Close the left navigation

Environmental Health Economic Analysis Annotated Bibliography

Go Back

Details

Research article
Authors

Plascak JJ, Schootman M, Rundle AG, Xing C, Llanos AAM, Stroup AM, Mooney SJ

Journal

International Journal of Health Geographics

Summary
The authors used a point-based virtual neighborhood audit method to spatially autocorrelate built environment and compared it to virtual neighborhood that was audited by trained professionals. The authors found that the spatially autocorrelated audit items were well-predicted using regression Kriging spatial models and that predicted responses to neighborhood physical disorder-related items correlated strongly with one another, especially within the areas of racial-ethnic compostion, socioeconomic indicators, and residential mobility.
Population

Not available

Health Outcomes

  • Not available

Health Outcome List:

  • Not available

Environmental Agents

List of Environmental Agents:

  • Built environment

Source of Environmental Agents:

  • Built environment

Economic Evaluation / Methods and Source

Type:

  • Not available

Cost Measures:

  • Not available

Potential Cost Measures:

  • Not available

Benefits Measures:

  • Not available

Potential Benefits Measures:

  • Not available

Location:

  • Essex County, New Jersey

Models Used:

  • Nested semivariograms and regression Kriging
  • Receiver Operator Curve (ROC) Area Under the Curve (AUC)
  • isostropic, Gaussian kernel
  • nonparametric, spatially varying probability surfaces
  • semivariograms of deviance residuals
  • Local Ordinary Kriging (OK)
  • root mean squared prediction error (RMSPE)

Models References:

  • Not available

Methods Used:

  • The authors — 1) conducted a virtual visual audit of Essex County, New Jersey and surrounding areas, looking at the built environment characteristics on non-highway streets; and 2) compared spatial properties prediction to what their auditors found using statistical analysis.

Sources Used:

  • Google Street View (GSV); CANVAS virtual audit tool (Bader et al., 2015); Census; Additional sources cited in the publication.

Economic Citation / Fundings

Citation:

  • Plascak JJ, Schootman M, Rundle AG, Xing C, Llanos AAM, Stroup AM, Mooney SJ. Spatial Predictive Properties of Built Environment Characteristics Assessed by Drop-and-spin Virtual Neighborhood Auditing. International Journal of Health Geographics. 2020. 19; 1.
  • Pubmed
  • DOI

NIEHS Funding:

  • P30ES005022

Other Funding:

  • R01HD087460, K07CA222158, P30CA072720, P2CHD058486, K99LM012868