Examples of Pulling Census Data and Making Maps

Load R Packages

library(openxlsx)
library(tidyverse)
library(data.table)
library(stringi)
library(pander)
library(psych)

Potentially Useful Links Related to Geolocation, Area-Level Data, US Census, and Mapping

• http://eglenn.scripts.mit.edu/citystate/tag/r/
• http://www.city-data.com
• https://www1.nyc.gov/assets/doh/downloads/pdf/data/2015chp-qn01.pdf
• https://rconsortium.github.io/censusguide/
• https://m.usps.com/m/ZipLookupAction
• https://geomap.ffiec.gov/FFIECGeocMap/GeocodeMap1.aspx
• https://gps-coordinates.org
• https://geocoding.geo.census.gov/geocoder/locations/onelineaddress
• https://rpubs.com/jhofman/nycmaps

Working with Census Data in R
Julia Silge on tidycensus
Lookup US Census American Community Survey (ACS) Variables Here
Components of Geographic Identifiers (GEOIDs)
Setting Up a Census API Key to Facilitate Pulling Census Data Directly into R

library(tigris)
library(dplyr)
library(leaflet)
library(sp)
library(ggmap)
library(maptools)
library(broom)
library(httr)
library(rgdal)
library(tidyverse)
library(tidycensus)
library(sf)
library(kableExtra)

options(tigris_use_cache = TRUE)

Individuals with Person and Place Characteristics

indiv <- readRDS("indiv.rds")

head(indiv) %>%
  kbl() %>%
  kable_paper(full_width = FALSE)

PID	Gender	GEOID	CTract	cen_long	cen_lat
1	M	12071000700	700	-81.87042	26.63124
2	M	34001001100	1100	-74.43150	39.36434
3	M	36005001900	1900	-73.91160	40.80433
4	M	36005001900	1900	-73.91160	40.80433
5	M	36005002500	2500	-73.91855	40.80727
6	F	36005002702	2702	-73.91396	40.80654

Obtain Geometry of Census Tracts in the NYC Area

nyc_tracts <- tracts(state = '36', county = c('061','047','081','005','085','059','119'))

A Map of NYC with a Single Location Marked

leaflet(nyc_tracts) %>%
  addTiles() %>% 
  addCircleMarkers(~-73.9973, ~40.7308, radius = 5, color = "green") %>%
  setView(-73.8740, 40.7769, zoom = 11.45)

Pull Four Variables from the Most Recent American Community Survey (ACS)

nyc_struc <- get_acs(geography = "tract", 
                     variables = c("B06009_001", "B06009_002",
                                   "B17001_001", "B17001_002"), 
                     state = "36",
                     county = c("005","047","061","081","085","059","119"),
                     geometry = TRUE,
                     output = "wide") %>% 
mutate(pct_poverty = B17001_002E/B17001_001E,
       pct_noHS = B06009_002E / B06009_001E)

nyc_struc$CTract <- as.numeric(substr(nyc_struc$GEOID, 6, 11))

nyc_struc <- na.omit(nyc_struc)

Map Showing Proportion of Adults without High School Diploma by Census Tract (All of NYC)

pal <- colorNumeric(palette = "viridis", 
                    domain = nyc_struc$pct_noHS)

nyc_struc %>%
    st_transform(crs = "+init=epsg:4326") %>%
    leaflet(width = "100%") %>%
    addProviderTiles(provider = "CartoDB.Positron") %>%
    addPolygons(popup = ~ str_extract(NAME, "^([^,]*)"),
                stroke = FALSE,
                smoothFactor = 0,
                fillOpacity = 0.7,
                color = ~ pal(pct_noHS)) %>%
    addLegend("bottomright", 
              pal = pal, 
              values = ~ pct_noHS,
              title = "No High School Diploma",
              opacity = 1)

Merge Data on People, Their Chacteristics and Locations with Census Tract and Geographic Data

nyc_struc <- merge(nyc_struc, indiv, by = c("GEOID", "CTract"))

nyc_struc$Gender <- factor(nyc_struc$Gender)

A Map of NYC with Many Locations Marked

leaflet(nyc_struc) %>%
  addTiles() %>%
  addCircleMarkers(~cen_long, ~cen_lat, radius = 1, 
                   color = ~ifelse(Gender == "M", "navy", "red"), fillOpacity = 0.5) %>%
  addCircleMarkers(~-73.9973, ~40.7308, radius = 5, color = "green") %>%
  setView(-73.8740, 40.7769, zoom = 11.45)

Some Resources Related to Area-Level Deprivation Measures

Miller, R. L., Strzyzykowski, T., Lee, K. S., Chiaramonte, D., Acevedo-Polakovich, I., Spring, H., … & Ellen, J. M. (2018). Structural Effects on HIV Risk Among Youth: A Multi-level Analysis. AIDS and Behavior, 1-17.

Neighborhood poverty

1. percent of households at or below poverty level
2. percent of households single-parent female-headed
3. percent of adult residents without high school diploma
4. percent of residents over age 16 and unemployed
5. percent of homes vacant
6. percent of households not affluent

Social Determinants of Health in CDC HIV Surveillance Report

1. Federal poverty status: proportion of residents in the census tract who were living below the U.S. poverty level (i.e., below a specified threshold) at any time during the 12 months before the survey response (individuals aged 18 years and older)
2. Education level: proportion of residents in the census tract with less than a high school diploma (individuals aged 18 years and older)
3. Median household income: median income for a household within the census tract during the 12 months before the survey response
4. Employment status: proportion of residents in the census tract in the workforce without a job (individuals aged 16 years and older)
5. Health insurance coverage: proportion of residents in the census tract without health insurance or health coverage plan (individuals aged 18 years and older)
6. Vacant housing: the proportion of housing units in the census tract that were vacant at the time of the survey response

Messer, L. C., Laraia, B. A., Kaufman, J. S., Eyster, J., Holzman, C., Culhane, J., … & O’campo, P. (2006). The development of a standardized neighborhood deprivation index. Journal of Urban Health, 83(6), 1041-1062.

Creating a Deprivation Index in R using Census estimates