Mirja Quante1, Elizabeth M Cespedes Feliciano2, Sheryl L Rifas-Shiman3, Sara Mariani4, Emily R Kaplan4, Michael Rueschman4, Emily Oken5, Elsie M Taveras6, Susan Redline7. 1. Department of Neonatology, University of Tuebingen, Tuebingen, Germany; Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, Massachusetts. Electronic address: mirja.quante@med.uni-tuebingen.de. 2. Division of Research, Kaiser Permanente Northern California, Oakland, California. 3. Division of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts. 4. Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, Massachusetts. 5. Division of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. 6. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Division of General Academic Pediatrics, Department of Pediatrics, MassGeneral Hospital for Children, Boston, Massachusetts. 7. Division of Sleep and Circadian Disorders, Department of Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, Massachusetts; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Abstract
PURPOSE: Emerging data indicate that the timing and rhythms of energetic behaviors may influence metabolism and obesity risk. Our aim was to derive diurnal rest-activity patterns from actigraphy in adolescents and analyze associations with adiposity measures and cardiometabolic risk factors. METHODS: Adolescents in the Project Viva cohort wore a wrist actigraph over 7 days. We derived markers of daily rest-activity patterns from actigraphy using nonparametric models, generating measurements of relative amplitude (RA). RA reflects the normalized difference in activity measured during the most active 10-hour period and the least active 5-hour period, averaged over multiple 24-hour periods. Using multivariable-adjusted linear regression models, we estimated associations of RA and its components with markers of adiposity (body mass index, waist circumference, skinfolds, dual-energy X-ray absorptiometry fat mass) and cardiometabolic health (cardiometabolic risk score, derived as the mean of five sex-specific internal z-scores for waist circumference, systolic blood pressure, high-density lipoprotein cholesterol scaled inversely, and log-transformed triglycerides and homeostatic model assessment of insulin resistance). RESULTS: A total of 778 adolescents provided at least 5 days of valid actigraphy data. The average age was 13.2 (±.9) years, 52% were female, and the average RA was .9 (±.1). A higher RA reflecting higher activity during wakefulness and lower activity during the night was associated with more favorable indices of adiposity (e.g., -.35 kg/m2 lower body mass index per each .04 units increment of RA; 95% confidence interval: -.60 to -.09). CONCLUSIONS: In this large sample of adolescents, a higher RA emerged as a novel biomarker, associated with more favorable cardiometabolic profiles.
PURPOSE: Emerging data indicate that the timing and rhythms of energetic behaviors may influence metabolism and obesity risk. Our aim was to derive diurnal rest-activity patterns from actigraphy in adolescents and analyze associations with adiposity measures and cardiometabolic risk factors. METHODS: Adolescents in the Project Viva cohort wore a wrist actigraph over 7 days. We derived markers of daily rest-activity patterns from actigraphy using nonparametric models, generating measurements of relative amplitude (RA). RA reflects the normalized difference in activity measured during the most active 10-hour period and the least active 5-hour period, averaged over multiple 24-hour periods. Using multivariable-adjusted linear regression models, we estimated associations of RA and its components with markers of adiposity (body mass index, waist circumference, skinfolds, dual-energy X-ray absorptiometry fat mass) and cardiometabolic health (cardiometabolic risk score, derived as the mean of five sex-specific internal z-scores for waist circumference, systolic blood pressure, high-density lipoprotein cholesterol scaled inversely, and log-transformed triglycerides and homeostatic model assessment of insulin resistance). RESULTS: A total of 778 adolescents provided at least 5 days of valid actigraphy data. The average age was 13.2 (±.9) years, 52% were female, and the average RA was .9 (±.1). A higher RA reflecting higher activity during wakefulness and lower activity during the night was associated with more favorable indices of adiposity (e.g., -.35 kg/m2 lower body mass index per each .04 units increment of RA; 95% confidence interval: -.60 to -.09). CONCLUSIONS: In this large sample of adolescents, a higher RA emerged as a novel biomarker, associated with more favorable cardiometabolic profiles.
Authors: Elissa K Hoopes; Melissa A Witman; Michele N D'Agata; Felicia R Berube; Benjamin Brewer; Susan K Malone; Michael A Grandner; Freda Patterson Journal: Chronobiol Int Date: 2021-01-13 Impact factor: 2.877
Authors: Jingyi Qian; Nuria Martinez-Lozano; Asta Tvarijonaviciute; Rafael Rios; Frank A J L Scheer; Marta Garaulet Journal: Sleep Date: 2021-05-14 Impact factor: 5.849
Authors: Chloe Wilson; Alissa Nichles; Natalia Zmicerevska; Joanne Sarah Carpenter; Yun Ju Christine Song; Catherine McHugh; Blake Hamilton; Samuel Hockey; Elizabeth M Scott; Ian B Hickie Journal: BMJ Open Date: 2021-06-29 Impact factor: 2.692