The Influence of Self-Reported Tobacco Use on Baseline Concussion Assessments

Abstract

INTRODUCTION

Traumatic brain injury (TBI) has become a significant health concern for military veterans, service members, and their families as an estimated 12% to 23% of U.S. Service Members returning from Operations Enduring Freedom, Iraqi Freedom, and New Dawn experienced a TBI while deployed.1 Since the turn of the century, roughly 375 000 TBIs have been diagnosed in U.S. Service Members with the overwhelming majority (82.4%) qualifying as mild (mTBI) or concussion.2 Despite the impact of recent deployments on the incidence rate of concussions in military populations, the majority of cases have occurred in non-deployed settings.3 Concussion is a complex injury that can result in a multitude of symptoms, as well as, functional deficits. Thus, to monitor symptoms and measure impairment post-injury, a number of organizations have endorsed baseline test batteries for high-risk populations like soldiers and athletes.4-6 Baseline test batteries have included clinical tools (eg, Sport Concussion Assessment Tool [SCAT]) and computerized neurocognitive tests (eg, Automated Neuropsychological Assessment Metrics) in various combinations to establish pre-injury symptoms, cognitive function, and balance. Although factors such as sleep,7,8 learning disorders,9 sex,10 fitness level,11 and genetics12 have been shown to influence baseline performance, the effects of tobacco use on baseline assessment scores are unknown.

The U.S. military has an alarmingly high prevalence of tobacco use compared to the civilian population. According to the most recent surveys, 41.2% of active-duty personnel report using one or more forms of tobacco in the past month13 and close to half of the population (49.2%) report tobacco use in the past year.14 Along with the various health hazards, tobacco use has been linked to poor training performance and early discharge from military service.15-17 Furthermore, the tobacco plant contains nicotine, a highly addictive chemical compound known for its stimulant effects. Some studies18,19 suggest that the nicotine within the tobacco plant may improve memory and concentration. However, a lack of nicotine in active tobacco users can cause symptoms (ie, headache, nausea, irritability, and difficulty concentrating) similar to those experienced by individuals post-concussion. Concussion baseline batteries typically include symptom, memory, and concentration assessments. Thus, it is important to understand the influence of tobacco use on these items. This is particularly important in young and active populations that use tobacco and are also at increased risk for concussion.

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Establishing symptom, balance, and cognitive scores pre-injury is an integral piece of the concussion management process.4 However, various factors have been found to affect baseline scores,7-12 thus altering their clinical value post-concussion. Identifying factors that may influence baseline scores is critical to the clinical interpretation of concussion assessments in the pre- and post-test model era. With roughly half of the military population using tobacco products, it is important to understand how cigarette and smokeless tobacco use may influence baseline concussion assessments. Therefore, the purpose of this study was to compare baseline concussion assessment scores between military cadets that report tobacco use and those who do not. Our hypothesis was that military service members who report tobacco use would perform worse on baseline balance and neurocognitive assessments, report more baseline symptoms, and describe increased sensation-seeking scores compared to tobacco nonusers.

METHODS

Study Design and Setting

A cross-sectional design was used to compare baseline concussion assessment scores between military cadets that use tobacco and those who do not. The cadets were recruited from a young physically active population at the United States Military Academy at West Point and the United States Air Force Academy in Colorado Springs. All study procedures were reviewed and approved by the Institutional Review Board at each site and underwent review and approval by their respective Human Research Protections Office. Before data collection, all participants provided informed consent.

Participants

From January 2014 to March 2016, 7358 cadets at two U.S. Service Academies (United States Air Force Academy and United States Military Academy) enrolled in the National Collegiate Athletic Association and the Department of Defense Concussion Assessment, Research and Education (CARE) Consortium Clinical Study Core. At the time of data analysis, 7154 cadets had completed the baseline battery of assessments that included a self-reported tobacco use question. Cadets were eligible to complete a baseline as long as they were not receiving medical care for a concussion. Those with a recent concussion had to be cleared for at least 30-days prior to completing the baseline battery.

Procedures

Cadets enrolled in the CARE Consortium’s Clinical Study Core completed the Level A assessment battery. The Level A battery includes neurocognitive, neurological, postural stability, and symptom assessments and captures demographic and medical history information. Both service academies have implemented the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), Standardized Assessment of Concussion (SAC), Balance Error Scoring System (BESS), SCAT-3 Symptom Evaluation, and Brief Symptom Inventory-18 (BSI-18) into their baseline battery. A detailed description of the CARE methods was previously published.20

In addition to the clinical assessments, the cadets also completed sport, academic, and medical history forms, as well as, an interests and preference survey [Brief Sensation Seeking Scale (BSSS)]. In the medical section, participants were asked about tobacco use. The question read: “Have you used tobacco (eg, smoked, dipped) in the past month?” The responses (eg, yes, no) to this question were used to classify cadets into two groups: tobacco users and tobacco nonusers. If the participant selected “yes,” they were asked to report the number of “cigarettes/cigars” or “cans of dip” used per week. Data were collected via the CARE participant portal, a web-based application, or on case report forms using paper/pencil and entered into the database.

Statistical Analysis

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Initially, descriptive statistics including medians and interquartile ranges and means ± standard deviations were calculated for each dependent variable by the level of the independent variable. The tobacco group (user vs nonuser) served as the independent variable and dependent variables included ImPACT, SAC, BESS, SCAT-3 Symptom, BSI-18, and BSSS scores as summarized in Table I. Total scores were used for the SAC, BESS, BSI-18, and BSSS. ImPACT scores were broken down into the following summary components: impulse control, reaction time, symptom severity, verbal memory, visual memory, and visual-motor speed. Variables for the SCAT-3 Symptom Evaluation included total number of symptoms and symptom severity. Separate Mann-Whitney U-tests were used to compare all baseline assessment scores between tobacco users and tobacco nonusers. Since sex has been shown to influence baseline performance, a secondary analysis stratified by sex was performed. To correct for multiple comparisons an adjusted P-value was used (P < 0.004). Given the large sample size, z values (r = z/√n)21 were used to estimate effect sizes (ES) to interpret the magnitude of significant differences observed between groups.21 ES strengths were interpreted as small (0.01-0.39), medium (0.40-0.69), and large (0.70-1.00).21

RESULTS

Overall, 17.2% of cadets (1178 males, 54 females; 19.98± 1.38 y, 70.93 ± 3.16 in, 181.92 ± 28.75 lbs) that consented to participate in the CARE Consortium CSC reported tobacco use within a month of their initial baseline assessments and 82.8% of cadets (4421 males, 1501 females; 19.64 ± 1.38 y, 69.56 ± 3.68 in, 165.87 ± 27.68 lbs) reported that they had not used tobacco prior to baseline testing. Roughly 19.6% (240/1232) of the cadets who reported using tobacco within a month of testing did not report weekly use of cigarettes or dip and 1.8% (22/1232) did not answer the weekly use question. Of the 79% of cadets who reported weekly tobacco use, 46% smoked cigars or cigarettes, 47% dipped, and roughly 7% smoked and dipped. Weekly tobacco usage is summarized in Table II.

In the non-stratified analyses, group differences were detected for impulse control, ImPACT symptom severity, and the BSSS. More specifically, those who used tobacco performed significantly worse on the impulse control sections of the ImPACT, reported greater ImPACT symptom severity scores, and were more likely to take risks as measured by the BSSS. However, the ESs were very small (0.056-0.184). No differences were detected for BESS, SAC, verbal memory, visual memory, visual-motor speed, reaction time, BSI-18, SCAT-3 total symptom, or SCAT-3 symptom severity scores. Descriptive statistics, P-values, and ESs by the group are reported in Table III.

In the analyses stratified by sex, statistically significant group differences were detected for impulse control, ImPACT symptom severity, and the BSSS scores in males but not females. Males who used tobacco performed significantly worse on the impulse control section of the ImPACT, reported greater ImPACT symptom severity scores, and were more likely to take risks as measured by the BSSS. However, the ESs were relatively small (P = 0.063-0.182). No statistically significant differences were noted between groups for the females. Descriptive statistics, P-values, and ESs for both sexes are reported in Supplementary Tables S1 and S2.

DISCUSSION

Our findings suggest that very subtle differences exist on concussion baseline assessments and in personality traits between military cadets who use tobacco and those who do not. The differences detected were specific to the ImPACT and BSSS. Cadets that reported tobacco use performed significantly worse on the impulse control section of ImPACT and described a greater severity of symptoms prior to the test. These individuals were also more likely to take risks as measured by the BSSS. Despite these differences, other components of the baseline battery were not influenced by tobacco use. Furthermore, these differences were not detected in females when the analysis was stratified by sex. Although it is possible that our female sample was underpowered, as only 54 females admitted to using tobacco in the last month, it should be noted that a much smaller portion of females (3.5%) used or admitted to using tobacco compared to males (26.6%). Overall, our results suggest that tobacco use should at least be taken into consideration when administering concussion baseline assessments and interpreting post-injury assessments in relation to baseline status; however, the effects may be nominal.

In this study, although the ES was relatively small (r = 0.061), military cadets who reported tobacco use in the past month performed worse on the impulse control section of the ImPACT. Although the potential mechanism behind these deficits remains unclear, there have been multiple mechanisms cited explaining the relationship between cigarette smoking and neurocognitive impairment. These have included the direct cytotoxicity to neuronal and glial cells as a result of compounds found in cigarette smoke,22,23 as well as, indirect effects of smoking on obesity and insulin resistance, which have been linked with higher rates of neurocognitive impairment.24 Furthermore, levels of impulsivity are higher in individuals with a history of drug use or abuse,25 which may explain the impulse control deficit noted in the tobacco group. It is also feasible that their decline in performance was due to nicotine withdrawal rather than tobacco exposure. Nicotine withdrawal has been linked to difficulty concentrating and impaired performance within 4 to 12 h of smoking cessation.26-29 However, time since last exposure was not captured, thus it is unclear which mechanism, if any, may have been responsible for the subtle deficits observed in tobacco users in the current study.

Cadets who reported tobacco use also reported greater symptom severity scores on the ImPACT symptom scale. However, this finding was not consistent with the SCAT-3 symptom list scores, as no differences were noted between groups. Both lists have 22 items, however, the ImPACT scale lists nausea, vomiting, fatigue, and low energy as separate items whereas the SCAT-3 combines “Nausea and vomiting” and “Fatigue and low energy” and includes two additional items: “Feeling slowed down” and “More Emotional”. Although the reason for these differences is unknown, our results may have been influenced by the data collection method (ie, electronic versus paper/pencil) or testing sequence. Regardless, knowing that overlap exists between nicotine withdrawal and concussion symptoms (ie, headaches, nausea, difficulty concentrating, irritability, and anxiety), tobacco use should be taken into consideration when conducting baseline testing and evaluating a patient post-concussion. More specifically, the clinician should review prescribed medications, over-the-counter supplements, and lifestyle behaviors that may exacerbate symptoms, such as caffeine, nicotine, or stimulant use.30 Patient education should be tailored to address any factors that may impede performance or recovery.

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Although a few baseline differences were observed between tobacco users and nonusers, in the current study, the ESs were relatively small. The lack of an effect may likely be attributed to imprecision in assessing our subjects’ most recent tobacco use, type of use (eg, regular vs occasional), or tobacco dosage (eg, cans of dip/cigarette packs a day). Furthermore, environmental restrictions at the academy may have limited our subjects’ ability to use tobacco. Thus, the tobacco group may not have been truly representative of tobacco users, throughout the military, and these effects may be larger in another sample (eg, enlisted soldiers, during deployments). Given the small ESs, it is unclear if similar effects would be observed in non-military populations. More research is needed to determine how tobacco influences baseline scores in other populations that use tobacco products, such as major league baseball players and high school athletes. This is particularly important with an increase in nicotine use among athletes in recent years,31 mainly smokeless tobacco.32 Furthermore, other factors, such as testing environment,33 genotypes,12 sleep duration,7,8 and competitive sport34,35 have also been associated with significant baseline differences. Clinicians should be cognizant of the various factors that have the ability to influence baseline scores. These factors should be taken into consideration when administering and interpreting both baseline and post-injury assessments.

Future research should seek to understand the influence of tobacco use on the military-specific assessments, as well as, within a service member population, where environmental factors may contribute to increased tobacco use. Although the differences observed in this study are service academy specific, the results should be considered military-wide as all branches of the military require that service members take a neurocognitive test (ie, Automated Neuropsychological Assessment Metrics or ImPACT) during pre-deployment screening.36 Additionally, post-concussion, the Military Acute Concussion Evaluation is used to gauge severity of symptoms and cognitive deficits. Of particular concern outside of the academy environment is the high prevalence of tobacco use.13 Understanding how tobacco may influence a soldier’s cognitive function pre-injury and what role it may play in exacerbating symptoms post-injury could help guide clinical decision-making.

Limitations

These findings are not without limitations. Administration of the baseline test battery, including the time of day and assessment order, varied within and across service academies. Furthermore, some testing was performed during basic training, when subjects may be sleeping less than normal and fatigued. Despite asking weekly usage, we were unable to accurately dichotomize our tobacco group by usage-behavior (heavy vs light) as the majority of them were light users and regrettably, we did not capture time since their last exposure to tobacco or daily dosage (eg, packs/cans per day). Because of the statistical design and data available, we were unable to account for factors such as sleep, learning disorders, fitness level, and genetics. Lastly, because of the nature of the study design we cannot infer a causal relationship between tobacco usage and poor baseline performance. Future research should seek to minimize the extraneous variables and enhance the study design (ie, case-control, randomized controlled trial) so that inferences can be made about tobacco usage and neurocognitive testing and symptom endorsement. Additionally, the influence of tobacco use on recovery post-concussion should be explored.

CONCLUSIONS

Tobacco users performed significantly worse than tobacco nonusers on the impulse control section of the ImPACT, reported greater symptom severity scores on the ImPACT, and were more likely to take risks as measured by the BSSS. Despite statistical significance, these results should be interpreted with caution, as the overall ESs were very small. In summary, there are a number of factors that may influence baseline scores. Although many of these factors are fixed, some are modifiable and should be taken into consideration when planning and administering baseline assessments. Whenever possible, factors that may influence baseline performance should be recognized and controlled. Based on the current study, tobacco use should at least be documented during baseline testing and taken into consideration when interpreting baseline performance.

FUNDING

This project was supported, in part, by the Grand Alliance Concussion Assessment, Research and Education (CARE) Consortium, funded by the National Collegiate Athletic Association and the Department of Defense. The U.S. Army Medical Research Acquisition Activity, 820 Chandler Street, Ford Detrick MD 21702-5014 is the awarding and administering acquisition office. This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Psychological Health and Traumatic Brain Injury Program under Award No. W81XWH-14-2-0151. Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the Department of Defense.

CONFLICT OF INTEREST

The authors have no conflict of interest to declare.

This manuscript was presented orally at the National Athletic Trainers’ Association Clinical Symposium and AT Expo in Houston, TX on June 27, 2017.

The views expressed are solely those of the authors and do not reflect the official policy or position of the U.S. Army, U.S. Air Force, the Department of Defense, or the U.S. Government.

REFERENCES

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