Monthly-Term Associations Between Air Pollutants and Respiratory Morbidity in South Brazil 2013-2016: A Multi-City, Time-Series Analysis.
Dayana Milena Agudelo-CastañedaElba Calesso TeixeiraLarissa AlvesJulián Alfredo Fernández NiñoLaura Andrea Rodriguez-VillamizarPublished in: International journal of environmental research and public health (2019)
Most air pollution research conducted in Brazil has focused on assessing the daily-term effects of pollutants, but little is known about the health effects of air pollutants at an intermediate time term. The objective of this study was to determine the monthly-term association between air pollution and respiratory morbidity in five cities in South Brazil. An ecological time-series study was performed using the municipality as the unit of observation in five cities in South Brazil (Gravataí, Triunfo, Esteio, Canoas, and Charqueadas) between 2013 and 2016. Data for hospital admissions was obtained from the records of the Hospital Information Service. Air pollution data, including PM10, SO2, CO, NO2, and O3 (µg/m3) were obtained from the environmental government agency in Rio Grande do Sul State. Panel multivariable Poisson regression models were adjusted for monthly counts of respiratory hospitalizations. An increase of 10 μg/m3 in the monthly average concentration of PM10 was associated with an increase of respiratory hospitalizations in all age groups, with the maximum effect on the population aged between 16 and 59 years (IRR: Incidence rate ratio 2.04 (95% CI: Confidence interval = 1.97-2.12)). For NO2 and SO2, stronger intermediate-term effects were found in children aged between 6 and 15 years, while for O3 higher effects were found in children under 1 year. This is the first multi-city study conducted in South Brazil to account for intermediate-term effects of air pollutants on respiratory health.
Keyphrases
- air pollution
- preterm infants
- healthcare
- particulate matter
- heavy metals
- gestational age
- mental health
- public health
- emergency department
- human health
- health information
- risk assessment
- physical activity
- young adults
- big data
- climate change
- cystic fibrosis
- chronic obstructive pulmonary disease
- social media
- deep learning
- life cycle