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.
Keywords: Cardiovascular disease; Emergency room visits; Particulate matter; Time series analysis.