Comparison of three bioelectrical impedance methods with DXA in overweight and obese men

Objective: To compare bioelectrical impedance analysis (BIA) of body composition using three different methods against DXA in overweight and obese men. Research Methods and Procedures: Forty‐three healthy overweight or obese men (ages 25 to 60 years; BMI, 28 to 43 kg/m²) underwent BIA assessment of body composition using the ImpediMed SFB7 (version 6; ImpediMed, Ltd., Eight Mile Plains, Queensland, Australia) in multifrequency mode (Imp‐MF) and DF50 single‐frequency mode (Imp‐SF) and the Tanita UltimateScale (Tanita Corp., Tokyo, Japan). Validity was assessed by comparison against DXA using linear regression and limits of agreement analysis. Results: All three BIA methods showed good relative agreement with DXA [Imp‐MF: fat mass (FM), r² = 0.81; fat‐free mass (FFM), r² = 0.81; percentage body fat (BF%), r² = 0.69; Imp‐SF: FM, r² = 0.65; FFM, r² = 0.76; BF%, r² = 0.40; Tanita: BF%, r² = 0.44; all p < 0.001]. Absolute agreement between DXA and Imp‐MF was poor, as indicated by a large bias and wide limits of agreement (bias, ±1.96 standard deviation; FM, ?6.6 ± 7.7 kg; FFM, 8.0 ± 7.1 kg; BF%, ?7.0 ± 6.6%). Imp‐SF and Tanita exhibited a smaller bias but wide limits of agreement (Imp‐SF: FM, ?1.1 ± 8.5 kg; FFM, 2.5 ± 7.9 kg; BF%, ?1.7 ± 7.3% Tanita: BF%, 1.2 ± 9.5%). Discussion: Compared with DXA, Imp‐MF produced large bias and wide limits of agreement, and its accuracy estimating body composition in overweight or obese men was poor. Imp‐SF and Tanita demonstrated little bias and may be useful for group comparisons, but their utility for assessment of body composition in individuals is limited.     

Differences in daily energy expenditure in lean and obese women: the role of posture allocation

Objective: A low resting metabolic rate (RMR) is considered a risk factor for weight gain and obesity; however, due to the greater fat‐free mass (FFM) found in obesity, detecting an impairment in RMR is difficult. The purposes of this study were to determine the RMR in lean and obese women controlling for FFM and investigate activity energy expenditure (AEE) and daily activity patterns in the two groups. Methods and Procedures: Twenty healthy, non‐smoking, pre‐menopausal women (10 lean and 10 obese) participated in this 14‐day observational study on free‐living energy balance. RMR was measured by indirect calorimetry; AEE and total energy expenditure (TEE) were calculated using doubly labeled water (DLW), and activity patterns were investigated using monitors. Body composition including FFM and fat mass (FM) was measured by dual energy X‐ray absorptiometry (DXA). Results: RMR was similar in the obese vs. lean women (1601 ± 109 vs. 1505 ± 109 kcal/day, respectively, P = 0.12, adjusting for FFM and FM). Obese women sat 2.5 h more each day (12.7 ± 3.2 h vs. 10.1 ± 2.0 h, P < 0.05), stood 2 h less (2.7 ± 1.0 h vs. 4.7 ± 2.2 h, P = 0.02) and spent half as much time in activity than lean women (2.6 ± 1.5 h vs. 5.4 ± 1.9 h, P = 0.002). Discussion: RMR was not lower in the obese women; however, they were more sedentary and expended less energy in activity than the lean women. If the obese women adopted the activity patterns of the lean women, including a modification of posture allocation, an additional 300 kcal could be expended every day.     

Sarcopenic/Obesity and Physical Capacity in Older Men and Women: Data From the Nutrition as a Determinant of Successful Aging (NuAge)—the Quebec Longitudinal Study

Sarcopenia and obesity have been independently associated with physical capacity impairments. However, few studies have investigated the impact of sarcopenic/obesity on physical capacity in older individuals using objective measures of physical capacity and body composition. This study included 904 older individuals aged between 68 and 82 years old. Body composition (fat mass (FM) and lean body mass (LBM) by dual‐energy X‐ray absorptiometry (DXA)), physical capacity (timed up and go, chair stands, walking speed at normal and fastest pace, and one leg stand), sum of reported chronic conditions and physical activity level were measured. A global physical capacity score was then calculated giving a maximal score of 20. Finally, four groups were created within genders based on sarcopenia and obesity ((i) nonsarcopenic/nonobese; (ii) sarcopenic/nonobese; (iii) nonsarcopenic/obese; (iv) sarcopenic/obese). The four groups were significantly different for the sit‐to‐stand test and the one leg stand test (P < 0.05) and only for the one leg stand test in women (P < 0.05). In both genders results for the global physical capacity score revealed that both obese groups (sarcopenic and nonsarcopenic) were similar (P = 0.14 in men and P = 0.19 in women) and had a lower global physical capacity score compared to nonsarcopenic/nonobese individuals (P < 0.05). In addition, sarcopenic women displayed a higher score than both obese nonsarcopenic and obese sarcopenic groups (P < 0.01). Sarcopenic/obese men and women do not display lower physical capacity compared to nonsarcopenic/obese individuals in this cohort of well‐functioning older men and women. Obesity per se appears to contribute more to lower physical capacity than sarcopenia.     

A Weight Reduction Program Preserves Fat‐Free Mass but Not Metabolic Rate in Obese Adolescents

Objective: To determine the effects of a multidisciplinary weight reduction program on body composition and energy expenditure (EE) in severely obese adolescents. Research Methods and Procedures: Twenty‐six severely obese adolescents, 12 to 16 years old [mean BMI: 33.9 kg/m²; 41.5% fat mass (FM)] followed a 9‐month weight reduction program including moderate energy restriction and progressive endurance and resistance training. Body composition was assessed by DXA, basal metabolic rate by indirect calorimetry, and EE by whole‐body indirect calorimetry with the same activity program over 36‐hour periods before starting and 9 months after the weight reduction period. Results: Adolescents gained (least‐square mean ± SE) 2.9 ± 0.2 cm in height, lost 16.9 ± 1.3 kg body weight (BW), 15.2 ± 0.9 kg FM, and 1.8 ± 0.5 kg fat‐free mass (FFM) (p < 0.001). Basal metabolic rate, sleeping, sedentary, and daily EE were 8% to 14% lower 9 months after starting (p < 0.001) and still 6% to 12% lower after adjustment for FFM (p < 0.05). Energy cost of walking decreased by 22% (p < 0.001). The reduction in heart rate during sleep and sedentary activities (?10 to ?13 beats/min), and walking (?20 to ?25 beats/min) (p < 0.001) resulted from both the decrease in BW and physical training. Discussion: A weight reduction program combining moderate energy restriction and physical training in severely obese adolescents resulted in great BW and FM losses and improvement of cardiovascular fitness but did not prevent the decline in EE even after adjustment for FFM.     

Validation of BIA in Obese Children and Adolescents and Re‐evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT²/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturer's equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = ?2.211 + 1.115 (HT²/Z), with r² of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.     

Relationship of Leptin Concentration to Gender,Menopause, Age,Diabetes, and Fat Mass in African Americans

This investigation was designed to determine the relationship of leptin concentration to gender, sex hormones, menopause, age, diabetes, and fat mass in African Americans. Participants included 101 African Americans, 38 men (mean age, 34. 2 ± 7. 4 years), 29 age-matched premenopausal women (mean age, 32. 6 ± 3. 7 years), and 36 postmenopausal women (mean age, 57. 8 ± 5. 9 years). The women were not taking exogenous sex hormones, and 12 subjects were diabetic. Percent body fat was calculated with the Siri formula, fat mass (FM) was calculated as weight x percent body fat, and Fat-free mass (FFM) was calculated as weight minus FM. Fasting plasma was assayed for leptin, estradiol, free testosterone, glucose, and insulin concentrations. The nondiabetics had an oral glucose tolerance test (OGTT). The diabetics compared with the non-diabetics had a higher central fat index (^P=0. 04) but otherwise were similar to nondiabetics in all parameters measured. Body mass index, percent body fat, and FM were greater in women than men (p<0. 001). Leptin concentrations in men, premenopausal, and postmenopausal women were: 7. 51 ± 8. 5, 33. 9 ± 17. 3, 31. 4 ± 22. 3 ng/mL. Leptin/FM x 100 in the three groups were: 28. 9 ± 16. 1, 98. 65 ± 44. 9, 77. 1 ± 44. 5 ng/mL/kg. The gender difference in leptin concentration and leptin/FM was significant (p<0. 001), but the difference between premenopausal and postmenopausal women was not. In each group, weight, percent body fat, and FM were highly correlated with leptin concentration. Multiple regression analyses with leptin concentration as the dependent variable and age, diabetic status, percent body fat, weight, FM, FFM, estradiol, and free testosterone concentrations as independent variables demonstrated that the determinants of leptin concentration in men was weight only (R=0. 83,p<0. 001), in premenopausal women it was FM only (R=0. 57,P<0. 001), and in postmenopausal women it was weight only (R=0. 67, p<0. 001). With diabetics excluded, the multiple regression analysis was repeated with fasting insulin concentration and the area under the insulin curve during the OGTT included as independent variables. The results for this multiple regression analyses were the same as the first. Therefore, leptin concentration in African Americans is determined by gender and fat mass. Menopause, age, and diabetes do not affect leptin concentration.     

Validation of DXA Body Composition Estimates in Obese Men and Women

The aim of this study was to determine the accuracy of dual‐energy X‐ray absorptiometry (DXA)‐derived percentage fat estimates in obese adults by using four‐compartment (4C) values as criterion measures. Differences between methods were also investigated in relation to the influence of fat‐free mass (FFM) hydration and various anthropometric measurements. Six women and eight men (age 22–54 years, BMI 28.7–39.9 kg/m², 4C percent body fat (%BF) 31.3–52.6%) had relative body fat (%BF) determined via DXA and a 4C method that incorporated measures of body density (BD), total body water (TBW), and bone mineral mass (BMM) via underwater weighing, deuterium dilution, and DXA, respectively. Anthropometric measurements were also undertaken: height, waist and gluteal girth, and anterior‐posterior (A‐P) chest depth. Values for both methods were significantly correlated (r² = 0.894) and no significant difference (P = 0.57) was detected between the means (DXA = 41.1%BF, 4C = 41.5%BF). The slope and intercept for the regression line were not significantly different (P > 0.05) from 1 and 0, respectively. Although both methods were significantly correlated, intraindividual differences between the methods were sizable (4C‐DXA, range = ?3.04 to 4.01%BF) and significantly correlated with tissue thickness (chest depth) or most surrogates of tissue thickness (body mass, BMI, waist girth) but not FFM hydration and gluteal girth. DXA provided cross‐sectional %BF data for obese adults without bias. However, individual data are associated with large prediction errors (±4.2%BF). This error appears to be associated with tissue thickness indicating that the DXA device used may not be able to accurately account for beam hardening in obese cohorts.     

PIXImus DXA with Different Software Needs Individual Calibration to Accurately Predict Fat Mass

Objective: To validate GE PIXImus2 DXA fat mass (FM) estimates by chemical analysis, to compare previously published correction equations with an equation from our machine, and to determine intermachine variation. Research Methods and Procedures: C57BL/6J (n = 16) and Aston (n = 14) mice (including ob/ob), Siberian hamsters (Phodopus sungorus) (n = 15), and bank voles (Clethrionomys glareolus) (n = 37) were DXA scanned postmortem, dried, then fat extracted using a Soxhlet apparatus. We compared extracted FM with DXA‐predicted FM corrected using an equation designed using wild‐type animals from split‐sample validation and multiple regression and two previously published equations. Sixteen animals were scanned on both a GE PIXImus2 DXA in France and a second machine in the United Kingdom. Results: DXA underestimated FM of obese C57BL/6J by 1.4 ± 0.19 grams but overestimated FM for wild‐type C57BL/6J (2.0 ± 0.11 grams), bank voles (1.1 ± 0.09 grams), and hamsters (1.1 ± 0.13 grams). DXA‐predicted FM corrected using our equation accurately predicted extracted FM (accuracy 0.02 grams), but the other equations did not (accuracy, ?1.3 and ?1.8 grams; paired Student's t test, p < 0.001). Two similar DXA instruments gave the same FM for obese mutant but not lean wild‐type animals. Discussion: DXA using the same software could use the same correction equation to accurately predict FM for obese mutant but not lean wild‐type animals. PIXImus machines purchased with new software need validating to accurately predict FM.     

Total and Regional Fat and Serum Cardiovascular Disease Risk Factors in Lean and Obese Children and Adolescents

Objective: This study was conducted to evaluate the association of total and central adiposity with serum cardiovascular disease (CVD) risk factors in lean and obese Portuguese children and adolescents. Research Methods and Procedures: A total of 87 girls (13.2 ± 1.6 years old, 29.9 ± 6.4% body fat [mean ± SD]) and 72 boys (13.2 ± 1.6 years old, 20.8 ± 9.9% body fat) volunteered for the study. Whole‐body composition and fat distribution, from DXA and anthropometry, and serum lipids, lipoproteins, and apolipoproteins were evaluated. Results: The sum of three trunk skinfolds (STS) was highly correlated with total trunk fat mass measured by DXA (p < 0.001). Body mass index, DXA‐measured percentage of body fat, trunk fat mass, STS, and the waist‐to‐height ratio were generally found to be associated with triacylglycerol, the ratio of total cholesterol (TC) to high density lipoprotein‐cholesterol (HDL‐C), low density lipoprotein‐cholesterol (LDL‐C), and apolipoprotein B levels, (significant age‐adjusted r between 0.16 and 0.27, p < 0.05). Body mass index, STS, and the waist circumference were also associated with HDL‐C (p < 0.05), whereas no body composition variable significantly correlated with TC or apolipoproteins A‐I. The STS was significantly correlated with HDL‐C (p < 0.01), TC/HDL‐C (p < 0.05), and apolipoproteins A‐I (p < 0.05) independently of whole‐body fatness. Obese subjects (n = 73) had higher TC, LDL‐C, TC/HDL‐C, and apolipoprotein B than did non‐obese subjects (n = 86), and significant associations between central adiposity and some lipid variables (triacylglycerol and HDL‐C) were found in obese children and adolescents that were not present in leaner individuals. Discussion: DXA‐ and anthropometry‐based whole‐body and central fat measures are associated with serum CVD risk factors in Portuguese boys and girls. Obese children and adolescents have a poorer lipid profile than do their leaner counterparts. Trunk skinfolds, which are easy to obtain even in large samples, predict CVD risk factors to the same extent as DXA‐based variables, in some cases, independently of total fatness.     

Effects of Obesity on Substrate Utilization during Exercise

Objective: The capacity for lipid and carbohydrate (CHO) oxidation during exercise is important for energy partitioning and storage. This study examined the effects of obesity on lipid and CHO oxidation during exercise. Research Methods and Procedures: Seven obese and seven lean [body mass index (BMI), 33 ± 0.8 and 23.7 ± 1.2 kg/m², respectively] sedentary, middle‐aged men matched for aerobic capacity performed 60 minutes of cycle exercise at similar relative (50% Vo _2max) and absolute exercise intensities. Results: Obese men derived a greater proportion of their energy from fatty‐acid oxidation than lean men (43 ± 5% 31 ± 2%; p = 0.02). Plasma fatty‐acid oxidation determined from recovery of infused [0.15 μmol/kg fat‐free mass (FFM) per minute] [1‐¹³C]‐palmitate in breath CO₂ was similar for obese and lean men (8.4 ± 1.1 and 29 ± 15 μmol/kg FFM per minute). Nonplasma fatty‐acid oxidation, presumably, from intramuscular sources, was 50% higher in obese men than in lean men (10.0 ± 0.6 versus 6.6 ± 0.8 μmol/kg FFM per minute; p < 0.05). Systemic glucose disposal was similar in lean and obese groups (33 ± 8 and 29 ± 15 μmol/kg FFM per minute). However, the estimated rate of glycogen‐oxidation was 50% lower in obese than in lean men (61 ± 12 versus 90 ± 6 μmol/kg FFM per minute; p < 0.05). Discussion: During moderate exercise, obese sedentary men have increased rates of fatty‐acid oxidation from nonplasma sources and reduced rates of CHO oxidation, particularly muscle glycogen, compared with lean sedentary men.     

Precision and Accuracy of Dual‐Energy X‐ray Absorptiometry for Determining in Vivo Body Composition of Mice

Objective: To evaluate the precision and accuracy of dual‐energy X‐ray absorptiometry (DXA) for the measurement of total‐bone mineral density (TBMD), total‐body bone mineral (TBBM), fat mass (FM), and bone‐free lean tissue mass (LTM) in mice. Research Methods and Procedures: Twenty‐five male C57BL/6J mice (6 to 11 weeks old; 19 to 29 g) were anesthetized and scanned three times (with repositioning between scans) using a peripheral densitometer (Lunar PIXImus). Gravimetric and chemical extraction techniques (Soxhlet) were used as the criterion method for the determination of body composition; ash content was determined by burning at 600°C for 8 hours. Results: The mean intraindividual coefficients of variation (CV) for the repeated DXA analyses were: TBMD, 0.84%; TBBM, 1.60%; FM, 2.20%; and LTM, 0.86%. Accuracy was determined by comparing the DXA‐derived data from the first scan with the chemical carcass analysis data. DXA accurately measured bone ash content (p = 0.942), underestimated LTM (0.59 ± 0.05g, p < 0.001), and overestimated FM (2.19 ± 0.06g, p < 0.001). Thus, DXA estimated 100% of bone ash content, 97% of carcass LTM, and 209% of carcass FM. DXA‐derived values were then used to predict chemical values of FM and LTM. Chemically extracted FM was best predicted by DXA FM and DXA LTM [FM = ?0.50 + 1.09(DXA FM) ? 0.11(DXA LTM), model r² = 0.86, root mean square error (RMSE) = 0.233 g] and chemically determined LTM by DXA LTM [LTM = ?0.14 + 1.04(DXA LTM), r² = 0.99, RMSE = 0.238 g]. Discussion: These data show that the precision of DXA for measuring TBMD, TBBM, FM, and LTM in mice ranges from a low of 0.84% to a high of 2.20% (CV). DXA accurately measured bone ash content but overestimated carcass FM and underestimated LTM. However, because of the close relationship between DXA‐derived data and chemical carcass analysis for FM and LTM, prediction equations can be derived to more accurately predict body composition.     

Leptin Responses to Weight Loss in Postmenopausal Women: Relationship to Sex‐Hormone Binding Globulin and Visceral Obesity

Objective: Leptin concentrations increase with obesity and tend to decrease with weight loss. However, there is large variation in the response of serum leptin levels to decreases in body weight. This study examines which endocrine and body composition factors are related to changes in leptin concentrations following weight loss in obese, postmenopausal women. Research Methods and Procedures: Body composition (DXA), visceral obesity (computed tomography), leptin, cortisol, insulin, and sex hormone‐binding globulin (SHBG) concentrations were measured in 54 obese (body mass index [BMI] = 32.0 ± 4.5 kg/m²; mean ± SD), women (60 ± 6 years) before and after a 6‐month hypocaloric diet (250 to 350 kcal/day deficit). Results: Body weight decreased by 5.8 ± 3.4 kg (7.1%) and leptin levels decreased by 6.6 ± 11.9 ng/mL (14.5%) after the 6‐month treatment. Insulin levels decreased 10% (p < 0.05), but mean SHBG and cortisol levels did not change significantly. Relative changes in leptin with weight loss correlated positively with relative changes in body weight (r = 0.50, p < 0.0001), fat mass (r = 0.38, p < 0.01), subcutaneous fat area (r = 0.52, p < 0.0001), and with baseline values of SHBG (r = 0.38, p < 0.01) and baseline intra‐abdominal fat area (r = ?0.27, p < 0.06). Stepwise multiple regression analysis showed that baseline SHBG levels (r² = 0.24, p < 0.01), relative changes in body weight (cumulative r² = 0.40, p < 0.05), and baseline intra‐abdominal fat area (cumulative r² = 0.48, p < 0.05) were the only independent predictors of the relative change in leptin, accounting for 48% of the variance. Discussion: These results suggest that obese, postmenopausal women with a lower initial SHBG and more visceral obesity have a greater decrease in leptin with weight loss, independent of the amount of weight lost.     

Association Between the 4 bp Proinsulin Gene Insertion Polymorphism (IVS‐69) and Body Composition in Black South African Women

The objective of the study was to examine the association between a functional 4 bp proinsulin gene insertion polymorphism (IVS‐69), fasting insulin concentrations, and body composition in black South African women. Body composition, body fat distribution, fasting glucose and insulin concentrations, and IVS‐69 genotype were measured in 115 normal‐weight (BMI <25 kg/m²) and 138 obese (BMI ≥30 kg/m²) premenopausal women. The frequency of the insertion allele was significantly higher in the class 2 obese (BMI ≥35kg/m²) compared with the normal‐weight group (P = 0.029). Obese subjects with the insertion allele had greater fat mass (42.3 ± 0.9 vs. 38.9 ± 0.9 kg, P = 0.034) and fat‐free soft tissue mass (47.4 ± 0.6 vs. 45.1 ± 0.6 kg, P = 0.014), and more abdominal subcutaneous adipose tissue (SAT, 595 ± 17 vs. 531 ± 17 cm², P = 0.025) but not visceral fat (P = 0.739), than obese homozygotes for the wild‐type allele. Only SAT was greater in normal‐weight subjects with the insertion allele (P = 0.048). There were no differences in fasting insulin or glucose levels between subjects with the insertion allele or homozygotes for the wild‐type allele in the normal‐weight or obese groups. In conclusion, the 4 bp proinsulin gene insertion allele is associated with extreme obesity, reflected by greater fat‐free soft tissue mass and fat mass, particularly SAT, in obese black South African women.     

Physical Activity Levels Are Low in Free‐Living Adults with Chronic Paraplegia

Objectives: To compare physical activity levels (PALs) of free‐living adults with chronic paraplegia with World Health Organization recommendations and to compare energy expenditure between persons with complete vs. incomplete paraplegia. Research Methods and Procedures: Twenty‐seven euthyroid adults (17 men and 10 women) with paraplegia (12.5 ± 9.5 years since onset; 17 with complete lesions and 10 with incomplete lesions) participated in this cross‐sectional study. Resting metabolic rate was measured by indirect calorimetry and total daily energy expenditure (TDEE) by heart rate monitoring. PAL was calculated as TDEE/resting metabolic rate. Total body water was measured by deuterium dilution and fat‐free mass (FFM) and fat mass (FM) by calculation (FFM = total body water/0.732; FM = weight ? FFM). Obesity was defined using the following percentage FM cutoffs: men 18 to 40 years >22% and 41 to 60 years >25%; and women 18 to 40 years >35% and 41 to 60 years >38%. Results: Nineteen subjects (70.4%; 13 men and six women) were obese. Fifteen subjects (56%) engaged in structured physical activity 1.46 ± 0.85 times during the observation period for a mean of 49.4 ± 31.0 minutes per session. Despite this, mean PAL of the group was 1.56 ± 0.34, indicative of limited physical activity. TDEE was 24.6% lower in subjects with complete paraplegia (2072 ± 505 vs. 2582 ± 852 kcal/d, p = 0.0372). Discussion: PAL of the group was low, indicating that persons with paraplegia need to engage in increased frequency, intensity, and/or duration of structured physical activity to achieve a PAL ≥1.75 and, thereby, to offset sedentary activities of daily living.     

Effects of Exercise on Metabolic Risk Variables in Overweight Postmenopausal Women: A Randomized Clinical Trial

Objective: This study examined the effects of exercise on metabolic risk variables insulin, leptin, glucose, and triglycerides in overweight/obese postmenopausal women. Research Methods and Procedures: Sedentary women (n = 173) who were overweight or obese (BMI ≥ 25 kg/m² or ≥24 kg/m² with ≥33% body fat), 50 to 75 years of age, were randomized to 12 months of exercise (≥45 minutes of moderate‐intensity aerobic activity 5 d/wk) or to a stretching control group. Body composition (DXA) and visceral adiposity (computed tomography) were measured at baseline and 12 months. Insulin, glucose, triglycerides, and leptin were measured at baseline and 3 and 12 months. Insulin resistance was evaluated by the homeostasis model assessment formula. Differences from baseline to follow‐up were calculated and compared across groups. Results: Exercisers had a 4% decrease and controls had a 12% increase in insulin concentrations from baseline to 12 months (p = 0.0002). Over the same 12‐month period, leptin concentrations decreased by 7% among exercisers compared with remaining constant among controls (p = 0.03). Homeostasis model assessment scores decreased by 2% among exercisers and increased 14% among controls from baseline to 12 months (p = 0.0005). The exercise effect on insulin was modified by changes in total fat mass (trend, p = 0.03), such that the exercise intervention abolished increases in insulin concentrations associated with gains in total fat mass. Discussion: Regular moderate‐intensity exercise can be used to improve metabolic risk variables such as insulin and leptin in overweight/obese postmenopausal women. These results are promising for health care providers providing advice to postmenopausal women for lifestyle changes to reduce risk of insulin resistance, coronary heart disease, and diabetes.     

Racial Differences in Adipocyte Size and Relationship to the Metabolic Syndrome in Obese Women

Objective: To determine whether racial differences exist in the relationship of the abnormalities defining the metabolic syndrome (MS) to regional adiposity and fat cell size (FCS) in obese postmenopausal women. Research Methods and Procedures: We determined the relationship of metabolic variables associated with the MS to regional body composition and abdominal (ABD) and gluteal (GLT) FCS in 25 white (CAU) and 25 African‐American (AF‐AMER) older women matched for age (58 ± 5 years; mean ± SD) and BMI (35 ± 4 kg/m²). Results: MS was present in 36% of the AF‐AMER and 57% of the CAU women. There were no differences in total body, trunk, gluteofemoral fat mass or regional FCS, but AF‐AMER women had 22% lower visceral fat, 24% higher insulin, and 31% lower triglyceride levels than CAU women (p < 0.05). Multiple regression analysis with body fat, visceral ABD fat area, and FCS as independent variables showed that GLT FCS was independently correlated with 2‐hour insulin (r = 0.56), triglyceride (r = 0.62), and high‐density lipoprotein cholesterol (r = ?0.72) levels in AF‐AMER women but not in CAU women, where only systolic blood pressure correlated with subcutaneous ABD fat area (r = 0.57) (p < 0.05). Discussion: The associations between GLT FCS and metabolic dysfunction in obese AF‐AMER but not CAU women suggest that central obesity is a less valid predictor of the MS in obese postmenopausal AF‐AMER women than in CAU women and that GLT FCS may be a more sensitive indicator of risk for the MS in AF‐AMER women.     

Obese reproductive-age women exhibit a proatherogenic inflammatory response during hyperglycemia

Objective: The objective was to determine if physiological hyperglycemia induces a proatherogenic inflammatory response in mononuclear cells (MNCs) in obese reproductive‐age women. Research Methods and Procedures: Seven obese and 6 age‐matched lean women (20 to 39 years of age) underwent a 2‐hour 75‐g oral glucose tolerance test. The release of interleukin‐6 (IL‐6) and interleukin‐1β (IL‐1β) from MNCs cultured in the presence of lipopolysaccharide (LPS) was measured after isolation from blood samples drawn fasting and 2 hours after glucose ingestion. Reactive oxygen species (ROS) generation and intra‐nuclear nuclear factor κB (NFκB) from MNCs were quantified from the same blood samples. Insulin resistance was estimated by homeostasis model assessment of insulin resistance (HOMA‐IR). Total body fat and truncal fat were determined by DXA. Results: Obese women had a higher (p < 0.03) total body fat (42.2 ± 1.1 vs. 27.7 ± 2.0%), truncal fat (42.1 ± 1.2 vs. 22.3 ± 2.4%), and HOMA‐IR (3.3 ± 0.5 vs. 1.8 ± 0.2). LPS‐stimulated IL‐6 release from MNCs was suppressed during hyperglycemia in lean subjects (1884 ± 495 vs. 638 ± 435 pg/mL, p < 0.05) but not in obese women (1184 ± 387 vs. 1403 ± 498 pg/mL). There was a difference (p < 0.05) between groups in the hyperglycemia‐induced MNC‐mediated release of IL‐6 (?1196 ± 475 vs. 219 ± 175 pg/mL) and IL‐1β (?79 ± 43 vs. 17 ± 12 pg/mL). In addition, the obese group exhibited increased (p < 0.05) MNC‐derived ROS generation (39.3 ± 9.9 vs. ?1.0 ± 12.8%) and intra‐nuclear NFκB (9.4 ± 7.3 vs. ?23.5 ± 13.5%). Truncal fat was positively correlated with the MNC‐derived IL‐6 response (ρ = 0.58, p < 0.05) and intra‐nuclear NFκB (ρ = 0.64, p < 0.05). Discussion: These data suggest that obese reproductive‐age women are unable to suppress proatherogenic inflammation during physiological hyperglycemia. Increased adiposity may be a significant contributor to this pro‐inflammatory susceptibility.     

Assessing Body Composition among 3‐ to 8‐Year‐Old Children: Anthropometry,BIA, and DXA

Objective: To examine the inter‐relationships of body composition variables derived from simple anthropometry [BMI and skinfolds (SFs)], bioelectrical impedance analysis (BIA), and dual energy x‐ray (DXA) in young children. Research Methods and Procedures: Seventy‐five children (41 girls, 34 boys) 3 to 8 years of age were assessed for body composition by the following methods: BMI, SF thickness, BIA, and DXA. DXA served as the criterion measure. Predicted percentage body fat (%BF), fat‐free mass (FFM; kilograms), and fat mass (FM; kilograms) were derived from SF equations [Slaughter (SL)1 and SL2, Deurenberg (D) and Dezenberg] and BIA. Indices of truncal fatness were also determined from anthropometry. Results: Repeated measures ANOVA showed significant differences among the methods for %BF, FFM, and FM. All methods, except the D equation (p = 0.08), significantly underestimated measured %BF (p < 0.05). In general, correlations between the BMI and estimated %BF were moderate (r = 0.61 to 0.75). Estimated %BF from the SL2 also showed a high correlation with DXA %BF (r = 0.82). In contrast, estimated %BF derived from SFs showed a low correlation with estimated %BF derived from BIA (r = 0.38); likewise, the correlation between DXA %BF and BIA %BF was low (r = 0.30). Correlations among indicators of truncal fatness ranged from 0.43 to 0.98. Discussion: The results suggest that BIA has limited utility in estimating body composition, whereas BMI and SFs seem to be more useful in estimating body composition during the adiposity rebound. However, all methods significantly underestimated body fatness as determined by DXA, and, overall, the various methods and prediction equations are not interchangeable.     

Sex Differences in the Association of Thigh Fat and Metabolic Risk in Older Adults

We have previously shown a favorable association of subcutaneous leg fat with markers of insulin resistance and dyslipidemia in postmenopausal women. It is not known whether there is a sex dimorphism in the association of lower‐body adiposity with reduced metabolic risk. Thus, our primary aim was to determine whether the favorable association of thigh subcutaneous fat, independent of abdominal fat, is also observed in older men. Mid‐thigh and abdominal fat areas were measured by computed tomography (CT) in 108 older men and postmenopausal women (mean ± s.d.; 69 ± 7 years). Additionally, trunk and leg fat mass (FM) were measured by dual‐energy X‐ray absorptiometry (DXA). Markers of insulin resistance and dyslipidemia were determined from oral glucose tolerance tests and lipid and lipoprotein measurements, respectively. Outcomes were fasted and postchallenge (area under the curve, AUC) insulin (INS_AUC) and glucose (GLU_AUC), product of the insulin and glucose AUC (INS_AUC × GLU_AUC), triglycerides (TG), and high‐density lipoprotein (HDL)‐cholesterol. Consistent with our previous findings in postmenopausal women, adjusting for DXA trunk FM revealed a favorable association of DXA leg FM with the metabolic risk outcomes in both older men and postmenopausal women. Likewise, adjusting for CT abdominal visceral fat generally revealed a favorable association of CT thigh fat with metabolic risk outcomes in women, but not men. The discordance between the DXA and CT results in men is unclear but may be due to sex differences in visceral fat accrual. The mechanisms underlying the protective effect of thigh fat on metabolic risk factors need to be elucidated.     

Anthropometrics Do Not Influence Dual X-ray Absorptiometry (DXA) Measurement of Fat in Normal to Obese Adults: A Comparison with In Vivo Neutron Activation Analysis (IVNA)

Dual-energy X-ray absorptiometry (DXA) is now a commonly used method for the determination of bone mineral status and body composition in humans. The purposes of this study were to compare fat mass by in vivo neutron activation analysis (FM_IVNA) with that by DXA (FM_DXA) in an anthropometrically heterogeneous sample of healthy adult men (n=33) and women (n=36) (19=≤BMI≤39), and to determine whether differences in fat mass estimates between the two methods (ΔFM) were attributable to subject anthropometry as defined by several circumference (waist, iliac crest, thigh) and skinfold thickness (umbilical, suprailiac, abdominal) measurements. No significant differences between FM_DXA and FM_IVNA were observed in men (p=0.46) or women (p=0.09). The two methods were very highly correlated in both sexes (women r²=0.97, p<0.001, men r²=0.91, p<0.001), although the regression line for men was significantly different from the line of identity (p=0.043). These results suggest modest trends toward underestimation of FM_DXA in men when FM_IVNA<18 kg, and overestimation in men when FM_IVNA>18 kg. ΔFM (IVNA-DXA) was not significantly related to any combination of skinfold thicknesses and circumferences in either gender. Age explained 27% of the variance in ΔFM for the men (p=0.008). Furthermore, ΔFM was not significantly related to inter-method disparity in total-body bone mineral measurements in men or women (p<0.05). The present study demonstrates strong correlation in fat measurements between IVNA and DXA in men and women ranging from normal to markedly obese. Correction for subject anthropometry does not significantly improve this relationship.