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.
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).
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.
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.
From the Office of Population Research and Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ.
This work was supported by the National Institutes of Health grants R01AG016790 to N.G. (from the National Institute on Aging) and R24HD047879 (from The Eunice Kennedy Shriver National Institute of Child Health and Human Development). The funding agency had no role in the study design and analysis or the decision to submit the article for publication.
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Correspondence: Megan A. Todd, Office of Population Research, Wallace Hall, 2nd floor, Princeton University, Princeton, NJ 08544. E-mail: email@example.com.
Received January 8, 2013
Accepted June 27, 2013