Theoretical prediction of life expectancy using lifestyle factors in the EPIC-Heidelberg cohort. (30th September 2020)

• Record Type: Journal Article
• Authors: Srour, B; Hüsing, A; Gonzales Maldonado, S; Kühn, T; Kaaks, R
• Is Part Of: European journal of public health. Volume 30(2020)Supplement 5
• Publication Date: 2020-09-30
• Subjects: Epidemiology -- Europe -- Periodicals; Public health -- Europe -- Periodicals; 362.109405
• DOI: 10.1093/eurpub/ckaa165.054
• Languages: English
• ISSNs: 1101-1262

Abstract

Abstract: Background: The past few decades have witnessed a substantial increase in life expectancy in Western countries, leading to an increase in the prevalence of age-related chronic diseases. Several lifestyle risk factors (i.e. smoking, adiposity, unhealthy diet, heavy alcohol drinking and lack of physical activity) have been responsible for a large proportion of premature deaths, as they can affect the incidence of age-related chronic diseases. Our objective was to predict the loss of residual life expectancy (RLE) associated with these lifestyle factors, using data from the EPIC-Heidelberg cohort, linked to an up-to-date mortality registry. Methods: A total of 23, 324 German adults, aged 40 years and above were included (1994-1998) and followed until June 2019. A multi-adjusted parametric proportional hazard model (Gompertz hazard distribution), used to predict survival probabilities, followed by a life table approach was used. Results: At age 40, being a heavy smoker (> 10 cigarettes/day) was associated with 10.5 y loss of RLE in men and 8.3 in women. Low body mass index (< 22.5 kg/m2) was associated with a RLE loss of 3.7 y in men and 1.4 y in women, while obesity was associated with 4.4 y in men and 3.8 y in women. Heavy alcohol drinking (> 4 drinks/day) was associated with a loss of 4.5 y in men, and high red/processed meat consumption (≥ 120 g/day) was associated with a loss of 1.1y in men and 2.1 y in women. Compared with an overall healthy lifestyle, combined unhealthy behaviors were associated with a loss of RLE of 21.4 y in men and 15.5 y in women. Conclusions: Prevention strategies encouraging the adoption of an overall healthy lifestyle, particularly by avoiding smoking, heavy alcohol drinking, excess body fatness and reducing red/processed meat consumption, help reducing premature deaths. An extension of this project using blood biomarkers measures is ongoing. Key messages: Adopting a healthy lifestyle by avoiding or reducing the exposure to risk factors might contribute to a longer life expectancy. Tobacco use, adiposity, and alcohol are probably the main modifiable lifestyle factors affecting life expectancy.