title: Healthy lifestyles and cardiovascular risk profiles in young Australian adults: the Childhood Determinants of Adult Health Study.
abstract: BACKGROUND
  We examined whether a healthy lifestyle was associated with cardiovascular risk factors in a cohort of young adults.
  
  
  METHODS
  Cross-sectional.
  
  
  METHODS
  Data from the 2004-2006 Childhood Determinants of Adult Health Study (age range 25-36 years) were used. A lifestyle score [0 (unhealthy) to 8 (healthy)] was derived from eight behaviours (normal body mass index, nonsmoking, low alcohol, salt, meat and regular fish consumption, leisure time physical activity and skim milk use). Using linear regression to adjust sociodemographic characteristics, we examined relationships between the lifestyle score and blood pressure (BP), low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol, triglycerides, insulin, glucose and an estimate of insulin resistance (IR).
  
  
  RESULTS
  In men (n = 863), after adjustment, higher lifestyle scores were linearly associated with lower diastolic BP [regression coefficient (beta): -0.83; 95% confidence interval (CI): -1.23 to -0.43], LDL cholesterol (beta: -0.05; 95% CI: -0.09 to -0.007), HDL cholesterol (beta: 0.01; 95% CI: 0.001-0.003), insulin (beta: -0.50; 95% CI: -0.75 to -0.25) and IR (beta: -0.10; 95% CI: -0.16 to -0.04). In women (n = 941), after adjustment, healthy lifestyles were linearly associated with HDL cholesterol (beta: 0.02; 95% CI: 0.01 to 0.04) and glucose (beta: -0.02; 95% CI: -0.04 to -0.003). There were significant nonlinear associations of the lifestyle score with triglycerides in males and with diastolic BP, LDL cholesterol, triglycerides, insulin and IR in females.
  
  
  CONCLUSIONS
  Even in young adults, a healthy lifestyle is clearly associated with a better cardiovascular risk profile.
authors.affiliation: Menzies Research Institute, University of Tasmania, Hobart, Tasmania, Australia. Seana.Gall@utas.edu.au
authors.forename: Seana L
authors.initials: SL
authors.lastname: Gall
authors.forename: Konrad
authors.initials: K
authors.lastname: Jamrozik
authors.forename: Leigh
authors.initials: L
authors.lastname: Blizzard
authors.forename: Terry
authors.initials: T
authors.lastname: Dwyer
authors.forename: Alison
authors.initials: A
authors.lastname: Venn
mesh_terms: D000328:Adult; D000367:Age Factors; D000428:Alcohol Drinking / Q000009:adverse effects; D001315:Australia; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000097:blood / Q000209:etiology* / Q000503:physiopathology / Q000517:prevention & control*; D003430:Cross-Sectional Studies; D004032:Diet / Q000009:adverse effects; D015444:Exercise; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D008019:Life Style; D016014:Linear Models; D008055:Lipids / Q000097:blood; D008297:Male; D016017:Odds Ratio; D018570:Risk Assessment; D012307:Risk Factors; D040242:Risk Reduction Behavior; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D007328:Insulin; D008055:Lipids