georgia {geostan} | R Documentation |
Georgia all-cause, sex-specific mortality, ages 55-64, years 2014-2018
Description
A simple features (sf) object for Georgia counties with sex- and age-specific deaths and populations at risk (2014-2018), plus select estimates (with standard errors) of county characteristics. Standard errors of the ICE were calculated using the Census Bureau's variance replicate tables.
Usage
georgia
Format
A simple features object with county geometries and the following columns:
- GEOID
Six digit combined state and county FIPS code
- NAME
County name
- ALAND
Land area
- AWATER
Water area
- population
Census Bureau 2018 county population estimate
- white
Percent White, ACS 2018 five-year estimate
- black
Percent Black, ACS 2018 five-year estimate
- hisp
Percent Hispanic/Latino, ACS 2018 five-year estimate
- ai
Percent American Indian, ACS 2018 five-year estimate
- deaths.male
Male deaths, 55-64 yo, 2014-2018
- pop.at.risk.male
Population estimate, males, 55-64 yo, years 2014-2018 (total), ACS 2018 five-year estimate
- pop.at.risk.male.se
Standard error of the pop.at.risk.male estimate
- deaths.female
Female deaths, 55-64 yo, 2014-2018
- pop.at.risk.female
Population estimate, females, 55-64 yo, years 2014-2018 (total), ACS 2018 five-year estimate
- pop.at.risk.female.se
Standard error of the pop.at.risk.female estimate
- ICE
Index of Concentration at the Extremes
- ICE.se
Standard error of the ICE estimate, calculated using variance replicate tables
- income
Median household income, ACS 2018 five-year estimate
- income.se
Standard error of the income estimate
- college
Percent of the population age 25 or higher than has a bachelors degree of higher, ACS 2018 five-year estimate
- college.se
Standard error of the college estimate
- insurance
Percent of the population with health insurance coverage, ACS 2018 five-year estimate
- insurance.se
Standard error of the insurance estimate
- rate.male
Raw (crude) age-specific male mortality rate, 2014-2018
- rate.female
Raw (crude) age-specific female mortality rate, 2014-2018
- geometry
simple features geometry for county boundaries
Source
Centers for Disease Control and Prevention, National Center for Health Statistics. Underlying Cause of Death 1999-2018 on CDC Wonder Online Database. 2020. Available online: https://wonder.cdc.gov/ (accessed on 19 October 2020).
Donegan, Connor and Chun, Yongwan and Griffith, Daniel A. (2021). “Modeling community health with areal data: Bayesian inference with survey standard errors and spatial structure.” Int. J. Env. Res. and Public Health 18 (13): 6856. DOI: 10.3390/ijerph18136856 Data and code: https://github.com/ConnorDonegan/survey-HBM.
Kyle Walker and Matt Herman (2020). tidycensus: Load US Census Boundary and Attribute Data as 'tidyverse' and 'sf'-Ready Data Frames. R package version 0.11. https://CRAN.R-project.org/package=tidycensus
US Census Bureau. Variance Replicate Tables, 2018. Available online: https://www.census.gov/programs-surveys/acs/data/variance-tables.2018.html (accessed on 19 October 2020).
Examples
data(georgia)
head(georgia)
library(sf)
plot(georgia[,'rate.female'])