biostudies-literatureUnknown11Haring R<h4>Background</h4>Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association.<h4>Methods</h4>Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7%) occurred. Subjective health was assessed by SF-12 derived physical (PCS-12) and mental component summaries (MCS-12), and a single-item self-rated health (SRH) question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. VariableBMC medical research methodology103https://www.ebi.ac.uk/biostudies/studies/S-EPMC3152941biostudies-literatureSelf-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best.PMC3152941Dorr MWallaschofski HVolzke HKohlmann TFeng YSMoock JNauck MHaring RfalseSelf-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best.<h4>Background</h4>Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association.<h4>Methods</h4>Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7%) occurred. Subjective health was assessed by SF-12 derived physical (PCS-12) and mental component summaries (MCS-12), and a single-item self-rated health (SRH) question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. Variable2011-01-01T00:00:00Z2011 Jul2025-05-29T21:52:28.17Z2025-05-29T21:52:28.17ZS-EPMC31529412174969710.1186/1471-2288-11-103