Elsevier

The Lancet

Volume 386, Issue 9993, 8–14 August 2015, Pages 533-540
The Lancet

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

https://doi.org/10.1016/S0140-6736(15)60175-1Get rights and content

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<0·0001 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.

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.

Funding

Knut and Alice Wallenberg Foundation and the Swedish Research Council.

Introduction

Adequate identification and risk stratification of individuals with reduced life expectancy, especially in the middle-aged to elderly population, is an important public health priority1 and a central issue in clinical decision making. Epidemiological studies that obtain several measurements through questionnaires, physical assessments, and biological samples can be done to compare the prognostic value of risk factors of short-term mortality and provide new hypotheses about health determinants. Moreover, these risk factors can be combined into a prognostic index to provide information about individual mortality risk or other health-related measures. Traditionally, association with mortality has been studied for one risk factor at a time,2, 3, 4, 5, 6 and the few studies that have investigated more than one risk factor did not assess different causes of death and based their analyses on small study samples.7 Several prognostic indices for short-term mortality exist, but they have mainly been developed for and assessed in older individuals or in high-risk populations.8, 9 Furthermore, the small sample sizes and the small number of risk factors investigated are the main limitations of all previous studies.

The UK Biobank project10 includes about 500 000 men and women aged 40–70 years. The participants underwent blood draw for biobanking and participated in detailed, questionnaire-based, physical, and biological measurements during 2007–10. Data from these assessments have been made available to all researchers worldwide after an approved application. We aimed to use these data to do a systematic and untargeted investigation of the associations between most of the available measurements and 5 year all-cause and cause-specific mortality. We also aimed to create a prognostic index including only self-reported information to estimate individual mortality risk.

Section snippets

Study design and participants

Participants were enrolled in the UK Biobank from April, 2007, to July, 2010, from 21 assessment centres across England, Wales, and Scotland using standardised procedures. When participants agreed to take part in UK Biobank, they visited their closest assessment centre to provide baseline information, physical measures, and biological samples. In this prospective population-based study, we included all measurements available on April 10, 2014. We excluded variables that were missing in more

Results

Between April, 2007, and July, 2010, 498 849 participants were enrolled from 21 centres across England, Wales, and Scotland using standardised procedures specified in the protocol. We excluded participants with more than 80% variables missing (n=746), resulting in 498 103 (54% of whom were women) participants included in our main analyses.

Of these 498 103 participants aged 37–73 years, 8532 (39% of whom were women) died during a median follow-up of 4·9 years (IQR 4·33–5·52; table 1). The most

Discussion

In this large, contemporary prospective cohort study, we did an extensive analysis of associations of more than 600 measurements with 5 year all-cause and cause-specific mortality in UK Biobank participants). In this report, we have presented only a small part of our findings; however, all our results are available in an interactive website where the observed associations can be explored in detail to generate new research hypotheses. Several key messages can be deduced from this study. First,

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