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.

This study aimed to evaluate dynamic balance capability, bathyesthesia, and the composite compensation of bathyesthesia and visual sense for dynamic balance assessed by use of force plates and to examine their correlation to age in a cross-sectorial manner. Participants of this study were 147 healthy people (55 men, 92 women). To evaluate dynamic balance capability, we evaluated the index of postural stability (IPS), which is the logarithmic value of the ratio of the area of stability limits to the area of postural sway, with participants standing on a hard surface with eyes opened. To measure bathyesthesia, we evaluated the modified index of postural stability (MIPS), i.e., the IPS with participants standing on a soft surface with eyes closed. As for the composite compensation index of bathyesthesia and visual sense for dynamic balance, we calculated the rubber IPS Romberg ratio (MIPS/IPS). The correlation coefficients (Spearman’s rho) of IPS, MIPS and MIPS/IPS to age were −0.666 (p < 0.001), −0.697 (p < 0.001) and −0.600 (p < 0.001), respectively. These results suggest that dynamic balance capability and bathyesthesia decline with advancing age, and the composite compensation of bathyesthesia and visual sense for dynamic balance strengthens with advancing age.

    Clinical research is essential for the practice of evidence-based medicine. This study reports on our current practice of clinical research support in Mito Kyodo General Hospital and discusses future challenges. In April 2013, the University of Tsukuba hired a clinical research assistant to provide clinical research support in Mito Kyodo General Hospital. The clinical research assistant worked full-time in the hospital in collaboration with 3 university faculty members. The target population for this study comprised 450 medical personnel including doctors, nurses, and other medical staff. From April 2014, 1 of the 3 faculty members visited the hospital once a month to offer clinical research consultations and deliver a lecture on nursing research. We analyzed past records of clinical research support and conducted a questionnaire survey to explore the level of satisfaction of the medical personnel. Four-hundred and ninety records of 91 research topics proposed by 68 medical personnel were identified. Of these, 93.4% were proposed by doctors or nurses. Most studies employed an observational study design (64.8%) and were conducted in order to make a presentation at an academic conference (51.1%). The consultation sessions were held 1–5 times, for 40–405 min, and lasted from 1–84 days per research topic. Consultations mostly pertained to research design and protocol planning (57.1%). Forty-seven clients were invited to participate in the questionnaire survey, 30 of whom provided valid responses. The results showed that 96.6% of the clients were satisfied with the consultations. The number of clients who participated in the consultations comprised only 15.1% of the target population. These practice biases need to be addressed in future. However, nearly all respondents were satisfied with the consultations. These findings suggest that our clinical research support was beneficial to medical personnel.

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.