Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2019 Oct 1.
Published in final edited form as: Exp Clin Psychopharmacol. 2018 Jul 23;26(5):467–475. doi: 10.1037/pha0000212

Comparison of Subjective Response to Alcohol in Caucasian and Hispanic/Latino Samples

Kailey A Richner 1, William R Corbin 1, Kyle R Menary 1
PMCID: PMC6162153  NIHMSID: NIHMS960616  PMID: 30035578

Abstract

Individual differences in subjective response (SR) to alcohol (e.g., stimulation, sedation) are a significant predictor of negative alcohol outcomes. Previous studies have reported ethnic differences in SR (e.g., between some Asian populations and Caucasians), but very few studies have examined SR among Hispanic/Latino individuals. To address this gap in the literature, the present study utilized data from a large-scale, placebo-controlled alcohol administration study to examine differences in SR between Hispanic/Latino and Caucasian individuals. Social drinkers (N = 447) aged 21 to 25 were randomized to receive either a targeted .08g% BAC dose of alcohol or placebo. Only non-Hispanic Caucasian participants (n = 234) and Hispanic/Latino participants (n = 87) were utilized in analyses. SR was assessed at baseline, on the ascending limb of the blood alcohol curve, at peak BAC, and on the descending limb. Repeated measures ANCOVA was utilized to examine interactions between beverage condition, ethnicity, and time predicting SR. The interaction between beverage condition, ethnicity, and time was significant only for low-arousal negative SR (negative sedative effects), such that Hispanic/Latino individuals experienced stronger sedative effects under alcohol (vs. placebo) compared to Caucasian individuals. Caucasians and Hispanic/Latinos showed a similar profile of response with respect to positive aspects of SR (e.g., stimulation). In summary, Hispanic/Latino individuals reported stronger negative SR to alcohol compared to Caucasian individuals, which may be protective against alcohol-related problems. However, future studies are needed to investigate why Hispanic/Latino males remain at relatively high risk for alcohol problems despite stronger negative SR relative to Caucasians.

Keywords: alcohol, subjective response, ethnicity, placebo, Hispanic/Latino

Introduction

According to the Centers for Disease Control and Prevention (2010), excessive alcohol use is associated with an average of 88,000 deaths in the United States each year. Moreover, from 1998 to 2014, non-traffic related alcohol deaths among 18 to 24 year olds increased by 21%, mainly due to alcohol poisoning (Hingson, Zha, & Smyth, 2017). When considering monetary costs, excessive alcohol use cost the United States 249 billion dollars in 2010; a 2.7% increase from 2006 (Sacks et. al, 2015). Binge drinking accounted for 76.7% of those costs alone. With the financial and societal costs of alcohol use increasing, not to mention the myriad of other related health consequences, it is important to understand the mechanisms that underlie development of alcohol use and alcohol use disorders (AUDs).

Subjective response (SR) to alcohol represents one well-established risk factor for the development of AUDs (Morean & Corbin, 2010; Trim et al., 2009). SR includes a broad range of responses to alcohol across the BAC curve (King et al., 2011; Morean & Corbin, 2010). The ascending limb of the BAC curve is associated more often with high-arousal effects (e.g., stimulation), while the descending limb is associated with low-arousal (e.g., sedative) effects (Martin et.al., 1993; Newlin & Thompson, 1990). Although subjective response varies among individuals within a particular racial/ethnic group, there are also established differences in SR across different racial/ethnic groups, and these individual differences are associated with differences in rates of AUDs across these groups. A variety of studies have examined differences in SR between Caucasians, Asians, African Americans, and Hispanics/Latinos (Pedersen et al., 2011; Pedersen & McCarthy, 2013; Schuckit et al., 2004; Duranceaux et al., 2007; Rueger et al., 2015). As an example, Rueger et al. (2015) found that a high dose (0.8 g/kg) of alcohol produced greater stimulation and sedation along with less liking of alcohol effects in heavy drinking Chinese men relative to heavy drinking Caucasian men, suggesting a potentially protective profile of subjective response among Chinese drinkers.

Compared to research in other ethnic groups, research on SR in Hispanic/Latino populations is scarce. This is an important weakness in the current empirical literature, as prior research has shown that there are higher rates of alcohol consumption, alcohol dependence, and alcohol-related mortality in some groups of Hispanic/Latino men compared to the general U.S. population (Caetano et al., 2008; Caetano, 1997; Singh and Hoyert, 2000; Stinson et al., 2001). Conversely, some evidence suggests that Hispanic/Latina women drink less than non-Hispanic Caucasian women and are at lower risk for alcohol dependence (Caetano & Kaskutas, 1995; Canino, 1994; Dawson & Grant, 1998; O’Malley & Johnston, 2002). One potential mechanism that might explain these group differences in alcohol use and alcohol-related problems is SR to alcohol. For example, perhaps Hispanic/Latino men experience stronger positive SR to alcohol compared to other groups (e.g., Caucasian men and women, Latina women), leading to greater positive reinforcement of drinking and higher risk for problems. At the same time, it is possible that Hispanic/Latina women experience weaker positive SR (e.g., less stimulation) or stronger negative SR (greater sedation) to alcohol, leading to less positive reinforcement and/or aversive reactions to drinking and lower risk for problems.

We were only able to identify one study that directly examined SR to alcohol in both Hispanic/Latino and non-Hispanic/Latino individuals. Schuckit et al. (2004) examined subjective response in participants with a positive family history of alcohol use disorders using the Subjective High Assessment Scale (SHAS; Schuckit & Gold, 1988), which primarily reflects the negative, sedating effects of alcohol (e.g., dizzy, woozy, intoxicated, etc.). The Latino sample in this study was characterized by at least one parent, grandparent, or great grandparent from Mexico, South America, or the Caribbean. More than 90% of participants identified a relative originating from Mexico, with South America as the second most common parental origin at 35%. The origin of the sample is important to consider with regard to generalizability to Hispanic individuals from other cultural backgrounds (Randolph, Stroup-Benham, Black, & Markides, 1998). When examining SR across the entire BAC curve, the authors found that there were no statistically significant differences in SHAS scores between genders or between Latinos and Caucasians. However, women had slightly higher SHAS scores on the ascending limb of the BAC curve and at peak BAC, and Latino subjects also had non-significantly higher SHAS scores at most time points compared to Caucasian subjects. These subtle differences resulted in a marginally significant (p = .07) interaction between gender, ethnicity, and time such that Latina women reported higher SHAS scores over the course of the BAC curve compared to Latino men. The authors did not directly test whether Latina women also had higher SHAS scores compared to Caucasian women and/or Caucasian men, but it seems reasonable to hypothesize that Latina women may represent a subgroup that experiences particularly strong negative alcohol effects, which could protect them from the development of alcohol related problems (at least compared to Latino men).

Given the limited research on differences in SR between Caucasian and Hispanic/Latino samples, the current study sought to comprehensively characterize and compare SR to alcohol (and placebo) in these two groups. The only prior study directly examining SR in Hispanic/Latino individuals (Schuckit et al., 2004) lacked a placebo control and focused on only one aspect of SR (negative sedative effects). Thus, the present study utilized multiple measures of SR to capture multiple dimensions of subjective effects (e.g., stimulation, sedation, relaxation, aggression) and utilized a placebo condition in order to distinguish between alcohol’s pharmacological effects and alcohol expectancies. We were unable to examine potential heterogeneity of SR within the Hispanic/Latino sample given the modest sample size and primarily Mexican-American heritage of our Hispanic sample. Based on prior studies demonstrating racial group differences in sedative alcohol response (Rueger et al., 2015; Pederson & McCarthy, 2013, Duranceaux et al., 2007) and the results of the Schuckit et al. (2004) study in a Hispanic/Latino sample, we hypothesized that Hispanic/Latino individuals would experience stronger sedative effects from alcohol (above and beyond placebo) compared to Caucasian individuals, and that this effect would be driven by Hispanic/Latina women reporting higher sedative effects compared to Hispanic/Latino men. In regard to other dimensions of subjective response (e.g., stimulation, relaxation, aggression), there was not sufficient prior research to inform clear hypotheses. Thus, although we examined the full range of SR across the BAC curve, a priori hypotheses were restricted to group differences in sedative effects of alcohol.

Method

Participants

Social drinkers aged 21 to 25 were recruited from a large southwestern university in the United States and the surrounding communities. Of the total sample (N = 447), 52.2% identified as non-Hispanic Caucasian (n = 234), and 19.4% identified as Hispanic/Latino (n = 87). Within this sample of 321, 52% (n = 166) were male. Of the 126 participants not included in analyses, 34% identified as Asian, 27% as Black or African American, 24% as “Other,” 7% as White/Caucasian (without identifying as either Hispanic or Non-Hispanic), 6% as American Indian/Alaskan Native, and the remaining 2% declined to identify their race. Two participants were not included in analyses due to extreme values for weekly drinking that were unlikely to be accurate (e.g., over 100 drinks per week). One participant in the placebo condition who believed that they did not receive any alcohol and 7 participants who did not reach a minimum BrAC of 0.06% in the alcohol condition were also excluded from analyses. The resulting sample size for analyses was 311, of which 74% (n = 229) were non-Hispanic Caucasian and 26% (n = 82) were Hispanic/Latino.

Procedure

All procedures were approved by the Human Subjects Review Board at the University in which the research was conducted (Arizona State University, protocol #1210008481, Contextual Influences on Alcohol Response and its Relation to Drinking Outcomes). Participants were first screened via a telephone screening questionnaire in order to determine preliminary eligibility. Exclusion criteria included: contraindications to consuming alcohol, current use of psychotropic or prescription pain medications, past month illicit drug use (other than marijuana), daily or near daily use of marijuana, current alcohol dependence, anxiety or mood disorder, current or past participation in an abstinence oriented treatment program, and for women, pregnancy or nursing.

After participants were determined to be eligible through a telephone screen, they were scheduled to come to the laboratory to complete interviews and surveys. At this session, participants completed the Alcohol Use Disorders and Associated Disabilities Interview Schedule-IV (AUDADIS-IV; Grant et al., 2003), the Timeline Follow-Back Interview (TLFB; Sobell & Sobell, 1992), and a series of questionnaires. Based on the AUDADIS-IV, participants who met criteria for past month alcohol dependence, anxiety disorder, or mood disorder were excused from further participation. After the interview session, eligible participants returned to the lab on a weekday at 5 p.m. to complete the alcohol challenge session. Participants were asked to refrain from consuming alcohol 24 hours prior to this session and to refrain from eating any food or consuming caffeinated products 4 hours prior.

Before participants arrived for the second session, they were randomly assigned to one of four drinking contexts: group simulated bar, group lab, solitary simulated bar, or solitary lab. The simulated bar context is a custom-built bar and lounge area that includes typical bar accoutrements such as glassware, alcohol bottles, and neon signs, and the lab condition consists of a typical office space absent of any distinctive decorations. Group contexts consisted of two to three participants drinking together, as opposed to solitary contexts where participants drank alone. Within each context, participants were randomly assigned to either the alcohol or placebo condition (see Figure 1 for the ethnic group composition by context and beverage condition). Participants who were assigned to the placebo condition were then “yoked” to a previous participant who had received alcohol in the same context so that the timing of assessments was matched across beverage condition (this was necessary because timing of some assessments was dependent upon BAC; see below). Upon arrival at the second session, participants were again confirmed to be over the age of 21 and were asked to review the consent form that they signed previously. BrAC was then tested to confirm an initial .00 g% level and female participants completed a pregnancy test and confirmed a negative result. Gender, height, and weight for each participant was recorded and this information was used to calculate appropriate alcohol dosing to achieve a peak BAC of .08g%. A weight-adjusted portion of pretzels and water were also provided to standardize stomach contents and extend the ascending limb of the BAC curve (in order to provide sufficient time for all assessments). Baseline measures of heart rate, cortisol, body sway, and SR (without reference to alcohol) were then taken.

Figure 1.

Figure 1.

Open in a new tab

Participant Distribution across Drinking Contexts

In the alcohol condition, participants were given a 1:3 ratio of 80 proof vodka to mixer (cranberry juice, lemon-lime soda, and lime juice), with alcohol and mixer amounts calculated based on age, height, weight, and gender (Curtin & Fairchild, 2003). In the placebo condition, participants were served in an identical manner, although their drink included flat tonic water rather than vodka (poured from a vodka bottle in plain view of the participant). In both conditions, glasses were rimmed with vodka and two drops of vodka from a bottle ostensibly containing lime juice were placed on the surface of each drink. Participants were served 3 drinks and had 6 minutes to consume each of the drinks, with a 1 minute rest period between each drink. At the end of the third drink, an 8-minute alcohol absorption period began. At the end of the alcohol absorption period, BrACs were taken with handheld breathalyzers every 10 minutes for the duration of the study (all research assistants were blind to beverage condition; only the supervisor taking BrACs had knowledge of the condition). Once participants BrACs reached 0.06 g% on the ascending limb, SR measures were administered. The descending SR measures were then taken when the participant’s BrAC returned to the same level as the ascending limb assessment (e.g., if ascending measures were completed at a BrAC of .066 g%, descending measures were also completed at a BrAC as close as possible to .066 g%). At the completion of all study procedures, participants were held at the lab until their BrACs were below 0.03 g%, at which time they were debriefed, paid, and given a ride home via a taxi service.

Measures

The Subjective Effects of Alcohol Scale (SEAS).

The SEAS (Morean et al., 2013) was recently developed to assess SR across the full affective space, meaning that both high-arousal and low-arousal effects are assessed, as well as positively-valenced and negatively-valenced effects. This results in four categories of subjective effects that roughly correspond to sedation (low-arousal, negatively valenced effects (LAN); dizzy, woozy, etc.), stimulation (high-arousal, positively valenced effects (HAP); lively, talkative, etc.), aggression (high-arousal, negatively valenced effects (HAN); demanding, aggressive, etc.), and relaxation (low-arousal, positively valenced effects (LAP); relaxed, calm, etc.).

Prior research has demonstrated that this measure has incremental validity in the prediction of drinking outcomes relative to other measures of SR including the BAES and the SHAS (Morean et al., 2013). For the present study the various quadrants of SR had moderate to high levels of internal consistency reliability at baseline (HAP: α = .87; HAN: α = .77; LAP: α = .82; LAN: α = .78), ascending (HAP: α = .93; HAN: α = .71; LAP: α = .85; LAN: α = .83), peak (HAP: α = .94; HAN: α = .79; LAP: α = .86; LAN: α = .91), and descending (HAP: α = .95; HAN: α = .78; LAP: α = .91; LAN: α = .92).

Timeline Follow-Back (TLFB).

Frequency and quantity of alcohol use over the past 30 days was assessed using the Timeline Follow-Back (TLFB) interview (Sobell & Sobell, 1992). Total number of binge episodes (4 drinks on a single occasion for women, 5 drinks on a single occasion for men) in the past 30 days was utilized as a covariate in analyses. The TLFB has been shown to be valid and highly reliable for assessing recent alcohol use in college students (Sobell et al., 1986; Pedersen et al., 2012).

Data Analysis

Distributions of all variables were examined before conducting primary analyses and variables were transformed as necessary to normalize distributions. To evaluate ethnic group differences in SR, we used repeated measures ANCOVA with beverage condition (alcohol vs. placebo) and ethnicity (non-Hispanic Caucasian vs. Hispanic/Latino) as between subject factors, and time (ascending limb, peak BAC, and descending limb) as a within subject factor. Baseline SR, gender, and past-month binge drinking were included as covariates in all models. Drinking context, which was experimentally manipulated as part of the larger study, was also included as a covariate in all analyses using dummy codes for both social context (0 = solitary contexts, 1 = group contexts) and physical context (0 = laboratory contexts, 1 = bar contexts).

Primary hypotheses were concerned with potential three-way interactions between beverage condition, ethnicity, and time, and potential two-way interactions between beverage condition and ethnicity predicting SR. A significant three-way interaction would indicate that subjective response to alcohol (relative to placebo) differs by ethnicity, and that the magnitude of the ethnic group difference in alcohol response varies across the BAC curve. A significant two-way interaction between beverage condition and ethnic group would indicate that ethnic group differences in subjective response to alcohol (relative to placebo) do not differ as a function of timing across the BAC curve.

If a significant three-way interaction was found, it was decomposed by examining the two-way interaction between beverage condition and ethnicity at each time-point (ascending, peak, and descending). If no significant three-way interaction was found in the repeated measures ANCOVA, two-way interactions between beverage condition and ethnicity (collapsed across all time-points) were examined.

Finally, to test our secondary hypothesis that ethnic differences in subjective response (specifically, sedative effects) would be driven by Hispanic/Latina women reporting particularly strong sedative effects under alcohol (vs. placebo), if we obtained a significant interaction predicting SR, we ran additional analyses examining the time by gender by beverage condition interaction predicting SR within each ethnic group.

Results

Preliminary Analyses

SEAS subscale scores and blood alcohol levels (BACs) by beverage condition and ethnicity are shown for each timepoint in Table 1. The HAN and LAN subscales of the SEAS were log transformed at every timepoint due to non-normality (high positive skew). To ensure that our placebo manipulation achieved the desired effect, we examined perceived number of drinks consumed and perceived BAC by beverage condition. Participants in the alcohol condition believed that they had consumed 3.35 (SD = 1.06) alcoholic drinks compared to 2.67 (SD = 1.13) in the placebo condition, representing an 80% placebo response. For estimated BAC, participants in the alcohol condition reported a mean of .068 (SD = .022) relative to .046 (SD = .024) in the placebo condition for a 68% placebo response. Thus, there was strong evidence for the effectiveness of the placebo manipulation. Finally, total number of binge drinking episodes (4 drinks in one occasion for women, 5 drinks in one occasion for men) in the last 30 days was examined by ethnic group. Caucasian participants reported more binge drinking occasions in the past month (M = 4.0, SD = 3.47) compared to Hispanic/Latino participants (M = 3.32, SD = 2.55), though this difference was not statistically significant (F(1,309) = 2.69, p = .10). Nonetheless, to ensure this small difference did not affect results, we included binge drinking (also log-transformed due to non-normality) as a covariate in all analyses.

Table 1.

Descriptives and Subjective Response Means by Beverage Condition and Ethnic Group

Non-Hispanic Caucasian (N = 229) Hispanic/Latino (N = 82)
Alcohol (n = 134)
M (SD)		 Placebo (n = 95)
M (SD)		 Alcohol (n = 48)
M (SD)		 Placebo (n = 34)
M (SD)
Gender (% Male) 47% 55.8% 60.4% 50%
Ascending BAC (g%) .069 (.011) .00 .069 (.007) .00
Peak BAC (g%) .079 (.013) .00 .083 (.012) .00
Descending BAC (g%) .067 (.009) .00 .069 (.008) .00
Baseline HAP 4.64 (1.97) 4.44 (1.10) 4.92 (2.03) 4.55 (1.84)
Baseline HAN 0.38 (0.93) 0.39 (1.05) 0.33 (0.67) 0.48 (0.95)
Baseline LAP 6.99 (1.57) 7.25 (1.53) 7.21 (1.74) 6.64 (1.44)
Baseline LAN 0.06 (0.20) 0.07 (0.20) 0.13 (0.40) 0.25 (1.02)
Ascending HAP 6.16 (2.10) 4.67 (2.16) 6.51 (2.09) 4.61 (2.12)
Ascending HAN 0.60 (1.12) 0.26 (0.63) 0.52 (1.04) 0.27 (0.59)
Ascending LAP 6.57 (1.97) 6.66 (1.82) 7.22 (1.83) 6.18 (1.55)
Ascending LAN 1.44 (1.60) 0.65 (0.94) 1.91 (2.11) 0.74 (1.37)
Peak HAP 5.24 (2.11) 4.06 (2.29) 5.80 (2.14) 4.32 (1.75)
Peak HAN 0.50 (0.98) 0.22 (0.60) 0.60 (1.08) 0.21 (0.55)
Peak LAP 6.38 (1.79) 6.16 (1.90) 6.88 (2.00) 6.02 (1.79)
Peak LAN 1.00 (1.47) 0.42 (0.78) 1.81 (2.02) 0.43 (1.16)
Descending HAP 4.56 (2.30) 3.58 (2.28) 5.02 (2.27) 3.75 (2.06)
Descending HAN 0.48 (1.10) 0.27 (0.74) 0.35 (0.66) 0.14 (0.34)
Descending LAP 6.29 (2.05) 6.18 (2.28) 6.62 (2.05) 5.90 (1.62)
Descending LAN 0.66 (1.17) 0.19 (0.56) 1.21 (1.78) 0.26 (0.72)
Open in a new tab

Note: Range of SEAS scores is 0–10.

Effects of Ethnicity and Beverage Condition on SEAS Scores

SEAS HAP (Stimulation) Effects.

The three-way interaction between beverage, ethnicity, and time predicting HAP effects was not significant (F(2,299) = .076, p = .93), nor was the two-way interaction between beverage condition and ethnicity (F(1,300) = .155, p = .69). See Figure 2 for a depiction of the non-significant three-way interaction. The main effect of beverage condition was significant (F(1,300) = 45.3, η2 = .131, p < .001), indicating stronger HAP SR under alcohol across all participants. There was no significant main effect of ethnicity on HAP SR (F(1,300) = .676, p = .41).

Figure 2.

Figure 2.

Open in a new tab

High Arousal Positive (HAP) Subjective Response in Caucasians and Hispanic/Latinos

SEAS HAN (Aggression) Effects.

The three-way interaction between beverage, ethnicity, and time predicting HAN effects was not significant (F(2,298) = .632, p = .53), nor was the two-way interaction between beverage condition and ethnicity (F(1,299) = .084, p = .77). See Figure 3 for a depiction of the non-significant three-way interaction. The main effect of beverage condition was significant (F(1,299) = 13.15, η2 = .042, p < .001), indicating stronger HAN effects under alcohol across all participants. There was no significant main effect of ethnicity on HAN SR (F(1,299) = .182, p = .67).

Figure 3.

Figure 3.

Open in a new tab

High Arousal Negative (HAN) Subjective Response in Caucasians and Hispanic/Latinos

SEAS LAP (Relaxation) Effects.

The three-way interaction between beverage, ethnicity, and time predicting LAP effects was not significant (F(2,299) = .713, p = .49), nor was the two-way interaction between beverage condition and ethnicity (F(1,300) = .435, p = .51). See Figure 4 for a depiction of the non-significant three-way interaction. The main effect of beverage condition was significant (F(1,300) = 4.633, η2 = .015, p = .032), indicating stronger HAN effects under alcohol across all participants. There was no significant main effect of ethnicity on HAP SR (F(1,300) = 1.468, p = .23).

Figure 4.

Figure 4.

Open in a new tab

Low Arousal Positive (LAP) Subjective Response in Caucasians and Hispanic/Latinos

SEAS LAN (Sedation) Effects.

As hypothesized, the three-way interaction between beverage, ethnicity, and time predicting LAN effects was statistically significant (F(2,298) = 3.761, η2 = .025, p = .024). Visual inspection of the interaction, which is plotted in two panels in Figure 5, suggests both ethnic groups experience stronger LAN SR under alcohol compared to placebo, but Hispanic/Latino individuals experienced stronger LAN SR under alcohol compared to non-Hispanic/Caucasian individuals. In order to fully decompose this interaction, we examined the two-way interaction between ethnicity and beverage condition at each timepoint following beverage consumption: ascending, peak, and descending. This analysis revealed that the ethnicity by beverage condition interaction was significant at peak BAC (F(1,300) = 4.929, η2 = .016, p = .027), but not on the ascending limb (F(1,300) = .214, p = .644) or the descending limb (F(1,301) = 1.18, p = .28). Thus, although sedative effects of alcohol (relative to placebo) tended to be larger for Hispanic/Latino relative to Caucasian participants, the magnitude of this difference was greatest at peak BAC. In order to characterize the magnitude of the ethnic group difference in LAN SR at peak BAC, we examined the main effect of beverage condition at this timepoint within each ethnic group. Results showed that the effect of beverage condition on peak LAN SR was more than twice as large among Hispanic/Latino participants (F(1,74) = 14.771, η2 = .166, p < .001) relative to non-Hispanic Caucasian participants (F(1,221) = 15.355, η2 = .065, p < .001).

Figure 5.

Figure 5.

Open in a new tab

Low Arousal Negative (LAN) Subjective Response in Caucasians and Hispanic/Latinos

Finally, to determine whether this interaction was driven primarily by Hispanic/Latina women reporting particularly strong LAN SR under alcohol, we examined the three-way interaction between gender, beverage condition, and time as well as the two-way interaction between gender and beverage condition within the Hispanic/Latino sample. Neither interaction was significant (three-way: F(2,72) = 1.052, p = .35, two-way: F(1,73) = .015, p = .90), indicating that the greater LAN effects observed under alcohol among Hispanic/Latino individuals were common to both genders, and the overall ethnic group differences were not driven by Hispanic/Latina women reporting particularly strong LAN SR under alcohol.

Discussion

The current study focused on differences in subjective response to alcohol (SR) between two ethnic groups: non-Hispanic Caucasians and Hispanics/Latinos. This is an important contribution given the relative lack of prior studies examining SR in Hispanic/Latino samples. Beyond the understudied topic, strengths of the current study relative to many prior studies include the use of a strong placebo control and assessment of SR across the full affective space. Prior studies of racial/ethnic group differences in SR have not examined either high-arousal, negatively valenced effects (e.g., aggression) or low-arousal, positively valenced effects (e.g., relaxation).

Interestingly, ethnic group differences in the current study were restricted to low arousal, negatively valenced effects (e.g., sedation) with stronger LAN effects observed among Hispanic/Latino participants relative to non-Hispanic Caucasians. Overall, the findings suggest that there are more similarities than differences in SR between Hispanics and non-Hispanic Caucasians (most of the interaction effects were not significant). Although ethnic group differences in SR were limited to sedation, this particular aspect of SR represents a robust risk factor for later heavy drinking and related problems (Schuckit, 1994, King et al., 2011).

Our hypothesis that ethnic differences in SR would be driven by Hispanic/Latina women reporting especially strong sedative effects was not supported. Although it is possible that we failed to find support for this hypothesis due to insufficient power to detect a three-way interaction, the two-way interaction between beverage condition and gender was very small within the Latino sample. Thus, any such interaction may be relatively small in magnitude even if it could be detected in a larger sample. This suggests that, at least within the current sample, Hispanic/Latino individuals as a group demonstrated a pattern of subjective response (stronger sedative effects) that has been consistently linked to a lower risk for later binge drinking and alcohol-related problems (e.g., Schuckit, 1994; King et al., 2011).

Although prior research has shown that Hispanic/Latina women drink less and are at lower risk for alcohol problems compared to Caucasian women (Caetano & Kaskutas, 1995; Canino, 1994; Dawson & Grant, 1998; O’Malley & Johnston, 2002), Hispanic/Latino men tend to drink just as much as Caucasian men (Caetano & Clark, 1998) with higher rates of alcohol dependence in some Hispanic/Latino men compared to the general U.S. population (Caetano et al., 2008). The absence of differential sensitivity to sedative alcohol effects by gender and the presence of gender differences in drinking within Hispanic/Latino populations suggests that other factors may “override” protection provided by a strong sedative response to alcohol among Hispanic/Latino males, a notion that is supported by recent studies. For example, Ceballos et al. (2012) reported greater positive alcohol expectancies among male Latino college students compared to female Latina college students. Along similar lines, Corbin et al. (2008) found that male Latino college students reported greater perceived drinking among peers compared to female Latina students, and greater perceived peer drinking was associated with more individual drinking and more permissive values regarding drinking.

While gender differences in drinking norms and expectancies are certainly not exclusive to Hispanic/Latino populations (e.g., Iwamoto et al., 2014), at least one study has found that gender differences in these constructs are larger among Hispanic/Latino individuals compared to Caucasians (Corbin et al., 2008), lending credence to the idea that these factors may override protection afforded by a low-risk SR profile in Hispanic/Latino men, putting them at greater risk for heavy drinking and alcohol-related problems compared to Hispanic/Latina women and other ethnic groups. However, it is important to note that gender differences within Hispanic/Latino samples may depend on other cultural factors. For example, while acculturation is consistently associated with increased risk for heavy drinking in women, effects are less consistent in men (Zemore, 2007), which may result in a closing of the gender gap among highly acculturated Latinos in the US. There are also important differences by nationality, with much larger gender differences in drinking among Mexican-Americans, relative to Puerto Rican- and Cuban-Americans (Ramisetty-Mikler, Caetano, & Rodriguez, 2010). Thus, it may be important to understand factors related to particular sub-groups of Latinos (e.g., culturally specific norms) when examining gender differences in drinking behavior.

A related question that the present study did not address involves mechanisms underlying differential subjective response in Hispanic/Latino individuals compared to Caucasian individuals. Although cultural differences between Hispanic and non-Hispanic Caucasians might well impact expectancies regarding alcohol effects, presumably they would not impact alcohol’s pharmacological effects, and the use of a placebo control in the current study should address any group differences in expectancies. One possibility is that the ethnic group differences are due, at least in part, to differential alcohol exposure either across development or during critical developmental periods. Although our analyses controlled for past 30 day drinking, this does not rule out the possibility that Caucasian and Hispanic/Latino participants differed in important ways in alcohol exposure at earlier time-points. Another possibility is that greater sedative effects of alcohol among Hispanic/Latino individuals are due to genetic differences, perhaps in alcohol-metabolizing genes as has been found in some Asian populations (e.g., Eng et al., 2007, Luczak et al., 2006). In fact, one study found that the allele of the ALDH2 gene that protects against alcoholism in Asian populations had a very low frequency in a Mexican American sample, and there were other genes related to alcohol metabolism and neurotransmission that uniquely predicted risk for alcoholism in this population (Konishi et al., 2004). Thus, if additional studies replicate the pattern of SR observed among Hispanic participants in the current study, it will be important to examine potential genetic underpinnings of this response. Again, such efforts will need to pay careful attention to potential sub-group differences within Latino samples, as genetic factors may differ substantially by nationality. For example, among Asian populations, both alcohol metabolizing genes and SR differ considerably between individuals of Korean and Chinese origin (Duranceaux et al., 2007).

Although the results of the present study provide important new information about subjective response to alcohol among Hispanics/Latinos, there are several limitations that must be acknowledged. In the current sample, males were overrepresented across the ethnic groups. The sample size of the Hispanic/Latino group was also modest, though it was similar to or larger than many prior studies of ethnic group differences in SR (e.g., Schuckit et al., 2004). The specific sample of Hispanics/Latinos in the current study was primarily Mexican American. Thus, as discussed previously, it is possible that results would not generalize to Hispanic/Latino young adults with different cultural backgrounds. In addition, participants were largely college students (79%). Because college students tend to drink more heavily than non-college age-matched peers (Dawson et al., 2004), results might not generalize to other young adults, though the students and non-students did not significantly differ in typical alcohol use in our sample, and typical drinking was included as a covariate in the analyses. Finally, the current study included manipulations of drinking context. Although we controlled for drinking context in the analyses, the sample size was not sufficient to examine potential interactions between beverage, context, and ethnicity. Moreover, because some participants were nested within groups (group bar and group lab), it is possible that group level dynamics effected SR, and that such group effects differed by ethnicity. In sum, future studies of SR in Hispanic/Latino samples need to include larger samples of women and include a broader range of Hispanic/Latino cultures (e.g., South American, Cuban, Puerto Rican). Examining potential gender differences may also be important in understanding the role of SR in determining drinking behavior in different Latino subgroups.

In sum, the present study provides the first empirical data regarding differences in the full range of SR between Hispanic/Latino individuals and Caucasian individuals. Group differences were restricted to low-arousal, negatively valenced subjective effects (e.g., sedation), with stronger effects reported by Hispanics/Latinos. Although this pattern of response should protect against heavy drinking, studies of drinking behavior do not find lower risk for negative outcomes among Hispanic/Latino males in particular, suggesting that other factors may override the potential protection provided by negative SR for this group. Future studies are needed to understand potential gender differences in SR among Hispanics/Latinos and environmental or cultural variables that may override effects of these individual differences.

Public Significance Statement.

Hispanic/Latino individuals reported stronger negative sedating effects (e.g., dizziness) after consuming alcohol compared to Caucasian individuals. While these results suggest that Hispanic/Latino individuals ought to be somewhat protected from heavy drinking and alcohol-related problems due to a more negative response to alcohol, other studies have found that Hispanic males have elevated rates of alcohol-related problems compared to Caucasian males. Further studies are needed to identify other factors (e.g., expectancies) that may override the protection that is provided by a more negative subjective response to alcohol among Latino men.

REFERENCES

  1. Caetano R, Tam T, Greenfield T, Cherpitel C, & Midanik L (1997). DSM-IV alcohol dependence and drinking in the US population: a risk analysis. Annals of Epidemiology, 7(8), 542–549. [DOI] [PubMed] [Google Scholar]
  2. Caetano R, Clark CL (1998). Trends in alcohol consumption patterns among Whites, Blacks, and Hispanics: 1984 and 1995. Journal of Studies on Alcohol, 59, 659–668. [DOI] [PubMed] [Google Scholar]
  3. Caetano R, Kaskutas LA (1995). Changes in drinking patterns among whites, blacks and Hispanics, 1984–1992. Journal of Studies on Alcohol, 59, 558–565. [DOI] [PubMed] [Google Scholar]
  4. Caetano R, Ramisetty-Mikler S, Rodriguez LA (2008). The Hispanic Americans Baseline Alcohol Survey (HABLAS): rates and predictors of alcohol abuse and dependence across Hispanic national groups. Journal of Studies on Alcohol and Drugs, 69, 441–448. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Canino G (1994). Alcohol use and misuse among Hispanic women: Selected factors, processes, and studies. International Journal of the Addictions, 29(9), 1083–1100. [DOI] [PubMed] [Google Scholar]
  6. Ceballos NA, Czyzewska M, Croyle K (2012). College drinking among Latinos (as) in the United States and Mexico. American Journal of Addiction, 6, 544–549. [DOI] [PubMed] [Google Scholar]
  7. Centers for Disease Control and Prevention. (2010). Alcohol and public health: Data and maps. Retrieved from: https://www.cdc.gov/alcohol/data-stats.htm.
  8. Corbin WR, Vaughan EL, Fromme K (2008). Ethnic differences and the closing of the sex gap in alcohol use among college-bound students. Psychology of Addictive Behaviors, 22, 240–248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Curtin JJ, Fairchild BA (2003). Alcohol and cognitive control: Implications for regulation of behavior during response conflict. Journal of Abnormal Psychology, 112, 424–436. [DOI] [PubMed] [Google Scholar]
  10. Dawson DA, & Grant BF (1998). Family history of alcoholism and gender: their combined effects on DSM-IV alcohol dependence and major depression. Journal of Studies on Alcohol, 59, 97–106. [DOI] [PubMed] [Google Scholar]
  11. Dawson DA, Grant BF, Stinson FS, & Chou PS (2004). Another look at heavy episodic drinking and alcohol use disorders among college and non-college youth. Journal of Studies on Alcohol, 65, 477–488. [DOI] [PubMed] [Google Scholar]
  12. Duranceaux NC, Schuckit MA, Luczak SE, Eng MY, Carr LG, & Wall TL (2007). Ethnic Differences in Level of Response to Alcohol Between Chinese Americans and Korean Americans. Journal of Studies on Alcohol and Drugs, 69, 227–234. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Eng MY, Luczak SE, Wall TL (2007). ALDH2, ADH1B, and ADH1C genotypes in Asians: A literature review. Alcohol, Research, & Health, 30, 22–27. [PMC free article] [PubMed] [Google Scholar]
  14. Grant BF, Dawson DA, Stinson FS, Chou PS, Kay W, Pickering R (2003). The Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV (AUDADIS-IV): reliability of alcohol consumption, tobacco use, family history of depression and psychiatric diagnostic modules in a general population sample. Drug and Alcohol Dependence, 71, 7–16. [DOI] [PubMed] [Google Scholar]
  15. Hingson R, Zha W, & Smyth D (2017). Magnitude and trends in heavy episodic drinking, alcohol impaired driving, and alcohol related mortality and overdose hospitalizations among emerging adults of college ages 18–24 in the United States, 1998–2014. Journal of Studies on Alcohol and Drugs, 78(4), 540–548. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Iwamoto DK, Corbin W, Lejuez C, MacPherson L (2014). College men and alcohol use: Positive alcohol expectancies as a mediator between distinct masculine norms and alcohol use. Psychology of Men & Masculinity, 15, 29–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. King AC, de Wit H, McNamara PJ, Cao D (2011). Rewarding, stimulant, and sedative alcohol response and relationship to future binge drinking. Archives of General Psychiatry, 68, 389–399. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Konishi T, Luo HR, Calvillo M, Mayo MS, Lin KM, & Wan YJ (2004). ADH1B*1, ADH1C*2, DRD2 (−141C Ins), and 5-HTTLPR are associated with alcoholism in Mexican American men living in Los Angeles. Alcoholism: Clinical and Experimental Research 28, 1145–1152. [DOI] [PubMed] [Google Scholar]
  19. Luczak SE, Glatt SJ, Wall TL (2006). Meta-Analyses of ALDH2 and ADH1B with alcohol dependence in Asians. Psychological Bulletin, 132, 607–621. [DOI] [PubMed] [Google Scholar]
  20. 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, 140–146. [DOI] [PubMed] [Google Scholar]
  21. Morean ME, Corbin WR (2010). Subjective response to alcohol: A critical review of the literature. Alcoholism: Clinical and Experimental Research, 34, 385–395. [DOI] [PubMed] [Google Scholar]
  22. Morean ME, Corbin WR, Treat TA (2013). The Subjective Effects of Alcohol Scale: Development and psychometric evaluation of a novel assessment tool for measuring subjective response to alcohol. Psychological Assessment, 25, 780–795. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Newlin DB, Thomson JB (1990). Alcohol challenge with sons of alcoholics: A critical review and analysis. Psychological Bulletin, 108, 383–402. [DOI] [PubMed] [Google Scholar]
  24. O’Malley PM, & Johnston LD (2002). Epidemiology of alcohol and other drug use among American college students. Journal of Studies on Alcohol, Supplement, (14), 23–39. [DOI] [PubMed] [Google Scholar]
  25. Pedersen ER, Grow J, Duncan S, Neighbors C, & Larimer ME (2012). Concurrent validity of an online version of the timeline followback assessment. Psychology of Addictive Behaviors, 26(3), 672–677. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Pedersen SL, Treloar HR, Burton CM, McCarthy DM (2011). Differences in implicit associations about alcohol between Blacks and Whites following alcohol administration. Journal of Studies on Alcohol and Drugs, 72, 270–278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. 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]
  28. Ramisetty-Mikler S, Caetano R, & Rodriguez LA (2010). The Hispanic Americans Baseline Alcohol Survey (HABLAS): Alcohol consumption and sociodemographic predictors across Hispanic national groups. Journal of Substance Use, 15, 402–416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Randolph WM, Stroup-Benham C, Black SA, & Markides KS (1998). Alcohol use among Cuban-Americans, Mexican-Americans, and Puerto Ricans. Alcohol Research and Health, 22, 265–269. [PMC free article] [PubMed] [Google Scholar]
  30. Rueger SY, Hu H, McNamara P, Cao D, Hao W, King AC (2015). Differences in subjective response to alcohol in heavy and light-drinking Chinese men versus Caucasian American men. Addiction, 110, 91–99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Sacks JJ, Gonzales KR, Bouchery EE, Tomedi LE, Brewer RD (2015). 2010 National and state costs of excessive alcohol consumption. American Journal of Preventive Medicine, 49, e73–e79. [DOI] [PubMed] [Google Scholar]
  32. Schuckit MA (1994). Low level of response to alcohol as a predictor of future alcoholism. The American Journal of Psychiatry, 151, 184–189. [DOI] [PubMed] [Google Scholar]
  33. Schuckit MA, Gold EO (1988). A simultaneous evaluation of multiple markers of ethanol/placebo challenges in sons of alcoholics and controls. Archives of General Psychiatry, 45, 211–216. [DOI] [PubMed] [Google Scholar]
  34. Schuckit MA, Smith TL, Kalmijn J (2004). Findings across subgroups regarding the level of response to alcohol as a risk factor for alcohol use disorders: A college population of women and Latinos. Alcoholism: Clinical and Experimental Research, 28, 1499–1508. [DOI] [PubMed] [Google Scholar]
  35. Singh GK, & Hoyert DL (2000). Social epidemiology of chronic liver disease and cirrhosis mortality in the United States, 1935–1997: trends and differentials by ethnicity, socioeconomic status, and alcohol consumption. Human Biology, 72, 801–820. [PubMed] [Google Scholar]
  36. Sobell LC, Sobell MB (1992). Timeline follow-back In Measuring alcohol consumption (pp. 41–72). Humana Press. [Google Scholar]
  37. Sobell MB, Sobell LC, Klajner F, Pavan D, & Basian E (1986). The reliability of a timeline method for assessing normal drinker college students’ recent drinking history: Utility for alcohol research. Addictive Behaviors, 11(2), 149–161. [DOI] [PubMed] [Google Scholar]
  38. Stinson FS, Grant BF, & Dufour MC (2001). The critical dimension of ethnicity in liver cirrhosis mortality statistics. Alcoholism: Clinical and Experimental Research, 25, 1181–1187. [PubMed] [Google Scholar]
  39. Trim RS, Schuckit MA, Smith TL (2009). The relationships of the level of response to alcohol and additional characteristics of alcohol use disorders across adulthood: a discrete-time survival analysis. Alcoholism: Clinical and Experimental Research, 33, 1562–1570. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Zemore SE (2007). Acculturation and alcohol among Latino adults in the United States: a comprehensive review. Alcoholism: Clinical and Experimental Research, 31, 1968–1990. [DOI] [PubMed] [Google Scholar]

RESOURCES