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Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality

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  • Dana A. Glei
  • Noreen Goldman
  • Germán Rodríguez
  • Maxine Weinstein

Abstract

type="main"> The proliferation of biosocial surveys has increased the importance of weighing the costs and benefits of adding biomarker collection to population-based surveys. A crucial question is whether biomarkers offer incremental value beyond self-reported measures, which are easier to collect and impose less respondent burden. We use longitudinal data from a nationally representative sample of older Taiwanese (aged 54+ in 2000, examined in 2000 and 2006 with mortality follow-up through 2011) to address that question with respect to predicting all-cause mortality. A summary measure of biomarkers improves mortality prediction (as measured by the area under the receiver operating characteristic curve) compared with self-reports alone, but individual biomarkers perform better than the summary score. We find that incorporating change in biomarkers over a six-year period yields a small improvement in mortality prediction compared with one-time measurement. But, is the incremental value worth the costs?

Suggested Citation

  • Dana A. Glei & Noreen Goldman & Germán Rodríguez & Maxine Weinstein, 2014. "Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality," Population and Development Review, The Population Council, Inc., vol. 40(2), pages 331-360, June.
    • Handle: RePEc:bla:popdev:v:40:y:2014:i:2:p:331-360
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    File URL: http://hdl.handle.net/10.1111/j.1728-4457.2014.00676.x
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    References listed on IDEAS

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    2. Sarah Brown & Pulak Ghosh & Daniel Gray & Bhuvanesh Pareek & Jennifer Roberts, 2017. "Saving Behaviour and Biomarkers: A High-Dimensional Bayesian Analysis of British Panel Data," Working Papers 2017005, The University of Sheffield, Department of Economics.

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