Converting health risks into loss of life years - a paradigm shift in clinical risk communication

Shan Pou Tsai, Chi Pang Wen, Min Kuang Tsai, Po Jung Lu, Jackson Pui Man Wai, Christopher Wen, Wayne Gao, Xifeng Wu

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


For facilitating risk communication in clinical management, such a ratio-based measure becomes easier to understand if expressed as a loss of life expectancy. The cohort, consisting of 543,410 adults in Taiwan, was recruited between 1994 and 2008. Health risks included lifestyle, biomarkers, and chronic diseases. A total of 18,747 deaths were identified. The Chiang’s life table method was used to estimate a loss of life expectancy. We used Cox regression to calculate hazard ratios (HRs) for health risks. The increased mortality from cardiometabolic risks such as high cholesterol (HR=1.10), hypertension (HR=1.48) or diabetes (HR=2.02) can be converted into a loss of 1.0, 4.4, and 8.9 years in life expectancy, respectively. The top 20 of the 30 risks were associated with a loss of 4 to 10 years of life expectancy, with 70% of the cohort having at least two such risk factors. Smoking, drinking, and physical inactivity each had 5-7 years loss. Individuals with diabetes or an elevated white count had a loss of 7-10 years, while prolonged sitting, the most prevalent risk factor, had a loss of 2-4 years. Those with diabetes (8.9 years) and proteinuria (9.1 years) present at the same time showed a loss of 16.2 years, a number close to the sum of each risk. Health risks, expressed as life expectancy loss, could facilitate risk communication. The paradigm shift in expressing risk intensity can help set public health priorities scientifically to promote a focus on the most important ones in primary care

Original languageEnglish
Pages (from-to)21513-21525
Number of pages13
Issue number17
Publication statusPublished - Sept 15 2021


  • cohort
  • hazard ratio
  • health risks
  • life expectancy
  • mortality

ASJC Scopus subject areas

  • Ageing
  • Cell Biology


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