School of Public Health and Community Medicine, Institute of Medicine, Gothenburg University, Göteborg, Sweden.
Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, United Kingdom.
Front Public Health. 2023 Jul 19;11:1178353. doi: 10.3389/fpubh.2023.1178353. eCollection 2023.
Knowledge of the distribution, prevalence, and clustering of multiple health and lifestyle related behaviors (HLBs) among adolescents can inform the development of effective health-promoting policies and interventions. We assessed the clustering of multiple HLBs among 11, 13 and 15-year-old Swedish adolescents and examined the socioeconomic and demographic correlates for the identified clusters.
We used data from the 2017/2018 Swedish Health Behaviour in School-aged children (HBSC) study to conduct sex and age-stratified latent class analysis (LCA). The LCA was based on five HLBs: eating behavior and habits (EBH), physical activity (PA), tobacco usage (TU), alcohol consumption (AC) and sleeping habits and patterns (SHPs). Multinomial logistic regression models were used to assess the associations between the identified clusters and the socioeconomic and demographic characteristics of adolescents and their parents.
Health behaviors varied by sex and age. Four distinct clusters were identified based on sex: cluster 1 (Mixed eating behaviors and habits, physical activity and low alcohol consumption), cluster 2 (Healthy lifestyle behaviors), cluster 3 (Unhealthy lifestyle behaviors), and cluster 4 (Breakfast, low alcohol consumption and tobacco usage). In the age-stratified analyzes, three clusters were identified: cluster 1 (Unhealthy lifestyle behaviors), cluster 2 (Moderately healthy lifestyle behaviors) and cluster 3 (Healthy lifestyle behaviors). The multinomial analysis showed that sex, age, family situation and perceived family wealth were strong predictors of health behaviors. Unhealthy behaviors were most commonly associated with socioeconomic disadvantage, having a migrant background, and living in reconstructed families or single-parent households.
Health behaviors vary significantly based on socioeconomic and demographic circumstances. Targeted policies and intervention programs are necessary to improve HLBs among vulnerable and at-risk adolescents.
了解青少年多种健康相关行为（HLBs）的分布、流行情况和聚集性，可为制定有效的促进健康政策和干预措施提供信息。本研究评估了瑞典 11、13 和 15 岁青少年多种 HLBs 的聚集情况，并探讨了确定的聚类与社会经济和人口统计学特征之间的相关性。
本研究使用了 2017/2018 年瑞典学生健康行为调查（HBSC）的数据进行分层潜类别分析（LCA）。LCA 基于 5 种 HLBs：饮食行为和习惯（EBH）、身体活动（PA）、烟草使用（TU）、酒精使用（AC）和睡眠习惯和模式（SHPs）。多变量逻辑回归模型用于评估确定的聚类与青少年及其父母的社会经济和人口统计学特征之间的相关性。
不同性别和年龄的健康行为存在差异。根据性别确定了 4 个不同的聚类：聚类 1（混合饮食行为和习惯、身体活动和低酒精消费）、聚类 2（健康生活方式行为）、聚类 3（不健康生活方式行为）和聚类 4（早餐、低酒精消费和烟草使用）。在年龄分层分析中，确定了 3 个聚类：聚类 1（不健康生活方式行为）、聚类 2（中度健康生活方式行为）和聚类 3（健康生活方式行为）。多变量分析表明，性别、年龄、家庭状况和感知家庭财富是健康行为的强有力预测因素。不健康行为最常见于社会经济劣势、移民背景、生活在重建家庭或单亲家庭的青少年中。
健康行为根据社会经济和人口统计学特征存在显著差异。需要有针对性的政策和干预计划来改善弱势和高危青少年的 HLBs。
