ArticleBMC public health2026
The importance of investigating temporal variability in short-term effects of air pollution on mortality at the local level: a 12-year study in a high-risk Italian area.
Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundCurrent evidence on short-term effects of air pollution on mortality often overlooks potential temporal variation and non-linear exposure-response relationships, bringing to biased effect estimates and limited accuracy of health risk assessments.
methodsLeveraging high-quality daily environmental data from local air quality monitoring stations, we examined temporal changes and non-linear associations between daily concentrations of PM10, PM2.5, NO2, and SO2 and mortality from natural, cardiovascular, and respiratory causes in a high-risk area surrounding the city of Florence (Italy), from 2008 to 2019. Missing environmental data were handled through multiple imputation. For each air pollutant, we fitted Poisson regression models assuming: (1) a linear effect which was constant over time, (2) a linear effect allowed to flexibly vary over the study period, and (3) a non-linear effect which was constant over time. Regression splines were used to model non-linearities.
resultsDuring the entire period, we found that higher levels of PM2.5, and SO2 were associated with increased mortality. These effects were time-varying, with a peak observed during 2012–2015, despite lower pollutant concentrations. Only PM2.5 exhibited a non-linear relationship with natural and cardiovascular mortality, with greater effects at higher concentrations. The effects of NO2 were minimal.
conclusionsIn the study area, the harmful effects of air pollution did not decline over time despite decreasing pollutant concentrations. This pattern may reflect changes in airborne particles composition, possibly linked to variations in traffic and major infrastructures development, or complex interactions with meteorological factors. Our findings highlight the need of high-quality local studies to disentangle complex exposure-response dynamics and support effective, context-specific regulatory decisions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.