Road traffic noise and incidence of primary hypertension: a prospective analysis in UK Biobank

Abstract

BACKGROUND AND AIM The quality of evidence regarding the associations between road traffic noise and hypertension is low due to the limitations of cross-sectional study design, with the role of air pollution remains to be further clarified. To evaluate associations of long-term road traffic noise and air pollution exposure with incident primary hypertension, we conducted a prospective population-based analysis in UK Biobank. METHODS Road traffic noise was estimated at baseline residential address using the Common Noise Assessment Method model. Incident primary hypertension (ICD 10: I10) was ascertained through linkage with medical records for ~250 000 participants. Cox proportional hazard models were used to estimate hazard ratios (HRs) for association between road traffic noise and incident primary hypertension, adjusting for covariates determined via directed acyclic graph. RESULTS During a median of 8.1 years follow up, 21 185 incident primary hypertension cases were ascertained. The HR for a 10 dB[A] increase in mean weighted average 24-h road traffic noise level (Lden) exposure was 1.08 [95% confidence interval (CI) 1.02, 1.14]. A dose-response relationship was found, with HRs of 1.14 (95% CI: 1.04, 1.26) for Lden > 65dB[A] vs. ≤ 55dB[A] (P trend <0.05), and HRs of 1.15 (95% CI: 1.04, 1.26) for night-time road traffic noise (Lnight)>55 dB[A] vs. ≤ 45dB[A] (P trend <0.05). The associations were all robust to adjustment for fine particulate matter (PM2.5) and nitrogen dioxide (NO2). Furthermore, the highest incident hypertension risk was seen in the group who were exposed to the highest level of both road traffic noise and air pollution. CONCLUSIONS Long-term exposure to road traffic noise was associated with increased incidence of primary hypertension, and the effect estimates were greater in those with higher air pollution exposure. KEYWORDS road traffic noise; air pollution; primary hypertension; prospective analysis