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

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Titel: Medium-Term Lag-Response Associations Between PM10 Exposure and All-Cause Mortality in Valencia and London: A Time-Stratified Case-Crossover Study
Autoren: Bin Zhou, Katrin Gohlsch, Surendra Ranpal, Jiancong Wang, Christoph Knote
Quelle: Journal of Epidemiology and Global Health, Vol 15, Iss 1, Pp 1-12 (2025)
Verlagsinformationen: Springer, 2025.
Publikationsjahr: 2025
Bestand: LCC:Public aspects of medicine
Schlagwörter: PM10 exposure, Medium term lag response associations, Lagging time windows of 21 days, All cause mortality, Environmental epidemiology, Temporal lag methodological structures, Public aspects of medicine, RA1-1270
Beschreibung: Abstract 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.
Publikationsart: article
Dateibeschreibung: electronic resource
Sprache: English
ISSN: 2210-6014
Relation: https://doaj.org/toc/2210-6014
DOI: 10.1007/s44197-025-00459-x
Zugangs-URL: https://doaj.org/article/afb03717211c4e0e89ddcff6b5cc08ae
Dokumentencode: edsdoj.fb03717211c4e0e89ddcff6b5cc08ae
Datenbank: Directory of Open Access Journals
Beschreibung
Abstract:Abstract 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.
ISSN:22106014
DOI:10.1007/s44197-025-00459-x