» Articles » PMID: 24858838

Covariance Among Multiple Health Risk Behaviors in Adolescents

Overview
Journal PLoS One
Date 2014 May 27
PMID 24858838
Citations 19
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: In a diverse group of early adolescents, this study explores the co-occurrence of a broad range of health risk behaviors: alcohol, cigarette, and marijuana use; physical inactivity; sedentary computing/gaming; and the consumption of low-nutrient energy-dense food. We tested differences in the associations of unhealthy behaviors over time, and by gender, race/ethnicity, and socioeconomic status.

Methods: Participants were 8360 students from 16 middle schools in California (50% female; 52% Hispanic, 17% Asian, 16% White, and 15% Black/multiethnic/other). Behaviors were measured with surveys in Spring 2010 and Spring 2011. Confirmatory factor analysis was used to assess if an underlying factor accounted for the covariance of multiple behaviors, and composite reliability methods were used to determine the degree to which behaviors were related.

Results: The measured behaviors were explained by two moderately correlated factors: a 'substance use risk factor' and an 'unhealthy eating and sedentary factor'. Physical inactivity did not reflect the latent factors as expected. There were few differences in the associations among these behaviors over time or by demographic characteristics.

Conclusions: Two distinct, yet related groups of health compromising behaviors were identified that could be jointly targeted in multiple health behavior change interventions among early adolescents of diverse backgrounds.

Citing Articles

Analyzing risky behaviors among different minority and majority race in teenagers in the USA using latent classes.

Aslam Z, Asim M, Javaid I, Rasheed F, Akhter M Front Behav Neurosci. 2023; 17:1089434.

PMID: 36865773 PMC: 9971590. DOI: 10.3389/fnbeh.2023.1089434.


Effectiveness of a school-based nutrition education program on waist circumference and dietary behavior among overweight adolescents in Puducherry, India.

Ponnambalam S, Palanisamy S, Singaravelu R, Arambakkam Janardhanan H J Educ Health Promot. 2022; 11:323.

PMID: 36568006 PMC: 9768697. DOI: 10.4103/jehp.jehp_413_22.


Developing Health Lifestyle Pathways and Social Inequalities across Early Childhood.

Mollborn S, Lawrence E, Krueger P Popul Res Policy Rev. 2021; 40(5):1085-1117.

PMID: 34720278 PMC: 8552713. DOI: 10.1007/s11113-020-09615-6.


Contributions and Challenges in Health Lifestyles Research.

Mollborn S, Lawrence E, Saint Onge J J Health Soc Behav. 2021; 62(3):388-403.

PMID: 34528487 PMC: 8792463. DOI: 10.1177/0022146521997813.


A Multiple Health Behavior Change, Self-Monitoring Mobile App for Adolescents: Development and Usability Study of the Health4Life App.

Thornton L, Gardner L, Osman B, Green O, Champion K, Bryant Z JMIR Form Res. 2021; 5(4):e25513.

PMID: 33843590 PMC: 8076990. DOI: 10.2196/25513.


References
1.
Hallal P, Victora C, Azevedo M, Wells J . Adolescent physical activity and health: a systematic review. Sports Med. 2006; 36(12):1019-30. DOI: 10.2165/00007256-200636120-00003. View

2.
Dennis M, Titus J, Diamond G, Donaldson J, Godley S, Tims F . The Cannabis Youth Treatment (CYT) experiment: rationale, study design and analysis plans. Addiction. 2002; 97 Suppl 1:16-34. DOI: 10.1046/j.1360-0443.97.s01.2.x. View

3.
Sallis J, Prochaska J, Taylor W . A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc. 2000; 32(5):963-75. DOI: 10.1097/00005768-200005000-00014. View

4.
Basen-Engquist K, Edmundson E, Parcel G . Structure of health risk behavior among high school students. J Consult Clin Psychol. 1996; 64(4):764-75. DOI: 10.1037//0022-006x.64.4.764. View

5.
Donovan J, JESSOR R, Costa F . Adolescent health behavior and conventionality-unconventionality: an extension of problem-behavior theory. Health Psychol. 1991; 10(1):52-61. View