Protocol - Neighborhood Concentrated Disadvantage
The protocol is based on extracting data from the U.S. Census Bureau on a set of variables related to the concept of "concentrated disadvantage" (Sampson, et al.,1997). All the relevant variables are available from the long form of the 1990 and 2000 SF3, and from the 5-year ACS estimates. ACS estimates are annually updated; as of May 2022, 5-year data sets range from 2011-2015 to 2016-2020. Once the data are extracted, an index score of concentrated disadvantage can be calculated at the neighborhood level of interest; this is usually based on census tract or census block group data.
Assuming that information on current address (see PhenX Demographics domain, Current Address measure) has been collected for a study respondent, then it is possible to use geocoding to link the address of a study participant to his or her local neighborhood (a geographic area). The link is typically by a Census-defined area, such as a census block group or a census tract or by Zone Improvement Plan (ZIP) code area (captured by the U.S. Census Bureau as a ZIP Code Tabulation Area [ZCTA]).
When comparing the 2011-2015 ACS 5-year estimates with the 2016-2020 ACS 5-year estimates, there are several points to consider. For more information on the 2016-2020 ACS changes, please visit the American Community Survey Guidance for Data Users website: https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data/2020/5-year-comparison.html
Table B02001: Race. The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website.
The original paper by Sampson et al. (1997) was based on the use of variables from the 1990 Decennial Census and applied to a neighborhood definition based on aggregates of Census tracts, called neighborhood clusters.
The Social Environments Working Group (WG) recommends that researchers follow Sampson et al. (1997) and conduct a factor analysis (e.g., a principal components analysis using varimax rotation methods or alpha-scoring factor analysis). The extracted variables are typically very highly correlated, undermining any investigation of unique effects. Sampson et al. (1997, p. 920) find that, consistent with urban theory, these six, poverty-related variables are highly associated and load on the same factor; their work was based on 1990 Census data for Chicago. Other studies in other settings confirm that these variables (poverty, percentage of single-parent families, percentage of family members on welfare and unemployed, and a measure of racial segregation) load on a single factor with individual factor loadings typically exceeding 0.8.
The Social Environments WG recommends that investigators record and report the factor loading scores for each variable used in the factor analysis. These scores would vary across studies, but knowing how they vary (i.e., what other studies found) would allow for comparison between studies. Depending on the purpose of the study, investigators may want to remove the measure of Percent Black from the scale if the unique effects of racial concentration are a key research emphasis.
The calculation of concentrated disadvantage based on factor analysis generates a measure that is sample dependent (i.e., study specific). However, it is important to note that this is a well-established, robust, and highly cited measure across the social sciences and public health. The social science literature has long argued that neighborhood disadvantage is not a single-item construct captured by, for example, a measure of poverty (e.g., percentage of individuals below the poverty level) or measures such as the Index of Concentration at the Extremes (Massey, 2001).
Accessing and Understanding the American Community Survey (ACS) Data
The ACS data used in this protocol can be accessed by using Excel to read the Summary Files at the U.S. Census Bureau’s data.census.gov website (https://data.census.gov) or using SAS programs to read the files. Users can find additional information on these tools at the following locations:
Using Excel to Access Summary Files: https://www2.census.gov/programs-surveys/acs/summary_file/2020/documentation/tech_docs/ACS_SF_Excel_Import_Tool.pdf
Using SAS to Access Summary Files: https://www.census.gov/programs-surveys/acs/library/handbooks/summary-file.html
The technical documentation for the American Community Survey (ACS) summary files is available online at http://www.census.gov/programs-surveys/acs/technical-documentation.html. Select the “Summary File Documentation” link, and then select the data set of interest. Users not familiar with Census data should consult the technical materials.
If the user is interested in additional variables beyond those included in the neighborhood concentrated disadvantage protocol, they should be aware that not all ACS estimates are available for all geographies. These missing estimates are due to data suppression techniques by which the U.S. Census Bureau limits disclosure of individual data and does not release estimates with poor statistical reliability. Additional information about data suppression and the specific estimates it impacts can be found at http://www.census.gov/programs-surveys/acs/technical-documentation/data-suppression.html.
Although block group data have long been available from the Census File Transfer Protocol site, not all tables have block groups available for download at data.census.gov. Information about the types of geographies that are available are in the Appendix Tables as detailed in the technical documentation at https://www.census.gov/programs-surveys/acs/library/handbooks/summary-file.html.
Calculating Neighborhood Concentrated Disadvantage
Concentrated disadvantage is derived from six Census variables:
1. Percent of Individuals Below the Poverty Line (derived from ACS Table C17002)
2. Percent of Households Receiving Public Assistance (derived from ACS Table B19057)
3. Percent Female-Headed Families (derived from ACS Table B11001)
4. Percent Unemployed (derived from ACS Table B23025)
5. Percent Less Than Age 18 (derived from ACS Table B01001)
6. Percent Black (derived from ACS Table B02001)
Concentrated disadvantage is calculated for all subareas within a study area.
While some commercial data products may include the derivation of some of these variables, the detailed material below is based on the assumption that the user will go to the U.S. Census Bureau (original source) for all the raw data counts needed to calculate the individual variables that create the measure Concentrated Disadvantage. The protocol text uses the unique ID of individual variables. These descriptions can be found in the “Table Shells” download on the Summary File Technical Documentation (available here https://www.census.gov/programs-surveys/acs/technical-documentation/table-shells.html). Note: users may download tables as Excel files from https://data.census.gov. The tables do not use the unique ID of the variables presented in the summary files but do contain header data that describe the variable.
1: "Percent of Individuals Below the Poverty Line" is derived from data in ACS 5-Year “Table C17002: Ratio of Income to Poverty Level in the Past 12 Months.”
Table C17002: Ratio of Income to Poverty Level in the Past 12 Months
Universe: Population for whom poverty status is determined.
There are eight variables included in table C17002 (see line 14188 of the ACS2020_Table_Shells.xlsx file available in the Technical Documentation).
Table C17002: Ratio of Income to Poverty Level in the Past 12 Months is reproduced below:
.50 to .99
1.00 to 1.24
1.25 to 1.49
1.50 to 1.84
1.85 to 1.99
2.00 and over
The percent of individuals below the poverty line=[(C17002002 + C17002003) / C17002001] * 100.
2: "Percent of Households Receiving Public Assistance" is derived from ACS "TableB19057: Public Assistance Income in the Past 12 Months for Households.”
Table B19057: Public Assistance Income in the Past 12 Months for Households
There are three variables included in Table B19015. Table B19015 is reproduced below:
With public assistance income
No public assistance income
Male householder, no wife present
Female householder, no husband present
Householder living alone
Householder not living alone
The “percent of female-headed families”=(B11001006/B11001001) * 100.
4: "Percent Unemployed" is derived from ACS "Table B23025: Employment Status for the Population 16 Years and Over."
Table B23025: Employment Status for the Population 16 Years and Over
Universe: Population 16 years and over.
From the 2020 Subject Definitions document (p. 68), the U.S. Census Bureau definition of being unemployed is the following:
"All civilians 16 years old and over are classified as unemployed if they (1) were neither &rsquot;at work&rsquot; nor &rsquot;with a job but not at work&rsquot; during the reference week,and (2) were actively looking for work during the last 4 weeks,and (3) were available to start a job. Also included as unemployed are civilians who did not work at all during the reference week, were waiting to be called back to a job from which they had been laid off, and were available for work except temporary illness. Examples of job-seeking activities are: registering at a public or private employment office; meeting with prospective employers; investigating possibilities for starting a professional practice or opening a business; placing or answering advertisements; writing letters of application; being on a union or professional register"
Table B23025 contains seven cells. The table is reproduced below.
In labor force:
Civilian labor force:
Not in labor force
Black or African American alone
American Indian and Alaska Native alone
Native Hawaiian and Other Pacific Islander alone
Some other race alone
Two or more races:
Two races including Some other race
Two races excluding Some other race, and three or more races
The "Percent Black"=(B02001003/B02001001) * 100
Personnel and Training Required
Knowledge of Census data products and websites, such as data.census.gov, and/or publicly available data portals (e.g., National Historical Geographic Information System), and/or commercial geospatial data products, such as that provided by vendors like GeoLytics or Social Explorer.
After extracting the necessary data, statistical methods are used (e.g., principal component analysis and factor analysis).
Access to a desktop/laptop computer with Internet access to download raw data from the U.S. Census Bureaus data.census.gov website. Statistical packages (e.g., SPSS, SAS) for data manipulation and factor analysis.
|Specialized requirements for biospecimen collection||No|
|Average time of greater than 15 minutes in an unaffected individual||No|
Mode of Administration
Secondary Data Analysis
Infant, Toddler, Child, Adolescent, Adult, Senior, Pregnancy
Not applicable; derived from publicly available secondary data.
The Social Environments Working Group preferred an objective measure using U.S. Census Bureau data over a questionnaire that would rely on subjective judgment based on retrospective ascertainment, which is likely to be unreliable. Additionally, the measure of "concentrated disadvantage" is derived from the work of Sampson and colleagues (1997) on the Project on Human Development in Chicago Neighborhoods (PHDCN), which is a well-known, large-scale study.
The measure has been used in numerous papers including, the highly cited (3,000+ citations) paper by Sampson et al. (1997).
|caDSR Common Data Elements (CDE)||Social Environment Neighborhood Concentrated Disadvantage Assessment Score||3150986||CDE Browser|
|Logical Observation Identifiers Names and Codes (LOINC)||Neighborhood disadvantage proto||63036-8||LOINC|
Process and Review
The SDOH-X WG reviewed the measures in the Social Environments domain in May 2022.
Guidance from the SDOH-X WG includes:
• Updated protocol
Back-compatible: there are changes to the Data Dictionary, previous version of the Data Dictionary and Variable mapping in Toolkit archive (link)
The Expert Review Panel #2 (ERP 2) reviewed the measures in the Demographics, Social Environments and Environmental Exposures domains.
Guidance from ERP 2 includes:
• Replaced protocol
• New Data Dictionary
Back-compatible: there are changes to the Data Dictionary, previous version of the Data Dictionary and Variable mapping in Toolkit archive (link)
Protocol Name from Source
U.S. Census Bureau, 1990 and 2000 Decennial Censuses (SF3); and American Community Survey (ACS), 5-year estimates, 2011-2015 to 2016-2020.
Recommended data sources include the following:
The U.S. Census Bureau decennial Census (1990, 2000).
American Community Survey (ACS) products (specifically, the 5-year estimates), http://www.census.gov/programs-surveys/acs.
Kawachi, I., & Berkman, L. (2003). Neighborhoods and health. New York: Oxford University Press.
Massey, D. S. (2001). The prodigal paradigm returns: ecology comes back to sociology. In: Booth A, Crouter A, eds. Does It Take a Village? Community Effects on Children, Adolescents, and Families. Mahwah, NJ: Lawrence Erlbaum Associates; 41-48.
Massey, D. S., & Denton, N. (1993). American apartheid: Segregation and the making of the underclass. Cambridge, MA: Harvard University Press.
Sampson, R. J., Morenoff, J., & Gannon-Rowley, T. (2002). Assessing neighborhood effects: Social processes and new directions in research. Annual Review of Sociology, 28, 443-478.
Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277(5238), 918-924.
Wilson, W. J. (1987). The truly disadvantaged: The inner city, the underclass, and public policy. Chicago: University of Chicago Press.
|Variable Name||Variable ID||Variable Description||dbGaP Mapping|
|PX211302010000||Percent Of Individuals Below The Poverty more||Variable Mapping|
|PX211302060000||Percent Black (derived from ACS Table B02001)||N/A|
|PX211302030000||Percent Female-Headed Families (derived from more||N/A|
|PX211302020000||Percent of Households Receiving Public more||Variable Mapping|
|PX211302040000||Percent Unemployed (derived from ACS Table B23025)||N/A|
|PX211302050000||Percent Less Than Age 18 (derived from ACS more||N/A|
Neighborhood Concentrated Disadvantage
May 31, 2016
This measure uses readily available secondary data from the U.S. Census Bureau.
This measure examines various population characteristics at the neighborhood level to determine the concentration of poverty. In the social science and public health literatures, one of the most important indicators for a host of individual outcome measures that are incorporated at the neighborhood level is Neighborhood Concentrated Disadvantage.
neighborhood concentrated disadvantage, Social environments, American Community Survey, ACS, neighborhood poverty, public assistance, U.S. Census, SES Measures (income, education, occupation), environmental health disparities, neighborhood built environment
|Protocol ID||Protocol Name|
|211301||Neighborhood Concentrated Disadvantage|
|211302||Neighborhood Concentrated Disadvantage|