thesis for caffeine research paper

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• Published: 25 February 2021

The impact of daily caffeine intake on nighttime sleep in young adult men

• Janine Weibel 1 , 2 ,
• Yu-Shiuan Lin 1 , 2 , 3 ,
• Hans-Peter Landolt 4 , 5 ,
• Joshua Kistler 1 , 2 ,
• Sophia Rehm 6 ,
• Katharina M. Rentsch 6 ,
• Helen Slawik 7 ,
• Stefan Borgwardt 3 ,
• Christian Cajochen 1 , 2   na1 &
• Carolin F. Reichert 1 , 2   na1  

Scientific Reports volume  11 , Article number:  4668 ( 2021 ) Cite this article

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• Slow-wave sleep

Acute caffeine intake can delay sleep initiation and reduce sleep intensity, particularly when consumed in the evening. However, it is not clear whether these sleep disturbances disappear when caffeine is continuously consumed during daytime, which is common for most coffee drinkers. To address this question, we investigated the sleep of twenty male young habitual caffeine consumers during a double-blind, randomized, crossover study including three 10-day conditions: caffeine (3 × 150 mg caffeine daily), withdrawal (3 × 150 mg caffeine for 8 days, then switch to placebo), and placebo (3 × placebo daily). After 9 days of continuous treatment, electroencephalographically (EEG)-derived sleep structure and intensity were recorded during a scheduled 8-h nighttime sleep episode starting 8 (caffeine condition) and 15 h (withdrawal condition) after the last caffeine intake. Upon scheduled wake-up time, subjective sleep quality and caffeine withdrawal symptoms were assessed. Unexpectedly, neither polysomnography-derived total sleep time, sleep latency, sleep architecture nor subjective sleep quality differed among placebo, caffeine, and withdrawal conditions. Nevertheless, EEG power density in the sigma frequencies (12–16 Hz) during non-rapid eye movement sleep was reduced in both caffeine and withdrawal conditions when compared to placebo. These results indicate that daily caffeine intake in the morning and afternoon hours does not strongly impair nighttime sleep structure nor subjective sleep quality in healthy good sleepers who regularly consume caffeine. The reduced EEG power density in the sigma range might represent early signs of overnight withdrawal from the continuous presence of the stimulant during the day.

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Introduction

Caffeine is the most popular psychoactive substance in the world 1 , consumed daily by around 80% of the population 2 . While caffeine is frequently used to counteract sleepiness and boost performance 3 , its consumption is commonly avoided in the evening 4 , 5 to prevent adverse consequences on nocturnal sleep 3 . The sleep disrupting effects of caffeine are mainly attributed to its influence on the homeostatic component of sleep-wake regulation. Sleep homeostasis describes the increase in sleep pressure during time awake and its dissipation during the following sleep episode 6 , which has been suggested to be related to rising and decreasing concentrations of adenosine 7 . Caffeine is an adenosine receptor antagonist, which blocks the A 1 and A 2A adenosine receptors in the central nervous system 1 . It may, thus, attenuate the increase in sleep pressure during wakefulness 8 and lead to delayed sleep initiation and more superficial sleep 9 .

The effects of caffeine intake on the quality and quantity of sleep depend on the timing of its consumption. More specifically, caffeine consumed in the evening hours prolongs sleep latency 10 , 11 , 12 , 13 , 14 , reduces total sleep time (TST) 10 , 11 , 12 , 14 , 15 , shortens deep sleep 10 , 12 , 13 , 14 , 15 , and decreases electroencephalographically (EEG)-derived slow-wave activity (SWA) 10 , while activity in the sigma range is increased 10 . However, evening caffeine intake only accounts for approximately 10–20% of the total daily caffeine intake in regular consumers 4 , 5 . It needs to be elucidated whether habitual caffeine intake restricted to the morning and afternoon hours similarly affects nighttime sleep.

Furthermore, not only the timing but also the frequency of preceding caffeine intake prior to sleep may be an important factor for the repercussions on sleep. The majority of the worldwide population consumes caffeine on a daily basis 2 , which can lead to tolerance development due to the recurrent supply of the psychostimulant 1 . In line with these results, the sleep-disrupting effects of continuous high-dose caffeine in the morning, afternoon, and evening (3 × 400 mg) intake vanished and only stage 4 sleep remained reduced after 1 week of caffeine intake 12 . However, whether more sensitive markers for sleep intensity such as spectral sleep EEG measures, adapt to the long-term exposure to the stimulant has to our best knowledge not yet been investigated.

Importantly, not only caffeine per se, but also the state of acute abstinence to which regular consumers expose themselves every night, might affect sleep. This so-called overnight abstinence represents the start of a caffeine withdrawal phase 16 . Withdrawal symptoms such as increased tiredness 17 , longer sleep duration, and better sleep quality 18 can be observed at a subjective level starting roughly 12 h after last caffeine intake 17 . However, the influence of caffeine withdrawal on objective EEG-derived sleep variables were not systematically reported up to date and remain to be compared against a placebo-baseline.

Here we aimed at determining whether daily caffeine intake during morning and afternoon hours impairs nighttime sleep structure and sleep intensity after continuous daytime caffeine intake over 9 days. We hypothesized a reduced depth of sleep after caffeine intake, indexed in shortened slow-wave sleep (SWS) duration and a decrease in SWA compared to placebo. Moreover, we hypothesized that the abrupt cessation from the daily intake generates acute subjective withdrawal symptoms, and changes sleep structure and intensity compared to both the daily caffeine intake and the placebo-baseline.

Salivary caffeine levels

Caffeine levels significantly differed between each of the three conditions (main effect of condition: F 2,90.7  = 46.12, p  < 0.001) with the highest levels in the caffeine condition and the lowest in the placebo condition (post-hoc comparisons: p all  < 0.01). In addition, a significant interaction of the factors condition and time ( F 2,89.6  = 10.65, p  < 0.001) confirmed that caffeine levels were modulated by time with levels decreasing during nighttime sleep in the caffeine condition only (post-hoc comparison: p  < 0.001), see Fig.  1 .

Average caffeine levels collected prior to and after nighttime sleep (grey bar) in the placebo (black open circles), caffeine (blue filled circles), and withdrawal (red semi-filled circles) condition (mean values ± standard errors). The x-axis indicates the mean time of day of sample collection and color-coded asterisks represent significant ( p  < 0.05) post-hoc comparisons of the interaction effect condition × time.

Table 1 summarizes the statistical analyses of subjective sleep quality and objective sleep structure assessed during nighttime sleep. Analyses of subjective sleep quality assessed with the Leeds Sleep Evaluation Questionnaire (LSEQ) did not reveal significant differences among the three conditions in any of the four domains of sleep quality ( p all  > 0.05).

In line with these results, the analyses of the polysomnography (PSG) did not reveal significant differences in total sleep time (TST), sleep efficiency (SE), sleep latencies, or the relative amount of sleep stages among the three conditions ( p all  > 0.05).

In a next step, we analyzed all-night EEG power density in the range of 0.75–32 Hz over the central derivations recorded during non-rapid eye movement (NREM) sleep. In contrast to our assumptions, we did not find any significant differences among the three conditions in the lower frequency bins (0.75–13.25 Hz; p all  > 0.05). However, power density was significantly reduced compared to placebo in the sigma range during both withdrawal (frequency bins 13.5–17.25 Hz and 18–18.5 Hz; p all  < 0.05) and caffeine (frequency bins 13.5–16 Hz; p all  < 0.05).

In a second step, we were interested in the temporal dynamics of both SWA and sigma activity across the night assessed during NREM sleep. As depicted in Fig.  2 (top panel), SWA showed a typical temporal pattern with increased activity during the first NREM cycle followed by a steady decline across the night (main effect of time: F 39,613  = 26.28, p  < 0.001). However, differences among the three conditions did not reach significance (main effect of condition: F 2,178  = 1.33, p  = 0.27). Also, the interaction of condition and time was not significant ( F 78,1060  = 0.89, p  = 0.74).

Temporal dynamics of SWA (top) and sigma activity (bottom) during the first four sleep cycles in the placebo (black open circles), caffeine (blue filled circles), and the withdrawal (red semi-filled circles) condition (mean values). The x-axis indicates the mean time of day. While SWA (0.75–4.5 Hz) was not significantly affected by the treatment, sigma activity (12–16 Hz) showed reduced activity during both caffeine and withdrawal compared to the placebo condition ( p all  < 0.05). The inset in each right upper corner represents the mean values ± standard errors of the all-night SWA and sigma activity respectively during NREM sleep in the placebo, caffeine, and withdrawal condition. While all-night SWA (0.75–4.5 Hz) did not differ among the conditions, sigma activity (12–16 Hz) was lower in the caffeine and withdrawal condition compared to placebo ( p  < 0.05). All analyses are based on log-transformed data.

As illustrated in Fig.  2 (bottom panel), sigma activity was significantly reduced in both the caffeine and withdrawal conditions compared to placebo intake (main effect of condition: F 2,209  = 19.96, p  < 0.001; post-hoc comparisons: p  < 0.001) and the interaction of condition and time tended to be significant ( F 78,1049  = 1.25, p  = 0.08).

Taken together, we could not confirm our assumption of a caffeine-induced reduction of sleep depth, neither in terms of shorter SWS nor in terms of reduced SWA in the caffeine compared to the placebo condition. Based on the discrepancies between the present results and a previous study about the effects of chronic caffeine intake on sleep 12 , we thus explored whether differences in the individual levels of caffeine before sleep could explain the variance within SWS and SWA. However, no significant effects were observed when controlling for dependent observations within subjects ( p  > 0.05).

Subjective caffeine withdrawal symptoms

Analyses of the relative withdrawal symptoms yielded a significant main effect of condition ( F 2,20.2  = 11.30, p  < 0.01) indicating more withdrawal symptoms during the withdrawal compared to the caffeine condition (post-hoc comparison: p  < 0.01), depicted in Fig.  3 . This effect was modulated by time (interaction of condition × time: F 2,37.2  = 3.43, p  = 0.04), such that the increase in symptoms during the withdrawal compared to caffeine condition was particularly present during the last measurement ( p  < 0.01), i.e. 31 h after the last caffeine intake in the withdrawal condition.

Relative withdrawal symptoms in the caffeine and withdrawal condition (i.e. withdrawal score of the caffeine and withdrawal condition respectively minus the score of the placebo condition) assessed 35 min, 4 h, and 8 h after wake-up on day ten of treatment. Depicted are mean values and standard errors of the relative values (i.e. difference to placebo). Overall, volunteers reported more withdrawal symptoms in the withdrawal condition compared to the caffeine condition ( p  < 0.05). This difference was particularly present 8 h after wake-up during withdrawal compared to caffeine ( p  < 0.001).

The aim of the present study was to investigate the influence of daily daytime caffeine intake and its cessation on nighttime sleep in habitual caffeine consumers under strictly controlled laboratory conditions. Strikingly, caffeine consumption did not lead to clear-cut changes in nighttime sleep structure nor in subjective sleep quality when assessed 8 and 15 h after the last intake in the caffeine and withdrawal condition, respectively. The evolution of subjective withdrawal symptoms indicates that withdrawal becomes perceivable at earliest between 27–31 h after intake. However, compared to placebo, EEG power density was reduced in the sigma range during both caffeine and withdrawal conditions. We conclude that daily daytime intake of caffeine does not strongly influence nighttime sleep structure nor subjective sleep quality in healthy men when consumed in the morning, midday, and in the afternoon. In contrast to the reported increases in sigma activity after acute caffeine intake 10 , the observed changes in the sigma frequencies might point to early signs of caffeine withdrawal which occur due to overnight abstinence and presumably derive from preceding caffeine-induced changes in adenosine signaling.

To quantify the influence of caffeine on sleep, the stimulant is commonly administered close to the onset of a sleep episode 10 , 11 , 12 , 13 , 14 , for instance within 1 h prior to bedtime 10 , 11 , 13 , 14 . Taking into account that caffeine plasma levels peak within 30–75 min following caffeine ingestion 19 , consumption within 1 h prior to sleep allows the stimulant to exert its maximum effects at sleep commencement. Indeed, the sleep disrupting effects of caffeine are frequently reported to affect sleep initiation or the first half of the sleep episode 10 , 11 , 12 , 13 , 14 . Moreover, sleep intensity, which is usually strongest at the beginning of the night 20 , was particularly disrupted during the first sleep cycle, as indexed in reduced SWS and SWA 10 . However, caffeine intake in the evening, particularly after 9 pm is rare 5 , presumably to avoid impairment of subsequent sleep 3 . Up to date it remained fairly unclear whether caffeine intake in the morning and afternoon still bears the potential to disrupt nighttime sleep. While we observed a delay of 25 min in sleep episodes during caffeine intake prior to the laboratory part, PSG-derived data after 9 days of regular caffeine intake did not yield a significant change in sleep architecture. Thus, our data provide first evidence that daily daytime caffeine intake does not necessarily alter subsequent sleep structure and SWA when consumed > 8 h prior to sleep. Importantly, our findings do not preclude potential impairments of nighttime sleep after morning caffeine intake, if preceded by several days of abstinence from the stimulant 21 . It rather appears likely that the duration of preceding caffeine consumption drives the discrepancies between acute and chronic effects of caffeine on sleep.

Chronic caffeine intake induces some tolerance development in both physiological measures such as cortisol 22 , blood pressure 23 , heart rate 24 , and also subjective measures such as alertness 18 . Over time, the stimulatory effects of the substance vanish potentially due to changes in adenosine levels 25 and/or adenosine receptors 26 , 27 , 28 . Accordingly, a 1-week treatment of caffeine reduced the sleep disrupting effects, even under conditions of high evening dosages 12 . Thus, the available evidence and the absence of clear-cut changes in the present study point to adaptive processes in sleep initiation, sleep structure, and subjective sleep quality due to the long-term exposure to the stimulant.

However, chronic caffeine consumption bears the risk of withdrawal symptoms when abruptly ceased. These symptoms have been reported to occur as early as 6 h but with peak intensity being reached within 20–51 h after last caffeine intake 17 . While 25 h of caffeine abstinence might not affect nighttime sleep structure 12 , 32 h of abstinence improved subjective sleep quality 18 . Thus, scheduling the start of the sleep episode to 15 h after the last caffeine intake, as in our withdrawal condition, was probably too early to detect changes in sleep structure or subjective sleep quality. In line with this assumption, volunteers subjectively indicated withdrawal symptoms 31 h after caffeine abstinence in the withdrawal condition compared to caffeine. Thus, our findings support the notion that the alterations in sleep structure and subjective sleep quality induced by caffeine abstinence potentially develop at a later stage (> 27 h) of caffeine withdrawal.

Most strikingly and unexpectedly, a reduction in NREM sigma activity during both the withdrawal and caffeine conditions was observed, a phenomenon which is commonly reported under conditions of enhanced sleep pressure 29 , 30 , 31 , 32 . Thus, it seems at first glance in contrast to the reported increases in this frequency range 10 , 21 and the well-known alerting effects after acute caffeine intake 18 . However, during conditions of chronic caffeine intake, mice showed a deeper sleep compared to placebo 33 . Moreover, repeated caffeine intake enhances the sensitivity of adenosine binding 34 presumably due to upregulated adenosine receptors 26 , 27 , 28 or changes in the functions of adenosine receptor heteromers 35 . These neuronal alterations in the adenosinergic system might drive the commonly observed changes in the homeostatic sleep-wake regulation such as increased sleepiness when caffeine intake is suddenly ceased 17 . As reported previously, we also observed in the present study higher subjective sleepiness following caffeine withdrawal when compared to the placebo and caffeine conditions 36 . Thus, the reduction in sigma activity might reflect adenosinergic changes which already emerge 8 and 15 h after the last caffeine intake in the caffeine and withdrawal condition, respectively. This reduction might reflect withdrawal symptoms which chronic consumers reverse daily by the first caffeine dose. Given the high prevalence of daily caffeine consumers in the society, these findings stress the importance to carefully control for prior caffeine intake when assessing sleep in order to exclude potential confounding by induced withdrawal symptoms which are only detectable in the microstructure of sleep.

Our study has some limitations which must be taken into careful consideration when interpreting the present findings. First, age moderates the effects of caffeine on sleep 11 , 14 . Thus, the present results cannot be generalized to other age groups such as to middle-aged consumers which are more vulnerable to the caffeine-induced effects on sleep 11 , 14 . Second, only a limited number of participants were studied. However, a well-controlled study design was employed and power calculation on the basis of an earlier study 12 indicated a sufficient sample size. Third, we do not have any information about the participants’ genetic polymorphisms which have been shown to modulate the metabolism of caffeine 37 . In addition, a genetic variation of the ADORA2A genotype has been linked with caffeine sensitivity to the effects on sleep 38 . Thus, carriers of this genetic variance are more likely to curtail caffeine consumption and are consequently excluded from the present study leading to a selection bias. However, the focus of the present study was to investigate habitual caffeine consumers as they represent the majority of the worldwide population 2 . Fourth, to reduce variance in the data incurred by the influence of the menstrual cycle on sleep 39 and the interaction between caffeine metabolism and the use of oral contraceptives 40 , 41 , only male volunteers were included which clearly reduces the generalizability of the findings.

In conclusion, we report evidence that daily daytime intake of caffeine and its cessation has no strong effect on sleep structure or subjective sleep quality. However, the quantitative EEG analyses revealed reduced activity in the sigma range during both caffeine and withdrawal. These subtle alterations point to early signs of caffeine withdrawal in the homeostatic aspect of sleep-wake regulation which are already present as early as 8 h after the last caffeine intake. Thus, habitual caffeine consumers constantly expose themselves to a continuous change between presence and absence of the stimulant. Around the clock, their organisms dynamically adapt and react to daily presence and nightly abstinence.

Participants

Twenty male volunteers were recruited into the present study through online advertisements and flyers distributed in public areas. Interested individuals aged between 18 and 35 years old (mean age ± SD: 26.4 ± 4 years) and reporting a daily caffeine consumption between 300 and 600 mg (mean intake ± SD: 478.1 ± 102.8 mg) were included. The self-rating assessment for the daily amount of caffeine intake was structured based on Bühler et al. 42 , and the amount of caffeine content was defined according to Snel and Lorist 3 . To ensure good health, volunteers were screened by self-report questionnaires and a medical examination conducted by a physician. Additionally, all volunteers reported good sleep quality assessed with the Pittsburgh Sleep Quality Index (PSQI; score ≤ 5) 43 and showed no signs of sleep disturbances (SE > 70%, periodic leg movements < 15/h, apnea index < 10) in a PSG recorded during an adaptation night in the laboratory scheduled prior to the start of the study. To control for circadian misalignment, volunteers who reported shiftwork within 3 months and transmeridian travels (crossing > 2 time zones) within 1 month prior to study admission were excluded. Further exclusion criteria comprised body mass index (BMI) < 18 or > 26, smoking, drug use, and extreme chronotype assessed by the Morningness-Eveningness Questionnaire (MEQ; score ≤ 30 and ≥ 70) 44 . To reduce variance in the data incurred by the effect of menstrual cycle on sleep 39 and the interaction between caffeine metabolism and the use of oral contraceptives 40 , 41 , only male volunteers were studied. A detailed description of the study sample can be found in Weibel et al. 36 .

All volunteers signed a written informed consent and received financial compensation for study participation. The study was approved by the local Ethics Committee (EKNZ) and conducted according to the Declaration of Helsinki.

Design and protocol

We employed a double-blind, randomized, crossover study including a caffeine, a withdrawal, and a placebo condition. Volunteers were allocated to the order of the three conditions based on pseudo-randomization, for more details see Weibel et al. 36 . As illustrated in Fig.  4 , each condition started with an ambulatory part of 9 days, followed by a laboratory part of 43 h. In each condition, participants took either caffeine (150 mg) or placebo (mannitol) in identical appearing gelatin capsules (Hänseler AG, Herisau, Switzerland) three times daily, scheduled at 45 min, 255 min, and 475 min after awakening, for a duration of 10 days. This regimen was applied based on a previous study investigating tolerance to the effects of caffeine and caffeine cessation 18 . To enhance caffeine withdrawal in the withdrawal condition, treatment was abruptly switched from caffeine to placebo on day nine of the protocol (255 min after wake-up, 15 h before sleep recording).

Illustration of the study design. Twenty volunteers participated in a placebo, a caffeine, and a withdrawal condition during which they ingested either caffeine or placebo capsules three times daily (wake-up + 45 min, + 255 min, and + 475 min). Each condition started with an ambulatory part of 9 days and was followed by a laboratory part of 43 h. After 9 days of continuous treatment, we recorded 8 h of polysomnography (PSG), indicated as arrows, during nighttime sleep under controlled laboratory conditions. The sleep episode was scheduled to volunteers’ habitual bedtime.

During the 9 days of the ambulatory part, volunteers were asked to maintain a regular sleep-wake rhythm (± 30 min of self-selected bedtime/wake-up time, 8 h in bed, no daytime napping), verified by wrist actimetry (Actiwatch, Cambridge Neurotechnology Ltd., Cambridge, United Kingdom), and to keep subjective sleep logs. While the participants were compliant, they scheduled sleep episodes differently within the accepted range of ± 30 min. During intake of caffeine (i.e. caffeine and withdrawal condition), the ambulatory sleep episodes were on average around 25 min later as compared to placebo (results see supplements). The duration of the ambulatory part was set for 9 days based on the maximum duration of withdrawal symptoms 17 and thus, to avoid carry-over effects from the previous condition. Furthermore, volunteers were requested to refrain from caffeinated beverages and food (e.g. coffee, tea, soda drinks, and chocolate), alcohol, nicotine, and medications. Caffeine abstinence and compliance to the treatment requirements were checked by caffeine levels from the daily collection of fingertip sweat of which results are reported in the supplemental material of Weibel et al. 36 and which indicate very good adherence to the treatments.

On day nine, volunteers admitted to the laboratory at 5.5 h prior to habitual sleep time. Upon arrival, a urinary drug screen (AccuBioTech Co., Ltd., Beijing, China) was performed to ensure drug abstinence. Electrodes for the PSG were fitted and salivary caffeine levels collected. An 8-h nighttime sleep episode was scheduled at volunteers’ habitual bedtime starting 8 and 15 h after the last caffeine intake in the caffeine and withdrawal condition, respectively. The next day, volunteers rated their subjective sleep quality by the LSEQ 45 and potential withdrawal symptoms by the Caffeine Withdrawal Symptom Questionnaire (CWSQ) 46 .

To reduce potential masking effects on our outcome variables, we standardized food intake, light exposure, and posture changes throughout the laboratory part. Accordingly, volunteers were housed in single apartments under dim-light (< 8 lx) during scheduled wakefulness and 0 lx during sleep. Volunteers were asked to maintain a semi-recumbent position during wakefulness, except for restroom breaks. In addition, volunteers received standardized meals in regular intervals. Social interactions were restricted to team members and no time-of-day cues were provided throughout the in-lab protocol.

Salivary caffeine

To characterize individual caffeine levels during nighttime sleep, we report salivary caffeine levels assessed 3 h prior to the scheduled sleep episode and 5 min after wake-up. Samples were stored at 5 °C following collection, later centrifuged (3000 rpm for 10 min) and subsequently kept at − 28 °C until analyses. Liquid chromatography coupled to tandem mass spectrometry was used to analyze the levels of caffeine. One dataset in the withdrawal condition was lost.

Subjective sleep quality

Subjective sleep quality was assessed 10 min upon scheduled wake-up time with a paper and pencil version of the LSEQ 45 . Volunteers were asked to rate 10 items on visual analogue scales which are grouped into four domains (getting to sleep (GTS), quality of sleep (QOS), awake following sleep (AFS), and behavior following wakening (BFW)).

Polysomnographic recordings

PSG was continuously recorded during 8 h of nighttime sleep using the portable V-Amp device (Brain Products GmbH, Gilching, Germany). Grass gold cup electrodes were applied according to the international 10–20 system including two electrooculographic, two electromyographic, two electrocardiographic, and six electroencephalographic derivations (F3, F4, C3, C4, O1, O2). Channels were referenced online against the linked mastoids (A1, A2). Signals were recorded with a sampling rate of 500 Hz and a notch filter was online applied at 50 Hz.

Each epoch of 30 s of the recorded PSG data was visually scored according to standard criteria 47 by three trained team members blind to the condition. SWS was additionally classified into stage 3 and 4 based on Rechtschaffen and Kales 48 . The scoring agreement between the three scorers was regularly confirmed to reach > 85%.

TST was defined as the sum of the time spent in sleep stages 1–4 and rapid eye movement (REM) sleep. Sleep latency to stage 1 and 2 was calculated as minutes to the first occurrence of the corresponding sleep stage following lights off. REM sleep latency was calculated as minutes to the first occurrence of REM sleep following sleep onset. NREM sleep was calculated as sum of sleep stages 2, 3 and 4. All sleep stages are expressed as relative values (%) of TST.

Spectral analysis was performed by applying fast Fourier transformation (FFT; hamming, 0% overlapped, 0.25 Hz bins) on 4-s time windows. Artifacts were manually removed based on visual inspection, and data were log-transformed prior to spectral analyses. All-night EEG power density during NREM sleep was analyzed for each 0.25 Hz frequency bin in the range of 0.75–32 Hz recorded over the central derivations (C3, C4). SWA was defined as EEG power density between 0.75–4.5 Hz and sigma activity between 12–16 Hz. Sleep cycles were defined based on adapted rules developed by Feinberg and Floyd 49 and divided into 10 NREM and four REM sleep intervals within each cycle. Ten nights were excluded from sleep analyses due to technical problems (placebo: n  = 3; caffeine: n  = 4; withdrawal: n  = 3).

Caffeine withdrawal symptoms

Withdrawal symptoms were first assessed 35 min after wake-up and subsequently prior to each treatment administration with the self-rating CWSQ 46 . Twenty-three items are grouped into seven factors (fatigue/drowsiness, low alertness/difficulty concentrating, mood disturbances, low sociability/motivation to work, nausea/upset stomach, flu-like feelings, headache) and were rated on a 5 point scale by choosing between 1 (not at all) and 5 (extremely). Prior to analyses, eight items have been reversed scored as they were positively worded (e.g. alert or talkative) in the questionnaire. To assess caffeine withdrawal, we first calculated a sum score comprising all 23 items of the caffeine withdrawal questionnaire. Missing responses to single items were replaced by the median response of each condition over all volunteers in the respective time of assessment. In a next step, we calculated relative withdrawal symptoms in the caffeine and withdrawal condition (i.e. the difference of the withdrawal score in the caffeine and withdrawal condition respectively minus the score of the placebo condition). The data of one volunteer was lost due to technical difficulties.

Statistical analyses

Analyses were performed with the statistical package SAS (version 9.4, SAS Institute, Cary, NC, USA) by applying mixed model analyses of variance for repeated measures (PROC MIXED) with the repeated factors ‘condition’ (placebo, caffeine, withdrawal) and/or ‘time’ (levels differ per variable) and the random factor ‘subject’. The LSMEANS statement was used to calculate contrasts and degrees of freedom were based on the approximation by Kenward and Roger 50 . Post-hoc comparisons were adjusted for multiple comparisons by applying the Tukey-Kramer method. A statistical significance was defined as p  < 0.05. One dataset has been excluded from all the analyses due to non-compliance with the treatment requirements (caffeine: n  = 1).

Data availability

The present data are available upon request from the corresponding author.

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Acknowledgements

The present work was performed within the framework of a project granted by the Swiss National Science Foundation (320030_163058) and was additionally funded by the Nikolaus und Bertha Burckhardt-Bürgin-Stiftung and the Janggen-Pöhn-Stiftung. Further, we thank our interns Andrea Schumacher, Laura Tincknell, Sven Leach, and all our study helpers for their help in data acquisition and all our volunteers for participating in the study. Moreover, we gratefully acknowledge the help in study organization provided by Dr. Ruta Lasauskaite and the medical screenings conducted by Dr. med. Martin Meyer and Dr. med. Corrado Garbazza.

Author information

These authors contributed equally: Christian Cajochen and Carolin F. Reichert.

Authors and Affiliations

Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland

Janine Weibel, Yu-Shiuan Lin, Joshua Kistler, Christian Cajochen & Carolin F. Reichert

Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland

Neuropsychiatry and Brain Imaging, Psychiatric Hospital of the University of Basel, Basel, Switzerland

Yu-Shiuan Lin & Stefan Borgwardt

Institute of Pharmacology and Toxicology, University of Zürich, Zürich, Switzerland

Hans-Peter Landolt

Sleep & Health Zürich, University Center of Competence, University of Zürich, Zürich, Switzerland

Laboratory Medicine, University Hospital Basel, Basel, Switzerland

Sophia Rehm & Katharina M. Rentsch

Clinical Sleep Laboratory, Psychiatric Hospital of the University of Basel, Basel, Switzerland

Helen Slawik

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Contributions

C.R., C.C. and S.B. designed the study; J.W., Y.S.L. and HS collected the data; J.W., C.R. and C.C. analyzed and interpreted the data; J.W. and C.R. drafted the manuscript; C.C., Y.S.L. and H.P.L. critically revised the manuscript regarding its intellectual content; J.K., S.R. and K.R. provided the resources for the caffeine measurements and performed its analyses; all authors reviewed the present article.

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Correspondence to Christian Cajochen .

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Weibel, J., Lin, YS., Landolt, HP. et al. The impact of daily caffeine intake on nighttime sleep in young adult men. Sci Rep 11 , 4668 (2021). https://doi.org/10.1038/s41598-021-84088-x

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65 Caffeine Essay Topic Ideas & Examples

🏆 best caffeine topic ideas & essay examples, ⭐ good research topics about caffeine, 👍 simple & easy caffeine essay titles.

• Negative Effects of Caffeine and Energy Drinks It leads to avoidance of making choices and biasness and may result in impaired self-regulation that may affect the social problems of the users.
• The Caffeine Effect on Students’ Test Performance Thus, the critical interest in this experiment is to determine the relationship between coffee consumption before exams and students’ own performance on those exams. We will write a custom essay specifically for you by our professional experts 808 writers online Learn More
• Starbucks and Caffeine: Is It Unhealthy? It is the caffeine in coffee which makes it addictive, so addictive in fact that it’s the most addictive substance known to mankind.
• Restrictions, Warning Labels, or Other Controls on Caffeine Use The risks of caffeine intoxication are underrated, and only a few products include warnings, which increases the probability of exposing the consumer to unknown effects of the commodity.
• Cardiovascular Disease and Caffeine Effects There have been conflicting ideas about the effects of caffeine on the body especially in relation to the development of cardiovascular diseases. The increased prevalence of cardiovascular diseases is mainly due to the changes in […]
• The Impact of Caffeine on Athletic Performance Caffeine is a legal substance, so it may be used to enhance athletic performance within the bounds of the law. The amount of anhydrous caffeine given to study participants is an independent variable.
• Critique: “Spilling the Beans: How Much Caffeine Is Too Much?” The third was the most specific and supported paragraph about the specifics of the European country’s culture and habits regarding coffee.
• Caffeine: Health Benefits and Risks The topic I want to address today is on health effects of caffeine. It is mostly found in seeds of the Coffea plant, and the safe dose is determined to be 400 mg/day.
• Aspirin, Acetaminophen, Ibuprofen, Naproxen, Caffeine: Analgesics Analysis The reduced synthesis of prostaglandins prevents the brain from receiving information of pain and inflammation while the reduced synthesis of thromboxanes hinders the formation of blood clots.
• The Effect of Caffeine on Pulse and Respiration Rates The bodily effect of caffeine, known by its chemical name of 1,3,7-trimethylxanthine, is thought to be related to the production of energy in the form of adenosine triphosphate. The aim of this experiment is to […]
• Decaffeinated Coffee Is Not Caffeine-Free This is what triggered the research fronted by the Professor to determine the degree of caffeine in decaffeinated coffee brands, in the market.
• The Effect of Caffeine on the Blood Glucose Level The goal of the investigation was to explore the effect of caffeine on the blood glucose level. The only difference between the two groups was the administration of plain water to one group and the […]
• Consumption of Caffeine Is Associated With Reduced Risk of Parkinson’s Disease The risk of the disease was found to reduce more progressively with the increase in the level of coffee consumption. Some observers argue that the level of reduction in cases of PD amongst coffee drinkers […]
• Caffeine Addiction and Negative Effects The thesis of this paper is that scientists need to reclassify caffeine as a potentially addictive stimulant drug. In addition to the potential to cause addictive behavior, caffeine can have an adverse effect on the […]
• Physical Performance Among Athletes: The Impact of Caffeine Consequently, the proposed research topic is the investigation of caffeine’s effect on physical and cognitive performance among athletes who are not used to the continuous intake of this element.
• Caffeine: Absorption, Distribution, Metabolism Immediately after the consumption of caffeine, the paraxanthine and caffeine concentration increases in the body within 8 to 9 hours and it leaves minute traces of toxicology into the blood. The sudden cessation in the […]
• Caffeine Addiction as a Mental Disorder And it is a rather pragmatic question stipulated by the professionals need to debate about, but not by the addiction nature itself.
• Effects of Caffeine on Open Field Behavior of the Rat It was studies the psychological function of behavior of rats and the influence of caffeine on it through 8-9 weeks from the beginning of application of caffeine.
• Caffeine Consumption in Personal Experience It is possible to note that, in the case of tolerance, the situation is somewhat similar to the consumption in general.
• Caffeine: Does Acute Consumption Affect Aerobic Performance? The research regarding the connection between caffeine consumption and one’s response to exercising is replete with studies failing to find any significant effects of the stimulant on people’s vitals.
• Caffeine and Its Positive Impacts on Mental Activity The increased level of these neurotransmitters results in increased neuron activity in the body. That being the case, the affected individuals will be forced to consume high doses of coffee in order to increase the […]
• Prenatal Caffeine Exposure’ Effects To prove the hypothesis, the authors conduct the experimental study that delves into the investigation of the major concerns of the issue.
• Caffeine: Carriers, Addiction and Diseases When caffeine is taken in, the body absorbs and then gets rid of it fast. But, generally, it creates no threat to the physical and social aspects of health, like the addictive drugs do, though […]
• Why College Students Should Not Turn to Caffeine The paper will look at some of the trend of involvement of college students into caffeine consumption and the risks that surround consumption of caffeine by college students.
• Caffeine and Its Effects on Brain: Long-Term Physiological Changes
• The Confusion and Inconsistencies About the Effects of Caffeine
• Caffeine and Bicarbonate for Speed: A Meta-Analysis of Supplements Potential for Improving Intense Endurance Exercise Performance
• Insomnia: Sleep and Caffeine Related Components
• Caffeine and Global Spatial Processing in Habitual and Non-habitual Caffeine Consumers
• Cognition and Brain Activation in Response to Various Doses of Caffeine: A Near-Infrared Spectroscopy Study
• Caffeine, Stress, and Proneness to Psychosis-Like Experiences
• The Alarming Aspects and Effects of Caffeine
• Caffeine and Energy Drinks: High Levels of Stress
• Alcohol, Caffeine, and Nicotine: The Most Widely Consumed Psychotropic Drugs Worldwide
• Caffeine Enhances Memory Performance in Young Adults During Their Non-optimal Time of Day
• Combination Ergotamine and Caffeine Improve Seated Blood Pressure and Presyncope Symptoms in Autonomic Failure
• Caffeine and Its Effects on the Human Body and Society
• Prenatal Nutrition: The Effects of Caffeine and Green Tea
• Caffeine Consumption and the Number of Sleep Needed
• Natural Product Extraction: Isolation of Caffeine From Tea, Thin Layer Chromatography
• Caffeine: The Health Benefits of Drinking Coffee, or Anything With Caffeine in It
• Caffeine Controls Glutamatergic Synaptic Transmission and Pyramidal Neuron Excitability in Human Neocortex
• Blood and Caffeine: Behavioral and Side Effects of Caffeine
• Caffeine Citrate for Apnea of Prematurity: A Prospective, Open-Label, Single-Arm Study Neonates
• Caffeine Consumption During Pregnancy Accelerates the Development of Cognitive Deficits in Offspring
• Association Between Plasma Caffeine and Other Methylxanthines and Metabolic Parameters in a Psychiatric Population Treated With Psychotropic Drugs Inducing Metabolic Disturbances
• Caffeine and Modulate of Food Intake Depending on the Context That Gives Access to Food: Comparison With Dopamine Depletion
• Improved Exercise Tolerance With Caffeine and Modulation of Both Peripheral and Central Neural Processes in Human
• Chlorpheniramine and the Analgesic Effect in Migraine of Usual Caffeine, Acetaminophen, and Acetylsalicylic Acid Combination
• Caffeine and Responsiveness With Different Individuals
• Energy Drinks and the Neurophysiological Impact of Caffeine
• Coffee With High Caffeine Content Augments Fluid and Electrolyte Excretion at Rest
• Caffeine and Parkinson’s Disease: Multiple Benefits and Emerging Mechanisms
• Individual Differences Affecting Caffeine Intake
• Caffeine Addiction and Chronic Fatigue Recovery
• Caffeine and Selective Adenosine Receptor Antagonists as New Therapeutic Tools for the Motivational Symptoms of Depression
• Legal Drugs: Caffeine’s Effects
• Caffeine Consumption and General Health in Secondary School Children: A Cross-Sectional and Longitudinal Analysis
• Reason for Using Caffeine in Dermocosmetics: Sunscreen Adjuvant
• Caffeine and Primary Headaches: Friend or Foe
• Caffeine and Sleep Deprivation: Pros and Cons for Tired Individuals
• Pre-exercise Caffeine Intake Enhances Bench Press Strength Training Adaptations
• Caffeine: The World’s Drug of Choice
• Coffee, Tea, and Caffeine Intake and the Risk of Severe Depression
• Caffeine and Exercise Performance: Possible Directions for Definitive Findings
• Chicago (A-D)
• Chicago (N-B)

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IvyPanda . "65 Caffeine Essay Topic Ideas & Examples." March 2, 2024. https://ivypanda.com/essays/topic/caffeine-essay-topics/.

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Making Caffeine Work For You

Written by lauren smyth.

Let’s face it: Caffeine is a drug. So is Tylenol. So are cough drops. So, in fact, are many of the everyday things we use to overcome life’s inconveniences.

Just like your average pharmaceutical, caffeine has its ideal dosage, its side effects, and its limitations. You wouldn’t triple your usual dose of Aspirin just because you didn’t sleep well last night and woke up with a dehydration headache. And if you did, you’d expect bad results. This is the same way we should approach caffeine, especially as college students who need to maximize this productivity powerhouse’s benefit—and yet, most of us slurp down enough coffee to revitalize an army, and we don’t even realize we’re overdoing it.

I’m no pharmacist, but I am a college student, which makes me an expert consumer of the world’s favorite molecule. Here are some tips for getting the most out of your daily cup of joe.

1. Caffeine can help you wake up. Caffeine stimulates the production of cortisol, a chemical the body releases in response to danger that improves awareness and alertness. This, in turn, can give you a morning boost–if you need it.

“Some may welcome the additional alertness while others may feel more anxious/jittery,” said Ashley Palmer, Hillsdale College’s resident dietician. “I would recommend if individuals do choose to drink coffee first thing in the morning, to hydrate first and consume caffeine with food.”

2. Don’t drink too late. Caffeine has a long half-life. It takes your body anywhere between 2 and 10 hours to metabolize. Thus, it’s best not to drink caffeine—especially coffee—in the afternoon.

3. Don’t drink too much. On average, an 8 oz cup of coffee or 1.5 shots of espresso contains about 100 mg of caffeine. It’s considered safe to consume up to 400 mg per day—but just because you can doesn’t mean you should. If you’ve ever gotten the caffeine jitters, it’s because you drank too much. When consumed at a reasonable speed and in reasonable amounts, caffeine should give you a gentle, gradual energy boost, not make you feel like you’re about to launch into space.

4. Drink water with your coffee. Caffeine is a diuretic. In English, that means it makes you pee. It’s not particularly dehydrating, according to recent research, but if your only source of fluid throughout the day is coffee, espresso, and energy drinks, you might find yourself running to the bathroom faster than you can replace your body’s water supply. This can lead you to over-consume those caffeinated drinks.

5. Don’t drink coffee on an empty stomach. Because your body absorbs caffeine faster without food, this can lead to jitters, anxiety, rapid heart rate, and other unpleasant side effects of a caffeine overdose. 

6. Make sure caffeine is really what you need. If you’re desperate for a boost in the late afternoon, Palmer recommends heading to the fridge instead of the coffee pot.

“I usually recommend eating every 3-4 hours,” Palmer said, “so if students are feeling tired later in the afternoon, they should ask themselves when was the last time they ate.”

7. Boost your performance at the gym. Caffeine may improve strength, endurance, and alertness for gym-goers of all levels. The best benefits are unlocked by sipping a solo cup of coffee about 45 minutes before your workout. Note: Exercise temporarily reduces your digestive ability, which can lead to stomach upset if you overdo it. So, as always, consume in moderation.

8. Skip the energy drinks. For most people, energy drinks are simply too much caffeine mixed with too little fluid, then consumed too quickly. This can contribute to caffeine tolerance, in which you must increase your intake before you feel any beneficial effects.

9. Watch out for “decaf.” It’s still caffeinated—just a tiny bit, which I’ve discovered through bitter experience can become noticeable if you either drink a lot of it or if you’re one of the unlucky few who metabolizes caffeine slowly. And it can still keep you awake at night.

When consumed in moderation, caffeine is a reasonable option to help tired students compensate for a night or two of poor sleep, recover their energy early in the morning, and stay alert during class. The key is to avoid using it like a crutch.

Savor the taste, savor the effects, and savor the opportunity to hunker down in a cozy coffee shop—but make sure your caffeine is working for you.

Published in April 2024

（很全面）SpringBoot 使用 Caffeine 本地缓存

作者：超级小豆丁 http://www. mydlq.club/article/56/

二、缓存组件 Caffeine 介绍

• Caffeine 性能
• Caffeine 配置说明

三、SpringBoot 集成 Caffeine 两种方式

四、springboot 集成 caffeine 方式一.

• Maven 引入相关依赖
• 定义服务接口类和实现类
• 测试的 Controller 类

五、SpringBoot 集成 Caffeine 方式二

• Caffeine 版本：2.8.0
• SpringBoot 版本：2.2.2.RELEASE

https://www. jianshu.com/p/c72fb0c78 7fc https://www. cnblogs.com/rickiyang/p /11074158.html 博文示例项目 Github 地址： https:// github.com/my-dlq/blog- example/tree/master/springboot/springboot-caffeine-cache-example

缓存在日常开发中启动至关重要的作用，由于是存储在内存中，数据的读取速度是非常快的，能大量减少对数据库的访问，减少数据库的压力。

之前介绍过 Redis 这种 NoSql 作为缓存组件，它能够很好的作为分布式缓存组件提供多个服务间的缓存，但是 Redis 这种还是需要网络开销，增加时耗。本地缓存是直接从本地内存中读取，没有网络开销，例如秒杀系统或者数据量小的缓存等，比远程缓存更合适。

按 Caffeine Github 文档描述，Caffeine 是基于 JAVA 8 的高性能缓存库。并且在 spring5 (springboot 2.x) 后，spring 官方放弃了 Guava，而使用了性能更优秀的 Caffeine 作为默认缓存组件。

1、Caffeine 性能

可以通过下图观测到，在下面缓存组件中 Caffeine 性能是其中最好的。

2、Caffeine 配置说明

• weakValues 和 softValues 不可以同时使用。
• maximumSize 和 maximumWeight 不可以同时使用。
• expireAfterWrite 和 expireAfterAccess 同事存在时，以 expireAfterWrite 为准。

软引用：如果一个对象只具有软引用，则内存空间足够，垃圾回收器就不会回收它；如果内存空间不足了，就会回收这些对象的内存。

弱引用：弱引用的对象拥有更短暂的生命周期。在垃圾回收器线程扫描它所管辖的内存区域的过程中，一旦发现了只具有弱引用的对象，不管当前内存空间足够与否，都会回收它的内存

SpringBoot 有俩种使用 Caffeine 作为缓存的方式：

• 方式一：直接引入 Caffeine 依赖，然后使用 Caffeine 方法实现缓存。
• 方式二：引入 Caffeine 和 Spring Cache 依赖，使用 SpringCache 注解方法实现缓存。

下面将介绍下，这俩中集成方式都是如何实现的。

1、Maven 引入相关依赖

3、定义测试的实体对象, 4、定义服务接口类和实现类.

UserInfoService

UserInfoServiceImpl

5、测试的 Controller 类

Diet Coke or Coke Zero? Dietitian reveals which one is healthier

Let’s get fizz-ical.

A Toronto-based registered dietitian has evaluated the healthfulness of the no-calorie diet sodas Coke Zero and Diet Coke — and the results are soda-pressing for Coke fans.

“Both contain aspartame, caffeine, natural flavors, and caramel colors, etc.,” Abbey Sharp began her peppy pop post Sunday on TikTok.

“The key difference is that Diet Coke is sweetened exclusively with aspartame , whereas Coke Zero also contains a sweetener called acesulfame potassium or Ace-K,” Sharp continued. “While the wellness community will call both of these sweeteners complete poison, the reality is, they’re both FDA-approved and have been deemed safe in moderation.”

Aspartame, sold under the brand names Nutrasweet, Equal, and Sugar Twin, is about 200 times sweeter than sugar. Last year, the World Health Organization’s cancer research arm classified aspartame as “possibly carcinogenic to humans,” calling for further research on potential health risks.

But the Food and Drug Administration said it disagrees with that label , noting that it “does not mean that aspartame is actually linked to cancer.”

The FDA says the acceptable daily intake for aspartame is up to 50 milligrams per kilogram of body weight each day.

Ace-K, also known as Sunett and Sweet One, is also about 200 times sweeter than table sugar.

The FDA regulates Ace-K as a food additive, emphasizing that it has reviewed more than 90 studies of possible toxic effects of the substance.

A 2022 French study linked aspartame to an increased risk of stroke and Ace-K to a higher risk of coronary artery disease.

Said Sharp: “I’m generally not concerned about either of these sweeteners, though I prefer not to take the risk specifically in pregnancy with Ace-K because it has been shown to cross the placenta .”

Another major difference between Diet Coke and Coke Zero, Sharp points out, is caffeine content.

A 12-ounce can of Diet Coke has about 46 milligrams, while Coke Zero has 34 milligrams.

In drawing her conclusion, Sharp said discipline is key.

“Honestly, diet sodas are not health foods. They should be treated no differently than regular, full-sugar soda,” she reasoned. “They don’t really add anything to the diet except for maybe some pleasure and a little energy kick. Diet, zero, regular, whatever, if you’re gonna drink soda, choose the one you like the most and enjoy in moderation.”

For her part, Nashville-based registered dietitian  Jenny Beth Kroplin cautioned to Parade last month that artificial sweeteners may cause the body to crave sweets.

“Aspartame and acesulfame potassium don’t raise blood glucose levels,” Kroplin explained. “However, the sweetness of artificial sweeteners may trigger the cephalic phase in the release of insulin and cause an increase in insulin levels in the body over time.”

Commenters on Sharp’s 95-second video, which drew more than 18,000 views in mere hours, shared their Coke preferences.

“Coke zero tastes better. Diet coke has a weird aftertaste,” one TikToker argued.

“Diet Coke is just superior especially with a lime,” another insisted.

“I don’t care for the taste for either one. Though cherry coke 0 wasn’t terrible,” a third admitted.

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Mountain Dew, Orange Crush, and 9 Other Sodas You Should Avoid at All Costs

With their fizzy mouthfeel and refreshing taste, sodas can be extremely satisfying (and seemingly thirst-quenching). But the reality is that most of these beverages are laden with sugar and caffeine, and provide little nutritional value or hydration. While most sodas deliver a quick rush of energy due to their high sugar content, this is usually followed by a dreaded crash that leaves you feeling sluggish and out of sorts.

The caffeine in many of these popular drinks can also trigger an increased heart rate and anxiety, which can disrupt your sleep pattern and leave you feeling exhausted. Plus, the empty calories in sugary sodas can contribute to weight gain and lead to more serious health issues like obesity, heart disease, and type 2 diabetes, according to the Harvard T. H. Chan School of Public Health .

Here are 11 sodas you might want to avoid due to their high sugar and caffeine content.

1. Mountain Dew

Known for its vibrant green hue and crisp taste, Mountain Dew contains a high caffeine content of about 55 milligrams per 12 ounce Its sugar content is also staggering at around 46 grams per serving (about 11 teaspoons of sugar!). This combination makes it one of the most stimulating sodas on the market, which can be appealing to those looking for a quick energy boost.

But don't be fooled — the Dew's high-calorie content and lack of essential nutrients make it a poor choice for hydration or health. According to one Redditor whose daughter-in-law works as a dentist, she sees "more patients with Mountain Dew mouth than meth mouth." Do yourself a favor and do not google "meth mouth."

2. Orange Crush

Offering a refreshing burst of orange (despite not containing any actual orange), this soda comes with 44 grams of sugar per 12 ounce serving, and no caffeine. The high sugar content can lead to rapid spikes in blood sugar levels, making it a less than ideal choice for those managing diabetes or looking to maintain stable energy levels throughout the day. Orange Crush also lacks any nutritional value, and offers zero vitamins or minerals that are beneficial for health.

Instead of pouring all that sugar into your body, consider giving our dirty sodas a try. This way you can control what goes into it and customize flavors to your liking.  Related:   15 Meaningless Nutritional Claims by Some of Your Favorite Foods

3. Coca-Cola

Arguably the most iconic soda, Coca-Cola contains 39 grams of sugar and about 34 milligrams of caffeine per 12 ounces (46 milligrams for Diet Coke). The drink's classic flavor comes from a mix of high fructose corn syrup and caffeine, which provide an instant pleasure hit but also contribute to long-term health issues like obesity and tooth decay. Drinking soda regularly can potentially lead to caffeine dependency and withdrawal symptoms, a study finds.

Let's just put is this way — anything that can  remove rust from cast-iron cookware  probably isn't great for your digestive system.

If you thought you'd simply switch to Pepsi, we hate to rain on your parade, but it's worse. Very similar to Coca-Cola in its makeup, Pepsi packs slightly more sugar at 41 grams per 12 ounces , and about 38 milligrams of caffeine . While some say it offers a slightly sweeter and sharper taste compared to its main competitor, it still shares the same health implications due to its high sugar and caffeine levels.

Related:   Pepsi Pushes 'Pilk:' A Pepsi Cola and Milk 'Dirty Soda'

5. Dr Pepper

Boasting a unique blend of 23 flavors , Dr Pepper (not a real doctor) offers 40 grams of sugar and around 41 milligrams of caffeine per 12 ounces While its distinct taste is a favorite among soda lovers, it poses similar health risks — including an increased risk of dental problems and weight gain. Its high caffeine content can also lead to insomnia and stomach irritability in sensitive individuals.

Dr Pepper also has a pretty high sodium content (55 milligrams), which can contribute to increased blood pressure and cardiovascular strain if consumed in excess.

For more consumer news and other savvy life hacks, please sign up for our free newsletters.

6. Fanta Pineapple

This one sucks because Fanta Pineapple is so delicious. Bursting with tropical flavor, this soda just hits different on a scorching summer day. But sadly, it contains about 48 grams of sugar per 12 ounces (at least it has no caffeine, though). While it might seem like a fun, fruity option, its high sugar content can significantly impact blood sugar levels and contribute to tooth decay.

Despite its appealing flavor, Fanta Pineapple offers no nutritional benefits, lacks any vitamins, minerals, or fiber, and is a less-than-ideal choice for those seeking healthy beverage options.

Related:   11 Absurdly Easy Recipes That Start With a Can of Soda

7. Barq's Root Beer

Known for its caramel flavor with a hint of vanilla, Barq's contains 44 grams of sugar per 12-ounce serving, and about 22 milligrams of caffeine. Though its caffeine content is lower than some other brands, the high sugar level still poses health risks and won't help with proper hydration. Its sodium content of 65 milligrams is also quite high for a soda.

8. Crush Strawberry

Offering a bold fruity flavor that is both sweet and refreshing, Crush Strawberry is a definite fan favorite. "It’s like drinking a can of candy," says one user . But each 12-ounce serving of Crush Strawberry contains about 43 grams of sugar , putting it on the higher end of soft drinks. Like other Crush varieties, it is also caffeine-free.

But its high sugar content can lead to blood sugar spikes and subsequent energy crashes, which are not ideal for overall health management. It also does not provide any nutritional benefits in the way of essential vitamins, minerals, or fiber.

9. Sunkist Orange

Another orange-flavored soda, Sunkist packs a whopping 52 grams of sugar per 12 ounces (that's more than other sodas), and contains about 40 milligrams of caffeine . Its high sugar and caffeine content make it one of the more problematic sodas — especially for individuals trying to manage energy levels and maintain a healthy diet.

Sunkist's other flavors, including peach and fruit punch, are also not much better in terms of sugar. It's peach-flavored soda boasts about 46 grams of sugar per 12 ounce serving, while the fruit punch one packs 48 grams.

10. Mug Cream Soda

A popular choice for those who prefer a creamy, smooth vanilla flavor in their soda, Mug's is certainly a favorite for many pop lovers. Known for its rich, frothy head when poured, it's reminiscent of a classic cream soda. "Cream soda, so good," writes one Redditor — we have to agree. But sadly, it also contains 47 grams of sugar per 12-ounce serving, which is on par with many other sweetened soft drinks.

Though it does not contain caffeine, it also doesn't offer any real nutritional benefits and should be consumed in moderation due to its high sugar content.

This beloved lemon-lime soda is caffeine-free but contains 38 grams of sugar per 12 ounce serving. Its refreshing taste can be appealing, especially on a hot day, but like other sodas on this list, it does not offer much nutritional value, and could contribute to health problems if consumed in excess. Its cousin, Sprite, also boasts the same amount of sugar per can.

Contrary to most sodas on this list, though, 7-UP contains 60 milligrams of potassium per serving. Potassium is an essential mineral that can help lower blood pressure and reduce fluid retention. Though considering most health authorities recommend a daily intake of 3,500 to 4,700 milligrams of potassium, you're probably better off looking to sources that are higher in potassium such as fruits, vegetables, and fish, rather than chugging cans of 7-Up.

This article was originally published on Cheapism

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Caffeine Intake and Mental Health in College Students

Raphael a. o bertasi.

1 Department of Family Medicine, Mayo Clinic, Jacksonville, USA

Yasmine Humeda

2 Department of Family Medicine, Florida State University College of Medicine, Tallahassee, USA

Tais G. O Bertasi

Justin kimsey, george pujalte.

The effect of caffeine on the human body, both short-term and long-term, has been studied in great depth, particularly its association with psychiatric disorders. This study aims to investigate whether there is a correlation between caffeine intake and anxiety and depression among college students.

Methodology

A survey was administered to college students at Florida State University. Data regarding participant characteristics and caffeine intake were collected. Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 scores were used to assess symptoms of anxiety and depression, respectively.

A total of 114 participants were included in the survey, consisting mainly of women (94 [82.5%]) and junior-level students (37 [32.5%]). The main source of caffeine was coffee (64.0%), and the main reasons for caffeine intake were pleasure (43.9%) and to study outside of class (29.8%); however, no association was found between sex or grade point average and number of cups of caffeine consumed. Upper levels of education (super senior or fifth-year students), depressive symptoms (poor appetite, overeating, sleep disorders, depressed mood), and anxiety were statistically associated with greater caffeine intake ( P < 0.05).

Conclusions

As caffeine is commonly consumed and our study showed that its intake was associated with depressive symptoms and higher levels of anxiety in college students, further studies are needed to determine a possible causality, so that measures may be taken to educate these students about alternative methods for increasing energy and alertness.

Introduction

Due to its availability, caffeine is widely used as a source of energy. Coffee, pills, soda, and energy drinks are some of the most popular sources of caffeine. Some of the benefits that have been attributed to moderate caffeine intake include increased attention, alertness, mood elevation, increased cognitive function and fewer cognitive failures, lower risk of suicide, and fewer depressive symptoms [ 1 ]. Thus, caffeine use is extremely prevalent among college students. The college lifestyle, however, appears to lend itself to higher caffeine intake compared to the rest of the population [ 2 ]. College students use very high doses of caffeine, an average of over 800 mg/day, which is approximately double the recommended safe dosage [ 3 ].

The short-term and long-term effects of caffeine on the human body have been studied. Research to date has primarily focused on caffeine’s exacerbation of anxiety, sleep disorders, and depression in patients diagnosed with psychiatric symptoms [ 4 - 6 ]. Caffeine consumption has been associated with an increase in anxiety in adults with generalized anxiety disorder [ 7 ]. However, those who consume caffeine also tend to experience greater positive effects on behavior, including alertness and arousal [ 5 ].

This study examines whether there is a correlation between caffeine intake and anxiety and depression in college students (both with and without a previous diagnosis of either mental health condition).

Materials and methods

An online survey using Qualtrics XM (Qualtrics, Seattle, WA, USA) was randomly distributed to college students at Florida State University via email, Twitter, and Facebook in 2016. Participants were eligible if they were college students enrolled at Florida State University and could answer a questionnaire via email. Students who for any reason were not able to answer questions on an emailed questionnaire were excluded. We collected demographic characteristics (e.g., sex and year in school), grade point average (GPA), previous diagnosis of depression or anxiety, and caffeine intake-related information (e.g., source, frequency, and reason). For this study, one cup was defined as eight ounces of liquid. The Generalized Anxiety Disorder-7 (GAD-7) [ 8 ] and Patient Health Questionnaire-9 (PHQ-9) [ 9 ] were included in the survey to assess anxiety and depressive diagnoses, respectively. The sensitivity and specificity of GAD-7 and PHQ-9 diagnosis, using a cut point of 10, are 89% and 88% and 82% and 88%, respectively [ 8 , 9 ]. Therefore, a diagnosis of anxiety and depression were considered when the participant reached a score greater than or equal to 10 on GAD-7 and PHQ-9, respectively. However, when the score was <10, we considered the greater the total score on each questionnaire the higher the level of each disorder.

Questions were in the English language with multiple-choice answers and were filled by the participants. The questions applied in the survey are provided in the Appendix. Data were anonymously extracted to an Excel spreadsheet (Microsoft, Inc., Redmond, WA, USA).

Each question had four possible responses: zero = “not at all,” one = “several days,” two = “over half the days,” and three = “nearly every day.” The total scale score classified the level of anxiety and depression, with higher scores representing a greater severity of either disorder.

Each questionnaire answer was evaluated individually and as part of the total score of the complete anxiety and depression assessment. Statistical analysis was performed with SPSS, version 21 (IBM Corp., Armonk, NY, USA). As the data were not normally distributed, the Kruskal-Wallis test was used to compare numeric and categorical data, and in case of statistically significant results, the Mann-Whitney test was performed. The Pearson product-moment correlation coefficient (r) assessed a correlation between the two numeric datasets. P values less than 0.05 were considered statistically significant.

This study was approved by the Mayo Clinic Institutional Review Board (#16-005552). Online informed consent was obtained from all participants before collecting any data.

The survey was answered by 114 participants, including 94 women (82.5%) and 20 men (17.5%). Most of the students were in their junior year of college (37 [32.5%]) and had a GPA between 3.5 and 4.0 (75 [65.8%]). Their main source of caffeine was coffee (73 [64.0%]), and their main reasons for caffeine intake were pleasure or enjoyment (50 [43.9%]) and to study outside of class (34 [29.8%]). Table ​ Table1 1 presents all demographic and caffeine-related characteristics of the participants.

Students’ year at school and their caffeine source were associated with the number of cups of caffeine they consumed per week (P = 0.02 and P < 0.001, respectively). Super senior students consumed more caffeine than freshmen, sophomores, and juniors (P = 0.02, P = 0.02, and P = 0.05, respectively), while juniors consumed more coffee than freshmen (P = 0.03). Moreover, coffee and soda were used as caffeine sources more often than tea (P < 0.001 and P = 0.01, respectively). There was no association between sex or GPA and the number of cups of caffeine consumed.

Regardless of previous diagnoses of anxiety or depression, one item from the GAD-7 and three from the PHQ-9 were significantly associated with caffeine consumption (P < 0.03). The items listed were “poor appetite or overeating” (PHQ-9), “trouble falling or staying asleep or sleeping too much” (PHQ-9), “feeling down, depressed, or hopeless” (PHQ-9), and “becoming easily annoyed or irritable” (GAD-7). Students who experienced any of the above problems “nearly every day” had more caffeine intake per week than those who answered “not at all” or “several days” (P < 0.05; Figure ​ Figure1 1 ).

Box plot comparing amount of caffeine intake per week and frequency of symptoms identified in the Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 questionnaires with P < 0.05 in the Kruskal-Wallis test (P values for the Mann-Whitney test assessing each answer are also in the graph). One cup equals eight ounces of liquid.

Moreover, there was a positive correlation between the GAD-7 anxiety score and the number of cups of caffeine consumed per week (r = 0.24, P = 0.01), but not with the depression score on the PHQ-9 (r = 0.01, P = 0.88; Figure ​ Figure2 2 ).

GAD-7 = Generalized Anxiety Disorder-7

One cup equals eight ounces of liquid

Correlation: r = 0.240, P = 0.01.

For participants without a previous diagnosis of anxiety and depression, only the question regarding “poor appetite or overeating” had a significant difference: those who answered “nearly every day” or “over half of days” had more caffeine intake per week than those who answered “not at all” or “several days” (P < 0.05). A slightly positive, but not statistically significant association, was found between caffeine intake and scores greater than or equal to 10 in GAD-7 and PHQ-9 (P = 0.09 and P = 0.29, respectively).

The results of this study suggest a correlation between high caffeine intake and symptoms of anxiety and depression in college students. Caffeine is the most commonly consumed central nervous system stimulant worldwide [ 10 ], with coffee being the most preferred source [ 11 ]. Tea, soda, chocolate, and energy drinks are also commonly used by people of all ages, with some containing even higher amounts of caffeine [ 12 ]. The main motivations for caffeine consumption include enhanced physical performance, greater energy, personal enjoyment, improved concentration, reduced stress, and fulfilling social purposes [ 13 , 14 ].

Mahoney et al. [ 15 ] showed that, among 1,145 college students, the main motivation for caffeine consumption was increased wakefulness, followed by taste. Meanwhile, Micoulaud-Franchi et al. [ 16 ] found that enhancement of academic performance and improvement of wakefulness among college students were the main reasons for caffeine consumption. These studies are partially in line with our own, which reported enjoyment and optimized studying as the primary motivations.

The motives for caffeine consumption, and the association found between upper levels of education (i.e., super senior) and greater caffeine intake, suggest that students might believe caffeine may help improve academic performance. Interestingly, educational achievement was shown to have a negative association with caffeine intake [ 2 ]. This finding was not contradicted by our study, which showed no positive association between caffeine intake and GPA. The sought-after effect of caffeine on enhanced academic performance deserves further investigation.

Behavior and mood symptoms linked to psychiatric disorders have also been associated with caffeine consumption. Caffeine inhibits adenosine receptors in the central nervous system, mainly in the hippocampus, amygdala, and prefrontal cortex (locations with high concentrations of these receptors that are associated with emotion, cognition, and motivation), which might play a role in the association between depression and caffeine consumption [ 17 - 19 ].

Several studies have reported an inverse association between depression and caffeine intake, which suggests that caffeine consumption may work as a protective factor for depression [ 19 - 22 ]. However, it is important to note that these studies included only older participants, with mean ages greater than 40. A systematic review of 15 articles assessing people of all ages found that a high consumption of coffee decreases the risk of depression [ 23 ]. However, if only children and adolescent studies from the systematic review are considered, this association ceases to exist. Studies that assessed children and adolescents showed only a positive association between depression and caffeine intake [ 24 - 26 ]. Iranpour and Sabour [ 19 ] showed that an increment of 1 mg of caffeine per day had a different effect on depressive symptoms in each age range; however, further studies should be conducted to clarify such age-related effects of caffeine intake.

There is still no clear evidence to support the idea that caffeine causes depression. Either people prone to depression self-medicate with more caffeine to improve their energy and concentration, or caffeine properties interact in the brain, leading to depressive symptoms [ 27 ]. We hypothesize that the age of consumption may have an important effect on this association. In our study of college students, we found that symptoms of depression such as poor appetite or overeating, sleep disturbances, and feelings of hopelessness were positively associated with caffeine consumption (Figure ​ (Figure1 1 ).

Similarly, caffeine may affect anxiety-like behaviors by inhibiting adenosine receptors, particularly the A2A receptor [ 28 ]. Higher levels of caffeine intake have been linked to higher anxiety levels when consuming at least one cup of coffee per day [ 17 , 24 , 29 ]. Indeed, in our study, participants with higher levels of caffeine intake had higher GAD-7 scores (Figure ​ (Figure2). 2 ). It is worth noting that there are some genetic variations in adenosine receptors that lead to different anxiety behaviors in light caffeine users [ 30 ]. Therefore, levels of caffeine sensitivity may vary in this population and should be addressed in further studies.

Our study has some limitations, such as its design and small sample size. Although interesting, our findings are speculative. They should not be extrapolated and must be analyzed with caution. However, our results do contribute to the understanding of the effects of caffeine on psychiatric disorders, especially in young adults/adolescents, as there are scant data in this age range. Additional studies should be performed on the physical and psychological repercussions of caffeine on people of different ages, especially youth.

As our study showed an association between caffeine intake and depressive symptoms, caffeine cannot be deemed a protective factor for depression as it is in adults older than 40. Additionally, greater consumption of caffeine by college students was associated with higher levels of anxiety, as measured by the GAD-7 scores. As caffeine is commonly consumed and our study showed that its intake was associated with depressive symptoms and higher levels of anxiety in college students, further studies are needed to determine a possible causality, so that measures might be taken to educate these students about alternative methods for increasing energy and alertness.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

Human Ethics

Consent was obtained or waived by all participants in this study. Mayo Clinic Institutional Review Board issued approval 16-005552

Animal Ethics

Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.