Combined body mass index with high-sensitivity C-reactive protein as independent predictors for chronic kidney disease in a relatively healthy population in Taiwan

Y. W. Tsai, M. C. Lu, Y. H. Lin, Y. C. Lee, W. C. Li, J. Y. Chen, S. S. Chang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Background/Objectives: Obesity, a chronic inflammatory state, increases risk of cardiovascular disease and insulin resistance, which are the leading cause of end-stage renal disease (ESRD). We evaluated the relationship between body mass index (BMI) and high-sensitivity C-reactive protein (hsCRP) level and impaired kidney function to determine the predictive value of both markers for estimating chronic kidney disease (CKD) risk in a healthy adult population in Taiwan. Subjects/Methods: In a retrospective cross-sectional study of 4100 subjects ≥18 years, a multivariate logistic regression model was used to assess the relationship among BMI, high hsCRP levels and CKD. Receiver-operating characteristic curve and Youden index were developed to define the discrimination power of combining BMI with hsCRP for CKD prediction and to determine the best predictive index. Results: Overweight/obese subjects with high hsCRP levels had the highest odds ratio for CKD (P=0.048). In females, combining BMI with hsCRP for CKD prediction was superior to that of males (0.890 vs 0.623, respectively; both P<0.001). For females, the Youden index was 25.65 kg/m 2 for BMI and 1.04 μg/ml for hsCRP. Conclusions: Overweight/obesity with higher hsCRP levels is associated with reduced renal function and increased risk for CKD. BMI and hsCRP levels can be used as surrogate markers for CKD risk, especially for females.

Original languageEnglish
Pages (from-to)766-771
Number of pages6
JournalEuropean Journal of Clinical Nutrition
Volume70
Issue number7
DOIs
Publication statusPublished - Jul 1 2016
Externally publishedYes

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Taiwan
Chronic Renal Insufficiency
C-Reactive Protein
Body Mass Index
Population
Obesity
Logistic Models
Kidney
Disease Resistance
ROC Curve
Chronic Kidney Failure
Insulin Resistance
Cardiovascular Diseases
Cross-Sectional Studies
Biomarkers
Odds Ratio

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Nutrition and Dietetics

Cite this

Combined body mass index with high-sensitivity C-reactive protein as independent predictors for chronic kidney disease in a relatively healthy population in Taiwan. / Tsai, Y. W.; Lu, M. C.; Lin, Y. H.; Lee, Y. C.; Li, W. C.; Chen, J. Y.; Chang, S. S.

In: European Journal of Clinical Nutrition, Vol. 70, No. 7, 01.07.2016, p. 766-771.

Research output: Contribution to journalArticle

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abstract = "Background/Objectives: Obesity, a chronic inflammatory state, increases risk of cardiovascular disease and insulin resistance, which are the leading cause of end-stage renal disease (ESRD). We evaluated the relationship between body mass index (BMI) and high-sensitivity C-reactive protein (hsCRP) level and impaired kidney function to determine the predictive value of both markers for estimating chronic kidney disease (CKD) risk in a healthy adult population in Taiwan. Subjects/Methods: In a retrospective cross-sectional study of 4100 subjects ≥18 years, a multivariate logistic regression model was used to assess the relationship among BMI, high hsCRP levels and CKD. Receiver-operating characteristic curve and Youden index were developed to define the discrimination power of combining BMI with hsCRP for CKD prediction and to determine the best predictive index. Results: Overweight/obese subjects with high hsCRP levels had the highest odds ratio for CKD (P=0.048). In females, combining BMI with hsCRP for CKD prediction was superior to that of males (0.890 vs 0.623, respectively; both P<0.001). For females, the Youden index was 25.65 kg/m 2 for BMI and 1.04 μg/ml for hsCRP. Conclusions: Overweight/obesity with higher hsCRP levels is associated with reduced renal function and increased risk for CKD. BMI and hsCRP levels can be used as surrogate markers for CKD risk, especially for females.",
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