INTRODUCTION: We aimed to identify developmental trajectories of cigarette use and risk factors associated with the distinct developmental courses of smoking in Chinese early adolescents from age 12 to 16 years. METHODS: Analysis was conducted with secondary data from a longitudinal, prospective cohort of 3,521 Chinese adolescents randomly selected from 4 rural and 7 urban middle schools in Wuhan, China. A group-based growth mixture modeling approach was adopted to identify developmental trajectories of cigarette use. Multilayered intrapersonal (e.g., attitudes toward smoking) and interpersonal (e.g., parental smoking and perceived parental disapproval of smoking) risk factors selected from an ecological perspective were prospectively linked to the identified patterns of smoking trajectory. RESULTS: Three trajectory patterns were identified from the whole cohort: nonsmokers (48.7%), stable light/occasional smokers (48.6%), and accelerating smokers (2.7%). After adjustments for gender, urban residence, and family socioeconomic status, adolescents with higher levels of problems in parent-child relationships and family disharmony, higher perceived norms of peer smoking, higher proportion of good friend smoking, having more troubles with teachers, poorer academic performance, and reporting more frequent depressive symptoms were significantly more likely to be in the trajectory group of either stable light/occasional smokers or accelerating smokers than in the group of nonsmokers. The probability of being in the accelerating smoking trajectory group was positively and significantly related to parental smoking and lack of school bonding. CONCLUSIONS: Study findings help to advance knowledge of the distinct developmental courses of smoking behavior and their associations with multilayered risk factors among Chinese early adolescents.
RCT Entities:
INTRODUCTION: We aimed to identify developmental trajectories of cigarette use and risk factors associated with the distinct developmental courses of smoking in Chinese early adolescents from age 12 to 16 years. METHODS: Analysis was conducted with secondary data from a longitudinal, prospective cohort of 3,521 Chinese adolescents randomly selected from 4 rural and 7 urban middle schools in Wuhan, China. A group-based growth mixture modeling approach was adopted to identify developmental trajectories of cigarette use. Multilayered intrapersonal (e.g., attitudes toward smoking) and interpersonal (e.g., parental smoking and perceived parental disapproval of smoking) risk factors selected from an ecological perspective were prospectively linked to the identified patterns of smoking trajectory. RESULTS: Three trajectory patterns were identified from the whole cohort: nonsmokers (48.7%), stable light/occasional smokers (48.6%), and accelerating smokers (2.7%). After adjustments for gender, urban residence, and family socioeconomic status, adolescents with higher levels of problems in parent-child relationships and family disharmony, higher perceived norms of peer smoking, higher proportion of good friend smoking, having more troubles with teachers, poorer academic performance, and reporting more frequent depressive symptoms were significantly more likely to be in the trajectory group of either stable light/occasional smokers or accelerating smokers than in the group of nonsmokers. The probability of being in the accelerating smoking trajectory group was positively and significantly related to parental smoking and lack of school bonding. CONCLUSIONS: Study findings help to advance knowledge of the distinct developmental courses of smoking behavior and their associations with multilayered risk factors among Chinese early adolescents.
Authors: C R Colder; P Mehta; K Balanda; R T Campbell; K P Mayhew; W R Stanton; M A Pentz; B R Flay Journal: Health Psychol Date: 2001-03 Impact factor: 4.267
Authors: Jennifer B Unger; Li Yan; Sohaila Shakib; Louise Ann Rohrbach; Xinguang Chen; Guo Qian; Chih-Ping Chou; Shan Jianguo; Stanley Azen; Hong Zheng; C Anderson Johnson Journal: Prev Med Date: 2002-04 Impact factor: 4.018
Authors: Bin Xie; Chunhong Liu; Chih Ping Chou; Jiang Xia; Donna Spruijt-Metz; Jie Gong; Yan Li; Hanxiang Wang; C Anderson Johnson Journal: J Adolesc Health Date: 2003-09 Impact factor: 5.012