Abstract: Objective:The aim of this study was to identify patterns of sedentary behavior in Chinese adults and examine associations between these patterns,sociodemographic,behavioral manners and health variables.Methods:A total of 408 adults without obesity genetic history,severe acute or chronic illness,disability,neural function damage and mental illness were enrolled in the study.Participants completed a health and sociodemography questionnaire and provided height and weight value.Sedentary behavior was assessed by physical activity log,in the meantime,accelerometer was used to measure objectively physical activity status and to verify the validity of physical activity log in evaluating sedentary behavior.Pattern of sedentary behavior was identified by clustering analysis,classification effect was verified by discriminant analysis.Results:four sedentary patterns were identified:mixed sedentary behavior pattern,entertainment sedentary behavior pattern,occupational sedentary behavior pattern and screen-based sedentary behavior pattern.Its effect is better to classify the crowd,the percentage of adults is62.9% in screen-based sedentary behavior pattern and entertainment sedentary behavior pattern,these two kinds of patterns are the main patterns of urban residents in our country.Age and education variables show significant differences among four patterns,the percentage of the elders is higher in four patterns,the percentage of people educated highly is 62.2%in occupational sedentary behavior pattern.The percentage of people in ≥10000steps/day group is much less than the<10000steps/day group,participants in “30minutes/day MVPA”is only38.6% exceed the goal of “≥10000steps/day”,they are not consistent.The percentage of people in overweight-obesity group and suffering from chronic diseases group is much less than normal weight group and non-suffering from chronic diseases group,there is no statistical significance.Conclusion:mixed sedentary behavior pattern,entertainment sedentary behavior pattern,occupational sedentary behavior pattern and screen-based sedentary behavior pattern are optimal clustering scheme,it can better distinguish the samples.the percentage of the elders is higher in four patterns,the elder was used to especially take part in mixed sedentary behavior pattern.the percentage of the well-educated people is higher in occupational sedentary behavior pattern.Step/day,MVPA,obesity and chronic disease variables show significant differences among four patterns,it is obvious that sedentary behavior is not the only risk factor of obesity and chronic disease,important of physical activity and dietary should be considered.