Risk communication, respiratory health risks, and air pollution forecasting in the city of Rio de Janeiro, Brazil

ABSTRACT

Objective:  Although communicating air pollution risks is critical for protecting public health, particularly in low- and middle-income countries (LMICs), its effectiveness remains underexplored. This study evaluated current risk communication practices in the city of Rio de Janeiro, Brazil, by assessing the associations between short-term exposure to pollutants and respiratory-related hospital admissions; the ability of the Brazilian national índice de qualidade do ar (IQAr, air quality index) to reflect health risks; and the accuracy of pollutant forecasts in comparison with monitored concentrations.

Methods:  Exposure and health data for the 2014-2019 period were obtained through a research partnership with local government officials. Poisson generalized linear models were employed to determine whether IQAr values and short-term exposure to air pollutants, including nitrogen dioxide (NO₂) and particulate matter (PM), were associated with daily hospital admissions for respiratory disease. Bias-corrected, forecasted daily concentrations of individual air pollutants from the Goddard Earth Observing System Composition Forecast Composition Forecast (GEOS-CF) model were employed to assess the performance of existing forecasting tools for use in risk communication.

Results:  Significant associations were consistently observed between hospital admissions for respiratory disease and short-term exposures to NO₂ and coarse PM, with excess risks of 5.1% (95% CI: 1.3-8.9%) and 5.6% (95% CI: 1.5-9.9%), respectively, per interquartile range increases in lag day 0-1 exposures. Values of IQAr were not significantly associated with respiratory health events, likely due to their failure to capture the health risks associated with NO₂. Bias-corrected forecasts from the GEOS-CF model showed strong correlations with observed pollutant concentrations.

Conclusions:  These findings indicate that adopting a health-based, multi-pollutant index, combined with improved forecasting tools, could substantially strengthen risk communication in the city of Rio de Janeiro and other LMIC settings.

Keywords:
Air pollutants/analysis; Air pollution/adverse effects; Nitrogen dioxide; Particulate matter; Developing countries; Respiratory tract diseases/epidemiology