RESUMO
OBJECTIVE: The present study aimed to determine the association between chronic exposure to fine particulate matter (PM2.5), sociodemographic aspects, and health conditions with COVID-19 mortality in Colombia. METHODS: We performed an ecological study using data at the municipality level. We used COVID-19 data obtained from government public reports up to and including July 17th, 2020. We defined PM2.5 long-term exposure as the 2014-2018 average of the estimated concentrations at municipalities obtained from the Copernicus Atmospheric Monitoring Service Reanalysis (CAMSRA) model. We fitted a logit-negative binomial hurdle model for the mortality rate adjusting for sociodemographic and health conditions. RESULTS: Estimated mortality rate ratios (MRR) for long-term average PM2.5 were not statistically significant in either of the two components of the hurdle model (i.e., the likelihood of reporting at least one death or the count of fatal cases). We found that having 10% or more of the population over 65 years of age (MRR = 3.91 95%CI 2.24-6.81), the poverty index (MRR = 1.03 95%CI 1.01-1.05), and the prevalence of hypertension over 6% (MRR = 1.32 95%CI1.03-1.68) are the main factors associated with death rate at the municipality level. Having higher hospital beds capacity is inversely correlated to mortality. CONCLUSIONS: There was no evidence of an association between long-term exposure to PM2.5 and COVID-19 mortality rate at the municipality level in Colombia. Demographics, health system capacity, and social conditions did have evidence of an ecological effect on COVID-19 mortality. The use of model-based estimations of long-term PM2.5 exposure includes an undetermined level of uncertainty in the results, and therefore they should be interpreted as preliminary evidence.