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. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: J Dual Diagn. 2024 Mar 12;20(2):99–110. doi: 10.1080/15504263.2024.2325531

Evaluating Alcohol Use Severity in Terms of Cigarette Smoking-Related Processes and Anxiety/Depression Among Adult Latinx Smokers

Michael J Zvolensky 1,2,3, Justin M Shepherd 1, Bryce K Clausen 1, Brooke Y Redmond 1, Marcel de Dios 3,4, Miguel Ángel Cano 5
PMCID: PMC11021163  NIHMSID: NIHMS1978224  PMID: 38471033

Abstract

Objective.

Although empirical work focused on smoking-drinking comorbidity among Latinx persons is growing, no work has explored the relation between alcohol use severity in terms of co-occurring smoking processes and mental health. Therefore, the present investigation aimed to explore the prevalence and role of alcohol use severity in relation to clinically significant tobacco and mental health problems among English-speaking Latinx adults who smoke cigarettes.

Methods.

Participants included 338 English-speaking Latinx adults who smoked cigarettes daily (Mage = 35.5 years; SD = 8.65; age range 18-61; 37.3% female).

Results.

Results indicated that approximately 68% of male and 61% of female smokers scored above established clinical cutoffs for hazardous and harmful alcohol use and possible alcohol dependence. Moreover, alcohol use severity was associated with increased risk for cigarette dependence, perceived barriers for quitting, and more problematic symptoms when trying to quit. Alcohol use severity was also related to more severe anxiety and depressive symptoms.

Conclusions.

Overall, the current findings suggest that intervening to reduce alcohol use severity may be important to improving smoking cessation and mental health among Latinx persons who smoke.

Keywords: Latinx, cigarette smoking, alcohol use, anxiety, depression, health disparities, comorbidity

The Latinx/Hispanic (hereafter, Latinx) population in the United States (US) is a tobacco disparities group (Castro, 2016). Although the prevalence of daily smoking among Latinx persons, in general, is less than non-Latinx White persons (Society, 2018; Trinidad et al., 2009; Trinidad et al., 2011), smoking behavior is often not adequately addressed in clinical settings. For example, smoking is often not assessed among Latinx persons in healthcare settings (Cokkinides et al., 2008; Sonnenfeld et al., 2009), and this group has a lower probability of accessing smoking cessation guidance (e.g., advice to quit, education about the dangers of smoking) or treatment compared to non-Latinx White individuals (Bustamante et al., 2010; Cokkinides et al., 2008; Goding Sauer et al., 2019; Houston et al., 2005). Research has also found empirical evidence that Latinx individuals who smoke cigarettes are less likely to utilize nicotine replacement therapy, which can improve quit success (Babb et al., 2020; Levinson et al., 2004; Thorndike et al., 2002).

Smoking often co-occurs with alcohol use in the Latinx population. For example, some work has found that nearly 40% of Latinx heavy drinkers smoke cigarettes (Bandiera et al., 2019; Falk et al., 2006). Although there are various sources of influence in the co-occurrence of smoking and drinking (Drobes, 2002), the synergistic effects of using both substances can heighten one’s risk for chronic diseases and mortality (Bjartveit & Tverdal, 2005; Hart et al., 2010; Pelucchi et al., 2006). To date, most work on smoking-alcohol co-occurrence has been focused on non-Latinx White samples, but available work has found consistent and clinically meaningful interrelations in the US Latinx population. For instance, Latinx persons using alcohol are more likely to smoke cigarettes compared to Latinx persons who do not use alcohol (Cox et al., 2005). In studies of Latinx smokers, weekly drinking (Rodríguez-Esquivel et al., 2009) and heavy drinking (Woolard et al., 2015) have been identified as unique risk factors for health and wellness. Moreover, previous studies have also found alcohol consumption among Latinx smokers to be associated with greater positive and negative smoking outcome expectancies (Britton et al., 2021; Rodriguez-Cano et al., 2022).

Although past work on Latinx persons has focused on smoking-drinking comorbidity, it is limited in several ways. First, studies have yet to examine whether alcohol use severity is related to clinically relevant smoking processes such as cigarette dependence (Pomerleau et al., 1994), perceived barriers for quitting (Macnee & Talsma, 1995), or severity of problems experienced when trying to quit (Brown et al., 2002). This gap in the literature limits the understanding of linkages between alcohol use severity and the broad range of processes related to the maintenance and relapse of smoking among Latinx co-users. Secondly, past work has yet to distinguish the effects of alcohol use severity from other substance use behaviors such as non-alcohol drug use. Accordingly, additional research is needed to better understand the unique explanatory value of alcohol use severity among Latinx individuals who smoke while accounting for non-alcohol drug use and well-established sociocultural factors (e.g., age, education). Lastly, a growing body of work largely focused on non-Latinx White samples has found smoking and more severe alcohol use to be related to poorer mental health (Goodwin et al., 2017; Zvolensky et al., 2018). However, it is unclear among Latinx persons who smoke if alcohol use severity is associated with more severe mental health problems like anxiety and depression. This knowledge is clinically important given the association between negative emotional states and more severe and persistent forms of substance use (Weinberger et al., 2017; Weinberger et al., 2019) that may require more intensive and targeted interventions.

The present investigation aimed to explore the prevalence and role of alcohol use severity in relation to clinically significant tobacco and mental health problems among English-speaking Latinx adults who smoke cigarettes. First, it was hypothesized that greater levels of alcohol use severity would be related to greater cigarette dependence, problems experienced during prior quit attempts, and perceived barriers for smoking cessation. Second, it was hypothesized that greater alcohol use severity would also be associated with higher anxiety and depression symptoms. For all models (except for cigarette dependence), we adjusted for factors related to smoking as well as mental health in the Latinx population, including age (Park et al., 2012), sex (Piper et al., 2010; Pogun & Yararbas, 2009), education (Piper et al., 2010), nativity (Castro et al., 2012), the average number of cigarettes smoked per day (Benowitz, 1999), and drug use problem severity (Goodwin et al., 2011).

Method

Participants

The present sample included 338 English-speaking Latinx adults who engaged in daily cigarette smoking (Mage = 35.5 years; SD = 8.65; age range 18-61; 37.3% female). Participants identified as Latinx and approximately 87% of the sample was born in the US. In terms of race, 72.4% identified as Latinx White, followed by 11.0% other, 7.1% Black or African American, 4.2% Alaska Native or American Indian, 3.3% Multiracial/more than one race, 1.2% Native Hawaiian or Other Pacific Islander, and 0.9% Asian. Most were employed full-time (76.3%) and reported an annual income of ≥ $50,000 (59.7%), followed by 15.7% between $35,000-$49,999, 9.2% between $25,000-$34,999, 6.8% between $15,000-$24,999, 5% between $10,000-$14,999, 1.5% between $5,000-$9,999, and the remaining 3.8% reported an income of $0-4,999.

Participants were recruited nationally throughout the US and the state-wide distribution was as follows: 18% California, 16.9% New York, 15.1% Texas, 10.9% Florida, 5% Colorado, 4.1% Arizona, 2.7% Pennsylvania, 2.4% New Jersey, 2.4% Georgia, 1.8% Illinois, 1.5% Ohio, 1.5% Nevada, 1.5% Michigan, 1.5% Aransas, 1.2% Virginia, 1.2% Massachusetts, 0.9% Washington, 0.9% Missouri, 0.9% Indiana, 0.9% Alabama, 0.6% Wyoming, 0.6% Utah, 0.6% Tennessee, 0.6% Oregon, 0.6% Oklahoma, 0.6% North Dakota, 0.6% Nebraska, 0.6% Maryland, 0.6% Maine, 0.6% Idaho, 0.6% Hawaii, 0.3% Wisconsin, 0.3% South Carolina, 0.3% North Carolina, 0.3% New Mexico, 0.3% New Hampshire, 0.3% Minnesota, 0.3% Connecticut.

Procedures

Participants were recruited nationally throughout the US from February 2021 to July 2021 using Qualtrics Panels, an online survey management system that has been implemented in prior research and has been successfully used to target specific populations to gather valid and reliable data (e.g., internal consistency, internal validity, external consistency; Heen et al., 2014; Walter et al., 2018). Participants with a Qualtrics Panels account who identified as Latinx/Hispanic and endorsed current cigarette smoking were sent an advertisement. Respondents who expressed interest were then screened for eligibility and directed to an anonymous survey. Eligible participants were at least 18 years of age, identified as Hispanic or Latinx, and reported current daily cigarette smoking (≥ 5 cigarettes per day). Participants provided voluntary informed consent before completing the online survey. Upon completion, participants could opt to receive the equivalent of $10.75 in compensation for the study via cash-based incentives (i.e., gift cards), rewards miles, or rewards points. To ensure valid responses, survey completion times were evaluated (i.e., less than one-half the median survey completion time) as well as recording IP addresses to prevent multiple attempts to complete the survey by the same respondent. Based on the safeguards, eight cases were identified and removed from subsequent analyses. The study was approved by the Institutional Review Board of the university where the study took place.

Measures

Demographics Questionnaire

A demographics questionnaire was completed by all participants and in the current study, age, sex assigned at birth (0 = male, 1 = female), education (1 = Less than high school, 2 = Some high school, 3 = Completed high school [or equivalent], 4 = Some college, 5 = Associate’s Degree, 6 = Bachelor’s Degree, 7 = Master’s Degree, 8 = Doctoral Degree, 9 = More than Doctorate), and nativity (0 = Born in US; 1 = Other) were used as covariates.

Smoking History Questionnaire (SHQ)

The SHQ (Brown et al., 2002) measures smoking-related demographic information (e.g., age of regular daily smoking, the total number of years smoking daily, number of failed quit attempts) and is also used to assess the severity of problems experienced during prior quit attempts. The average number of cigarettes smoked per day item was used as a covariate. As in past work (Zvolensky et al., 2004), a mean composite score of the severity of problem symptoms experienced during past quit attempts was derived from this measure. Specifically, this item asks, “While trying to quit, how serious have each of the following problems been for you?” Examples of the 17 items include weight gain, headaches, irritability, or insomnia. Items were rated on a 5-point Likert-type scale from 1 (not at all) to 5 (extremely). The severity of these items was averaged to create a composite score and utilized as a criterion variable. The composite score demonstrated strong internal consistency (α = .96).

Drug Abuse Screening Test (DAST-10)

The DAST-10 (Yudko et al., 2007) is a 10-item measure that assesses drug use problem severity. Individuals respond (0 = no, 1 = yes) to each item (e.g., “Are you always able to stop using drugs when you want to?”). Items are not anchored to a specific drug class and can include use related to cannabis (marijuana, hashish), solvents (e.g., paint thinner), tranquilizers (e.g., Valium), barbiturates, cocaine, stimulants (e.g., speed), hallucinogens (e.g., LSD) or narcotics (e.g., heroin). Scores range from 0-10 with lower scores indicating no problems related to drug abuse and high scores indicating severe levels of drug abuse problems (0 = no problems reported, 1-2 = low levels, 3-5 = moderate levels, 6-8 = substantial levels, and 9-10 = severe levels). In the current investigation, the DAST-10 total score was used as a covariate and had good internal consistency (α = .84).

Alcohol Use Disorders Identification (AUDIT)

The AUDIT (Saunders et al., 1993) is a 10-item self-report measure that was developed to assess problematic alcohol use. Items (e.g., “How often during the last year have you failed to do what was normally expected from you because of drinking?”) are rated on various scales that are anchored to each specific item and are summed to a total score (range = 0-40) as well as the three subscales, including, alcohol consumption (items 1-3; range = 0-12), dependence (items 4-6; range = 0-12), and related problems (items 7-10 range = 0-16; Higgins-Biddle & Babor, 2018; Saunders et al., 1993). The AUDIT total score is a measure of hazardous drinking and was used to differentiate individuals without problems (< 7 for females and < 8 for males) from those with potential problems (≥7 for females and ≥ 8 for males; Higgins-Biddle & Babor, 2018) and to identify four ‘zones’ with increasing risk and intervention levels: zone 1 – low risk (below cut-off; 0-7), zone 2 – hazardous level (simple advice; 8-15), zone 3 – harmful level (simple advice plus brief counseling and monitoring; 16-19), and zone 4 – probable alcohol use disorder (referral to specialize for evaluation and treatment; 20-40; Babor & Higgins-Biddle, 2001). The AUDIT total score was used as a predictor in the current investigation and demonstrated excellent internal consistency (α = .94).

Fagerström Test for Cigarette Dependence-Revised

The FTCD-R (Korte et al., 2013) is a 6-item scale that assesses degrees of cigarette dependence. Scores range from 0-16, with higher scores reflecting higher levels of physiological dependence on cigarettes. As in prior work, items 2, 5, and 6 were scored on a 4-point Likert-type scale ranging from 0 (never) to 3 (always). In the present study, the FTCD-R was used as a criterion variable and had low internal consistency (α = .64); although low internal consistency for the FTCD-R is common (Korte et al., 2013). Past work indicates positive relations with biochemical markers of tobacco use (e.g., saliva cotinine), and high test-retest reliability (Heatherton et al., 1991; Pomerleau et al., 1994), including among Latinx individuals who smoke (Zvolensky, Bakhshaie, et al., 2019).

Barriers for Cessation (BCS)

The BCS (Macnee & Talsma, 1995) is a 19-item self-report measure of perceived barriers to or stressors resulting from smoking cessation (e.g., “Feeling less in control of your moods”). Responses are rated on a 4-point Likert scale ranging from 0 (not a barrier) to 3 (large barrier). The BCS has demonstrated strong psychometric properties in past work (Garey et al., 2017) and has been used among Latinx individuals who smoke cigarettes (Britton et al., 2021). In the present study, the BCS total score demonstrated strong internal consistency (α = .95) and was utilized as a criterion variable.

Overall Anxiety Severity and Impairment Scale (OASIS)

The OASIS (Norman et al., 2006) is a five-item measure of anxiety severity and level of impairment due to anxiety symptoms. Participants are instructed to rate each item (e.g., “In the past week, when you have felt anxious, how intense or severe was your anxiety?”) on a scale ranging from 0-4 with anchors specific to each item (e.g., 0 = little or none; 4 = extreme). Past research has indicated that a cutoff score of 8 or greater reflects a probable anxiety disorder (Norman et al., 2011). In the current investigation, the OASIS demonstrated excellent internal consistency (α = .94) and was used as a criterion variable.

Overall Depression Symptom and Impairment Scale (ODSIS)

The ODSIS (Bentley, Gallagher, Carl, & Barlow, 2014) is a five-item measure designed to assess symptoms and functional impairment associated with depression. Participants rate each item (e.g., “In the past week, how often did you have difficulty engaging in or being interested in activities you normally enjoy because of depression?”) on a scale ranging from 0-4 with anchors specific to each item (e.g., 0 = none; 4 = all the time). The ODSIS has demonstrated strong convergent and discriminant validity in clinical and nonclinical samples and is invariant across diverse samples (Ito et al., 2015). Psychometric work has identified a clinical cut score of 8 or greater as indicative of a probable mood disorder (Bentley, Gallagher, Carl, & Barlow, 2014). The ODSIS total score evidenced excellent internal consistency (α = .94) and was used in the current study as a criterion variable.

Analytic Strategy

Analyses were conducted using SPSS version 28 (IBM, 2021). A power analysis was conducted and indicated that a sample size of 338 was sufficient to detect medium effects. First, descriptive statistics and bivariate correlations among the study variables were examined. Next, five hierarchical regression analyses were conducted to test the association of alcohol use severity with cigarette dependence, severity of problems experienced during prior quit attempts, perceived barriers for smoking cessation as well as anxiety and depression symptoms. The first step for all models (except for cigarette dependence) included the following covariates: age (Park et al., 2012), sex (Piper et al., 2010; Pogun & Yararbas, 2009), education (Piper et al., 2010), nativity (Castro et al., 2012), the average number of cigarettes smoked per day (Benowitz, 1999), and drug abuse problem severity (Goodwin et al., 2011). For cigarette dependence, the average number of cigarettes smoked per day was not included as a covariate due to collinearity. Alcohol use severity was then entered on the second step. The data met the assumptions of linear regression analyses. Model fit for each of the steps was evaluated with the F statistic and change in R2. Change in R2 and squared semi-partial correlations (sr2) were used as indices of effect size (interpreted as .01 = small, .09 = moderate, and .25 = large; Cohen, 1988). Bonferroni corrections were employed for each set of conceptually specific analyses (smoking: .05/3 = p < .01, and mental health: .05/2 = p < .02).

Results

Descriptive Statistics and Bivariate Correlations

Descriptive statistics and bivariate correlations are presented in Tables 1 and 2. The average number of years of daily smoking was 14.4 years (SD = 9.4). Participants smoked an average of 10.8 (SD = 8.8) cigarettes per day, which is slightly higher than other nationally representative Latinx samples (M = 8.8, SD = 8.4; Kristman-Valente & Flaherty, 2016) and reported an average of 4.9 (SD = 6.8) prior failed quit attempts.

Table 1.

Descriptive Statistics by Alcohol Use Severity (N = 338)

Male Female
Variable Non-Drinkers
(n = 14)		 Non-Hazardous
Drinkers (n = 52)		 Hazardous Drinkers
(n = 146)		 Non-Drinkers
(n = 16)		 Non-Hazardous
Drinkers (n = 33)		 Hazardous Drinkers
(n = 77)
Age 35.43 (8.08) 37.46 (7.92) 34.37 (7.91) 38.69 (10.56) 38.30 (9.81) 34.61 (9.25)
Education 7 (50.0%) 34 (65.3%) 107 (73.3%) 6 (37.5%) 14 (42.4%) 35 (45.5%)
Nativity 0 (0.0%) 5 (9.6%) 20 (13.7%) 2 (12.5%) 3 (9.1%) 13 (16.9%)
Cigarettes per Day 10.00 (5.82) 11.35 (7.60) 10.84 (10.71) 10.19 (5.67) 11.45 (6.72) 10.23 (7.19)
Drug Use Problems 2.07 (2.62) 1.12 (1.83) 3.98 (2.94) 2.00 (1.93) 1.58 (2.46) 3.30 (2.92)
Alcohol Use 0.00 (0.00) 4.23 (1.84) 21.22 (8.97) 0.00 (0.00) 3.06 (1.85) 17.47 (7.89)
Cigarette Dependence 6.79 (3.45) 5.29 (3.11) 7.56 (2.83) 5.75 (2.72) 5.85 (2.54) 6.47 (3.01)
Barriers to Cessation 24.21 (16.00) 23.40 (14.42) 31.90 (13.73) 17.13 (15.35) 21.79 (14.98) 31.30 (12.61)
Quit Problems 3.00 (1.06) 2.42 (0.99) 3.21 (1.06) 2.17 (1.02) 2.38 (1.10) 3.01 (0.89)
Anxiety 5.50 (7.10) 4.04 (4.49) 9.38 (5.56) 7.69 (6.01) 4.33 (5.66) 8.06 (5.16)
Depression 4.71 (5.48) 3.96 (4.37) 9.77 (5.56) 7.69 (5.87) 3.88 (5.53) 8.55 (5.56)
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Note. Mean (SD) / N [%]; Education = % listed as Bachelor’s Degree or higher (Coded: 0 = less than Bachelor’ degree, 1 = Bachelor’s degree or higher); Nativity = % listed as other (Coded: 0 = Born in US, 1 = Other); Cigarettes per Day = Smoking History Questionnaire (Brown et al., 2002); Drug Use Problems = DAST-10 Total Score (Yudko et al., 2007); Alcohol Use = AUDIT Total Score (Saunders et al., 1993); Cigarette Dependence = FTCD-R Total Score (Korte et al., 2013); Barriers to Cessation = Barriers to Cessation Scale (Macnee & Talsma, 1995); Quit Problems = Smoking History Questionnaire - Quit Problems Subscale (Brown et al., 2002); Anxiety = OASIS Total Score (Norman et al., 2006); Depression = ODSIS Total Score (Bentley et al., 2014).

Table 2.

Bivariate Correlations

Variable 1 2 3 4 5 6 7 8 9 10 11 12
1. Age -
2. Sex .05 -
3. Education .06 −.26** -
4. Nativity .04 .04 .04 -
5. Cigarettes per Day .10 −.02 −.08 −.09 -
6. Drug Use Problems −.15** −.08 .07 −.02 −.004 -
7. Alcohol Use −.19** −.19** .21** .06 −.02 .58** -
8. Cigarette Dependence −.07 −.12* .13* −.10 .26** .38** .42** -
9. Barriers to Cessation −.18** −.08 .23** −.07 −.001 .47** .51** .47** -
10. Quit Problems −.18** −.12* .20** .05 .06 .43** .48** .46** .74** -
11. Anxiety −.17** −.07 .12* .01 −.03 .51** .51** .40** .58** .52** -
12. Depression −.20** −.07 .09 −.01 .01 .52** .53** .42** .55** .52** .90** -
Mean/n 35.53 126 203 43 10.78 2.98 14.09 6.68 28.45 2.90 7.52 7.71
SD/% 8.65 37.3% 60.1% 12.7% 8.77 2.90 10.89 3.02 14.57 1.07 7.71 5.89
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Note. **p < .01, *p < .05; Sex % listed as females (Coded: 0 = male, 1 = female); Education = % listed as Bachelor’s Degree or higher (Coded: 0 = less than Bachelor’ degree, 1 = Bachelor’s degree or higher); Nativity = % listed as other (Coded: 0 = Born in US, 1 = Other).

Alcohol Use Severity Prevalence

Regarding alcohol use severity, for males (n = 212), 6.6% identified as non-drinkers, followed by 24.5% as non-hazardous drinkers. The remaining 68.9% reported scores above the established clinical cut-off (≥ 8 for males), which is an indicator of hazardous and harmful alcohol use and possible alcohol dependence (Babor & Higgins-Biddle, 2001). For females (n = 126), 12.7% identified as non-drinkers, followed by 26.2% as non-hazardous drinkers, and the remaining 61.1% meeting scores above the established clinical cut-off for hazardous drinking (≥7 for females). The AUDIT also uses a classification system with four ‘zones’ to identify increasing risk and intervention levels; across the sample, 35.5% were classified in zone 1, followed by 22.5% in zone 2, 11.2% in zone 3, and 30.8% in zone 4.

Smoking Variables1

For cigarette dependence, the first step with covariates was statistically significant (R2 = .17, F [5, 332] = 13.41, p < .001), with drug use problem severity emerging as a statistically significant univariate predictor. In step two, alcohol use severity accounted for a statistically significant increase in variance (ΔR2 = .05, F [1, 331] = 15.64, p < .001).

For severity of quit problems, the first step with covariates was statistically significant (R2 = .23, F [6, 331] = 17.42, p < .001), with age, education, and drug use problem severity emerging as statistically significant predictors. In step two, alcohol use severity accounted for a statistically significant increase in variance (ΔR2 = .06, F [1, 330] = 19.73, p < .001).

For perceived barriers for smoking cessation, the first step with covariates was statistically significant (R2 = .28, F [6, 331] = 21.70, p < .001), with age, education, and drug use problem severity emerging as statistically significant predictors. In step two, alcohol use severity accounted for a statistically significant increase in variance (ΔR2 = .06, F [1, 330] = 24.81, p < .001).

Mental Health Variables

For anxiety, the first step with covariates was statistically significant (R2 = .27, F [6, 331] = 20.77, p < .001), with age and drug use problem severity emerging as statistically significant predictors. In step two, alcohol use severity accounted for a statistically significant increase in variance (ΔR2 = .06, F [1, 330] = 23.67, p < .001).

In terms of depression, the first step with covariates was statistically significant (R2 = .29, F [6, 331] = 22.56, p < .001), with age and drug use problem severity emerging as statistically significant predictors. In step two, alcohol use severity accounted for a statistically significant increase in variance (ΔR2 = .07, F [1, 330] = 26.17, p < .001).

Discussion

Previous research has linked alcohol use severity to the maintenance of smoking and negative mood among the general population (Batel et al., 1995; Hagman et al., 2008; McKee et al., 2006; Verplaetse & McKee, 2017). However, there has been comparatively little work focused on individual differences in alcohol use behavior and tobacco and mental health clinical comorbidity among Latinx persons who smoke. The present study sought to document the prevalence of alcohol use problems and test if alcohol use severity was related to clinically relevant co-occurring smoking processes and poorer mental health among adult English-speaking US Latinx individuals who smoke cigarettes.

In the present sample, one that was not selected based on alcohol use severity, there was a high prevalence of alcohol use problems among Latinx individuals who smoke. Specifically, 69% of male and 61% of female smokers scored at or above established clinical cutoffs for hazardous and harmful alcohol use and possible alcohol dependence (Babor & Higgins-Biddle, 2001). Related work conducted among primarily non-Latinx daily tobacco smokers found that 32.4% of the sample met above the established cut-off for hazardous drinking (LaRowe et al., 2020) whereas other work among male smokers has shown that 65.5% met for hazardous drinking (Choi et al., 2020). Using the zone classification system of the AUDIT, approximately 30% scored in the most severe zone of ‘referral to specialize for evaluation and treatment’ and another 11% scored in the second most severe zone of ‘simple advice plus brief counseling and monitoring.’ Overall, there was robust evidence of a high prevalence of alcohol use problems among adult English-speaking Latinx individuals who smoke living in the US.

As expected, there was consistent empirical support for the relation between alcohol use problems and more severe smoking processes linked to the maintenance and relapse of tobacco use. Specifically, alcohol use severity was related to greater cigarette dependence, severity of quit problems, and perceived barriers for smoking cessation. The alcohol use severity findings were evident above and beyond the variance accounted for by theoretically and empirically relevant covariates; as such, the observed effects may be clinically significant (West, 2007), particularly considering the prevalence of alcohol use problems among the sample. These data extend the limited past work on Latinx individuals who smoke cigarettes and have been observed to have greater alcohol use (Cox et al., 2005). Findings also evince the higher rate of binge and heavy drinking (Rodríguez-Esquivel et al., 2009; Woolard et al., 2015). Moreover, these findings collectively document relatively broad-based relations for alcohol use severity to numerous smoking processes among Latinx individuals who smoke cigarettes.

As expected, the current study supported the empirical evidence demonstrating an association between alcohol use problems and the severity of anxiety and depression after accounting for covariates. The observed effects in the current study may again be potentially clinically noteworthy (West, 2007). Past work among the US Latinx population in general, and smokers specifically, has consistently found that higher levels of anxiety and depression symptoms are related to a lesser quality of life (Talavera et al., 2018; Zvolensky, Rogers, et al., 2019), higher rates of poorer health (Escalera et al., 2022), and engagement in maladaptive health behaviors (e.g., smoking; Shepherd et al., 2022). The current findings add to this literature and suggest that alcohol use severity is an important indicator that may uniquely contribute to poorer mental health among this group. Thus, the current data indicate that intra-individual differences in alcohol use severity offer unique explanatory value for anxiety and depression even when considering the role of concurrent substance use problems. Accordingly, the study results suggest that there may be merit to integrating more targeted interventions for alcohol use problems within therapeutic modalities and prevention efforts for Latinx individuals who smoke cigarettes.

Clinically, the present data suggest that there should be routine clinical screening for alcohol use problems among Latinx persons who smoke. For instance, Latinx persons who smoke are less likely than non-Latinx White persons to receive cessation-related advice from medical providers or engage in empirically supported medical and behavior cessation treatment (Babb et al., 2020; Babb et al., 2017), Further, Latinx persons who drink are less likely to receive alcohol-specific treatment or more than one session of care (Chartier & Caetano, 2010; Schmidt et al., 2006). Identifying and intervening to reduce alcohol use problems may be important to improve smoking cessation and mental health among this population; the clustering of these conditions is linked to higher healthcare costs and public health burden (Pronk et al., 2004). By reducing alcohol use severity, there may be opportunity to have a corresponding impact on co-occurring tobacco and mental health problems. There has been some effort to address alcohol in the context of smoking among the Latinx population (Correa-Fernández et al., 2017). There is a need to build from this work and develop integrated interventions, perhaps that are culturally tailored, for Latinx persons who smoke that experience alcohol use problems. For instance, there may be merit for future intervention work to incorporate a focus on protective factors such as ethnic identity and cultural values (e.g., familism; Waldron et al., 2022; Wells et al., 2001) as well as experiences with acculturation and related stress, a demonstrated risk factor for increased alcohol use and tobacco smoking (Rodriquez et al., 2019; Ruiz et al., 2022). Theoretically, there could be value in considering a range of strategies, including brief tactics focused on educating Latinx persons who smoke about the risk related to alcohol use to more intensive tactics that seek to promote simultaneously change in smoking, drinking, and mental health.In terms of study limitations, the study focused on cross-sectional data, thereby precluding causal interpretations. Future research could benefit from a longitudinal design to further delineate the observed associations over time. Such work would be fruitful to further delineate the order of substance onset (e.g., does cigarette smoking preceed alcohol misuse or vice versa) to better inform models of prevention and subsequent treatment efforts. Second, individuals were self-selected for the investigation, potentially limiting the generalizability of the current findings. It may be important to replicate and extend the current findings to treatment-seeking and other probability-based samples. Third, we focused on the main effect of alcohol use severity in terms of tobacco and mental health. Future research could build upon the current findings and explore if alcohol use interacts with social determinants of health (e.g., racial/ethnic discrimination, subjective social status, acculturative stress; Cabral & Cuevas, 2020) in terms of tobacco and mental health problems. Fourth, although we used the AUDIT, a psychometrically valid, albeit brief index of hazardous drinking, future studies may benefit from including a multi-modal assessment of alcohol use to further delineate hazardous drinking from alcohol use disorder. Fifth, the sample was comprised of English-speaking Latinx persons living in the United States which may limit the generalizability of the findings to Latinx persons with lower levels of acculturation. For instance, future research would benefit from testing the observed relations among monolingual Spanish-speaking Latinx persons to further extend the findings in the current work. Finally, study data were based solely on self-report questionnaires, leaving the potential for measurement variance effects. A multimethod measurement protocol could be usefully employed in future work, including clinical interviews and laboratory paradigms.

Overall, the results of the present investigation contribute to a limited area of research - alcohol use severity and smoking and mental health among Latinx persons in the US. Findings indicated that alcohol use problems were highly prevalent, and the severity of alcohol use was associated with significant increases in an array of adverse smoking and negative mood indicators. Future research exploring alcohol use severity and its relation to smoking and mental health over time may further elucidate the associations observed in the current study.

Table 3.

Associations of Alcohol Use Severity in Relation to Cigarette Dependence, Quit problems, Barriers for Smoking Cessation, Anxiety Symptoms, and Depression Symptoms (N = 338)

Cigarette Dependence B SE t p 95% Bootstrapped CI sr2 R2/R2 Change
Step 1 .168
  Age −0.003 0.02 −0.18 .856 −0.04 0.03 <.001
  Sex −0.38 0.33 −1.18 .237 −1.02 0.25 .004
  Education 0.17 0.10 1.77 .078 −0.02 0.37 .008
  Nativity −0.84 0.45 −1.85 .065 −1.73 0.05 .009
  Drug Use Problems 0.38 0.05 7.19 <.001 0.28 0.48 .129
Step 2 .053
  Alcohol Use 0.08 0.02 4.74 <.001 0.05 0.12 .053
Quit Problems B SE t p 95% Bootstrapped CI sr2 R2/R2 Change
Step 1 .240
  Age −0.02 0.01 −2.94 .003 −0.03 −0.01 .020
  Sex −0.08 0.11 −0.69 .488 −0.29 0.14 .001
  Education 0.12 0.03 3.51 .001 0.05 0.18 .028
  Nativity 0.21 0.15 1.38 .170 −0.09 0.52 .004
  Cigarettes per Day 0.01 0.01 1.95 .052 0.00 0.02 .009
  Drug Use Problems 0.14 0.02 8.00 <.001 0.11 0.18 .147
Step 2 .055
  Alcohol Use 0.03 0.01 5.07 .001 0.02 0.04 .055
Barriers for Cessation B SE t p 95% Bootstrapped CI sr2 R2/R2 Change
Step 1 .282
  Age −0.21 0.08 −2.66 .008 −0.37 −0.06 .015
  Sex 0.73 1.46 0.50 .619 −2.15 3.60 .001
  Education 1.95 0.44 4.43 <.001 1.09 2.82 .043
  Nativity −2.79 2.05 −1.37 .173 −6.82 1.23 .004
  Cigarettes per Day 0.05 0.08 0.58 .563 −0.11 0.20 .001
  Drug Use Problems 2.20 0.24 9.27 <.001 1.74 2.67 .186
Step 2 .062
  Alcohol Use 0.43 0.08 5.61 <.001 0.28 0.58 .062
Anxiety B SE t p 95% Bootstrapped CI sr2 R2/R2 Change
Step 1 .273
  Age −0.07 0.03 −2.16 .032 −0.13 −0.01 .010
  Sex 0.01 0.58 0.02 .981 −1.14 1.16 <.001
  Education 0.32 0.18 1.80 .072 −0.03 0.67 .007
  Nativity 0.28 0.82 0.34 .734 −1.33 1.89 <.001
  Cigarettes per Day −0.005 0.03 −0.15 .879 −0.07 0.06 <.001
  Drug Use Problems 0.97 0.09 10.17 <.001 0.78 1.15 .227
Step 2 .061
  Alcohol Use 0.17 0.03 5.49 .001 0.11 0.23 .061
Depression B SE t p 95% Bootstrapped CI sr2 R2/R2 Change
Step 1 .290
  Age −0.09 0.03 −2.74 .006 −0.15 −0.02 .016
  Sex −0.04 0.59 −0.07 .941 −1.20 1.11 <.001
  Education 0.22 0.18 1.25 .213 −0.13 0.57 .003
  Nativity 0.06 0.82 0.07 .946 −1.56 1.68 <.001
  Cigarettes per Day 0.02 0.03 0.62 .539 −0.04 0.08 .001
  Drug Use Problems 1.01 0.10 10.56 <.001 0.82 1.20 .239
Step 2 .067
  Alcohol Use 0.18 0.03 5.85 <.001 0.12 0.24 .067
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Note. N = 338. Sex (Coded: 0 = male, 1 = female); Education (Coded: 1 = Less than High School, 2 = Some High School, 3 = Completed High School (or equivalent), 4 = Some College, 5 = Associate’s Degree, 6 = Bachelor’s Degree, 7 = Master’s Degree, 8 = Doctoral Degree, 9 = More than Doctorate); Nativity = (Coded: 0 = Born in US, 1 = Other); Cigarettes per Day = Smoking History Questionnaire (Brown et al., 2002); Drug Use Problems = DAST-10 Total Score (Yudko et al., 2007); Alcohol Use = AUDIT Total Score (Saunders et al., 1993); Cigarette Dependence = FTCD-R Total Score (Korte et al., 2013); Barriers to Cessation = Barriers to Cessation Scale (Macnee & Talsma, 1995); Quit Problems = Smoking History Questionnaire - Quit Problems Subscale (Brown et al., 2002); Anxiety = OASIS Total Score (Norman et al., 2006); Depression = ODSIS Total Score (Bentley et al., 2014).

Funding

Research reported in this publication was supported by the National Institute on Minority Health and Health Disparities (NIMHD) of the National Institutes of Health (NIH) to the University of Houston under Award Number U54MD015946. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Disclosure Statement

The authors report no conflicts of interest.

1

Regression models were conducted for severity of quit problems, perceived barriers for smoking cessation, anxiety, and depression including cigarette dependence as a covariate in place of average number of cigarettes per day. While cigarette dependence was a significant predictor in step one of each model, the patterns of findings remained unchanged

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