5 y Mortality Predictors

5 year mortality predictors in 498 103 UK Biobank participants: a prospective population-based study

Andrea Ganna, PhD

,

 Prof Erik Ingelsson, MD

Published Online: 03 June 2015

DOI: http://dx.doi.org/10.1016/S0140-6736(15)60175-1

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Article Info

• Summary
• Full Text
• Tables and Figures
• References
• Supplementary Material

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Summary

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.

Findings

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 a="" and="" href="http://www.ubble.co.uk/" in="" men="" nbsp="" p="0·0007" style="color: #004480; text-decoration: none;" target="_blank" women="">dedicated website

 allows the interactive exploration of all results along with calculation of individual risk through an online questionnaire.

Interpretation

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./.../

Supplementary Material

Title	Description	Type	Size
Supplementary appendix		pdf	1.82 MB
Supplementary appendix		xlsx	5.52 MB