Quantifying the health benefits of transit-oriented development: Creation and application of the San Diego Public Health Assessment Model (SD-PHAM)

Elsevier, Transport Policy, Volume 115, January 2022
Authors: 
Frank L.D., Fox E.H., Ulmer J.M., Chapman J.E., Braun L.M.
As evidence of the health impacts of transportation investments has grown, planners have increasingly used health impact assessments (HIAs) to evaluate transportation plans, projects, and policies. Most HIAs to date, however, have been limited in their ability to quantify health impacts due to a lack of validated methods and tools, scarcity of disaggregate and locally-relevant data, and cost. This paper presents the development and application of a quantitative HIA tool designed to address these and other common limitations of existing HIAs. Developed through a grant from the San Diego Association of Governments and the San Diego County Health and Human Services, the tool is based on detailed modeled regression analyses associating the built environment with physical activity, safety, diabetes, hypertension, and asthma in a large sample of California Health Interview Survey participants. The tool allows users to enter built environment characteristics for baseline and future development scenarios and estimate corresponding health impacts. This paper describes the development of this tool and its application to the Palomar Gateway District rail transit station area in San Diego County. The results suggest that plan-endorsed projected build-out is associated with increased physical activity from walking for transportation, park visitation, and reductions in type 2 diabetes and high blood pressure. Potential for increased exposure to air pollution among children and teens may, however, attenuate some of these benefits. Quantifying both the positive and the negative health outcomes of transportation investments can inform proposals and reduce health risks. This study demonstrates how the application of an evidence-based software tool can support the HIA process and create empirical evidence useable within transportation decisions and planning practice.