title: Serum uric acid is associated with dietary and lifestyle factors in elderly women in suburban Guangzhou in Guangdong province of south China.
abstract: OBJECTIVE
  To estimate the prevalence of hyperuricemia and lifestyle risk factors for hyperuricemia in elderly women.
  
  
  METHODS
  Cross-sectional study.
  
  
  METHODS
  The suburban area of Guangzhou, Guangdong province, China.
  
  
  METHODS
  The study included 856 Chinese women aged 60 to 102 years who received their annual health examinations in the suburban area of Guangzhou, south China in 2002.
  
  
  METHODS
  Information on anthropometric measurements and lifestyle factors were obtained via a questionnaire processed by the attending physicians or nurses. Blood biochemistry was performed after subjects fasted for 8-14 h. Unconditional logistic regression analysis was used to investigate associations between hyperuricemia, meat intake quintiles, physical activity quintiles, and alcohol intake quintiles.
  
  
  RESULTS
  The prevalence of hyperuricemia in the studied population was 12.01%. Alcohol, meat and seafood consumption; being overweight or obese; hypertension; and abnormal triglyceride levels were strongly associated with a higher prevalence of hyperuricemia. Physical activity was inversely related to the prevalence of hyperuricemia. The odds ratios for hyperuricemia for quintiles of physical activity were 1.00, 0.74, 0.72, 0.63, and 0.55 (P<0.01).
  
  
  CONCLUSIONS
  Our data suggest that the prevalence of hyperuricemia is high in elderly women in suburban Guangzhou in Guangdong province of South China. Obesity, meat and seafood intake and alcohol consumption are associated with a higher prevalence of hyperuricemia, whereas daily physical activity is inversely related to the prevalence of hyperuricemia.
authors.affiliation: Department of Cardiovascular Diseases, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510630, China.
authors.forename: Z
authors.initials: Z
authors.lastname: Xiong
authors.forename: C
authors.initials: C
authors.lastname: Zhu
authors.forename: X
authors.initials: X
authors.lastname: Qian
authors.forename: J
authors.initials: J
authors.lastname: Zhu
authors.forename: Z
authors.initials: Z
authors.lastname: Wu
authors.forename: L
authors.initials: L
authors.lastname: Chen
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000428:Alcohol Drinking / Q000097:blood / Q000378:metabolism; D000818:Animals; D000886:Anthropometry; D002681:China / Q000453:epidemiology; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000503:physiopathology; D033461:Hyperuricemia / Q000453:epidemiology*; D008019:Life Style; D016015:Logistic Models; D008460:Meat; D008875:Middle Aged; D009043:Motor Activity; D009765:Obesity / Q000150:complications / Q000503:physiopathology; D016017:Odds Ratio; D015995:Prevalence; D012307:Risk Factors; D017747:Seafood / Q000032:analysis; D011795:Surveys and Questionnaires; D014280:Triglycerides / Q000097:blood; D014527:Uric Acid / Q000097:blood*
chemical_list: D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D014280:Triglycerides; D014527:Uric Acid