Intraday effects of ambient PM1 on emergency department visits in Guangzhou, China: A case-crossover study

Abstract Background Short-term exposure to PM2.5 has been widely associated with human morbidity and mortality. However, most up-to-date research was conducted at a daily timescale, neglecting the intra-day variations in both exposure and outcome. As an important fraction in PM2.5, PM1 has not been investigated about the very acute effects within a few hours. Methods Hourly data for size-specific PMs (i.e., PM1, PM2.5, and PM10), all-cause emergency department (ED) visits and meteorological factors were collected from Guangzhou, China, 2015–2016. A time-stratified case-crossover design with conditional logistic regression analysis was performed to evaluate the hourly association between size-specific PMs and ED visits, adjusting for hourly mean temperature and relative humidity. Subgroup analyses stratified by age, sex and season were conducted to identify potential effect modifiers. Results A total of 292,743 cases of ED visits were included. The effects of size-specific PMs exhibited highly similar lag patterns, wherein estimated odds ratio (OR) experienced a slight rise from lag 0–3 to 4–6 h and subsequently attenuated to null along with the extension of lag periods. In comparison with PM2.5 and PM10, PM1 induced slightly larger effects on ED visits. At lag 0–3 h, for instance, ED visits increased by 1.49% (95% confidence interval: 1.18–1.79%), 1.39% (1.12–1.66%) and 1.18% (0.97–1.40%) associated with a 10-μg/m3 rise, respectively, in PM1, PM2.5 and PM10. We have detected a significant effect modification by season, with larger PM1-associated OR during the cold months (1.017, 1.013 to 1.021) compared with the warm months (1.010, 1.005 to 1.015). Conclusions Our study provided brand-new evidence regarding the adverse impact of PM1 exposure on human health within several hours. PM-associated effects were significantly more potent during the cold months. These findings may aid health policy-makers in establishing hourly air quality standards and optimizing the allocation of emergency medical resources.