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Neighborhood Environmental Vulnerability Index


Citation: The creation of the neighborhood environmental vulnerability index was published in the Journal of Urban Health. The citation is as follows:

Uong S, Zhou J, Lovinsky-Desir S, Albrecht SS, Azan A, Chambers EC, Sheffield PE, Thompson A, Wilson J, Woo Baidal J, Stingone JA. The creation of a multidomain neighborhood environmental vulnerability index across New York City. Journal of Urban Health 2023; 100(5):1007-1023.

Previously, our paper was posted on a preprint server:

Uong SP, Zhou J, Lovinsky-Desir S, et al. The Creation of a Multidomain Neighborhood Environmental Vulnerability Index. medRxiv. Published online January 1, 2022:2022.12.14.22283064. doi:10.1101/2022.12.14.22283064

1. Overview

We developed a Neighborhood Environmental Vulnerability Index (NEVI) to measure vulnerability to environmental pollution using publicly available data. We applied the Toxicological Prioritization Index (ToxPi) to integrate data across different domains, characterize neighborhood vulnerability to environmental pollution in New York City (NYC), and determine if sources of vulnerability varied across neighborhoods.

2. Downloading the NEVI for NYC

The current version of the NEVI for NYC can be downloaded in the data/processed folder. The data file is available in multiple formats at the following spatial scales:

Census tract-level

Zip code-level

nevi plot

3. Folder Structure

We have organized relevant files for the calculation of the NEVI in the following folders:

  • code and instructions: Code for the calculation of the index
  • data:
    • data/raw: data files downloaded before any data cleaning/processing
    • data/processed: data files after any data cleaning/processing or created manually
  • figures and tables: figures and tables created from our code

4. Data Sources

We used two primary data sources for the following features used to calculate the NEVI:

Other data sources used to create zip code-level NEVI:

5. Requirements

You will need the following software, R packages, and data to calculate the NEVI.

5.1 Software and R Packages

  1. Download the following software:
  1. Run the following code in R to install the following packages:
  • These required packages are needed for the creation of the NEVI.
     install.packages(c('tidyverse','tidycensus','rio'), dependencies = TRUE)
    
  • These optional packages are needed for the creation of clusters and figures and tables presented in the manuscript.
     install.packages(c('factoextra','cluster','skimr','janitor','factoextra','sf','ggpubr','ggsn','ggspatial','tigris','ggsflabel','ggpubr','colorBlindness','ggpattern','gplots'), dependencies = TRUE)
     devtools::install_github('yutannihilation/ggsflabel')
    
  1. We used the following versions of software and packages:
  • Software:
    • R: 4.1.1 ("Kick Things")
    • RStudio: 2021.09.0+382 ("Ghost Orchid")
    • ToxPi GUI: version 2.3, August 2019 update
  • Packages:
    • tidyverse: 1.3.1
    • tidycensus: 1.1.2
    • rio: 0.5.29
  • Optional Packages
    • cluster: 2.1.2
    • factoextra: 1.0.7
    • skimr: 2.1.3
    • janitor: 2.1.0
    • sf: 1.0.3
    • ggpubr: 0.4.0
    • ggsn: 0.5.0
    • ggspatial: 1.1.5
    • nycgeo: 0.1.0.9000
    • tigris: 1.5
    • devtools: 2.4.3
    • ggsflabel: 0.0.1
    • ggpubr: 0.4.0
    • colorBlindness: 0.1.9
    • ggpattern: 0.2.0
    • gplots: 3.1.1

5.2 Data

  • U.S. Centers for Disease Control and Prevention PLACES 2020
  • U.S. American Community Survey, 5-year estimates from 2015-2019
    • To download the data, refer to our code: code and instructions/A1-download-census-data.Rmd
    • More information about the American Community 5-year estimates here.

6. Code and Instructions

To calculate the NEVI, you will need to follow the instructions in these documents in the code and instructions folder. Click on the corresponding markdown (.md) files to view the code and instructions directly online.

There are also other code available to accomplish optional tasks:

7. Cloning this Repository with RStudio

Below are steps to clone this repository to your local device with RStudio. Please refer to this link for more information about using git in RStudio.

  1. On top this page, click on Code and copy the link to this git repository (starts with https://github.com/...).
  2. Open RStudio.
  3. In RStudio, click on FileNew Project...Version ControlGit.
  4. Under "Repository URL", paste the link of the git repository.
  5. Under "Project directory name", name your project directory.
  6. Under "Create project as subdirectory of:", select the folder in which you would like your project directory to be located.
  7. Click on Create Project when you are done to clone your repository! This should take a minute or two to complete.

8. Grant Information

The creation of this index was conducted under contract to the Health Effects Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. CR-83998101) and certain motor vehicle and engine manufacturers (#4985-RFA20-1B/21-8). The contents of this repository do not necessarily reflect the views of HEI, or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Additional funding was received from the Robert Wood Johnson Foundation (Amos Medical Faculty Development Award) and National Institutes of Health National Institute of Environmental Health Sciences (T32ES007322, R00ES027022, P30ES023515, and R01ES030717), National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111022), and National Heart, Lung, and Blood Institute (K01HL140216).

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