» Articles » PMID: 31574957

Association Between Health Literacy and Subgroups of Health Risk Behaviors Among Chinese Adolescents in Six Cities: A Study Using Regression Mixture Modeling

Overview
Publisher MDPI
Date 2019 Oct 3
PMID 31574957
Citations 10
Authors
Affiliations
Soon will be listed here.
Abstract

Adolescents engage in health risk behaviors (HRBs) that influence their current and future health status. Health literacy (HL) is defined as how well a person can get and understand the health information and services, and use them to make good health decisions. HL can be used to participate in everyday activities actively and apply new information to the changing circumstances. HRBs commonly co-occur in adolescence, and few researchers have examined how HL predicts multiple HRBs in adolescence. In this study we examined the subgroups of HRBs, and investigated heterogeneity in the effects of HL on the subgroups. In total, 22,628 middle school students (10,990 males and 11,638 females) in six cities were enrolled by multistage stratified cluster sampling from November 2015 to January 2016. The measurement of HL was based on the Chinese Adolescent Interactive Health Literacy Questionnaire (CAIHLQ). Analyses were conducted with regression mixture modeling approach (RMM) by Mplus. By this study we found four latent classes among Chinese adolescents: Low-risk class, moderate-risk class 1 (smoking/alcohol use (AU)/screen time (ST)), moderate-risk class 2 (non-suicidal self-injury (NSSI)/suicidal behaviors (SB)/unintentional injury (UI)), and high-risk class (smoking/AU/ST/NSSI/SB/UI) which were 64.0%, 4.5%, 28.8% and 2.7% of involved students, respectively. Negative correlations were found between HL and HRBs: higher HL accompanied decreased HBRs. Compared to the low-risk class, moderate-risk class 1 (smoking/AU/ST), moderate-risk class 2 (NSSI/SB/UI), and high-risk class (smoking/AU/ST/NSSI/SB/UI) showed OR (95%CI) values of 0.990 (0.982-0.998), 0.981 (0.979-0.983) and 0.965 (0.959-0.970), respectively. Moreover, there was heterogeneity in the profiles of HRBs and HL in different classes. It is important for practitioners to examine HRBs in multiple domains concurrently rather than individually in isolation. Interventions and research should not only target adolescents engaging in high levels of risky behavior but also adolescents who are engaging in lower levels of risky behavior.

Citing Articles

Behavioral correlates of health literacy among university students of health sciences in Kosovo: a cross-sectional study.

Jerliu N, Kamberi H, Mone I, Krasniqi P, Burazeri G Croat Med J. 2025; 65(6):493-500.

PMID: 39812098 PMC: 11748448.


Exploring the Association Between Adolescents' Health Literacy and Health Behavior by Using the Short Health Literacy (HLS-Q12) Questionnaire.

Sukys S, Kuzmarskiene G, Motiejunaite K Healthcare (Basel). 2025; 12(24.

PMID: 39766012 PMC: 11728227. DOI: 10.3390/healthcare12242585.


The relationship between cumulative ecological risk and health risk behaviors among Chinese adolescents.

Wang J, Xie Y, Zhang Y, Xu H, Zhang X, Wan Y BMC Public Health. 2024; 24(1):603.

PMID: 38403637 PMC: 10895731. DOI: 10.1186/s12889-024-17934-y.


The impact of mental health literacy intervention on in-service teachers' knowledge attitude and self-efficacy.

Bichoualne A, Oubibi M, Rong Y Glob Ment Health (Camb). 2024; 10:e88.

PMID: 38161751 PMC: 10755373. DOI: 10.1017/gmh.2023.77.


Factors related with nursing students' health literacy: a cross sectional study.

Ramon-Arbues E, Granada-Lopez J, Anton-Solanas I, Cobos-Rincon A, Rodriguez-Calvo A, Gea-Caballero V Front Public Health. 2023; 11:1053016.

PMID: 37275493 PMC: 10234423. DOI: 10.3389/fpubh.2023.1053016.


References
1.
Hamza C, Stewart S, Willoughby T . Examining the link between nonsuicidal self-injury and suicidal behavior: a review of the literature and an integrated model. Clin Psychol Rev. 2012; 32(6):482-95. DOI: 10.1016/j.cpr.2012.05.003. View

2.
Manganello J . Health literacy and adolescents: a framework and agenda for future research. Health Educ Res. 2007; 23(5):840-7. DOI: 10.1093/her/cym069. View

3.
Pasch K, Nelson M, Lytle L, Moe S, Perry C . Adoption of risk-related factors through early adolescence: associations with weight status and implications for causal mechanisms. J Adolesc Health. 2008; 43(4):387-93. PMC: 2577596. DOI: 10.1016/j.jadohealth.2008.02.009. View

4.
Loef M, Walach H . The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis. Prev Med. 2012; 55(3):163-70. DOI: 10.1016/j.ypmed.2012.06.017. View

5.
Reyna V, Farley F . Risk and Rationality in Adolescent Decision Making: Implications for Theory, Practice, and Public Policy. Psychol Sci Public Interest. 2015; 7(1):1-44. DOI: 10.1111/j.1529-1006.2006.00026.x. View