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A Journal on Sports Medicine

Official Journal of the Italian Sports Medicine Federation
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Medicina dello Sport 2011 September;64(3):269-84


language: English, Italian

Relationship between physical activity and environment in Shanghai, China: analysis and evaluation in adults aged 45-80

Zhang Y. 1, Chen L. 2, Zhu W. 3, Liu X. 4, Chen D. 5

1 Department of Sports Recreation, Shanghai University of Sport, Shanghai, China 2 Environment Science and Engineering Department, Dong Hua University, Shanghai, China 3 Kinesmetrics Laboratory, Department of Kinesiology and Community Health, University of Illinois at Urbana, Champaign, IL, USA 4 Institute of Sports Science, Shanghai, China 5 Shanghai Institute Of Technology, Shanghai, China


Aim. The aim of the study was to investigate the associations between physical activity level, social demographic characteristics and environment in Chinese middle-aged and older adults, and to evaluate the physical activity-related environment of urban areas.
Methods. Sociodemographics and perceived environment were assessed by questionnaires distributed to 1100 participants, aged 45-80 years, of 13 selected communities belonging to three districts from urban centers, subcivic centers and suburbs of Shanghai between April-October 2009. Physical activity was measured by a pedometer. The analysis of relationship between physical activity and environment and the evaluation of communities and districts of Shanghai were conducted with the method of gray correlation analysis in January-June, 2010.
Results. Bivariate relationship analysis showed how employment status, education, “whether walking is the main exercise”, health status have positive and body mass index has negative associations with physical activity; body-building club, traffic safety, street design, ground surface, crossing the street and activity environment are the largest six factors affecting physical activities. The order of comprehensive evaluation of the three districts is: LuWan, YangPu and MinHang; the order of 13 communities is: N3 > N2 > N4 > N10 > N9 > N11 > N7 > N6 > N5 > N8 > N1 > N12 > N13. From above, the urban center environment is most appropriate for physical activity, subcivil center ranks the second position and suburbs the last. The urban environment is most appropriate for physical activity, subcivil center ranks the second position and suburb the last. The logical result proved the gray correlation analysis is an effective method to study the relationship between physical activity and environment.
Conclusion. These findings collectively suggest that public health, city planning and environment protecting need to consider how to create more livable and pedestrian-friendly community areas, especially in developing countries, as China.

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