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. Author manuscript; available in PMC: 2023 Dec 1.
Published in final edited form as: Addict Behav. 2022 Jul 26;135:107428. doi: 10.1016/j.addbeh.2022.107428

Pharmacodynamic Determinants of Hangover: An Intravenous Alcohol Self-Administration Study in Non-Dependent Drinkers

Bethany L Stangl 1, Emily L Vogt 2, Lauren E Blau 1, Corbin D Ester 1, Aruna Gogineni 3, Nancy Diazgranados 2, Vatsalya Vatsalya 1,4, Vijay A Ramchandani 1
PMCID: PMC9482023  NIHMSID: NIHMS1830989  PMID: 35995014

Abstract

Alcohol hangover refers to the combination of negative mental and physical symptoms that can be experienced after an episode of alcohol consumption, typically emerging as blood alcohol concentration (BAC) approaches zero. Hangover has been associated with heavy drinking and may be relevant in the transition to alcohol use disorder (AUD). Our aim was to examine hangover prevalence and associated symptoms following intravenous alcohol self-administration (IV-ASA), and to identify possible predictors of hangover in non-dependent drinkers.

Ninety-five non-dependent drinkers completed an IV-ASA session. Pharmacodynamic measures of alcohol consumption included peak and average breath alcohol concentrations. Subjective measures of alcohol response included the Drug Effects Questionnaire and Biphasic Effects of Alcohol Scale. The Alcohol Hangover Scale assessed hangover symptoms from the end of the session until the following morning.

78% of participants endorsed at least one hangover symptom following IV-ASA. There was no association between hangover scores and IV-ASA measures of alcohol consumption. Additional mediation and moderation analysis revealed that self-reported intoxication was a significant mediator of the relationship between recent drinking and hangover symptoms.

Hangover symptoms may be an early marker of the relationship between subjective response to alcohol and heavy drinking for those with no prior history of AUD. In particular, the effects of hangover go beyond exposure to alcohol and an individual’s subjective response to this exposure is associated with their experience of hangover. Future studies should further characterize the determinants of hangover across different populations of drinkers to better understand the risk for AUD and inform prevention methods.

Keywords: Alcohol, Hangover, Intravenous alcohol self-administration, Subjective Response, Non-dependent drinkers

Introduction

Hangover is a commonly occurring negative consequence, related to heavy alcohol consumption[1]. Hangover is defined as “the combination of negative mental and physical symptoms which can be experienced after a single episode of alcohol consumption, starting when blood alcohol concentration (BAC) approaches zero.”[2] Physical symptoms of hangover include: headache, thirst, tiredness, sleepiness, muscular aches, and nausea. The neuropsychological symptoms associated with hangover include dizziness, reduced alertness, and potential cognitive or mood changes along with irritability, low mood and anxiety[3–5]. Hangover has been associated with several societal consequences such as increased absenteeism, reduced productivity,[6] and impaired driving[7]. Significant correlations between hangover severity, neurocognitive performance,[8] and sustained reaction time have been established[9]. These relationships may contribute to impairment the day after intoxication, which has implications for productivity[8, 9].

Despite numerous negative consequences associated with hangover, it has received relatively little research focus. Hangover is an important area of research study given the general postulation that it is a marker for an alcohol use disorder (AUD). Frequent hangover and insensitivity to hangover among young adults have been linked to future problematic alcohol use and to the development of an AUD[10, 11]. Swift and Davidson posit that hangover susceptibility may be an early marker for individual differences in the liability to developing physical dependence on alcohol[4, 12, 13]. Withdrawal, in turn, is one of the diagnostic criteria for the presence of an AUD in the Diagnostic and Statistical Manual for psychiatric disorders DSM-5[14]. While hangover and withdrawal share similarities, they are distinct phenomena [59, 60]. Understanding the factors associated with hangover can help elucidate the mechanisms underlying the transition from alcohol consumption to the development of an AUD.

Previous research has shown that alcohol consumption patterns relate to hangover frequency and severity[11, 12, 15]. A recent publication examining hangover found a positive association between frequency and severity of hangover, along with positive associations with various drinking measures, suggesting evidence for reverse tolerance [16, 17]. Additionally, certain measures of subjective response to alcohol, including lower sensitivity to alcohol, are associated with a significant increase in risk of future AUD and may predict hangover following alcohol use[18, 19]. While these studies have examined hangover symptoms following oral consumption of alcohol, only one to our knowledge has used intravenous alcohol administration. The Computer-assisted Alcohol Infusion System (CAIS) controls breath alcohol concentration (BrAC) variation[20, 21]. By controlling such variation, all participants can achieve the same level of exposure per alcohol infusion[22, 23]. CAIS has been an effective tool showing reliability in repeated self-administration behavior as well as an accurate reflection of drinking patterns in the real-world setting[24, 25]. This system has been used to examine predictors of alcohol consumption, as well as the risk for AUD[25, 26]. Our previous work has shown mild to moderate hangover symptoms using CAIS[5]. Importantly, this method has demonstrated sensitivity to detect differences in subjective response for heavier drinkers[27, 28] and has revealed associations between subjective response[29] and alcohol expectancies with IV self-administration measures[25].

Alcohol expectancy, defined as the durable beliefs of alcohol’s effects, is an important construct in contemporary psychosocial approaches for understanding alcohol use and abuse[30] Stamates, Lau-Barraco and Linden-Carmichael identified alcohol expectancy as one potential factor that can account for the relationship between drinking experiences and drinking outcomes[31]. Individual differences are purported to exist in the expected effects of alcohol on mood and behavior[32]. Positive expectancies (e.g., tension reduction, greater sociability) have been associated with increased alcohol consumption, especially among heavier drinkers compared to lighter drinkers. While the evidence related to negative alcohol expectancies (e.g., cognitive and physical impairment) has been inconsistent,[31, 33] negative expectancies generally relate to decreased alcohol consumption[25, 34, 35]. Previous research has examined the role of both positive and negative experiences in understanding drinking behavior; however, to our knowledge, no studies have explored how expectancies may relate to hangover.

Our current study primarily examined hangover prevalence following intravenous alcohol self-administration (IV-ASA), using CAIS. We pursued analyses focused on the single item of hangover to examine potential sources of variability hypothesizing that those that achieved higher alcohol exposures during IV-ASA would report greater endorsement of hangover. We also examined the endorsement of associated symptoms of hangover using the alcohol hangover scale. Additionally, we examined potential predictors of hangover including drinking history, alcohol sensitivity, and alcohol expectancy measures in non-dependent drinkers. We expected those with heavier drinking histories and greater alcohol sensitivity and expectancies would be associated with hangover.

Methods

Participants

Male and female healthy volunteers (n=95), aged 21–45 years, were recruited under an approved clinical protocol for IV-ASA in non-treatment-seeking drinkers. The protocol was registered at clinicaltrials.gov (NCT00713492). The research approved through the NIH Institutional Review Board and conducted at the National Institutes of Health Clinical Center in Bethesda, Maryland. All participants provided written informed consent and received compensation.

Potential volunteers were brought in for a screening visit which included a medical history and physical examination, blood tests for routine blood chemistry and liver function, and urine drug screen. The Structured Clinical Interview for DSM-IV-TR (SCID) was conducted to assess for major psychiatric disorders including alcohol or substance abuse and dependence[36]. Participants seeking treatment for alcohol use, those with current or past alcohol dependence, or other past substance use disorders as determined by the SCID were excluded. Major medical problems, positive hepatitis or HIV test, or current diagnosis of psychiatric illness were basis for exclusion.

Study Session Procedures

Participants were asked to abstain from alcohol for 48 hours. Participants completed sessions individually with only the study nurse and research staff present. Upon arrival to the research unit, a breathalyzer test (Drager Alcotest 6510 plus, Drager Safety Diagnostics, Inc., Irving, TX) was performed to ensure a zero-breath alcohol concentration (BrAC). A urine sample was collected for a drug screen for all participants, and a urine beta-hCG pregnancy test for females. Both tests were required to be negative. Participants received a standardized 350 kcal metabolic meal and completed brief medical and drinking history questionnaires. An indwelling intravenous catheter was then inserted into a vein in the antecubital fossa of the non-dominant arm, using a sterile technique. This catheter was used for the alcohol infusion.

Infusion profiles were individualized for each participant based on height, weight, sex, and age, using CAIS[37]. A 6% solution of ethanol in normal saline was used. Further nuances of the IV-ASA session procedures have been previously described by other studies that employed this methodology[22, 25]. We chose this paradigm as it affords us variability in alcohol consumption allowing us to study the impact of a range of alcohol consumption levels and subjective responses on hangover prevalence.

The IV infusion session began at ~12PM with a 25-minute directed priming phase where participants were prompted to push the button four times to increase their estimated BrAC to approximately 30 mg% within 10 minutes. Following a 15-minute rest period, participants entered a 125 minute free-access phase where they could press the button whenever they chose to experience a standardized increment in BrAC[22]. Participants were told they could press the button to self-administer alcohol to levels similar to those experienced during a typical drinking episode. The button was inactivated whenever the next press would yield a BrAC increase that exceeded a preset safety limit of 100 mg%. Previous research has shown that IV alcohol self-administration behavior reflects real-world drinking behavior[25, 26].

At the end of the session, participants remained in the hospital for at least two hours after the end of the self-administration phase, or until their BrAC level fell below 20mg%, whichever occurred later. At this time, participants were debriefed and sent home in a taxi. In the next 1–2 days, the participants were contacted by phone and administered a hangover assessment (described below) for the time period from hospital discharge until 10 am the next morning.

Outcome Variables

Recent drinking history was assessed using the 90-day Timeline Followback (TLFB)[38] and the Alcohol Use Disorders Identification Test (AUDIT)[39]. TLFB measures captured drinking metrics for the past 90 days, including Total Drinks (TD90), Drinking Days (DD90), Average Drinks per Drinking Day (DPD90), and Heavy Drinking Days (HD90). AUDIT is 10-item self-report screening questionnaire used to assess alcohol consumption, drinking behaviors and alcohol-related problems. A total score of 8 or higher is considered indicative of harmful drinking behavior.

Additionally, pharmacodynamic measures of alcohol consumption obtained from the IV-ASA paradigm, included the estimated peak BrAC (mg%) during the free-access phase, estimated average BAC (mg%) during the free-access phase, number of infusions selected, and total ethanol consumed in grams (EtOH) during the session.

At the start of the study session, participants completed the self-report assessment Alcohol Effects Questionnaire (AEFQ)[40]. The AEFQ has 40 true/false statements that assess personal beliefs about the effects of alcohol on oneself, and includes eight scales. The six positive scales are called: global positivity, social and physical pleasure, sexual enhancement, power and aggression, social expressiveness, and relaxation and tension reduction. The two negative scales include cognitive and physical impairment and careless unconcern.

At baseline, during the directed priming phase (10-minute and 20-minute time points), approximately every 15 min during the infusion session, and 15 minutes post-infusion, serial subjective measures of alcohol response were collected (see study session timeline in Figure 1). The Drug Effects Questionnaire (DEQ), which measures subjective effects of certain drugs and in this study measured in-the-moment effects of alcohol on the following five items: “Do you feel drug effects?”, “Do you like drug effect?”, “Would you want more?”, “Do you feel high?”, and “Do you feel intoxicated?”[41]. The Biphasic Alcohol Effects Scale (BAES) provides scores for “Stimulation” and “Sedation”[42].

Figure 1.

Figure 1.

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Timeline of Study Session and Administration of Measures

Following the study session, the Alcohol Hangover Scale (AHS) was administered during a follow-up phone call with the participant the next day. The participant was asked to report on the items in the AHS, including hangover and associated symptoms, for the period from the participant’s release from the hospital until 10AM the next morning[43]. AHS included measures of the severity of symptoms including hangover, headache, thirsty, tired, nausea, stomach-ache, heart-racing, dizziness, and loss of appetite. All symptoms were rated on a scale of 0 (none) to 7 (incapacitating).

Data Analysis

To examine the effects of IV-ASA on hangover, the score of the individual item “hangover” from the AHS was used to separate the participants into two categorical groups, those who indicated a score greater than zero on the 7-point scale for the item of hangover (H+), and those that indicated a score of zero for the item of hangover (H−). This single item assessment of hangover of the AHS has previously been shown to be more accurate than an aggregate score of other symptoms of hangover [44]. Classification of participants using the individual hangover item enabled us to examine differences in the overall AHS scores for differences in other non-specific symptoms such as tired or thirsty. A demographic comparison of sex, race, education, and age was conducted between these two groups to evaluate any potential confounding effects of these variables on hangover symptoms. Comparison of drinking history as measured by TLFB, AUDIT, IV-ASA measures, subjective response, and AEFQ measures between H+ and H− participants was done using analysis of variance (ANOVA) while covarying for sex.

To examine sources of variability in hangover, we conducted a bivariate correlational analysis to identify select measures of subjective response, alcohol expectancies, and recent and in-session drinking behavior that may be associated with the presence and/or degree of hangover symptoms. Linear regression analysis was then performed to examine the relationship between various expectancies and subjective response measures (AEFQ, AUDIT, BAES, DEQ) and the presence of hangover as defined by the AHS.

Based on the results of these regressions, several mediation and moderation analyses were conducted in SPSS (build 1.0.0.1162) using the PROCESS macro developed for SPSS by Andrew F. Hayes (available at http://processmacro.org/index.html), to further elucidate the relationship of expectancies and subjective response with the presence of hangover following the IV-ASA session[45]. In all models, the AHS single item hangover measure was used as the dependent variable, and the total AUDIT score was used as the independent variable, as it had the strongest relationship with AHS for the H+ group in the regression analysis.

Statistical analysis was conducted using SPSS 20.0 (IBM Corporation, Chicago IL), with the level of statistical significance set at p ≤ 0.05.

Results

Participant demographics, including drinking history measures and the IV-ASA paradigm and behavior metrics, are listed in Table 1. Overall, results show that 78% of participants endorsed having at least one hangover-associated symptom on the AHS following IV-ASA. The most commonly reported items in the full sample were tired (68.4%), thirsty (58.9%) and headache (32.6%). While these symptoms are expected following unlimited alcohol consumption even in non-intravenous models, almost all measures in the hangover scale showed differences between the H+ and H− groups (Figure 2). Further analysis revealed that the H− and H+ groups were not significantly different with respect to age, sex, race, level of education, recent drinking history, positive alcohol expectancies, or in-session alcohol consumption measures (see Table 1). Although not statistically significant, average and peak BrAC as well as total ethanol self-infused (in g) were lower in the H+ group than the H− group. An independent samples t-test revealed a statistically significant difference between H+ and H− groups only for the negative AEFQ (t=2.018, p=0.046), which was higher for the H+ group than it was for the H− group.

Table 1.

Demographic and Drinking Measures for the full study sample, and for the Hangover-Positive (H+) and Hangover-Negative (H−) groups.

Total (N=95) H+ group (N=26) H− group (N=69)
Age (years) 25.5 (0.48) 25.4 (1.00) 25.5 (0.54)
Females (n, %) 44, 46.3% 10, 38.5 34, 49.3%
Race (n, % white) 57, 60% 18, 69.2% 39, 56.5%
Education 16.2 (0.20) 16.1 (0.32) 16.3 (0.25)
Recent Drinking History (90-day Timeline Followback)
Total Drinks 73.5 (4.5) 68.0 (7.7) 75.7 (5.5)
Drinking Days 24.4 (1.2) 25.2 (2.5) 24.0 (1.4)
Drinks/Drinking Day 3.1 (0.14) 2.8 (0.24) 3.2 (0.17)
Heavy Drinking Days 6.9 (0.77) 5.5 (1.4) 7.4 (0.91)
Alcohol Use Disorder Identification Test (AUDIT)
Total Score 5.5 (0.24) 5.4 (0.50) 5.5. (0.28)
Alcohol Expectancies (Alcohol Effects Questionnaire)
Positive 14.0 (0.57) 14.6 (0.98) 13.8 (0.69)
Negative 4.7 (0.27) 5.6 (0.42)* 4.4 (0.33)*
IV-Alcohol Self-Administration Consumption Measures
Average Breath Alcohol Concentration (mg%) 39.8 (2.9) 32.7 (5.2) 42.3 (3.5)
Peak Breath Alcohol Concentration (mg%) 61.7 (3.8) 54.5 (6.8) 64.2 (4.5)
Total Rewards Earned 12.7 (0.7) 13.2 (0.8) 11.3 (1.3)
Total Ethanol Consumed (g) 34.6 (21.1) 33.3 (20.1) 41.6 (25.4)
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Note: All values are Mean (S.D.) unless indicated otherwise. Heavy Drinking Days defined as days where 5+/4+ drinks were consumed by males/females.

*

significant difference between H+ and H− groups.

Figure 2.

Figure 2.

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Endorsement of Hangover Symptoms

Despite this lack of major inter-group differences, further analysis of within-group differences revealed opposing associations within the H+ compared to the H− group. A split, bivariate correlational analysis of both groups indicated that total AUDIT score was significantly correlated with the AHS hangover item (r=0.44, p<0.05), the AHS total score (r=0.69, p<0.01), and the DEQ intoxicated score (r=0.42, p<0.05) for the H+ group, while there were no significant correlations between AUDIT and any other measures for the H− group. Linear modeling of these correlations revealed that the AHS total score, AHS single item hangover measure, and DEQ intoxicated scores were significantly correlated with AUDIT scores for the H+ group, but not the H− group (see Figures 3A–C). Additionally, there was a stronger, albeit non-significant correlation between the maximum sedation item on the BAES with the AUDIT score, for the H+ compared to the H− group (see 3D).

Figure 3.

Figure 3.

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AUDIT Predicts (a) Total Post Visit Score (b) Hangover (c)Intoxication and (d) Sedation Measures

Mediation analysis revealed that Model 1 with DEQ intoxicated score as the mediator, was significant overall (R2= 0.3717, p< 0.001) (Figure 4). A direct effect of AUDIT score on hangover was not found to be significant. However, there was a significant indirect effect of AUDIT score on hangover through the DEQ intoxicated score (bootstrapped estimate of b=0.0812, 95% CI [0.011, 0.3215]). This result means that, while higher AUDIT scores alone did not predict hangover in non-dependent drinkers, the combination of higher AUDIT and DEQ intoxicated scores during IV-ASA significantly predicted hangover in this sample. Additionally, moderation analysis from Model 2 revealed a trend for a negative interaction between BAES maximum sedation and AUDIT scores in non-dependent drinkers. Individuals with higher AUDIT scores and decreased BAES sedation scores were those most likely to experience hangover following IV-ASA (ΔR2= 0.079, F1,94 = 3.771, p=0.073 (Figure 5). Although non-significant, this trend suggests that individuals with higher AUDIT scores may be more likely to experience hangover and that the relationship was weaker in individuals that also experienced increased sedation during the session. Age, sex, peak BrAC, and average BrAC were included as covariates in both these models, but none were found to be significant. However, negative alcohol expectancy was also included as a covariate in both models and had a significant covariate effect in the maximum sedation moderation model (b=−0.430, p<0.01).

Figure 4.

Figure 4.

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Intoxication Mediates the Relationship between AUDIT and Hangover

Figure 5.

Figure 5.

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Sedation Moderates the Relationship between AUDIT and Hangover

Discussion

This study provides a novel approach to examining the relationship between alcohol consumption and pharmacodynamic responses and presentation of hangover following a free-access IV-ASA paradigm. Greater drinking has been related to less intense but more frequent hangovers occurring within the same period[11, 15]. Frequency of heavy drinking has been cross-sectionally related to frequency of hangovers[12]. Maney et al. (2002) classified adolescent drinkers into high-risk or low-risk based on their self-reported engagement in binge alcohol consumption and found that high-risk drinkers were more likely to endorse having a hangover[46]. Piasecki et al. (2010) postulated that hangover propensity may be related to individual differences in alcohol response and that hangover-reactive individuals might be more sensitive to both the immediate and post-intoxication effects of consuming alcohol[12]. Furthermore, Ylikarhri et al. (1974) also stated that individuals who report hangover are prone to report greater subjective intoxication from a fixed dose of alcohol[47]. Our results indicate two potential models of hangover symptoms in non-dependent drinkers and high risk drinking as measured by the AUDIT: one with perceived intoxication mediating the relationship between risky drinking and hangover, and another with maximum sedation moderating the relationship between risky drinking and hangover. These models are the first to examine the pathway between high risk drinking and hangover using subjective response as a mediating or moderating factor.

Given that previous research has shown that subjective response to alcohol is associated with heavy drinking and predictive of AUD, results from this study suggest that hangover symptoms may be an early marker of the relationship between subjective response and AUD[17]. More specifically, this study revealed that the intoxication that the non-dependent drinkers experienced during the priming phase of IV-ASA, coupled with their drinking history, significantly predicted hangover. This result not only implicates the role of alcohol sensitivity and subjective response in mediating hangover, but also supports prior research showing that heightened sensitivity to alcohol’s effects is associated with greater sensitivity to hangover[5, 11, 12]. As sedation typically occurs later during a drinking episode, using the maximum sedation reported during the IV-ASA session was appropriate. Of note, earlier research has suggested that individuals who are family history positive for AUD or are heavier drinkers typically report lower sedation on the descending limb of a drinking episode[48–51]. Model 2, although trending, supports this research that lower reports of sedation may be an important factor to examine in transition from lighter to heavier drinking, given that our sample was non-dependent. A recent factor analysis of the Alcohol Dependence Scale (ADS) identified a three-factor solution that included a Physical Symptoms factor. The individual item of hangover in the ADS loaded onto the factor “Physical Symptoms” along with other alcohol response indicator items of withdrawal (i.e., delirium tremens). Clinical measures such as major depressive disorder and family history were predictors of this factor, supporting the role of alcohol response in AUD and that hangover may have clinical implications [58]. Additionally, the significant difference in AEFQ negative expectancies between the H+ and H− groups and the covariate effect of the AEFQ negative item in the maximum sedation model indicates that negative alcohol expectancies may also be involved in this relationship between subjective response to alcohol and subsequent hangover, which aligns with existing literature suggesting that alcohol expectancies influence alcohol use and misuse[52–55].

Hangover is important to study, as it is often the result of heavy alcohol consumption and has been shown to be a potential marker of the transition to problem drinking. These models provide insights to a behavioral mechanism underlying hangover symptoms, specifically through perceived intoxication during priming and maximum sedation during IV-ASA. These subjective response markers of hangover may offer a means to identify and prevent the transition from at-risk drinking behavior to AUD, offering potential clinical significance for diagnosis and treatment. These models also further elucidate the role of subjective response to alcohol as a means of connecting the neurobiological underpinnings of AUD to measurable behavioral metrics in non-dependent drinkers. It is noteworthy that craving was not found to be a significant predictor of hangover symptoms following IV-ASA; however, this may be because this study only examined hangover in non-dependent drinkers that had low reports of craving.

While this study revealed useful insights into the factors that inform hangover symptoms in non-dependent drinkers, there are some limitations to note. The sample size of the study did not provide us the power necessary to examine certain factors that may have been mediating or moderating the emergence of hangover symptoms following IV-ASA. Participants were not recruited prospectively based on history of hangover which likely contributed to the lower sample size of the hangover-positive group. Future studies should aim to recruit participants specifically based on hangover history to maximize statistical power to examine a broader range of factors. Another potential limitation is that the AHS was originally designed to assess acute hangover symptoms in real time, while we used it as a retrospective manner, albeit over a relatively short timeframe. Although we ideally tried to administer the AHS by the morning after the infusion session, we allowed a second day for follow-up if we were unable to make contact with the participant. As hangover is most detectable before 10AM the following morning [47], it should be noted that participants who we were unable to reach until later were recalling their symptoms. This study was comprehensive in its assessment of subjective response factors related to hangover; yet, there was no meaningful examination of biological measures related to hangover. In line with other studies that have investigated the biological basis of hangover, it would be interesting to study potential changes in liver function and other biological measures as possible markers underlying the altered subjective responses and higher prevalence of hangover in the H+ group. Interestingly, our sample did not show a relationship between alcohol consumption measures and hangover. This finding has been previously reported, for those who claim to be hangover resistant despite drinking similar amounts[56] and for social drinkers who have similar demographics[57]. Although our participants were not in a fixed alcohol challenge, we did not see significant differences in alcohol consumption, as measured by BrAC during IV-ASA, between H+ and H− groups. In tandem with our results, these findings suggest that hangover is dependent on a variety of factors and supports the importance of further studying the complexities underlying hangover in future studies.

Finally, it will be important to explore these relationships in heavier drinking populations, especially in terms of understanding the clinical significance of hangover as it relates to the progression and onset of AUD[13]. If certain components of subjective response are still predictive of hangover in heavier drinking populations, this finding could offer a mechanism for developing improved clinical diagnostics or interventions for AUD.

Hangover is an important marker that may indicate an individual’s risk of transitioning from risky drinking behavior to AUD in the future. An important key to unlocking this trajectory is sensitivity to the acute effects of alcohol. Other determinants of one’s sensitivity to alcohol, including genetics and environmental factors (e.g. alcohol expectancies), could help elucidate this relationship.

Highlights:

  • Following an intravenous alcohol self-administration human lab study in non-dependent drinkers, 78% of participants reported at least one hangover symptom on a standardized hangover assessment.

  • There was no significant association between hangover symptom scores and lab measures of alcohol consumption

  • Self-reported intoxication during the IV alcohol self-administration significantly mediated the relationship between recent drinking measures and hangover symptoms.

Acknowledgements:

This study was supported by the NIAAA Division of Intramural Clinical and Biological Research (Z1A AA000466). The authors thank Dr. Mary Lee, Dr. David T. George, Nurse Practitioners LaToya Sewell, Tonette Vinson and Yvonne Horneffer for medical support and monitoring the safety of the participants; as well as Dr. Reza Momenan for operational support. The authors would also like to thank the staff of the 5SWS day hospital and 1-SE alcohol clinic at the NIH Clinical Center. The Computer-Assisted Infusion Software (CAIS) was developed with support from Dr. Sean O’Connor, Dr. Martin Plawecki and Mr. Victor Vitvitskiy from the Indiana Alcohol Research Center, Indiana University School of Medicine (P60 AA007611). Finally, the authors are grateful and appreciative for the clinical oversight and guidance from the late Dr. Daniel Hommer.

Footnotes

Declarations of Interest: None

Conflict of Interest: None

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