High-normal albuminuria predicts metabolic syndrome in middle-aged Korean men: a prospective cohort study

Maturitas. 2014 Feb;77(2):149-54. doi: 10.1016/j.maturitas.2013.10.013. Epub 2013 Nov 1.

Abstract

Objective: High-normal albuminuria has recently been associated with an elevated risk of cardiovascular disease. However, it is uncertain whether high-normal albuminuria is associated with metabolic syndrome (MetS). The objective of this prospective cohort study was to investigate whether a temporal relationship exists between a high-normal urine albumin-to-creatinine ratio (UACR) and the development of MetS.

Study design: A total of 4338 healthy Korean men who had their UACRs and MetS components assessed in 2005 were enrolled in the study. A MetS-free cohort of 1364 individuals, who did not have any conditions that would have excluded them from the study, was followed up until 2010.

Main outcome measure: MetS was defined according to the joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention.

Results: Cox proportional hazards models were used to estimate the hazard ratio (HR) associated with normal UACR values stratified into following tertiles: <3.12 μg/mg, ≥3.12, <4.87 μg/mg, and ≥4.87 μg/mg. The UACR was categorised into the following tertiles. During 4470.6 person-years of follow-up, 247 incident cases of MetS developed between 2006 and 2010. The third UACR tertile was associated with the development of MetS after adjusting for multiple baseline covariates (HR 1.57; 95% confidence interval: 1.14-2.18).

Conclusions: On the basis of our 5-year follow-up study, a high-normal UACR predicts the development of MetS in Korean men.

Keywords: Albuminuria; Cohort studies; Metabolic syndrome; Urine albumin creatinine ratio.

MeSH terms

  • Adult
  • Aged
  • Albuminuria / complications*
  • Biomarkers / urine
  • Humans
  • Male
  • Metabolic Syndrome / complications
  • Metabolic Syndrome / urine*
  • Middle Aged
  • Prospective Studies
  • Republic of Korea

Substances

  • Biomarkers