Measuring changes in neighborhood disorder using Google Street View longitudinal imagery: a feasibility study

ABSTRACT

Few studies have used longitudinal imagery of Google Street View (GSV) despite its potential for measuring changes in urban streetscape characteristics relevant to health, such as neighborhood disorder. Neighborhood disorder has been previously associated with health outcomes. We conducted a feasibility study exploring image availability over time in the Philadelphia metropolitan region and describing changes in neighborhood disorder in this region between 2009, 2014, and 2019. Our team audited Street View images from 192 street segments in the Philadelphia Metropolitan Region. On each segment, we measured the number of images available through time, and for locations where imagery from more than one time point was available, we collected eight neighborhood disorder indicators at three different times (up to 2009, up to 2014, and up to 2019). More than 70% of the streets segments had at least one image. Neighborhood disorder increased between 2009 and 2019. Future studies should study the determinants of change of neighborhood disorder using longitudinal GSV imagery.

KEYWORDS:

• Geographic factors
• longitudinal studies
• observation
• pedestrians
• residence characteristics

This article is related to:

Research for city practice

Acknowledgements

We would like to thank all the students that helped us with data collection. This work was supported by the National Institute of Aging (R56AG049970, DP1AG069870-011), the Eunice K. Shriver National Institute of Child Health and Human Development (R21HD062965-02), a generous gift from Dana and David Dornsife to the Drexel University Dornsife School of Public Health, the Urban Health Collaborative at Drexel University, and the Built Environment and Health Research Group at Columbia University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/23748834.2023.2207931.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

The work was supported by the Fundación Alfonso Martín Escudero [2018 Postdoctoral fellowship]; Health and Environmental Sciences Institute [R01ES030994]; National Heart, Lung, and Blood Institute [R01HL148431]; National Institute on Aging of the National Institutes of Health [R56 AG049970].

Notes on contributors

Pedro Gullon

Pedro Gullón, PhD MPH MD is an Assistant Professor of Public Health at the University of Alcalá. His research interests are how cities and neighborhoods shape health inequalities, and the intersection of macro determinants of health with urban health inequalities.

Dustin Fry

Dustin Fry, PhD, MPH is a postdoctoral researcher at the USDA Forest Service, Philadelphia Field Station. His research focuses on the relationship between neighborhood environments and health outcomes with a particular interest in the use of novel data sources to explore policy-relevant research questions.

Jesse J. Plascak

Dr. Jesse J. Plascak is an Assistant Professor of Cancer Prevention and Control within the Ohio State University College of Medicine. He leads two National Institutes of Health research projects that both investigate the role of social and built environment characteristics on cancer disparities. One project focuses on breast cancer survival and whether epigenomic mechanisms might be involved in associations between social and built environment factors and cancer outcomes. A separate project is investigating relationships between time-varying built environment factors colon and rectum cancer outcomes. Together, these projects will lead to better understanding of neighborhood factors and cancer outcomes.

Stephen J. Mooney

Stephen Mooney is an Assistant Professor of Epidemiology at the University of Washington, where his research focuses on epidemiologic methods for the use of Big Data to study the relationship of place and health. He has been exploring uses of Google Street View for neighborhood measurement since 2010.

Gina S. Lovasi

Gina S. Lovasi, PhD, MPH is Dornsife Associate Professor of Urban Health in the Department of Epidemiology and Biostatistics and Associate Dean for Education at Drexel University Dornsife School of Public Health. Her ongoing NIA-funded project is a longitudinal investigation of local retail establishments and their implications for cardiovascular disparities and aging across the US. Dr. Lovasi is MPI of an NIMHD-funded T-37 training grant entitled Global Alliance for Training in Health Equity Research. She has authored more than 130 peer-reviewed articles and co-edited the book Urban Public Health: A Research Toolkit for Practice and Impact (Oxford University Press, 2020).