Biases in Assertions of Self-Rated Health
Exploring the Role of the Respondent, Country of Residence, and Interviewer
Keywords:Response Bias, Cross-National Comparison, Europe, Reporting Behavior, Self-Rated Health, Survey of Health, Ageing and Retirement in Europe (SHARE)
Comparative analyses frequently examine respondents’ self-rated health (SRH), assuming that it is a valid and comparable measure of generic health. However, given SRH’s vagueness, this assumption is questionable due to (1) manifold non-health influences, such as personal characteristics including optimism, interviewer effects on the rating, and cultural contexts, as well as (2) potential gender, age- or country-specific expectations for one’s health or frames of reference. Conceptually, two major components of SRH can be distinguished: latent health and reporting behavior. While latent health exclusively refers to objective health status, reporting behavior collectively refers to non-health characteristics (NH) affecting SRH. The present paper is primarily concerned with the latter and aims to identify whether and how NH bias SRH, including possible differences by gender, age, and country of residence.
The presented analyses are based on data from 16,183 participants in five countries drawn from the fifth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE). Latent health is controlled via a wide array of health indicators and the residuals are examined with a model covering NH from three different sources: the interviewer, the respondent, and the country of residence. To identify subgroup-specific response behaviors, all analyses are carried out separately by gender, three age groups (50-64, 65-79, and 80+ years), and country of residence.
The analyses uncovered influences of – among others–the interviewer’s SRH, the respondent’s life satisfaction, and the country of residence on SRH, while other factors differed by subgroup. The amount of explained variance due to such reporting behavior (with a mean of seven percent) can be deemed meaningful, considering that controlling for latent health already explains around half of SRH’s variance. The greatest source of non-health influences was respondent characteristics, with the interviewer and country having smaller effects.
These results illustrate the importance of taking NH into account when using SRH measures. Future research on complementing SRH with factual questions in survey design is advisable.
* This article belongs to a special issue on “Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity”.
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