The purpose of this study was to assess the changes occurring in risky and running-based physical play using a two-dimensional mood scale and salivary stress markers, and to determine the differences between the two activities. Fifteen elementary school students participated in a risky play program (e.g., rock walking, wall climbing) and running-based physical play program (e.g., tag, relay race). Twodimensional mood scale and salivary stress markers were measured before and after each program. The results of the analysis showed that the participants’ vitality level increased, and their mood became livelier and more energetic after the physical play regardless of the physical play condition. Stability level did not change significantly in either condition. In a running-based physical play program, the mood states of the participants varied, with some participants reporting a more pleasant mood state and others reporting a decrease in mood state. Regarding the results on stress, chromogranin A levels were increased only in the risk exercise play condition. However, salivary amylase levels did not change significantly in either condition. These results indicate that mental stress increased in the risky play condition, despite the pleasant mood. The results suggest that risky play generates positive stress (eustress) for the children. Because differences in mood change and stress dynamics were observed depending on the type of physical play, it is recommended that children engage in a variety of physical play.

　The ratio of limits of stability (LOS) to base of support (BOS) should be large. However, balance tests often inadequately address LOS and tend to overlook BOS. Moreover, higher difficulty levels may hinder some middle-aged and elderly individuals from performing these tests. This study aims to explore variations in foot breadth (0 cm, 10 cm) and the day-to-day reliability in rate of LOS per BOS (LPB) of two motions, examining relationships between LPBs in ten middle-aged and elderly males. A pressure-sensitive mat and force platform measured BOS and LOS, respectively, with the former positioned on top of the latter. Subjects, following BOS measurements, assessed LOS through circular (rotational motion) and four-directional tilting motions. These measurements spanned three days. Two-way analysis of variance demonstrated no significant interaction differences for both motions; however, there was a notable main effect of the breadth factors. LPB for both motions was consistently higher at 10 cm than at 0 cm throughout the study. All intraclass correlation coefficients were >0.80. Relationships between LPBs were >0.87. In conclusion, day-to-day reliability demonstrated a moderate or larger extent. The LOS for rotational motion was <40% of BOS (0 cm: 33.5%, 10 cm: 36.6%), whereas for tilting motion, was approximated 50% of BOS (0 cm: 50.2%, 10 cm: 53.9%). Ultimately, LPB increased with the widening of foot distance in both motions. Furthermore, there was a strong relationship between the LPBs.

　The impact of age, living space, and driving on physical fitness and motor abilities in the elderly may vary across different age groups. This study aimed to examine the associations between age, living space, driving, and physical fitness and motor abilities using structural equation modeling to elucidate the relationships among these factors. The study included 88 early-stage elderly women aged 65 to 74 years (70.9 ± 2.5 years) and 169 late-stage elderly women aged 75 years and older (81.0 ± 3.7 years). Physical fitness and motor abilities were measured through tests including hand grip strength, knee extension strength, standing on one leg with eyes open and using functional reach, 10-m maximal walking, cross-step moving on four spots, and hip displacement in the anteroposterior direction. The analysis found no significant relationships among the factors in the early-stage group. However, in the late-stage group, significant associations emerged between age and living space with physical fitness and motor abilities (−0.36, 0.22). Furthermore, using Pearson’s product-moment correlation coefficient, a significant correlation was observed between Living Space Assessment (LSA) and both knee extension strength and hip joint mobility. While driving did not show a direct impact, age and living space notably influenced at least lower limb strength and hip strategy, emphasizing the importance of these factors in maintaining motor abilities in late-stage elderly women.

　In this study, the subjects pedaled bicycles while checking ergometers to keep pedal rotations at approximately 50%rpm of the maximum effort, in order to verify the impact on the Grading ability when changing the intensity (20%rpm, 40%rpm, 60%rpm, 80%rpm) between 2 types of load (weights of 5%kp, 8%kp). The subjects were 15 healthy adult males (24.5 ± 2.5 years old) between the ages of 22 - 25 years old. The maximum cadence at each load was obtained with a bicycle ergometer, and the pedal cadence corresponding to 50%rpm of the maximum cadence was sustained for 20 seconds. Then, pedaling at a rate corresponding to four different cadences was performed twice each without checking the ergometer, and the error between the target value and the exerted power was examined. The results of the study showed that the gradation of muscle output adjustment was possible in bicycle pedaling exercise, which is a multijoint alternating exercise, and that the error was larger at low cadence (20%rpm) than at other cadences.

　A body composition measurement is commonly used as a health promotion tool for residents. This study analyzed the patterns of regional skeletal muscle distribution among participants in a body composition measurement event. A total of 618 participants (74.1% women, mean age: 64.5 years) provided skeletal muscle data using Tanita MC 980-MA Plus, a multi-frequency bioelectrical impedance analysis device. The skeletal muscle score (SMS) for different body regions (right arm, left arm, trunk, right leg, and left leg) was used to categorize participants into groups based on their muscle distribution patterns. The latent class analysis identified four classes: Class 1 (19.4%) with low SMS in all body regions; Class 2 (25.9%) with low SMS in the upper body; Class 3 (39.8%) with normal SMS in all body regions; and Class 4 (14.4%) with high SMS in all body regions. This information has guided us in refining the handouts introducing exercises to be used in the body composition measurement.