Using latent class analysis to profile risk behaviors among sexual minority students

2018 ◽  
pp. 120
Author(s):  
Yongwen Jiang ◽  
Jan Mermin ◽  
Tara Cooper ◽  
Rosemary ReillyChammat ◽  
Samara VinerBrown
2018 ◽  
Vol 25 (5) ◽  
pp. 572-592 ◽  
Author(s):  
Megan E. Sutter ◽  
Annie E. Rabinovitch ◽  
Michael A. Trujillo ◽  
Paul B. Perrin ◽  
Lisa D. Goldberg ◽  
...  

This study explored patterns of intimate partner violence (IPV) victimization and perpetration in 150 sexual minority women (SMW): 25.3% had been sexually victimized, 34% physically victimized, 76% psychologically victimized, and 29.3% suffered an IPV-related injury. A latent class analysis found four behavioral patterns: (1) minor-only psychological perpetration and victimization; (2) no IPV; (3) minor–severe psychological, physical assault, and injury victimization, and minor-only psychological, physical, and injury perpetration; and (4) severe psychological, sexual, physical assault, and injury victimization and perpetration. Individuals who experienced and/or perpetrated all types experienced the greatest heterosexism at work, school, and in other contexts.


Author(s):  
Shikha Kukreti ◽  
Tsung Yu ◽  
Po Wei Chiu ◽  
Carol Strong

Abstract Background Modifiable risk behaviors, such as smoking, diet, alcohol consumption, physical activity, and sleep, are known to impact health. This study aims toward identifying latent classes of unhealthy lifestyle behavior, exploring the correlations between sociodemographic factors, identifying classes, and further assessing the associations between identified latent classes and all-cause mortality. Methods For this study, the data were obtained from a prospective cohort study in Taiwan. The participants’ self-reported demographic and behavioral characteristics (smoking, physical activity, alcohol consumption, fruit and vegetable intake, and sleep) were used. Latent class analysis was used to identify health-behavior patterns, and Cox proportional hazard regression analysis was used to find the association between the latent class of health-behavior and all-cause mortality. Results A complete dataset was obtained from 290,279 participants with a mean age of 40 (12.4). Seven latent classes were identified, characterized as having a 100% likelihood of at least one unhealthy behavior coupled with the probability of having the other four unhealthy risk behaviors. This study also shows that latent health-behavior classes are associated with mortality, suggesting that they are representative of a healthy lifestyle. Finally, it appeared that multiple risk behaviors were more prevalent in younger men and individuals with low socioeconomic status. Conclusions There was a clear clustering pattern of modifiable risk behaviors among the adults under consideration, where the risk of mortality increased with increases in unhealthy behavior. Our findings can be used to design customized disease prevention programs targeting specific populations and corresponding profiles identified in the latent class analysis.


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