The effect of high-dose, short-term caffeine intake on the renal clearance of calcium, sodium and creatinine in healthy adults.

The consumption of caffeine has been linked to osteoporosis, believed to be due to enhanced bone resorption as a result of increased calcium excretion in the urine. However, the amount of calcium in the urine may not necessarily reflect the true effect of caffeine on calcium clearance. This study therefore examined the impact of high-dose, short-term caffeine intake on renal clearance of calcium, sodium and creatinine in healthy adults. In a double-blind clinical study, participants chewed caffeine (n = 12) or placebo (n = 12) gum for 5 minutes at 2-hour intervals over a 6-hour treatment period (800 mg total caffeine). Caffeine increased renal calcium clearance by 77%. Furthermore, the effect was positively correlated with sodium clearance and urine volume, suggesting that caffeine may act through inhibition of sodium reabsorption in the proximal convoluted tubule. This study confirmed that caffeine does increase renal calcium clearance and fosters further investigation into safe consumption of caffeine.

Effects of strategic early-morning caffeine gum administration on association between salivary alpha-amylase and neurobehavioural performance during 50 h of sleep deprivation.

Self-assessment is the most common method for monitoring performance and safety in the workplace. However, discrepancies between subjective and objective measures have increased interest in physiological assessment of performance. In a double-blind placebo-controlled study, 23 healthy adults were randomly assigned to either a placebo (n = 11; 5 F, 6 M) or caffeine condition (n = 12; 4 F, 8 M) while undergoing 50 h (i.e. two days) of total sleep deprivation. In previous work, higher salivary alpha-amylase (sAA) levels were associated with improved psychomotor vigilance and simulated driving performance in the placebo condition. In this follow-up article, the effects of strategic caffeine administration on the previously reported diurnal profiles of sAA and performance, and the association between sAA and neurobehavioural performance were investigated. Participants were given a 10 h baseline sleep opportunity (monitored via standard polysomnography techniques) prior to undergoing sleep deprivation (total sleep time: placebo = 8.83 ±â€¯0.48 h; caffeine = 9.01 ±â€¯0.48 h). During sleep deprivation, caffeine gum (200 mg) was administered at 01:00 h, 03:00 h, 05:00 h, and 07:00 h to participants in the caffeine condition (n = 12). This strategic administration of caffeine gum (200 mg) has been shown to be effective at maintaining cognitive performance during extended wakefulness. Saliva samples were collected, and psychomotor vigilance and simulated driving performance assessed at three-hour intervals throughout wakefulness. Caffeine effects on diurnal variability were compared with previously reported findings in the placebo condition (n = 11). The impact of caffeine on the circadian profile of sAA coincided with changes in neurobehavioural performance. Higher sAA levels were associated with improved performance on the psychomotor vigilance test during the first 24 h of wakefulness in the caffeine condition. However, only the association between sAA and response speed (i.e. reciprocal-transform of mean reaction time) was consistent across both days of sleep deprivation. The association between sAA and driving performance was not consistent across both days of sleep deprivation. Results show that the relationship between sAA and reciprocal-transform of mean reaction time on the psychomotor vigilance test persisted in the presence of caffeine, however the association was relatively weaker as compared with the placebo condition.

The impact of caffeine consumption during 50 hr of extended wakefulness on glucose metabolism, self-reported hunger and mood state.

Caffeine is known for its capacity to mitigate performance decrements. The metabolic side-effects are less well understood. This study examined the impact of cumulative caffeine doses on glucose metabolism, self-reported hunger and mood state during 50 hr of wakefulness. In a double-blind laboratory study, participants were assigned to caffeine (n = 9, 6M, age 21.3 ± 2.1 years; body mass index 21.9 ± 1.6 kg/m2 ) or placebo conditions (n = 8, 4M, age 23.0 ± 2.8 years; body mass index 21.8 ± 1.6 kg/m2 ). Following a baseline sleep (22:00 hours-08:00 hours), participants commenced 50 hr of sleep deprivation. Meal timing and composition were controlled throughout the study. Caffeine (200 mg) or placebo gum was chewed for 5 min at 01:00 hours, 03:00 hours, 05:00 hours and 07:00 hours during each night of sleep deprivation. Continual glucose monitors captured interstitial glucose 2 hr post-breakfast, at 5-min intervals. Hunger and mood state were assessed at 10:00 hours, 16:30 hours, 22:30 hours and 04:30 hours. Caffeine did not affect glucose area under the curve (p = 0.680); however, glucose response to breakfast significantly increased after 2 nights of extended wakefulness compared with baseline (p = 0.001). There was a significant main effect of day, with increased tiredness (p < 0.001), mental exhaustion (p < 0.001), irritability (p = 0.002) and stress (p < 0.001) on the second day of extended wake compared with day 1. Caffeine attenuated the rise in tiredness (p < 0.001), mental exhaustion (p = 0.044) and irritability (p = 0.018) on day 1 but not day 2. Self-reported hunger was not affected by sleep deprivation or caffeine. These data confirm the effectiveness of caffeine in improving performance under conditions of sleep deprivation by reducing feelings of tiredness, mental exhaustion and irritability without exacerbating glucose metabolism and feelings of hunger.

Timing of food intake during simulated night shift impacts glucose metabolism: A controlled study.

Eating during the night may increase the risk for obesity and type 2 diabetes in shift workers. This study examined the impact of either eating or not eating a meal at night on glucose metabolism. Participants underwent four nights of simulated night work (SW1-4, 16:00-10:00 h, <50 lux) with a daytime sleep opportunity each day (10:00-16:00 h, <3 lux). Healthy males were assigned to an eating at night (NE; n = 4, meals; 07:00, 19:00 and 01:30 h) or not eating at night (NEN; n = 7, meals; 07:00 h, 09:30, 16:10 and 19:00 h) condition. Meal tolerance tests were conducted post breakfast on pre-night shift (PRE), SW4 and following return to day shift (RTDS), and glucose and insulin area under the curve (AUC) were calculated. Mixed-effects ANOVAs were used with fixed effects of condition and day, and their interactions, and a random effect of subject identifier on the intercept. Fasting glucose and insulin were not altered by day or condition. There were significant effects of day and condition × day (both p < 0.001) for glucose AUC, with increased glucose AUC observed solely in the NE condition from PRE to SW4 (p = 0.05) and PRE to RTDS (p < 0.001). There was also a significant effect of day (p = 0.007) but not condition × day (p = 0.825) for insulin AUC, with increased insulin from PRE to RTDS in both eating at night (p = 0.040) and not eating at night (p = 0.006) conditions. Results in this small, healthy sample suggest that not eating at night may limit the metabolic consequences of simulated night work. Further study is needed to explore whether matching food intake to the biological clock could reduce the burden of type 2 diabetes in shift workers.

It's not just what you eat but when: The impact of eating a meal during simulated shift work on driving performance.

Shiftworkers have impaired performance when driving at night and they also alter their eating patterns during nightshifts. However, it is unknown whether driving at night is influenced by the timing of eating. This study aims to explore the effects of timing of eating on simulated driving performance across four simulated nightshifts. Healthy, non-shiftworking males aged 18-35 years (n = 10) were allocated to either an eating at night (n = 5) or no eating at night (n = 5) condition. During the simulated nightshifts at 1730, 2030 and 0300 h, participants performed a 40-min driving simulation, 3-min Psychomotor Vigilance Task (PVT-B), and recorded their ratings of sleepiness on a subjective scale. Participants had a 6-h sleep opportunity during the day (1000-1600 h). Total 24-h food intake was consistent across groups; however, those in the eating at night condition ate a large meal (30% of 24-h intake) during the nightshift at 0130 h. It was found that participants in both conditions experienced increased sleepiness and PVT-B impairments at 0300 h compared to 1730 and 2030 h (p < 0.001). Further, at 0300 h, those in the eating condition displayed a significant decrease in time spent in the safe zone (p < 0.05; percentage of time within 10 km/h of the speed limit and 0.8 m of the centre of the lane) and significant increases in speed variability (p < 0.001), subjective sleepiness (p < 0.01) and number of crashes (p < 0.01) compared to those in the no eating condition. Results suggest that, for optimal performance, shiftworkers should consider restricting food intake during the night.