The investigation was conducted in Hebei Province, China, a region situated in the northern part of the country that experiences significant seasonal temperature variations and frequent episodes of air pollution. The study utilized a county-level two-stage time-series design, leveraging daily data on mortality, PM2.5 concentrations, and meteorological variables from 172 counties over the cold seasons spanning from 2014 to 2019. This extensive dataset allowed the researchers to analyze the temporal dynamics of exposure and its lagged effects on health outcomes with high granularity, providing a detailed view of how short-term environmental changes translate into population-level health impacts.

Defining the specific periods of exposure was a critical methodological step in this research. The authors defined pollution waves as periods lasting at least two consecutive days where PM2.5 levels exceeded county-specific percentile thresholds. Similarly, cold events were identified as periods where temperatures fell below specific county-specific temperature percentiles for at least two consecutive days. The concept of joint exposure was strictly limited to days when these two event periods overlapped in time. This overlap period began when the later of the two events started and ended when either event concluded, ensuring that the analysis focused exclusively on the days when residents were simultaneously subjected to both cold stress and elevated particulate pollution.

The statistical analysis employed quasi-Poisson distributed lag models to estimate county-specific cumulative relative risks over lag days 0 through 10 following a one-day change in the binary exposure indicator. These individual county estimates were then pooled using multivariate random-effects meta-analysis to produce a comprehensive assessment of the association. The primary analysis focused on non-accidental mortality under the P75T10 definition, which was selected because it retained the greatest event support and county coverage after the exposure redefinition process. This approach allowed the researchers to quantify the additional risk attributable to the overlap of these two environmental factors.

The results of the study were striking. A total of 975,471 non-accidental deaths were recorded in the dataset. Under the primary P75T10 definition, 113 counties contributed to the pooled analysis, with the majority located in the central-southern part of Hebei Province. The analysis revealed that a one-day joint exposure indicator was associated with an average pooled cumulative relative risk of 2.918 for non-accidental mortality over the 10-day lag period. This indicates that the risk of death was nearly three times higher during days of overlapping cold and pollution events compared to days without such overlap, a magnitude of effect that is considerably larger than the risks associated with either cold events or pollution waves alone.

In contrast, the relative risks for pollution-wave-only days and cold-event-only days were significantly lower. The study found a relative risk of 1.144 for pollution-wave-only days and 1.098 for cold-event-only days. This comparison underscores the disproportionate health burden imposed by the simultaneous presence of both stressors. The findings suggest that the physiological mechanisms triggered by cold stress, such as vasoconstriction and increased blood pressure, may be exacerbated by the inflammatory responses induced by fine particulate matter, leading to a compounded risk for cardiovascular and respiratory mortality.

The robustness of these findings was tested through various sensitivity analyses. The primary estimate remained generally consistent across alternative specifications, including different lag-spline functions, temporal-trend adjustments, humidity controls, continuous-exposure models, and spatial-covariance structures. However, the estimate was attenuated when the maximum lag was extended to 27 days, suggesting that the acute impact of overlapping events is most pronounced in the immediate days following exposure. Additionally, estimates under stricter definitions, such as P80T10 and P90T10, also showed elevated risks, although the precision of the estimates varied depending on the number of counties contributing to the analysis.

It is important to note that the primary pooled estimate was driven predominantly by counties in the central-southern plains of Hebei, and there was substantial heterogeneity between counties. Estimates under the T05 definitions were less precise due to the limited number of counties contributing to the analysis, and the P90T05 definition was not estimable. This geographic concentration of the effect highlights the importance of local environmental and demographic factors in shaping the health impacts of overlapping environmental hazards. The findings support the need for geographically targeted and coordinated preparedness strategies that address both air quality and cold weather risks simultaneously.

The study contributes to the growing body of evidence on the health effects of environmental stressors and emphasizes the importance of considering the temporal overlap of multiple hazards in public health planning. By demonstrating the significant mortality risk associated with overlapping PM2.5 pollution waves and cold events, the research provides a compelling argument for integrated environmental health policies. These policies should aim to mitigate the combined impact of air pollution and extreme cold, particularly in regions where such overlaps are frequent. The findings have implications for early warning systems, which could be enhanced to alert public health authorities and the general population when conditions are likely to lead to overlapping exposure, thereby enabling timely interventions to reduce health risks.

Subject of Research: Mortality associations with overlapping PM2.5 pollution waves and cold events in Hebei Province, China: a county-level two-stage time-series study

Article Title: Mortality associations with overlapping PM2.5 pollution waves and cold events in Hebei Province, China: a county-level two-stage time-series study

Article References: Zhang, Z., Yan, L., Jin, Y., Chu, H., Qi, T., Guo, Y., Liu, X., & Yang, L. (2026). Mortality associations with overlapping PM2.5 pollution waves and cold events in Hebei Province, China: a county-level two-stage time-series study. BMC Public Health. https://doi.org/10.1186/s12889-026-29816-6

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29816-6

Keywords: Mortality, associations, overlapping, pollution, waves, cold, events, Hebei, Province, China, county-level, two-stage