抽象的な

2018 ???????: ????????????????: ?????????????? - ?????????????????????

 フランシス・オキャラハンとカイル・ワイアット

 Abstract Statement of the Problem: Poor sleep quality and excessive daytime sleepiness are positively associated with common mental disorders such as depression, anxiety and somatoform disorders, as well as lapses in concentration and daytime tiredness. These relationships are complicated among university students who have high caffeine consumption and high stress, both of which affect sleep quality. Methodology & Theoretical Orientation: This was a quantitative study involving 175 full-time university students from 17 to 25 years (mean=19.43, SD=2.06). Students completed an online questionnaire about their sleep quality, daytime functioning, caffeine consumption and recent level of stress symptomatology. Findings: Poor quality sleep was associated with diminished daytime functioning. Increased caffeine consumption influenced daytime functioning by lowering the quality of an individual???s sleep. However, the relationship between quantity of caffeine consumption and sleep was dependent on the time of day the caffeinated beverages were consumed. Increased stress was related to both reduced sleep quality and reduced daytime functioning. Conclusion: The findings highlight the implications for daytime functioning of university students not getting sufficient quality sleep and the role of lifestyle factors pertaining to caffeine use and stress. Introduction Caffeine (1,3,7-trimethylxanthine), particularly in the form of coffee, has become one of the most widely consumed and geographically distributed ergogenic aids, and is rated as the most widely consumed stimulant in the world. In the United States, for example, 90% of adults consume caffeine-infused beverages (ie, coffee, tea, energy, or other drinks) almost daily with consumption averaging 200 mg/day. Self-report data on caffeine consumption tend to underreport actual levels due to the confounding of “coffee” and “caffeine”—with other sources, such as analgesics including cold remedies, hot chocolate, tea, and energy drinks, often overlooked. For example, Wendte et al painstakingly documented the habitual intake of their participants, selecting those who regularly ingested from 100 to 500 mg of caffeine a day, finding an actual consumption range of 154–1285 mg. Such is the ubiquity of caffeine that it provides methodological challenges in terms of investigating its effects: it is difficult to provide a truly caffeine-free diet and given that the vast majority of people in countries such as the United States ingest caffeine of various forms almost daily,few research participants can present to a laboratory as truly caffeine naive. The popularity of caffeine is driven not only by taste, given that it is a common additive in the modern diet, but also by its reputation as a stimulant. A study by Desbrow and Leveritt also highlights the power associated with this reputation as a stimulant. They report that most athletes believe that caffeine improves both endurance and concentration. Notwithstanding lay perceptions, the evidence of a relationship between caffeine and performance is, however, substantial. The ability of caffeine to enhance physical performance was formally identified early in the 20th century and since then scholarly and military interest in the role of nutrition on physical performance has been intense. A comprehensive review by the Military Nutrition Division of the US Army Research Institute of Environmental Medicine found that of the nutritional components to have the clearest identifiable benefits, caffeine stands out most clearly as being a positive. Pharmacologically, caffeine is an adenosine-receptor antagonist. As such, it appears that the effects of caffeine on performance occur largely through its occupation of adenosine receptors. It acts primarily on A1 and A2A receptors, which in turn are related to functions of the brain associated with sleep, arousal, and cognition. Caffeine is efficiently and quickly absorbed by the stomach and small intestine, with peak plasma levels occurring in the first 30 min. Caffeine has a highly variable half-life, ranging from 2 to 10 h dependent on endogenous and exogenous factors. Nicotine use, for example, can increase the metabolic speed of caffeine by as much as 50%.This short half-life, however, may enable caffeine to be used strategically to enhance daytime functioning with an impact on sleep quality that could be predicted and mitigated. The residual effects, however, may be significant. Shi et al demonstrated that tolerance depends on the amount of caffeine consumed, and the schedule of consumption and elimination. They use a parametric pharmacokinetic–pharmacodynamic model to suggest that it can take up to 20 h (or the equivalent of four or five half-lives) for the effects of caffeine tolerance to wear off. Caffeine is placed in an unusual juxtaposition in relation to human performance: it clearly has the potential to enhance performance, but amongst its known side effects are sleep deprivation, which brings with it a risk of performance deficits. In this review, we examine this balance in the context of daytime functioning. The key question that we seek to answer is: can caffeine undo the harm it potentially causes through reducing the quality of overnight sleep? That is, can performance be sustained into a second day, subsequent to a night of sleep impaired through caffeine consumption, through the administration of caffeine? We explore this question in two distinct phases. First, we examine evidence illuminating the relationship between caffeine consumption and subsequent quality and quantity of nighttime rest. Second, we consider evidence as to whether performance deficits caused by sleep deprivation linked to caffeine can be reversed by caffeine consumption during the subsequent daytime period . Finally, we consider how these two stages can be reconciled in a single model that enables the effect of caffeine on daytime to be considered. Conclusion: integrating the findings Attempts to design integrated mathematical models that can predict the effects of sleep/wake schedules while incorporating adenosine-receptor antagonists like caffeine are rare. The two best validated predictive models of performance do not account for the interference by caffeine,1 while Benitez et al and Ramakrishnan et al attempt to incorporate caffeine, but do so by “cleaning up” the scenario by only looking at effects under conditions of total sleep deprivation. Two models have broken this trend: Puckeridge et al and Ramakrishnan et al.1 The more recent “unified” model1 is based on data drawn from two studies and then validated against a further five studies using a variety of populations and scenarios, but only used PVT data as a performance measure. None of the datasets used to validate the model followed normal day–night rhythms, with the focus of the model validation being on sleep rather than caffeine. Biography Frances O’Callaghan is a Health Psychologist in the School of Applied Psychology, Griffith University, Australia. Her research focuses on psychosocial influences on health and illness, sleep disorders and fetal alcohol spectrum disorders. f.ocallaghan@griffith.edu.au