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Longitudinal trends in asthma emergency department visits, pollutant and pollen levels, and weather variables in the Bronx from 2001-2008.

David S KorditMarina ReznikCheng-Shiun LeuSunit P Jariwala
Published in: The Journal of asthma : official journal of the Association for the Care of Asthma (2019)
Objective: To evaluate how asthma-related emergency department visits (AREDV), air pollutant levels, pollen counts, and weather variables changed from 2001 to 2008 in the Bronx, NY. Methods: 42,065 daily AREDV values (1 January 2001 to 31 December 2008) were collected using our institution's Clinical Looking Glass software. Daily values of sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), temperature, and humidity were obtained from the National Climatic Data Center's Bronx station. Daily tree pollen counts were obtained from the Armonk counting station near the Bronx. Median values for each variable were analyzed using the Mann-Whitney test to compare 2001-2004 and 2005-2008 values. Simple linear regression examined associations between AREDV and individual pollutants. Due to seasonal variations of the variables, each season was considered separately. Results: There were significant decreases for AREDV, SO2, CO, and humidity for all seasons, and for NO2 in the spring and winter. Significant increases occurred for O3 in the spring, fall, and winter; for temperature in the summer and winter; and for tree pollen in the spring. Significant positive associations were found between AREDV and SO2, CO, NO2, and humidity, respectively, while significant negative associations were found between AREDV and O3 and temperature, respectively. Conclusions: From 2001 to 2008, significant: a) decreases in AREDV, SO2, CO, and humidity for all seasons, and decreases in NO2 for the spring and winter; and b) increases in O3, temperature, and spring tree pollen were observed. By tracking and anticipating environmental and pollutant changes, efforts can be made to minimize AREDV.
Keyphrases
  • emergency department
  • physical activity
  • chronic obstructive pulmonary disease
  • lung function
  • cross sectional
  • big data
  • machine learning
  • allergic rhinitis
  • data analysis
  • human health
  • neural network