title: Association between insulin resistance and development of microalbuminuria in type 2 diabetes: a prospective cohort study.
abstract: OBJECTIVE
  An association between insulin resistance and microalbuminuria in type 2 diabetes has often been found in cross-sectional studies. We aimed to reassess this relationship in a prospective Taiwanese cohort of type 2 diabetic subjects.
  
  
  METHODS
  We enrolled 738 normoalbuminuric type 2 diabetic subjects, aged 56.6 ± 9.0 years, between 2003 and 2005 and followed them through the end of 2009. Average follow-up time was 5.2 ± 0.8 years. We used urine albumin-to-creatinine ratio to define microalbuminuria and the homeostasis model assessment of insulin resistance (HOMA-IR) to assess insulin resistance. The incidence rate ratio and Cox proportional hazards model were used to evaluate the association between HOMA-IR and development of microalbuminuria.
  
  
  RESULTS
  We found incidences of microalbuminuria of 64.8, 83.5, 93.3, and 99.0 per 1,000 person-years for the lowest to highest quartiles of HOMA-IR. Compared with those in the lowest quartile of HOMA-IR, the incidence rate ratios for those in the 2nd, 3rd, and highest quartiles were 1.28 (95% CI 0.88-1.87), 1.44 (0.99-2.08), and 1.52 (1.06-2.20), respectively (trend test: P < 0.001). By comparison with those in the lowest quartile, the adjusted hazard ratios were 1.37 (0.93-2.02), 1.66 (1.12-2.47), and 1.76 (1.20-2.59) for those in the 2nd, 3rd, and highest HOMA-IR quartiles, respectively.
  
  
  CONCLUSIONS
  According to the dose-response effects of HOMA-IR shown in this prospective study, we conclude that insulin resistance could significantly predict development of microalbuminuria in type 2 diabetic patients.
authors.affiliation: Division of Health Policy Research and Development, Institute of Population Health Sciences, National Health Research Institutes, Taiwan.
authors.forename: Chih-Cheng
authors.initials: CC
authors.lastname: Hsu
authors.forename: Hsing-Yi
authors.initials: HY
authors.lastname: Chang
authors.forename: Meng-Chuan
authors.initials: MC
authors.lastname: Huang
authors.forename: Shang-Jyh
authors.initials: SJ
authors.lastname: Hwang
authors.forename: Yi-Ching
authors.initials: YC
authors.lastname: Yang
authors.forename: Tong-Yuan
authors.initials: TY
authors.lastname: Tai
authors.forename: Hung-Jen
authors.initials: HJ
authors.lastname: Yang
authors.forename: Chwen-Tzuei
authors.initials: CT
authors.lastname: Chang
authors.forename: Chih-Jen
authors.initials: CJ
authors.lastname: Chang
authors.forename: Yu-Sheng
authors.initials: YS
authors.lastname: Li
authors.forename: Shyi-Jang
authors.initials: SJ
authors.lastname: Shin
authors.forename: Ken N
authors.initials: KN
authors.lastname: Kuo
mesh_terms: D000368:Aged; D000418:Albumins / Q000032:analysis; D000419:Albuminuria / Q000097:blood / Q000175:diagnosis* / Q000652:urine; D001786:Blood Glucose / Q000378:metabolism; D003404:Creatinine / Q000652:urine; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000503:physiopathology* / Q000652:urine*; D005215:Fasting / Q000097:blood; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007333:Insulin Resistance; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011446:Prospective Studies
chemical_list: D000418:Albumins; D001786:Blood Glucose; D003404:Creatinine; D006442:Glycated Hemoglobin