scholarly journals Latent Class Analysis of Adolescent Health Behaviors

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Molly Jacobs
Author(s):  
Simone Pettigrew ◽  
Liyuwork M. Dana ◽  
Alison McAleese ◽  
Alice Bastable ◽  
Catherine Drane ◽  
...  

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 425 ◽  
Author(s):  
Melinda J. Hutchesson ◽  
Mitch J. Duncan ◽  
Stina Oftedal ◽  
Lee M. Ashton ◽  
Christopher Oldmeadow ◽  
...  

University students have high rates of health risk behaviors and psychological distress. This study explores patterns of health behaviors among a sample of Australian university students, and determines whether patterns of health behaviors are associated with psychological distress and demographic characteristics. Cross-sectional data from the University of Newcastle Student Healthy Lifestyle Survey 2019 were analyzed. Fruit and vegetable intake, sugar-sweetened beverage intake, physical activity, sitting time, smoking, alcohol intake, drug use, sleep and psychological distress were assessed. Latent class analysis (LCA) was used to identify patterns of health risk behaviors, and latent class regression to explore associations between psychological distress and demographic characteristics with health behavior classes. Analysis included 1965 students (mean age 25.8 ± 8.6 years, 70.7% female). Three patterns of health behaviors were identified: healthier (48.6%), moderate (40.2%) and unhealthy (11.2%) lifestyle classes. Students in the moderate and unhealthy lifestyle classes had higher odds of moderate (OR 1.43 and 2.37) and high/very high psychological distress risk (OR 2.71 and 11.69). Students in the unhealthy and moderate lifestyle classes had a higher odds of being male, younger, enrolled in transition to university and English language courses, Aboriginal or Torres Strait Islander descent and to report some financial difficulty. Study findings may be used to inform the design of mental health interventions for university students that target key health risk behaviors.


2013 ◽  
Vol 49 (11) ◽  
pp. 935-941 ◽  
Author(s):  
Hannah Noel ◽  
Simon Denny ◽  
Bridget Farrant ◽  
Fiona Rossen ◽  
Tasileta Teevale ◽  
...  

2020 ◽  
Author(s):  
Li Zhang ◽  
Xiangyang Bi ◽  
Zhihong Ding

Abstract BackgroundA strong association between individual health behaviors and health outcomes has been emphasized by previous analyses. However, how individual health behaviors can be classified into health lifestyles and the manner in which health lifestyles have impacted Chinese oldest-old’s health status are largely unknown.MethodsAnalyzing the 2014 Chinese Longitudinal Healthy Longevity Survey (CLHLS), latent class analysis was applied to identify predominant health lifestyles among Chinese oldest-old aged 85 to 105.ResultsFour distinct classes representing health lifestyles emerged. Health lifestyles were found to be strongly associated with Chinese oldest-old’s health outcomes which were measured by self-rated health, functional independence, cognitive function and chronic diseases, even after controlling for demographic features as well as individual and parental socioeconomic disadvantage. Findings also showed a convergence of health disparities caused by demographic and SES characteristics in very old age.ConclusionsChinese oldest-old showed four predominant health lifestyles with only 21.9% of the sample had consistently healthy lifestyle behaviors. The significant influence of health lifestyles on health remained after age 85, .highlighting the importance of promoting health lifestyles to advance the oldest-old’s health status.


2014 ◽  
Vol 41 (6) ◽  
pp. 663-672 ◽  
Author(s):  
Charu Mathur ◽  
Melissa Stigler ◽  
Katherine Lust ◽  
Melissa Laska

Little is known about the complex patterning of weight-related health behaviors in 2- and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college students. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health behaviors that represent multiple theoretically/clinically relevant dimensions of obesity risk among 2- versus 4-year college students using cross-sectional statewide surveillance data ( N = 17,584). Additionally, differences in class membership on selected sociodemographic characteristics were examined using a model-based approach. Analysis was conducted separately for both college groups, and five and four classes were identified for 2- and 4-year college students, respectively. Four classes were similar across 2- and 4-year college groups and were characterized as “mostly healthy dietary habits, active”; “moderately high screen time, active”; “moderately healthy dietary habits, inactive”; and “moderately high screen time, inactive.” “Moderately healthy dietary habits, high screen time” was the additional class unique to 2-year college students. These classes differed on a number of sociodemographic characteristics, including the proportion in each class who were classified as obese. Implications for prevention scientists and future intervention programs are considered.


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