Development of a community severance index for urban areas in the United States: A case study in New York City

Environ Int. 2024 Mar:185:108526. doi: 10.1016/j.envint.2024.108526. Epub 2024 Feb 28.

Abstract

Background and aims: Traffic-related exposures, such as air pollution and noise, have a detrimental impact on human health, especially in urban areas. However, there remains a critical research and knowledge gap in understanding the impact of community severance, a measure of the physical separation imposed by road infrastructure and motorized road traffic, limiting access to goods, services, or social connections, breaking down the social fabric and potentially also adversely impacting health. We aimed to robustly quantify a community severance metric in urban settings exemplified by its characterization in New York City (NYC).

Methods: We used geospatial location data and dimensionality reduction techniques to capture NYC community severance variation. We employed principal component pursuit, a pattern recognition algorithm, combined with factor analysis as a novel method to estimate the Community Severance Index. We used public data for the year 2019 at census block group (CBG) level on road infrastructure, road traffic activity, and pedestrian infrastructure. As a demonstrative application of the Community Severance Index, we investigated the association between community severance and traffic collisions, as a proxy for road safety, in 2019 in NYC at CBG level.

Results: Our data revealed one multidimensional factor related to community severance explaining 74% of the data variation. In adjusted analyses, traffic collisions in general, and specifically those involving pedestrians or cyclists, were nonlinearly associated with an increasing level of Community Severance Index in NYC.

Conclusion: We developed a high spatial-resolution Community Severance Index for NYC using data available nationwide, making it feasible for replication in other cities across the United States. Our findings suggest that increases in the Community Severance Index across CBG may be linked to increases in traffic collisions in NYC. The Community Severance Index, which provides a novel traffic-related exposure, may be used to inform equitable urban policies that mitigate health risks and enhance well-being.

Keywords: Akaike information criterion (AIC); Annual Average Daily Traffic (AADT); Bureau of Transportation Statistics (BTS, US Department of Transportation, US-DOT); Census Block Group (CBG); Database of Road Transportation Emissions (DARTE); Federal Highway Administration (FHWA); Generalized Additive Model (GAM); New York City (NYC); OpenStreetMap (OSM); US Environmental Protection Agency (US-EPA); United States (US).

MeSH terms

  • Accidents, Traffic
  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • Cities
  • Humans
  • New York City
  • Noise
  • United States

Substances

  • Air Pollutants