Unhealthy lifestyles and clusters status among 3637 adolescents aged 11-23 years: a school-based cross-sectional study in China

Abstract

Background: Unhealthy lifestyles are risk factors for non-communicable diseases (NCDs) and tend to be clustered, with a trajectory that extends from adolescence to adulthood. This study investigated the association of diets, tobacco, alcohol, physical activity (PA), screen time (ST) and sleep duration (SD) in a total of six lifestyles, separately and as cumulative lifestyle scores, with sociodemographic characteristics among school-aged adolescents in the Chinese city of Zhengzhou.

Methods: In the aggregate, 3,637 adolescents aged 11-23 years were included in the study. The questionnaire collected data on socio-demographic characteristics and lifestyles. Healthy and unhealthy lifestyles were identified and scored, depending on the individual score (0 and 1 for healthy and unhealthy lifestyles respectively), with a total score between 0 and 6. Based on the sum of the dichotomous scores, the number of unhealthy lifestyles was calculated and divided into three clusters (0-1, 2-3, 4-6). Chi-square test was used to analyze the group difference of lifestyles and demographic characteristics, and multivariate logistic regression was used to explore the associations between demographic characteristics and the clustering status of unhealthy lifestyles.

Results: Among all participants, the prevalence of unhealthy lifestyles was: 86.4% for diet, 14.5% for alcohol, 6.0% for tobacco, 72.2% for PA, 42.3% for ST and 63.9% for SD. Students who were in university, female, lived in country (OR = 1.725, 95% CI: 1.241-2.398), had low number of close friends (1-2: OR = 2.110, 95% CI: 1.428-3.117; 3-5: OR = 1.601, 95% CI: 1.168-2.195), and had moderate family income (OR = 1.771, 95% CI: 1.208-2.596) were more likely to develop unhealthy lifestyles. In total, unhealthy lifestyles remain highly prevalent among Chinese adolescents.

Conclusion: In the future, the establishment of an effective public health policy may improve the lifestyle profile of adolescents. Based on the lifestyle characteristics of different populations reported in our findings, lifestyle optimization can be more efficiently integrated into the daily lives of adolescents. Moreover, it is essential to conduct well-designed prospective studies on adolescents.

Keywords: Adolescent; Cluster; Life style.

Fig. 1

Six categories of lifestyles among participants (N = 3637). Figure 1 shows the proportion of healthy and unhealthy counts by sociodemographic characteristics in each lifestyle. Association of socio-demographic characteristics with proportion of dietary behavior (Fig. 1A), alcohol behavior (Fig. 1B), tobacco behavior (Fig. 1C), PA behavior (Fig. 1D), ST behavior (Fig. 1E) and SD behavior (Fig. 1F). Unhealthy dietary behavior: Diet quality score of 4 and above; Unhealthy alcohol behavior: Drank at least one glass of wine in the last month; Unhealthy tobacco behavior: Smoked at least one day in the last month; Unhealthy PA behavior: PARS-3 scores between 0 and 19; Unhealthy ST behavior: Daily average ST > 2 h in the last month; Unhealthy SD behavior: Sleep deprivation in the last week (less than 9 h/d for middle school students, less than 8 h/d for high school and vocational high school students, less than 7 h/d for university students). Abbreviations: PA, physical activity; PARS-3, physical activity rating scale-3; ST, screen time; SD, sleep duration