Cross-sectional data from the Survey of Health, Ageing and Retirement in Europe (SHARE) are a common source of information in comparative studies of population health in Europe. In the largest part, these data are based on longitudinal samples, which are subject to health-specific attrition. This implies that estimates of population health based on cross-sectional SHARE datasets are biased as the data are selected on the outcome variable of interest. We examine whether cross-sectional datasets are selected based on health status. We compare estimates of the prevalence of full health, healthy life years at age 50 (HLY), and rankings of 18 European countries by HLY based on the observed, cross-sectional SHARE wave 7 datasets and full samples. The full samples consist of SHARE observed and attrited respondents, whose health trajectories are imputed by microsimulation. Health status is operationalised across the global index of limitations in activities of daily living (GALI). HLY stands for life expectancy free of activity limitations. Cross-sectional datasets are selected based on health status, as health limitations increase the odds of attrition from the panel in older age groups and reduce them in younger ones. In older age groups, the prevalence of full health is higher in the observed cross-sectional data than in the full sample in most countries. In most countries, HLY is overestimated based on the cross-sectional data, and in some countries, the opposite effect is observed. While, due to the small sample sizes of national surveys, the confidence intervals are large, the direction of the effect is persistent across countries. We also observe shifts in the ranking of countries according to HLYs of the observed data versus the HLYs of the full sample. We conclude that estimates on population health based on cross-sectional datasets from longitudinal, attrited SHARE samples are over-optimistic.