Medium-Term Lag-Response Associations Between PM10 Exposure and All-Cause Mortality in Valencia and London: A Time-Stratified Case-Crossover Study

Background: Air pollution is among the top five environmental risk factors for human health worldwide. However, our understanding of the physiological responses to PM₁₀ exposure over medium-term lag periods remains limited. This study aims to examine the medium-term lag–response associations—using lagging time windows of up to 21 days—between PM₁₀ exposure and all-cause mortality in Valencia and London from 2002 to 2006. Methods: We used a time-stratified case-crossover design; building on the methodologies of Tobias et al. and Bhaskaran et al., we applied a fixed-effects conditional quasi-Poisson regression model to quantify the association between PM₁₀ exposure and all-cause mortality. We also analyzed three different temporal lag methodological models for the exposure–mortality relationships. Results: We found distinct differences in the relative risk (RR) patterns of PM₁₀ exposure and all-cause mortality. In Valencia, the RR varied significantly, with confidence intervals that were wider than in London, where the RR remained more stable, fluctuating closely around 1. Significant associations were observed at early lag periods in both cities, consistent with Tobias et al. Notably, Valencia showed a significant peak in RR at lag 14, which was not observed in London. Subgroup analysis in Valencia also indicated delayed effects in younger populations. Scenario 3 (cumulative lag model) is conceptually closer to the cumulative progression of health risks associated with PM₁₀ exposure and produces higher RR estimates compared to Scenario 1 and 2. Conclusions: This study highlights the critical importance of addressing medium-term lag-response associations and methodological variations in environmental epidemiology. The findings have important clinical and public health implications and offer insights for risk assessment, healthcare planning, and the development of policies to mitigate the health impacts of PM₁₀ exposure.