Ambient Air Quality Exposure Among CHLA Pediatric Patients

Exposure to poor air quality can adversely impact the health of children and contribute to the development and exacerbation of asthma and other respiratory diseases. Despite the risk that air quality can have on the health of children, knowledge of air quality exposure for children seen across an entire pediatric health system is not known. The purpose of this study is to understand the epidemiology of air quality exposure among all children and children with a diagnosis of asthma seen across the Children’s Hospital Los Angeles from 2017-2023. We conducted this preliminary study through spatial analysis of electronic health records and ambient air quality data, and referenced additional policy and development data retrieved from the  SCAG RDP Content Library . Through overlaying geographic contextual data on social, economic, and environmental exposure data with patient records, our study can educate health care professionals, health system leaders, policymakers, and foster advancement in pediatric health system delivery.

Ambient air pollution has long been linked to respiratory diseases such as asthma. Air quality can be measured through its individual components such as particulate matter and NO 2 . Particulate Matter (PM) contains microscopic solids or liquid droplets that are small enough to be inhaled and impact the upper and lower airways. Particulate matter is measured in microns. For example, PM 2.5 are particulate matter less than 2.5 microns or less. PM can come from a variety of sources including stovetops, indoor pollutants, car emissions, and wood burning. Exposure to poor ambient air quality can lead to adverse respiratory health effects, and children are particularly at risk of developing respiratory diseases such as asthma. To measure air quality, we can look to the concentration of PM 2.5, PM 10 , and NO 2 . Nitrogen Dioxide (NO 2 ) in particular is strongly associated with gas combustion vehicle emissions. According to the National Lung Association, "Monitors show the highest concentrations of outdoor NO  2   in large urban regions such as...Los Angeles" (NLA, 2024). In our preliminary study, we explored the spatial implications of the relationship between ambient PM 2.5 , PM 10 , and NO 2, and the residential address of children seen at a children’s hospital from electronic health records. We also explored the spatial relationship between air quality, patient residential locations, and important geographic environmental factors that contribute to adverse air quality such as proximity to freeways/highways. While children seen at the Children’s Hospital Los Angeles come from all over the United States and from several areas across the world, we focused our initial study on the Los Angeles County region. vehicular traffic.

Despite the risk that air quality can have on the health of children, knowledge of air quality exposure for children seen across an entire pediatric health system is not known. The purpose of this study was to understand the epidemiology of air quality exposure among all children seen across the Children’s Hospital Los Angeles from 2017-2023.

We plan to use our findings to educate and guide healthcare professionals and policymakers to identify and risk-stratify patients that may be at risk for exposure to poor air quality. This key step will allow for healthcare teams and systems to optimize the use of limited resources and maximize the benefit of deploying preventative measures for children at most risk to exposure to poor air quality. This project will also serve as a foundation for future work at the Children’s Hospital Los Angeles to study the association of ambient air quality exposure and respiratory disease diagnoses in children using electronic health records.

With IRB approval, we collected and mapped CHLA patient data January 2017- December 2023. The individual patient records were obtained from the hospital's electronic health records. In compliance with HIPAA regulations, the patient addresses were geocoded using ArcGIS Pro to secure patient information/identities. We obtained air quality data spatial data from Plume Labs and AccuWeather, which provided modeled estimates of PM2.5, PM10, and NO2. Air quality data was then spatially joined with the patient address coordinate points.

To analyze exposure to air quality, we created quantile maps for exposure to PM2.5, PM10, and NO2. Three separate maps were created and categorized amount of exposure to each type of pollution into three quantiles, ranging from high to low.

We then cross examined this data with demographic data showcasing income levels by census tract to understand the possible disparities in exposure to poor air quality based on socioeconomic status.

Overlaying patient data with demographic data and physical features

*Spatial resolutions limited to uphold HIPPA regulations protecting patients' privacy

Methodology: Add census tract and patient points to map so that we can calculate the ratio of patients in the total population of each census tract. To protect patient identities, we multiplied each tract's percentage value by a random amount of noise (0.9-1.1).

Patients + Air Quality are spatially joined and classified into five quantiles ranging from high to low exposure to the specified pollutant. This information is overlaid with the freeway buffers and shown side by side with median household income data to study the relationship between patients' level of air quality exposure , proximity to freeways, and income level.

Results: Slide to observe relationships between exposure to each pollutant and social demographic data modeled via median household income.

• As we can see, low income neighborhoods have higher concentrations of freeway exposure and pollutant exposure.

• Greenspace could mitigate susceptibility to respiratory illness, as trees allow for the carbon sequestration and natural air filtering. By increasing equitable access to greenspace, we can improve ambient air quality exposure and therefore lower risks of respiratory illness in pediatric patients.

This study aims to uncover the social, environmental, and geographic factors that shape health outcomes and accessibility to healthcare services for children. The goal of this study is to explore relationship between socioeconomic status, physical location, and exposure to air quality for all pediatric patients seen at the Children’s Hospital Los Angeles. I hope to leverage spatial analysis by connecting patient data with air quality and demographic data and visualize factors that lead to heightened risks of asthma. Ultimately, this work will be presented to healthcare professionals, health system leaders, and policymakers to foster advancements in targeted preventative healthcare and planning efforts to children at most risk for exposure to poor air quality and respiratory diseases.