title: Clustering of risk factors for chronic diseases among adolescents from Southern Brazil.
abstract: OBJECTIVE
  To investigate the clustering of risk behaviors for chronic non-communicable diseases and their associated factors among adolescents from Southern Brazil.
  
  
  METHODS
  In 2008, a survey was conducted with 3990 adolescents aged 14-15 years (mean: 14.3; SD: 0.6) from the 1993 Pelotas Birth Cohort Study. Clustering was determined by comparing observed (O) and expected (E) prevalence of all possible combinations of the four risk factors investigated (smoking, alcohol intake, low fruit intake, and physical inactivity). We carried out Poisson regression to evaluate the effect of individual characteristics on the presence of at least three risk behaviors.
  
  
  RESULTS
  All risk factors tended to cluster together (O/E prevalence=3.0), especially smoking and alcohol intake (odds ratio to present on behavior in the presence of other >5.0). Approximately 15% of adolescents displayed three or more risk behaviors. Females (adjusted OR=1.55), people 15 years and older (OR=1.47), with black skin color (OR=1.23), and of low socioeconomic level (OR=1.29) were more likely to display three or more risk factors.
  
  
  CONCLUSIONS
  These findings suggest that lifestyle-related risk factors tend to cluster among adolescents. Identifying subgroups at greater risk of simultaneously engaging in multiple risk behaviors may aid in the planning of preventive strategies.
authors.affiliation: Department of Population and Health, Federal University of Rio Grande, Rio Grande, Brazil. scdumith@yahoo.com.br
authors.forename: Samuel C
authors.initials: SC
authors.lastname: Dumith
authors.forename: Ludmila C
authors.initials: LC
authors.lastname: Muniz
authors.forename: Rafael M
authors.initials: RM
authors.lastname: Tassitano
authors.forename: Pedro C
authors.initials: PC
authors.lastname: Hallal
authors.forename: Ana M B
authors.initials: AM
authors.lastname: Menezes
mesh_terms: D000293:Adolescent; D000428:Alcohol Drinking / Q000009:adverse effects / Q000453:epidemiology* / Q000523:psychology; D001938:Brazil / Q000453:epidemiology; D016000:Cluster Analysis; D015331:Cohort Studies; D004034:Diet Surveys; D015444:Exercise / Q000502:physiology* / Q000523:psychology; D005247:Feeding Behavior / Q000208:ethnology / Q000523:psychology; D005260:Female; D005500:Follow-Up Studies; D005638:Fruit; D015438:Health Behavior / Q000208:ethnology*; D006306:Health Surveys; D006801:Humans; D008297:Male; D009035:Mothers / Q000193:education; D016012:Poisson Distribution; D015995:Prevalence; D012307:Risk Factors; D040242:Risk Reduction Behavior; D012309:Risk-Taking; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology* / Q000523:psychology; D012923:Social Class