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Original Studies

Executive Dysfunction Related to Binge Drinking in Ischemic Stroke

Laari, Siiri P.K. MA*,†; Kauranen, Tatu V. PhD; Turunen, Katri E.A. MA*; Mustanoja, Satu M. MD, PhD; Tatlisumak, Turgut MD, PhD§; Poutiainen, Erja T. PhD*,†,∥

Author Information
Cognitive and Behavioral Neurology: March 2020 - Volume 33 - Issue 1 - p 23-32
doi: 10.1097/WNN.0000000000000222
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Abstract

Binge drinking is a growing public health concern; its prevalence among adults has increased significantly during the past decade (Grucza et al, 2018). Binge drinking, or heavy episodic drinking, refers to the consumption of five or more standard drinks (13.5 gram of ethanol) within 2 hours (National Institute on Alcohol Abuse and Alcoholism, 2004). Binge drinking in the absence of an alcohol use disorder (AUD) is suggested to represent the milder end of the continuum of alcohol-related cognitive disorders (Stephens and Duka, 2008).

Research on adolescents has shown that deficits in executive functions, which provide top-down regulation of goal-directed behavior (Nigg, 2017), are associated with a history of several binge-drinking sessions, even without an AUD (Squeglia et al, 2012; Winward et al, 2014a, 2014b). Adolescents with a history of binge drinking have also shown verbal memory dysfunction, part of which can be explained by their executive dysfunction (Mota et al, 2013; Parada et al, 2011; Winward et al, 2014b; for a review, see Carbia et al, 2018). However, very few studies exist regarding the effect of subdiagnostic binge drinking, that is, social drinking that does not fulfill the criteria for AUD, on adult cognition.

We found only two studies on binge-drinking’s effect on adult cognition. First, male truck drivers who reported a history of binge drinking performed poorer than non–binge-drinking peers in an executive dysfunction task requiring response inhibition (de Oliveira et al, 2016). Second, elderly individuals reporting binge drinking had more self-reported cognitive dysfunction than elderly individuals reporting no binge drinking (Virta et al, 2010). However, research on binge drinking in adults has not been able to replicate the aforementioned association between cognitive deficits and subdiagnostic binge drinking on a larger scale (Horvat et al, 2015). We undertook this study to discover whether individuals who have suffered an acute brain injury (eg, as a result of first-ever ischemic stroke) would experience any potential additive negative effect of binge drinking on associated cognitive deficits. To our knowledge, no studies have so far attempted to examine this.

Cognitive impairment is a common effect of ischemic stroke and occurs in 35% to 90% of all cases, depending on how the term is defined (Gottesman and Hillis, 2010). Executive function and verbal memory are among the most common cognitive domains that are affected by an ischemic stroke (Barker-Collo et al, 2012; Turunen et al, 2018).

The aim of our study was to determine whether cognitive dysfunction related to ischemic stroke would be more severe in patients with a history of binge drinking than in patients without a history of binge drinking. We hypothesized that a history of subdiagnostic binge drinking would positively correlate with executive and verbal memory dysfunction after a first-ever ischemic stroke.

METHODS

Participants

The ischemic stroke patients included in our study were part of a consecutive inpatient cohort that was established by Helsinki University Hospital and Lapland Central Hospital from April 2007 to October 2009. The inclusion criteria were first-ever supratentorial ischemic stroke, age 18 to 65 years, and native Finnish speaker. The exclusion criteria were a history or current diagnosis of disease(s) affecting cognition (ie, neurologic or psychiatric diseases); severely altered state of consciousness; and severe aphasia, as measured by the Finnish version of the Boston Diagnostic Aphasia Examination (Laine et al, 1997). Additional exclusion criteria were previous or present AUD or substance use disorder and a diagnosis of F10 to F19 (World Health Organization, 2004). Of the 282 patients fulfilling the criteria, 38 refused to participate in the study, 19 were lost due to logistic reasons, and six were unable to complete the neuropsychological assessment. Of the 219 patients who enrolled in our study, seven decided to drop out 3 months after the stroke, and six were lost due to logistic reasons. As a result, a final total of 206 ischemic stroke patients participated in our study.

For the control group, we recruited 50 demographically comparable, healthy individuals—all of whom were related to the patients by being either their spouses, siblings, relatives, or friends. The inclusion and exclusion criteria for the control group were the same as for the patients, minus the history or diagnosis of ischemic stroke. We screened the control group using a telephone interview that covered the inclusion and exclusion criteria as well as sex, age, and education so as to form a demographically comparable control group to our ischemic stroke patients.

The study met the criteria set by the Declaration of Helsinki and its later amendments, and the ethics committee of Helsinki University Central Hospital approved the study protocol. In addition, each participant signed an informed consent form before participating in the study.

Clinical Assessment

First, for the ischemic stroke diagnosis, an experienced stroke neurologist conducted a clinical evaluation and performed brain imaging on patients receiving acute care at the Helsinki University Hospital and the Lapland Central Hospital. To measure the severity of the ischemic stroke, a neurologist administered the National Institutes of Health Stroke Scale (NIHSS; Goldstein et al, 1989) at the time of patient arrival and discharge from the hospital. We used the NIHSS severity score at discharge from the hospital in order to separate patients into two severity groups so that we could assess the effect of ischemic stroke severity on cognitive functions. We calculated the average NIHSS score of our stroke sample and grouped patients who scored lower than our ischemic stroke sample average on the NIHSS into the very mild stroke severity group and patients who scored average or greater than our sample average into the mild/moderate stroke severity group. A neurologist (S.M.M.) also used the Trial of Org 10172 of the Acute Stroke Treatment Criteria (Adams et al, 1997) to determine ischemic stroke etiology (ie, large-artery atherosclerosis, cardioembolism, small-artery occlusion, other determined, or undetermined). In addition, S.M.M. evaluated the lesion site and size (in millimeters, taken from the plane where the largest diameter was observed), any previous silent infarction lesion size, carotid artery stenosis, and age-related white matter changes. Age-related white matter changes were evaluated according to a widely used age-related white matter changes scale (Wahlund et al, 2001) using axial images from noncontrast CT or MRI fluid-attenuated inversion recovery series.

Next, an experienced clinical neuropsychologist administered an initial screening interview for inclusion, a structured clinical interview, and a neuropsychological assessment for both the ischemic stroke patients and the healthy controls (HCs). For the patients, both the inclusion interview and the structured interview were conducted while the patients received care at the hospital; the neuropsychological assessment was conducted 3 months after ischemic stroke diagnosis to ensure that the patients were medically stable. For the HCs, the inclusion interview was conducted by telephone, and the structured interview was conducted at the hospital at the same time as the neuropsychological assessment.

In the structured clinical interview, the ischemic stroke patients and HCs were asked questions measuring potential confounders and effect modifiers. The interview covered the study participants’ age; education status (years of education); history of attention and learning disabilities; history of neurologic and psychiatric diseases; past and/or present diagnosis of AUD (or other substance use disorders); current use/history of psychotropic medications; previous transient ischemic attacks; serum cholesterol level; vascular risk factors (including tobacco smoking); and diagnosis/history of diabetes mellitus, atrial fibrillation, hypertension, obesity, myocardial infarction, and heart failure. We also used the patients’ medical records to obtain glycated hemoglobin and fasting glucose levels.

Neuropsychological Assessment

An experienced clinical neuropsychologist administered a neuropsychological assessment for both the ischemic stroke patients and the HCs using the Finnish version of each test. Altogether, we covered nine cognitive functions and mood state in the assessment, as follows:

  • Executive functions were assessed using the difference time score of the Stroop Test (Lezak et al, 2012), the difference time score of Trail Making Test B−A (Lezak et al, 2012), and a phonemic fluency test (Lezak et al, 2012).
  • Working memory was assessed using the Backwards Digit Span subtest of the Wechsler Adult Intelligence Scale—Third Edition (WAIS–III; Wechsler, 1997) and an interference task (Lezak et al, 2012).
  • Verbal memory was assessed using the Logical Memory subtest of the Wechsler Memory Scale—Revised (WMS–R; Wechsler, 1987), which includes immediate recall of the first story told, delayed recall of the same story, and a list learning task (Lezak et al, 2012).
  • Visuospatial memory was assessed using the Benton Revised Visual Retention Test (Lezak et al, 2012), which involves immediate and delayed recall of designs.
  • Processing speed was assessed using the Digit Symbol subtest of the WAIS–III, the Stroop Test of naming colors, and Form A of the Trail Making Test.
  • Motor skills were assessed using a reciprocal hand movement, a dynamic repetition of three hand movements, and a finger-tapping test (Lezak et al, 2012).
  • Verbal function was assessed using a modified version of the Token Test (Lezak et al, 2012) and a semantic fluency test (Lezak et al, 2012).
  • Visuospatial function was assessed using a geometric figures copy task (Lezak et al, 2012) and a visuospatial searching task (Lezak et al, 2012).
  • Reasoning ability was assessed using the Similarities and Block Design subtests of the WAIS–III.
  • Mood state and fatigue were assessed using a modified version of the Profile of Mood States questionnaire (McNair and Lorr, 1964).

Binge-drinking and Non–binge-drinking Groups

We based the classification criteria we used for determining binge-drinking history on the shortened version (Aalto et al, 2006) of the Alcohol Use Disorders Identification Test (Saunders et al, 1993); that is, average drinking frequency and average number of standard drinks containing 13.5 grams of ethanol per drinking occasion over the last year. A standard drink is equivalent to 1.65 standard units of alcohol. Alcohol consumption covered any alcoholic drinks, including beer, wine, and hard liquor. We used the shortened version of the test because for patients, the test was conducted as part of the structured interview during their hospital care and we did not want to tire them.

Individuals who reported typically consuming five or more alcoholic drinks per occasion were placed in the binge-drinking group. Individuals who reported typically consuming four or fewer (0–4) drinks per occasion were placed in the non–binge-drinking group. Both ischemic stroke patients and the HCs were required to abstain from alcohol for at least 24 hours before beginning the neuropsychological assessment.

Statistical Analysis

We used SPSS (Version 22) for all of the statistical analyses. When necessary, basic transformations were used to obtain variable normality. Demographic and clinical variables were compared using an independent t test (normally distributed variables) and a chi-square test (nonparametric variables).

Propensity score matching with a 1:2 matching ratio was used to adjust for baseline differences between the binge-drinking and non–binge-drinking groups. This matching was conducted separately for ischemic stroke patients and HCs because the baseline difference regarding stroke severity was only applicable for the patients. Demographic and clinical variable differences between the binge-drinking and non–binge-drinking groups, or their significant associations with cognitive variables, were included in the iteration of the propensity score. The psmatching custom dialogue was used in conjunction with the SPSS software. The psmatching program performs all analyses in R through the SPSS R-Plugin (Version 3.1.3).

After propensity score matching, we compared nine cognitive functions between the binge-drinking and non–binge-drinking groups (including both the ischemic stroke patients and the HCs) using a multivariate analysis of variance (MANOVA). Each cognitive function was analyzed in a separate MANOVA; when applicable, post-MANOVA, separate tests were analyzed with a subsequent ANOVA. Next, we added covariates to the analyses: Groups were compared with a multivariate analysis of covariance (MANCOVA) and a subsequent analysis of covariance (ANCOVA), with the covariates of age and education (in years) set as continuous variables and ischemic stroke severity (according to NIHSS score) set as a categorical variable. Ischemic stroke severity categories were no stroke; very mild stroke, defined as stroke severity less than our stroke group average; and mild/moderate stroke, defined as stroke severity equal to or greater than our stroke group average. Interaction terms were included in the statistical MANCOVA model only for those covariates that had significant interaction with the main factor—binge drinking. The statistical significance level was set at P≤0.05.

RESULTS

Clinical Assessment

Ischemic stroke severity in the patient group, as measured using the NIHSS, was on average 1.63, corresponding to a mild stroke on NIHSS definition; the maximum recorded score was 13.00, corresponding to a moderate stroke on NIHSS definition. We divided the ischemic stroke patients in our study into two stroke severity groups according to our average of 1.63 (rounded up to correspond to an NIHSS score of 2): The first stroke severity group, a very mild stroke, corresponded to a score of 0 to 2 on the NIHSS (less than our stroke group average), and the second stroke severity group, a mild/moderate stroke, corresponded to a score of 2 to 13 on the NIHSS (stroke group average or greater). The HCs constituted a third severity group—no stroke.

Binge-drinking and Non–binge-drinking Groups

The covariates included in the iteration of the propensity score were gender and education—for both the stroke patients and the HCs—with ischemic stroke severity added for the stroke patients and smoking added for the HCs. The propensity score-matching procedure yielded 63 binge-drinking stroke patients who matched with 126 non–binge-drinking stroke patients, and 13 binge-drinking HCs who matched with 26 non–binge-drinking HCs. A total of 17 stroke patients and 11 HCs were unmatched and were not included in any further analyses. The final binge-drinking group consisted of 76 participants (both stroke patients and HCs), and the non–binge-drinking group consisted of 152 participants (both stroke patients and HCs).

A comparison of the demographic data and vascular risk factors between the binge-drinking (n=76) and non–binge-drinking (n=152) groups—stroke patients and HCs analyzed together—is provided in Table 1. There were no significant differences in demographic data between the binge-drinking and non–binge-drinking groups (except for the drinking variable, by definition). Ischemic stroke patients (binge-drinking vs non–binge-drinking) were also analyzed separately for clinical stroke-related variables (Table 2).

TABLE 1
TABLE 1:
Demographic and Vascular Risk Factors Compared Between the Binge-drinking and Non–binge-drinking Groups
TABLE 2
TABLE 2:
Clinical Assessment and Brain Imaging Variables Compared Between Binge-drinking and Non–binge-drinking Ischemic Stroke Patient Groups

Neuropsychological Assessment

We used a MANOVA to analyze the three executive function tests (difference time score of the Stroop Test, difference time score of Trail Making Test B−A, and a phonemic fluency test score) as dependent variables and binge drinking as an independent variable. The MANOVA showed a significant multivariate effect of all three executive function tests as a group in relation to binge drinking: F3,224=2.78, P=0.041, ηp2=0.036.

Next, we used a MANCOVA to examine the same three executive function tests as dependent variables; binge drinking as an independent variable; and age, education, and stroke severity (ie, no stroke, very mild stroke, and mild/moderate stroke) as covariates. The MANCOVA showed a significant main effect of binge drinking for all three executive function tests as a group: F3,217=7.07, P<0.001, ηp2=0.089 (Table 3).

TABLE 3
TABLE 3:
MANCOVAs and Subsequent ANCOVAs for Each Cognitive Function

In subsequent ANCOVAs, the binge-drinking group, on average, performed poorer than the non–binge-drinking group on each test of executive function: First, the Stroop Test difference time score was significantly higher in the binge-drinking group (63.5±3.91, M±SEM) than in the non–binge-drinking group (50.1±2.65), ANCOVA, F1,219=10.54, P=0.001, ηp2=0.046. Second, the Trail Making Test difference time score was significantly higher in the binge-drinking group than in the non–binge-drinking group (82.1±6.60, vs 73.7±4.48), ANCOVA, F1,219=9.79, P=0.002, ηp2=0.043. Third, the binge-drinking group produced significantly fewer words per minute on the phonemic fluency test than the non–binge-drinking group (11.9±0.69 vs 13.1±0.48), ANCOVA, F1,219=8.22, P=0.005, ηp2=0.036. In addition, the interaction between severity of ischemic stroke and binge drinking, and between education and binge drinking, qualified these main effects, as described in the following paragraphs.

A first significant interaction effect between binge drinking and ischemic stroke severity for executive function was observed after a MANCOVA: F6,436=6.00, P=0.037, ηp2=0.030. A subsequent ANCOVA showed an interaction between binge drinking and stroke severity in the Stroop Test difference time score: F2,4775=5.43, P=0.005, ηp2=0.047. When this interaction was analyzed using Bonferroni corrected post hoc pairwise comparisons within this ANCOVA measurement, binge-drinking stroke patients with a mild/moderate stroke showed a significantly higher Stroop Test difference time score than non–binge-drinking stroke patients with a mild/moderate stroke (M difference=32.5±8.02, P<0.001).

A second significant interaction effect between binge drinking and education for executive function was observed after a MANCOVA: F3,217=4.78, P=0.003, ηp2=0.062. Subsequent ANCOVAs showed that there were interactions between binge drinking and education in the Stroop Test difference time score (F1,4722=5.37, P=0.021, ηp2=0.024), the Trail Making Test difference time score (F1,0.46=7.92, P=0.005, ηp2=0.035), and the phonemic fluency test score (F1,188=6.55, P=0.011, ηp2=0.029). Overall, the less education (in years) a participant received (stroke patient or HC), the more strongly binge drinking was found to be associated with poor performance on tests of executive function.

As for the other cognitive functions (working memory, verbal memory, visuospatial memory, processing speed, motor skills, verbal function, visuospatial function, and reasoning ability), an initial MANOVA consisting of two to three neuropsychological tests per function as dependent variables and binge drinking as an independent variable were run separately for each cognitive function. Next, each of these cognitive functions was analyzed using a MANCOVA, with age, education, and stroke severity as covariates. There was no significant effect of binge drinking (Table 3) and no significant interaction in any of these analyses. With respect to mood state, there was no significant effect of binge drinking (Table 1).

DISCUSSION

As hypothesized, we showed that a history of binge drinking without a diagnosis of AUD (subdiagnostic binge drinking) was associated with executive dysfunction in our adult ischemic stroke patients. First, there was a significant interaction between binge drinking and ischemic stroke severity for executive function; that is, binge-drinking patients with a mild/moderate stroke had significantly more executive dysfunction than non–binge-drinking patients with a mild/moderate stroke. Second, in every executive function test, when ischemic stroke patients and HCs were analyzed together, the binge-drinking group had significantly more executive dysfunction and significantly lower performance on tests than the non–binge drinking group. Third, a significant interaction between binge drinking and length of education was observed for executive function, indicating that more education attenuates the negative effect of binge drinking on executive functions. Contrary to expectations, we did not find a significant difference between the binge-drinking and non–binge-drinking groups on verbal memory performance.

The key finding in our study is the interaction between binge drinking and ischemic stroke severity. Subdiagnostic binge drinking appeared to increase the adverse effects of a first-ever ischemic stroke on executive functions. Compared to the patients with a very mild stroke, or the HCs, the patients with a mild/moderate stroke displayed an association between a history of binge drinking and poor inhibition on the Stroop Test. One possible explanation for this finding could be that both binge drinking and ischemic stroke damage partly similar brain networks that are distributed across the frontal areas underlying executive functions (Stuss, 2011). Binge-drinking-related executive dysfunction has previously been associated with anatomic and functional alterations in the prefrontal regions of the brain (Banca et al, 2016; Campanella et al, 2013; López-Caneda et al, 2012; for a review, see Welch et al, 2013). In our study, however, only seven participants in the binge-drinking group displayed a frontal ischemic lesion; thus, binge-drinking patients with a frontal lesion would have formed statistically too small of a group to compare their executive function with that of non–binge-drinking patients with a frontal lesion. Frontal-subcortical circuits subserving executive functions, however, extend to various other areas in the brain; the most important circuits extend from the lateral prefrontal cortices to the thalamus via the caudate, putamen, and other basal ganglia (Henri-Bhargava et al, 2018). Damage to these diffuse circuits as a result of an ischemic lesion may result in a clinical profile with executive dysfunction that shares similarities with that resulting from dysfunction of the prefrontal cortex itself (Henri-Bhargava et al, 2018). Therefore, ischemic lesions in our stroke patient group may have affected the same frontal-subcortical circuits as episodes of binge drinking did, which may explain the interaction effect we observed.

In several previous studies of adolescents, binge-drinking-related cognitive deficits were shown to be difficult to detect despite detectible differences in the brain function of binge-drinking adolescents compared with non–binge-drinking adolescents (Dager et al, 2014; López-Caneda et al, 2012; Maurage et al, 2009). Other studies have shown that executive functions are especially vulnerable to the toxic effect of alcohol during the prefrontal region’s maturation process in adolescence (Bava and Tapert, 2010; Oscar-Berman and Marinković, 2007). Our results suggest that, in adults, the burden to the brain posed by ischemic stroke may exacerbate preexisting binge-drinking-related cognitive changes, which would have been more subtle (subclinical) prestroke.

A second important study finding is that when the ischemic stroke patients and the HCs were analyzed together, the binge-drinking group’s executive functions were shown to be more impaired than those of the non–binge-drinking group. A history of binge drinking was associated with poor performance on the Stroop Test, which measures one’s capability to inhibit irrelevant responses; the Trail Making Test; and a phonemic fluency test, which measures one’s capability for set-shifting (Miyake et al, 2000). With regard to the Stroop Test, our results corroborated results from a previous study of adults (de Oliveira et al, 2016) and previous studies of adolescents (Sanhueza et al, 2011; Winward et al, 2014a). These studies showed that participants reporting a history of binge drinking had similar difficulties inhibiting irrelevant responses on the Stroop Test as our participants. Our finding of inhibiting dysfunction related to binge drinking is also consistent with previous studies that showed poorer performance in binge-drinking than non–binge-drinking adolescents using various tests to measure inhibition (Bø et al, 2016; Henges and Marczinski, 2012; Parada et al, 2012; Scaife and Duka, 2009; Townshend and Duka, 2005).

As regards set-shifting and cognitive flexibility (determined by the Trail Making Test), the low performance observed in the binge-drinking group in our study of ischemic stroke patients supports previous results obtained using the same test in adolescents (Salas-Gomez et al, 2016; Winward et al, 2014b, 2014c). In our study, the binge-drinking group came up with fewer words on a phonemic fluency test than the non–binge-drinking group, reflecting poor set-shifting ability. Interestingly, we were the first researchers to show this effect of binge drinking using a phonemic fluency test; the only previous study that used this task, in adolescents, failed to show any differences between the binge-drinking and non–binge-drinking groups (Parada et al, 2012). Our results further support the idea that binge-drinking affects set-shifting problems, which links with binge-drinking adolescents using different set-shifting tasks than the ones we used in our study (Scaife and Duka, 2009; Yoo and Kim, 2016).

The third finding of our study, the significant interaction between education and binge drinking, is important but hardly surprising. This interaction indicated that the less education a participant obtained, the more likely that a history of binge drinking would lead to poor performance on all three executive function tests, regardless of additive brain injury/stroke. This result was consistent with an earlier study that associated heavy drinking with slower psychomotor function in low-educated adults with primary school compared with highly educated adults with a secondary school degree (Sabia et al, 2011). Additionally, our results are in line with previous studies associating a higher level of education with fewer stroke-related cognitive deficits, including executive and memory dysfunction (Ojala-Oksala et al, 2012; Sachdev et al, 2004). The lowest education (primary school) and highest education (further education than high school) of our participants corresponded rather well with the education categories used in previous studies by Sabia et al (2011) and Ojala-Oksala et al (2012).

Education is one of the key variables used to measure cognitive reserve (Stern, 2009), and, according to the cognitive reserve hypothesis (Stern, 2009), a high level of education as an indicator of cognitive reserve may lead to clinically normal cognitive readouts, despite brain damage. In accordance with this hypothesis, the interaction effect of stroke and education suggests that several years of education might counterbalance the combined adverse effects of binge drinking on ischemic stroke that was observed in our study.

Altogether, our findings on the effect of binge drinking on executive dysfunction in ischemic stroke patients are of interest because very few studies have previously been able to show the cognitive consequences of binge drinking in adults without AUD (de Oliveira et al, 2016; Virta et al, 2010). In contrast, adults who have a diagnosed AUD consistently present with distinct cognitive deficits (Oscar-Berman, 1980). Even though none of the participants in our study had an AUD, binge drinking was associated with executive dysfunction. Moreover, the self-reported average alcohol consumption was moderate in our sample: The binge-drinking group, on average, consumed 13 standard drinks (22 units) of alcohol per week, which is just inside the weekly limit for low-risk drinking (National Institute on Alcohol Abuse and Alcoholism, 2004).

Previous studies have suggested an inverted U-shaped relation between alcohol use and cognitive outcome, that is, small doses have been suggested to be beneficial for one’s health (Anstey et al, 2009). However, the health benefits of consuming even a small amount of alcohol, including a potential beneficial effect on cognition, have recently been questioned (Topiwala and Ebmeier, 2018). Our results indirectly support the hypothesis that binge drinking without an AUD represents the milder end of the alcohol-related cognitive dysfunction continuum (Stephens and Duka, 2008). In summary, our results suggest that ischemic stroke and binge drinking without an AUD cumulatively add to an individual’s risk of executive dysfunction.

Contrary to our hypothesis based on previous studies in adolescents (Mota et al, 2013; Parada et al, 2011; Winward et al, 2014b; for a review, see Carbia et al, 2018), our study did not find an association between binge drinking and verbal memory in adult ischemic stroke patients. This finding was in discrepancy with previous studies of adolescents (Mota et al, 2013; Parada et al, 2011) using the same Logical Memory subtest of the WMS–R that we used in our study. First, compared to these previous studies, the presence of stroke and age (ie, adult) as factors in our study could have introduced more heterogeneity on memory function. Second, another task we used for measuring verbal memory, a list learning task, was shorter and required less strategy use (Carbia et al, 2018) than the task used in previous studies that found binge-drinking memory dysfunction in adolescents (Parada et al, 2011; Sanhueza et al, 2011).

Study Limitations

One of the limitations of this study is that it employed a cross-sectional design, whereby there may have been a reciprocal link between alcohol use and disinhibition (as previously suggested by Hicks et al, 2012). Executive dysfunction may be both a risk factor for, and a consequence of, binge drinking (for a review, see Verdejo-Garcia et al, 2008). At least in our sample, there was no significant difference in the frequency of developmental attention and learning disorders between the binge-drinking and non–binge-drinking groups. Furthermore, the shortened version of the Alcohol Use Disorder Test (first two questions) that we used is not as reliable in determining binge drinking as a full-length binge-drinking questionnaire. Overall, an alcohol use questionnaire is a subjective estimate and is not as exact and reliable a measure as, for example, blood alcohol concentration. Nevertheless, this shortened version is widely used in clinical settings and has been shown to be effective in identifying heavy drinking (Aalto et al, 2006).

Regarding stroke-related factors, stroke risk has been strongly associated with heavy drinking (Kadlecová et al, 2015). Nonetheless, we found no significant differences in hemispheric stroke side, cardiovascular risk factors, stroke etiology, and/or white matter changes associated with cognitive decline between the binge-drinking and non–binge-drinking groups (Joosten et al, 2013). Thus, it is unlikely that cardiovascular risk factors or clinical conditions other than first-ever ischemic stroke would explain the performance differences in the executive functions observed between the binge-drinking and non–binge-drinking stroke patients in our study. Finally, the conclusions of our study are limited to ischemic stroke patients with a mild to moderate stroke, as stroke severity in our sample was restricted to an NIHSS score of 0 to 13. Further research is needed to determine whether patients with more severe strokes experience a significantly worse additive effect of stroke and binge drinking on their cognitive function.

CONCLUSION

The present study is part of a line of research that is aimed at understanding the adverse effect of alcohol on cognition. The association we found between executive dysfunction and subdiagnostic binge drinking is important because it extends the available literature on adolescents to adults. The current data highlight the risks of alcohol use that does not necessarily meet the criteria for AUD but rather falls within the limit of low-risk drinking. Ours is the first study to show that executive dysfunction caused by an ischemic stroke is more evident in individuals with a history of binge drinking versus non binge drinking. Moreover, we highlight here that a high education level may be an attenuating factor in the combined negative effect of binge drinking and ischemic stroke on all executive function measures. These findings have important clinical and public health implications and suggest that it is worth considering the role of alcohol consumption in the clinical evaluation of conditions such as stroke.

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Keywords:

binge drinking; alcohol; executive functions; cognition; ischemic stroke

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