title: Hypovolaemia was associated with clustering of major cardiovascular risk factors in general population.
abstract: BACKGROUND
  Previous studies indicated that the clustering of major cardiovascular disease (CVD) risk factors is common, and multiple unhealthy lifestyles are responsible for the clustering of CVD risk factors. However, little is known about the direct association between the volume load and the clustering of CVD risk factors in general population.
  
  
  METHODS
  We investigated the association of the clustering of CVD risk factors (defined as two or more of the following factors: hypertension, diabetes, dyslipidemia and overweight) with volume load, which was evaluated by bioelectrical impedance analysis. Hypovolaemia was defined as extracellular water/total body water (ECW/TBW) at and under the 10th percentile for the normal population.
  
  
  RESULTS
  Among the 7900 adults, only 29.3% were free of any pre-defined CVD risk factors and 40.8% had clustering of CVD risk factors. Hypovolaemia in clustering group was statistically higher than that either in the single or in the none risk factor group, which was 23.7% vs. 17.0% and 10.0%, respectively (P <0.001). As a categorical outcome, the percentage of the lowest quartiles of ECW/TBW and TBW/TBWwatson in clustering group were statistically higher than either those in the single or in the none risk factor group, which were 44.9% vs. 36.9% and 25.1% (P <0.001), 36.2% vs. 32.2% and 25.0%, respectively (P <0.001). After adjusting of potential confounders, hypovolaemia was significantly associated with clustering of CVD risk factors, with an OR of 1.66 (95% CI, 1.45-1.90).
  
  
  CONCLUSIONS
  Hypovolaemia was associated with clustering of major CVD risk factors, which further confirms the importance of lifestyle for the development of CVD.
authors.forename: Xianglei
authors.initials: X
authors.lastname: Kong
authors.forename: Xiaojing
authors.initials: X
authors.lastname: Ma
authors.forename: Jing
authors.initials: J
authors.lastname: Yao
authors.forename: Shuting
authors.initials: S
authors.lastname: Zheng
authors.forename: Meiyu
authors.initials: M
authors.lastname: Cui
authors.affiliation: Department of Nephrology, Qianfoshan Hospital, Shandong University, No,16766, Jingshi Road, Jinan 250014, PR China. qianyixdmgmail@163.com.
authors.forename: Dongmei
authors.initials: D
authors.lastname: Xu
mesh_terms: D000328:Adult; D001810:Blood Volume; D001811:Blood Volume Determination; D001823:Body Composition; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology*; D016009:Chi-Square Distribution; D002681:China / Q000453:epidemiology; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000453:epidemiology; D050171:Dyslipidemias / Q000453:epidemiology; D017097:Electric Impedance; D005260:Female; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D020896:Hypovolemia / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D008019:Life Style; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D050177:Overweight / Q000453:epidemiology; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors