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.
References
[1]
Eaton DK, Kann L, Kinchen S, Shanklin S, Ross J, et al. (2010) Youth risk behavior surveillance - United States, 2009. MMWR Surveill Summ 59: 1–142.
[2]
D'Amico EJ, Ellickson PL, Collins RL, Martino S, Klein DJ (2005) Processes linking adolescent problems to substance-use problems in late young adulthood. Journal of Studies on Alcohol 66: 766–775.
[3]
Hallal PC, Victora CG, Azevedo MR, Wells JCK (2006) Adolescent physical activity and health. Sports Medicine 36: 1019–1030. doi: 10.2165/00007256-200636120-00003
[4]
Basen-Engquist K, Edmundson EW, Parcel GS (1996) Structure of health risk behavior among high school students. Journal of Consulting and Clinical Psychology 64: 764–775. doi: 10.1037/0022-006x.64.4.764
[5]
Lytle LA, Kelder SH, Perry CL, Klepp K-I (1995) Covariance of adolescent health behaviors: the Class of 1989 study. Health Education Research 10: 133–146. doi: 10.1093/her/10.2.133
[6]
Sanchez A, Norman GJ, Sallis JF, Calfas KJ, Cella J, et al. (2007) Patterns and correlates of physical activity and nutrition behaviors in adolescents. American Journal of Preventive Medicine 32: 124–130. doi: 10.1016/j.amepre.2006.10.012
[7]
Prochaska JJ, Spring B, Nigg CR (2008) Multiple health behavior change research: An introduction and overview. Preventive Medicine 46: 181–188. doi: 10.1016/j.ypmed.2008.02.001
[8]
Sallis JF, Prochaska JJ, Taylor WC (2000) A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc 32: 963–975. doi: 10.1097/00005768-200005000-00014
[9]
Pearson R, Turner LW, Young ME, Knickerbocker C (2007) Correlates of healthy eating and physical activity among students in grades 6–12. American Journal of Health Studies 22: 170–178.
[10]
MacArthur GJ, Smith MC, Melotti R, Heron J, Macleod J, et al. (2012) Patterns of alcohol use and multiple risk behaviour by gender during early and late adolescence: the ALSPAC cohort. Journal of Public Health 34: i20–i30. doi: 10.1093/pubmed/fds006
[11]
Nelson MC, Gordon-Larsen P (2006) Physical activity and sedentary behavior patterns are associated with selected adolescent health risk behaviors. Pediatrics 117: 1281–1290. doi: 10.1542/peds.2005-1692
[12]
Carson V, Pickett W, Janssen I (2011) Screen time and risk behaviors in 10- to 16-year-old Canadian youth. Preventive Medicine 52: 99–103. doi: 10.1016/j.ypmed.2010.07.005
[13]
Donovan JE, Jessor R, Costa FM (1991) Adolescent health behavior and conventionality-unconventionality: An extension of problem-behavior therapy. Health Psychology 10: 52–61. doi: 10.1037/0278-6133.10.1.52
[14]
Jessor R and Jessor SL (1977) Problem behavior and psychosocial development: A longitudinal study of youth. New York: Academic Press.
[15]
D'Amico E, Tucker J, Miles JV, Zhou A, Shih R, et al. (2012) Preventing alcohol use with a voluntary after-school program for middle school students: Results from a cluster randomized controlled trial of CHOICE. Prevention Science 13: 415–425. doi: 10.1007/s11121-011-0269-7
[16]
Substance Abuse Mental Health Services Administration (SAMHSA) (2008) Results from the 2007 National Survey on Drug Use and Health.
[17]
Johnson RA, Hoffmann JP (2000) Adolescent cigarette smoking in U.S. racial/ethnic subgroups: Findings from the National Education Longitudinal Study. Journal of Health and Social Behavior 41: 392–407. doi: 10.2307/2676293
[18]
Johnston LD, O'Malley PM, Bachman JG, Schulenberg JE (2009) Monitoring the Future national survey results on drug use, 1975–2008. Volume I: Secondary school students. Bethesda: National Institute on Drug Abuse.
[19]
Kandel DB, Kiros GE, Schaffran C, Hu MC (2004) Racial/ethnic differences in cigarette smoking initiation and progression to daily smoking: A multilevel analysis. American Journal of Public Health 94: 128–135. doi: 10.2105/ajph.94.1.128
[20]
WestEd (2011) California Healthy Kids Survey. Available: http://chks.wested.org/about. Accessed 9 April 2013.
[21]
Bachman JG, O'Malley PM, Johnston LD, Schulenberg JE, Wallace Jr JM (2011) Racial/ethnic differences in the relationship between parental education and substance use among U.S. 8th-, 10th-, and 12th-grade students: Findings from the Monitoring the Future Project. Journal of Studies on Alcohol & Drugs 72: 279–285.
[22]
Little TD (2009) Longitudinal structural equation modeling. New York: Guilford Press.
[23]
Raykov T (2009) Evaluation of scale reliability for unidimensional measures using latent variable modeling. Measurement and Evaluation in Counseling and Development 42: 223–232. doi: 10.1177/0748175609344096
[24]
Raykov T, Dimitrov DM, Asparouhov T (2010) Evaluation of scale reliability with binary measures using latent variable modeling. Structural Equation Modeling: A Multidisciplinary Journal 17: 265–279. doi: 10.1080/10705511003659417
[25]
Efron B, Tibshirani RJ (1994) An introduction to the bootstrap. New York: Chapman & Hall.
[26]
Muthén BO, Muthén L (2011) Mplus 6.11. Los Angeles: Muthen and Muthen.
[27]
Shih RA, Miles JN, Tucker JS, Zhou AJ, D'Amico EJ (2010) Racial/ethnic differences in adolescent substance use: mediation by individual, family, and school factors. Journal of Studies of Alcohol and Drugs 71: 640–651.
[28]
Centers for Disease Control and Prevention (2010) Smoking and tobacco use - Highlights by state.
[29]
Marshall SJ, Biddle SJH, Gorely T, Cameron N, Murdey I (2004) Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis. International Journal of Obesity 28: 1238–1246. doi: 10.1038/sj.ijo.0802706
[30]
Chan D (2008) So why ask me? Are self-report data really that bad? In: Lance CE, Vandenberg RJ, editors. Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences. New York: Psychology Press. pp. 309–336.
[31]
D'Amico EJ, McCarthy DM (2006) Escalation and initiation of younger adolescents' substance use: The impact of perceived peer use. Journal of Adolescent Health 39: 481–487. doi: 10.1016/j.jadohealth.2006.02.010
[32]
Dennis M, Titus JC, Diamond G, Donaldson J, Godley SH, et al. (2002) The Cannabis Youth Treatment (CYT) experiment: Rationale, study design and analysis plans. Addiction 97: 16–34. doi: 10.1046/j.1360-0443.97.s01.2.x
[33]
Shillington AM, Clapp JD (2000) Self-report stability of adolescent substance use: Are there differences for gender, ethnicity and age? Drug and Alcohol Dependence 60: 19–27. doi: 10.1016/s0376-8716(00)80004-6
[34]
Miller WR, Rollnick S (2012) Motivational interviewing: Helping people change. New York: Guilford Press.
