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The importance of correcting for health-related survey non-response when estimating health expectancies
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Journal Article
The importance of correcting for health-related survey non-response when estimating health expectancies
2024
Overview
Most studies on health expectancies rely on self-reported health from surveys to measure the prevalence of disabilities or ill health in a population At best, such studies only correct for sample selection based on a limited number of characteristics observed on the invitees Using longitudinal data from the Trondelag Health Study (HUNT), I investigate the extent to which adjustments for a health-related sample selection affect the age profiles for the prevalence of functional impairment (FI) and the associated disability-free life expectancy (DFLE). I estimate a probit model with sample selection under the identifying restriction that the strength of the health-related selection is of similar order to the strength of the selection on observable characteristics. I then compute the selection-adjusted FI prevalence rates and trace out the implications for DFLE using the Sullivan method. The analysis confirms that poor health measured at younger ages correlates with non-response behaviour in later waves of the survey, and that even for a conservative lower bound for the assumed degree of health-related selection, the estimated age profiles for DFLE lie systematically below the corresponding profiles when controlling only for selection on observable characteristics. Health related non-response downwardly biases the raw sample prevalence rates for FI obtained from survey data and contributes to overestimating the expansion in DFLE.
Publisher
Max-Planck-Gesellschaft zur Foerderung der Wissenschaften,Max Planck Institute for Demographic Research,Max Planck Institut für Demografische Forschung
