DOI: 10.3886/icpsr39241
title: IPUMS Contextual Determinants of Health (CDOH) Race and Ethnicity Measure: Income Inequity by County, United States, 2005-2022
title: Archival Version

description: The IPUMS Contextual Determinants of Health (CDOH) data series
provides access to measures of disparities, policies, and counts, by state
or county, for historically marginalized populations in the United States
including Black, Asian, Hispanic/Latina/o/e/x, and LGBTQ+ persons, and
women.
The IPUMS CDOH data are made available through ICPSR/DSDR for merging
with the National Couples'
Health and Time Study (NCHAT), United States, 2020-2021 (ICPSR 38417)
by approved restricted data researchers. All other researchers can access
the IPUMS CDOH data via the IPUMS CDOH
website.
Unlike other IPUMS products, the CDOH data are organized into multiple
categories related to Race and Ethnicity, Sexual and Gender Minority,
Gender, and Politics. The measures were created from a wide variety of data
sources (e.g., IPUMS NHGIS, the Census Bureau, the Bureau of Labor Statistics, the Movement Advancement Project, and
Myers Abortion Facility Database).
Measures are currently available for states or counties from approximately
2015 to 2020.
The Race and Ethnicity measure in this release is an indicator of income inequity which is measured using the index of concentration at the extremes (ICE). ICE is a measure of social polarization within a particular geographic unit. It shows whether people or households in a geographic unit are concentrated in privileged or deprived extremes. The privileged group in this study is the number of households with a householder identifying as White alone, not Hispanic or Latino, with an income equal to or greater than $100,000. The deprived group in this study is the number of households with a householder identifying as a different race/ethnic group (e.g., Black alone, Asian alone, Hispanic or Latino), with an income equal to or less than $25,000. To work with the IPUMS CDOH data, researchers will need to use the variable <strong>MATCH_ID</strong> to merge the data in DS1 with NCHAT surveys within the virtual data enclave (VDE).
description: The purpose of this study is to provide researchers the
ability to merge the NCHAT (National Couples' Health and Time Study) data
with the Contextual Determinants of Health (CDOH).
description: The variable <strong>MATCH_ID</strong> is intended to allow users
to merge the IPUMS Contextual Determinants of Health (CDOH) data with the
NCHAT (National Couples' Health and Time Study). 
These data provide summary data on income inequity between racial
groups in the United States from 2005-2022. Please refer to page 3 of the
User Guide for the formula used to create these percentages.
description: DS1 contains 42 income inequity variables which use the the index of concentration at the extremes (ICE) to describe income inequity between racial groups. These data also include the ID variable
<strong>MATCH_ID</strong> to merge the CDOH data with NCHAT data and the random
county identifier <strong>GEOID_RANDOM</strong> to allow researchers to control for
the county within their analyses.
description: The Contextual Determinants of Health (CDOH) measures were
created from a wide variety of data sources (e.g., IPUMS NHGIS, the Census Bureau, the Bureau of Labor Statistics, the Movement Advancement Project, and
Myers Abortion Facility Database).
Measures are currently available for states or counties from approximately
2015 to 2020.
description: Datasets: 
DS1: IPUMS Contextual Determinants of Health (CDOH) Race and Ethnicity Measure: Income Inequity by County, United States, 2005-2022
description: Historically marginalized populations in the United States including Black, Asian, Hispanic/Latina/o/e/x, and LGBTQ+ persons, and women. Smallest Geographic Unit: County
description: record abstractsEach dataset includes <strong>MATCH_ID</strong>s for all
respondents in NCHAT. This variable should be used to merge the IPUMS CDOH
variables to NCHAT surveys within ICPSR's virtual data enclave (VDE).Each dataset also includes the variable <strong>GEOID_RANDOM</strong>. This
variable is included so investigators can control for the county within
their analyses (e.g., whether respondents are living within the same
county) without knowing the actual county of the NCHAT respondent. This was
done to preserve participant confidentiality.