Associations between non-optimum temperatures and cardiovascular hospital admissions and effect modification by ambient particulate air pollution: a two-stage time-series study in China

It remains unclear whether non-optimum temperatures are associated with hospital admissions for subtypes of cardiovascular events, and how PM_2.5 and black carbon (BC) modify these associations.

Hospital admission data of major cardiovascular events were obtained from two major national health insurance systems across 270 cities of prefecture-level or above in China during 2013-2017. A two-stage time-series study was conducted using a generalized additive model with a quasi-Poisson family, combined with a distributed lag nonlinear regression model, to explore the exposure-response associations of non-optimum temperatures with hospital admissions. Effect modification was investigated by stratifying ambient particulate air pollution levels into quartile groups.

In a total of 24,564,921 hospital admission records for major cardiovascular events, compared with the minimum morbidity temperature (18.3 °C), the relative risks (RRs) of hospital admissions for total major cardiovascular events associated with extreme cold temperature (-3.1 °C, 2.5th percentile) and extreme hot temperature (27.9 °C, 97.5th percentile) were 1.69 [95% confidence interval (CI): 1.46-1.96] and 1.27 (95% CI: 1.15-1.41), respectively. Such temperature-hospital admission associations were amplified at high BC levels, especially under extreme hot temperature, with RR increased from 1.14 (95% CI: 1.02-1.28) in the first quartile to 1.53 (95% CI: 1.31-1.78) in the fourth quartile group of BC levels.

Our study suggests that both extreme cold and hot temperatures contribute to elevated hospital admission risks for major cardiovascular events, with high BC levels further exacerbating the risks associated with extreme hot temperature.

National Science Fund for Distinguished Young Scholars of China (grant number 82525058), National Natural Science Foundation of China (grant number 82203991), and Youth Top Talent Program of Xi'an Jiaotong University.