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Published in final edited form as: Drug Alcohol Depend. 2023 Jan 13;244:109709. doi: 10.1016/j.drugalcdep.2022.109709

Is perception reality? Associations among “light” cigarettes and number of cigarettes smoked per day.

Roberta Freitas-Lemos 1, Allison N Tegge 1,2, Liqa N Athamneh 1, Yu-Hua Yeh 1, William H Craft 1, Jeffrey S Stein 1, Tracy T Smith 3, Irina Stepanov 4, Vaughan W Rees 5, K Michael Cummings 3, Richard J O’Connor 6, Peter G Shields 7, Dorothy K Hatsukami 8, Warren K Bickel 1
PMCID: PMC10081565  NIHMSID: NIHMS1865503  PMID: 36642000

Abstract

Introduction:

Cigarette filter ventilation and light descriptors are associated with lowered perceptions of risk and smoking more cigarettes per day (CPD). This study examined the relationship between usual cigarette ventilation, perception, and CPD.

Methods:

A crowdsourced sample (N=995) of individuals who smoke higher-ventilated (=>20% ventilation) or lower-ventilated (=<10% ventilation) cigarettes identified their usual cigarette as “light” or “full flavor”, and reported their average CPD.

Results:

We found: 1) no association between ventilation status and perception of light versus full flavor (AUC=0.58), with the inaccurate perception being more prevalent in younger individuals (p = 0.041) and those who smoke L&M (73%, p<0.001) and Camel (61%, p=0.006) brands; and 2) perception, but not ventilation of usual cigarette, was significantly associated with CPD (p=0.006), with individuals who perceived their cigarettes as light reporting an average of 13% more cigarettes per day (2.6 CPD), compared to those who perceived their cigarette as full flavor.

Conclusions:

Perceptions of light versus full-flavor, but not ventilation status, predicted CPD. These findings may inform anti-smoking health communication strategies and smoking cessation interventions.

Implications:

Tobacco control policies should eradicate the perception of cigarettes as light or full-flavored. Future research investigating the associations between cigarette filter ventilation and smoking behavior should consider the confounding effects that may lie in an individual’s perceptions of their cigarettes.

Keywords: cigarette descriptors, filter ventilation, light cigarettes, full flavor cigarettes, perceptions

INTRODUCTION

In the 1960s, tobacco manufacturers introduced filter ventilation as a design feature in cigarettes. The use of filter ventilation allowed manufacturers to report lower smoke yields of tar and nicotine using standardized machine testing protocols (Centers for Disease Control and Prevention (CDC), 1997; Kozlowski et al., 1998a; National Cancer Institute, 2001). Moreover, the cigarette industry touted cigarette filter ventilation as a method to reduce smoking-related harm and, in the 1970s, began marketing brands with descriptors such as ‘light’, ‘mild’, or ‘low’ (hereafter referred to as ‘light’), implying light cigarettes were safer than conventional “regular” cigarettes (Alpert et al., 2018). As a result, “less harm” was associated with less harshness and lower tar and nicotine yield among individuals who smoke ventilated cigarettes (Shiffman et al., 2001).

Unfortunately, public health officials and consumers failed to recognize that filter ventilation allowed engagement in compensatory behaviors to get higher nicotine delivery. Achieving higher nicotine intake was possible because the nicotine levels in tobacco are typically similar across cigarettes with varying filter ventilation. These behaviors include taking larger and more frequent puffs, inhaling more deeply, smoking to a shorter butt length, blocking ventilation holes, and smoking more cigarettes per day (Kozlowski and O’Connor, 2002; National Cancer Institute, 2001). Such changes in smoking intensity occur, despite a lack of awareness of filter ventilation (King et al., 2021; Kozlowski et al., 1998b), because most individuals who smoke try to maximize their nicotine intake to reach rewarding sensations and to avoid the negative effect of nicotine withdrawal (Benowitz and Others, 2001). In fact, contrary to cigarette manufacturers’ marketing, smoking light cigarettes does not reduce toxicant exposure, nor cancer and other diseases risks compared to smoking brands described as regular or full flavor (National Cancer Institute, 2001) and may actually increase harm (Song et al., 2017).

The Family Smoking Prevention and Tobacco Control Act (2009) prohibits misleading cigarette descriptors such as light on tobacco product labels, packaging, or advertising in the US. Even though the ban was implemented more than a decade ago, cigarette manufacturers employ other communication strategies, including color-coded packaging (e.g., silver) and other descriptors (e.g., smooth) to communicate the impression of light (Hammond and Parkinson, 2009; King et al., 2010; Wakefield et al., 2002). Indeed, misperceptions about light cigarettes being less harmful persisted after the ban (Carroll et al., 2021; Yong et al., 2016, 2011).

Because of industry marketing, it is reasonable to assume that many individuals who smoke may have associated brands described as light and low tar with higher filter ventilation, whereas those smoking regular and full flavor brands are associated with lower filter ventilation. Even 10 years after the removal of light and low tar brand descriptors on packs and in advertising, many individuals who smoke still believe that brands that are more highly ventilated are less dangerous (Leas et al. 2017). However, inaccurate perception of light versus full flavor and ventilation of usual cigarettes (i.e., lower-ventilated cigarettes perceived as light and higher-ventilated cigarettes perceived as full flavor) may exist due to the multiple cigarette varieties available in a range of package colors, other descriptors, and lack of awareness of filter ventilation levels. Whether the perception of light versus full flavor or ventilation status drives current smoking behavior remains an important unanswered question. Experimentally disentangling these labels from each other may provide insightful information.

This study examined the relationship between an individual’s usual cigarette ventilation, perception of light versus full flavor, and smoking behavior measured by CPD. To accomplish this, two competing hypotheses were tested: the ventilation-driven hypothesis and the perception-driven hypothesis. In the ventilation-driven hypothesis, we examined the relationship between cigarette ventilation status, that is, ‘higher-ventilated cigarettes’ (HVCs; => 20% ventilation) or lower-ventilated cigarettes (LVCs; <=10% ventilation), and CPD. In the perception-driven hypothesis, we examined the relationship between a participant’s perception of their usual cigarette (i.e., ‘light’ or ‘full flavor’) and CPD.

METHODS

Participants

Participants (N=2204) were recruited between August 2020 and June 2021 from Amazon Mechanical Turk (Mturk). Respondents completed a screening questionnaire to determine eligibility. Participants were eligible if they: 1) were 21–65 years old, 2) selected cigarettes as their primary source of nicotine, 3) smoked at least 10 CPD on average during the last 30 days, and 4) reported smoking either an HVC or LVC. Participants provided electronic informed consent, approved by an Institutional Review Board at Virginia Polytechnic Institute and State University.

Procedure

Participants completed an online survey (Qualtrics, Provo, UT). The survey contained demographic questions, tobacco use history, and measures of tobacco dependence. This study is part of a larger study that examined the effect of cigarette packages’ health warnings on tobacco purchasing. The mean survey completion time was approximately 38 minutes. Compensation included a $2.00 payment for completing the survey and an additional $3.00 bonus depending on responses to attention and instructional quiz. Additionally, inclusion required passing a CAPTCHA verification at the beginning and end of the survey.

Data cleaning

Mturk is a crowdsourcing option for researchers to screen, enroll, and compensate a large number of participants. Despite the flexibility and utility of crowdsourcing platforms, poor-quality data is often an area of concern (Chmielewski and Kucker, 2020). Data quality has been associated with completing a series of attention checks and systematic responses (Craft et al., 2022). To mitigate potential poor quality data, we removed individuals that failed an attention check question (“Which would you rather have? $500 now or $1000 now; n=631) and provided non-systematic discounting data, according to Jonhson and Bickel (2008) criteria (n=578). Note that delay discounting was a primary outcome measure in the larger study. Our final sample size used in this analysis was N=995 (45% of the full sample). A post hoc power analysis was performed using the observed effect size between perception and CPD (Cohen’s d=0.18; small effect size), and found we achieved 80.9% power.

Study measures

Demographics.

Participant information was collected, including age, gender, race, ethnicity, education level, and personal income.

Cigarette dependence.

The Fagerstrom Test for Cigarette Dependence (FTCD) was administered to determine the level of nicotine dependence (Fagerström, 2012).

Perception of light versus full flavor.

A single item assessed which cigarette descriptor participants considered to best describe their usual cigarette. “Which of the following words best describes the type of cigarette you smoke?” Participants chose between light or full flavor.

Ventilation level of usual cigarette.

A two-item questionnaire was used to identify participants’ usual cigarettes. First, participants selected their usual brand of cigarettes from a list of 15 brands. Then, participants chose a picture of their usual style and flavor from the reported brand. Cigarette ventilation levels (HVCs; => 20% ventilation and LVCs; <=10% ventilation) were determined based on a list of 164 cigarette styles as in Freitas-Lemos (2021). Participants who reported smoking a different cigarette were not included in the study. Cigarette ventilation levels were assessed using general methods previously described (O’Connor et al., 2008). Study-specific procedures are described in Carroll et al. (2021). Participants were required to be from the United States and have at least a 90% acceptance rate by previous requesters.

Perception accuracy.

A participant is defined as having an inaccurate perception of their cigarettes if individuals who smoke HVCs perceive their usual cigarettes as full flavor and individuals who smoke LVCs perceive their usual cigarettes as light. All other participants are considered to have an accurate perception of their cigarettes.

Cigarettes per day.

A single item assessed the number of CPD: “During the past month, how many individual cigarettes did you smoke during an average day?” Participants entered a numeric value in a text box.

Statistical Analysis

Participants’ characteristics are summarized using means (standard deviations) and frequencies (percentages) and compared between the two groups (ventilation: HVC and LVC; or perception: light and full flavor) using t-tests and Fisher’s exact tests, where appropriate. Effect sizes for significant differences are reported using Cohen’s d (1988) for continuous and Phi (Funder and Ozer, 2019) for categorical measures, performed using the effectsize package in R (Ben-Shachar et al., 2020).

Predictive performance of ventilation levels on preference was evaluated using a Receiver Operator Characteristic (ROC) curve and summarized using the area under the ROC curve (AUC). Age differences were compared between perception accuracy (accurate versus inaccurate) using linear regression, and differences in perception accuracy rates across cigarette brands were determined using Fisher’s exact test. Note that Basic, Doral, Merit, Parliament, and Salem brands were combined into an “other” category due to their low occurrence (<5 participants each) in the dataset.

First, univariate linear regressions were performed with CPD as the outcome measure and perception of light versus full flavor, usual cigarette filter ventilation, and participants’ characteristics (i.e.. age, gender, race, ethnicity, education, annual income, and FTCD score) as the explanatory variables. Second, to explore the impact of potential confounders, we performed a multiple linear regression of participants’ characteristics, perceptions of light versus full flavor, and usual cigarette filter ventilation. Model selection was performed to determine the optimal model, including covariates. The exhaustive model space was queried to determine the final set of explanatory variables to model CPD as the outcome variables. The model with the lowest Bayesian Information Criterion (BIC) was selected as the optimal model. All analyses were completed in R with a significance level determined by p<0.05.

RESULTS

Participants’ characteristics

Demographic characteristics and tobacco-related assessments were compared between the groups (light versus full flavor and HVC versus LVC). Participants’ characteristics are reported in Table S1 in the Supplementary Materials. When comparing perception of light versus full flavor, we observed significant differences for gender (p=0.023; effect size = 0.09; “very small”), race (p=0.025; effect size = 0.12; “small”), education (p<0.001; effect size = 0.27; “medium”), and income (p<0.001; effect size = 0.16; “small”). Moreover, when comparing usual cigarette ventilation (i.e., HVCs versus LVCs), we observed significant differences for age (p<0.001; effect size = 0.30; “small”), gender (p=0.022; effect size = 0.09; “very small”), and education (p=0.002; effect size = 0.13; “small”). Interestingly, significant differences were observed in menthol status between those who perceived their usual cigarette as light or full flavor p<0.001; effect size = 0.12; “small”) and the FTCD scores between individuals who smoke HVCs and individuals who smoke LVCs (p=0.003; effect size = 0.19; “very small”). Note that these effect sizes range from very small (gender) to medium (education). Sensitivity analysis was conducted to compare the demographics of included and excluded participants (Table S2).

Association between perception and ventilation of usual cigarette

An association between cigarette ventilation and perception was not observed. Of individuals who smoke HVCs, 292 (53.48%) individuals perceived their usual cigarettes as light, while 254 (46.52%) individuals perceived them as full flavor. Of individuals who smoke LVCs, 184 (40.98%) individuals perceived their usual cigarettes as light, while 265 (59.02%) individuals perceived them as full flavor. Individuals with inaccurate perceptions reported smoking a significantly different number of CPD (F(2,992) = 6.091, p = 0.002), with individuals who smoked LVCs but perceived their usual cigarette as light reporting 23.6 CPD on average and individuals who smoked HVCs but perceived their cigarette as full flavor, reporting 18.7 CPD. Moreover, individuals with inaccurate perception were on average 1.4 years younger than those with accurate perception (F(1,993) = 4.185, p = 0.041).

Using a ROC curve, ventilation level was explored as a continuous measure to see whether ventilation was associated with accurate perception. Participants indicated a poor predictive performance of the classification of the cigarettes they smoked (AUC = 0.58; Figure 1A). For reference, an AUC of 0.5 would indicate a random association, and an AUC of 1.0 would be a perfect classifier. Our observed AUC of 0.58, though improved from a random classifier, does not provide substantial predictive performance. This is also supported by the roughly uniform distribution of participants’ perceptions across the two ventilation groups.

Figure 1.

Figure 1.

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(A) ROC curve indicating the predictive performance of ventilation levels on perception of light or full flavor cigarettes. The diagonal line indicates the performance of a random classifier. (B) Proportion of individuals with inaccurate perception grouped by cigarette brand. The vertical dashed line indicates the studywide inaccurate perception rate. Error bars represent the standard error of the estimate.

Additionally, we investigated which brands were leading to inaccurate perceptions (Figure 1B). The proportion of inaccurate perception for each cigarette brand was compared to the study-wide inaccurate perception rate of 44%. L&M (73%, p<0.001) and Camel (61%, p=0.006) showed higher rates of inaccurate perception compared to the study-wide average. Whereas Marlboro (32%, p<0.001) and Eagle (28%, p=0.014) indicated lower rates of inaccurate perception compared to the study-wide average.

Testing for the competing hypotheses on CPD

Next, we explored which hypothesis (i.e., ventilation-driven or perception-driven) was more predictive of our outcome measure, CPD. First, we examined the univariate relationship between our predictors and outcome measure of CPD (Table 1). In this analysis, perception was significantly associated with CPD (F(1,993)=7.731l, p=0.006). Specifically, individuals who perceived their cigarette as either light or full flavor reported consuming an average of 22.2 and 19.6 CPD, respectively. However, ventilation was not significantly associated with CPD (F(1,993) = 3.307, p=0.069), with individuals who smoked HVC and LVC reporting an average consumption of 20.1 and 21.8 CPD, respectively. Note that age, race, education, and FTCD were significantly associated with CPD (Table 1; age: p=0.009; race: p=0.007; ethnicity: p=0.004, education: p=0.007; FTCD: p<0.001). Gender was not associated with CPD.

Table 1.

Univariate linear regression associations of CPD and sample characteristics.

Variable Cigarettes per day P-value
Perception of light versus full flavor F(1,993) = 7.731 0.006
Cigarette filter ventilation F(1,993) = 3.307 0.069
Cigarette flavor F(1,993) = 1.319 0.251
Age F(1,993) = 6.950 0.009
Gender F(3,991) = 1.919 0.125
Race F(7,987) = 2.777 0.007
Ethnicity F(1,993) = 8.271 0.004
Education F(4,990) = 3.585 0.007
Annual Income F(3,991) = 1.237 0.295
FTCD F(1,993) = 16.620 <.001
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To investigate the competing hypotheses, model selection using ventilation, perception of light versus full flavor, and additional participant characteristics. The optimal model identified with the lowest BIC included perceptions, age, and FTCD (Table 2). When considering the inclusion probability of both ventilation and perceptions given the observed data, perception had a 63% probability of being included in the model, while ventilation had a 10% probability of being included.

Table 2.

Linear regression associations of CPD and sample characteristics after model selection.

Cigarettes per day
Adjusted coef. (95% CI)a p-value
Perception b 2.629 (0.845, 4.414) 0.004
Age −0.129 (−0.218, −0.040) 0.004
FTCD 0.953 (0.508, 1.399) <.001
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Note: Cl = confidence interval

a

Model selection was performed to investigate the inclusion of smokers’s usual cigarette filter ventilation, perception of light versus full flavor, age, gender, race, ethnicity, education, annual income, and FTCD score. Note after model selection, only smoker’s perception about their usual cigarette, age and FTCD remained in the model for CPD.

b

Full flavor is the reference level

DISCUSSION

This study examined the putative relationship among factors: ventilation level, perception of light versus full flavor, and CPD. The two primary results of this study are: 1) ) contrary to our original hypothesis, an association between ventilation level (i.e., higher or lower) and perception of light versus full flavor was not observed, with higher rates of inaccurate perceptions being more prevalent in younger individuals and those who smoke L&M and Camel brands; and 2) perception, but not ventilation of usual cigarette, was significantly associated with CPD, with individuals who perceived their cigarettes as light reporting an average of 2.6 more CPD (13% more) compared to those who perceived their cigarette as full flavor.

Even though some congruence between the perception and ventilation of usual cigarettes was observed, with the majority of individuals who smoked HVCs describing their cigarettes as light and individuals who smoked LVCs describing their cigarettes as full flavor, the association between the two variables was not significant. The lack of association could be due to a number of factors, including the opportunity for individuals who smoke ventilated cigarettes to adjust their nicotine intake and, therefore, not perceive their cigarettes as light. We observed that inaccurate perception was higher in younger individuals, which could be related to more limited exposure to cigarette descriptors on cigarette packages before they were prohibited and/or to brand descriptors (i.e., natural) or product features (i.e., pack colors) that are popular with younger individuals. Additionally, our study found that L&M and Camel brands exhibited the highest rates of inaccuracy, which may reflect how these brands have been marketed (Alpert et al., 2018). Our finding confirms that ventilation and perception of light versus full flavor are not concordant and should not be used interchangeably. To the best of our knowledge, we are the first study to attempt to disentangle filter ventilation (quantitative; percentage) from user-supplied cigarette descriptors (qualitative; light or full flavor).

Our findings of a significant association between perception of light and increased CPD is consistent with previous studies indicating that individuals who smoke and perceive their cigarettes as less harmful increase their exposures (Kozlowski and O’Connor, 2002). The number of CPD and the intensity of smoking are important determinants of exposure to tobacco smoke and increase the risk for adverse health outcomes, including heart disease and cancer (Hartono et al., 2019; Wolf et al., 1988). We observed a 13% increase in CPD for individuals who perceive their cigarettes as light, an appreciable difference. Hence, eliminating the misconception that light is healthier is imperative.

The marketing of light cigarettes was inherently misleading and dangerous because individuals adopted ventilated cigarettes under the false belief that they were safer due to presumed lower exposure to tar and nicotine. Filter ventilation is almost universally used in cigarettes today and is one of the ways manufacturers engineer cigarettes to allow individuals to adjust their nicotine delivery. Consistent with a previous study using PATH data that did not find significant relationships between filter ventilation and smoking outcomes (Carroll et al., 2021), the current study did not find a significant association between ventilation and CPD. Our findings, however, do not rule out that individuals who smoke HVCs could be exhibiting other compensatory smoking behaviors to circumvent smoke dilution and adjust their puffing patterns to get nicotine, such as inhaling longer, harder, more frequent puffs, and blocking the ventilation holes (Benowitz, 2001).

Regarding policy recommendations, our findings suggest that individuals’ perceptions of light versus full flavor could be targeted to decrease CPD. With regard to perceptions about light cigarettes, at least two policy directions could be taken. First, enhancing health communication efforts to eradicate the perception of cigarettes as light or full-flavored, as the perception of lightness is incorrect and misleading. Complimentary, individuals who smoke should be informed that cigarettes originally conveyed as light are not less harmful, and their use does not result in less nicotine consumption. For example, public service announcements could target demographics associated with brands that yield higher perception rates of light cigarettes. Second, increasing regulation of any features (e.g., pack colors, other descriptors) that may contribute to the perception of usual cigarettes as light (O’Connor and Hammond, 2018; Yong et al., 2016). Physical design of cigarette packs has been shown to influence perceptions about the products (Talhout et al., 2018). For example, multiple countries, such as Australia and Canada, have implemented a standardized packaging policy to remove positive associations between branding and smoking (Gravely et al., 2021).

The strengths of this study should be taken into consideration of its potential limitations. First, this sample is majority White and Non-Hispanic and smokes at least 10 cigarettes per day; therefore, the relevance of these findings to the broader population of individuals who smoke is unknown. However, the socioeconomic status of our sample is diverse, with participants endorsing a variety of income and education levels. Second, differences in demographics were observed between included and excluded participants. However, demographic differences have been noted in prior studies with individuals with substance use from Mturk (e.g., Freitas-Lemos et al., 2021a). Second, the online nature of this study potentially biases the findings, though a previous investigation has noted concordance between in-person and online research findings (Casler et al., 2013). Third, the ventilation cutoffs used in this study were those from a prior investigation; however, we acknowledge that different levels may lead to other findings.

As cigarette industry documents reveal, marketing strategies to modify the perception of cigarette harm (and not the health risk) to increase sales have long been employed (Morris, 1966; Senkus, 1953). Although this relationship is not novel, the present findings reinforce experimentally the enduring effect of attributing light descriptors to cigarettes. In light of these challenges, this study emphasizes the need for future research investigating associations between cigarette ventilation and smoking behavior to consider the confounding effects of an individual’s perceptions of their cigarette’s ventilation level.

Supplementary Material

1

Highlights.

  • No significant association between ventilation and perception of light or full flavor

  • Perception of light versus full flavor associated with increased smoking

  • Higher levels of cigarette filter ventilation not associated with increased smoking

Role of Funding Sources

Research reported in this publication was supported by the National Institutes of Health, National Cancer Institute grant (grant number 5P01CA217806 and 5R01CA179246). The content is solely the author’s responsibility and does not necessarily represent the official views of the NIH. All authors have contributed, read, and approved this version of the manuscript.

Although the following activities/relationships do not create a conflict of interest pertaining to this manuscript, in the interest of full disclosure, Dr. Bickel would like to report the following: W. K. Bickel is a principal of HealthSim, LLC; BEAM Diagnostics, Inc.; and Red 5 Group, LLC. In addition, he serves on the scientific advisory board for Sober Grid, Inc., and Ria Health, is a consultant for Alkermes, Inc., and works on a project supported by Indivior, Inc. Dr. Cummings and Dr. Rees serve as a paid expert witnesses in litigation against cigarette manufacturers.

Footnotes

Author Agreement Statement

We declare that this manuscript is original, has not been published before and is not currently being considered for publication elsewhere.

We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us. We understand that the Corresponding Author is the sole contact for the Editorial process. He is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs.

CRediT authorship contribution statement

Roberta Freitas-Lemos: Software, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration. Allison N. Tegge: Validation, Formal analysis, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization. Liqa N. Athamneh: Writing - Original Draft, Writing - Review & Editing. Yu-Hua Yeh: Writing - Original Draft, Writing - Review & Editing. William H. Craft: Writing - Original Draft, Writing - Review & Editing. Jeffrey S. Stein: Conceptualization, Methodology, Writing - Review & Editing. Tracy T. Smith: Writing - Review & Editing. Irina Stepanov: Writing - Review & Editing. Vaughan W. Rees: Writing - Review & Editing. K. Michael Cummings: Writing - Review & Editing. Richard J. O’Connor: Writing - Review & Editing. Peter G. Shields: Writing - Review & Editing, Supervision, Funding acquisition. Dorothy K. Hatsukami: Writing - Review & Editing, Supervision, Funding acquisition. Warren K. Bickel: Conceptualization, Methodology, Resources, Writing - Review & Editing, Supervision, Funding acquisition.

Conflict of interest

The other authors report no conflict of interest.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Data availability statement

Readers are encouraged to email wkbickel@vtc.vt.edu to obtain more data for this study.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1865503-supplement-1.docx (22KB, docx)

Data Availability Statement

Readers are encouraged to email wkbickel@vtc.vt.edu to obtain more data for this study.

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