ArticleFrontiers in public health2023
The clustering of multiple health and lifestyle behaviors among Swedish adolescents: a person-oriented analysis.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- Effectiveness of the Components of a Digital Multiple Health Behavior Intervention Among University Students (Buddy): Factorial Randomized Trial.Journal of medical Internet research · 2026Trial
- Physical Activity-Sedentary Behaviour Profiles and Co-Occurring Lifestyle Behaviours Among Adolescents: A Person-Oriented Analysis.Nutrients · 2026Article
- Shared Behavioural Determinants of Short Sleep and Obesity From Childhood to Adolescence: An Analyses of Growing Up in Scotland Birth Cohort 1.Pediatric obesity · 2026Observational
- Beyond the Gut: Brain Fog, Sleep Quality, Cognitive Function and Quality of Life in Celiac Disease.Nutrients · 2026Observational
- Social determinants of clusters of health behaviours: a longitudinal cohort study using latent- class analysis.BMC public health · 2026Article
- Hierarchical Analysis of Physical Activity Determinants in Brazilian Adolescents: A Cross-Sectional Study.Sports (Basel, Switzerland) · 2026Article
- Concomitant associations of dietary behaviours and physical activity with body composition in adolescents.BMC public health · 2025Article
- Exploring maternal health, lifestyle, and socioeconomic influences on childhood obesity in Australia.BMC public health · 2025Article
- Non-random aggregations of healthy and unhealthy lifestyles and their population characteristics - pattern recognition in a large population-based cohort.Archives of public health = Archives belges de sante publique · 2025Article
- Association of unhealthy lifestyles and suicidal behaviors among Chinese middle school students: a latent class analysis.BMC psychiatry · 2025Article
- Article
- Dietary Knowledge and Its Associated Factors Among Patients with Diabetes and Hypertension in Tertiary Hospitals in Dodoma, Tanzania: A Cross-sectional Study.The East African health research journal · 2025Article
- Impact of Digital Media, School Problems, and Lifestyle Factors on Youth Psychosomatic Health: A Cross-Sectional Survey.Children (Basel, Switzerland) · 2024Article
- Associations between dietary behaviours and the mental and physical well-being of Swedish adolescents.Child and adolescent psychiatry and mental health · 2024Article
- Sedentary Activities and Food Intake among Children and Adolescents in the Zhejiang Province of China: A Cross-Sectional Study.Nutrients · 2023Article
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4 authors.
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Abstract
Background: 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. Methods: 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. Results: 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. Conclusion: 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.
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