We utilize a time-series semi-parametric Poisson regression approach, incorporating natural cubic splines for temperature, to study the short-term associations between PM 10 and daily mortality due to cardiovascular, respiratory, and… Click to show full abstract
We utilize a time-series semi-parametric Poisson regression approach, incorporating natural cubic splines for temperature, to study the short-term associations between PM 10 and daily mortality due to cardiovascular, respiratory, and cardiorespiratory events for seven municipalities in Mexico City Metropolitan Area (2001-2013). Our results demonstrate that assessing seasonality, along with temperature variability, is vital in understanding the relationship between air pollution and mortality events. Additionally, our findings support the World Health Organization’s morbidity and mortality threshold for PM 10 within the assessed municipalities. We were able to identify associations between different meteorological seasons and air pollutions effects on mortality. Lastly, we demonstrate that geographical differences are modulating the relationship between air pollutants and mortality for models with and without distributed lagged. Our findings highlight the need for policy-driven approaches that take into consideration the dynamics of meteorological influences and geographic variability in terms of mitigating future deleterious health impacts of air pollutants in facilitating mortality risk.
               
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