Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Sep 16.
Published in final edited form as: Alcohol Clin Exp Res. 2019 May 21;43(7):1575–1584. doi: 10.1111/acer.14076

PRELIMINARY EVIDENCE THAT REAL WORLD SLEEP TIMING AND DURATION ARE ASSOCIATED WITH LABORATORY-ASSESSED ALCOHOL RESPONSE

Brant P Hasler 1, Meredith L Wallace 1, Sarah J White 1, Brooke S G Molina 1, Sarah L Pedersen 1
PMCID: PMC7493816  NIHMSID: NIHMS1028139  PMID: 31070238

Abstract

Background:

Sleep timing and evening chronotype have been implicated in alcohol use problems but research has yet to study them in relation to theory-driven lab-based measures of alcohol use disorder risk. The current study examined (a) whether chronotype, sleep timing, and/or sleep duration are associated with alcohol response (subjective stimulation, sedation, and behavioral disinhibition), and (b) if sex and race moderate these associations.

Methods:

Adult drinkers (N=144; 46 female participants) completed two counterbalanced beverage administration sessions (alcohol, non-alcohol) during which they rated stimulation/sedation and completed a cued go/no go task. They reported bed and wake times over 10 days.

Results:

Later sleep timing was associated with greater increases in alcohol stimulation, but among male and White participants only. Later sleep timing (among male participants) and greater eveningness (examined among White male participants only) were associated with greater overall stimulation on average in the alcohol session relative to the non-alcohol session, irrespective of alcohol consumption. More variable sleep duration was associated with greater increases in sedation.

Conclusions:

These findings offer preliminary, but novel evidence that sleep characteristics may relate to the relative stimulating and sedating effects of alcohol, thereby influencing the risk for alcohol problems.

Keywords: chronotype, sleep, alcohol, impulsivity

Introduction

Growing evidence links sleep to alcohol use and alcohol-related problems (e.g., (Roehrs and Roth, 2001, Wong et al., 2015, Brower et al., 2011, Hasler et al., 2014, Hasler et al., 2016, Roehrs and Roth, 2018). Along with sleep disturbances, many studies have reported that evening chronotypes (i.e., having a preference for later timing of sleep and activity) engage in greater alcohol use. Emerging data suggest that one potential pathway to increased risk for heavy alcohol use in evening chronotypes is through greater impulsivity and altered reward responsiveness, which are linked in turn to alcohol outcomes (e.g., (Stautz and Cooper, 2013). Further elucidation of this potential link through examination of sensitivities to the acute effects of alcohol is a critical next step in understanding why eveningness preference is associated with increased risk for heavy alcohol involvement.

Evening chronotypes consistently report heavier alcohol involvement than morning chronotypes (E.g., (Tavernier and Willoughby, 2013, Negriff et al., 2011, Saxvig et al., 2012, Adan, 1994). In parallel, some studies link self-reports of actual sleep timing (which may or may not correspond to preferred timing) to alcohol use (Pieters et al., 2010, Pasch et al., 2010). Longitudinal evidence suggests that both evening chronotype and later actual sleep timing predict more extreme binge alcohol use a year later (Hasler et al., 2017b). Notably, eveningness is often accompanied by more variable sleep timing (Soehner et al., 2011, Wittmann et al., 2006), which is also associated with alcohol involvement and thus is a hypothesized factor linking eveningness and alcohol problems (Wittmann et al., 2006). Cross-sectional studies link larger weekday-weekend differences in sleep timing with greater alcohol, tobacco, and marijuana use (O’Brien and Mindell, 2005, Pasch et al., 2010), while longitudinal studies report that larger weekday-weekend differences in sleep duration predict more alcohol use disorder (AUD) symptoms 3- and 5-years later (Hasler et al., 2014), and greater self-reported variability in sleep timing predicts an earlier age of onset for AUD (Hasler et al., 2016). Examining multiple components of sleep (e.g., self-reported preference of sleep timing, actual sleep timing, variability in actual sleep timing) within the same study is important to further understand which domains of sleep are most related to risk for heavy alcohol involvement.

Sleep timing, eveningness, and alcohol response

Individual differences in alcohol response are widely studied risk factors for AUD, heavy drinking, and alcohol problems (Ray et al., 2016). Reduced sensitivity, or low response, to the acute sedating and negative effects of alcohol has been shown to confer risk for alcohol problems and AUD (Schuckit, 1984, Schuckit and Smith, 1996). Conversely, increased sensitivity to the rewarding or stimulating effects of alcohol has also been shown to increase risk for negative alcohol use outcomes (Corbin et al., 2008, King et al., 2011, King et al., 2016).

Evening chronotypes may experience a differential response to alcohol as these individuals appear to have altered reward function. However, findings are mixed regarding whether this manifests as hypo- or hypersensitivity to reward, with findings of both increased sensation seeking and novelty seeking (Kang et al., 2015, Tonetti et al., 2010, Caci et al., 2004), as well as reduced reward responsiveness (Hasler et al., 2010). Neuroimaging evidence also suggests that evening chronotypes exhibit altered neural response to reward that is relevant to alcohol involvement ((Hasler et al., 2017a, Hasler et al., 2013). Given these findings, evening chronotypes may also experience increased sensitivity to the rewarding effects of alcohol, i.e. the stimulating effects (Hendler et al., 2011). Although a few studies suggest that other sleep factors, such as daytime sleepiness, insomnia, and circadian time of administration, influence the response to alcohol (Roehrs and Roth, 2001, Van Reen et al., 2013), none of these studies have examined eveningness or sleep timing. Differences in alcohol response may partly account for why evening chronotypes experience increased risk for alcohol problems.

Sleep timing, eveningness, and impulsivity

Eveningness may be characterized by greater impulsivity and risk-taking, independent of alcohol consumption. Evening chronotypes endorse higher levels of general impulsivity on self-report measures (Kang et al., 2015, Russo et al., 2012, Caci et al., 2005, Adan et al., 2010), but studies using task-based measures of risk-taking (the Balloon Analogue Risk Task) or behavioral disinhibition (cued go/no-go task) reported no chronotype differences (Killgore, 2007) or equivocal results (Kang et al., 2015), respectively. Greater variability in sleep timing has not been directly examined in relation to impulsivity or behavioral disinhibition. Given that alcohol can impair impulse control (e.g., (Weafer and Fillmore, 2008), it is plausible that impulsivity associated with eveningness and later or more variable sleep timing may be exacerbated by alcohol consumption.

Key moderators of sleep-alcohol response associations

Sex and race are potentially important moderators of sleep-alcohol response associations. Sex differences are well-documented in alcohol use and alcohol problems (Nolen-Hoeksema, 2004), and while understudied in alcohol response studies, evidence suggests that females may feel more intoxicated and be more impaired at the same blood alcohol content as males (Miller et al., 2009). Sex differences are also apparent in sleep characteristics, with males tending to report later sleep timing (Roenneberg et al., 2007) and shorter sleep duration (Knutson et al., 2010). Furthermore, males may be more sensitive to chronotype associations with reward function (Hsu et al., 2012) and substance use ((Broms et al., 2011). Differences between Black and White individuals are also apparent across alcohol- (Zapolski et al., 2014) and sleep-related constructs (Malone et al., 2017, Paech et al., 2017), but have been largely neglected in alcohol response studies. Tentative evidence suggests that Black drinkers may experience sharper increases in stimulation following alcohol consumption compared to White drinkers (Pedersen and McCarthy, 2013).

We extend prior work by assessing, with electronic daily diary methods, actual sleep timing and variability in sleep timing as well as a measure of chronotype. We also expand prior research on sleep timing and altered reward responsiveness and impulsivity by examining acute subjective response and objectively-measured behavioral disinhibition following alcohol and non-alcohol beverage consumption in a within-subject administration in the laboratory.

Study Hypotheses

For our primary hypotheses, we hypothesized that later sleep timing, more variable sleep timing, and eveningness preference would be associated with (a) increased sensitivity to alcohol’s stimulating effects, and (b) a sharper increase in behavioral disinhibition after alcohol consumption relative to a control condition (non-alcohol beverage consumption). We also examined whether sleep timing was associated with the subjective sedating effects of alcohol relative to the control beverage, although we did not have an a priori hypothesis regarding the direction of effect. Given that basal levels of sleepiness predict a more sedating response to alcohol (Roehrs and Roth, 2001), we also hypothesized that shorter and/or more variable sleep duration would be associated with: (a) greater self-reported sedating effects of alcohol; and (b) greater behavioral disinhibition following alcohol consumption relative to consumption of a control beverage. Finally, given differences in both sleep and alcohol consumption for male and female individuals and Black and White individuals, we ran secondary analyses to explore whether sex or race moderated associations between any of the sleep variables and response to alcohol.

Methods

Participants

Data from two separate studies (Study 1: n=148; Study 2: n=92) that were designed to be able to combined for data analysis on key variables were utilized in the current study. These protocols utilized nearly-identical methods (identical design for recruitment, compensation, alcohol administration, EMA protocol) and focused on young adulthood when alcohol use disorder is most likely to onset (Grant et al., 2015). Given that these studies were designed to be combined, the methods are presented as one study (total n=240) with differences (specific measures were only included in one of the studies) noted. The overarching aim of both studies was to examine impulsivity and alcohol response outside and inside the laboratory. Study 1 was designed to examine these processes across race in a sample enriched for impulsivity by recruiting participants with and without ADHD histories. Study 2 expanded recruitment without the focus on race and added measures not included in Study 1 (e.g., chronotype). Both studies initially recruited participants from Pittsburgh ADHD Longitudinal Study (PALS), an ongoing study designed to examine alcohol use outcomes for individuals diagnosed with ADHD in childhood relative to those without ADHD. The PALS sample predominantly consists of White male adults and we recruited all eligible Black drinkers of both genders from PALS to participate in Study 1. When recruitment switched to the community we matched the demographics of this recruitment to what had been obtained in PALS to reduce possible differences. By design we recruited half of the participants in both Study 1 and 2 to have a childhood history of ADHD to enhance the distribution of impulsivity in our sample, allow for examination of specific processes across both race and ADHD history, and to allow for recruitment from a large, well-characterized ongoing study with data spanning childhood into adulthood (PALS).

Participants were required to be 21–36 years old and current drinkers (drank alcohol in the last month), self-identify as Black/African American or White/European American during the phone screen, and consumed in the past 6 months the equivalent amount of alcohol as would be given during the laboratory alcohol administration. To minimize risk of potential harm (e.g., increasing likelihood of relapse), participants were excluded if they had received prior AUD/SUD treatment and/or were currently abstaining or limiting their alcohol use due to fear of having a problem. However, there was not an upper threshold in amount or frequency of alcohol consumed or level of alcohol problems for eligibility. For safety purposes, given the alcohol consumption component of the study, participants were also excluded if they reported significant medical or psychiatric illness (e.g., psychotic disorders, liver disease), weighed greater than 250 pounds, were pregnant or breastfeeding, or were currently taking medication for which use of alcohol is contraindicated. Of the 240 participants enrolled, 226 had complete alcohol administration data. Of the 226, 146 had at least 2 days each of useable weekday and weekend morning sleep diary data. We set this as a minimum threshold for inclusion in the analyses in order to adequately capture the typical variations in sleep timing and duration that occur across weekdays and weekends (Wittmann et al., 2006). Two participants identified as “other race” upon completion of the full demographics questionnaire and were dropped from analyses. The final subsample for the current study is 144 (n=83 from study 1; n=61 from study 2).

The final sample was 68.1% male (n=98) with a mean age of 27.9 (SD: 4.2; range 21–35 years old). The majority of participants identified as White/European American (74.3%, n=107) and the remainder (n=37, 25.7%) identified as Black/African American. Almost half (46.5%, n = 67) had a history of ADHD in childhood.

Participants were recruited into both studies either from the community (posted fliers, Craigslist advertisements) or from the Pittsburgh ADHD Longitudinal Study (Molina, 2016). Participants recruited from the community completed a phone screen of DSM-IV ADHD symptoms from childhood and a parallel informant report was obtained over the phone to verify presence/absence of childhood ADHD. Other psychiatric illnesses (with the exception of psychotic disorders and bipolar disorder) were not included in the screener as they were not part of the eligibility criteria.

Study design

Study procedures were approved by the University of Pittsburgh’s Institutional Review Board. Participants who met eligibility criteria were randomly assigned to complete either the alcohol or control (non-alcoholic beverage where they were informed they were drinking a non-alcoholic beverage) session first. On the day of their first session, participants provided informed consent and then completed a practice Cued Go No-Go task (CGNG) prior to baseline measurements (e.g., subjective alcohol response). Within-subject sessions were scheduled approximately 1 week apart. Participants were instructed to refrain from alcohol, medications, and other drug use for 24 hours prior to both sessions. A breath alcohol test was used to verify abstinence from alcohol. Tobacco users and individuals with a prescription for ADHD stimulant medication were instructed to abstain from tobacco use/stimulant medication the day of the sessions. They were also instructed to not eat or drink any fluids other than juice or water for 8 hours prior to their session. Participants who were taking medication that was safe to use while consuming alcohol but could affect subjective or physiological assessments (e.g., pseudoephedrine) were asked to not take the medication prior to the beverage sessions.

Participants arrived at the laboratory between 11:00 AM and 1:00 PM for both beverage sessions. Approximately 30 minutes after arrival, baseline measures were taken and approximately an hour after arrival participants received a beverage. In the alcohol session participants received a dose of alcohol equivalent to 0.72 g/kg alcohol for males, 0.65 g/kg alcohol for females, designed to reach a peak blood alcohol concentration of approximately 0.075 to 0.080 mg% (Sher and Walitzer, 1986). The alcohol drinks were made using 50% alcohol (vodka) in 20% solution with cranberry juice. During the control session, participants consumed only cranberry juice and were told that they were not drinking alcohol. Participants were instructed to consume 1/3 of their beverage every 10 minutes over a 30-minute period. For both beverage sessions participants had their breath alcohol content (BrAC) taken (see Figure 3 for the means across time) and completed self-reports of subjective response prior to beverage consumption and then 5, 20, and 35 minutes after beverage completion (see Figure 4 for a depiction of beverage session protocol). Participants completed the CGNG 35 minutes after beverage completion in both sessions to assess behavioral disinhibition on the ascending limb of the blood alcohol curve. The alcohol administration session lasted approximately 5 hours since participants were required to remain in the lab until their BrAC was ≤ .02%. The non-alcohol control beverage session lasted approximately 3 hours and was identical to the alcohol session on the ascending limb of blood alcohol curve. This design allowed a direct examination of change in response that occurs from being in an unfamiliar setting and interacting with study staff. We did not examine responses on the “descending” limb on the non-alcohol session to decrease participant burden and to allow for time to complete study questionnaires (e.g., past 30-day alcohol use) without an additional visit to the lab. All participants were reimbursed $100 for the alcohol session and $50 for the control session.

Figure 3.

Figure 3

Open in a new tab

Greater variability in sleep duration associated with a greater sedation response post-alcohol consumption. Plots show predicted outcome values from models when variability in sleep duration is one standard deviation above (“high”) or below (“low”) the mean, at average levels of covariates. Average breath alcohol content (BrAC) is depicted in shadow grey.

Figure 4.

Figure 4

Open in a new tab

Protocol design for beverage sessions. BrAC=Breath alcohol content. BAES= Biphasic Alcohol Effects Scale. CGNG=Cued Go/No-Go Task.

While both beverage sessions were designed to be similar through the ascending limb of the blood alcohol curve, some specific procedures were implemented for the alcohol session to ensure participant safety and comfort. A questionnaire was administered to verify compliance with pre-session instructions, women were given a urine pregnancy test to confirm that they were not pregnant, and a low-fat meal was provided prior to alcohol consumption. BrAC and subjective response were also assessed on the descending limb of the blood alcohol curve (see Figure 4). The timing of the assessments on the descending limb were spaced out relative to the ascending limb to reduce participant fatigue. After completion of the alcohol session assessments, each participant was provided a meal and was allowed to watch TV/relax while their BrAC reached 0.02% (see procedures outlined in the NIAAA Recommended Council Guidelines on Ethyl Alcohol Administration in Human Experimentation for additional safety procedures that were used (Alcoholism, 2005).

Participants completed a 10-day ecological momentary assessment protocol (EMA; (Shiffman et al., 2008) that was initiated on Fridays following completion of each participant’s second lab-based protocol. All participants were provided instruction on how to complete the prompts (e.g., wait until done driving) on their personal smartphone or study phone. Participants received 6 prompts daily via text message with the text containing a direct link to a password protected web-based questionnaire. They could earn up to $110 for completing above 80% of the assessments. The current study utilizes data from the first prompt of the day, as this was the sole time when the previous night’s sleep was assessed.

Measures

Demographic variables.

Participants reported their sex (male=0; female=1), age, self-identified race (African American/Black=0; European American/White=1), and estimated household income (1: <$10,000 to 7: >$100,000).

Chronotype and sleep variables.

Participants were asked to report bedtimes and waketimes during every morning assessment throughout the 10-day EMA (i.e., “What time did you fall asleep last night?” and “What time did you wake up today?”), which were used to derive the sleep variables of interest. To assess sleep timing, we calculated midsleep as the halfway point between bedtime and wake time. We calculated sleep duration as the difference, in hours, between bedtime and waketime. We examined both mean midsleep and sleep duration (average over all available days) in subsequent analyses, as well as variability in midsleep and sleep duration (standard deviation over all available days).

Chronotype was assessed during the non-alcohol control beverage visit via the Composite Scale of Morningness (CSM; (Smith et al., 1989), a widely-used measure that has been validated against sleep timing, body temperature, and subjective alertness (Natale and Alzani, 2001). The score is obtained by the sum of 13 Likert-type items, and ranges from 13 (extreme eveningness preference) to 55 (extreme morningness preference). Since the CSM was only administered in Study 2, and that study only included White males (n=60); this precluded examination of sex or race differences in chronotype. Participants from this study did not differ from the 84 participants from Study 1 on any of the other study variables.

Acute alcohol response.

Subjective response to alcohol was measured using the Biphasic Alcohol Effects Scale (BAES: (Martin et al., 1993). Seven items assess stimulating effects (e.g., elated) and 7 assess sedating effects (e.g., sluggish) on a 1 (“not at all”) to 10 (“extremely”) scale. The BAES has been used to discriminate sedating and stimulating effects of alcohol in alcohol administration studies (Earleywine and Erblich, 1996).

Behavioral Disinhibition.

The Cued Go/No-Go (CGNG) task is a reaction time measure of response inhibition (see Figure 4 for timing of CGNG in the protocol). Participants are presented with either a Go (vertical rectangle) or No-Go (horizontal rectangle) cue that most often (75% of the time) signals that a corresponding target (Go target: green rectangle; No-Go target: blue rectangle) will follow. The primary outcome of interest is behavior in trials that present a Go cue followed by a No-Go target. A higher proportion of times a participant fails to inhibit pressing the button on these incongruent trials is an indicator of lower response inhibition (greater disinhibition). The CGNG is a widely-used measure of response inhibition in alcohol administration studies and is related to increased sensitivity to alcohol (Fillmore, 2003).

Alcohol use.

Alcohol use in the past 30 days was assessed with the Substance Use Questionnaire (Molina and Pelham Jr, 2003) which includes questions about alcohol use adapted from existing measures (Jessor et al., 1989, 1992). As part of the questionnaire battery following the non-alcohol session protocol, participants reported how frequently they drank alcohol (scored on an ordinal scale ranging from 0: not at all to 6: all 30 days) and the frequency of drinking 5+ drinks per day (range=0–30 days) in the past 30 days.

Data analysis

All data analyses were conducted in SPSS 24 (Corp., 2016) and R version 3.4.0 (Team, 2017). Sleep-related variables are described above. The three primary repeatedly measured laboratory alcohol outcome measures were computed as the difference between alcohol and non-alcohol control (a) stimulation and (b) sedation, measured using the BAES prior to beverage consumption and at 5-, 20-, and 35-minutes post-beverage consumption; and (c) the difference between accuracy (cued Go/No-Go behavioral disinhibition task) measured at 35-minutes post-beverage consumption in the alcohol and control conditions. We focused on the difference between alcohol and control condition to directly quantify the additional effects of alcohol on stimulation, sedation, and accuracy above and beyond what may be observed based on laboratory effects.

To test our primary hypotheses related to the effect of sleep on stimulation and sedation alcohol response, we used mixed-effects models to regress repeatedly measured stimulation and sedation on each sleep measure (summary measure of midTIB or TIB from EMA study or SMITH score), time during the lab visit (pre-drink, 5-, 20-, and 35-minutes post-drink in the lab; included as a fixed factor), and the sleep-by-time interaction. Models were also adjusted for age, sex (male or female), race (White or Black), presence/absence of ADHD history, order (alcohol or control visit first), income, and the BrAC from the alcohol condition at the respective time point (see Figure 3 for the mean BrAC at each timepoint for the full sample). In the covariance structure, we included a random intercept nested within a random study effect and autoregressive (lag 1) within-subject error structure to account for observed temporal dependency between successive observations. If the sleep-by-time interaction was not significant, we examined the main effect of sleep.

To test our primary hypothesis related to sleep and accuracy, we used mixed effects models to regress accuracy at 35-minutes post-drink on each sleep measure, adjusted for age, sex (male or female), race (White or Black), presence/absence of ADHD history, order (alcohol or control visit first), income, and the BrAC from the alcohol condition at 35 minutes. The covariance structure included a random study effect to account for potential nesting of individuals within each study.

To test our secondary hypotheses regarding moderation, we used similar models to evaluate whether race or sex moderated the association of sleep with the alcohol response variable. If an interaction with sleep was present, we performed stratified analyses to aid in interpretation.

Results

Sample characteristics and demographic differences in sleep

Sample characteristics are shown in Table 1. Male and female participants did not differ on any of the sleep variables other than mean sleep duration, with females reporting longer mean sleep durations (7.89 vs 7.37 hours; t(142)=−2.28, p=0.03). Black and White participants differed only in sleep duration variability, with Black participants reporting more variable sleep durations than White participants (1.66 vs 1.24; (t(142)=3.32, p=0.002). There were no differences in sleep or chronotype based on childhood ADHD history.

Table 1.

Sample characteristics

Measure Mean ± SD Range
Age 27.77 ± 4.20 21–35
Sex, n (%) 98 (68.0%) males/46 (31.9%) females
Race, n (%) 107 (74.3%) White/European American
37 (25.7%) Black/African American
Ethnicity, n (%) 3 (0.02%) Hispanic
ADHD history, n (%) 67 (46.5 %) ADHD/77 (53.5%) nonADHD
Alcohol use past 30 days
 Frequency of drinkinga 2.63 ± 1.42 0–5
 Frequency of 5+ drinks 2.79 ± 3.79 0–30
Sleep variables
 Midsleep, mean 4:29 ± 1:25 1:59 – 8:46
 Midsleep, variability (SD) 0:54 ± 0:28 0:10 – 2:24
 Sleep duration, mean 7h 32m ± 1h 10m 4h 50m – 13h 23m
 Sleep duration, variability (SD) 1h 21m ± 0h 43m 0h 10m – 4h 54m
Composite Scale of Morningness (CSM)b 33.53 ± 9.14 14–52
Open in a new tab

NOTE:

a

Frequency of drinking was scored on an ordinal scale: 0 = not at all; 1=1–2 days; 2 =3–5 days, 3= 6–9 days; 4 =10–19 days; 5 =20–29 days; 6= all 30 days;

b

n=60

Sleep and sensitivity to the stimulating effects of alcohol

There were no sleep-by-time interactions or main effects of sleep on the stimulating effects of alcohol. Thus, across the sample, the levels of mean midsleep, midsleep variability, mean sleep duration, and sleep duration variability were not associated with the trajectory of alcohol stimulation or the overall level of alcohol stimulation across time.

In secondary analyses, we observed a three-way interaction among mean midsleep, time, and race (X2=16.26, df=3, p=0.001; Supplemental Tables S1). This interaction indicates that the effect of midsleep on the trajectory of stimulation differed between White and Black participants. Specifically, White participants with later midsleep timing tended to have the greatest increase in stimulation from 0 to 5 minutes (β(SE) for Race*Sleep*Time (5 vs. 0) =0.41(0.16); t=2.60, p=0.010). There were no significant post-hoc interaction effects when comparing the change from either 0 to 20 or 0 to 35 minutes (p≥0.099); see Figure 1). This interpretation of the three-way interaction was confirmed in stratified analyses (Table S2). Among White drinkers only (N=107), investigation of the midsleep by time interaction (X2=14.06, df=3, p=0.003) showed that each hour of later midsleep was associated with an additional 0.25 increase in alcohol stimulation (relative to control stimulation) from 0 to 5 minutes (β=0.25, SE=0.07, t=3.47, p=0.006) but not from 0 to 20 or 0 to 35 minutes (p≥0.054). Among Black drinkers only (N=37), investigation of the midsleep by time interaction (X2=7.33, df=3, p=0.062) showed no effect of later midsleep on stimulation from 0 to 5 minutes (β=−0.15, SE=0.16, t=−0.98, p=0.331) and 0 to 20 minutes (β=−0.15, SE=0.18, t=−0.82, p=0.410). However, from 0 to 35 minutes we observed that each hour of later midsleep was associated with an additional 0.25 increase in alcohol stimulation (β=0.25, SE=0.19, t=1.27, p=0.207). The p-value for this effect was non-significant; however, because of the smaller number of Black drinkers, we focus on the magnitude of this effect, which was similar to that of the significant effect of midsleep from 0 to 5 minutes among the larger sample of White drinkers.

Figure 1.

Figure 1

Open in a new tab

Midsleep timing X race X time interaction and stimulation response post-alcohol consumption. Plots show predicted outcome values from models when midsleep timing is one standard deviation above (“Late”) or below (“Early”) the mean, at average levels of covariates.

Also in secondary analyses, we observed a two-way interaction between midsleep and sex (β=−0.29, SE=0.15, t=−2.01, p=0.046; Table S3). This interaction indicates that, relative to females (coded 2), males (coded 1) with each hour later midsleep tended to have an additional increase of 0.29 in stimulation in the alcohol session across time relative to the control session, irrespective of whether it was pre- or post-consumption. This finding was further confirmed in stratified analyses (Table S4). Among males only (N=98), each additional hour later of midsleep was associated with a 0.16 increase in stimulation in the alcohol session across time relative to control session (β=0.16, SE=0.07, t=2.23, p=0.028). However, among females only (N=46) we observed no effect of midsleep on stimulation (β=−0.07, SE=0.15, t=−0.45, p=0.651; see Figure 2).

Figure 2.

Figure 2

Open in a new tab

Midsleep timing X sex interaction and stimulation ratings. Plots show predicted outcome values from models when midsleep timing is one standard deviation above (“Late”) or below (“Early”) the mean, at average levels of covariates.

Sleep and sensitivity to the sedating effects of alcohol

We observed a sleep duration variability by time interaction (X2=9.60, df=3, p=0.022; Table S5), such that having a one-unit greater sleep duration variability was associated with a 0.62 additional increase in alcohol sedation (relative to control) from 0 to 35 minutes (β=0.62, SE=0.21, t=2.98, p=0.003; Figure 3). Variability in sleep duration did not differentiate in the trajectory of alcohol sedation from 0 to 5 or 0 to 20 (p≥0.129) We did not observe any main or interactive effects of any other sleep variables (duration, midsleep, midsleep variability) on alcohol sedation. We also did not find any interactions between any of the sleep variables and sex or race with respect to the sedating effects of alcohol.

Sleep and behavioral disinhibition

No sleep variables were associated with accuracy during incongruent trials on the CGNG, at 35-minutes post-alcohol consumption relative to 35-minutes post-non-alcohol consumption, and no interactions with sex or race were observed.

Chronotype and stimulation, sedation, and behavioral disinhibition

Among the subsample of n=60 participants with chronotype data (all White males), there was a main effect of eveningness (CSM score), such that each 1-point increase in eveningness preference (i.e., a lower CSM score) was associated with a 0.05 increase in alcohol stimulation relative to control across all time points (β=−0.05, SE=0.02, t=−2.67, p=0.010; Table S6). Eveningness was not associated with sedation ratings or behavioral disinhibition.

Discussion

Accumulating evidence suggests that the timing, duration, and variability of sleep are implicated in impulsivity, reward function, and alcohol use. The present findings are the first to examine these sleep characteristics in relation to acute response to alcohol, and secondarily, to examine potential sex and race differences in these associations. In contrast to our primary hypotheses, we did not observe associations between sleep characteristics and the stimulating effects of alcohol irrespective of sex or race. However, we did observe that greater variability in sleep duration was associated with a stronger sedating response to alcohol. Notably, our secondary analyses examining the moderating role of sex and race were more consistent with our predictions that sleep timing may correlate with the stimulating effects of alcohol. Among White drinkers (not Black drinkers) we found associations between later midsleep timing and greater sensitivity to the stimulating effects of alcohol. Furthermore, among White drinkers, this association was driven by changes occurring within the first five minutes (following completion of a 30-minute drinking period), whereas among Black drinkers, we did not observe a similar magnitude increase in stimulation until 35-minutes post-drink. We also found associations between later sleep timing and more generally increased stimulation ratings during the alcohol visit (including the pre-drink assessment) among males (but not females) and replicated among those with greater eveningness preference among White males only. That is, later sleep timing and greater eveningness preference in White males were associated with increased stimulation on the alcohol visit even prior to beverage consumption. These findings, while preliminary, have potential implications for both the prevention and treatment of alcohol problems.

We found that a more variable sleep duration was associated with greater sedation post-alcohol consumption, irrespective of sex or race. More variable sleep duration could reflect worse overall sleep adequacy and greater sleep debt, making individuals sleepier overall and thus more vulnerable to the sedating effects of alcohol (Roehrs and Roth, 2001). Notably, this association was only statistically significant at 35-minutes post-consumption (not at the earlier 5- and 20-minute time points), which could relate to a build-up of fatigue and/or sleepiness occurring throughout the laboratory session. Although more variable sleep duration is typically related to both worse sleep quality and overall functioning (e.g., Lemola et al., 2013), findings have been mixed regarding its relation to alcohol use and related problems (e.g., (Hasler et al., 2014, Pasch et al., 2010)). While experiencing increased sedation following alcohol use may be associated with decreased risk for alcohol use (e.g., (Pedersen and McCarthy, 2013), these findings may also indicate the importance of considering when alcohol administration studies are conducted during the day. The effect of alcohol appears to vary by time-of day (reviewed in (Hasler et al., 2012c), with relatively greater sedation post-alcohol at 8 AM relative to 4 PM (Roehrs et al., 1992). Thus, drinking alcohol earlier in the day, as in the current study, was related to more sedation and this may be particularly relevant for individuals with more variable sleep duration.

Time-of day effects may be relevant more broadly to the observed results. Findings from other studies suggest that time of day for measuring the subjective effects of alcohol may affect the magnitude of stimulation experienced. For example, one study reported that time-of-day influenced the relative sedating versus stimulating effects of alcohol in young adults, with greater stimulating effects in the evening (Van Reen et al., 2013). Evidence of the relatively greater stimulation included a longer latency to sleep onset, which could further delay sleep timing and potentially contribute to a positive feedback cycle in which hypersensitivity to the stimulating effects of alcohol among those with late sleep timing could maintain or exacerbate the tendency for later sleep timing, leading to more alcohol consumption.

Our novel finding that later sleep timing is associated with greater sensitivity to the stimulating effects of alcohol immediately following alcohol consumption in White participants extends prior findings that link sleep timing to altered reward responsiveness (Hasler et al., 2013, Hasler et al., 2012b, Hasler et al., 2012a, Hasler et al., 2010, Forbes et al., 2012, Randler and Saliger, 2010). Prior studies in this area have investigated predominantly White samples, largely ignoring potential race differences; our findings suggest this is an oversight that should be addressed. Later sleep timing may increase sensitivity to stimulation via altered circadian modulation of mesolimbic/dopaminergic reward circuitry (Logan et al., 2017). If so, pharmacological interventions (e.g., Naltrexone) designed to reduce the stimulating effects of alcohol via effects on dopaminergic reward processes may reduce risk in individuals identified as having later sleep timing.

Notably, later sleep timing (in males) and eveningness preference (in an analysis restricted to White males) was associated with reports of greater relative stimulation both at pre- and post-beverage consumption. Because stimulation was assessed during the alcohol session relative to the non-alcohol session, we speculate that higher pre-consumption stimulation ratings could suggest an anticipatory sensitivity to the rewarding effects of alcohol. In contrast, among White participants overall, later sleep timing was associated with increases in relative stimulation only after beverage consumption, more consistent with the consummatory (or “liking”) aspects of reward (Berridge and Robinson, 2003). While needing replication using more targeted measures of reward (e.g., Drug Effects Questionnaire in examination of alcohol response; (Morean et al., 2013), such findings add to the broader literature linking eveningess preference to altered reward function (Kang et al., 2015, Tonetti et al., 2010, Caci et al., 2004, Hasler et al., 2013) and greater endorsement of drinking motives to enhance pleasure (Digdon and Landry, 2013).

In contrast to predictions, we found no associations between sleep characteristics and acute alcohol effects on our behavioral measure of impulsivity (cued go/no-go task). This joins a mixed literature on sleep, impulsivity, and risk-taking, where the most consistent associations are found between evening chronotype and self-reported impulsivity (Kang et al., 2015, Russo et al., 2012, Caci et al., 2005, Adan et al., 2010), whereas associations between evening chronotype and behavioral measures of impulsivity have been weak (Kang et al., 2015) or nonexistent (Killgore, 2007). A similarly mixed story is observed for sleep duration, with some studies reporting that less sleep is associated with greater impulsivity and/or risk-taking (Anderson et al., 2009, Gruber et al., 2012), while others report null findings or less impulsivity and/or risk-taking (see Womack, 2013 for review). To our knowledge, our study is the first to examine how sleep is related to inhibitory control as function of alcohol consumption. Our results indicate that alcohol may not further exacerbate inhibitory control deficits for individuals with less sleep or later sleep timing.

While our multi-method design has numerous strengths, several limitations deserve mention. All reported associations should be viewed as cross-sectional. Future studies should allow for temporal precedence and consider experimental manipulations of sleep timing and/or duration to probe causal influences of sleep on alcohol response. Given that the broader aims that informed the design of Study 1 and Study 2 did not involve sleep, our sleep measures were all based on self-report, with no objective measures of sleep (e.g., wrist actigraphy) or circadian timing (e.g., dim light melatonin onset). Unlike some prior studies (Roehrs et al., 1992, Van Reen et al., 2013), we did not objectively assess daytime sleepiness via the multiple sleep latency test prior to beverage consumption, which obscures interpretation of our findings given prior evidence that basal sleepiness influences the sedating response to alcohol (Roehrs and Roth, 2001) and the possibility that those with shorter sleep duration, later sleep timing, or greater eveningness preference were more sleepy during the laboratory sessions (although evidence suggests that evening-types are not sleepier during the day overall (Rosenthal et al., 2001, Taillard et al., 1999)). Likewise, while our laboratory-based alcohol administration was a strength, it was not done at a typical drinking time. Future studies with a later start time for the alcohol administration, such as late afternoon/early evening when alcohol use peaks (Arfken, 1988), are needed. Our study also did not include an even number of females and Black drinkers compared to males and White drinkers which may have reduced our ability to detect effects and increases the importance of replication with larger subgroup sizes. Given the lack of research that examines alcohol response across race and/or sex and the average total sample size of alcohol administration studies being approximately ~ 40 participants (Quinn et al., 2011) our smaller sub groups (e.g., n = 37 Black drinkers) still contribute substantively to this literature. Lastly, by design our study did not include a placebo condition which precludes the examination of pharmacological versus expectancy effects in response to alcohol. However, our use of a non-alcohol beverage is an important first step as it does not have the limitations of placebo deception failures and allows for a true sober comparison, as opposed to a dosage-set response that occurs when people believe they have consumed alcohol (Martin et al., 1993).

Our findings may have important implications for the prevention and treatment of alcohol problems. Our findings converge with a growing literature suggesting that evening-types show altered reward function in conjunction with problematic substance use, while also identifying ways by which these associations may vary by sex and race. This suggests that assessing eveningness preference and/or actual sleep timing and considering both sex and race may be important in characterizing an overall risk profile. Given that evening chronotypes also endorse more enhancement drinking motives (Digdon and Landry, 2013), future investigations should consider how hypersensitivity to the stimulating effects of alcohol may contribute to drinking motives, and/or interact with drinking motives to further exacerbate AUD risk. Furthermore, our findings may inform the development of approaches to enhance the efficacy of treatments for AUD. For example, modifying sleep timing may diminish the stimulating effects of alcohol in White individuals, thereby reducing problematic alcohol consumption in turn. With this in mind, follow-up studies should include assessment of sleep prior to lab-based alcohol administrations, as well as experimental manipulations of sleep timing and/or duration to probe causal effects on alcohol response.

Supplementary Material

Supp TableS1-6

Acknowledgments

Sources of support: This work was supported by grants from the National Institutes of Health, including K01DA032557 (Hasler) and K01 AA021135 (Pedersen), as well as a Foundation Grant from ABMRF/The Foundation for Alcohol Research (Pedersen).

References

  1. National Household Study on Drug Abuse. Substance Abuse and Mental Health Services Administration. 1992.
  2. ADAN A 1994. Chronotype and personality factors in the daily consumption of alcohol and psychostimulants. Addiction, 89, 455–62. [DOI] [PubMed] [Google Scholar]
  3. ADAN A, NATALE V, CACI H & PRAT G 2010. Relationship between circadian typology and functional and dysfunctional impulsivity. Chronobiology International, 27, 606–19. [DOI] [PubMed] [Google Scholar]
  4. ALCOHOLISM, N. A. C. O. A. A. A. 2005. Recommended Council Guidelines on Ethyl Alcohol Administration in Hu- man Experimentation, Revised May 2005 [Online]. Available: http://www.niaaa.nih.gov/Resources/ResearchResources/job22.htm. [Accessed].
  5. ANDERSON B, STORFER-ISSER A, TAYLOR HG & ROSEN CL 2009. Associations of executive function with sleepiness and sleep duration in adolescents. Pediatrics, 123, e701–e707. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. ARFKEN CL 1988. Temporal pattern of alcohol consumption in the United States. Alcoholism: Clinical and Experimental Research, 12, 137–42. [DOI] [PubMed] [Google Scholar]
  7. BERRIDGE KC & ROBINSON TE 2003. Parsing reward. Trends in Neurosciences, 26, 507–13. [DOI] [PubMed] [Google Scholar]
  8. BROMS U, KAPRIO J, HUBLIN C, PARTINEN M, MADDEN PA & KOSKENVUO M 2011. Evening types are more often current smokers and nicotine-dependent-a study of Finnish adult twins. Addiction, 106, 170–177. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. BROWER KJ, HOFFMANN R, CONROY DA, ARNEDT JT & ARMITAGE R 2011. Sleep homeostasis in alcohol-dependent, depressed and healthy control men. European Archives of Psychiatry and Clinical Neuroscience, 261, 559–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. CACI H, MATTEI V, BAYLÉ FJ, NADALET L, DOSSIOS C, ROBERT P & BOYER P 2005. Impulsivity but not venturesomeness is related to morningness. Psychiatry research, 134, 259–265. [DOI] [PubMed] [Google Scholar]
  11. CACI H, ROBERT P & BOYER P 2004. Novelty seekers and impulsive subjects are low in morningness. European Psychiatry, 19, 79–84. [DOI] [PubMed] [Google Scholar]
  12. CORBIN WR, GEARHARDT A & FROMME K 2008. Stimulant alcohol effects prime within session drinking behavior. Psychopharmacology, 197, 327–337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. CORP., I. 2016. 24.0 ed. Armonk, NY: IBM Corp. [Google Scholar]
  14. DIGDON N & LANDRY K 2013. University students’ motives for drinking alcohol are related to evening preference, poor sleep, and ways of coping with stress. Biological Rhythm Research, 44, 1–11. [Google Scholar]
  15. EARLEYWINE M & ERBLICH J 1996. A confirmed factor structure for the Biphasic Alcohol Effects Scale. Experimental and Clinical Psychopharmacology, 4, 107. [Google Scholar]
  16. FILLMORE MT 2003. Reliability of a computerized assessment of psychomotor performance and its sensitivity to alcohol-induced impairment. Percept Mot Skills, 97, 21–34. [DOI] [PubMed] [Google Scholar]
  17. FORBES EE, DAHL RE, ALMEIDA JR, FERRELL RE, NIMGAONKAR VL, MANSOUR H, SCIARRILLO SR, HOLM SM, RODRIGUEZ EE & PHILLIPS ML 2012. PER2 rs2304672 polymorphism moderates circadian-relevant reward circuitry activity in adolescents. Biological Psychiatry, 71, 451–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. GRANT BF, GOLDSTEIN RB, SAHA TD, CHOU SP, JUNG J, ZHANG H, PICKERING RP, RUAN WJ, SMITH SM & HUANG B 2015. Epidemiology of DSM-5 alcohol use disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA psychiatry, 72, 757–766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. GRUBER R, CASSOFF J, FRENETTE S, WIEBE S & CARRIER J 2012. Impact of sleep extension and restriction on children’s emotional lability and impulsivity. Pediatrics, 130, e1155–e1161. [DOI] [PubMed] [Google Scholar]
  20. HASLER BP, ALLEN JJB, SBARRA DA, BOOTZIN RR & BERNERT RA 2010. Morningness-eveningness and depression: Preliminary evidence for the role of BAS and positive affect. Psychiatry Research, 176, 166–173. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. HASLER BP, CASEMENT MD, SITNICK SL, SHAW DS & FORBES EE 2017a. Eveningness among late adolescent males predicts neural reactivity to reward and alcohol dependence two years later. Behavioural Brain Research [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. HASLER BP, DAHL RE, HOLM SM, JAKUBCAK JL, RYAN ND, SILK JS, PHILLIPS ML & FORBES EE 2012a. Weekend-weekday advances in sleep timing are associated with altered reward-related brain function in healthy adolescents. Biological Psychology, 91, 334–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. HASLER BP, FRANZEN PL, DE ZAMBOTTI M, PROUTY D, BROWN SA, TAPERT SF, PFEFFERBAUM A, POHL KM, SULLIVAN EV, DE BELLIS MD, NAGEL BJ, BAKER FC, COLRAIN IM & CLARK DB 2017b. Eveningness and later sleep timing are associated with greater risk for alcohol and marijuana use in adolescence: Initial findings from the National Consortium on Alcohol and Neurodevelopment in Adolescence. Alcoholism: Clinical and Experimental Research, 41, 1154–1165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. HASLER BP, GERMAIN A, NOFZINGER EA, KUPFER DJ, KRAFTY RT, ROTHENBERGER SD, JAMES JA, BI W & BUYSSE DJ 2012b. Chronotype and diurnal patterns of positive affect and affective neural circuitry in primary insomnia. Journal of Sleep Research [DOI] [PMC free article] [PubMed]
  25. HASLER BP, KIRISCI L & CLARK DB 2016. Restless sleep and variable sleep timing during late childhood accelerate the onset of alcohol and drug involvement. Journal of Studies on Alcohol and Drugs, 77, 649–655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. HASLER BP, MARTIN CS, WOOD DS, ROSARIO B & CLARK DB 2014. A longitudinal study of insomnia and other sleep complaints in adolescents with and without alcohol use disorders. Alcoholism: Clinical and Experimental Research, 38, 2225–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. HASLER BP, SITNICK SL, SHAW DS & FORBES EE 2013. An altered neural response to reward may contribute to alcohol problems among late adolescents with an evening chronotype. Psychiatry Research: Neuroimaging, 214, 357–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. HASLER BP, SMITH LJ, COUSINS JC & BOOTZIN RR 2012c. Circadian rhythms, sleep, and substance abuse. Sleep Medicine Reviews, 16, 67–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. HENDLER RA, RAMCHANDANI VA, GILMAN J & HOMMER DW 2011. Stimulant and sedative effects of alcohol. Behavioral neurobiology of alcohol addiction Springer. [DOI] [PubMed] [Google Scholar]
  30. HSU C-Y, GAU SS-F, SHANG C-Y, CHIU Y-N & LEE M-B 2012. Associations between chronotypes, psychopathology, and personality among incoming college students. Chronobiology International, 29, 491–501. [DOI] [PubMed] [Google Scholar]
  31. JESSOR R, DONOVAN JE & COSTA FM 1989. Health behavior questionnaire Boulder, CO: Institute of Behavioral Science, University of Colorado. [Google Scholar]
  32. KANG JI, PARK CI, SOHN SY, KIM HW, NAMKOONG K & KIM SJ 2015. Circadian preference and trait impulsivity, sensation-seeking and response inhibition in healthy young adults. Chronobiol Int, 32, 235–41. [DOI] [PubMed] [Google Scholar]
  33. KILLGORE WD 2007. Effects of sleep deprivation and morningness-eveningness traits on risk-taking. Psychological Reports, 100, 613–26. [DOI] [PubMed] [Google Scholar]
  34. KING AC, DE WIT H, MCNAMARA PJ & CAO D 2011. Rewarding, stimulant, and sedative alcohol responses and relationship to future binge drinking. Archives of general psychiatry, 68, 389–399. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. KING AC, HASIN D, O’CONNOR SJ, MCNAMARA PJ & CAO D 2016. A prospective 5-year re-examination of alcohol response in heavy drinkers progressing in alcohol use disorder. Biological psychiatry, 79, 489–498. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. KNUTSON KL, VAN CAUTER E, RATHOUZ PJ, DELEIRE T & LAUDERDALE DS 2010. Trends in the prevalence of short sleepers in the USA: 1975–2006. Sleep, 33, 37–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. LOGAN RW, HASLER BP, FORBES EE, FRANZEN PL, TORREGROSSA MM, HUANG YH, BUYSSE DJ, CLARK DB & MCCLUNG CA 2017. Impact of sleep and circadian rhythms on addiction vulnerability in adolescents. Biological Psychiatry [DOI] [PMC free article] [PubMed]
  38. MALONE SK, PATTERSON F, LOZANO A & HANLON A 2017. Differences in morning–evening type and sleep duration between Black and White adults: Results from a propensity-matched UK Biobank sample. Chronobiology International, 1–13. [DOI] [PMC free article] [PubMed]
  39. MARTIN CS, EARLEYWINE M, MUSTY RE, PERRINE MW & SWIFT RM 1993. Development and validation of the Biphasic Alcohol Effects Scale. Alcoholism: Clinical and Experimental Research, 17, 140–6. [DOI] [PubMed] [Google Scholar]
  40. MILLER MA, WEAFER J & FILLMORE MT 2009. Gender differences in alcohol impairment of simulated driving performance and driving-related skills. Alcohol & Alcoholism, 44, 586–593. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. MOLINA BS & PELHAM WE JR 2003. Childhood predictors of adolescent substance use in a longitudinal study of children with ADHD. Journal of abnormal psychology, 112, 497. [DOI] [PubMed] [Google Scholar]
  42. MOLINA BSG, SIBLEY MH, PEDERSEN SL, & PELHAM WE 2016. The Pittsburgh ADHD Longitudinal Study. In: L H (ed.) Attention-deficit hyperactivity disorder: Adult outcomes and its predictors New York, NY: Oxford University Press. [Google Scholar]
  43. MOREAN ME, DE WIT H, KING AC, SOFUOGLU M, RUEGER SY & O’MALLEY SS 2013. The drug effects questionnaire: psychometric support across three drug types. Psychopharmacology, 227, 177–192. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. NATALE V & ALZANI A 2001. Additional validity evidence for the composite scale of morningness. Personality and Individual Differences, 30, 293–301. [Google Scholar]
  45. NEGRIFF S, DORN LD, PABST SR & SUSMAN EJ 2011. Morningness/eveningness, pubertal timing, and substance use in adolescent girls. Psychiatry Research, 185, 408–413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. NOLEN-HOEKSEMA S 2004. Gender differences in risk factors and consequences for alcohol use and problems. Clinical psychology review, 24, 981–1010. [DOI] [PubMed] [Google Scholar]
  47. O’BRIEN EM & MINDELL JA 2005. Sleep and risk-taking behavior in adolescents. Behavioral Sleep Medicine, 3, 113–33. [DOI] [PubMed] [Google Scholar]
  48. PAECH GM, CROWLEY SJ, FOGG LF & EASTMAN CI 2017. Advancing the sleep/wake schedule impacts the sleep of African-Americans more than European-Americans. PloS one, 12, e0186887. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. PASCH KE, LASKA MN, LYTLE LA & MOE SG 2010. Adolescent sleep, risk behaviors, and depressive symptoms: are they linked? American Journal of Health Behavior, 34, 237–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. PEDERSEN SL & MCCARTHY DM 2013. Differences in acute response to alcohol between African Americans and European Americans. Alcoholism: Clinical and Experimental Research, 37, 1056–1063. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. PIETERS S, VAN DER VORST H, BURK WJ, WIERS RW & ENGELS RC 2010. Puberty-dependent sleep regulation and alcohol use in early adolescents. Alcoholism: Clinical and Experimental Research, 34, 1512–8. [DOI] [PubMed] [Google Scholar]
  52. RANDLER C & SALIGER L 2010. Relationship between morningness–eveningness and temperament and character dimensions in adolescents. Personality and Individual Differences, 50, 148–152. [Google Scholar]
  53. RAY LA, BUJARSKI S & ROCHE DJ 2016. Subjective response to alcohol as a research domain criterion. Alcoholism: Clinical and Experimental Research, 40, 6–17. [DOI] [PubMed] [Google Scholar]
  54. ROEHRS T & ROTH T 2001. Sleep, sleepiness, sleep disorders and alcohol use and abuse. Sleep Medicine Reviews, 5, 287–297. [DOI] [PubMed] [Google Scholar]
  55. ROEHRS T & ROTH T 2018. Insomnia as a path to alcoholism: tolerance development and dose escalation. Sleep, 41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. ROEHRS T, ZWYGHUIZEN-DOORENBOS A, KNOX M, MOSKOWITZ H & ROTH T 1992. Sedating effects of ethanol and time of drinking. Alcoholism, Clinical and Experimental Research, 16, 553–7. [DOI] [PubMed] [Google Scholar]
  57. ROENNEBERG T, KUEHNLE T, JUDA M, KANTERMANN T, ALLEBRANDT K, GORDIJN M & MERROW M 2007. Epidemiology of the human circadian clock. Sleep Medicine Reviews, 11, 429–438. [DOI] [PubMed] [Google Scholar]
  58. ROSENTHAL L, DAY R, GERHARDSTEIN R, MEIXNER R, ROTH T, GUIDO P & FORTIER J 2001. Sleepiness/alertness among healthy evening and morning type individuals. Sleep medicine, 2, 243–248. [DOI] [PubMed] [Google Scholar]
  59. RUSSO PM, LEONE L, PENOLAZZI B & NATALE V 2012. Circadian preference and the big five: The role of impulsivity and sensation seeking. Chronobiology international, 29, 1121–1126. [DOI] [PubMed] [Google Scholar]
  60. SAXVIG IW, PALLESEN S, WILHELMSEN-LANGELAND A, MOLDE H & BJORVATN B 2012. Prevalence and correlates of delayed sleep phase in high school students. Sleep medicine, 13, 193–9. [DOI] [PubMed] [Google Scholar]
  61. SCHUCKIT MA 1984. Subjective responses to alcohol in sons of alcoholics and control subjects. Arch Gen Psychiatry, 41, 879–84. [DOI] [PubMed] [Google Scholar]
  62. SCHUCKIT MA & SMITH TL 1996. An 8-year follow-up of 450 sons of alcoholic and control subjects. Arch Gen Psychiatry, 53, 202–10. [DOI] [PubMed] [Google Scholar]
  63. SHER KJ & WALITZER KS 1986. Individual differences in the stress-response-dampening effect of alcohol: A dose-response study. Journal of Abnormal Psychology, 95, 159. [DOI] [PubMed] [Google Scholar]
  64. SHIFFMAN S, STONE AA & HUFFORD MR 2008. Ecological momentary assessment. Annual review of clinical psychology, 4, 1–32. [DOI] [PubMed] [Google Scholar]
  65. SMITH CS, REILLY C & MIDKIFF K 1989. Evaluation of three circadian rhythm questionnaires with suggestions for an improved measure of morningness. Journal of Applied Psychology, 74, 728–738. [DOI] [PubMed] [Google Scholar]
  66. SOEHNER AM, KENNEDY KS & MONK TH 2011. Circadian preference and sleep-wake regularity: associations with self-report sleep parameters in daytime-working adults. Chronobiology international, 28, 802–809. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. STAUTZ K & COOPER A 2013. Impulsivity-related personality traits and adolescent alcohol use: a meta-analytic review. Clinical psychology review, 33, 574–592. [DOI] [PubMed] [Google Scholar]
  68. TAILLARD J, PHILIP P & BIOULAC B 1999. Morningness/eveningness and the need for sleep. Journal of Sleep Research, 8, 291–5. [DOI] [PubMed] [Google Scholar]
  69. TAVERNIER R & WILLOUGHBY T 2013. Are all evening-types doomed? Latent class analyses of perceived morningness-eveningness, sleep and psychosocial functioning among emerging adults. Chronobiology International, 1–11. [DOI] [PubMed]
  70. TEAM RC 2017. R: A language and environment for statistical computing Vienna, Austria.: R Foundation for Statistical Computing. [Google Scholar]
  71. TONETTI L, ADAN A, CACI H, DE PASCALIS V, FABBRI M & NATALE V 2010. Morningness-eveningness preference and sensation seeking. European Psychiatry, 25, 111–5. [DOI] [PubMed] [Google Scholar]
  72. VAN REEN E, RUPP TL, ACEBO C, SEIFER R & CARSKADON MA 2013. Biphasic effects of alcohol as a function of circadian phase. Sleep, 36, 137–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. WEAFER J & FILLMORE MT 2008. Individual differences in acute alcohol impairment of inhibitory control predict ad libitum alcohol consumption. Psychopharmacology, 201, 315–324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. WITTMANN M, DINICH J, MERROW M & ROENNEBERG T 2006. Social jetlag: Misalignment of biological and social time. Chronobiology International, 23, 497–509. [DOI] [PubMed] [Google Scholar]
  75. WONG MM, ROBERTSON GC & DYSON RB 2015. Prospective relationship between poor sleep and substance-related problems in a national sample of adolescents. Alcoholism, clinical and experimental research, 39, 355–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. ZAPOLSKI TC, PEDERSEN SL, MCCARTHY DM & SMITH GT 2014. Less drinking, yet more problems: understanding African American drinking and related problems. Psychological bulletin, 140, 188. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp TableS1-6
NIHMS1028139-supplement-Supp_TableS1-6.docx (26.5KB, docx)

RESOURCES