OBJECTIVE: To investigate the relationship between urine pH and metabolic syndrome (MetS) and its components, while controlling for covariates. SUBJECTS AND METHODS: This cross-sectional study was conducted on 5,430 Japanese subjects (4,691 without MetS; 739 with MetS) undergoing health assessments. Partial correlation analysis and analysis of covariance were used for controlling confounding parameters (age, gender, levels of serum uric acid and high-sensitivity C-reactive protein, estimated glomerular filtration rate, and smoking and drinking status). Using multiple logistic regression analyses, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for MetS incidence were calculated across urine pH categories. Path analysis was used to determine the relationship between MetS and urine pH. RESULTS: Subjects with MetS had significantly lower urine pH (5.9 ± 0.7) than those without MetS (6.0 ± 0.7) (p < 0.001). Partial correlation analysis showed that systolic and diastolic blood pressure, and triglyceride and fasting plasma glucose levels were negatively correlated with urine pH, while high-density lipoprotein cholesterol was positively correlated with urine pH. Analysis of covariance indicated that urine pH decreased with an increasing number of metabolic abnormalities. Adjusted ORs (95% CI) for the presence of MetS in subjects with urine pH 5.5-6.0 and pH <5.5 were 1.34 (1.04-1.73) and 1.52 (1.09-2.13), respectively (reference: subjects with a urine pH >6.0). CONCLUSION: The MetS and its components were independently associated with lower urine pH.
OBJECTIVE: To investigate the relationship between urine pH and metabolic syndrome (MetS) and its components, while controlling for covariates. SUBJECTS AND METHODS: This cross-sectional study was conducted on 5,430 Japanese subjects (4,691 without MetS; 739 with MetS) undergoing health assessments. Partial correlation analysis and analysis of covariance were used for controlling confounding parameters (age, gender, levels of serum uric acid and high-sensitivity C-reactive protein, estimated glomerular filtration rate, and smoking and drinking status). Using multiple logistic regression analyses, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for MetS incidence were calculated across urine pH categories. Path analysis was used to determine the relationship between MetS and urine pH. RESULTS: Subjects with MetS had significantly lower urine pH (5.9 ± 0.7) than those without MetS (6.0 ± 0.7) (p < 0.001). Partial correlation analysis showed that systolic and diastolic blood pressure, and triglyceride and fasting plasma glucose levels were negatively correlated with urine pH, while high-density lipoprotein cholesterol was positively correlated with urine pH. Analysis of covariance indicated that urine pH decreased with an increasing number of metabolic abnormalities. Adjusted ORs (95% CI) for the presence of MetS in subjects with urine pH 5.5-6.0 and pH <5.5 were 1.34 (1.04-1.73) and 1.52 (1.09-2.13), respectively (reference: subjects with a urine pH >6.0). CONCLUSION: The MetS and its components were independently associated with lower urine pH.
Authors: Mary Ann Cameron; Naim M Maalouf; Beverley Adams-Huet; Orson W Moe; Khashayar Sakhaee Journal: J Am Soc Nephrol Date: 2006-04-05 Impact factor: 10.121
Authors: Young Hye Cho; Sang Yeoup Lee; Dong Wook Jeong; Eun Jung Choi; Kyung Jee Nam; Yun Jin Kim; Jeong Gyu Lee; Yu Hyone Yi; Young Jin Tak; Byung Mann Cho; Soo Bong Lee; Ka Young Lee Journal: J Res Med Sci Date: 2014-07 Impact factor: 1.852