The aim of this study was to reveal the association between feasibility of lifestyle physical activity and individual variables such as demographic attribute, psychological variable on physical activity (stage of physical activity) among Japanese adults, and to examine the variables for tailored strategies on lifestyle activity. Study 1: Forty-nine items were selected as suitable items of questionnaire to measure on feasibility of lifestyle physical activity associated with walking behavior. Twenty-nine out of 49 items were used for analysis on this study since these were the questions which can be answered by everyone. Study 2: 321 individuals (mean age: 41.2 ± 12.4) completed a questionnaire. Exploratory factor analysis yielded three factors: alternative behavior, leisure behavior, and frequent behavior. Feasibility of each behavior is significantly related to individual variables. Alternative behavior is significantly higher among people who are single, metropolitan residing, low BMI, and action, maintenance stage. Leisure behavior is significantly higher among people who are aged between 20 and 30, single, metropolitan residing, and low BMI. Frequent behavior is significantly higher among people who are female, aged between 40 and 60, married, and inoccupation. Results indicated that gender, age, marital status, area of residence, occupational conditions, BMI and the stage of physical activity can be the considerable variables for tailored strategy on lifestyle physical activity. Warrant study to develop the effective intervention program based on these findings.

  The purpose of this study was to compare physical activity, lower leg muscle strength and calf muscle thickness in elderly women from autumn to winter. Participants were 34 healthy elderly women (62-84 years) who lived within a farming and fishery community in the Noto Peninsula, Japan. Steps per day were counted for 9 days at the middle of November (autumn) and at the end of January (winter) using a pedometer. Physical activities were classed as walking, working, sports, outings, or outdoor housework according to self-report. The total time spent on each activity was calculated. Plantar-flexion and dorsi-flexion strength and the thickness of the triceps surae muscle were measured at the day before (autumn) or after (winter) the activity recording period. Number of steps was less in winter (mean 7230 (standard deviation 3118) steps) than in autumn (8878 (3296) steps) (p < 0.001). Total walking time was similar between winter and autumn, but the other total activity times were less in winter than in autumn (p < 0.05). Plantar-flexor strength (67.9 (16.8) vs. 72.6 (16.8) kg) and dorsi-flexor strength (12.2 (3.2) vs. 13.4 (3.0) kg) were lower in winter than in autumn (p < 0.05). The change in step number from autumn to winter was significantly correlated with the change in plantar-flexor strength (r = 0.44, p < 0.05). No significant difference was recognized between calf muscle thicknesses in autumn and winter. These results indicate that physical activity and lower leg muscle strength decease in winter.

  Health disparities result from socio-economic factors. To elucidate the mechanism producing this Gap, the accumulation of comprehensive, non-fragmented evidence is said to be necessary. Healthy elderly begin experiencing eroding lifestyle-caused diseases as they age. It is assumed that if we can analyze the multi-faceted comprehensive day-to-day lifestyle using social epidemiology research methods, it is possible to quantify the health structure, and predict outcomes (healthy, requiring care, or death). Using AGES mass tracking, data was collected from a wide range of lifestyle factors and socio-economic and psychological factors, based on the ICF’s classification covariance structure analysis. The study’s aim was to configure, visualize and validate the health structure (social life) hypothetical model.

  Economic factors are the foundational mechanism for defining health structure, with psychological and social factors acting as intermediate (intervention) factors, defining the physical factor by way of the mental (QOL) factor.Quantifying these health factors can predict outcomes for the next 4 years using retrospective cohort analysis. In order to maintain and promote health the importance of providing social activities, thus producing mental satisfaction by participation (effect of internal and external factors) and the importance of psychological factors that produce a sense of trust has been shown. Preventive effects can be expected in the health policy of the future, and must be stressed. Activation of social factors can also intervene in the external community (harmony). A topic for future research in prevention is the development of health measurement by the intervention mechanism assessment and model optimization.