title: Exploring clinical predictors of cardiovascular disease in a central Australian Aboriginal cohort.
abstract: BACKGROUND
  For Aboriginal populations, predicting individuals at risk of cardiovascular disease (CVD) is difficult due to limitations and inaccuracy in existing risk-prediction algorithms. We examined conventional and novel risk factors associated with insulin resistance and the metabolic syndrome and assessed their relationships with subsequent CVD events.
  
  
  METHODS
  Longitudinal cohort.
  
  
  METHODS
  Aboriginal people (n = 739) from Central Australia completed population-based risk-factor surveys in 1995 and were followed up in 2005. Principal components analysis (PCA), regression and univariate analyses (using ROC defined cut-off points) were used to identify useful clinical predictors of primary CVD.
  
  
  RESULTS
  PCA yielded five components: (1) lipids and liver function; (2) insulin resistance; (3) blood pressure and kidney function; (4) glucose tolerance; and (5) anti-inflammatory (low fibrinogen, high HDL cholesterol). Components 2, 3 and 4, and age were significant independent predictors of incident CVD, and smoking approached significance. In univariate analysis fasting glucose ≥ 4.8 mmol/l, total:HDL cholesterol ratio ≥ 5.7, non-HDL cholesterol ≥ 4.3 mmol/l, gamma-glutamyl transferase ≥ 70 U/l, albumin creatinine ratio ≥ 5.7 mg/mmol, systolic blood pressure ≥ 120 mmHg and diastolic blood pressure ≥ 70 mmHg were useful predictors of CVD. The co-occurrence of three or more risk variables (fasting glucose ≥ 4.8 mmol/l, total:HDL cholesterol ratio ≥ 5.7, blood pressure (systolic ≥ 120 mmHg; diastolic ≥ 70 mmHg; albumin:creatinine ratio ≥ 5.7 mg/mmol and smoking) had sensitivity of 82.0% and specificity of 59.9% for predicting incident CVD.
  
  
  CONCLUSIONS
  Age is the strongest predictor of CVD for this population. For clinical identification of individuals at high risk, screening for the combination of three or more of hyperglycaemia, dyslipidaemia, hypertension, albuminuria and smoking may prove a useful and efficient strategy.
authors.affiliation: Onemda VicHealth Koori Health Unit, Centre for Health and Society, School of Population Health, University of Melbourne, Australia. jnluke@unimelb.edu.au
authors.forename: Joanne N
authors.initials: JN
authors.lastname: Luke
authors.forename: Alex D
authors.initials: AD
authors.lastname: Brown
authors.forename: Laima
authors.initials: L
authors.lastname: Brazionis
authors.forename: Kerin
authors.initials: K
authors.lastname: O'Dea
authors.forename: James D
authors.initials: JD
authors.lastname: Best
authors.forename: Robyn A
authors.initials: RA
authors.lastname: McDermott
authors.forename: Zaimin
authors.initials: Z
authors.lastname: Wang
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Wang
authors.forename: Kevin G
authors.initials: KG
authors.lastname: Rowley
mesh_terms: D000328:Adult; D000367:Age Factors; D000419:Albuminuria / Q000175:diagnosis / Q000208:ethnology; D001315:Australia / Q000453:epidemiology; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure; D002318:Cardiovascular Diseases / Q000097:blood / Q000175:diagnosis / Q000208:ethnology* / Q000503:physiopathology; D015897:Comorbidity; D050171:Dyslipidemias / Q000175:diagnosis / Q000208:ethnology; D005260:Female; D006306:Health Surveys; D006801:Humans; D006943:Hyperglycemia / Q000175:diagnosis / Q000208:ethnology; D006973:Hypertension / Q000175:diagnosis / Q000208:ethnology; D018836:Inflammation Mediators / Q000097:blood; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance / Q000208:ethnology; D007668:Kidney / Q000503:physiopathology; D016014:Linear Models; D008055:Lipids / Q000097:blood; D008137:Longitudinal Studies; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis / Q000208:ethnology; D008875:Middle Aged; D016017:Odds Ratio; D015995:Prevalence; D025341:Principal Component Analysis; D018570:Risk Assessment; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects / Q000208:ethnology; D013997:Time Factors; D055815:Young Adult
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D018836:Inflammation Mediators; D007328:Insulin; D008055:Lipids