Abstract
Objective
To assess lifestyle characteristics among parental electronic cigarette (e-cigarette), marijuana and tobacco users.
Methods
A total of 1214 parents (77% mothers and 23% fathers) were surveyed and categorized into five exposure groups: e-cigarette use only (1%), marijuana use only (3%), tobacco products only (10%), multi-exposed [11% (marijuana, e-cigarette and tobacco)], and non-users [75% (no e-cigarette, tobacco or marijuana)].
Results
Similar to non-users, the e-cigarette group had no illicit drug use. Further, e-cigarette users were more likely, in adjusted models, to self-identify as non-smokers and exercise compared with tobacco and multi-exposed groups. Although marijuana users also had higher odds of self-identifying as non-smokers compared to tobacco and multi-exposed groups, they were more likely than non-users to drink alcohol.
Conclusion
E-cigarette and marijuana using parents were less likely to identify as smokers. E-cigarette users had healthier lifestyle characteristics than the other exposed groups. Clinicians should consider specifically screening for parental e-cigarette and marijuana use as assessing for only “smoking” may underrepresent first-and second-hand exposure. Additionally, clinicians should be aware that marijuana using parents are more likely to drink alcohol and should counsel accordingly.
Introduction
Rates of combustible tobacco use have been declining over the past several decades [1]. Yet electronic cigarette (e-cigarette) use is increasing in adults ≥25 years, having doubled to 4.2% between 2012 and 2014 [1]. Among e-cigarette users, 11.4% vape exclusively, having never smoked tobacco [2]. In contrast, 60% of e-cigarette users supplement vaping with traditional cigarette use [2]. Furthermore, exclusive e-cigarette users are at increased risk for initiating subsequent combustible cigarette use within 2 years [3], [4], [5], [6], [7]. Almost a third of women in Oklahoma and Texas who use both e-cigarettes and combustible tobacco report using both products in the preconception period [8]. Further, 6% of non-smokers vaped >3 months before pregnancy. However, this rate was reduced to 0.5% during the last 3 months of pregnancy [8].
Though perceived as safer than traditional cigarettes [9], e-cigarettes contain potentially toxic inhalants such as formaldehyde, acetaldehyde and acrolein [10]. As a result, oxidative stress and inflammatory responses in the lung and irritation throughout the respiratory tract are potential consequences of e-cigarette use [11]. The chemicals present in e-cigarette aerosols are mutagenic and may, in users, increase risk of cancer and adverse reproductive outcomes [10]. Several of these substances cross the placenta and may impact the developing fetus [12]. In animal models, exposure to e-cigarette vapor during pregnancy is linked with both greater maternal and neonatal inflammatory markers [13]. Although there are no human studies, there is a higher risk of decreased body weight, impaired postnatal lung growth, and impaired cardiac function for offspring born to pregnant animals exposed to e-cigarette vapor [14]. Animal models have also demonstrated an association between maternal e-cigarette exposure with long-term cognitive and epigenetic effects in offspring [15].
Similar to rates of e-cigarette use, marijuana use is highest among adults of reproductive age [16]. Marijuana and traditional cigarette use occur in up to 21% of young adults [17]. In contrast to alcohol and combustible tobacco consumption, marijuana use is increasing among pregnant women coincident with state-based legalization [18], [19]. Rates of marijuana use may be further underestimated based on self-report alone as Young-Wolff et al. [20] found that prevalence of marijuana use during pregnancy was higher based on toxicology than by patient recall [20]. Use among parents with children less than 18 years of age has also risen from 4.9% in 2002 to 6.8% in 2015, increasing risk for childhood marijuana exposure [21].
Tetrahydrocannabinol is absorbed through the lungs and rapidly enters the blood stream reaching the brain within minutes [22]. Heavy, chronic use in young people can lead to long-term impairment of attention and memory which worsen with persistent use and early initiation [22]. Combustible marijuana has similarly harmful constituents as tobacco smoke [23]. Although evidence suggests that the risk of lung cancer is lower than with tobacco, marijuana smoking is also associated with adverse lung health such as inflammation of large airways, lung hyperinflation and chronic bronchitis [22].
Tetrahydrocannabinol rapidly crosses the placenta enabling concentrations in fetal blood to closely resemble those in maternal blood [24]. Thus, the fetus has an increased risk of exposure to marijuana and resultant adverse birth outcomes. Pregnant women using marijuana exclusively had 12 times greater odds of miscarriage or stillbirth as compared with non-users [25]. Additionally, marijuana use during pregnancy is associated with preterm labor, preterm birth, and decreased birth weight [24], [26]. Infants with prenatal marijuana exposure are more likely to be admitted to the neonatal intensive care unit [26], [27]. Maternal marijuana use has been linked with long-term outcomes in children such as poor cognitive performance and increase behavioral problems such as depressive symptoms, anxiety and inattentiveness. However, there is currently insufficient evidence to establish causality [24], [28], [29], [30].
Despite these toxicities, pregnant women and adults of reproductive age perceived marijuana and e-cigarettes as safer than combustible tobacco [8], [31], [32], [33], [34], [35], [36]. Rates of both e-cigarette and marijuana use are increased with perception of decreased harm [37], [38]. Parental utilization of other substances with adverse health consequences such as illicit drugs and tobacco are associated with less healthy behaviors including decreased exercise [39], [40]. However, there is a paucity of data on the associated lifestyle behaviors of marijuana and e-cigarette users, particularly among parents of newborns. Therefore, we sought to assess lifestyle characteristics, including identification as a non-smoker, exercise, alcohol use and illicit drug use, in relation to parental use of e-cigarettes and marijuana.
Materials and methods
This is an analysis of self-administered survey data collected from parents of live-born infants at Maria Fareri Children’s Hospital (MFCH) at Westchester Medical Center, Valhalla, NY, USA and six affiliate birthing hospitals in the Hudson Valley Region of New York. Inclusion criteria were parents ≥18 years of age, with singleton live births, who speak Spanish or English. Parents were excluded if they spoke a language other than Spanish or English, were <18 years of age, did not have the capacity to consent, or had multiple births. Surveys were administered between July 2016 and July 2018. The study was approved by the NY Medical College Institutional Review Board for the Protection of Human Subjects. We have complied with the World Medical Association Declaration of Helsinki regarding ethical conduct of research involving human subjects.
Data collection
Survey tools: Maternal and paternal survey tools (Supplementary Material) were adapted from the Center of Disease Control’s Pregnancy Risk Assessment Monitoring System-Phase 7 [41], the National Institutes of Health and Food and Drug Administration collaborative study – Population Assessment of Tobacco and Health [42], the National Health and Nutrition Examination Survey [43] and the U.S. Census Bureau [44]. The validated survey included 39 questions in the maternal survey and 37 in the paternal questionnaire. Maternal surveys differed from paternal by a question on prenatal care and smoking cessation during pregnancy.
Variable definitions
Exposure groups included exclusive e-cigarette users, exclusive marijuana users [marijuana, pot, bud, hashish, K2 (synthetic marijuana)], tobacco product users (hookah, smokeless tobacco, snus pouches, cigarettes and cigars), multi-exposed (two or more of e-cigarette, marijuana or tobacco products), and non-users (absence of e-cigarette, tobacco or marijuana products). E-cigarette use was defined as use 12 months prior to or during the pregnancy [42]. Tobacco use was defined as use 3 months prior to or during pregnancy [42]. Marijuana use was defined as use 1 month prior to or during pregnancy [41].
Lifestyle behaviors include physical activity, identification as a non-smoker, alcohol use and substance use. Physical activity was defined as exercise ≥3 days per week or <3 days per week during the 12 months prior to the pregnancy [41]. Alcohol use was defined as any use 3 months prior to or during the pregnancy [41]. Illicit drug use included use of cocaine, amphetamines or tranquilizers 1 month prior to or during pregnancy [42].
Covariates included demographics such as age, education, marital status, employment, race/ethnicity and adverse life events. Education was defined as less than or at least completion of high school or greater (includes some college or associate’s degree, Bachelor’s degree and advanced degree) [35], [42], [45]. Subjects were considered married if they self-reported being married or in a domestic partnership and not married if separated, single, never married, widowed or divorced [43], [46]. Adverse life events were defined by 14 factors including homelessness, trouble paying rent or mortgage or other bills, family sickness, partner incarceration, unwanted pregnancy, divorce, military deployment, partner separation, partner discord, the death of a close relative/friend, the presence of excessive alcohol or drug use in a close family member/friend and reduced or loss of employment [41]. Adverse life events score included the total number of factors reported and was categorized into those reporting ≥3 events and <3 events [47].
Statistical analysis
Lifestyle behaviors, covariates and demographics were compared by e-cigarette use, marijuana use, tobacco use, multi-exposed and non-use in bivariate analysis using chi-square (χ2) or Fisher’s exact tests. Multiple logistic regression models were used to determine odds ratios and 95% confidence intervals (CI) for the association of parental exposures and lifestyle behaviors while controlling for covariates. These covariates were selected if they had a P-value of 0.1 or less in the bivariate analysis. Final models controlled for race/ethnicity, age in years, gender, education and adverse life events score. Separate models were conducted using exclusive e-cigarette users and exclusive marijuana users as reference categories. Due to paucity of illicit drug use, multivariate analysis of this behavior could not be conducted. Receiver operator characteristic (ROC) curves with concordance index (C-statistic) were generated to assess predictive accuracy modeling. Statistical significance was determined by a P value less than 0.05. Analyses utilized STATA version 14.0 (Stata Corporation, College Station, TX, USA).
Results
A total of 1689 mothers and 811 fathers were approached of which 969 mothers and 297 fathers consented (Figure 1). Fifty-two were excluded, two of which withdrew consent and 50 had incomplete consent forms. A total of 1214 subjects were included in the analysis. The maternal response rate was 57% and paternal response rate was 37%. There were 1% e-cigarette users, 3% marijuana users, 10% tobacco product users, 11% multi-exposed and 75% non-users.
Flow diagram of subjects approached, consented, and included by exposure group.
E-cigarette, e-cigarette use only; marijuana, marijuana use only; tobacco, tobacco product use only; multi-exposed, any combination of e-cigarette, marijuana or tobacco products; non-user, neither e-cigarette, marijuana, nor tobacco use.
Bivariate analysis
Table 1 shows the characteristics among exposure groups (e-cigarette, marijuana, tobacco, multi-exposed and non-users). Tobacco users and non-users were on average older than e-cigarette users, marijuana users and multi-exposed. The multi-exposed had fewer Hispanic and more White parents compared with other groups. Mothers were more likely to be e-cigarette users or non-users compared to fathers. E-cigarette users were least likely to have attained education beyond high school, and non-users were more often married. The multi-exposed had the highest rate of adverse life events. Employment status was similar among all groups.
Demographics and characteristics by exposure groups.
| n (%) | E-cigarette n=17 | Marijuana n=40 | Tobacco n=123 | Multi-exposed n=128 | Non-user n=906 | P-value | |
|---|---|---|---|---|---|---|---|
| Age | 18–24 | 5 (29) | 14 (35) | 26 (21) | 38 (30) | 143 (16) | <0.001 |
| 25–35 | 9 (53) | 19 (48) | 70 (57) | 68 (53) | 504 (56) | ||
| >35 | 3 (18) | 7 (18) | 27 (22) | 22 (17) | 249 (28) | ||
| Gender | Male | 3 (8) | 14 (35) | 43 (35) | 46 (36) | 173 (19) | <0.001 |
| Female | 14 (82) | 26 (65) | 80 (65) | 82 (64) | 733 (81) | ||
| Race | White | 8 (47) | 15 (38) | 51 (44) | 70 (57) | 338 (40) | 0.008 |
| Black | 3 (18) | 8 (21) | 20 (17) | 25 (20) | 134 (16) | ||
| Hispanic | 6 (35) | 16 (41) | 41 (35) | 25 (20) | 327 (38) | ||
| Other | 0 (0) | 0 (0) | 5 (4) | 3 (2) | 56 (7) | ||
| >High schoola | 6 (35) | 21 (54) | 65 (53) | 59 (47) | 579 (65) | <0.001 | |
| Employed | 11 (65) | 24 (60) | 74 (61) | 76 (59) | 572 (64) | 0.797 | |
| Married | 11 (65) | 17 (51) | 57 (52) | 45 (41) | 632 (72) | <0.001 | |
| Adverse life eventsb | 1 (6) | 5 (13) | 29 (24) | 57 (45) | 95 (10) | <0.001 | |
| Identify as non-smoker | 12 (71) | 26 (65) | 32 (26) | 11 (9) | 869 (96) | <0.001 | |
| Exercise for ≥3 days | 11 (65) | 17 (43) | 47 (39) | 45 (36) | 392 (44) | 0.111 | |
| Alcoholc | 8 (47) | 29 (73) | 83 (67) | 87 (68) | 430 (47) | <0.001 | |
| Illicit drug used | 0 (0) | 1 (3) | 1 (1) | 14 (11) | 0 (0) | <0.001 | |
aMore than completion of high school. bScore including ≥3 events. cUse 3 months prior to or during pregnancy. dUse 1 month prior to or during pregnancy. E-cigarette, e-cigarette use only; marijuana, marijuana use only; tobacco, tobacco product use only; multi-exposed, any combination of e-cigarette, marijuana or tobacco products; non-user, neither e-cigarette, marijuana, nor tobacco use. Bold designates P<0.05.
E-cigarette users and marijuana users were more likely to identify as non-smokers than tobacco users and the multi-exposed. Non-users were most likely to report non-smoking status. Groups did not differ in rates of exercise. E-cigarette users and non-users had the lowest rates of alcohol use while marijuana users had the highest. The multi-exposed had the highest rate of illicit drug use. There was no illicit drug use in the e-cigarette and non-user groups precluding further multivariate analysis.
Multivariate analysis
Table 2 shows results of multivariate models using e-cigarette users and marijuana users as reference groups and controlling for age, race/ethnicity, gender, education and adverse life events. Other than non-users, e-cigarette users exhibited the healthiest lifestyle characteristics, including higher odds of identifying as a non-smoker and increased odds of exercise compared to tobacco users and the multi-exposed. Although, marijuana users were more likely than tobacco users and the multi-exposed to identify as non-smokers, they were more likely than non-users to consume alcohol.
Multivariate logistic regression comparing behaviors among groups to e-cigarette and marijuana.
| Outcome: lifestyle behaviorsa | Marijuanab | E-cigarettec | |||
|---|---|---|---|---|---|
| OR (95% CI) | C-statistic | OR (95% CI) | C-statistic | ||
| Not exercise ≥3 days | E-cigarette | 0.35 (0.1–1.2) | 0.62 | 1 (ref) | 0.62 |
| Marijuana | 1 (ref) | 2.86 (0.9–9.6) | |||
| Tobacco | 1.19 (0.6–2.6) | 3.34 (1.1–10.0) | |||
| Multi-exposed | 1.32 (0.6–2.9) | 3.78 (1.3–11.2) | |||
| Non-user | 0.95 (0.5–1.9) | 2.71 (0.97–7.6) | |||
| Alcohold | E-cigarette | 0.33 (0.1–1.2) | 0.74 | 1 (ref) | 0.74 |
| Marijuana | 1 (ref) | 3.01 (0.8–11.0) | |||
| Tobacco | 0.78 (0.3–1.9) | 2.35 (0.8–7.2) | |||
| Multi-exposed | 0.74 (0.3–1.8) | 2.24 (0.7–6.9) | |||
| Non-user | 0.29 (0.1–0.7) | 0.89 (0.3–2.5) | |||
| Identify as a smoker | E-cigarette | 0.63 (0.2–2.2) | 0.91 | 1 (ref) | 0.91 |
| Marijuana | 1 (ref) | 1.60 (0.5–5.6) | |||
| Tobacco | 4.57 (2.1–10.1) | 7.31 (2.3–23.1) | |||
| Multi-exposed | 16.38 (6.4–41.7) | 26.19 (7.4–92.1) | |||
| Non-user | 0.07 (0.03–0.2) | 0.11 (0.04–0.3) | |||
aAdjusting for race/ethnicity, age, gender, education, and adverse life events score. bMarijuana is a reference category. cE-cigarette is a reference category. dAlcohol use 3 months prior to or during pregnancy. Bold designates P<0.05. E-cigarette, e-cigarette use only; marijuana, marijuana use only; tobacco, tobacco product use only, multi-exposed, any combination of e-cigarette, marijuana or tobacco products; non-user, neither e-cigarette, marijuana, nor tobacco use.
Discussion
Our study is the first to assess the lifestyle characteristics of exclusive parental e-cigarette and marijuana users. As expected, non-users had the healthiest lifestyle characteristics including identification as a non-smoker, decreased alcohol use and no illicit drug use. Interestingly, exclusive e-cigarette users overwhelmingly identified as non-smokers and exhibited other healthier choices. While marijuana users also identified as a non-smoker, they were more likely to use alcohol.
Parental use of tobacco and illicit substances correlate with unhealthy behaviors [39], [40]. In our study, exclusive e-cigarette and marijuana use was associated with healthier characteristics. Our findings suggest parents who engage in healthy activities such as exercise may be similarly choosing substances they perceive as healthier alternatives to tobacco and illicit drugs. Absence of widespread e-cigarette regulations including graphic label warnings and child-appealing flavoring may amplify the false belief of safety [10]. Furthermore, state-based legalization of marijuana also contributes to an increased perception of safety [48].
Interestingly, both e-cigarette users and marijuana users did not identify as smokers. Self-identification as a non-smoker has not been well studied in parents. Our study is the first to assess identification as a non-smoker among multiple exposure groups and correctly predicted 91% of those identifying as non-smokers (C-statistic=0.91). This finding has clinical implications highlighting the necessity for providers to specifically screen for e-cigarette and marijuana use. Simply screening for “smoking” may be insufficient and under-represent patterns of use. Currently the American College of Obstetrics and Gynecology guidelines note the increase in e-cigarette use, but recommended screening tools continue to emphasize combustible tobacco products [49]. Thus, parents who vape or use marijuana but do not self-identify as smokers may be undetected. Our study supports the American Academy of Pediatrics most recent recommendation to assess for all nicotine exposure, specifically including screening for e-cigarette use as well as independently assessing for marijuana use [50].
Our analysis was unique in that exposures were assessed among parents of newborns. The rate of parental e-cigarette use in our study (1%) was lower than the parental rate (4%) reported by Garbutt et al. [35]. The difference in the rate of e-cigarette use we found in our study may represent conservative use in new parents as studies have shown pregnant women are less likely to use substances [51], [52]. We found comparable rates of marijuana use (3%) to nationally reported rates in pregnant women (3.9%) [53]. The rate of parental tobacco use in our study (10%) was consistent with nationally reported rates of tobacco use during pregnancy (10.9%) [54].
There are several limitations to our study. Data was collected via a survey, thus, behaviors are subject to underreporting compared to toxicology [20] and recall bias. However, self-reported behavior may more accurately reflect clinician encounters which inform counseling on substance use. Duration of exposure to e-cigarette, marijuana and tobacco differed based on the validated survey questions used [Population Assessment of Tobacco and Health (PATH), Pregnancy Risk Assessment Monitoring System (PRAMS)] [41], [42]. Nevertheless, these durations of exposure are commonly reported in other studies [8], [17]. Additionally, our survey tool did not assess motivation for e-cigarette use. Previous studies have demonstrated that pregnant women perceived e-cigarette use as safer than combustible tobacco [9], [32], [34]. It is therefore plausible that e-cigarette use by parents could be perceived by them as a mechanism to quit combustible tobacco. E-cigarettes as a vehicle for cessation has been evaluated in several studies with mixed results [9], [10], [55], [56]. Future studies should investigate parental motivation for e-cigarette use.
Another limitation is our low parental response rate (paternal 37% and maternal 57%). Greater medical, social and educational demands are placed on new parents during the postpartum hospitalization which may limit capacity to respond to research surveys. However, our response rate did fall into the typical response rate range [57]. Rates of certain exposures were low, especially parental e-cigarette users. However, we found significant differences that persisted in adjusted models that were highly predictive (91% correctly predicted identification as non-smokers).
Our study has several strengths. Our ability to control for adverse life events which are known to be associated with both substance use [40] and lifestyle behaviors [58], improves the validity of our conclusions. Furthermore, by isolating exclusive e-cigarette, marijuana and tobacco use in comparison with multi-exposed and non-users allows for better discernment of the association of exposures and a spectrum of clinically relevant lifestyle behaviors. By focusing on the parents, we further delineate lifestyle behaviors in a previously under-studied population.
Our study demonstrates exclusive parental e-cigarette and marijuana users do not identify as smokers. We also determined that exclusive parental e-cigarette users had healthier lifestyle behaviors while marijuana users had increased alcohol use. These findings should raise awareness in clinicians encountering adults of reproductive age during the preconception, pregnancy and postpartum time periods allowing providers to better screen and counsel families. Educational initiatives should be considered to raise awareness of potential harms in the setting of increased legalization of marijuana and a dearth of regulations around e-cigarettes.
Acknowledgments
We would like to thank all the mothers and fathers who took the time to participate in this study. We also would like to thank all of the research participants, including medical students-Christopher Stoll, Daniel Schwab, Brian Hanyok, Brian Yost, Mayra Ramirez, Jennifer Kutt, Dana Greene, Sarah Spiegel, Amythis Soltani, Mohammed Alzoobaee, Janki Shah, Bianca Zapanta, Maliha Rahman, Bryony Lucas, Kyle Mobbs, Minette Finney, Reba Gillis and Paolo Velendia, and clinical research coordinator – Clare Giblin for contributing immensely to data collection and the staff at affiliate hospitals for their cooperation.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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The online version of this article offers supplementary material (https://doi.org/10.1515/jpm-2019-0392).
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