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, Raudenbush, & Earls, 1997). All the relevant variables are available from the long form of the 1990 and 2000 decennial Censuses. 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) and any previous address(es) (see PhenX Environmental Exposures domain, Residential History measure) has been collected for a study respondent, then via geocoding it is possible to link the address of a study participant to his or her local neighborhood (a geographic area), typically by a Census-defined area, such as a census block-group or census tract, or by Zone Improvement Plan (ZIP) code area. 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 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 (note: their work was based on 1990 Census data for Chicago). Other studies in other settings confirm that these six 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 Working Group recommends that investigators record and report the factor loading scores for each variable used in the factor analysis. These would vary across studies but knowing how they vary (i.e., what other studies found) would allow for comparison between studies. 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., percent of individuals below the poverty level) or measures such as the Index of Concentration at the Extremes (Massey, 2001).
LOINC codes that represent optional associated observation(s) for a clinical observation or laboratory test. A LOINC term may represent a single associated observation or panel containing several associated observations.
Updated the PhenX ID from "PhenX." to "PX" in Survey Question Source field to align with the variable identifier used in the PhenX Toolkit.; Added the PhenX protocol ID to the Component to clearly define the protocol version for which this panel is based upon.
Related Names
Neighborhood disadvantage proto Pan Panel PANEL.PHENX Panl
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