A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate. Issue 2 (8th August 2017)

• Record Type: Journal Article
• Authors: Thompson, Caroline A; Boothroyd, Derek B; Hastings, Katherine G; Cullen, Mark R; Palaniappan, Latha P; Rehkopf, David H
• Is Part Of: American journal of epidemiology. Volume 187:Issue 2(2018)
• Page Start: 347
• Page End: 357
• Publication Date: 2017-08-08
• Subjects: death certificates -- missing data -- mortality -- multiple imputation -- race/ethnicity -- vital statistics; Epidemiology -- Periodicals; Public health -- Periodicals; 614.4
• DOI: 10.1093/aje/kwx215
• Languages: English
• ISSNs: 0002-9262

Abstract

Abstract: The incomparability of old and new classification systems for describing the same data can be seen as a missing-data problem, and, under certain assumptions, multiple imputation may be used to "bridge" 2 classification systems. One example of such a change is the introduction of detailed Asian-American race/ethnicity classifications on the 2003 version of the US national death certificate, which was adopted for use by 38 states between 2003 and 2011. Using county- and decedent-level data from 3 different national sources for pre- and postadoption years, we fitted within-state multiple-imputation models to impute ethnicities for decedents classified as "other Asian" during preadoption years. We present mortality rates derived using 3 different methods of calculation: 1) including all states but ignoring the gradual adoption of the new death certificate over time, 2) including only the 7 states with complete reporting of all ethnicities, and 3) including all states and applying multiple imputation. Estimates from our imputation model were consistently in the middle of the other 2 estimates, and trend results demonstrated that the year-by-year estimates of the imputation model were more similar to those of the 7-state model. This work demonstrates how multiple imputation can provide a "forward bridging" approach to make more accurate estimates over time in newly categorized populations.