scholarly journals Clustering effects of health risk behavior on mental health and physical activity in Chinese adolescents

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Xiangren Yi ◽  
Zongyu Liu ◽  
Wenzhen Qiao ◽  
Xiuye Xie ◽  
Nuo Yi ◽  
...  
2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Mengcheng Wang ◽  
Jinyao Yi ◽  
Lin Cai ◽  
Muli Hu ◽  
Xiongzhao Zhu ◽  
...  

Author(s):  
Charles J Holahan ◽  
Carole K Holahan ◽  
Sangdon Lim ◽  
Daniel A Powers

Abstract Background Behavioral medicine is showing growing theoretical and applied interest in multiple health-risk behaviors. Compared to engaging in a single health-risk behavior, multiple health-risk behaviors are linked to increased morbidity and mortality. A contextual determinant of multiple risk behaviors may be living with a smoker. Purpose This study investigated the role of living with a smoker in predicting multiple health-risk behaviors compared to a single health-risk behavior, as well as whether these multiple risk behaviors occur across both physical activity and dietary domains. Moreover, the study tested these effects across 3 years in longitudinal and prospective (controlling for health-risk behaviors at baseline) analyses. Methods Participants were 82,644 women (age M = 63.5, standard deviation = 7.36, age range = 49–81) from the Women’s Health Initiative Observational Study. Analyses used multinomial and binary logistic regression. Results Living with a smoker was more strongly associated with multiple health-risk behaviors than with a single health-risk behavior. These multiple risk behaviors occurred across both physical activity and dietary domains. The effects persisted across 3 years in longitudinal and prospective analyses. Living with a smoker, compared to not living with a smoker, increased the odds of multiple health-risk behaviors 82% cross-sectionally and, across 3 years, 94% longitudinally and 57% prospectively. Conclusions These findings integrate research on multiple health-risk behaviors and on living with a smoker and underscore an unrecognized public health risk of tobacco smoking. These results are relevant to household-level interventions integrating smoking-prevention and obesity-prevention efforts.


PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242186
Author(s):  
Derrick Ssewanyana ◽  
Amina Abubakar ◽  
Charles R. J. C. Newton ◽  
Mark Otiende ◽  
George Mochamah ◽  
...  

Background Adolescents tend to experience heightened vulnerability to risky and reckless behavior. Adolescents living in rural settings may often experience poverty and a host of risk factors which can increase their vulnerability to various forms of health risk behavior (HRB). Understanding HRB clustering and its underlying factors among adolescents is important for intervention planning and health promotion. This study examines the co-occurrence of injury and violence, substance use, hygiene, physical activity, and diet-related risk behaviors among adolescents in a rural setting on the Kenyan coast. Specifically, the study objectives were to identify clusters of HRB; based on five categories of health risk behavior, and to identify the factors associated with HRB clustering. Methods A cross-sectional survey was conducted of a random sample of 1060 adolescents aged 13–19 years living within the area covered by the Kilifi Health and Demographic Surveillance System. Participants completed a questionnaire on health behaviors which was administered via an Audio Computer-Assisted Self–Interview. Latent class analysis on 13 behavioral factors (injury and violence, hygiene, alcohol tobacco and drug use, physical activity, and dietary related behavior) was used to identify clustering and stepwise ordinal logistic regression with nonparametric bootstrapping identified the factors associated with clustering. The variables of age, sex, education level, school attendance, mental health, form of residence and level of parental monitoring were included in the initial stepwise regression model. Results We identified 3 behavioral clusters (Cluster 1: Low-risk takers (22.9%); Cluster 2: Moderate risk-takers (67.8%); Cluster 3: High risk-takers (9.3%)). Relative to the cluster 1, membership of higher risk clusters (i.e. moderate or high risk-takers) was strongly associated with older age (p<0.001), being male (p<0.001), depressive symptoms (p = 0.005), school non-attendance (p = 0.001) and a low level of parental monitoring (p<0.001). Conclusion There is clustering of health risk behaviors that underlies communicable and non-communicable diseases among adolescents in rural coastal Kenya. This suggests the urgent need for targeted multi-component health behavior interventions that simultaneously address all aspects of adolescent health and well-being, including the mental health needs of adolescents.


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