Most people who go to fitness clubs or sports gyms for weight control, and many co-medicals and physicians believe that an increase in muscle mass and/or basal metabolic rate (BMR) is possible through a combination of regular exercise and optimal protein intake during weight loss. This seems a myth, and the reasons are discussed in this article. First, muscle mass is quite difficult to quantify. The limitations of body composition measurement should be well understood. Second, increasing muscle mass during weight loss is difficult. This might be attained through strict implementation of a protein-rich, low-carbohydrate diet; high-intensity resistance training; and aerobic exercise for a long duration. However, such a strict regimen is not feasible for most people. Finally, a 1-kg increase in muscle mass corresponds to an increase of only 13 kcal of BMR per day. Thus, an increase in muscle mass of 1 kg is difficult to achieve, while the gained BMR is approximately equivalent to a decrease of 13.5 kcal of BMR according to a 3-kg decrease of adipose tissue. Weight loss, unless through an extremely sophisticated weight control program, contributes to a decrease in BMR. However, it is an accomplished fact that women with significantly less muscle mass and lower BMR live longer than men with more muscle mass and higher BMR, regardless of ethnicity. Maintaining activities of daily living and daily activity function might be more essential.

Although body mass is known to be related to bone mass, defined as bone mineral density (BMD) and bone mineral content (BMC), little is known about the effects of body mass reduction programs on bone mass. This study assessed bone mass changes in response to four body mass reduction programs that utilized diet and/or exercise. Ninety-four obese or overweight women (age 49.3±7.1 years, body mass 68.5±7.7 kg) were randomly assigned 4 groups (2 intervention forms × 2 trials) : diet in trial 1 (D₁, n=27), diet plus exercise in trial 1 (DE₁, n=28), diet in trial 2 (D₂, n=21), and diet plus exercise in trial 2 (DE₂, n=18) . Body mass, body mass index (BMI), absolute and relative (%fat) fat mass, lean mass, BMC, and BMD were measured by dual energy X-ray absorptiometry before and after the 3-month intervention program. Body mass loss was similar in DI (-9.7%) and D₂ (-11.6%), and in DE₁ (-13.8%) and DE₂ (-12.2%) . However, BMC loss was different (P<0.05) between trial 1 and trial 2 for each intervention form (D₁: -3.2% vs D₂ ; -0.9%, DE₁: -4.5% vs DE₂: -0.8%) . With this in mind, multiple regression analyses were applied, with either change in BMC or BMD as the dependent variable, and other physical characteristics measured before and after the intervention program as independent variables. Results indicated that multiple correlation coefficients were statistically significant (R=0.61 with BMC, R=0.49 with BMD) . BMI after the intervention program and change in body mass were identified as the significant contributors to the change in BMC, while change in %fat and age were identified as the significant contributors to the change in BMD. These results suggest that, during body mass reduction, (1) physical characteristics are the significant contributors to changes in BMC and BMD and (2) exercise may not prevent the loss of bone mass.

The purpose of this study was to develop a simple and easy predictive model of leg, spine and whole body bone mineral density (BMD) from anthropometric, physical fitness, body composition and quantitative ultrasound (QUS) variables. Participants were 138 Japanese overweight and obese men (50.9 ± 9.6 yr, body mass index [BMI] 29.1 ± 2.6 kg/m²). We measured anthropometric variables (height, weight, BMI, chest, waist, hip, upper arm, thigh circumferences), physical fitness (grip strength, side steps, vertical jump, forced vital capacity), body composition (fat-free mass) and QUS. BMD was measured by dual energy X-ray absorptiometry. Multiple linear regression analyses showed that all predictive models for BMD were significant. As a result, the predictive model for leg BMD showed the highest model fitting. The Bland & Altman approaches demonstrated the (positive or negative) systematic error even though most plots were placed within ideal range. Predictive model from physical fitness, body composition and QUS would be useful for estimating whole body and regional BMD. Because these predictive models are likely to have some systemic errors, further research is needed to improve the predictive accuracy.

It has been reported that visceral fat (VF) is an independent predictor of the incidence for coronary heart disease, and is associated with its risk factors. The independent effects of exercise or dietary modification on VF remain to be fully elucidated, especially in obese middle-aged men. The purpose of this study was to investigate effects of exercise on VF compared to dietary modification. Thirty-five obese middle-aged men participated in this study. They consisted of exercise group (n=22, 51.4±11.6 yr, Group E) and diet group (n=13, 48.8±12.2 yr, Group D). Participants in Group E followed 90-min exercise sessions on a regular basis 3 days per week for 12 weeks. Participants in Group D attended weekly classes aimed at maintaining well-balanced 1,680 kcal/d diet for 12 weeks. Body weight decreased significantly in both groups (Group E : −2.9 kg, Group D : −5.4 kg). Visceral fat area (VFA) determined by computed tomography also decreased significantly (Group E : −32.0 cm², Group D : −39.4 cm²). An analysis of covariance adjusted by weight change revealed no significant group difference in VFA change. These results suggest that exercise-induced negative energy balance does not result in greater decrease in VFA as compared with dietary modification alone.

The purpose of this study was to compare estimates of human body composition determined from single-frequency bioelectrical impedance methods (S-BIM) and multi-frequency bioelectrical impedance methods (M-BIM) . The human body composition was assessed by dual energy X-ray absorptiometry (DEXA), 5 brands of S-BIM, and 2 brands of M-BIM. Forty-five women, aged 26-58 years, served as subjects. The S-BIM and M-BIM fat-free mass (FFM) estimates were highly correlated with the FFM measured by DEXA (r=0.82-0.93) . The standard errors of estimate (SEE) for FFM were approximately 2 kg. With the exception of the MLT-100 (which slightly underestimated FFM), all brands of BIM slightly overestimated FFM. The absolute mean differences between FFMDEXA and each of the 7 BIM estimates ranged from -3.02 kg to 3.46 kg. Although the 7 brands of BIM provided slightly different estimates, the results of this study suggest that 5-BIM and M-BIM are relatively valid in human body composition.

The purpose of this study was to determine the loss of visceral fat during weight loss program with diet only or diet plus exercise in premenopausal obese women (age 44±6 yr) . One hundred seventeen women (body mass index 29±3 kg /m²) were divided into diet only group (DO, n=40) and diet plus exercise group (DE, n=77) . DE was further divided into two groups: a group with a small change in VO₂max (DE₁, n=26) and a group with a large change in VO₂max (DE₂, n=51) . Height, weight, fat mass, %fat, fat-free mass (FFM), abdominal total fat area (TFA), visceral fat area (VFA), subcutaneous fat area (SFA) and VO₂max (ml/kg FFM/min) were measured before and after weight loss. The changes of weight, fat mass, %fat were significantly larger in DE than in DO. No difference was found in the changes of weight, fat mass, %fat between the DE₁ and DE₂. Percentage of change in VFA was significantly larger in DE₂ (41±15%) than in DE₁ (31±16%) . These data suggest that both weight-loss programs (DO and DE) contribute to a remarkable decrease in visceral fat. Addition of exercise training, which would induce an improvement in VO₂max, to dietary restriction, may elicit a greater effect on visceral fat.

A number of studies have shown that sleep disordered breathing (SDB) has a strong relation with obesity. The purpose of this study was to examine the effect of a short-term weight-loss program in obese men with SDB. In our 14-week weight-loss program, forty-one obese men (mean±SD, age ; 49.6±10.8 yr, body mass index ; 27.9±2.5 kg/m²) were assigned to 2 subgroups : diet only (DO ; n=19) and diet plus aerobic exercise (DE ; n=22). 2%, 3%, and 4% oxygen desaturation index (ODI) were measured by pulse oximetry before and after the weight-loss program. Weight and %fat significantly (p<0.05) decreased in the total subject pool consisting of DO plus DE (weight ; -8.4±3.5 kg, %fat ; -7.5±3.5%). 2%, 3%, and 4% ODI significantly decreased by -3.46±5.01 event/hour, -2.37±3.57 event/hour, and -1.99±2.84 event/hour, respectively. Significant correlations were found between 2%, 3%, and 4% ODI at baseline and changes of 2%, 3%, and 4% ODI during the weight-loss program (2% ODI ; r=0.48, 3% ODI ; r=0.51, 4% ODI ; r=0.67). Weight loss and %fat loss did not differ significantly between DO and DE (DO : -7.6±3.2 kg, -6.8±3.2%, DE : -9.2±3.7 kg, -8.1±3.7%). The increase in maximal oxygen uptake was slightly larger for DE (4.7±4.6 ml/kg/min) compared to DO (2.5±3.3 ml/kg/min), but there was no significant interaction. Changes of 2%, 3%, and 4% ODI did not differ significantly between groups. These results suggest that for obese men with SDB, the weight-loss program is an effective method, leading to improvement in SDB, although the combination of aerobic exercise to diet may not produce additional effects to SDB, compared with the diet only.

The purpose of this study was to investigate the accuracy of estimating human body composition changes using bioelectrical impedance (BI) methods during a weight-loss intervention. Subjects were forty-three obese men (age : 49.2±10.5 yr, BMI : 27.8±1.7 kg/m²) who completed a 14-week weight-loss intervention. In all subjects, fat mass (FM) and fat-free mass (FFM) were assessed by dual energy x-ray absorptiometry (DXA) as well as single- and multi-frequency BI methods (SBIM, MBIM) before and after the intervention. Resistance parameters were measured by SBIM and MBIM (SBIM : R₅₀ ; MBIM : R∞, R0, and Rfc). In nine subjects these variables were also measured at weeks 1 and 4. Weight decreased (P<0.05) by -8.0±3.2 kg during the intervention while FFM changes averaged -0.4±1.6 kg (DXA), -2.0±1.5 kg (SBIM), and -1.6±1.7 kg (MBIM). BI methods overestimated FFM before the intervention (before ; DXA : 54.4±4.8 kg, SBIM : 56.5±4.3 kg, MBIM : 55.9±4.5 kg). In nine subjects, FFM measured by SBIM (FFM_SBIM) and MBIM (FFM_MBIM) was similar to FFM measured by DXA(FFM_DXA)(after ; DXA : 54.6±5.4 kg, SBIM : 54.6±3.8 kg, MBIM : 54.6±4.1 kg), although BI methods overestimated the FFM before the intervention (before ; DXA : 54.9±5.1 kg, SBIM : 56.9±3.8 kg, MBIM : 56.3±4.4 kg). The ΔFM_SBIM and ΔFM_MBIM were highly correlated with the ΔFM_DXA(SBIM : r=0.87, MBIM : r=0.88). The ΔFFM_SBIM andΔFFM_MBIM were significantly correlated with the ΔFFM_DXA(SBIM : r=0.54, MBIM : r=0.49). The ΔR₅₀ and ΔRfc were also significantly correlated with the ΔFFM_DXA(R₅₀ : r=-0.63, Rfc : r=-0.48). These results suggest that during a weight-loss intervention, 1) BI methods and DXA provide similar estimates of human body composition change, although they overestimate FFM in obese men, and 2) changes of resistance parameters observed with BI methods may estimate human body composition change more accurately.