BACKGROUND: Predictors for incident albuminuria are not well known in population-based cohorts. The purpose of this study is to identify predictors of incident albuminuria in an unselected middle-aged population. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: Framingham Offspring Study participants who attended both the sixth (baseline; 1995-1998) and eighth (2005-2008) examination cycles. PREDICTORS: Standard clinical predictors were used. Predictors of incident albuminuria were identified using stepwise logistic regression analysis with age and sex forced into the model. OUTCOMES & MEASUREMENTS: Albuminuria was defined as urine albumin-creatinine ratio (UACR) ≥ 17 mg/g (men) or ≥ 25 mg/g (women). Individuals with albuminuria at baseline were excluded. RESULTS: 1,916 participants were available for analysis (mean age, 56 years; 54% women). Albuminuria developed in 10.0% of participants (n = 192) during 9.5 years. Age (OR, 2.09; P < 0.001), baseline diabetes (OR, 1.93; P = 0.01), smoking (OR, 2.09; P < 0.001), and baseline log UACR (OR per 1-SD increase in log UACR, 1.56; P < 0.001) were associated with incident albuminuria in a stepwise model. An inverse relationship with female sex (OR, 0.53; P < 0.001) and high-density lipoprotein (HDL) cholesterol level (OR, 0.80; P = 0.007) also was observed. Results were similar when participants with baseline chronic kidney disease (n = 102), defined as estimated glomerular filtration rate <60 mL/min/1.73 m(2), were excluded from the model. Age, male sex, low HDL cholesterol level, smoking, and log UACR continued to be associated with incident albuminuria when baseline diabetes (n = 107) was excluded. Age, male sex, and log UACR correlated with incident albuminuria after participants with baseline hypertension were excluded (n = 651). LIMITATIONS: Causality may not be inferred because of the observational nature of the study. One-third of participants did not return for follow-up, potentially attenuating the observed risks of albuminuria. CONCLUSIONS: The known cardiovascular risk factors of increasing age, male sex, diabetes, smoking, low HDL cholesterol level, and albuminuria within the reference range are correlates of incident albuminuria in the general population. Published by Elsevier Inc.
BACKGROUND: Predictors for incident albuminuria are not well known in population-based cohorts. The purpose of this study is to identify predictors of incident albuminuria in an unselected middle-aged population. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: Framingham Offspring Study participants who attended both the sixth (baseline; 1995-1998) and eighth (2005-2008) examination cycles. PREDICTORS: Standard clinical predictors were used. Predictors of incident albuminuria were identified using stepwise logistic regression analysis with age and sex forced into the model. OUTCOMES & MEASUREMENTS: Albuminuria was defined as urine albumin-creatinine ratio (UACR) ≥ 17 mg/g (men) or ≥ 25 mg/g (women). Individuals with albuminuria at baseline were excluded. RESULTS: 1,916 participants were available for analysis (mean age, 56 years; 54% women). Albuminuria developed in 10.0% of participants (n = 192) during 9.5 years. Age (OR, 2.09; P < 0.001), baseline diabetes (OR, 1.93; P = 0.01), smoking (OR, 2.09; P < 0.001), and baseline log UACR (OR per 1-SD increase in log UACR, 1.56; P < 0.001) were associated with incident albuminuria in a stepwise model. An inverse relationship with female sex (OR, 0.53; P < 0.001) and high-density lipoprotein (HDL) cholesterol level (OR, 0.80; P = 0.007) also was observed. Results were similar when participants with baseline chronic kidney disease (n = 102), defined as estimated glomerular filtration rate <60 mL/min/1.73 m(2), were excluded from the model. Age, male sex, low HDL cholesterol level, smoking, and log UACR continued to be associated with incident albuminuria when baseline diabetes (n = 107) was excluded. Age, male sex, and log UACR correlated with incident albuminuria after participants with baseline hypertension were excluded (n = 651). LIMITATIONS: Causality may not be inferred because of the observational nature of the study. One-third of participants did not return for follow-up, potentially attenuating the observed risks of albuminuria. CONCLUSIONS: The known cardiovascular risk factors of increasing age, male sex, diabetes, smoking, low HDL cholesterol level, and albuminuria within the reference range are correlates of incident albuminuria in the general population. Published by Elsevier Inc.
Authors: Auke H Brantsma; Stephan J L Bakker; Hans L Hillege; Dick de Zeeuw; Paul E de Jong; Ronald T Gansevoort Journal: Diabetes Care Date: 2005-10 Impact factor: 19.112
Authors: Jose Maria Pascual; Enrique Rodilla; Carmen Gonzalez; Santiago Pérez-Hoyos; Josep Redon Journal: Hypertension Date: 2005-05-16 Impact factor: 10.190
Authors: Folkert W Asselbergs; Gilles F H Diercks; Hans L Hillege; Ad J van Boven; Wilbert M T Janssen; Adriaan A Voors; Dick de Zeeuw; Paul E de Jong; Dirk J van Veldhuisen; Wiek H van Gilst Journal: Circulation Date: 2004-10-18 Impact factor: 29.690
Authors: D E Weiner; M A Carpenter; A S Levey; A Ivanova; E H Cole; L Hunsicker; B L Kasiske; S J Kim; J W Kusek; A G Bostom Journal: Am J Transplant Date: 2012-05-17 Impact factor: 8.086
Authors: Gearoid M McMahon; Conall M O'Seaghdha; Shih-Jen Hwang; James B Meigs; Caroline S Fox Journal: Nephrol Dial Transplant Date: 2013-09-19 Impact factor: 5.992
Authors: William M McClellan; David G Warnock; Suzanne Judd; Paul Muntner; Reshma Kewalramani; Mary Cushman; Leslie A McClure; Britt B Newsome; George Howard Journal: J Am Soc Nephrol Date: 2011-08-25 Impact factor: 10.121
Authors: Laura Y Zheng; Jason G Umans; Maria Tellez-Plaza; Fawn Yeh; Kevin A Francesconi; Walter Goessler; Ellen K Silbergeld; Eliseo Guallar; Barbara V Howard; Virginia M Weaver; Ana Navas-Acien Journal: Am J Kidney Dis Date: 2012-11-09 Impact factor: 8.860
Authors: Rozh H Al-Mashhadi; Martin M Bjørklund; Martin B Mortensen; Christina Christoffersen; Torben Larsen; Erling Falk; Jacob F Bentzon Journal: Diabetologia Date: 2015-05-31 Impact factor: 10.122
Authors: Daniel A Roseman; Shih-Jen Hwang; Emily S Manders; Christopher J O'Donnell; Ashish Upadhyay; Udo Hoffmann; Caroline S Fox Journal: Am J Cardiol Date: 2013-10-04 Impact factor: 2.778
Authors: Jennifer E Ho; Shih-Jen Hwang; Kai C Wollert; Martin G Larson; Susan Cheng; Tibor Kempf; Ramachandran S Vasan; James L Januzzi; Thomas J Wang; Caroline S Fox Journal: Clin Chem Date: 2013-07-19 Impact factor: 8.327