Environmental health : a global access science source · 2024
Impact of short-term exposure to air pollution on natural mortality and vulnerable populations: a multi-city case-crossover analysis in Belgium.
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Demoury Claire, Aerts Raf, Berete Finaba, Lefebvre Wouter, Pauwels Arno, Vanpoucke Charlotte, Van der Heyden Johan, De Clercq Eva M
Аннотация
BACKGROUND: The adverse effect of air pollution on mortality is well documented worldwide but the identification of more vulnerable populations at higher risk of death is still limited. The aim of this study was to evaluate the association between natural mortality (overall and cause-specific) and short-term exposure to five air pollutants (PM2.5, PM10, NO2, O3 and black carbon) and identify potential vulnerable populations in Belgium.
METHODS: We used a time-stratified case-crossover design with conditional logistic regressions to assess the relationship between mortality and air pollution in the nine largest Belgian agglomerations. Then, we performed a random-effect meta-analysis of the pooled results and described the global air pollution-mortality association. We carried out stratified analyses by individual characteristics (sex, age, employment, hospitalization days and chronic preexisting health conditions), living environment (levels of population density, built-up areas) and season of death to identify effect modifiers of the association.
RESULTS: The study included 304,754 natural deaths registered between 2010 and 2015. We found percentage increases for overall natural mortality associated with 10 μg/m3 increases of air pollution levels of 0.6% (95% CI: 0.2%, 1.0%) for PM2.5, 0.4% (0.1%, 0.8%) for PM10, 0.5% (-0.2%, 1.1%) for O3, 1.0% (0.3%, 1.7%) for NO2 and 7.1% (-0.1%, 14.8%) for black carbon. There was also evidence for increases of cardiovascular and respiratory mortality. We did not find effect modification by individual characteristics (sex, age, employment, hospitalization days). However, this study suggested differences in risk of death for people with preexisting conditions (thrombosis, cardiovascular diseases, asthma, diabetes and thyroid affections), season of death (May-September vs October-April) and levels of built-up area in the neighborhood (for NO2).
CONCLUSIONS: This work provided evidence for the adverse health effects of air pollution and contributed to the identification of specific population groups. These findings can help to better define public-health interventions and prevention strategies.
METHODS: We used a time-stratified case-crossover design with conditional logistic regressions to assess the relationship between mortality and air pollution in the nine largest Belgian agglomerations. Then, we performed a random-effect meta-analysis of the pooled results and described the global air pollution-mortality association. We carried out stratified analyses by individual characteristics (sex, age, employment, hospitalization days and chronic preexisting health conditions), living environment (levels of population density, built-up areas) and season of death to identify effect modifiers of the association.
RESULTS: The study included 304,754 natural deaths registered between 2010 and 2015. We found percentage increases for overall natural mortality associated with 10 μg/m3 increases of air pollution levels of 0.6% (95% CI: 0.2%, 1.0%) for PM2.5, 0.4% (0.1%, 0.8%) for PM10, 0.5% (-0.2%, 1.1%) for O3, 1.0% (0.3%, 1.7%) for NO2 and 7.1% (-0.1%, 14.8%) for black carbon. There was also evidence for increases of cardiovascular and respiratory mortality. We did not find effect modification by individual characteristics (sex, age, employment, hospitalization days). However, this study suggested differences in risk of death for people with preexisting conditions (thrombosis, cardiovascular diseases, asthma, diabetes and thyroid affections), season of death (May-September vs October-April) and levels of built-up area in the neighborhood (for NO2).
CONCLUSIONS: This work provided evidence for the adverse health effects of air pollution and contributed to the identification of specific population groups. These findings can help to better define public-health interventions and prevention strategies.