The purpose of this study was to elucidate the relation between double product break point (DPBP) and pulse wave velocity (PWV).Two hundred three healthy Japanese females were studied (mean age; 53.5 +/- 11.7 years old). The DPBP was measured by continuous incremental exercise test with a bicycle ergometer (ML-3600, Fukuda Electronic Co. Ltd). The work rate at DPBP was converted into metabolic equivalents (METs@DPBP). The brachial-ankle PWV (baPWV) was also measured. In addition, height, weight and mean blood pressure (mBP) were measured and physical activity condition in daily life (PA) was evaluated by questionnaire.The mean METs@DPBP was 5.0 +/- 0.7 METs. The mean baPWV was 1,373 +/- 254 cm/ sec. The relation between METs@DPBP and baPWV was investigated with the use of multiple linear regression models with adjustment for affecting factors of baPWV.In this study, it was identified that there was a significantly inverse relation between METs@DPBP and baPWV (p <0.01). This finding was independent from age, height, weight, mBP and PA. Thus, there was an inverse relation between sub-maximal aerobic capacity and arterial stiffness.

Previously, we have reported that age-predicted heart rate at 50%VO₂max (HR@50%VO₂max) is an effective index of adjusting appropriate exercise intensity for health promotion exercise. Thus, the aim of this study is to elucidate the change in HR at double product break point (HR@DPBP) and the validity of HR@50%VO₂max due to improvement of cardiovascular fitness. Ninety two healthy adults (57 +/- 9 years old), who participated in the health exercise training course, were studied. Participants were instructed how to control the intensity of physical activity for DPBP during their daily life. DPBP was determined with the use of incremental exercise test, and METs at DPBP (METs@DPBP), HR@DPBP, ratings of perceived exertion at DPBP (RPE@DPBP) were measured before and after the course. HR@50%VO₂max was calculated with the following formula; 138 - age/2 (bpm). METs@DPBP significantly increased (p<0.001) after 10 weeks of the course, whereas HR@DPBP did not change. Interestingly, however, there was a significantly positive correlation (p<0.001) between amount of change in METs@DPBP and that in HR@DPBP (ΔHR@DPBP). Multiple linear regression analysis indicated this correlation was independent from sex, age and amount of change in HR at rest (p<0.001). Before and after the course, proportion of study subjects’ %ΔHRs ((HR@50%VO₂max - HR@DPBP) / HR@DPBP x 100) within -10% ~ +10% were both 48.9%, and proportion of study subjects’ RPEs@DPBP within 11~13 were 92% and 85%, respectively. In this study, it was identified that significantly positive relation between amount of change in cardiovascular fitness and that of ΔHR@DPBP. This finding was independent from potentially affecting factors. In conclusion, this longitudinal study could suggest that HR@50%VO₂max and RPE were valuable indexes of determining exercise intensity for health promotion exercise.

Evidence suggests that sports activity can induce site-specific changes in bone mineral content (BMC) in athletes. Therefore, the first purpose of this study was to create a standard value for BMC (SV_BMC) that is independent of body size and physical exercise effect. The second purpose was to examine usefulness for the SV_BMC. In creating the SV_BMC, we recruited non-customer subjects who engaged in regular exercise but did not have site-specific changes to their bony structure. We studied 285 females (34.0±6.5 years) that were currently active, free from hormone treatment, and were not taking medication for any condition. Furthermore, all female subjects reported having a normal menstrual cycle. Bone area (BA), BMC and areal bone mineral density (aBMD) were measured by dual-energy X-ray absorption. Measurements of almost the complete skeleton, with the exception of the head, were taken (herein referred to as sub-total). This included scans of the entire spinal column, all 12 ribs, pelvis, full legs and arms. An allometry formula that relates BMC and BA was applied to determine the SV_BMC. To exclude the effect of body size, calculations were determined using the perpendicular distance from the data of each individual to that determined by allometry regression. Finally, the mean and standard deviation of the distance were converted into T-scores. In examination of reliability for the SV_BMC, we calculated the SV_BMC for three customer females who engaged in regular exercise. We found a significantly positive relationship between SV_BMC and weight/BMI. This correlation was weaker than the relationship between SV_BMC and BMC, as expected, or the relationship between SV_BMC and aBMD, with the exception of SV_BMC in the pelvis. In conclusion, this study suggests that SV_BMC is less affected by body size than by BMC or aBMD and the SV_BMC was provided highly useful in case study.