Smog in the Classroom: Power Plant Emissions, Pediatric Asthma, and School Attendance – A New Strategy

Adverse educational outcomes have been repeatedly linked to recurring school absenteeism, which are exacerbated by chronic illness. Asthma is the most prevalent pediatric chronic illness and is the leading cause of health-related school absenteeism. This study seeks to understand the impacts of coal power plant emissions on asthma aggravation and resulting school absenteeism. Data from a unique, nationally administered pediatric asthma survey are combined with power plant emissions information to estimate the emissions’ impacts on school absenteeism by asthmatic children. These particular data (confidential Behavioral Risk Factor Surveillance System asthma module) have never been exploited in this way, and present a novel large scale investigation into environmental impacts on educational outcomes through air quality. Exogenous wind pattern information and structural corrections for selection bias are used to identify households affected by emissions. Empirical results show a robustly positive relationship between power plant emissions and asthma induced school absences. Moreover, we show that without appropriate identification and controls for self-selection, effects of coal power plant emissions on school absenteeism are underestimated.

This methodology controls for important exogenous factors in a way that is especially useful to researchers who lack easy access to certain detailed information, such as monitor data and power plant characteristics on a national scale, and this presentation explores the ways researchers with limited resources can test hypotheses in an efficient, yet empirically robust, way. Participants will be encouraged to share their views on the burden of data accessibility in their line of work and the feasibility of implementing the methodology presented here. The NEHA community can provide insight on the validity of this approach in various public health and experimental settings as well as suggesting extensions to fields the presenters are unfamiliar with.