Black–White Disparities in Adult Mortality: Implications of Differential Record Linkage for Understanding the Mortality Crossover

Abstract

Mortality rates among black individuals exceed those of white individuals throughout much of the life course. The black-white disparity in mortality rates is widest in young adulthood, and then rates converge with increasing age until a crossover occurs at about age 85 years, after which black older adults exhibit a lower mortality rate relative to white older adults. Data quality issues in survey-linked mortality studies may hinder accurate estimation of this disparity and may even be responsible for the observed black-white mortality crossover, especially if the linkage of surveys to death records during mortality follow-up is less accurate for black older adults. This study assesses black-white differences in the linkage of the 1986–2009 National Health Interview Survey to the National Death Index through 2011 and the implications of racial/ethnic differences in record linkage for mortality disparity estimates. Match class and match score (i.e., indicators of linkage quality) differ by race/ethnicity, with black adults exhibiting less certain matches than white adults in all age groups. The magnitude of the black-white mortality disparity varies with alternative linkage scenarios, but convergence and crossover continue to be observed in each case. Beyond black-white differences in linkage quality, this study also identifies declines over time in linkage quality and even eligibility for linkage among all adults. Although linkage quality is lower among black adults than white adults, differential record linkage does not account for the black-white mortality crossover.

Comparability of Mortality Estimates from Social Surveys and Vital Statistics Data in the United States

“…The survey samples contained in most SLMFs, including the ones analyzed herein, meet these criteria. Lariscy 2011Lariscy , 2017Rogers et al 1997). False negatives occur when the NDI matching algorithm fails to match survey records and death records among deceased respondents causing them to appear "statistically immortal" (Pablos-Méndez 1994:1237.…”

“…Matching error is a potential source of systematic bias because it results from variations in the propensity to report key identifiers between subpopulation groups, data collection periods, and/or surveys. For instance, prior research with the NHIS-LMF has shown that racial/ethnic subgroup differences in record linkage can affect estimates of mortality disparities since members of some groups are more likely to be linked to the death certificates than members of other groups (Black et al 2017;Lariscy 2011Lariscy , 2017Palloni and Arias 2004;Rogers et al 1997). Matching errors can also arise when survey respondents either refuse or are not asked to provide certain identifiers.…”

Racial and Ethnic Disparities in Health

“…Mortality rates cross over around age 85 years, after which black mortality rates are lower than white mortality rates (Lariscy 2017;Lynch et al 2003;Nam 1995). The two leading explanations for the crossover are selective survival and data quality.…”

“…Age misreporting could result in downwardly biased mortality rates in vital statistics data as well as missed matches in survey data linked to death certificate data. Research has generally concluded that even with adjustment for data quality issues, black-white mortality convergence and crossover still occur, though death rates cross over at a later age with data correction (Hill et al 2000;Lariscy 2017;Lynch et al 2003).…”

“…The vital status of NHIS respondents has been ascertained through December 31, 2015 by probabilistic linkage to death certificate data maintained by the National Death Index (NDI) to produce the National Health Interview Survey Linked Mortality Files (NHIS-LMF) (National Center for Health Statistics [NCHS] 2018). Although the linkage process is highly accurate in ascertaining vital status, linkage may be more certain among NH white and US-born adults than some racial/ethnic minority and immigrant groups (Lariscy 2011(Lariscy , 2017).…”