No seasonal variation in physical activity of Han Chinese living in Beijing

Guanlin Wang, Baoguo Li, Xueying Zhang, Chaoqun Niu, Jianbo Li, Li Li, John R. Speakman

Physical activity (PA) is widely acknowledged to be beneficial to health and wellbeing, and is potentially influenced by a variety of environmental factors such as ambient temperature, weather conditions and air pollution levels. Since these factors vary seasonally, physical activity participation may also respond seasonally. Current population studies to profile physical activity often sample individuals only once, and this may result in biased estimates if there is strong seasonal variation. We conducted a study of 40 Han Chinese adults living in Beijing using GT3X accelerometers. We measured PA levels every two months across a complete year, while simultaneously monitoring ambient temperatures and air pollution levels. Average hourly vector magnitude (VM) and percentage time spent at each PA intensity (sedentary to light, moderate, vigorous and very vigorous) were measured. General Linear models (GLMs) were used to explore the effects of time of day, temperature and PM 2.5 levels on PA. One way ANOVA was used to test whether there were seasonal differences in body weight and body fatness. The main factors influencing activity levels were the time of day and individual characteristics including age and body fatness, but there was no significant difference between the months. In addition, there was no significant impact of either ambient temperature or air pollution levels (PM2.5). There were also no significant differences over the year in the time spent at sedentary-light, moderate and very vigorous PA levels, but for vigorous PA level which occupied less than 0.5% daily physical activity, both month and individual were significant factors. The relatively constant pattern of urban daily life, independent of time of year, may override the potential impacts of environmental factors that would be anticipated to impact PA levels. These subjects did not specifically avoid activity coincident with elevated air pollution levels (PM2.5). Single week long measurements of physical activity could provide a representative measurement of the physical active levels in this population.