Impact of daily caffeine intake and timing on electroencephalogram-measured sleep in adolescents

Abstract

Study Objectives:

Caffeine use is ubiquitous among adolescents and may be harmful to sleep, with downstream implications for health and development. Research has been limited by self-reported and/or aggregated measures of sleep and caffeine collected at a single time point. This study examines bidirectional associations between daily caffeine consumption and electroencephalogram-measured sleep among adolescents and explores whether these relationships depend on timing of caffeine use.

Methods:

Ninety-eight adolescents aged 11–17 (mean =14.38, standard deviation = 1.77; 50% female) participated in 7 consecutive nights of at-home sleep electroencephalography and completed a daily diary querying morning, afternoon, and evening caffeine use. Linear mixed-effects regressions examined relationships between caffeine consumption and total sleep time, sleep-onset latency, sleep efficiency, wake after sleep onset, and time spent in sleep stages. Impact of sleep indices on next-day caffeine use was also examined.

Results:

Increased total caffeine consumption was associated was increased sleep-onset latency (β = .13; 95% CI = .06, .21; P < .001) and reduced total sleep time (β = −.17; 95% confidence interval [CI] = −.31, −.02; P = .02), sleep efficiency (β = −1.59; 95% CI = −2.51, −.67; P < .001), and rapid eye movement sleep (β = −.12; 95% CI = −.19, −.05; P < .001). Findings were driven by afternoon and evening caffeine consumption. Reduced sleep efficiency was associated with increased afternoon caffeine intake the following day (β = −.006; 95% CI = −.012, −.001; P = .01).

Conclusions:

Caffeine consumption, especially afternoon and evening use, impacts several aspects of adolescent sleep health. In contrast, most sleep indicators did not affect next-day caffeine use, suggesting multiple drivers of adolescent caffeine consumption. Federal mandates requiring caffeine content labeling and behavioral interventions focused on reducing caffeine intake may support adolescent sleep health.

Citation:

Lunsford-Avery JR, Kollins SH, Kansagra S, Wang KW, Engelhard MM. Impact of daily caffeine intake and timing on electroencephalogram-measured sleep in adolescents. J Clin Sleep Med. 2022;18(3):877–884.

BRIEF SUMMARY

Current Knowledge/Study Rationale: Caffeine use is ubiquitous among adolescents and aggregated measures of caffeine intake are associated with parent- and adolescent-reported sleep disturbances, including shortened sleep duration. However, studies using objective electroencephalogram measures of sleep and examining bidirectional relationships between caffeine intake and sleep health in adolescents have been lacking.

Study Impact: Using daily caffeine and at-home sleep electroencephalogram measures, this study is the first to show that caffeine consumption results in longer sleep-onset latency and reduced sleep duration, efficiency, and rapid eye movement sleep among adolescents, and that associations are driven by afternoon and evening caffeine use. The findings have implications for policy recommendations, such as caffeine labeling on products, and behavioral sleep treatments for adolescents, which may incorporate caffeine reduction as a key focus.

INTRODUCTION

Caffeine consumption is ubiquitous among US adolescents,¹ with up to 95% reporting recent use.² While average daily caffeine intake among teens has been estimated at 50 mg,³ the amount consumed varies widely. For example, 1 study reported a range of 0–800 mg of caffeine intake per day over a 2-week period.⁴ Common caffeine sources among adolescents include soda, tea, coffee, and energy drinks,^2,3,5 the last of which is particularly concerning given the high caffeine content.^6–8 Although legal, widely used, and socially acceptable, when consumed in high amounts caffeine is nonetheless a psychoactive stimulant substance linked to detrimental effects on adolescent health and development, including cognitive, physiological, psychological, and cardiovascular functioning.^1,6–10

High caffeine intake may be particularly harmful to adolescent sleep health.^11,12 In particular, increased caffeine consumption may contribute to insufficient sleep among adolescents,¹³ including shorter duration,^4,5,14–22 increased wake after sleep onset (WASO),⁴ and more difficulty falling or staying asleep,^10,14,23 as assessed by parent or adolescent report, although not all studies have associated caffeine with adolescent sleep.^2,24,25 Daytime sleepiness^2,14 and dysfunction²⁶ also have been linked to high caffeine intake among adolescents, suggesting a possible vicious cycle, in which caffeine interferes with sleep and results in daytime sleepiness, which, in turn, contributes to greater caffeine consumption.²⁷

Despite links between caffeine, sleep, and adolescent health, several critical questions remain. First, previous studies have largely relied on self- or caregiver-reports of sleep,^{4,5,10,14–23,25} which are vulnerable to reporter biases. A handful have used actigraphy,^24,28,29 which estimates sleep based on movement and physiological assessments (eg, heart rate) rather than directly measuring sleep. Second, prior research has primarily focused on sleep duration or perceived sleep quality. In contrast, studies using electroencephalography (EEG), which examines a broad range of important outcomes, including sleep stages (ie, rapid eye movement [REM] and deep/slow-wave sleep [SWS]), have been lacking, although 1 small study has shown reduced slow-wave activity at the beginning of the night among adolescents who regularly use caffeine compared with nonusers.²⁹ Another experimental study of male teenagers showed reduced SWS following evening ingestion of 80 mg caffeine, but only among individuals with a higher level of SWS following placebo (ie, those with a higher need for deep sleep), suggesting interindividual variability in caffeine-induced SWS changes.³⁰

Third, it is unclear to what extent the timing of caffeine intake matters for understanding its impact on adolescent sleep. Adult studies suggest that evening caffeine consumption has a larger impact on sleep than morning caffeine use,³¹ and adolescents are known to use caffeine across the day, including evening.²⁶ Given that caffeine antagonizes adenosine A₁ and A_2A receptors, which are important to sleep/arousal regulation,³² and has an average half-life of 4–6 hours,³³ caffeine consumption occurring well before bedtime may impact adolescent sleep. However, only 1 study has examined caffeine timing and sleep among adolescents, and found that afternoon caffeine consumption was related to more self-reported—but not actigraphy-measured—sleep problems.²⁸ Finally, the direction of effect between caffeine consumption and sleep problems among adolescents is currently unknown: greater caffeine intake may lead to poor sleep; insufficient sleep and fatigue may lead to increased caffeine use; or caffeine and sleep may interact bidirectionally, creating a vicious cycle undermining adolescent health. To date, most studies have relied on aggregate caffeine measures (eg, querying consumption over a week,^10,19,22,23 month,^17,20,28 or year^5,15,16), which have not allowed for examination of the direction of effect.

The current study examines bidirectional associations between caffeine intake and sleep over a 7-day period in a community sample of adolescents and addresses prior limitations by assessing sleep at home using EEG, measuring caffeine consumption and sleep daily, and querying caffeine intake separately by time of day (morning, afternoon, evening). Our primary hypothesis was that total caffeine consumption would impact the subsequent night’s sleep (ie, shorter total sleep time [TST], longer sleep-onset latency [SOL], reduced sleep efficiency [SE], greater WASO). Second, we hypothesized that associations would be driven by caffeine consumed in the afternoon and evening. We also examined the impact of caffeine intake on sleep stages (REM, deep, light sleep). Finally, we explored whether poorer sleep would increase caffeine intake the following day, thus contributing to a vicious cycle.

METHODS

Participants

Adolescents aged 11–17 years were recruited year-round from the Durham, North Carolina, area between March 2019 and March 2020 via electronic flyers through local school systems, word of mouth, and a research participant contact database. All participants concluded participation prior to the coronavirus disease 2019 (COVID-19) lockdown. Inclusion criteria included ability to follow written/verbal instructions in English, ability to comply with study procedures, and access to a smartphone for daily survey completion. Exclusion criteria included reported sleep apnea or periodic leg movement syndrome diagnosis, current use of prescribed or over-the-counter sleep aids, and medical diagnosis or medication use likely to interfere with sleep as determined by the research team. If participants reported occasional (pro re nata PRN) melatonin use, a 7-day washout period was completed prior to study initiation (n = 2). Study compensation was $200. The Duke University School of Medicine Institutional Review Board approved all study procedures.

Procedure

Parents/guardians completed a prescreen telephone assessment, and potentially eligible participants and a parent/guardian attended an onsite intake visit. Participants and guardians signed an electronic informed-consent form (youth younger than age 12 years provided verbal assent). Eligible participants were provided with a sleep-EEG device and a study coordinator reviewed step-by-step instructions for use. Families were also provided with a device manual and links to instructional videos. Sleep was recorded for 7 consecutive nights beginning the evening of the onsite visit. Participants completed a daily electronic diary querying caffeine use via Research Electronic Data Capture (REDCap), a secure web platform. The diary link was sent each morning via text message, and an evening reminder was automatically sent if the diary was not completed. Following the seventh night, families returned EEG devices.

Measures

Sleep

Sleep was assessed at-home using a single-channel EEG device (Zmachine Insight+; General Sleep Corporation, Cleveland, OH), which is acceptable and feasible for use with adolescents.³⁴ Each night participants placed 1 disposable sensor behind each ear and 1 on the center of their neck directly prior to getting into bed, and removed the sensors immediately following their final awakening. Sensors were connected to the Zmachine Insight+ device via wires, and participants were instructed to place the device next to their bed (eg, bedside table). Sleep-staging scoring and summary measures of interest were calculated using Zmachine Insight+ software algorithms, which compare favorably with consensus scoring by polysomnographic technologists,^35,36 and included TST, SOL, SE, WASO, and total time spent in light (N1/N2), deep (N3), and REM sleep.

Caffeine intake

Each morning, adolescents completed a widely used sleep diary³⁷ which queried caffeine intake during the previous day.³⁸ Specifically, adolescents were asked, “How many caffeine drinks (eg, Coke, tea, coffee, etc) did you have yesterday?” and were queried separately for morning (before noon), afternoon (12–6 pm), and evening (after 6 pm).

Statistical analysis

All analyses were completed in R version 4.0.3³⁹ (R Foundation for Statistical Computing, Vienna, Austria), using 2-tailed tests of significance.

Primary analyses

Mixed-effects regression models for repeated measures controlling for age and sex examined relationships between (1) daily caffeine use (total; and by morning, afternoon, and evening) and subsequent sleep-EEG measures and (2) daily sleep-EEG measures and caffeine use the following day. Separate models were trained for each of the 27 possible combinations of the individual’s caffeine use and sleep-EEG measures. To test the relationship between afternoon caffeine use and TST, for example, 1 model was developed with daily afternoon caffeine use, age, and sex as fixed effects and that night’s TST as the dependent variable. We then developed a second model with nightly TST, age, and sex as fixed effects and afternoon caffeine use the following day as the dependent variable. All models included participant-specific intercepts (ie, random effects), allowing each participant to serve as his/her own control.

Caffeine use patterns

To further illustrate the impact of caffeine timing on sleep, daily caffeine use patterns were manually grouped as follows. Across all days from all participants, days with 0 total caffeine beverages consumed were assigned to a first cluster, No Caffeine. Days with morning caffeine use only were assigned to a second cluster, Morning Caffeine. Days with 0 evening caffeine use but not meeting criteria for the previous 2 groups were assigned to a third cluster, Afternoon Caffeine. Days with 1 evening caffeine drink were assigned to a fourth cluster, Evening Caffeine. Finally, days with > 1 evening caffeine drink were assigned to a fifth cluster, Heavy Evening Caffeine. Pairwise Tukey’s tests identified statistically significant differences in sleep measures between groups.

RESULTS

Participants

A total of 123 families completed a telephone prescreening, of whom 107 adolescents expressed interest, competed an in-person screening visit, and were eligible. Nine did not complete all study procedures, resulting in a sample of 98 who provided both sleep-EEG data (mean number of nights = 5.42; standard deviation 1.71) and caffeine use ratings. Of note, caffeine intake did not differ as a function of day of the week (weekend vs weekday; dummy coded) [morning caffeine: t(724) = −1.02, P = .31; afternoon caffeine: t(724)= −.82, P = .41; evening caffeine: t(721)= −1.15, P = .25] (see Table 1).

Table 1.

Demographic, sleep, and caffeine characteristics of the sample.

	Values
Demographic variables
Age, mean (SD), y	14.38 (1.77)
Sex (females), n (%)	49 (50%)
Race, n (%)
African American/Black	27 (28%)
Asian	3 (3%)
Native American/Alaska Native	1 (1%)
White	63 (64%)
More than 1 race	4 (4%)
Ethnicity (Hispanic), n (%)	6 (6%)
Sleep index, mean (SD)
TST, h	6.92 (1.48)
SE, %	82.12 (10.26)
SOL, min	45.30 (46.50)
WASO, min	35.78 (35.70)
REM sleep, h	1.86 (0.68)
Deep sleep, h	1.54 (0.41)
Light sleep, h	3.51 (1.00)
Caffeine (number of beverages), mean (SD)
Total	0.57 (1.12)
Morning	0.12 (0.35)
Afternoon	0.26 (0.57)
Evening	0.20 (0.58)

REM = rapid eye movement, SD = standard deviation, SE = sleep efficiency, SOL = sleep-onset latency, TST = total sleep time, WASO = wake after sleep onset.

Total caffeine use and subsequent sleep

Increased total caffeine intake was associated with shorter TST, reduced SE, longer SOL, and reduced REM sleep, but was not related to WASO, deep sleep, or light sleep. For every additional caffeinated beverage consumed by an adolescent in a day, on average, TST decreased by 10 minutes, SE was reduced by 2%, SOL increased by 8 minutes, and REM sleep decreased by 7 minutes compared with his or her typical sleep (see Table 2).

Table 2.

Associations between caffeine consumption (total and by timing) and subsequent sleep.

Sleep Index	Caffeine Consumption
	Total	Evening	Afternoon	Morning
TST	−.17 (−.31, −.02)*	−.47 (−.73, −.21)***	−.24 (−.47, −.01)*	.05 (−.32, .41)
SOL	.13 (.06, .21)***	.28 (.15, .41)****	.21 (.09, .33)***	.17 (−.02, .36)+
SE	−1.59 (−2.51, −.67)***	−3.75 (−5.36, −2.14)****	−1.37 (−2.81, .06)+	−.68 (−2.90, 1.53)
WASO	.01 (−.04, .07)	.04 (−.06, .14)	−.05 (−.14, .03)	.01 (−.12, .14)
REM sleep	−.12 (−.19, −.05)***	−.19 (−.32, −.07)**	−.20 (−.31, −.09)***	−.04 (−.22, .13)
Deep sleep	−.02 (−.06, .02)	−.01 (−.08, .06)	−.02 (−.09, .04)	−.03 (−.13, .07)
Light sleep	−.03 (−.12, .07)	−.27 (−.45, −.10)**	−.02 (−.17, .13)	.11 (−.13, .35)

Each value shows the β (95% confidence intervals) associated with the caffeine predictor and sleep outcome from each linear mixed model. Each model covaried for age and sex. Statistical significance is indicated as follows: ****P < .0001, ***P < .001, **P < .01, *P < .05, ⁺P < .10. REM = rapid eye movement, SE = sleep efficiency, SOL = sleep-onset latency, TST= total sleep time, WASO = wake after sleep onset.

Caffeine use timing and subsequent sleep

Evening caffeine intake was related to longer SOL and reduced TST, SE, REM, and light sleep, but was unrelated to WASO or deep sleep. For every evening caffeinated beverage consumed by an adolescent, on average, TST decreased by 28 minutes, SE was reduced by 4%, SOL increased by 17 minutes, REM decreased by 11 minutes, and light sleep decreased by 16 minutes compared with his or her typical sleep. Afternoon caffeine use was also related to shorter TST, longer SOL, and reduced REM. Afternoon caffeine use was not correlated with SE, WASO, deep sleep, or light sleep. For every afternoon caffeinated beverage consumed by an adolescent, on average, TST decreased by 14 minutes, SOL increased by 13 minutes, and REM decreased by 12 minutes compared with his or her typical sleep. Although not statistically significant, an average increase in SOL by 10 minutes for every morning caffeinated beverage is notable. Morning caffeine was unrelated to other sleep variables (see Table 2).

Sleep-EEG indices and next day caffeine use

No sleep-EEG index was associated with total caffeine use on the subsequent day (all P values >.05). When examined separately by timing, only reduced SE was associated with increased caffeine intake the following afternoon (β = −.006; 95% confidence interval [CI] = −.012, −.001; P = .01). No other relationships were significant (P > .05).

Caffeine use patterns and subsequent sleep-EEG indices

To further illustrate the impact of caffeine use on sleep indices, consumption was clustered into 5 patterns as described above. Figure 1 shows the mean number of caffeine drinks consumed at different times of day for each pattern. Note that days categorized as fitting the Evening or Heavy Evening Caffeine patterns often included consumption earlier in the day as well, particularly in the afternoon.

Figure 1. Mean caffeine use by timing (morning, afternoon, evening) for each of the sleep patterns.

Pairwise comparisons examining sleep differences among the 5 clusters indicated that the Heavy Evening pattern was associated with reduced TST compared with all other patterns, except for Evening. Both Heavy Evening and Evening patterns evidenced reduced SE compared with the No Caffeine pattern, and additionally, the Heavy Evening pattern showed decreased SE compared with the Morning and Afternoon patterns. Both Afternoon and Evening patterns showed increased SOL compared with the No Caffeine pattern, and the Heavy Evening pattern was associated with increased SOL compared with all patterns. Finally, the Heavy Evening pattern was associated with decreased REM compared to the No Caffeine pattern (see Table 3 and Figure 2).

Table 3.

Pairwise comparisons in sleep variables between caffeine patterns.

Group	Comparison Group	TST (Hours)	SE (%)	SOL (Minutes)	REM (Hours)
No Caffeine	Morning Caffeine	−0.03	1.16	−0.22	−0.02
No Caffeine	Afternoon Caffeine	0.00	−1.88	16.96*	−0.15
No Caffeine	Evening Caffeine	−0.42	−5.37**	18.30*	−0.24
No Caffeine	Heavy Evening Caffeine	−1.43**	−13.41***	54.86***	−0.57*
Morning Caffeine	Afternoon Caffeine	0.03	−3.04	17.18	−0.13
Morning Caffeine	Evening Caffeine	−0.40	−6.53	18.52	−0.21
Morning Caffeine	Heavy Evening Caffeine	−1.40*	−14.57***	55.08**	−0.54
Afternoon Caffeine	Evening Caffeine	−0.42	−3.49	1.34	−0.08
Afternoon Caffeine	Heavy Evening Caffeine	−1.43**	−11.53***	37.90*	−0.41
Evening Caffeine	Heavy Evening Caffeine	−1.01	−8.03	36.56*	−0.33

Values reflect mean differences between groups. Significance is denoted as follows: *P < .05, **P < .01, ***P < .001. REM = rapid eye movement, SE = sleep efficiency, SOL = sleep-onset latency, TST= total sleep time.

Figure 2. Differences in sleep indices by caffeine timing pattern.

1 = No Caffeine, 2 = Morning Caffeine, 3 = Afternoon Caffeine, 4 = Evening Caffeine, 5 = Heavy Evening Caffeine. Whiskers extend to outliers within 1.5× IQR of the high and low quartiles, respectively. hrs = hours, IQR = interquartile range, REM = rapid eye movement.

DISCUSSION

These results add to a growing literature highlighting the impact of caffeine on adolescent sleep health¹³ and corroborate prior findings regarding caffeine use and shortened sleep duration among adolescents using other sleep measures (ie, self-/parent report).^4,5,14–22 Additionally, the current study provides the first evidence from an objective sleep assessment of extended SOL, reduced SE, and decreased REM sleep following caffeine use among adolescents. The impact of caffeine intake on extending SOL and reducing SE is expected given the arousal-inducing effects of caffeine and is highly consistent with the adult literature.³¹ Additionally, a recent small study (n = 18 adolescent males) showed trends toward reduced SE and increased latency to persistent sleep following 80 mg caffeine administration occurring 4 hours prior to bedtime.³⁰

The impact of caffeine on sleep stages found in the current study—namely, reducing REM sleep without impact on deep sleep—is surprising given previously observed relationships between caffeine consumption and reduced SWS among adults³¹ and lower slow-wave activity among adolescents.²⁹ One possible reason for the current findings is that our deep sleep measure (ie, sum of deep sleep across the night) is less sensitive to caffeine than EEG spectra measures such as slow-wave activity.³¹ However, another recent study also did not consistently find effects of caffeine intake on SWS among adolescents, but rather found variability across individuals.³⁰ Other factors related to both caffeine (eg, acute vs chronic consumption⁴⁰) and deep sleep (timing; earlier vs later in the sleep period²⁹) may also impact whether associations are observed. Further exploration of a possible impact of caffeine intake on deep sleep—and who may be vulnerable to such a process and under what circumstances—is warranted.

This study is among the first to show an association between caffeine consumption and reduced REM sleep in humans, although decreased REM following caffeine administration has been reported among juvenile and adult nonhuman primates.^41,42 Although neither prior EEG study of sleep and caffeine in adolescents showed an impact on REM,^29,30 those studies used different methodologies (eg, comparing sleep between caffeine users vs nonusers rather than examining the impact of caffeine use on subsequent sleep within individuals²⁹) in small samples. In addition, although caffeine intake is not linked to reduced REM in adults,³¹ caffeine consumption may interact with other adolescent sleep changes to result in reduced REM duration. For example, caffeine may not impact REM specifically, but rather, due to its impact on increasing SOL, caffeine interacts with both biological (eg, delayed sleep patterns) and environmental (eg, late-night light exposure, early school start times) factors to result in shortened TST; and because REM occurs more frequently later in the night, it is disproportionately reduced compared with other sleep stages. Indeed, this is consistent with prior evidence showing that when TST is experimentally curtailed in adolescents, the REM reduction is proportionally greater than non-REM.⁴³ Future work should focus on replicating the current results and elucidating these intriguing possibilities. Regardless, the REM reduction observed in this study is concerning given its importance to cognition and psychological well-being during adolescence.⁴⁴

The current findings also dovetail with previous findings among adults³¹ and adolescents²⁸ suggesting that caffeine use timing may be important for understanding its impact on sleep—and specifically, that afternoon and evening consumption may be particularly detrimental to sleep. Interestingly, morning use approached an association with increased SOL, which, to our knowledge, has not been previously reported. The half-life of caffeine is ∼4–6 hours; however, due to demographic, behavioral (eg, diet), and genetic factors, significant interindividual differences in caffeine clearance exist.³³ Thus, while this finding did not reach statistical significance in our full sample, it may suggest that, for some adolescents (eg, those with slower caffeine metabolism) or when consumed at high doses, even caffeine intake occurring early in the day may interfere with the ability to fall asleep that night, and future research using rigorous measures of caffeine intake and pharmacokinetic sampling methodologies should examine this question.

In contrast, we largely did not find evidence linking sleep disturbances to increased next-day caffeine intake, although a significant relationship between reduced SE and increased subsequent afternoon caffeine intake was observed. This may suggest that, while caffeine intake consistently impacts sleep, daytime sleepiness resulting from poor sleep may be only 1 of many factors influencing caffeine consumption. For example, adolescents may use caffeine to improve mood, meet social demands, enhance sports or academic performance, suppress appetite, or because they enjoy the taste.^2,6 Clarifying potential pathways by which sleep may interact with other developmental factors to drive adolescent caffeine intake would be an interesting topic for future study.

This study has several limitations. First, although a strength of this study is its daily measure of caffeine, which allows for examination of the direction of effects, our measure neither specified caffeine dosage nor queried caffeine consumption separately by type of drink (eg, coffee, tea, soda) or from sources other than beverages (eg, foods such as chocolate). In addition, overall caffeine consumption was relatively low in our sample (< 1 caffeinated drink per day, on average), which may have limited detection of some potential effects. Second, sleep staging in the current study was determined using a single-channel, consumer-grade EEG device and was calculated using automated algorithms. Although this device may increase ecological validity of sleep measures by assessing sleep at home, and compares favorably with polysomnography,³⁵ the current methodology did not assess other potentially important sleep features, such as EEG spectra. In addition, while the sleep-staging algorithm accompanying the device compares favorably with consensus of polysomnographic technologists overall, sensitivities for light sleep designation (kappa = .84) have been shown to be somewhat higher than for deep sleep and REM (.74 and .72, respectively).³⁶ Future studies using objective, precise measures of caffeine dosage from a range of sources and high-density EEG montages will be important for further clarifying relationships between adolescent caffeine consumption and sleep physiology.

CONCLUSIONS

Caffeine consumption impacts subsequent sleep duration, latency, efficiency, and REM duration in adolescents. Reducing caffeine intake, particularly in the afternoon and evening, may enhance adolescent sleep, with the potential for downstream support of health and development. Caffeine education is already a part of adolescent behavioral sleep interventions;⁴⁵ however, refinement of strategies for dissemination of educational and behavioral techniques targeting caffeine and sleep to adolescents remains a clinical need. For example, as consumer-grade sleep technologies continue to advance, methods for assessing links between caffeine intake, particularly in the afternoon and evening, and sleep and communicating this information directly to the adolescents themselves (eg, through a smartphone app) may empower adolescents to observe the impact of caffeine and motivate behavior change. Additionally, federal mandates requiring labeling of caffeine content may be important for raising awareness of caffeine consumption arising from a variety of products as well as its potential health effects.⁴⁶

DISCLOSURE STATEMENT

All authors have reviewed and approved the manuscript. Work for this study was performed at Duke University School of Medicine. This study was funded by the Duke Institute for Brain Sciences (DIBS). Further funding was provided by National Institute of Mental Health grant K23MH108704 to J.R.L.-A. The funder/sponsor did not participate in the work. The authors report no conflicts of interest.

ABBREVIATIONS

CI

confidence interval

EEG

electroencephalography

REM

rapid eye movement

SE

sleep efficiency

SOL

sleep-onset latency

SWS

slow-wave sleep

TST

total sleep time

WASO

wake after sleep onset