All Components of Metabolic Syndrome Are Associated with Microalbuminuria in a Chinese Population.
OBJECTIVE
Albuminuria is a well-known predictor of poor renal and cardiovascular outcomes and associated with increased risk of all-cause mortality. The study aimed to evaluate the associations between metabolic characteristics and the presence of albuminuria.


METHODS
This cross-sectional study included 18,384 adult Chinese who participated in health examinations during 2013-2014. Differences in clinical characteristics were compared for microalbuminuria (MAU) and albuminuria, and between genders. Potential risk factors associated with the risk of developing MAU and albuminuria were analyzed using univariate logistic regression. Multiple logistic regression was applied to further identify the independent associations between different levels of risk factors and the presence of MAU and albuminuria. The area under the ROC curve (AUC) was used to determine the discriminatory ability of metabolic risk factors in detecting albuminuria.


RESULTS
There were significant gender differences in clinical characteristics according to albuminuria status. Risk for the presence of albuminuria was significantly associated with age, male gender, waist circumference (WC), waist-to-height ratio (WHtR), hypertension, fasting plasma glucose (FPG), and triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-C) in univariate logistic regression. Multiple logistic regression analysis indicated that the factors significantly associated with the presence of MAU were WC > 90cm, WHtR at 0.6-0.7, hypertension, FPG > 6.1 mmole/L, and TG/HDL-C ratio > 1.6. The optimal cutoffs for risk factors of metabolic syndrome (MetS) to predict albuminuria in males and females were: WC, 90.8 vs. 80.0 cm; WHtR, 0.53 vs. 0.52; MAP, 97.9 vs. 91.9 mmHg; FPG, 5.40 vs. 5.28 mmole/L; and TG/HDL-C, 1.13 vs. 1.08.


CONCLUSIONS
MetS and all its components were associated with the presence of MAU in a health check-up population in China. Gender specific and optimal cutoffs for MetS components associated with the presence of MAU were determined.
Division of Pediatric Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.|Faculty of Medicine, National Yang-Ming University, Taipei, Taiwan.
Yi-Yen
YY
Lee
Department of Emergency Medicine, Xiamen Chang-Gung Hospital, Xiamen, China.
Chih-Kai
CK
Yang
Department of Emergency Medicine, Xiamen Chang-Gung Hospital, Xiamen, China.|Department of Emergency Medicine, Chang-Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.|Department of Medicine, College of Medicine, Chang-Gung University, Taoyuan, Taiwan.
Yi-Ming
YM
Weng
Department of Emergency Medicine, Xiamen Chang-Gung Hospital, Xiamen, China.|Department of Emergency Medicine, Chang-Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Chung-Hsun
CH
Chuang
Department of Health Management, Xiamen Chang-Gung Hospital, Xiamen, China.
Wei
W
Yu
Department of Emergency Medicine, Chang-Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.|Department of Medicine, College of Medicine, Chang-Gung University, Taoyuan, Taiwan.
Jih-Chang
JC
Chen
Department of Emergency Medicine, Xiamen Chang-Gung Hospital, Xiamen, China.|Department of Emergency Medicine, Chang-Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Wen-Cheng
WC
Li
D000328:Adult; D000419:Albuminuria / Q000097:blood / Q000150:complications*; D019540:Area Under Curve; D044466:Asian People; D002681:China; D003404:Creatinine / Q000097:blood; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000150:complications*; D012372:ROC Curve; D012307:Risk Factors
D003404:Creatinine