A cross-sectional survey was done to investigate the pathways the physical activity acts in improving physical fitness and functional outcomes of older adults (60 years and above) using 880 community-dwelling older adults in Sri Lanka. Structural Equation Modeling (SEM) was used. The final SEM model included five latent factors and 14 co-variances. Goodness of Fit Index (GFI), Comparative fit index (CFI) and Root Mean Square Error of Approximation (RMSEA) values of the model were 0.95, 0.93, 0.91, and 0.05 respectively, indicating a good model fit. Strength enhances balance (β = .52, p
OBJECTIVES: To compare the prevalence and correlates of cigarette smoking among East Asian college students.
METHODS: Data were collected from college students (N=16,558) in China, Hong Kong, Malaysia, Singapore, South Korea, and Taiwan (response rate: 78%).
RESULTS: Religion was independently associated with college students' smoking in China (adjusted odds ratio [AOR] = 1.82) and South Korea (AOR = 0.80). Being a heavy drinker and having a higher exposure to secondhand smoke were associated with higher smoking rates (Ps < .001).
CONCLUSIONS: The East Asian economies show a varied prevalence of college smoking but a similar pattern of relationship with its correlates.
Study site: 21 institutions in 6 East Asian economies: 3 colleges each from Hong Kong, Malaysia, Singapore, and South Korea; 4 colleges from Taiwan; and 5 colleges from China.
BACKGROUND: Little is known on the level of physical inactivity and its behavioral and cultural correlates among East Asian college students.
PURPOSE: The aim of this study is to examine and compare the level and behavioral and cultural correlates of physical inactivity among college students in Taiwan, Hong Kong, South Korea, Singapore, and Malaysia.
METHOD: Data were collected from a representative sample of college students (N = 12,137) in five East Asian economies during the 2008-2009 academic year. The stratified random sampling (stratum: geographic region) was used to select participating institutions. The overall response rate was 77%.
RESULTS: The percentage of physically inactive students was 7.2% for Singapore, 8.0% for Malaysia, 13.5% for Taiwan, 16.8% for Hong Kong, and 28.5% for South Korea. When gender, age, and body mass index were controlled, fruit and vegetable consumptions were significant correlates for physical inactivity across all the five economies. In Hong Kong, Korea, and Taiwan, those who engaged in binge drinking at least once during the past 2 weeks were less likely to be physically inactive than those who did not. Religion and military experience did not independently predict physical inactivity in any of the five economies.
CONCLUSION: Physical inactivity varies greatly across different economies in East Asia that are usually grouped together and considered a single homogeneous entity by some researchers. However, in terms of correlates of physical inactivity, findings of the current study indicate that the transversal value of physical activity might be transformed into a universal.