Introduction

Shift work is associated with an increased risk of developing cardiometabolic diseases (Ho et al., 2022). Experimental research has demonstrated decreased insulin sensitivity after simulated nightshifts (Morris et al., 2016). Despite these well-documented consequences of shift work, feasible mitigation strategies are lacking. Exercise is beneficial for cardiometabolic health, with moderate-intensity exercise improving insulin sensitivity (Bird and Hawley, 2016). Therefore, exercise may alleviate the effect of shift work on cardiometabolic health. Hence, this study aimed to investigate the impact of exercise before or after a simulated nightshift on metabolic health in adults.   

Methods 

Seven healthy participants completed a familiarisation and three experimental trials in a randomised, counterbalanced, crossover design, separated by at least seven days. The experimental protocol involved a simulated 12-hour nightshift, with exercise (30 minutes cycling at 60% of VO_2max peak power) either immediately before (PRE) or immediately after (POST) the shift, or no exercise (CON). Each trial started at 07:00, with a nap opportunity from 15:00-17:00. The simulated nightshift then started at 20:00. During the shift, participants completed cognitive assessments, appetite and fatigue questionnaires, light physical activity, and consumed a standardised diet. Participants were then in bed from 10:00-16:00. Wrist actigraphy was used to ensure compliance. At 17:00, an oral glucose tolerance test (OGTT) was conducted, with blood samples collected for measurement of insulin and glucose, followed by an ad-libitum evening meal to assess energy intake. Linear mixed models were used to compare outcomes between trials. Data are presented as mean ± SD, with significance set at p<0.05. 

Results

No significant differences were present between the PRE, POST and CON trials for glucose AUC (675.3 ±131.1 AU, 700.1 ± 134.7 AU and 726.3 ± 140.8 AU, respectively; p= 0.761), insulin AUC (2862.1 ± 1307.3 AU, 3376.0 ± 1350.3 AU, and 3054.1 ± 617.2 AU, respectively; p= 0.470), Matsuda index (13.20 ± 3.44, 11.08 ± 2.34 and 11.72 ± 2.81 respectively; p= 0.381) and HOMA-IR (0.66 ± 0.06, 0.80 ± 0.25, and 0.77 ± 0.67, respectively; p= 0.151). No significant differences were observed for substrate utilisation (CHO oxidation PRE: 106.4 ± 25.8g vs POST: 105.4 ± 20.0g; p= 0.516 and fat oxidation PRE; -1.1 ± 3.4g vs POST: -2.3 ± 3.0g; p= 0.263), rate of perceived exertion (p= 0.216) or heart rate (p= 0.106) during exercise before compared to after the simulated nightshift. Ad-libitum energy intake was not significantly different between trials (1021 ± 500 Kcal, 1137 ± 454 Kcal, and 1108 ± 677 Kcal for PRE, POST and CON, respectively; p= 0.106).

Discussion 

This interim analysis demonstrated no significant impact of exercise before or after a simulated nightshift on metabolic health markers during an OGTT, or changes in physiological variables during exercise before compared to after a shift. The findings suggest that acute exercise is not sufficient to induce meaningful improvements in metabolic markers. However, due to the sample size in the current interim analysis, further research is warranted to fully understand the efficacy of exercise in mitigating the consequences of shift work on metabolic health.