Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015)

Matias, Thiago Sousa, Silva, Kelly Samara, Silva, Jaqueline Aragoni da, Mello, Gabrielli Thais de and Salmon, Jo 2018, Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015), BMC public health, vol. 18, pp. 1-9, doi: 10.1186/s12889-018-6203-1.

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Title Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015)
Author(s) Matias, Thiago Sousa
Silva, Kelly Samara
Silva, Jaqueline Aragoni da
Mello, Gabrielli Thais de
Salmon, JoORCID iD for Salmon, Jo orcid.org/0000-0002-4734-6354
Journal name BMC public health
Volume number 18
Article ID 1283
Start page 1
End page 9
Total pages 9
Publisher BioMed Central
Place of publication London, Eng.
Publication date 2018-11-21
ISSN 1471-2458
Keyword(s) cluster analysis
diet
adolescent
sedentary lifestyle
exercise
adolescent behavior
Brazil
health behavior
science & technology
life sciences & biomedicine
public, environmental & occupational health
Summary BACKGROUND: There is a lack of evidence regarding clusters of health-related behaviors among adolescents from low, lower-middle, and upper-middle income countries. This study aimed to identify clustering patterns of health-related behaviors (diet, physical activity [PA] and sedentary behavior [SB]) and association with sociodemographic variables among a population-based sample of Brazilian adolescents. METHODS: Cross-sectional data from the 2015 National School-Based Health Survey (PeNSE). A total of 102,072 (females: 51.7%) students in ninth-grade (age: 14.3 ± 1.1 years-old) enrolled in public and private schools were investigated in this study. Healthy and unhealthy diet, PA and SB were measured using a validated questionnaire. Two-step cluster analysis was conducted to identify lifestyle patterns. The methodology for complex analysis and weighting was used to inferential statistical procedures. Multinomial logistic regression assessed associations between sociodemographic factors and the clusters. RESULTS: Three reliable and meaningful clusters were identified and labelled as follows: (1) health-promoting SB and diet (32.6%); (2) health-promoting PA and diet (44.9%), and (3) health-risk (22.5%). Compared to boys, girls were less likely to be in clusters 1 (OR = 0.85; 95% CI = 0.78-0.93, p < 0.001) and 2 (OR = 0.43; 95% CI = 0.40-0.46, p < 0.001) than the health-risk cluster. Higher socioeconomic status was positively associated with health-promoting PA and diet, and negatively related to health-promoting SB and diet. Older adolescents were more likely to be in cluster 1 than in cluster 3, compared to younger adolescents. CONCLUSION: Approximately one-quarter of the population (health-risk cluster) reported engaging in multiple risk behaviors. Interventions may need to be tailored to specific adolescent groups, especially considering sociodemographic differences.
Language eng
DOI 10.1186/s12889-018-6203-1
Field of Research 1117 Public Health And Health Services
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30115962

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