Short-term effects of particulate matter exposure on emergency room visits for cardiovascular disease in Lanzhou, China: a time series analysis

Cardiovascular disease (CVD) has been the leading cause of death in China. Identifying the relationship between particulate matter (PM) and CVD in China is a significant challenge. In this study, daily CVD emergency room visit, environmental monitoring, and weather data from January 1, 2017, to December 31, 2018, in Lanzhou were collected. Generalized additive models (GAMs) were constructed to estimate the short-term effects of daily PM₂.₅, PMC, and PM₁₀ concentrations on CVD emergency room visits with different lag structures after controlling for the influence of meteorological elements and gaseous pollutants. Stratified analyses were conducted according to age (≥ 65 years and < 65 years), sex (male and female), cold season (from November to April), and warm season (from May to October). The results showed that each 10 μg/m³ increase in PM₂.₅ was associated with a 1.93% (95% CI 0.12–3.78%) increase in CVD emergency room visits at lag03, and no single lag model was statistically significant. The excess relative risks (ERRs) of PM₁₀ and PMC were not statistically significant at any lag pattern. The exposure-response curves demonstrated a nonlinear upward trend for these three PM pollutants. When adjusting for other gaseous pollutants, such as NO₂, SO₂, CO, and O₃, in the two-pollutant models, the associations between PM₁₀ and PMC and CVD emergency room visits did not change compared with the single-pollutant models. The ERRs of PM₂.₅ were 1.67% (95% CI 0.03–3.34%) at lag02 after adjustment for NO₂ and 1.65% (95% CI 0.02–3.30%) at lag02 after adjustment for SO₂. The ERRs of PM₂.₅ were still statistically significant at lag03 when we adjusted for any one of the gaseous pollutants. Susceptibility to PM₂.₅ was increased in people aged < 65 years, in males, and in the warm season. The findings are very important for local governments to develop environmental policies and strategies to reduce ambient PM₂.₅ levels.