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The life expectancy table generated in this study shows a substantial variation in life expectancy across individuals with different modifiable risk factors. Non-smokers and women had a higher life expectancy than smokers and men, respectively, with the difference in life expectancy ranging from 0.4 years to 2.7 years between non-smokers and smokers, and from 1.9 years to 5.9 years between women and men, depending on levels of other risk factors. Individuals with the lowest level (20 kg/m 2) and highest level of BMI (35 kg/m 2) had a lower life expectancy compared with those with a BMI of 25 kg/m 2. The variation in life expectancy was a function of the combination of risk factor values, with HbA 1c and eGFR consistently showing a negative and positive correlation, respectively, with life expectancy at any level combination of other risk factors. In 20-year-old women, this gap was 18.9 years (life expectancy range 35.0–53.9 years). Life expectancy of 20-year-old men varied from 29.3 years to 50.6 years, constituting a gap of 21.3 years between those with worst and best risk factor levels.
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There was a substantial variation in life expectancy across patients with different risk factor levels.
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The simulations were executed for all synthetic cohorts and life expectancy for each cell was calculated as mean survival time of the individuals in the respective cohort. For each of 1024 cells in the life expectancy table, a synthetic cohort containing 1000 individuals was created, with other risk factors assigned values representative of the real-world population. The following six important risk factors were included in the life table: sex age current smoking status BMI eGFR and HbA 1c. The simulation model was developed using data from a real-world population of patients with type 1 diabetes selected from the Swedish National Diabetes Register. We aimed to develop a life expectancy table using a recently published simulation model for individuals with type 1 diabetes. Tables reporting life expectancies by common risk factors are available for individuals with type 2 diabetes however, there is currently no published equivalent for individuals with type 1 diabetes.