Literature DB >> 29401361

A Multiple-Imputation "Forward Bridging" Approach to Address Changes in the Classification of Asian Race/Ethnicity on the US Death Certificate.

Caroline A Thompson1,2, Derek B Boothroyd3, Katherine G Hastings4, Mark R Cullen4, Latha P Palaniappan4, David H Rehkopf4.   

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.
© The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  death certificates; missing data; mortality; multiple imputation; race/ethnicity; vital statistics

Mesh:

Year:  2018        PMID: 29401361      PMCID: PMC5860289          DOI: 10.1093/aje/kwx215

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  19 in total

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3.  Problems with the collection and interpretation of Asian-American health data: omission, aggregation, and extrapolation.

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  5 in total

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