Next Article in Journal
Advancements in Digital Workflows for 3D-Printed Maxillofacial Soft Prostheses: Exploring Design and Materials in Direct Additive Manufacturing: A Scoping Review
Next Article in Special Issue
Morphological Analysis of US Treated PANC-1 Spheroids
Previous Article in Journal
Purification of Produced Water by Solvents to Enhance Oil Recovery and Reuse Separated Droplets
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Varying Caffeine Dosages and Consumption Timings on Cerebral Vascular and Cognitive Functions: A Diagnostic Ultrasound Study

1
Department of Radiological Science, College of Medical Science, Gachon University, Incheon 21936, Republic of Korea
2
Department of Health Science, Gachon University Graduate School, Incheon 21936, Republic of Korea
3
Neuroscience Research Institute, Gachon University, Incheon 21565, Republic of Korea
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Appl. Sci. 2025, 15(4), 1703; https://doi.org/10.3390/app15041703
Submission received: 30 November 2024 / Revised: 4 February 2025 / Accepted: 5 February 2025 / Published: 7 February 2025
(This article belongs to the Special Issue Applications of Ultrasonic Technology in Biomedical Sciences)

Abstract

:
Caffeine is consumed owing to its stimulatory effects; however, its excessive intake triggers adverse effects. Herein, we analyzed changes in physiological cerebrovascular and cognitive functions following the consumption of 100 and 200 mg of caffeine in healthy adults after 0/30/60 min to ascertain appropriate caffeine consumption habits. The peak systolic velocity (PSV), pulse wave velocity (PWV), and common carotid artery (CCA) diameter were measured using diagnostic ultrasound. Cognitive function was evaluated using the accuracy rate and response time on the two-back task. Percutaneous oxygen saturation (SpO2) and heart rate (HR) were assessed using patient monitoring systems. After consuming 100 mg of caffeine, systolic blood pressure (SBP) increased (p > 0.05) and SpO2 and accuracy rate improved by 30 min (p = 0.018 and p = 0.356) but declined by 60 min (p = 0.924 and p = 0.055). HR and response time continuously decreased (p = 0.209 and p = 0.061, respectively), while PWV showed no change (p > 0.05). After consuming 200 mg of caffeine, SBP (p < 0.05), diastolic blood pressure (p = 0.004 and p = 0.820), and SpO2 (p = 0.002 and p = 0.666) increased significantly, while the accuracy rate (p = 0.634 and p = 0.055, respectively) and response time (p < 0.05) decreased. PWV remained unchanged (p > 0.05). The results revealed distinct dose-dependent patterns on physiological and cognitive changes, with SBP and SpO2 exhibiting greater changes when a higher dose was consumed in a short duration. Although moderate caffeine intake may support vascular health and cognitive function, excessive intake reduces blood flow, alters vascular elasticity, and impairs cognitive activation. These findings highlight the need for guidelines to ensure safe and effective caffeine consumption.

1. Introduction

Caffeine is consumed worldwide in various forms such as coffee, chocolate, beverages, and pharmaceuticals [1]. The caffeine content varies by form, with approximately 17 mg/oz in coffee, 0.8 mg/oz in cocoa and hot chocolate, and 30–100 mg in medications [2]. Most caffeine intake occurs through coffee, which is consumed at various times throughout the day, such as after waking up or during meals [1,3]. Globally, since 2002, the coffee consumption per capita has increased by 37% over the last 20 years [4], resulting in a paralleled increase in caffeine intake. Currently, the U.S. FDA recommends a maximum daily caffeine intake of 400 mg for healthy adults. Similarly, Health Canada recommends maximum daily doses of 45–85 mg/day for children aged <12, 2.5 mg/kg/day for adolescents aged >12 years, 400 mg/day for adults, and 300 mg/day for pregnant women [5]. The European Food Safety Authority (EFSA) recommends daily caffeine intake limits of 0.2–2.0 mg/kg body weight (bw)/day for children (3–10 years), 0.4–1.4 mg/kg bw/day for adolescents (10–18 years), 400 mg/day for adults, and 200 mg/day for pregnant women. The Ministry of Food and Drug Safety of South Korea recommends maximum daily intakes of 2.5 mg/kg bw/day for children and adolescents, 400 mg/day for adults, and 300 mg/day for pregnant women [6,7]. Despite these guidelines, public awareness remains low, resulting in excessive caffeine consumption without consideration of the recommended limits. The primary driver of this consumption is the stimulatory effect of caffeine.
Caffeine exerts its stimulatory effects through multiple mechanisms. Its structural similarity to adenosine allows it to act as an antagonist, with stimulatory effects being a key outcome [8]. Adenosine typically binds to the A1 and A2A receptors in the brain, thereby reducing the release of glutamate and dopamine and inducing drowsiness and sleepiness [9]. However, caffeine binds to these receptors non-selectively, blocking adenosine-mediated signaling and enhancing neurotransmitter release. This results in reduced drowsiness, improved brain function, and sympathetic nervous system activation, which increases catecholamine release and alertness [8,10,11]. Additionally, caffeine induces vasoconstriction, elevates blood pressure (BP) [8,12,13], increases renal blood flow, and inhibits ion and fluid reabsorption, leading to diuretic effects [8]. After exerting these effects, caffeine is metabolized by the liver and excreted by the kidneys through the urine [14,15]. Its half-life in the body averages 3–5 h and varies according to physiological and environmental factors [8,16,17].
The positive effects of caffeine extend beyond its stimulatory effects. It activates lipase, promotes fat breakdown [14,15,18], enhances muscle strength by affecting muscle contraction [8,15,19], and aids in digestion by stimulating gastrin release and gastric acid secretion in the stomach and duodenum [20,21]. However, excessive caffeine intake can cause dehydration due to excessive diuresis, gastritis, or ulcers due to the overproduction of gastric acid [8,21], in addition to psychological side effects such as anxiety, tension, and insomnia [22]. High accessibility to caffeine also affects adolescent consumption, potentially causing electrolyte imbalances that impair growth and development, with potentially adverse effects on mental health during critical periods of physical and emotional change [23,24]. In pregnant women, excessive caffeine intake may result in caffeine crossing the placental barrier owing to its lipid solubility, potentially causing miscarriages or other complications [25].
The effects of caffeine, both in terms of dosage and duration, are well documented. While small doses of caffeine may improve cognitive function and vascular health, excessive amounts can lead to reduced blood flow, an increased heart rate (HR), and impaired cognitive performance [18,19,20]. Previous studies have reported cardiovascular responses, such as increased BP and HRs within 30–60 min after caffeine consumption, as well as improvements in cerebral oxygen saturation and working memory [21,22]. However, most studies have focused on specific doses (>300 mg) and have not systematically analyzed dose-dependent differences or combined vascular and cognitive changes over time.
To address the above knowledge gaps, the present study aimed to analyze the physiological and cognitive responses to varying doses of caffeine intake in a short duration using diagnostic ultrasonography and cognitive function task.

2. Materials and Methods

2.1. Participants

This study was approved by the Institutional Review Board (IRB No. 1044396-202404-HR-067-01). The participants in this study were recruited through bulletin boards of recruiting target institutions or public announcements posted on social networks, and 30 participants (male: 15; female: 15) voluntarily participated (Table 1). Prior to the experiment, participants were informed about this study’s purpose, procedures, and equipment safety. All participants provided their written informed consent to participate in this study.
The criteria for inclusion were healthy adults over the age of 20 without any disease, and the exclusion criteria are those who have a history of diseases possibly affecting cardiovascular function, take cardiovascular drugs, are physically weak or mentally ill, and are students affiliated with the same department as the researchers.

2.2. Experimental Protocols and Data Acquisition

The participants completed two experimental sessions held at the same time, one week apart. To minimize external factors influencing the results, the participants refrained from smoking and eating for 6 h before each session, avoided caffeine consumption for 12 h, and abstained from alcohol consumption for 24 h. The 12 h caffeine restriction was set according to its half-life: approximately 3–5 h.
During the measurements, all participants were seated on a fixed chair in the same position, with the back of their heads touching the wall. Velcro tape and a polyester band were placed around their foreheads to secure their heads in place and prevent any movement away from the wall.
A diagnostic ultrasound system (E-CUBE i7, ALPINION MEDICAL SYSTEMS Co., Ltd., Seoul, Republic of Korea) and a linear transducer array (L3-12T, ALPINION MEDICAL SYSTEMS Co., Ltd., Seoul, Republic of Korea) were used to locate and mark the right CCA for consistent measurements. The ultrasound measurements were performed by a radiologic technologist with experience in multiple ultrasound-related studies. BP was monitored using a smartwatch (SM-R850; Samsung Electronics, Suwon, Republic of Korea) worn on the left wrist and calibrated individually according to the manufacturer’s instructions. The HR and peripheral oxygen saturation (SpO2) were measured using a patient monitor (Bionics, Chuncheon, Republic of Korea), with sensors attached to the left index finger.
To assess cognitive performance, the participants practiced the N-back test once before the experiment to familiarize themselves with the task. The two-back (2B) test was then conducted using the DMDX software (DMDX version 6, University of Arizona Psychology Department, Tucson, AZ, USA). In this test, numbers ranging from 0 to 9 appeared randomly on the screen 40 times at 3 s intervals. Participants were required to indicate whether the current number matched the one presented two trials earlier by selecting “positive” or “negative.”
Subjective measures were evaluated using the visual analog scale (VAS) for comfort, Karolinska Sleepiness Scale (KSS) for drowsiness, and the Chalder Fatigue Scale (CFS) for fatigue. The VAS ranges from the most comfortable state (0) to the most uncomfortable state (10), whereas the KSS ranges from highest alertness (1) to greatest sleepiness (9) [26,27]. The CFS uses a 14-item Likert scale (eight items for physical fatigue and six for mental fatigue), with responses scored as better than usual (0), same as usual (1), worse than usual (2), and much worse than usual (3), yielding a total score of 0–42, with higher scores indicating greater fatigue [28].
Physiological and biosignal measurements were taken at three time points: before caffeine ingestion (0 min), 30 min after ingestion (30 min), and 60 min after ingestion (60 min), based on caffeine’s approximate absorption time of 45 min in the bloodstream [29]. Brightness mode (B-mode) and Doppler-mode ultrasound images of the right CCA were recorded for 5 s, capturing eight cardiac cycles (Figure 1). Blood pressure (BP) was measured concurrently using a smartwatch.
Participants consumed caffeine immediately following the 0 min measurement period. Caffeine doses were prepared using stick coffee (Kanu Mini Mild-Roasted Coffee Sticks; Dongsuh Foods Corporation, Incheon, Republic of Korea), containing 33 mg of caffeine per stick. For each trial, three (approximately 100 mg) or six sticks (approximately 200 mg) were dissolved in 200 mL of water. In the first experiment, the participants were randomly assigned to consume either 100 mg or 200 mg of caffeine, and the alternate dose was consumed in the second experiment. Therefore, a single-blind method was used, in which the participants were unaware of the intake amount.
Ultrasound images of the CCA were saved in DICOM format and analyzed using DICOM viewer software (Radiant DICOM Viewer Version 2021.2.2 (64-bit), Medixant, Poznan, Poland). The maximum diameter (MaxD) and minimum diameter (MinD) were measured from the B-mode images, while the average peak systolic velocity (PSV) over 5 s was calculated from the Doppler-mode images. HR and SpO2 values were averaged over 30 s of measurement, and systolic blood pressure (SBP) and diastolic blood pressure (DBP) were recorded using the smartwatch application.
The pulse wave velocity (PWV), a measure of arterial stiffness, was calculated using SBP, DBP, MaxD, and MinD according to Equations (1) and (2). Cognitive performance data, including accuracy rate and response time from the 2B test, were extracted using the DMDX software.
Stiffness   Index   ( S I ) = l n S B P D B P × M i n D D
where DD = MaxD − MinD
Pulse   Wave   Velocity   ( P W V ) = S I × D B P 2 × B D
where blood density (BD) = 1.050 g/cm3
The raw data for BP, diameter, PWV, PSV, HR, SpO2, accuracy rate, and response time were normalized using Equation (3) to calculate the change rates for statistical analysis.
C h a n g e   R a t e   ( C R ) = V a l u e   a t   0 , 30 , o r   60   m i n V a l u e   a t   0   m i n

2.3. Statistical Analysis

Statistical analyses were conducted using Jamovi software (version 2.2.5, free software, https://www.jamovi.org, accessed on 15 October 2024). Time-dependent changes (0, 30, and 60 min) were analyzed using repeated-measures analysis of variance (RM ANOVA). Sphericity was tested, and Greenhouse–Geisser corrections were applied where necessary. Tukey’s post hoc test was performed for significant effects (p < 0.05). Changes in caffeine dose (100 mg vs. 200 mg) were analyzed using paired t-tests. For subjective measures, the means and standard deviations were calculated to observe trends according to caffein doses and consumption times. Statistical significance was set at p = 0.05.

3. Results

All measurements were expressed as relative change rates, with the baseline at 0 min set to 1. Overall, SBP showed no significant differences at 30 (1.003 ± 0.037) or 60 min (1.009 ± 0.030) following the intake of 100 mg of caffeine (p > 0.05). However, following a 200 mg intake, SBP significantly increased at 30 (1.014 ± 0.029) and 60 min (1.029 ± 0.044) (p < 0.05) (Table 2).
DBP showed no significant differences at 30 (1.002 ± 0.048) or 60 min (0.997 ± 0.046) following 100 mg of caffeine intake (p > 0.05), whereas for the 200 mg intake, significant increases were observed from 0 to 30 min and 0 to 60 min (p = 0.004 and p = 0.006, respectively); however, no significant differences were noted between 30 and 60 min (p = 0.820) (Table 2 and Figure 2).
Significant differences were observed between 0 and 30 min (p = 0.016), but no significant differences were observed between 0 and 60 or 30 and 60 min (p = 0.504 and p = 0.138, respectively) following 100 mg of caffeine intake. For the 200 mg intake, no significant differences were observed at 30 min (1.001 ± 0.028) or 60 min (0.999 ± 0.030) (p > 0.05) (Table 3).
MinD showed significant differences from 0 to 30 min and 0 to 60 min (p = 0.031 and p = 0.048, respectively), but no significant differences were found between 30 and 60 min (p = 0.610) after 100 mg of caffeine intake. For the 200 mg intake, no significant differences were observed from 30 min (0.999 ± 0.036) and 60 min (0.996 ± 0.030) (p > 0.05) (Table 3 and Figure 3).
The PWV showed no significant differences at 30 (1.005 ± 0.136) or 60 min (1.053 ± 0.112) following 100 mg of caffeine intake (p > 0.05). For the 200 mg intake, no significant differences were observed at 30 (1.014 ± 0.162) or 60 min (1.001 ± 0.128) (p > 0.05) (Table 4 and Figure 4).
The PSV showed significant differences between 0 and 30 min (p < 0.001); however, no significant differences were observed between 0 and 60 min and 30 and 60 min (p = 0.056 and p = 0.407, respectively) following 100 mg of caffeine intake. For the 200 mg intake, no significant differences were observed from 30 min (0.960 ± 0.069) or 60 min (0.961 ± 0.099) (p > 0.05) (Table 5 and Figure 5).
HR showed significant differences between 0 and 60 min (p = 0.005) but no significant differences between 0 and 30 min and 30 and 60 min (p = 0.209 and p = 0.061, respectively) after 100 mg of caffeine intake. For the 200 mg intake group, significant differences were only observed from 0 to 60 min (p = 0.022), with insignificant changes observed between 0 and 30 and 30 and 60 min (p = 0.080, p = 0.235, respectively) (Table 5 and Figure 6).
SpO2 showed significant differences between 0 and 30 min and 0 and 60 min (p = 0.018 and p = 0.049, respectively) but no significant differences between 30 and 60 min (p = 0.924) after 100 mg of caffeine intake. For the 200 mg intake, significant differences were observed from 0 to 30 min and 0 to 60 min (p = 0.002 and p = 0.001, respectively) but not between 30 and 60 min (p = 0.666) (Table 5 and Figure 7).
The accuracy rate significantly differed between 30 and 60 min (p = 0.009); however, no significant differences were observed between 0 and 30 min and 0 and 60 min (p = 0.356 and p = 0.613, respectively) following 100 mg of caffeine intake. For the 200 mg intake, significant differences were observed between 0 and 60 min (p = 0.020) but not observed from 0 to 30 and 30 to 60 min (p = 0.634 and p = 0.055, respectively) (Table 6 and Figure 8).
The response time showed significant differences over time following both the 100 mg and 200 mg caffeine intake, with reductions observed between 30 min (0.963 ± 0.042, 0.976 ± 0.034) and 60 min (0.934 ± 0.046, 0.938 ± 0.047) (p < 0.05) (Table 6 and Figure 9).
Caffeine dosage significantly affected SBP at 60 min (p = 0.016) but not at 30 min (p = 0.145) (Table 7). Similarly, DBP significantly differed at 60 min (p = 0.031) but not at 30 min (p = 0.059) (Table 7). Furthermore, MaxD and MinD exhibited significant differences at 30 min (p = 0.019 and p = 0.029, respectively) but not at 60 min (p = 0.052) (Table 7). PWV, PSV, and HR showed no significant dose-dependent effects over time (p > 0.05), whereas the SpO2 differences were significant at 60 min (p < 0.05) but not at 30 min (p = 0.338) (Table 7). The accuracy rate and response time were not significantly affected (p > 0.05) (Table 7).
At a caffeine intake of 100 mg, the VAS score was 3.13 ± 2.19 at 0 min, 3.07 ± 2.03 at 30 min, and 2.80 ± 2.04 at 60 min. This value decreased by 0.06 at 30 min compared to that at 0 min and by 0.27 at 60 min compared to that at 30 min. For a caffeine intake of 200 mg, the VAS was 2.87 ± 2.16 at 0 min, 2.83 ± 2.09 at 30 min, and 2.57 ± 2.05 at 60 min. This value decreased by 0.03 at 30 min compared to that at 0 min and by 0.26 at 60 min compared to that at 30 min.
For a caffeine intake of 100 mg, the KSS was 4.87 ± 1.59 at 0 min, 4.00 ± 1.46 at 30 min, and 4.13 ± 1.41 at 60 min. This value decreased by 0.46 at 30 min compared to 0 min and by 0.28 at 60 min compared to 30 min. When the caffeine intake was 200 mg, the KSS was 5.00 ± 1.55 at 0 min, 3.87 ± 1.22 at 30 min, and 3.87 ± 1.28 at 60 min. The 200 mg intake decreased by 1.13 at 30 min compared to that at 0 min and showed no further decrease from 30 min to 60 min (0.00 change).
For a caffeine intake of 100 mg, the CFS was 16.30 ± 5.53 at 0 min, 14.40 ± 5.62 at 30 min, and 16.00 ± 5.64 at 60 min. This value decreased by 1.90 at 30 min compared to that at 0 min and increased by 2.10 at 60 min compared to that at 30 min. For a caffeine intake of 200 mg, the CFS was 14.80 ± 5.58 at 0 min, 13.20 ± 5.64 at 30 min, and 12.80 ± 5.31 at 60 min. This value decreased by 1.60 at 30 min compared to that at 0 min and decreased further by 0.40 at 60 min compared to that at 30 min (Table 8).
In short, the VAS scores decreased slightly at 60 min compared to those at 0 min for both doses, although this difference was insignificant. The KSS decreased at 30 min and showed minor increases at 60 min, indicating reduced sleepiness following caffeine intake. The CFS scores showed a transient reduction at 30 min with a slight rebound at 60 min for 100 mg and continued reduction at 200 mg (Table 8).

4. Discussion

In this study, the effects of caffeine intake on BP, HR, SpO2, blood vessel diameter, and cognitive function were analyzed. The BP change was not significant when 100 mg was ingested in a short duration, but BP increased significantly after 200 mg of intake. HR tended to decrease at both doses, and SpO2 increased further when 200 mg was ingested. In the cognitive function evaluation, the accuracy improved until 30 min after 100 mg of intake but decreased thereafter, and the accuracy continuously decreased when 200 mg was ingested. On the other hand, the reaction time was shortened under all conditions, suggesting the possibility that caffeine may have a positive effect on rapid cognitive response.
SBP demonstrated a general upward trend over time across all levels of caffeine intake, with a significant increase observed only at 200 mg. This increase could be attributed to the stimulation of the sympathetic nervous system, leading to catecholamine release, which induces vasoconstriction and subsequent BP elevation [8,10,13,20]. The most pronounced increase occurred approximately 45 min post-intake, aligning with the peak absorption of caffeine [29,30]. DBP showed a modest increase for up to 30 min following 100 mg of intake, followed by a decrease at 60 min. Conversely, a 200 mg intake resulted in a gradual increase in DBP up to 60 min. These observations are consistent with the mechanisms underlying SBP changes, indicating that the limited increase in DBP after 30 min of consuming 200 mg of caffein may reflect a physiological threshold influenced by blood flow. The changes in SBP and DBP were more pronounced with 200 mg than with 100 mg, with significant differences observed only at 60 min, indicating that higher caffeine doses exert greater effects on BP.
The MaxD and MinD increased at 30 min compared to the baseline with a 100 mg intake but decreased by 60 min. Following an intake of 200 mg, MaxD slightly increased at 30 min and subsequently slightly decreased at 60 min, while MinD progressively declined. These findings suggest that high doses of caffeine have a strong effect on vasoconstriction. Changes in MaxD and MinDs were more pronounced at 100 mg than at 200 mg, with significant differences observed only at 30 min, indicating a shorter recovery period for vessel diameter compared to BP [9,13].
PWV remained relatively stable at 30 min for all doses. At 100 mg, it increased slightly at 60 min, likely due to the smooth muscle contraction triggered by elevated intracellular calcium levels, resulting in vascular stiffening and increased wave propagation speed [31,32]. In contrast, the PWV at 200 mg remained constant for up to 60 min. Neither time nor dosage resulted in significant differences in the PWV. Previous studies have reported either the maintenance of or an increase in PWV following acute caffeine intake [32,33]. Differences in measurement methods, such as foot-to-foot versus the one-point approach, may account for these discrepancies. The latter provides more localized measurements, thereby reducing variability.
Overall, PSV exhibited a decreasing trend 30 min after intake across all doses. Recovery was observed after 60 min for 100 mg, whereas a slight decrease was observed for 200 mg. Although the reduction observed at 30 min was more substantial at a 100 mg caffein dose, both doses showed similar levels at 60 min, without significant differences. This aligns with the effects of caffeine on the carotid and peripheral arteries, where vasoconstriction impedes smooth blood flow owing to reduced adenosine activity [8,34,35]. HR decreased significantly over time for all doses, with greater reductions at 200 mg than at 100 mg at 30 min. After 60 min, both of the doses resulted in similar reductions. This trend is likely a baroreflex response to elevated BP, aimed at reflexively lowering HR [36,37,38]. SpO2 increased across all doses up to 30 min, followed by a slight decline at 100 mg, and continued to increase at 200 mg up to 60 min. These results are consistent with previous findings indicating that a low dose of caffeine reduces tissue oxygen consumption, leading to increased SpO2 levels [39,40].
In cognitive function tests, comprising the 2_B test assessment, the accuracy rate increased at 30 min for 100 mg but returned to baseline by 60 min, whereas it showed a continuous decline until 60 min after a 200 mg dose. The transient improvement at 30 min with the lower dose reflected the peak absorption and immediate effects of caffeine [29,30]. However, the subsequent decline highlights the short-lived nature of the cognitive effects of caffeine. Increased sympathetic activity due to higher caffeine doses likely contributed to the reduced accuracy. The participants’ stationary posture during the experiment may have activated the default mode network, which is associated with reduced focus and concentration [41,42,43,44,45,46]. The response time consistently improved over time for all doses, indicating enhanced cognitive arousal with caffeine intake, regardless of the dose.
Subjective measures, such as the VAS, KSS, and CFS, demonstrated increased comfort and reduced sleepiness and fatigue at 30 and 60 min for both doses. VAS and KSS showed greater changes at 100 mg, whereas CFS showed greater changes at 200 mg. These findings indicate the arousal effects of caffeine, which are mediated by dopaminergic modulation in the prefrontal cortex, which enhances mood and relaxation [47,48,49]. The general expectation of the effects of caffeine may have influenced the subjective evaluations regardless of the actual dose [50].
Overall, our findings indicate that caffeine exerts both dose- and time-dependent effects on physiological and cognitive parameters. Moderate caffeine intake appears to be beneficial for maintaining vascular health and cognitive activation, while excessive intake may lead to adverse vascular changes and cognitive impairment.
The limitations of this study include that the participants of the experiment were limited to their 20 s, so it was not possible to compare the results according to age, and the effect of caffeine on the patients with any disease could not be confirmed. In addition, the change after 60 min could not be confirmed because the measurement was made within a limited time up to 60 min after caffeine intake. The number of study participants is still small. Therefore, in a future study, it is necessary to supplement these limitations and increase the number of samples to conduct studies on various age groups and patients with diseases and additional studies on changes after 60 min.
Unlike some previous studies that were conducted in the lying down position and/or with a single dose [32,51], this study was conducted in a sitting position and with two different doses. In addition, this study examined the vascular physiology of caffeine, cognitive function, and subjective changes in comparison to the previous study [51].

5. Conclusions

Caffeine, which induces physiological and cognitive changes, is widely consumed in various forms, such as in coffee, chocolate, and medications. This study quantitatively analyzed the effects of caffeine intake (100 mg and 200 mg) and elapsed time (0, 30, and 60 min) on vascular physiology, cognitive function, and other subjective measures. The results revealed no significant changes in blood pressure or cognitive function with a 100 mg dose. However, the 200 mg dose significantly increased systolic blood pressure and diastolic blood pressure and impaired cognitive accuracy. Subjective measurements indicated reduced sleepiness and fatigue across all doses, reflecting the arousal effects of caffeine. This study highlighted the importance of moderately consuming caffeine. Low-dose caffeine intake over a short period is relatively safe and supports vascular and cognitive health, whereas high-dose caffeine intake over a short period causes vascular constriction and cognitive decline.
The practical implications of this study are as follows. Consuming a moderate amount of caffeine can promote vascular health and cognitive function. In addition, individualized guidelines should account for varying physiological responses to caffeine. Lastly, strategic use of the positive effects of caffeine, coupled with measures to prevent excessive consumption, is crucial.
Future research should explore the effects of caffeine in diverse age groups, health conditions, and the long-term effects of caffeine consumption to establish comprehensive guidelines.

Author Contributions

M.-K.C., H.-S.A., D.-E.K., D.-S.L., C.-S.P. and C.-K.K. were involved in conceptualization, data curation, formal analysis, investigation, methodology, resources, software, validation, visualization, and writing the original draft. C.-S.P. and C.-K.K. were involved in project administration, writing, reviewing, and editing as corresponding authors. C.-K.K. was involved in supervision and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by grants from the National Research Foundation of Korea (NRF), funded by the Korean government (MSIT) (No. 2020R1A2C1004355; No. 2022R1F1A1062766).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Gachon university (1044396-202404-HR-067-01, approval on 21 June 2024).

Informed Consent Statement

Informed consent was obtained from all participants.

Data Availability Statement

The data will be made available to interested individuals upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Nieber, K. The impact of coffee on health. Planta Med. 2017, 83, 1256–1263. [Google Scholar] [CrossRef] [PubMed]
  2. Barone, J.J.; Roberts, H.R. Caffeine consumption. Food Chem. Toxicol. 1996, 34, 119–129. [Google Scholar] [CrossRef] [PubMed]
  3. Kang, Y.-J. Effects of caffeine on nerve conduction velocity. J. Converg. Inf. Technol. 2020, 10, 195–199. [Google Scholar] [CrossRef]
  4. Quadra, G.R.; Brovini, E.M.; Dos Santos, J.A.; Paranaíba, J.R. Caffeine consumption over time. In Handbook of Substance Misuse and Addictions; Patel, V.B., Preedy, V.R., Eds.; Springer International Publishing: Cham, Switzerland, 2022; pp. 1535–1552. ISBN 978-3-030-92391-4. [Google Scholar]
  5. Mitchell, D.C.; Knight, C.A.; Hockenberry, J.; Teplansky, R.; Hartman, T.J. Beverage caffeine intakes in the U.S. Food Chem. Toxicol. 2014, 63, 136–142. [Google Scholar] [CrossRef]
  6. EFSA Panel on Dietetic Products, Nutrition and Allergies. Scientific Opinion on the safety of caffeine. EFS2 2015, 13, 4102. [Google Scholar] [CrossRef]
  7. Lee, J.-S.; Park, H.-S.; Han, S.; Tana, G.; Chang, M.-J. Study on relationship between caffeine intake level and metabolic syndrome and related diseases in Korean adults: 2013~2016 Korea National Health and Nutrition Examination Survey. J. Nutr. Health 2019, 52, 227. [Google Scholar] [CrossRef]
  8. Reddy, V.S.; Shiva, S.; Manikantan, S.; Ramakrishna, S. Pharmacology of caffeine and its effects on the human body. Eur. J. Med. Chem. Rep. 2024, 10, 100138. [Google Scholar] [CrossRef]
  9. Layland, J.; Carrick, D.; Lee, M.; Oldroyd, K.; Berry, C. Adenosine: Physiology, pharmacology, and clinical applications. JACC Cardiovasc. Intv. 2014, 7, 581–591. [Google Scholar] [CrossRef]
  10. McLellan, T.M.; Caldwell, J.A.; Lieberman, H.R. A review of caffeine’s effects on cognitive, physical and occupational performance. Neurosci. Biobehav. Rev. 2016, 71, 294–312. [Google Scholar] [CrossRef]
  11. Davis, J.M.; Zhao, Z.; Stock, H.S.; Mehl, K.A.; Buggy, J.; Hand, G.A. Central nervous system effects of caffeine and adenosine on fatigue. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2003, 284, R399–R404. [Google Scholar] [CrossRef]
  12. Cappelletti, S.; Piacentino, D.; Sani, G.; Aromatario, M. Caffeine: Cognitive and physical performance enhancer or psychoactive drug? Curr. Neuropharmacol. 2015, 13, 71–88. [Google Scholar] [CrossRef] [PubMed]
  13. Echeverri, D.; Montes, F.R.; Cabrera, M.; Galán, A.; Prieto, A. Caffeine’s vascular mechanisms of action. Int. J. Vasc. Med. 2010, 2010, 834060. [Google Scholar] [CrossRef] [PubMed]
  14. Zulli, A.; Smith, R.M.; Kubatka, P.; Novak, J.; Uehara, Y.; Loftus, H.; Qaradakhi, T.; Pohanka, M.; Kobyliak, N.; Zagatina, A.; et al. Caffeine and cardiovascular diseases: Critical review of current research. Eur. J. Nutr. 2016, 55, 1331–1343. [Google Scholar] [CrossRef] [PubMed]
  15. Tavares, C.; Sakata, R.K. Caffeine in the treatment of pain. Rev. Bras. Anestesiol. 2012, 62, 387–401. [Google Scholar] [CrossRef] [PubMed]
  16. Turnbull, D.; Rodricks, J.V.; Mariano, G.F.; Chowdhury, F. Caffeine and cardiovascular health. Regul. Toxicol. Pharmacol. 2017, 89, 165–185. [Google Scholar] [CrossRef]
  17. Reich, N.; Mannino, M.; Kotler, S. Using caffeine as a chemical means to induce flow states. Neurosci. Biobehav. Rev. 2024, 159, 105577. [Google Scholar] [CrossRef]
  18. Da Silva, L.A.; Pereira, R.A.; Túrmina, J.A.; Kerppers, I.I.; Osiecki, R.; Altimari, L.R.; Malfatti, C.R.M. Sulfonylurea induction of caffeine-enhanced insulin secretion and reduction of glycemic levels in diabetic rats. Pharm. Biol. 2014, 52, 956–960. [Google Scholar] [CrossRef]
  19. Bakker, R.; Steegers, E.A.P.; Obradov, A.; Raat, H.; Hofman, A.; Jaddoe, V.W.V. Maternal caffeine intake from coffee and tea, fetal growth, and the risks of adverse birth outcomes: The generation R Study. Am. J. Clin. Nutr. 2010, 91, 1691–1698. [Google Scholar] [CrossRef]
  20. Ruxton, C.H.S. The impact of caffeine on mood, cognitive function, performance and hydration: A review of benefits and risks. Nutr. Bull. 2008, 33, 15–25. [Google Scholar] [CrossRef]
  21. Nehlig, A. Effects of coffee on the gastro-intestinal tract: A narrative review and literature update. Nutrients 2022, 14, 399. [Google Scholar] [CrossRef]
  22. Delleli, S.; Ouergui, I.; Messaoudi, H.; Trabelsi, K.; Ammar, A.; Glenn, J.M.; Chtourou, H. Acute effects of caffeine supplementation on physical performance, physiological responses, perceived exertion, and technical-tactical skills in combat sports: A systematic review and meta-analysis. Nutrients 2022, 14, 2996. [Google Scholar] [CrossRef] [PubMed]
  23. Chang, Y.-E.; Chung, H.-K. Survey of caffeine intake from children’s favorite foods. Korean J. Nutr. 2010, 43, 475. [Google Scholar] [CrossRef]
  24. Kim, N.; Shin, W.; Kim, Y. Study on relevance of high-caffeine drink intake frequency to mental health of adolescents. Korean J. Food Culture 2017, 32, 66–74. [Google Scholar] [CrossRef]
  25. Qian, J.; Chen, Q.; Ward, S.M.; Duan, E.; Zhang, Y. Impacts of caffeine during pregnancy. Trends Endocrinol. Metab. 2020, 31, 218–227. [Google Scholar] [CrossRef]
  26. Geiger Brown, J.; Wieroney, M.; Blair, L.; Zhu, S.; Warren, J.; Scharf, S.M.; Hinds, P.S. Measuring subjective sleepiness at work in hospital nurses: Validation of a modified delivery format of the Karolinska sleepiness scale. Sleep Breath. 2014, 18, 731–739. [Google Scholar] [CrossRef]
  27. Kaida, K.; Takahashi, M.; Åkerstedt, T.; Nakata, A.; Otsuka, Y.; Haratani, T.; Fukasawa, K. Validation of the Karolinska sleepiness scale against performance and EEG variables. Clin. Neurophysiol. 2006, 117, 1574–1581. [Google Scholar] [CrossRef]
  28. Seo, B.N.; Kim, I. Differences of stress, sleep quality and metabolic syndrome by prolonged fatigue in early adulthood. Korean J. Adult Nurs. 2019, 31, 202. [Google Scholar] [CrossRef]
  29. Alsabri, S.G.; Mari, W.O.; Younes, S.; Elsadawi, M.A.; Oroszi, T.L. Kinetic and dynamic description of caffeine. J. Caffeine Adenosine Res. 2018, 8, 3–9. [Google Scholar] [CrossRef]
  30. Mort, J.R.; Kruse, H.R. Timing of blood pressure measurement related to caffeine consumption. Ann. Pharmacother. 2008, 42, 105–110. [Google Scholar] [CrossRef]
  31. Sato, K.; Sanders, K.M.; Gerthoffer, W.T.; Publicover, N.G. Sources of calcium utilized in cholinergic responses in canine colonic smooth muscle. Am. J. Physiol. 1994, 267, C1666–C1673. [Google Scholar] [CrossRef]
  32. Mahmud, A.; Feely, J. Acute effect of caffeine on arterial stiffness and aortic pressure waveform. Hypertension 2001, 38, 227–231. [Google Scholar] [CrossRef] [PubMed]
  33. Echeverri, D.; Pizano, A.; Montes, F.R.; Forcada, P. Acute effect of coffee consumption on arterial stiffness, evaluated using an oscillometric method. Artery Res. 2017, 17, 16. [Google Scholar] [CrossRef]
  34. Dix, L.M.L.; van Bel, F.; Baerts, W.; Lemmers, P.M.A. Effects of caffeine on the preterm brain: An observational study. Early Hum. Dev. 2018, 120, 17–20. [Google Scholar] [CrossRef] [PubMed]
  35. Ozkan, B.; Yüksel, N.; Anik, Y.; Altintas, O.; Demirci, A.; Cağlar, Y. The effect of caffeine on retrobulbar hemodynamics. Curr. Eye Res. 2008, 33, 804–809. [Google Scholar] [CrossRef] [PubMed]
  36. McClaran, S.R.; Wetter, T.J. Low doses of caffeine reduce heart rate during submaximal cycle ergometry. J. Int. Soc. Sports Nutr. 2007, 4, 11. [Google Scholar] [CrossRef]
  37. Sullivan, J.J.; Knowlton, R.G.; Brown, D.D. Caffeine affects heart rate and blood pressure response to prolonged walking. J. Cardiopulm. Rehabil. 1992, 12, 418–422. [Google Scholar] [CrossRef]
  38. Mosqueda-Garcia, R.; Tseng, C.J.; Biaggioni, I.; Robertson, R.M.; Robertson, D. Effects of caffeine on baroreflex activity in humans. Clin. Pharmacol. Ther. 1990, 48, 568–574. [Google Scholar] [CrossRef]
  39. Ruíz-Moreno, C.; Lara, B.; Brito De Souza, D.; Gutiérrez-Hellín, J.; Romero-Moraleda, B.; Cuéllar-Rayo, Á.; Del Coso, J. Acute caffeine intake increases muscle oxygen saturation during a maximal incremental exercise test. Br. J. Clin. Pharmacol. 2020, 86, 861–867. [Google Scholar] [CrossRef]
  40. Gonzaga, L.A.; VanderLei, L.C.M.; Gomes, R.L.; Valenti, V.E. Caffeine affects autonomic control of heart rate and blood pressure recovery after aerobic exercise in young adults: A crossover study. Sci. Rep. 2017, 7, 14091. [Google Scholar] [CrossRef]
  41. Menon, V. 20 years of the default mode network: A review and synthesis. Neuron 2023, 111, 2469–2487. [Google Scholar] [CrossRef]
  42. Luo, W.; Liu, B.; Tang, Y.; Huang, J.W.; Wu, J. Rest Promotes Learning: From the Perspective of Brain’s Default Mode Network Perspective. Behav. Sci. 2024, 14, 349. [Google Scholar] [CrossRef] [PubMed]
  43. Cheng, X.; Yuan, Y.; Wang, Y.; Wang, R. Neural antagonistic mechanism between default-mode and task-positive networks. Neurocomputing 2020, 417, 74–85. [Google Scholar] [CrossRef]
  44. Devaney, K.J.; Levin, E.J.; Tripathi, V.; Higgins, J.P.; Lazar, S.W.; Somers, D.C. Attention and default mode network assessments of meditation experience during active cognition and rest. Brain Sci. 2021, 11, 566. [Google Scholar] [CrossRef] [PubMed]
  45. Bonnelle, V.; Leech, R.; Kinnunen, K.M.; Ham, T.E.; Beckmann, C.F.; De Boissezon, X.; Greenwood, R.J.; Sharp, D.J. Default mode network connectivity predicts sustained attention deficits after traumatic brain injury. J. Neurosci. 2011, 31, 13442–13451. [Google Scholar] [CrossRef]
  46. Koshino, H.; Minamoto, T.; Yaoi, K.; Osaka, M.; Osaka, N. Coactivation of the default mode network Regions and Working Memory Network regions during task preparation. Sci. Rep. 2014, 4, 5954. [Google Scholar] [CrossRef]
  47. Astorino, T.A.; Roberson, D.W. Efficacy of acute caffeine ingestion for short-term high-intensity exercise performance: A systematic review. J. Strength Cond. Res. 2010, 24, 257–265. [Google Scholar] [CrossRef]
  48. Alasmari, F. Caffeine induces neurobehavioral effects through modulating neurotransmitters. Saudi Pharm. J. 2020, 28, 445–451. [Google Scholar] [CrossRef]
  49. Subramaniam, K.; Vinogradov, S. Improving the neural mechanisms of cognition through the pursuit of happiness. Front. Hum. Neurosci. 2013, 7, 452. [Google Scholar] [CrossRef]
  50. Beedie, C.J. All in the mind? Pain, placebo effect, and ergogenic effect of caffeine in sports performance. Open Access J. Sports Med. 2010, 1, 87–94. [Google Scholar] [CrossRef]
  51. Jin, Y.-B.; Kim, J.-H.; Song, C.-H.; Park, C.; Kang, C.-K. Diagnostic Ultrasound-Based Investigation of Central vs. Peripheral Arterial Changes Consequent to Low-Dose Caffeine Ingestion. Nutrients 2024, 16, 228. [Google Scholar] [CrossRef]
Figure 1. Brightness mode image of CCA measured using ultrasound.
Figure 1. Brightness mode image of CCA measured using ultrasound.
Applsci 15 01703 g001
Figure 2. Comparison of changes in SBP and DBP at each time point (the error bars indicate standard error). * p < 0.05.
Figure 2. Comparison of changes in SBP and DBP at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g002
Figure 3. Comparison of changes in the MaxD and MinD of the CCA at each time point (the error bars indicate standard error). * p < 0.05.
Figure 3. Comparison of changes in the MaxD and MinD of the CCA at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g003
Figure 4. Comparison of changes in the PWV of the CCA at each time point (the error bars indicate standard error).
Figure 4. Comparison of changes in the PWV of the CCA at each time point (the error bars indicate standard error).
Applsci 15 01703 g004
Figure 5. Comparison of changes in the PSV of the CCA at each time point (the error bars indicate standard error). * p < 0.05.
Figure 5. Comparison of changes in the PSV of the CCA at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g005
Figure 6. Comparison of changes in HR at each time point (the error bars indicate standard error). * p < 0.05.
Figure 6. Comparison of changes in HR at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g006
Figure 7. Comparison of changes in SpO2 at each time point (the error bars indicate standard error). * p < 0.05.
Figure 7. Comparison of changes in SpO2 at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g007
Figure 8. Comparison of the changes in accuracy rate at each time point (the error bars indicate standard error). * p < 0.05.
Figure 8. Comparison of the changes in accuracy rate at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g008
Figure 9. Comparison of the changes in response time at each time point (the error bars indicate standard error). * p < 0.05.
Figure 9. Comparison of the changes in response time at each time point (the error bars indicate standard error). * p < 0.05.
Applsci 15 01703 g009
Table 1. Participant information (mean ± SD).
Table 1. Participant information (mean ± SD).
Age (Years)Height (cm)Weight (kg)BMI (kg/m2)
Males (n = 15)22.93 ± 1.33174.93 ± 6.2574.73 ± 11.2724.35 ± 2.94
Females (n = 15)22.53 ± 1.36159.72 ± 3.2253.38 ± 5.6220.89 ± 1.75
Total (n = 30)22.73 ± 1.33167.33 ± 9.1564.06 ± 13.9422.63 ± 2.96
Abbreviations: BMI, body mass index; SD, standard deviation.
Table 2. Comparison of blood pressure parameters using RM ANOVA.
Table 2. Comparison of blood pressure parameters using RM ANOVA.
VariationCaffeine DoseTimeMean ± SDFpFactor 1Factor 2Mean Difference ± SE
(Factor 1–Factor 2)
tpTukey
SBP100 mg0 min11.40.2540 min30 min−0.00301 ± 0.00669−0.4500.895
30 min1.003 ± 0.0366660 min−0.00921 ± 0.00552−1.6670.235
60 min1.009 ± 0.0302630 min60 min−0.00620 ± 0.00436−1.4200.344
200 mg0 min110.3<0.001 *0 min30 min−0.01400 ± 0.00536−2.6100.037 *
30 min1.014 ± 0.0293660 min−0.02930 ± 0.00804−3.6400.003 *
60 min1.029 ± 0.0440330 min60 min−0.01530 ± 0.00563−2.7200.029 *
DBP100 mg0 min10.1790.8360 min30 min−0.00221 ± 0.00866−0.2550.965
30 min1.002 ± 0.0477760 min0.00262 ± 0.008420.3110.948
60 min0.997 ± 0.0463930 min60 min0.00483 ± 0.007060.6850.774
200 mg0 min17.850.001 *0 min30 min−0.02122 ± 0.00595−3.5640.004 *
30 min1.021 ± 0.0320760 min−0.02551 ± 0.00752−3.3900.006 *
60 min1.022 ± 0.0364930 min60 min−0.00429 ± 0.00711−0.6030.820
Abbreviations: DBP, diastolic blood pressure; F, F-statistic; p, p-value; SBP, systolic blood pressure; SE, standard Error; t, t-statistic. * p < 0.05
Table 3. Comparison of diameter using RM ANOVA.
Table 3. Comparison of diameter using RM ANOVA.
VariationCaffeine DoseTimeMean ± SDFpFactor 1Factor 2Mean Difference ± SE
(Factor 1–Factor 2)
tpTukey
MaxD100 mg0 min14.6100.014 *0 min30 min−0.01777 ± 0.00594−2.9900.016 *
30 min1.020 ± 0.0295160 min−0.0071 ± 0.00628−1.1300.504
60 min1.008 ± 0.0331730 min60 min0.01067 ± 0.005411.9700.138
200 mg0 min10.1300.8780 min30 min−0.00070 ± 0.00504−0.1360.990
30 min1.001 ± 0.0280060 min0.00214 ± 0.005490.3890.920
60 min0.999 ± 0.0299830 min60 min0.00282 ± 0.006650.4240.906
MinD100 mg0 min14.8400.011 *0 min30 min−0.01902 ± 0.00707−2.6890.031 *
30 min1.020 ± 0.0382060 min−0.01298 ± 0.00520−2.4970.048 *
60 min1.013 ± 0.0284930 min60 min0.00604 ± 0.006320.9560.610
200 mg0 min10.4270.6550 min30 min0.00229 ± 0.006740.3400.938
30 min0.999 ± 0.0364760 min0.00545 ± 0.005710.9530.612
60 min0.996 ± 0.0303330 min60 min0.00315 ± 0.005200.6060.818
Abbreviations: F, F-statistic; MaxD, maximum diameter; MinD, minimum diameter; p, p-value; SE, standard error; t, t-statistic. * p < 0.05
Table 4. Comparison of PWV using RM ANOVA.
Table 4. Comparison of PWV using RM ANOVA.
VariationCaffeine DoseTimeMean ± SDFpFactor 1Factor 2Mean Difference ± SE
(Factor 1–Factor 2)
tpTukey
PWV100 mg0 min12.8600.0660 min30 min−0.00245 ± 0.0254−0.09660.995
30 min1.005 ± 0.1364860 min−0.05081 ± 0.0208−2.43740.055
60 min1.053 ± 0.1116630 min60 min−0.04836 ± 0.0253−1.90900.156
200 mg0 min10.6950.5030 min30 min−0.02844 ± 0.0313−0.90900.639
30 min1.014 ± 0.1621860 min−0.00319 ± 0.0229−0.13900.989
60 min1.001 ± 0.1275130 min60 min0.02525 ± 0.02431.03900.559
Abbreviations: F, F-statistic; p, p-value; PWV, pulse wave velocity; SE, standard error; t, t-statistic.
Table 5. Comparison of the PSV, HR, and SpO2 using RM ANOVA.
Table 5. Comparison of the PSV, HR, and SpO2 using RM ANOVA.
VariationCaffeine DoseTimeMean ± SDFpFactor 1Factor 2Mean Difference ± SE
(Factor 1–Factor 2)
tpTukey
PSV100 mg0 min17.98<0.001 *0 min30 min0.0768 ± 0.01854.140<0.001 *
30 min0.927 ± 0.1006060 min0.0526 ± 0.02172.4200.056
60 min0.956 ± 0.1145730 min60 min−0.0242 ± 0.0186−1.3000.407
200 mg0 min12.110.1310 min30 min0.02918 ± 0.01501.9510.144
30 min0.960 ± 0.0694560 min0.03403 ± 0.01891.7970.190
60 min0.961 ± 0.0988530 min60 min0.00484 ± 0.01950.2480.967
HR100 mg0 min18.040.001 *0 min30 min0.0112 ± 0.00641.7600.209
30 min0.988 ± 0.0305460 min0.0310 ± 0.008753.5400.005 *
60 min0.973 ± 0.0385330 min60 min0.0198 ± 0.008142.4300.061
200 mg0 min16.090.008 *0 min30 min0.0187 ± 0.008302.2500.080
30 min0.980 ± 0.0401660 min0.0298 ± 0.010492.8400.022 *
60 min0.974 ± 0.0551130 min60 min0.0111 ± 0.006621.6700.235
SpO2100 mg0 min15.280.008 *0 min30 min−0.0043 ± 0.00148−2.9140.018 *
30 min1.004 ± 0.0080860 min−0.0038 ± 0.00153−2.4820.049 *
60 min1.003 ± 0.0080830 min60 min0.0005 ± 0.001330.3790.924
200 mg0 min111.5<0.001 *0 min30 min−0.00693 ± 0.00181−3.8210.002 *
30 min1.006 ± 0.0091360 min−0.00834 ± 0.00211−3.9470.001 *
60 min1.008 ± 0.0111330 min60 min−0.00142 ± 0.00164−0.8660.666
Abbreviations: F, F-statistic; HR, heart rate; PSV, peak systolic velocity; p, p-value; SE, standard error; SpO2, peripheral oxygen saturation; t, t-statistic. * p < 0.05
Table 6. Comparison of results of the two-back test using RM ANOVA.
Table 6. Comparison of results of the two-back test using RM ANOVA.
VariationCaffeine DoseTimeMean ± SDFpFactor 1Factor 2Mean Difference ± SE
(Factor 1–Factor 2)
tpTukey
Accuracy rate100 mg0 min13.310.044 *0 min30 min−0.01305 ± 0.00932−1.4000.356
30 min1.013 ± 0.0484260 min0.00903 ± 0.009470.9530.613
60 min0.991 ± 0.0492330 min60 min0.02207 ± 0.006843.2260.009 *
200 mg0 min15.440.007 *0 min30 min0.00537 ± 0.005860.9170.634
30 min0.995 ± 0.0321860 min0.02034 ± 0.007082.8740.020 *
60 min0.979 ± 0.0400930 min60 min0.01497 ± 0.006182.4230.055
Response time100 mg0 min130.4<0.001 *0 min30 min0.0445 ± 0.00944.740<0.001 *
30 min0.963 ± 0.0423860 min0.0701 ± 0.010486.690<0.001 *
60 min0.934 ± 0.0459030 min60 min0.0256 ± 0.007063.6200.003 *
200 mg0 min132.6<0.001 *0 min30 min0.0232 ± 0.006603.5200.005 *
30 min0.976 ± 0.0340860 min0.0637 ± 0.009286.860<0.001 *
60 min0.938 ± 0.0471330 min60 min0.0404 ± 0.007845.160<0.001 *
Abbreviations: F, F-statistic; p, p-value; SE, standard error; t, t-statistic. * p < 0.05
Table 7. Comparison of the change rate by caffeine dose using paired t-test.
Table 7. Comparison of the change rate by caffeine dose using paired t-test.
VariationTimeMean Difference ± SE
(100 mg–200 mg)
tp
SBP30 min−0.01097 ± 0.00732−1.49850.145
60 min−0.02008 ± 0.00786−2.55300.016 *
DBP30 min−0.01852 ± 0.00939−1.97200.059
60 min−0.02498 ± 0.01097−2.27600.031 *
MaxD30 min0.01953 ± 0.007832.4950.019 *
60 min0.00837 ± 0.006381.3110.201
MinD30 min0.02147 ± 0.009302.3070.029 *
60 min0.01718 ± 0.008442.0350.052
PWV30 min−0.00904 ± 0.04381−0.02060.838
60 min0.05229 ± 0.034641.51000.143
PSV30 min−0.03298 ± 0.02186−1.5090.144
60 min−0.00489 ± 0.03181−0.1540.879
HR30 min0.00818 ± 0.008970.9120.373
60 min−0.00185 ± 0.01311−0.1410.889
SpO230 min−0.002 ± 0.00205−0.9760.338
60 min−0.00437 ± 0.00213−2.0510.050 *
Accuracy rate30 min0.01782 ± 0.011681.5260.139
60 min0.01242 ± 0.014640.8490.404
Response time30 min−0.01296 ± 0.01064−1.2180.235
60 min−0.00403 ± 0.0117−0.3570.724
Abbreviations: DBP, diastolic blood pressure; HR, heart rate; MaxD, maximum diameter; MinD, minimum diameter; PSV, peak systolic velocity; PWV, pulse wave velocity; p, p-value; SBP, systolic blood pressure; SE, standard Error; SpO2, peripheral oxygen saturation; t, t-statistic. * p < 0.05
Table 8. Results of subjective evaluation.
Table 8. Results of subjective evaluation.
VariationCaffeine Dose0 minΔ30 minΔ60 min
VAS100 mg3.13 ± 2.19−0.063.07 ± 2.03−0.272.8 ± 2.04
200 mg2.87 ± 2.16−0.032.83 ± 2.09−0.262.57 ± 2.05
KSS100 mg4.87 ± 1.59−0.464.00 ± 1.46−0.284.13 ± 1.41
200 mg5.00 ± 1.55−1.133.87 ± 1.220.003.87 ± 1.28
CFS100 mg16.30 ± 5.53−1.9014.40 ± 5.62 2.1016.00 ± 5.64
200 mg14.80 ± 5.58−1.6013.20 ± 5.64−0.4012.80 ± 5.31
Abbreviations: CFS, Chalder Fatigue Scale; KSS, Karolinska Sleepiness Scale; VAS, visual analog scale.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Choi, M.-K.; Ahn, H.-S.; Kim, D.-E.; Lee, D.-S.; Park, C.-S.; Kang, C.-K. Effects of Varying Caffeine Dosages and Consumption Timings on Cerebral Vascular and Cognitive Functions: A Diagnostic Ultrasound Study. Appl. Sci. 2025, 15, 1703. https://doi.org/10.3390/app15041703

AMA Style

Choi M-K, Ahn H-S, Kim D-E, Lee D-S, Park C-S, Kang C-K. Effects of Varying Caffeine Dosages and Consumption Timings on Cerebral Vascular and Cognitive Functions: A Diagnostic Ultrasound Study. Applied Sciences. 2025; 15(4):1703. https://doi.org/10.3390/app15041703

Chicago/Turabian Style

Choi, Min-Ki, Hee-Seul Ahn, Da-Eun Kim, Da-Seul Lee, Chan-Sol Park, and Chang-Ki Kang. 2025. "Effects of Varying Caffeine Dosages and Consumption Timings on Cerebral Vascular and Cognitive Functions: A Diagnostic Ultrasound Study" Applied Sciences 15, no. 4: 1703. https://doi.org/10.3390/app15041703

APA Style

Choi, M.-K., Ahn, H.-S., Kim, D.-E., Lee, D.-S., Park, C.-S., & Kang, C.-K. (2025). Effects of Varying Caffeine Dosages and Consumption Timings on Cerebral Vascular and Cognitive Functions: A Diagnostic Ultrasound Study. Applied Sciences, 15(4), 1703. https://doi.org/10.3390/app15041703

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop