Chenshu Zhang1, Judith S Brook1, Carl G Leukefeld2, Mario De La Rosa3, David W Brook1. 1. a Department of Psychiatry , New York University School of Medicine , New York , New York , USA. 2. b Department of Behavioral Sciences , University of Kentucky , Lexington , Kentucky , USA. 3. c Center for Research on US Latino HIV/AIDS and Drug Abuse , Florida International University , Miami , Florida , USA.
Abstract
OBJECTIVE: To study the degree to which individuals in different trajectories of cigarette smoking from adolescence to the early forties are similar or different in terms of lack of preventive health behaviors (e.g., underuse of preventive health services, unhealthy eating habits) in early midlife. METHODS: Participants came from a community-based random sample of residents in two upstate New York counties (N = 548). Data were collected from adolescence to early midlife (mean age = 43 years, standard deviation [SD] = 2.8) at seven time points. Using growth mixture modeling, we statistically identified the number of smoking trajectories. Logistic regression analysis was used to study the relationship between the probabilities of participants' smoking trajectory group membership and lack of preventive behaviors in early midlife. RESULTS: Five trajectory groups of cigarette smokers were identified. With controls, as compared with the nonsmoker trajectory group, higher probabilities of belonging to the heavy/continuous smoker trajectory group and the late starter trajectory groups were significantly associated with a higher likelihood of lack of preventive health behaviors (adjusted odds ratio [AOR] = 3.49 and 4.02 respectively). In addition, as compared to the quitter/decreaser trajectory group, higher probabilities of belonging to the heavy/continuous smoker trajectory group and the late starter trajectory group were also significantly associated with a higher likelihood of lack of preventive health behaviors (AOR = 3.51 and 4.04 respectively). CONCLUSIONS: Intervention programs may consider focusing on heavy/continuous smokers and late starters in programs designed to promote adequate use of preventive health services and healthy general lifestyles in early midlife.
OBJECTIVE: To study the degree to which individuals in different trajectories of cigarette smoking from adolescence to the early forties are similar or different in terms of lack of preventive health behaviors (e.g., underuse of preventive health services, unhealthy eating habits) in early midlife. METHODS:Participants came from a community-based random sample of residents in two upstate New York counties (N = 548). Data were collected from adolescence to early midlife (mean age = 43 years, standard deviation [SD] = 2.8) at seven time points. Using growth mixture modeling, we statistically identified the number of smoking trajectories. Logistic regression analysis was used to study the relationship between the probabilities of participants' smoking trajectory group membership and lack of preventive behaviors in early midlife. RESULTS: Five trajectory groups of cigarette smokers were identified. With controls, as compared with the nonsmoker trajectory group, higher probabilities of belonging to the heavy/continuous smoker trajectory group and the late starter trajectory groups were significantly associated with a higher likelihood of lack of preventive health behaviors (adjusted odds ratio [AOR] = 3.49 and 4.02 respectively). In addition, as compared to the quitter/decreaser trajectory group, higher probabilities of belonging to the heavy/continuous smoker trajectory group and the late starter trajectory group were also significantly associated with a higher likelihood of lack of preventive health behaviors (AOR = 3.51 and 4.04 respectively). CONCLUSIONS: Intervention programs may consider focusing on heavy/continuous smokers and late starters in programs designed to promote adequate use of preventive health services and healthy general lifestyles in early midlife.
Entities:
Keywords:
Trajectory of cigarette smoking; lack of exercise; lack of preventive health behaviors; poor sleeping habits; underuse of preventive health services; unhealthy eating habits
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