A neighborhood-level potential health impact scoring tool to support local-level health impact assessments

ABSTRACT

Health Impact Assessments (HIAs) have quickly become a widely utilized tool for integrating health and health-related evidence and data into decision-making processes across a range of projects and policies. Integrating and utilizing a wide range of available data can be daunting. To support communities seeking to engage in health impact assessments, we developed the Neighborhood Potential Health Impact Score (NPHIS) methodology. We present the NPHIS method’s four-step process, and how this process was applied to an HIA focusing on the rebuilding of public housing following a natural disaster. We discuss developing the boundary definition, selection and definition of indicators, calculation of the NPHIS, and interpretation and utilization of the scores. Findings were validated using feedback from a community stakeholder advisory board as well as through feedback collected from focus groups of community residents. NPHIS methodology has proven to be a useful resource in better understanding the complex sources of potential health impacts facing communities, and in being an evidence-based, data-driven resource for HIA decision-makers and their stakeholders in our specific application. Other groups seeking to integrate similar data into their decision-making processes could benefit from replicating the NPHIS in their efforts.

KEYWORDS:

• Health impact assessment (HIA)
• community health assessment
• neighborhood health
• cumulative risk

This article is related to:

Research for city practice

Acknowledgments

The development of this manuscript was funded in part by the Texas Medical Center’s Health Policy Institute and by NIEHS Center Grant P30 ES006676. This project was also supported by a grant from the Health Impact Project, a collaboration of the Robert Wood Johnson Foundation and The Pew Charitable Trusts with funding from The Kresge Foundation.

The authors would like to thank Alexandra Nolen, Jimmy Dills, Elizabeth Fuller, Holly Avey, Christen Miller, Erin Ruel, Michelle Rushing, and Deirdre Oakley for their valuable contributions in helping to develop, refine, apply, and evaluate this method. We would also like to thank the members of the community steering committee for their time and input in applying the NPHIS to this project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Institute of Environmental Health Sciences [P30 ES006676];Pew Charitable Trusts [N/A].

Notes on contributors

John D. Prochaska

John D. Prochaska, DrPH, MPH, is an Assistant Professor in the Department of Preventive Medicine & Community Health at the University of Texas Medical Branch (UTMB). His primary research interests lie in understanding the interactions of multiple determinants of health and health disparities in vulnerable populations and communities. Previously, Dr. Prochaska worked in the UTMB Center to Eliminate Health Disparities focusing on impacts of natural disasters on community and neighborhood-level social and environmental determinants of health. Dr. Prochaska received his doctorate and masters degrees in public health from the Texas A&M University System Health Science Center in College Station, Texas.

Robert N. Buschmann

Robert N. Buschmann obtained his Ph.D. in Population Health Sciences from the University of Texas Medical Branch. His post-doctoral training was in community-based research in the Community-University Partnership for the Study of Children, Youth, and Families (CUP) at the University of Alberta in Edmonton, Alberta. He is currently a research associate at CUP, focusing on improving early learning and care with a 30-year initiative to end poverty in Edmonton. Previous to his current position, he worked in community-based health research and public policy analysis and research. His research interests include early learning and care, childhood adversity, and social determinants of health.

Daniel C. Jupiter

Daniel C. Jupiter obtained his Ph.D. in Mathematics from the University of Michigan. His post-doctoral training positions were in pure mathematics at Texas A&M University and bioinformatics at the Texas A&M Health Science Center. More recently, he was a Research Scientist and Assistant Professor in the Surgery Department at Scott & White Memorial Hospital and Texas A&M Health Science Center College of Medicine. He has been an Assistant/Associate Professor in Preventive Medicine and Community Health at the University of Texas Medical Branch since 2014. His research interests include lower extremity complications of diabetes, and, more recently, geographic variation in healthcare.