Feitong Wu1, Katja Pahkala2,3,4, Markus Juonala5,6, Suvi P Rovio2, Matthew A Sabin7, Tapani Rönnemaa5,6, Marie-Jeanne Buscot1, Kylie J Smith1, Satu Männistö8, Antti Jula9, Terho Lehtimäki10, Nina Hutri-Kähönen11, Mika Kähönen12, Tomi Laitinen13, Jorma S A Viikari5,6, Olli T Raitakari2,4,14, Costan G Magnussen1,2,4. 1. Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia. 2. Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland. 3. Paavo Nurmi Centre, Sports & Exercise Medicine Unit, Department of Physical Activity and Health, University of Turku, Turku, Finland. 4. Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland. 5. Department of Medicine, University of Turku, Turku, Finland. 6. Division of Medicine, Turku University Hospital, Turku, Finland. 7. Murdoch Children's Research Institute, Royal Children's Hospital, and Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia. 8. Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland. 9. National Institute for Health and Welfare, Turku, Finland. 10. Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center-Tampere, Tampere University, Tampere, Finland. 11. Department of Pediatrics, Tampere University and Tampere University Hospital, Tampere, Finland. 12. Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland. 13. Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland. 14. Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.
Abstract
CONTEXT: The influence of dietary pattern trajectories from youth to adulthood on adult glucose metabolism is unknown. OBJECTIVE: To identify dietary pattern trajectories from youth to adulthood and examine their associations with adult impaired fasting glucose (IFG). METHODS: Thirty-one-year population-based cohort study among 1007 youths aged 3-18 years at baseline in Finland. Diet intake was assessed in 1980, 1986, 2001, 2007, and 2011. Group-based trajectory modelling was used to identify dietary pattern (identified by factor analysis) trajectories. Adult IFG was measured by the latest available data from 2001, 2007, and 2011. RESULTS: Among 1007 participants, 202 (20.1%) developed IFG and 27 (2.7%) developed type 2 diabetes in adulthood (mean follow-up of 30.7 years; mean [SD] age 40.5 [5.0] years). Three dietary patterns were identified at baseline and were retained in 1986 and 2001: "Traditional Finnish," "High carbohydrate," and "Vegetables and dairy products." Three different patterns were identified in 2007, which remained similar in 2011: "Traditional Finnish and high carbohydrate," "Red meat," and "Healthy." Trajectories of increased or stably medium "red meat" pattern scores from youth to adulthood were detrimentally associated with IFG (relative risk 1.46, 95% CI 1.12-1.90 for Medium (M)-stable/M-large increase vs low-stable trajectory) after adjusting for confounders. This association was slightly reduced after further adjusting for long-term dietary fiber intake. CONCLUSION: Trajectories of an increased or stably moderate adherence to a "red meat" dietary pattern from youth to adulthood are associated with higher risk of adult IFG. This association is partly explained by low dietary fiber intake.
CONTEXT: The influence of dietary pattern trajectories from youth to adulthood on adult glucose metabolism is unknown. OBJECTIVE: To identify dietary pattern trajectories from youth to adulthood and examine their associations with adult impaired fasting glucose (IFG). METHODS: Thirty-one-year population-based cohort study among 1007 youths aged 3-18 years at baseline in Finland. Diet intake was assessed in 1980, 1986, 2001, 2007, and 2011. Group-based trajectory modelling was used to identify dietary pattern (identified by factor analysis) trajectories. Adult IFG was measured by the latest available data from 2001, 2007, and 2011. RESULTS: Among 1007 participants, 202 (20.1%) developed IFG and 27 (2.7%) developed type 2 diabetes in adulthood (mean follow-up of 30.7 years; mean [SD] age 40.5 [5.0] years). Three dietary patterns were identified at baseline and were retained in 1986 and 2001: "Traditional Finnish," "High carbohydrate," and "Vegetables and dairy products." Three different patterns were identified in 2007, which remained similar in 2011: "Traditional Finnish and high carbohydrate," "Red meat," and "Healthy." Trajectories of increased or stably medium "red meat" pattern scores from youth to adulthood were detrimentally associated with IFG (relative risk 1.46, 95% CI 1.12-1.90 for Medium (M)-stable/M-large increase vs low-stable trajectory) after adjusting for confounders. This association was slightly reduced after further adjusting for long-term dietary fiber intake. CONCLUSION: Trajectories of an increased or stably moderate adherence to a "red meat" dietary pattern from youth to adulthood are associated with higher risk of adult IFG. This association is partly explained by low dietary fiber intake.