Gong Yang
Faculty Member
Last active: 4/27/2017

Accelerometer-measured physical activity in Chinese adults.

Peters TM, Moore SC, Xiang YB, Yang G, Shu XO, Ekelund U, Ji BT, Tan YT, Liu DK, Schatzkin A, Zheng W, Chow WH, Matthews CE, Leitzmann MF
Am J Prev Med. 2010 38 (6): 583-91

PMID: 20494234 · PMCID: PMC2897243 · DOI:10.1016/j.amepre.2010.02.012

BACKGROUND - Following adoption of a Western lifestyle, China is experiencing a decline in physical activity levels, which is projected to contribute to future increases in the burden of chronic diseases.

PURPOSE - This study aims to target public health interventions and identify personal characteristics associated with physical activity and sedentary behavior in urban Chinese adults.

METHODS - In a sample of 576 men and women aged 40-74 years from Shanghai, multiple logistic regression was used to examine demographic, anthropometric, and lifestyle factors in relation to levels of physical activity and sedentary behavior assessed by Actigraph accelerometers.

RESULTS - Participants spent 317 minutes/day in physical activity and 509 minutes/day sedentary. In multivariate models, people aged > or =60 years were significantly less likely than those aged <50 years to engage in physical activity (OR=0.29, 95% CI=0.17, 0.49) and more likely to spend time sedentary (OR=2.77, 95% CI=1.53, 5.05). Similarly, obese individuals were less likely to be physically active (OR=0.34, 95% CI=0.17, 0.66) and they were suggestively more likely to be sedentary (OR=1.87, 95% CI=0.94, 3.71) than normal-weight individuals. Furthermore, current cigarette smokers were less physically active than those who formerly or never smoked (OR=0.47, 95% CI=0.28, 0.78).

CONCLUSIONS - Physical activity promotion programs in urban China should target older people, obese individuals, and cigarette smokers, as these population subgroups exhibited low levels of physical activity.

Published by Elsevier Inc.

MeSH Terms (19)

Acceleration Adult Aged Age Factors China Cohort Studies Female Humans Life Style Logistic Models Male Middle Aged Monitoring, Physiologic Motor Activity Multivariate Analysis Obesity Prospective Studies Smoking Urban Population

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