Abstract
Objectives.
The 2000 Census, which provides denominators used in calculating vital statistics and other rates, allowed multiple-race responses. Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denominators comparable. This report describes and evaluates the method used by the National Center for Health Statistics to bridge multiple-race responses obtained from Census 2000 to single-race categories, creating single-race population estimates that are available to the public.
Methods.
The authors fitted logistic regression models to multiple-race data from the National Health Interview Survey (NHIS) for 1997–2000. These fitted models, and two bridging methods previously suggested by the Office of Management and Budget, were applied to the public-use Census Modified Race Data Summary file to create single-race population estimates for the U.S. The authors also compared death rates for single-race groups calculated using these three approaches.
Results.
Parameter estimates differed between the NHIS models for the multiple-race groups. For example, as the percentage of multiple-race respondents in a county increased, the likelihood of stating black as a primary race increased among black/white respondents but decreased among American Indian or Alaska Native/black respondents. The inclusion of county-level contextual variables in the regression models as well as the underlying demographic differences across states led to variation in allocation percentages; for example, the allocation of black/white respondents to single-race white ranged from nearly zero to more than 50% across states. Death rates calculated using bridging via the NHIS models were similar to those calculated using other methods, except for the American Indian/Alaska Native group, which included a large proportion of multiple-race reporters.
Conclusion.
Many data systems do not currently allow multiple-race reporting. When such data systems are used with Census counts to produce race-specific rates, bridging methods that incorporate geographic and demographic factors may lead to better rates than methods that do not consider such factors.