2017Hormone and Metabolic ResearchRequires access

Serum Uric Acid Concentrations Can Predict Hypertension: A Longitudinal Population-Based Epidemiological Study

Rongjiong Zheng, Tianmeng Yang, Qingmei Chen, Changxi Chen, Yushan Mao

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Abstract

An elevated serum uric acid concentration may be associated with hypertension, which is the leading cause of death worldwide. However, whether the elevation is causal or a consequence of hypertension among the Chinese population remains unclear. This study was designed to investigate the longitudinal relationship between the serum uric acid concentrations and hypertension among Chinese individuals. This study included 5105 subjects, initially without hypertension, who were followed up for 9 years. The subjects were divided into four groups based on the serum uric acid quartile. Cox proportional hazard models were used to analyse the risk factors for hypertension development. Over the 9 years, 2259 of the subjects developed hypertension. The overall 9-year cumulative incidence of hypertension was 44.3%, ranging from 36.3% in quartile 1 to 42.4%, 44.1%, and 54.5% in quartiles 2, 3, and 4, respectively (p for trend<0.001). The Cox regression analyses indicated that the serum uric acid concentrations were independently and positively associated with the risk of incident hypertension. This longitudinal study demonstrated that high serum uric acid concentrations increase the risk of hypertension among the Chinese population.

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What this paper is about

An elevated serum uric acid concentration may be associated with hypertension, which is the leading cause of death worldwide. However, whether the elevation is causal or a consequence of hypertension among the Chinese population remains unclear. This study was designed to investigate the longitudinal relationship between the serum uric acid concentrations and hypertension among Chinese individuals. This study included 5105 subjects, initially without hypertension, who were followed up for 9 years. The subjects were divided into four groups based on the serum uric acid quartile. Cox proportional hazard models were used to analyse the risk factors for hypertension development. Over the 9 years, 2259 of the subjects developed hypertension. The overall 9-year cumulative incidence of hypertension was 44.3%, ranging from 36.3% in quartile 1 to 42.4%, 44.1%, and 54.5% in quartiles 2, 3, and 4, respectively (p for trend<0.001). The Cox regression analyses indicated that the serum uric acid concentrations were independently and positively associated with the risk of incident hypertension. This longitudinal study demonstrated that high serum uric acid concentrations increase the risk of hypertension among the Chinese population.

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Available abstract

An elevated serum uric acid concentration may be associated with hypertension, which is the leading cause of death worldwide. However, whether the elevation is causal or a consequence of hypertension among the Chinese population remains unclear. This study was designed to investigate the longitudinal relationship between the serum uric acid concentrations and hypertension among Chinese individuals. This study included 5105 subjects, initially without hypertension, who were followed up for 9 years. The subjects were divided into four groups based on the serum uric acid quartile. Cox proportional hazard models were used to analyse the risk factors for hypertension development. Over the 9 years, 2259 of the subjects developed hypertension. The overall 9-year cumulative incidence of hypertension was 44.3%, ranging from 36.3% in quartile 1 to 42.4%, 44.1%, and 54.5% in quartiles 2, 3, and 4, respectively (p for trend<0.001). The Cox regression analyses indicated that the serum uric acid concentrations were independently and positively associated with the risk of incident hypertension. This longitudinal study demonstrated that high serum uric acid concentrations increase the risk of hypertension among the Chinese population.

Key concepts: Quartile, Uric acid, Medicine, Internal medicine, Proportional hazards model, Hazard ratio, Population, Incidence (geometry)

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