Nonlinear and Lagged Associations of Compound Cold Wave–PM 2.5 Pollution Exposure with Cardiovascular Emergency Ambulance Calls: A Time-Series Study in Shijiazhuang, China

<title>Abstract</title> <p> <bold>Background：</bold> Cold waves and fine particulate matter (PM _2.5 ) pollution are well-recognized environmental risk factors for cardiovascular health. However, evidence remains limited regarding the health effects of compound exposure to different cold-wave intensities and PM _2.5 pollution levels, as well as the potential interactions between these environmental stressors. This study aimed to establish a multi-level cold wave–PM _2.5 compound exposure framework to evaluate the associations of different exposure combinations with cardiovascular emergency ambulance calls and to investigate their lagged and interactive effects. <bold>Methods：</bold> Daily cardiovascular emergency ambulance call records (n = 82,714), meteorological data, and air pollution data were collected in Shijiazhuang, China, from 1 January 2014 to 31 December 2023. Three cold-wave categories (T1–T3) were defined using temperature percentile thresholds, while four PM _2.5 pollution levels (P1–P4) were classified according to daily mean PM _2.5 concentrations. Compound cold wave–PM _2.5 exposure events were subsequently constructed. A distributed lag non-linear model (DLNM) combined with quasi-Poisson regression was applied to estimate both single-day and cumulative lag effects of different exposure patterns. Additive interactions between cold waves and PM _2.5 were assessed using the relative excess risk due to interaction (RERI). <bold>Results：</bold> A total of 82,714 cardiovascular emergency ambulance calls were recorded during the study period. Cold-wave exposure alone was consistently associated with an increased risk of cardiovascular emergency ambulance calls, with stronger cold waves (T3) showing more pronounced cumulative effects. In contrast, PM _2.5 exposure alone exhibited relatively weak associations, and no stable cumulative risk increase was observed. Compound cold wave–PM _2.5 exposure demonstrated substantial nonlinearity and heterogeneity, with considerable variation across different exposure combinations. The P2T3 event (moderate PM _2.5 pollution combined with a strong cold wave) was associated with the highest cumulative risk (RR = 1.137, 95% CI: 1.082–1.194). Interaction analyses further indicated that the joint effects of cold waves and PM _2.5 were not uniformly synergistic; instead, both positive and negative additive interactions were observed across different exposure combinations, suggesting that the health impacts of compound exposure varied according to cold-wave intensity, PM _2.5 pollution level, and population characteristics. Subgroup analyses additionally revealed differential susceptibility among males, older adults, and patients with different cardiovascular disease subtypes. <bold>Conclusion：</bold> Cold waves may represent a more important environmental driver of cardiovascular emergency ambulance calls than PM _2.5 pollution, whereas the health effects of PM _2.5 appear to be modified by exposure combinations and meteorological conditions. The health impacts of compound cold wave–PM _2.5 exposure were characterized by nonlinear, lagged, and heterogeneous associations across exposure combinations. These findings highlight the importance of incorporating multiple environmental stressors into environmental health risk assessment and early warning systems, rather than focusing on single environmental factors alone. </p>