title: Metabolically healthy obesity and risk of incident CKD.
abstract: OBJECTIVE
  Metabolically healthy obesity (MHO) is a unique obesity phenotype that apparently protects people from the metabolic complications of obesity. The association between MHO phenotype and incident CKD is unclear. Thus, this study investigated the association between MHO phenotype and incident CKD.
  
  
  METHODS
  A total of 3136 Japanese participants were enrolled in an 8-year follow-up cohort study in 2001. Metabolically healthy status was assessed by common clinical markers: BP, triglycerides, HDL cholesterol, and fasting plasma glucose concentrations. Body mass index ≥25.0 kg/m(2) was defined as obesity. CKD was defined by proteinuria or eGFR of <60 ml/min per 1.73 m(2). To calculate the odds ratio for incident CKD, logistic regression analyses were performed.
  
  
  RESULTS
  The crude incidence proportions of CKD were 2.6% (56 of 2122 participants) in participants with the metabolically healthy nonobesity phenotype, 2.6% (8 of 302) in those with the MHO phenotype, 6.7% (30 of 445) in those with the metabolically abnormal nonobesity phenotype, and 10.9% (29 of 267) in those with the metabolically abnormal obesity phenotype. Compared with metabolically healthy nonobesity phenotype, the odds ratios for incident CKD were 0.83 (95% confidence interval [95% CI], 0.36 to 1.72; P=0.64) for MHO, 1.44 (95% CI, 0.80 to 2.57; P=0.22) for metabolically abnormal nonobesity, and 2.80 (95% CI, 1.45 to 5.35; P=0.02) for metabolically abnormal obesity phenotype after adjustment for confounders, including age, sex, smoking statues, alcohol use, creatinine, uric acid, systolic BP, HDL cholesterol, and impaired fasting glucose or diabetes.
  
  
  CONCLUSIONS
  MHO phenotype was not associated with higher risk of incident CKD.
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Yoshitaka
authors: Y
authors: Hashimoto
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Muhei
authors: M
authors: Tanaka
authors: Division of Metabolism, Nephrology and Rheumatology, Japanese Red Cross Kyoto Daini Hospital, Kyoto, Japan; and.
authors: Hiroshi
authors: H
authors: Okada
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Takafumi
authors: T
authors: Senmaru
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Masahide
authors: M
authors: Hamaguchi
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Mai
authors: M
authors: Asano
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Masahiro
authors: M
authors: Yamazaki
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Yohei
authors: Y
authors: Oda
authors: Division of Metabolism, Nephrology and Rheumatology, Japanese Red Cross Kyoto Daini Hospital, Kyoto, Japan; and.
authors: Goji
authors: G
authors: Hasegawa
authors: Department of Internal Medicine, Oike Clinic, Kyoto, Japan.
authors: Hitoshi
authors: H
authors: Toda
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan;
authors: Naoto
authors: N
authors: Nakamura
authors: Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan; sayarinapm@hotmail.com.
authors: Michiaki
authors: M
authors: Fukui
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D015992:Body Mass Index; D016009:Chi-Square Distribution; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D015994:Incidence; D007564:Japan / Q000453:epidemiology; D007668:Kidney / Q000503:physiopathology; D008055:Lipids / Q000097:blood; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D000067329:Obesity, Metabolically Benign / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology*; D016017:Odds Ratio; D010641:Phenotype; D065840:Protective Factors; D011507:Proteinuria / Q000175:diagnosis / Q000453:epidemiology; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D008055:Lipids
keywords: body mass index; chronic kidney disease; epidemiology and outcomes; obesity; proteinuria
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