and the metabolic syndrome. However, the underlying kinetic determinants of HDL metabolism are not well understood. Research Methods and Procedures: We pooled data from 13 stable isotope studies to investigate the kinetic determinants of apoA‐I concentrations in lean and overweight—obese individuals. We also examined the associations of HDL kinetics with age, sex, BMI, fasting plasma glucose, fasting insulin, Homeostasis Model Assessment score, and concentrations of apoA‐I, triglycerides, HDL‐cholesterol and low‐density lipoprotein‐cholesterol. Results: Compared with lean individuals, overweight—obese individuals had significantly higher HDL apoA‐I fractional catabolic rate (0.21 ± 0.01 vs. 0.33 ± 0.01 pools/d; p < 0.001) and production rate (PR; 11.3 ± 4.4 vs. 15.8 ± 2.77 mg/kg per day; p = 0.001). In the lean group, HDL apoA‐I PR was significantly associated with apoA‐I concentration (r = 0.455, p = 0.004), whereas in the overweight—obese group, both HDL apoA‐I fractional catabolic rate (r = ?0.396, p = 0.050) and HDL apoA‐I PR (r = 0.399, p = 0.048) were significantly associated with apoA‐I concentration. After adjustment for fasting insulin or Homeostasis Model Assessment score, HDL apoA‐I PR was an independent predictor of apoA‐I concentration. Discussion: In overweight—obese subjects, hypercatabolism of apoA‐I is paralleled by an increased production of apoA‐I, with HDL apoA‐I PR being the stronger determinant of apoA‐I concentration. This could have therapeutic implications for the management of dyslipidemia in individuals with low plasma HDL‐cholesterol.     

The Effect of Electronic Self‐Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial

Technology may improve self‐monitoring adherence and dietary changes in weight loss treatment. Our study aimed to investigate whether using a personal digital assistant (PDA) with dietary and exercise software, with and without a feedback message, compared to using a paper diary/record (PR), results in greater weight loss and improved self‐monitoring adherence. Healthy adults (N = 210) with a mean BMI of 34.01 kg/m² were randomized to one of three self‐monitoring approaches: PR (n = 72), PDA with self‐monitoring software (n = 68), or PDA with self‐monitoring software and daily feedback messages (PDA+FB, n = 70). All participants received standard behavioral treatment. Self‐monitoring adherence and change in body weight, waist circumference, and diet were assessed at 6 months; retention was 91%. All participants had a significant weight loss (P < 0.01) but weight loss did not differ among groups. A higher proportion of PDA+FB participants (63%) achieved ≥5% weight loss in comparison to the PR group (46%) (P < 0.05) and PDA group (49%) (P = 0.09). Median percent self‐monitoring adherence over the 6 months was higher in the PDA groups (PDA 80%; PDA+FB 90%) than in the PR group (55%) (P < 0.01). Waist circumference decreased more in the PDA groups than the PR group (P = 0.02). Similarly, the PDA groups reduced energy and saturated fat intake more than the PR group (P < 0.05). Self‐monitoring adherence was greater in the PDA groups with the greatest weight change observed in the PDA+FB group.     

Elevated serum monocyte chemoattractant protein-4 and chronic inflammation in overweight subjects

Objective: Chronic inflammation observed in obesity has been reported to be implicated in the development of atherosclerosis. We screened candidate chemokines that link chronic inflammation and obesity. Research Methods and Procedures: Japanese overweight (n = 39, BMI 28.7 ± 0.65 kg/m²) and normal‐weight (n = 24, BMI 22.3 ± 0.45 kg/m²) subjects were enrolled. Using antibody‐based protein microarray, spot intensities of monocyte chemoattractant protein (MCP)‐4, eotaxin, and eotaxin‐2 correlated with anthropometric parameters. We further measured serum concentration of these chemokines and mRNA levels in adipose tissues obtained from volunteers. Results: Serum MCP‐4 levels showed positive correlation with BMI (r = 0.318, p = 0.014), waist (r = 0.316, p = 0.018), and waist‐to‐hip ratio (WHR) (r = 0.264, p = 0.049). Furthermore, MCP‐4 correlated with homeostasis model assessment of insulin resistance (r = 0.392, p = 0.002), high‐sensitivity C‐reactive protein (hsCRP) (r = 0.350, p = 0.006). In step‐wise multiple regression analyses, hsCRP independently correlated with MCP‐4 levels. The expression of MCP‐4 mRNA in visceral adipose tissue positively correlates with BMI. Serum eotaxin levels correlate with BMI (r = 0.262, p = 0.045) and WHR (r = 0.383, p = 0.003). Serum eotaxin‐2 levels correlated with BMI (r = 0.464, p < 0.001), waist (r = 0.333, p = 0.017), and WHR (r = 0.278, p = 0.048). However, eotaxin and eotaxin‐2 levels did not show significant correlation with hsCRP. Discussion: Serum levels of MCP‐4, eotaxin, and eotaxin‐2, which belong to CC chemokine family and share CC chemokine receptor 3, correlated with BMI. These chemokines, especially MCP‐4, may be critical molecules that link obesity and chronic inflammation.