A new online atlas can predict how life expectancy is affected by contracting one of 1800 diseases – although the tool may work well only for people in Denmark
16 June 2022
Working out the years lost to a disease is extraordinarily difficult. One approach involves examining statistics on the age at which the disease typically causes people to die, and how long these people would have been expected to live if they hadn’t developed the disease. However, this can only be calculated by researchers if the disease is classed as the cause of death.
A second approach is to calculate the average life expectancy for people who develop a specific disease at a certain age, then compare it with the life expectancy for people of the same age who don’t have the disease. But in practice, researchers tend to simplify these calculations and assume people develop a given condition at one particular age – for example, the impact of mental illnesses on mortality is generally calculated assuming that people developed a mental health condition at age 15.
This simplification means the statistics ignore the effect that diseases might have on the lifespan of people who developed them at different ages.
Now, Oleguer Plana-Ripoll at Aarhus University, Denmark, and his colleagues have applied an existing statistical model to estimate the life years lost to disease by about 7.4 million people living in Denmark between 2000 and 2018. The researchers focused on 1803 common conditions, including some affecting the lungs, circulatory system, gut, urinary tract, nervous system and brain.
Each individual was tracked by the team for the 18-year period, or until they died or no longer lived in Denmark. By the end of the study period, 14 per cent of the people had died. The data allowed the researchers to tailor their estimates of life expectancy so they could take into account the age at which someone developed one of the diseases.
The new tool, called the Danish Atlas of Disease Mortality, could become a useful resource for researchers investigating the mortality rates associated with particular diseases, says Plana-Ripoll. “We are giving them some preliminary results so they can know if it is worth getting hold of the raw data,” he says.
It could also be helpful for clinicians in their interactions with people who develop one of the conditions, he says. “They can see: how do the mortality rates for these patients at this age look? And do they, perhaps, [need to] set up some extra follow-up meetings with this individual?” says Plana-Ripoll.
However, the mortality metrics may not apply to people living outside of Denmark.
Journal reference: PLoS Medicine, DOI: 10.1371/journal.pmed.1004023
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