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Race Bridging

Race bridging refers to making data collected using one set of race categories consistent with data collected using a different set of race categories, to permit estimation and comparison of race-specific statistics at a point in time or over time. More specifically, race bridging is a method used to make multiple-race and single-race data collection systems sufficiently comparable with permit estimation and analysis of race-specific statistics such as birth and death rates. This entry provides an overview of the origins of race bridging and race-bridging methods and focuses on race bridging to estimate single-race population counts, as this has been the primary use of race bridging to date.

Background

The need for race bridging arose when the Office of Management and Budget (OMB) issued revised standards in 1997 for the collection, tabulation, and presentation of data on race and Hispanic origin within the federal statistical system. These standards replaced the 1977 OMB standards. The revised standards increased the minimum set of race categories from four (American Indian or Alaska Native [AIAN], Asian or Pacific Islander [AIP], Black, and White) to five (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White). In addition, the revised standards require federal data collection programs to allow respondents to select more than one race category when responding to a query on their racial identity. This means that under the revised standards, there are potentially 31 race groups (five single-race and 26 multiple-race groups), depending on whether a respondent selects one, two, three, four, or all five of the race categories. Because of the addition of the multiple-race groups, race data collected under the revised standards are not comparable with race data collected under the 1977 standards.

The question on race on the 2000 census was based on the revised OMB standards and so allowed respondents to select more than one race category. As a result, the race data on the 2000 census are not comparable with historical race data (e.g., previous censuses, administrative records, surveys, population estimates) or with data on other data systems that have not yet transitioned to the 1997 standards. As many data systems use population estimates to create rates, this left many data users unable to compute current statistics and to track changes over time. One such example is the problem faced by the National Center for Health Statistics (NCHS) in computing birth and death rates for 2000 and beyond and measuring and tracking changes in these vital events. As of 2004, most states had not revised the race question on their birth or death certificates and were still collecting race data using the 1977 race categories. Thus, the calculation of post-2000 race-specific birth and death rates (which use birth and death counts in the numerator and population estimates in the denominator) requires population estimates with the 1977 race categories.

OMB-Proposed Bridging Methods

Recognizing the need to make race data collected under the 1997 standards comparable with race data collected under the 1977 standards, the OMB proposed a number of bridging methods. The proposed methods fall into two broad categories, whole allocation methods and fractional allocation methods. Whole allocation methods assign each multiple-race respondent to only one of the possible single-race categories. Fractional allocation methods divide each multiple-race respondent into parts and assign a part to each possible single-race category. The proposed methods include the

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