Cadence is one of the walking parameters that indicate the level of intensity, but its utility to assess elderly Japanese women is not well documented. The aim of this study was to validate cadence as an index of walking intensity in elderly Japanese women. METHODS: We randomly allocated 50 community-dwelling elderly Japanese women (72.7 ± 6.7 yr) to either the standard-setting or validation group. The walking tests were conducted at the following intensities: walking tempo of 80, 90, 100, 110, 120, and 130 beats/min. The participants were placed under “Normal” or “Optimal” upon subjective discretion. The walking speed, step length, cadence, and heart rate (HR) were assessed using Polar RS800CX Run (Polar Sports Ltd, Finland). Ratings of perceived exertion (RPE) were recorded during the last 15 s of each test. RESULTS: In the standard-setting group, the HR corresponding to the 130 beats/min walking tempo was significantly higher than that for the below 100 beats/min walking tempo. RPE for the 130 beats/min walking tempo was significantly higher than that for the below 110 beats/min walking tempo. HRs and RPE for the 120 and 130 beats/min walking tempo were higher than those for normal walking. Any 15 subjects could not walk to keep the fastest tempo for 3 minutes. The measured step length, HR, cadence, and RPE were not significantly different between the standard-setting and validation groups. CONCLUSION: We determined that a walking tempo of 120 steps/minute can be used as the cutoff for minimally moderate intensity and safety in elderly Japanese women.

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Elderly adults should maintain or improve postural control in order to reduce risk of injury from falls. Several studies have identified weakness in leg muscle power and deficit in static postural control as the common risk factors for falls. The purpose of this study was to examine the relationship between static postural control and type of muscle power output in middle-aged and older men. Thirty-seven healthy men aged 40 to 69 years without disease or impairment affecting the musculoskeletal system were enrolled in this study. The measures used were body mass index (BMI), center of foot pressure in the open and closed condition (CoP; a static equilibrium function test), vertical jump, vertical force in sit-to-stand movement from a chair, rebound jump index (RJ), 8-sec maximal pedaling tests (a leg muscle power test) using a bicycle ergometer with a load of 0.15 and 0.45 N/kg of body weight (0.15 and 0.45 N/BW, respectively), 30-sec chair-stand test (CS-30), and 2-min step test. Partial correlation coefficients analysis, in which age was used as the control variables, revealed that the peak power in maximal pedaling test in 0.45/BW was related to the locus length per unit area (LNG/ AREA) in CoP with the eyes open (r = -0.40) and closed (r = -0.39). These results suggest that static postural control is related to the 8-sec maximal pedaling test.

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It is necessary to understand the developmental characteristics of children’s dynamic balance at the time of nervous system development, especially during coaching or when arranging an appropriate movement environment for children. This study aimed to examine gender and age differences in the dynamic balance. The subjects were aged 3–8 years (boys: 535, girls: 503). To assess the dynamic balance of the subjects, we used the “walking on a bar in zigzags” test; a score of 1–50 points (dynamic balance score) was given on the basis of the distance that they were able to cover on a stick (height, 3cm) that narrowed gradually (width, 6cm-2cm) and displayed a zigzag pattern. Our results showed a significant gender-based difference (F = 8.73, p < .01); however, the effect size was small (η² = 0.01). The dynamic balance score increased with age from age 2 years (boys : 10.1, girls : 10.9) to 8 years (boys : 30.5, girls : 30.9), and there were significant differences between all school years except between 7 years and 8 years. In conclusion, there was little or no sex difference of dynamic balance in the age range of 2–8 years. Furthermore, the dynamic balance develops with age from 2 years to 7 years.

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In physical education and sports science, multivariate analysis is needed when outcome variables are more than two at a time. Multivariate analysis is a generic term; several analyses (e.g. multivariate regression, factor analysis) are encompassed with multivariate analysis. Each analysis of multivariate analysis is based on different each theory. Because researchers can select an analysis from multivariate analysis group, research conclusions may change by types of multivariate analysis although when dataset is identical. In this article, we discussed the influence that the differences in types of multivariate analysis affected research findings. We analyzed the relationship between 8 physical fitness variables and physical activity and gender by multivariate analysis of covariance (MANCOVA), exploratory factor analysis (EFA), and structural equation modeling (SEM). There were small differences on results that were concerned with significance of estimated parameters by each analysis; however, effect size of each parameter was equal in MANCOVA, EFA, and SEM. When statistical assumptions (e.g. multivariate normality, statistical independence) are valid, selection of an analysis may be not a serious problem. On the other hand, when statistical assumptions are invalid, researchers should report details of dataset and the rational reason that selected the analysis because research conclusions may easily change by types of multivariate analysis.

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