Association between air pollution and hospital admissions for hypertension in Lanzhou, China

Abstract

Air pollution has been accepted as an important risk factor for hypertension. However, little is known about the association between air pollution and hospitalization for hypertension. In this study, we explored the association between six criteria air pollutants and hypertension hospitalization in Lanzhou, China. An over-dispersed Poisson regression model combined with a distributed lag nonlinear model (DLNM) was used. In addition, we investigated the effect of modification by sex, age, and season. A total of 30,197 hospitalization cases were identified during the study period. A 10μg/m³ increase in PM_2.5, PM₁₀, SO₂, and NO₂ concentrations or 1 mg/m³ increment in CO was significantly associated with relative risks (RRs) of hospital admissions due to hypertension 1.026 [95% confidence interval (CI): 1.010, 1.043], 1.010 (95%CI: 1.005, 1.015), 1.042 (95%CI: 1.001, 1.085), 1.028 (95%CI: 1.003, 1.052), and 1.106 (95%CI: 1.031, 1.186), respectively. No significant influence of O₃8h was found on hypertension hospital admissions. The associations differed by individual characteristics; the elderly (≥ 65 years) and females were highly vulnerable. The effects of PM_2.5, SO₂, and CO were more evident in the cool season than in the warm season. From exposure-response curves, we observe a nearly linear relationship for PM_2.5, PM₁₀, SO₂, NO₂, and CO. This study suggests that exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO is associated with hypertension morbidity.

Keywords: Air pollution; Distributed lag nonlinear model; Hospital admissions; Hypertension.