Cold and PM2.5 Linked to More Circulatory Ambulance Calls
Key Takeaways
- In Shijiazhuang, China, low apparent temperature was associated with higher circulatory EAC risk and delayed effects.
- Low apparent temperature accounted for a measurable share of circulatory EACs, and mild cold contributed the largest attributable burden.
- Most joint low-temperature and PM2.5 patterns were associated with higher circulatory EAC risk, with P1T3 showing the strongest cumulative pattern.
- Interaction patterns were mixed rather than uniformly synergistic, with overall antagonism and varying subgroup signals.
- Higher susceptibility appeared among males, older adults, and patients with hypertension.
A single-city ecological time-series reported in Chen et al. time-series analysis of apparent low temperature, PM2.5, and circulatory emergency ambulance calls in Shijiazhuang linked daily dispatch records from the Shijiazhuang Emergency Medical Center with citywide meteorologic and air-pollution data from 2014 through 2023. The dataset included 82,714 circulatory emergency ambulance calls (EACs), and outcomes were grouped by primary prehospital International Classification of Diseases, 10th Revision (ICD-10) diagnoses for circulatory disease overall as well as cerebrovascular disease, heart disease, and hypertension, with additional stratification by sex and age. Investigators calculated apparent temperature with the Steadman formulation, grouped low apparent temperature as T1 through T3 and PM2.5 events as P1 through P4, coded simultaneous exposures such as P1T3 and P2T2, and estimated lagged associations with distributed lag non-linear models and quasi-Poisson regression; additive interaction was assessed with relative excess risk due to interaction (RERI). A longer lag window was used for the single-exposure analyses, while joint-exposure models used a shorter window to preserve stability.
Low apparent temperature was associated with increased circulatory EAC risk, and 5% (95% CI 2%-6.1%) of circulatory EACs were attributable to low apparent temperature. Among joint exposure patterns, the strongest cumulative overall association appeared under P1T3, RR 1.146 (95% CI 1.088-1.207). The overall P2T2 interaction was antagonistic rather than synergistic, with RERI -0.089 (95% CI -0.153 to -0.024).
Peak single-day joint effects generally emerged several days after exposure rather than immediately. Across subgroup analyses, males, adults aged 65 years and older, and patients with hypertension appeared more susceptible, and interaction signals included both positive and negative patterns rather than a single directional effect. Sensitivity analyses, false-discovery-rate-adjusted subgroup analyses, and winter-only analyses were broadly consistent, with winter suggesting stronger joint effects for several outcomes.
Because the analysis was ecological and observational, the reported associations cannot resolve individual-level exposure or causality. Exposure estimates came from citywide fixed-site monitoring averages rather than personal measurements, low apparent temperature thresholds were location-specific, and the findings reflect one Chinese city rather than a setting that can be assumed to apply to North America. Joint exposures were also relatively sparse, with 183 joint exposure days overall and the rarest P4T3 category appearing on only 4 days, which helps explain why the most extreme combinations were unstable or excluded from some models. The chemical composition of PM2.5 was not available, limiting interpretation of which particulate mixtures might have driven the observed patterns.
The investigators concluded that combined apparent low temperature and PM2.5 were associated with higher circulatory emergency ambulance demand in Shijiazhuang, with delayed, subgroup-specific, and sometimes antagonistic interaction patterns.
Clinician Questions
How were low apparent temperature and PM2.5 joint exposure days defined in the Shijiazhuang circulatory emergency analysis?
Investigators calculated apparent temperature with the Steadman formulation from mean temperature, relative humidity, and wind speed; defined low apparent temperature as T1 (-5.32 °C < AT ≤ -3.43 °C), T2 (-6.95 °C < AT ≤ -5.32 °C), and T3 (AT ≤ -6.95 °C); grouped PM2.5 as P1 (75 to <115 μg/m3), P2 (115 to <150 μg/m3), P3 (150 to <203 μg/m3), and P4 (≥203 μg/m3); and labeled simultaneous cold-pollution days as joint events such as P1T3 or P2T2.
Why did the analysis use a longer lag window for apparent temperature alone than for joint PM2.5-cold exposure models?
Single apparent temperature models used lag 0-21 days to capture delayed cold effects, whereas joint PM2.5-cold models used lag 0-14 days because rarer combined exposure categories became unstable with longer lags. The authors said Akaike Information Criterion and model stability guided that choice, and extended analyses showed similar early patterns but more instability beyond 14 days.
What does a negative RERI mean for the P2T2 low-temperature and PM2.5 pattern?
In the overall circulatory analysis, a negative relative excess risk due to interaction means the combined effect of the P2T2 low-temperature and PM2.5 exposure pattern was smaller than the sum of the 2 exposures’ independent effects, so the interaction was antagonistic rather than synergistic.
How were circulatory emergency events classified in the Shijiazhuang ambulance dataset?
The dataset used daily emergency ambulance call records from the Shijiazhuang Emergency Medical Center and grouped outcomes by primary prehospital ICD-10 diagnoses recorded by emergency physicians, including circulatory system diseases overall plus cerebrovascular disease, heart disease, and hypertension, rather than hospital discharge diagnoses.