City-Specific Air Quality Warnings for Improved Asthma Self-Management

Abstract

Introduction: This study presents a framework for identifying "high-risk" days for asthma attacks associated with elevated concentrations of criteria pollutants using local information to warn citizens on days when the concentrations differ from Environmental Protection Agency Air Quality Index (AQI) warnings. Studies that consider the unique mixture of pollutants and the health data specific to a city provide additional information for asthma self-management. This framework is applied to air pollution and asthma data to identify supplemental warning days in Houston, Texas. Methods: A four-step framework was established to identify days with pollutant levels that pose meaningful increased risk for asthma attacks compared with baseline. Historical associations between 18,542 ambulance-treated asthma attacks and air pollutant concentrations in Houston, Texas (2004−2016; analyzed in 2018), were analyzed using a case-crossover study design with conditional logistic regression. Days with historically high associations between pollution and asthma attacks were identified as supplemental warning days. Results: Days with 8-hour maximum ozone >66.6 parts per billion for the 3 previous days and same-day 24-hour nitrogen dioxide >19.3 parts per billion pose an RR of 15% above baseline; concentrations above these levels pose an increased risk of 15% (RR=1.15, 95% CI=1.14, 1.16) and 30% (RR=1.30, 95% CI=1.29, 1.32), respectively. These warnings add an additional 12% days per year over the AQI warnings. Conclusions: Houston uses this framework to identify supplemental air quality warnings to improve asthma self-management. Supplemental days reflect risk lower than the National Ambient Air Quality Standards and consecutive poor air quality days, differing from the AQI.

A simple tree planting framework to improve climate, air pollution, health, and urban heat in vulnerable locations using non‐traditional partners

“…The gray‐shaded area indicates locations in the city where the average concentration of PM 2.5 pollution are in the upper quartile of PM 2.5 compared with the rest of the city (Figure 3a) (TCEQ, 2019) (none of the other pollutants assessed [NO 2 , O 3, SO 2 ] had average concentrations in the upper quartile compared to the rest of the city). The red hatched area indicates locations in the city in the high rate region (upper quartile compared with the rest of the city) for cardiac arrest and asthma attack (Figure 3b) (Ensor et al, 2013; Raun et al, 2013, 2019). The blue hatched area indicates locations in the city in the upper quartile of the proportion of a census block that flooded during Hurricane Harvey (Figure 3c).…”

“…The health department created the maps indicating areas of the city cardiac arrest and asthma attack (Figure 3b) (Ensor et al, 2013;Raun et al, 2013Raun et al, , 2019. The blue hatched area indicates locations in the city in the upper quartile of the proportion of a census block that flooded during Hurricane Harvey (Figure 3c).…”

“…In the third and final part, educating partners in non-traditional sectors, such as health professionals, on the connection between climate change and health can expand those working to mitigate climate change. In the example above, educating the health researchers that found the link between air pollution and adverse health effects in Houston regarding the potential that climate change could increase pollution and thus further exacerbate the health effects of concern (Ensor et al, 2013;Raun et al, 2013Raun et al, , 2019 provides the catalyst for the health researchers to actively join in climate change mitigation.…”

A spatiotemporal case‐crossover model of asthma exacerbation in the City of Houston

“…In addition to circumventing the difficulty in selecting a representative control group, using cases as their own controls means that subject‐dependent nuisance factors can be eliminated. These benefits are part of what makes a case‐crossover design an attractive approach for many epidemiological applications (Raun, Ensor, Pederson, Campos, & Persse, 2019 ; Sato et al, 2018 ).…”

Genomics-based deconvolution of multiplexed transcriptional responses to wood smoke particles defines rapid AHR signaling dynamics

“…vehicle emissions and large stationary sources). Instead, general air quality-based warnings and cautions (7), which are issued on a regional basis when pollution exceeds standard PM thresholds (8)(9)(10)(11), are the primary measure used to mitigate health effects of wildfire smoke. Although these daily warnings are useful for alerting impacted populations of potential health risks, they lack granular information regarding toxicity (7,12,13).…”