Do interviewer and physician health ratings predict mortality? A comparison with self-rated health

Megan A. Todd, Noreen Goldman

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

BACKGROUND: Despite the serious biases that characterize self-rated health, researchers rely heavily on these ratings to predict mortality. Using newly collected survey data, we examine whether simple ratings of participants' health provided by interviewers and physicians can markedly improve mortality prediction. METHODS: We use data from a prospective cohort study based on a nationally representative sample of older adults in Taiwan. We estimate proportional-hazard models of all-cause mortality between the 2006 interview and 30 June 2011 (mean 4.7 years' follow-up). RESULTS: Interviewer ratings were more strongly associated with mortality than physician or self-ratings, even after controlling for a wide range of covariates. Neither respondent nor physician ratings substantially improve mortality prediction in models that include interviewer ratings. The predictive power of interviewer ratings likely arises in part from interviewers' incorporation of information about the respondents' physical and mental health into their assessments. CONCLUSIONS: The findings of this study support the routine inclusion of a simple question at the end of face-to-face interviews, comparable to self-rated health, asking interviewers to provide an assessment of respondents' overall health. The costs of such an undertaking are minimal and the potential gains substantial for demographic and health researchers. Future work should explore the strength of the link between interviewer ratings and mortality in other countries and in surveys that collect less detailed information on respondent health, functioning, and well-being.

Original languageEnglish (US)
Pages (from-to)913-920
Number of pages8
JournalEpidemiology
Volume24
Issue number6
DOIs
StatePublished - Nov 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Epidemiology

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