georgia: 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

Arguments

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

Examples

Run this code

data(georgia)
head(georgia)

library(sf)
plot(georgia[,'rate.female'])

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