title: Does chronic kidney disease modify the association between body mass index and cardiovascular disease risk factors.
abstract: BACKGROUND
  Excess weight is paradoxically associated with better cardiovascular disease (CVD) outcomes and mortality in end-stage renal disease (ESRD) patients treated with hemodialysis. This association has been observed in chronic kidney disease (CKD) as well. One potential explanation for this inverse relationship is that the usual positive correlation between severity of CVD risk factors and higher body mass index (BMI) is reversed in CKD. To test this hypothesis, we determined the relationship between BMI and CVD risk factors in patients with and without CKD.
  
  
  METHODS
  This was a cross-sectional study of the nationally representative US National Health and Nutrition Examination Survey (NHANES) 1999-2006. CKD was defined as glomerular filtration rate <60 ml/min per 1.73 m2. Covariates were age, race/ethnicity, sex and use of relevant prescription medications. Outcome variables were total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, systolic blood pressure (SBP), diastolic blood pressure (DBP), C-reactive protein (CRP) and fasting glucose (FG).
  
  
  RESULTS
  There were 1,895 and 32,431 patients with and without CKD, respectively. Those with CKD were older and had higher BMI. The shapes of the association between BMI and total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, SBP, CRP and FG were similar in those with or without CKD. In a sensitivity analysis excluding patients taking relevant prescription medications, our results did not differ substantially.
  
  
  CONCLUSIONS
  CKD did not alter the shapes of the association between higher BMI and CVD risk factors. Inverse associations between BMI and CVD risk factors are unlikely to explain why CKD patients with higher BMI may have better outcomes.
authors: Department of Medicine, University of California, San Francisco, California 94143, USA. nisha.bansal@ucsf.edu
authors: Nisha
authors: N
authors: Bansal
authors: Eric
authors: E
authors: Vittinghoff
authors: Laura
authors: L
authors: Plantinga
authors: Chi-Yuan
authors: CY
authors: Hsu
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D015992:Body Mass Index; D002097:C-Reactive Protein / Q000032:analysis; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000503:physiopathology; D002908:Chronic Disease; D003430:Cross-Sectional Studies; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D016014:Linear Models; D008055:Lipids / Q000097:blood; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D009749:Nutrition Surveys; D009765:Obesity / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D018570:Risk Assessment; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D008055:Lipids; D002097:C-Reactive Protein