Observed causative impact of fine particulate matter on acute upper respiratory disease: a comparative study in two typical cities in China

Abstract

Association between fine particulate matter (PM_2.5) and respiratory health has attracted great concern in China. Substantial epidemiological evidences confirm the correlational relationship between PM_2.5 and respiratory disease in many Chinese cities. However, the causative impact of PM_2.5 on respiratory disease remains uncertain and comparative analysis is limited. This study aims to explore and compare the correlational relationship as well as the causal connection between PM_2.5 and upper respiratory tract infection (URTI) in two typical cities (Beijing, Shenzhen) with rather different ambient air environment conditions. The distributed lag nonlinear model (DLNM) was used to detect the correlational relationship between PM_2.5 and URTI by revealing the lag effect pattern of PM_2.5 on URTI. The convergent cross mapping (CCM) method was applied to explore the causal connection between PM_2.5 and URTI. The results from DLNM indicate that an increase of 10 μg/m³ in PM_2.5 concentration is associated with an increase of 1.86% (95% confidence interval: 0.74%-2.99%) in URTI at a lag of 13 days in Beijing, compared with 2.68% (95% confidence interval: 0.99-4.39%) at a lag of 1 day in Shenzhen. The causality detection with CCM quantitatively demonstrates the significant causative influence of PM_2.5 on URTI in both two cities. Findings from the two methods consistently show that people living in low-concentration areas (Shenzhen) are less tolerant to PM_2.5 exposure than those in high-concentration areas (Beijing). In general, our study highlights the adverse health effects of PM_2.5 pollution on the general public in cities with various PM_2.5 levels and emphasizes the needs for the government to provide appropriate solutions to control PM_2.5 pollution, even in cities with low PM_2.5 concentration.

Keywords: Acute upper respiratory disease; Causative impact; Convergent cross mapping; Distributed lag nonlinear model; Fine particulate matter; Health effect.