Department of Epidemiology and Public Health, University College London, United Kingdom / Inserm U1153, Epidemiology of Ageing and Neurodegenrative Diseases, Paris, France.
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden / Centre for Occupational and Environmental Medicine, Stockholm County Council, Sweden.
National Research Centre for the Working Environment, Copenhagen, Denmark.
Bispebjerg University Hospital, Copenhagen, Denmark.
Federal Institute for Occupational Safety and Health, Berlin, Germany.
Faculty of Medicine, Paris Descartes University, Paris, France / Inserm UMS 011, Population-Based Epidemiological Cohorts Unit, Villejuif, France.
Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, United Kingdom.
Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland.
Department of Health Sciences, Mid Sweden University, Sundsvall, Sweden.
Clinicum, Department of Public Health, Faculty of Medicine, University of Helsinki, Finland / Finnish Institute of Occupational Health, Helsinki, Finland.
Clinicum, Department of Public Health, Faculty of Medicine, University of Helsinki, Finland.
AS3 Employment, AS3 Companies, Viby J, Denmark.
Stress Research Institute, Stockholm University, Sweden / Department of Psychology, Umeå University, Sweden.
Finnish Institute of Occupational Health, Helsinki, Finland.
VIVE-The Danish Center for Social Science Research, Copenhagen, Denmark.
Clinicum, Department of Public Health, Faculty of Medicine, University of Helsinki, Finland.
National Research Centre for the Working Environment, Copenhagen, Denmark / Department of Public Health, Department of Psychology, University of Copenhagen, Denmark.
Department of Epidemiology and Public Health, University College London, United Kingdom.
Clinicum, Department of Public Health, Faculty of Medicine, University of Helsinki, Finland.
Department of Public Health, University of Turku, Turku University Hospital, Finland / Centre for Population Health Research, University of Turku, Turku University Hospital, Finland.
Department of Public Health, University of Turku, Turku University Hospital, Finland / Centre for Population Health Research, University of Turku, Turku University Hospital, Finland.
School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland / Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Stress Research Institute, Stockholm University, Sweden.
Faculty of Medicine, Paris Descartes University, France / Inserm UMS 011, Population-Based Epidemiological Cohorts Unit, Villejuif, France.
Division of Surgery and Interventional Science, Faculty of Medical Sciences, University College London, United Kingdom.
Department of Epidemiology and Public Health, University College London, United Kingdom / School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, United States.
Clinicum, Department of Public Health, Faculty of Medicine, University of Helsinki, Finland / Department of Epidemiology and Public Health, University College London, United Kingdom.
Importance: It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with disease-free life-years is unknown. Objective: To estimate the association between healthy lifestyle and the number of disease-free life-years. Design, Setting, and Participants: A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020. Exposures: Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: Optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors. Main Outcomes and Measures: The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease. Results: Of the 116043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P <.001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: Never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex. Conclusions and Relevance: In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.
American Medical Association , 2020. Vol. 180, no 5, p. 760-768