title: 5 year mortality predictors in 498,103 UK Biobank participants: a prospective population-based study.
abstract: BACKGROUND
  To our knowledge, a systematic comparison of predictors of mortality in middle-aged to elderly individuals has not yet been done. We investigated predictors of mortality in UK Biobank participants during a 5 year period. We aimed to investigate the associations between most of the available measurements and 5 year all-cause and cause-specific mortality, and to develop and validate a prediction score for 5 year mortality using only self-reported information.
  
  
  METHODS
  Participants were enrolled in the UK Biobank from April, 2007, to July, 2010, from 21 assessment centres across England, Wales, and Scotland with standardised procedures. In this prospective population-based study, we assessed sex-specific associations of 655 measurements of demographics, health, and lifestyle with all-cause mortality and six cause-specific mortality categories in UK Biobank participants using the Cox proportional hazard model. We excluded variables that were missing in more than 80% of the participants and all cardiorespiratory fitness test measurements because summary data were not available. Validation of the prediction score was done in participants enrolled at the Scottish centres. UK life tables and census information were used to calibrate the score to the overall UK population.
  
  
  RESULTS
  About 500,000 participants were included in the UK Biobank. We excluded participants with more than 80% variables missing (n=746). Of 498,103 UK Biobank participants included (54% of whom were women) aged 37-73 years, 8532 (39% of whom were women) died during a median follow-up of 4·9 years (IQR 4·33-5·22). Self-reported health (C-index including age 0·74 [95% CI 0·73-0·75]) was the strongest predictor of all-cause mortality in men and a previous cancer diagnosis (0·73 [0·72-0·74]) was the strongest predictor of all-cause mortality in women. When excluding individuals with major diseases or disorders (Charlson comorbidity index >0; n=355 043), measures of smoking habits were the strongest predictors of all-cause mortality. The prognostic score including 13 self-reported predictors for men and 11 for women achieved good discrimination (0·80 [0·77-0·83] for men and 0·79 [0·76-0·83] for women) and significantly outperformed the Charlson comorbidity index (p<0·0001 in men and p=0·0007 in women). A dedicated website allows the interactive exploration of all results along with calculation of individual risk through an online questionnaire.
  
  
  CONCLUSIONS
  Measures that can simply be obtained by questionnaires and without physical examination were the strongest predictors of all-cause mortality in the UK Biobank population. The prediction score we have developed accurately predicts 5 year all-cause mortality and can be used by individuals to improve health awareness, and by health professionals and organisations to identify high-risk individuals and guide public policy.
  
  
  BACKGROUND
  Knut and Alice Wallenberg Foundation and the Swedish Research Council.
authors.affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
authors.forename: Andrea
authors.initials: A
authors.lastname: Ganna
authors.affiliation: Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Electronic address: erik.ingelsson@medsci.uu.se.
authors.forename: Erik
authors.initials: E
authors.lastname: Ingelsson
mesh_terms: D000328:Adult; D000368:Aged; D001771:Blood Banks / Q000706:statistics & numerical data*; D002423:Cause of Death; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012307:Risk Factors; D015996:Survival Rate; D006113:United Kingdom