0222 A shift in the circadian timing of calories and an increase in sleep variability are associated with changes in cardiometabolic health in a real-world setting. (25th May 2022)

• Record Type: Journal Article
• Authors: McHill, Andrew; Velasco, Josie; Gillingham, Melanie; Shea, Steven; Olson, Ryan
• Is Part Of: Sleep. Volume 45(2022)Supplement 1
• Page Start: A101
• Page End: A101
• Publication Date: 2022-05-25
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsac079.220
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Obesity and cardiovascular disease are commonplace in industrialized societies, particularly in nightshift workers. To investigate whether a shift in the circadian timing of energy intake or an increase in sleep variability may be mechanisms for adverse cardiometabolic health, we leveraged a natural experiment that occurs in newly-hired bus operators as they transition from a regularly-timed training schedule into an erratically-timed (i.e., early-morning or late evening) work schedule. Methods: Twenty-one newly-hired bus operators (8 females, 37.1y±6.4y [mean±SD]) were studied in an ~90-day protocol. During dayshift training (i.e., baseline), participants underwent a battery of in-laboratory cardiometabolic health assessments (i.e., blood pressure [BP], blood draw, body fat percentage), and a salivary dim-light melatonin assessment (DLMO). Participants then completed daily sleep-wake diaries and recorded all food and beverages consumed using a photographic time-stamped phone application (MealLoggerTM) for one week. These measurements were repeated ~30 and ~90 days after starting their new work schedules operating a bus. Caloric intake was determined via registered dieticians and DLMO was defined using a 3pg/ml threshold. As indices of caloric timing we used the time when participants consumed 50% of daily calories (caloric midpoint), and the percent of daily calories consumed within 4h of DLMO. Sleep variability was measured as the standard deviation of sleep onset timing. Associations were calculated using Pearson's correlations. Results: After 90-days of working, caloric midpoint occurred 2h later than baseline (16:22±02:41 vs. 14:24±02:07; p<0.01). This shift in timing was correlated with increases in systolic BP (r2=0.28; p=0.02) and low-density lipoprotein cholesterol (r2=0.28; p=0.03). An increase in sleep variability at 90-days was also positively correlated with systolic BP (r2=0.31; p=0.02). The change in percent of calories consumed within 4h of DLMO was positively correlated with change in percentage body fat (r2=0.27; p=0.03). Last, there was no significant correlation between the change in daily calories consumed and body fat percentage (p=0.24). Conclusion: Changes in the timing of caloric intake relative to DLMO, along with increases in sleep variability, may be mechanisms for increased cardiometabolic risk. These behaviors are potential targets for intervention to improve cardiometabolic health. Support (If Any): R01HL105495, K01HL146992