Adherence to a Healthy Sleep Pattern and Risk of Chronic Kidney Disease: The UK Biobank Study |
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| Affiliation: | 1. Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA;2. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA;1. Keele Cardiovascular Research Group, Centre for Prognosis Research, Institutes of Applied Clinical Science and Primary Care and Health Sciences, Keele University, UK;2. Royal Stoke University Hospital, Stoke-on-Trent, UK;3. Division of Cardiology, McMaster University, Hamilton, Canada;4. Population Health Research Institute, Hamilton, Canada;5. ICES, Hamilton, Canada;6. Libin Institute, University of Calgary, Calgary, Canada;7. Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK;1. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN;2. Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN;3. Department of Neurology, Mayo Clinic, Rochester, MN;4. Women’s Health Research Center, Mayo Clinic, Rochester, MN;5. Division of Geriatric Medicine and Gerontology, Johns Hopkins University, Baltimore, MD;1. Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA;2. Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;3. Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA;4. Harvard Medical School, Boston, Massachusetts, USA;5. Computational Biology and Bioinformatics Program, Yale University, New Haven, Connecticut, USA;6. Division of Cardiovascular Medicine, Brigham and Women’s Hospital Heart and Vascular Center, Boston, Massachusetts, USA;1. Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA;2. Channing Division of Network Medicine, Department of Medicine, Brigham and Women''s Hospital and Harvard Medical School, Boston, MA, USA;3. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA;1. University of Texas Southwestern Medical School, Dallas, TX;2. Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX;3. Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD;4. Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD;5. Department of Kinesiology, Faculty of Medicine, Université Laval and VITAM – Centre de rercherche en santé durable, CIUSSS Capitale-Nationale, Québec, QC, Canada;6. AMRA Medical AB, Linköping, Sweden;7. Division of Society and Health, Linköping University, Linköping, Sweden;8. Division of Diagnostics and Specialist Medicine, Linköping University, Linköping, Sweden;9. Department of Health, Medicine, and Caring Sciences, Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden;10. Division of Biomedical Engineering, Department of Biomedical Engineering, Linköping University, Linköping, Sweden;11. University Hospitals Harrington Heart and Vascular Institute and Case Western Reserve University School of Medicine, Cleveland, OH;1. Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK;2. British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK;3. Human Nutrition Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle upon Tyne, UK;4. Center for Exercise Physiology Research, University Mayor, Santiago, Chile;5. Human Performance Lab, Education, Physical Activity and Health Research Unit, University Católica del Maule, Talca, Chile |
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| Abstract: | ObjectiveTo examine the association of a healthy sleep pattern, characterized by sleep of 7 to 8 h/d, morning person, no insomnia, no frequent snoring, and no daytime sleepiness, with the risk of chronic kidney disease (CKD).MethodsWe included 392,218 European adults, aged 38 to 73 years, who were free of CKD at recruitment between March 13, 2006, and October 1, 2010, from the UK Biobank study. Data on sleep behaviors were collected through questionnaires at recruitment. Cox proportional hazards regression models were used to assess the relations between the healthy sleep score and risk of CKD.ResultsWe identified 18,842 incident CKD cases after a mean follow-up of 11.1 (SD 2.2) years. The healthy sleep score was inversely associated with the risk of CKD in a dose-dependent manner (P for trend, <.001). Compared with the participants with a poor sleep pattern (score of 0-1), the multivariate adjusted hazard ratio of CKD was 0.77 (95% CI, 0.71 to 0.84) for those with the healthiest sleep pattern (score of 5). In addition, we found that the inverse association was stronger in individuals without history of hypertension compared with individuals with hypertension at baseline (P for interaction, .003) and in those 60 years of age or younger compared with their older counterparts (P for interaction, <.001).ConclusionOur data suggest that adherence to an overall healthy sleep pattern is associated with a lower risk of CKD, especially for individuals without history of hypertension and those who are younger. |
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