Abstract

This paper explores which demographic characteristics substantially bias self-reported physical and cognitive health status of older Europeans. The analysis utilises micro-data for 19 European countries from the Survey of Health, Ageing and Retirement in Europe to compare performance-tested outcomes of mobility and memory with their self-reported equivalents. Relative importance analysis based on multinomial logistic regressions shows that the bias in self-reported health is mostly due to reporting heterogeneities between countries and age groups, whereas gender contributes little to the discrepancy. Concordance of mobility and cognition measures is highly related; however, differences in reporting behaviour due to education and cultural background have a larger impact on self-assessed memory than on self-assessed mobility. Southern as well as Central and Eastern Europeans are much more likely to misreport their physical and cognitive abilities than Northern and Western Europeans. Overall, our results suggest that comparisons of self-reported health between countries and age groups are prone to significant biases, whereas comparisons between genders are credible for most European countries. These findings are crucial given that self-assessed data are often the only information available to researchers and policymakers when asking health-related questions.

Highlights

  • Understanding the bias in self-reported health and its determinants is of utmost importance, because subjective data are often the only information at hand when researchers and policymakers ask health-related questions

  • Based on the observation that demographic characteristics are most commonly used for comparative health studies, and that the same characteristics are associated with deviations in reporting behaviour, this study focuses on the main demographic characteristics only

  • In this study on older Europeans, we investigate the discrepancy between tested and selfreported health measures and explore which demographic characteristics are most important in explaining health misreporting

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Summary

Introduction

Understanding the bias in self-reported health and its determinants is of utmost importance, because subjective data are often the only information at hand when researchers and policymakers ask health-related questions. These data are readily available as their collection takes less time and is more cost-effective than performance-based health measures. Several studies show discrepancies between tested and self-reported health indicators [1,2,3,4,5,6,7,8,9]. In a metaanalysis, [1] find that correlation coefficients of tested and self-reported functional ability range from -0.72 to 0.60. Over- and underestimating health does harm the reliability of survey data, and individuals themselves

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