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Clustering of Risk Behaviors and their Social Determinants among Primary School Learners in Beijing, China: A Cross-sectional Study

BACKGROUND: Studies in developed countries reveal that poor lifestyle choices triggering diseases typically cluster among children. However, there is insufficient evidence on the clustering of risk behaviors among children in developing countries. This study aimed to determine the clustering of risk...

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Detalles Bibliográficos
Autores principales: Zhang, Yan, Ji, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4733749/
https://www.ncbi.nlm.nih.gov/pubmed/26063355
http://dx.doi.org/10.4103/0366-6999.158289
Descripción
Sumario:BACKGROUND: Studies in developed countries reveal that poor lifestyle choices triggering diseases typically cluster among children. However, there is insufficient evidence on the clustering of risk behaviors among children in developing countries. This study aimed to determine the clustering of risk behaviors and their social determinants among 4(th)-and 5(th) -grade learners in Beijing, China. METHODS: The sample comprised of 967 learners from six primary schools enrolled migrant and resident learners by two-stage stratified cluster sampling. Prevalence denoted the risk behaviors and their clustering. A log-linear model was used to explore the clustering patterns. Ordinal logistic regression determined the influence of demographic characteristics, school environment, and family context on behavioral clustering. RESULTS: The prevalence of none, one, two, and three or more risk factors was 61.2%, 20.0%, 10.8%, and 8.1% for infectious diseases and 46.0%, 30.6%, 15.4%, and 8.0% for chronic diseases, respectively. Some behaviors appeared dependent and were more likely to be observed together. The three most influential factors for infectious diseases were school type (odds ratio [OR] =4.47, 95% confidence interval [CI] 3.00–6.66), school located in an inner suburb (OR = 0.27, 95% CI 0.18–0.38), and gender (OR = 0.56, 95% CI 0.42–0.74). Regarding risk behaviors for chronic diseases, clustering was not associated with household registration status and number of appliances, but was significantly associated with school type (OR = 5.36, 95% CI 3.72–7.73), school located in an inner suburb (OR = 0.59, 95% CI 0.43–0.81), and gender (OR = 0.61, 95% CI 0.47–0.78). School environment variables were the most significant contributor to the number of risk behaviors. CONCLUSIONS: The characteristics of schools enrolling migrants and residents influenced the number of risk behaviors. Therefore, improved school conditions and integrated behavioral interventions are particularly recommended for health promotion.