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Researchers find self-reported health, walking pace greatest predictor of all-cause mortality

Health measures that can be attained through questionnaires and verbal interviews, without physical exams, show the highest accuracy in predicting cancer, cardiovascular, respiratory, digestive, and other disease-related morality in adults aged 40 to 70 years, according to recently published data in the Lancet.

“Our findings suggest that measures that can be simply obtained by verbal interview without physical examination (eg, self-reported health and walking pace) are the strongest predictors of all-cause mortality. Moreover, we could rank the measurements in terms of their predictive abilities, provide new insights about their relative importance, and show some unexpected associations,” Andrea Ganna, PhD, department of medical epidemiology and biostatistics at Karolinska Institutet, Sweden, and Erik Ingelsson, MD, department of molecular epidemiology and sciences for life laboratory, Uppsala University, Sweden, wrote.

Researchers recruited participants from UK Biobank for a prospective population-based study throughout England, Scotland and Wales from April 2007 to July 2010 to assess the correlation between available sex-specific measurements of demographics, health and lifestyle, and 5 year all-cause mortality and cause-specific mortality.

In total, 498,103 participants, aged 37 to 73 years, were included in the evaluation. At a 4.9 year follow-up, 8,532 participants had died (39% women). Breast cancer and lung cancer were the most common causes of death among women (n = 489) and men (n = 546), respectively.

Among men, the strongest predictor of all-cause mortality was self-reported health (C-index including age = 0.74; 95% CI, 0.73-0.75), and among women, a prior diagnosis of cancer was the strongest predictor (C-index = 0.73; 95% CI, 0.72-0.74).

Smoking habits were the strongest predictor of 5-year all-cause mortality in both men and women when participants with major diseases or disorders were omitted.

With the data obtained from the study, researchers developed a prediction score, based on 11 questions for women and 13 for men, that can predict 5 year all-cause mortality in middle-aged to elderly individuals. The score, which showed substantially better discrimination than the Charlson comorbidity index, showed good discrimination among both sexes and significantly better prediction compared with age alone (P < .0001).

“The prediction score … can be used by individuals to improve health awareness, and by health professionals and organizations to identify high-risk individuals and guide public policy,” Ganna and Ingelsson wrote.

In an accompanying editorial, Simon G. Thompson and Peter Willeit, both from the University of Cambridge, said that UK Biobank’s biggest future impact will likely be from its contribution towards more targeted analyses of risk factors for diseases and health outcomes.

“From a research point of view, UK Biobank is starting to show its true potential. Much more is yet to come: genetic and biochemical information, long-term follow-up, disease morbidity, and linked hospital admission and primary care records.  The fact that data are available to researchers worldwide is an adventurous and positive strategy,” Thompson and Willeit wrote.  – by Casey Hower

Disclosure: The researchers report no relevant financial disclosures.