Qian Xiao1, Jingyi Qian2,3, Daniel S Evans4, Susan Redline5, Nancy E Lane6, Sonia Ancoli-Israel7,8, Frank A J L Scheer9,3, Katie Stone. 1. Department of Epidemiology, Human Genetics and Environmental Health, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX qian.xiao@uth.tmc.edu. 2. Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA qian.xiao@uth.tmc.edu. 3. Division of Sleep Medicine, Department of Medicine, Harvard Medical School, Boston, MA. 4. Research Institute, California Pacific Medical Center Research Institute, San Francisco, CA. 5. Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Boston, MA. 6. Center for Musculoskeletal Health, Medicine and Rheumatology, University of California at Davis School of Medicine, Sacramento, CA. 7. Departments of Psychiatry and Medicine, University of California, San Diego, La Jolla, CA. 8. Department of Veterans Affairs San Diego Center of Excellence for Stress and Mental Health, La Jolla, CA. 9. Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, MA.
Abstract
OBJECTIVE: Disruption of rest-activity rhythms is cross-sectionally associated with metabolic disorders, including type 2 diabetes, yet it remains unclear whether it predicts impaired glucose metabolism and homeostasis. The aim of this study is to examine the cross-sectional and prospective associations between rest-activity rhythm characteristics and glycemic measures in a cohort of older men. RESEARCH DESIGN AND METHODS: Baseline rest-activity rhythms were derived from actigraphy with use of extended cosine model analysis. With subjects fasting, glucose, insulin, and HOMA of insulin resistance (HOMA-IR) were measured from blood at baseline and after ∼3.5 years. Type 2 diabetes was defined based on self-report, medication use, and fasting glucose. RESULTS: In the cross-sectional analysis (n = 2,450), lower 24-h amplitude-to-mesor ratio (i.e., mean activity-adjusted rhythm amplitude) and reduced overall rhythmicity were associated with higher fasting insulin and HOMA-IR (all P trend < 0.0001), indicating increased insulin resistance. The odds of baseline type 2 diabetes were significantly higher among those in the lowest quartile of amplitude (Q1) (odds ratio [OR]Q1 vs. Q4 1.63 [95% CI 1.14, 2.30]) and late acrophase group (ORlate vs. normal 1.46 [95% CI 1.04, 2.04]). In the prospective analysis (n = 861), multiple rest-activity characteristics predicted a two- to threefold increase in type 2 diabetes risk, including a lower amplitude (ORQ1 vs. Q4 3.81 [95% CI 1.45, 10.00]) and amplitude-to-mesor ratio (OR 2.79 [95% CI 1.10, 7.07]), reduced overall rhythmicity (OR 3.49 [95% CI 1.34, 9.10]), and a late acrophase (OR 2.44 [1.09, 5.47]). CONCLUSIONS: Rest-activity rhythm characteristics are associated with impaired glycemic metabolism and homeostasis and higher risk of incident type 2 diabetes.
OBJECTIVE: Disruption of rest-activity rhythms is cross-sectionally associated with metabolic disorders, including type 2 diabetes, yet it remains unclear whether it predicts impaired glucose metabolism and homeostasis. The aim of this study is to examine the cross-sectional and prospective associations between rest-activity rhythm characteristics and glycemic measures in a cohort of older men. RESEARCH DESIGN AND METHODS: Baseline rest-activity rhythms were derived from actigraphy with use of extended cosine model analysis. With subjects fasting, glucose, insulin, and HOMA of insulin resistance (HOMA-IR) were measured from blood at baseline and after ∼3.5 years. Type 2 diabetes was defined based on self-report, medication use, and fasting glucose. RESULTS: In the cross-sectional analysis (n = 2,450), lower 24-h amplitude-to-mesor ratio (i.e., mean activity-adjusted rhythm amplitude) and reduced overall rhythmicity were associated with higher fasting insulin and HOMA-IR (all P trend < 0.0001), indicating increased insulin resistance. The odds of baseline type 2 diabetes were significantly higher among those in the lowest quartile of amplitude (Q1) (odds ratio [OR]Q1 vs. Q4 1.63 [95% CI 1.14, 2.30]) and late acrophase group (ORlate vs. normal 1.46 [95% CI 1.04, 2.04]). In the prospective analysis (n = 861), multiple rest-activity characteristics predicted a two- to threefold increase in type 2 diabetes risk, including a lower amplitude (ORQ1 vs. Q4 3.81 [95% CI 1.45, 10.00]) and amplitude-to-mesor ratio (OR 2.79 [95% CI 1.10, 7.07]), reduced overall rhythmicity (OR 3.49 [95% CI 1.34, 9.10]), and a late acrophase (OR 2.44 [1.09, 5.47]). CONCLUSIONS: Rest-activity rhythm characteristics are associated with impaired glycemic metabolism and homeostasis and higher risk of incident type 2 diabetes.
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