title: Association between uric acid and cardiovascular risk variables in a non-hospitalized population.
abstract: BACKGROUND
  The association between uric acid (UA) and cardiovascular risk variables remains a controversial issue in epidemiological studies.
  
  
  OBJECTIVE
  To evaluate the association between UA, blood pressure (BP), anthropometric indices and metabolic variables in a non-hospitalized population stratified by UA quintiles.
  
  
  METHODS
  A cross-sectional observational study evaluated 756 individuals (369 males), aged 50.3 ± 16.12 years, divided in UA quintiles. BP, body mass index (BMI), abdominal circumference (AC), UA, glucose, insulin, HOMA-IR, total cholesterol (TC), LDL-c, HDL-c, triglycerides (TG) and creatinine (C) levels were obtained. The estimated glomerular filtration rate (eGFR) was calculated and arterial hypertension (AH) was considered when BP > 140x90 mmHg, overweight/obesity (OW/O) was considered when BMI > 25 kg/m² and metabolic syndrome (MS) was established according to the I Brazilian Guideline of MS.
  
  
  RESULTS
  1) There was no difference between the groups regarding the distribution by sex and age range; 2) The highest UA quintiles presented higher mean age (p < 0.01), BMI, AC (p < 0.01), SBP, DBP (p < 0.001), TC, LDL-c, TG (p < 0.01), C and eGFR (p < 0.001) and lower mean HDL-c (p < 0.001); 3) The group with the highest UA quintile showed higher prevalence of AH, OW/O and MS (p < 0.001); 4) Higher percentages of the lowest quintiles of insulin (p < 0.02) and HOMA-IR (p < 0.01) were observed with the lowest quintiles of UA; 5) A logistic regression analysis showed that UA and the variables that compose MS were associated with the occurrence of MS (p < 0.01).
  
  
  CONCLUSIONS
  Higher quintiles of uric acid were associated with a worse cardiovascular risk profile and a worse kidney function profile in the non-hospitalized population sample studied.
authors.affiliation: Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
authors.forename: Monica Cristina Campos
authors.initials: MC
authors.lastname: Barbosa
authors.forename: Andréa Araujo
authors.initials: AA
authors.lastname: Brandão
authors.forename: Roberto
authors.initials: R
authors.lastname: Pozzan
authors.forename: Maria Eliane Campos
authors.initials: ME
authors.lastname: Magalhães
authors.forename: Erika Maria Gonçalves
authors.initials: EM
authors.lastname: Campana
authors.forename: Flavia Lopes
authors.initials: FL
authors.lastname: Fonseca
authors.forename: Oswaldo Luiz
authors.initials: OL
authors.lastname: Pizzi
authors.forename: Elizabete Viana de
authors.initials: EV
authors.lastname: Freitas
authors.forename: Ayrton Pires
authors.initials: AP
authors.lastname: Brandão
mesh_terms: D000328:Adult; D000367:Age Factors; D015415:Biomarkers / Q000032:analysis; D001794:Blood Pressure; D015992:Body Mass Index; D001938:Brazil; D002318:Cardiovascular Diseases / Q000209:etiology* / Q000378:metabolism; D003430:Cross-Sectional Studies; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D007668:Kidney / Q000502:physiology; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications*; D008875:Middle Aged; D012307:Risk Factors; D014527:Uric Acid / Q000032:analysis*; D055105:Waist Circumference; D055815:Young Adult
chemical_list: D015415:Biomarkers; D007328:Insulin; D014527:Uric Acid