Identifying environmental drivers of asthma hotspots in Louisville, Kentucky, using sensors to capture spatially-explicit, real-time data on inhaler use: AIR Louisville program

Background

Louisville, Kentucky, ranks consistently in the top 20 most challenging places to live with asthma in the US. Local asthma surveillance activities, which rely upon asthma hospitalization reports and national survey prevalence data, do not provide real-time, spatially-explicit information that city leaders need to make intervention decisions.

Objective/purpose

The AIR Louisville program aimed to: 1) identify hotspots of highest density rescue inhaler use; 2) evaluate associations between asthma hotspots and specific environmental, neighborhood and socioeconomic drivers in real-time and space; and 3) generate multivariate models to evaluate the potential impact of public health intervention scenarios.

Methods

Participants (n=140) were enrolled through community locations and tracked their rescue inhaler use for 13 months with a GPS-enabled sensor, which passively collected the date, time and GPS location of each inhaler use. Using GIS and spatial tools, we mapped population-level asthma hotspots and extracted georeferenced environmental, climatic and socioeconomic data for each inhaler event. We modeled daily rescue inhaler use count using space-time resolved covariates through a negative binomial (NB) modeling technique. We developed full negative binomial models that controlled for confounding variables.

Results

Sensors collected 5,430 inhaler events, which were merged with 40 socioeconomic and environmental layers. In the multivariate NB models, significant positive associations with asthma inhaler use were identified with PM10, Air Quality Index, grass pollen, weed pollen, mold, and crime (p< 0.01). Significant negative associations were identified with tree pollen, neighborhood income and property value (p< 0.01). These models will be used to test intervention scenarios by predicting their potential impact on asthma activity.

Discussion/conclusion

Using sensors to track where and when asthma inhaler use occurs can strengthen asthma surveillance, improve understanding of environmental and neighborhood drivers of asthma, help cities target interventions and contribute to a health in all policies approach.

Learning Areas:

Chronic disease management and prevention
Clinical medicine applied in public health
Communication and informatics
Environmental health sciences
Epidemiology
Implementation of health education strategies, interventions and programs

Learning Objectives:
Describe the history of air quality and the current asthma burden in Louisville. Compare the value of sensor-collected asthma data for community asthma surveillance with historic data from national surveys and healthcare utilizations. List the associations between inhaler use and several environmental drivers in Louisville. Identify asthma hotspots across Louisville and Jefferson County.

Keyword(s): Air Pollution & Respiratory Health, Built Environment

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Kelly Henderson, MPH, has 8 years of experience in public health research related to social and environmental determinants of health. She received her Masters in Public Health at the University of California Berkeley and her undergraduate degree at Duke University. She joined Propeller Health as the research coordinator in January 2015.
Any relevant financial relationships? Yes

Name of Organization	Clinical/Research Area	Type of relationship
Propeller Health	Chronic Respiratory Diseas	Employment (includes retainer) and Stock Ownership

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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