Chapter 3Health Effects of E-Cigarette Use Among U.S. Youth and Young Adults

Introduction

This chapter focuses on the short-term and potential long-term health effects related to the incidence and continued use of electronic cigarettes (e-cigarettes) by youth and young adults. The sharp increase in the prevalence of e-cigarette use among youth and young adults, especially from 2011 to 2015 (Centers for Disease Control and Prevention [CDC] 2015, 2016), highlights the compelling need to learn more about this evolving class of products. This chapter highlights the scientific literature that addresses potential adverse health effects caused by direct exposure to aerosolized nicotine, flavorants, chemicals, and other particulates of e-cigarettes; secondhand exposure to e-cigarette aerosol; and exposure to the surface-deposited aerosol contaminants. Literature regarding harmful consequences of close contact with malfunctioning e-cigarette devices and ingestion of the nicotine-containing liquids (e-liquids) are also explored. This chapter examines available data on e-cigarettes and youth, reviews established human and animal data on harmful developmental effects of nicotine (prenatal and adolescent), and reviews data on e-cigarettes among adults when data on youth are not available. Of note, given the relatively recent emergence of e-cigarettes, data are not yet available that address the long-term health effects of use or exposure over several years compared with nonuse or exposure to air free from secondhand tobacco smoke and aerosol from e-cigarettes; thus, the discussion is limited in that regard.

Conclusions from Previous Surgeon General’s Reports

This chapter comprehensively reviews a new and emerging body of scientific evidence related to the use of e-cigarettes by youth and young adults. The enormous knowledge base on tobacco smoking and human health is also relevant to this discussion. That literature, which has been accumulating for more than 50 years, provides incontrovertible evidence that smoking is a cause of disease in almost every organ of the body (U.S. Department of Health and Human Services [USDHHS] 2004, 2014). Laboratory research has characterized the components of tobacco smoke and probed the mechanisms by which these constituents cause addiction and injury to cells, tissues, organs, and the developing fetus.

The evidence on the harmful consequences of nicotine exposure in conventional cigarettes, including addiction, and other adverse effects, is particularly relevant to e-cigarettes. Nicotine doses from e-cigarettes vary tremendously depending on characteristics of the user (experience with smoking conventional cigarettes or e-cigarettes), technical aspects of the e-cigarette, and levels of nicotine in the e-liquid. Although studies of nicotine doses in youth and young adults are lacking, studies of adults have found delivery of nicotine from e-cigarettes in doses ranging from negligible to as large as (Lopez et al. 2016; Vansickel and Eissenberg 2013; Spindle et al. 2015; St. Helen et al. 2016) or larger than (Ramôa et al. 2016) conventional cigarettes. Similarly, passive exposure to secondhand nicotine from e-cigarettes is just as large (Flouris et al. 2013) or lower than (Czogala et al. 2014) conventional cigarettes.

The findings of scientific research on smoking and involuntary exposure to tobacco smoke have been reviewed thoroughly in the 32 reports on smoking and health produced by the Surgeon General to date (there is one report on smokeless tobacco) (Table 3.1). The landmark first report was published in 1964 (U.S. Department of Health, Education, and Welfare [USDHEW] 1964), and the 50th-anniversary report, released in January 2014, comprehensively covered multiple aspects of cigarette smoking and health and lengthened the list of diseases caused by smoking and involuntary exposure to tobacco smoke (USDHHS 2014). Other Surgeon General’s reports that are particularly relevant to the present report include reports on the health consequences of smoking and involuntary exposure to tobacco smoke (USDHHS 2004, 2006), on the mechanisms by which smoking causes disease (USDHHS 2010), and on the health consequences of smoking on youth and young adults (USDHHS 1994, 2012). The Surgeon General’s reports on smoking and health have provided powerful conclusions on the dangers of nicotine. The 1988 report, released by Surgeon General C. Everett Koop, was the first to characterize smoking as addictive, and it identified nicotine as “…the drug in tobacco that causes addiction” (Appendix 3.1)¹ (USDHHS 1988, p. 9).

Table 3.1

Relevant conclusions from previous Surgeon General’s reports on smoking and health.

Subsequent reports expanded on the conclusions in the 1988 report related to nicotine—reaffirming that nicotine causes addiction, describing nicotine’s effects on key brain receptors (USDHHS 2010), and emphasizing that youth are more sensitive to nicotine than adults and can become dependent to nicotine much faster than adults (USDHHS 2012). This is of particular concern in the context of e-cigarettes because blood nicotine levels in e-cigarette users have been reported as being comparable to or higher than levels in smokers of conventional cigarettes (Lopez et al. 2016; Spindle et al. 2015), and serum cotinine (a nicotine metabolite) levels have been reported as being equal to that found in conventional cigarette users (Etter 2016; Marsot and Simon 2016). Because of their sensitivity to nicotine and subsequent addiction, about 3 out of 14 young smokers end up smoking into adulthood, even if they intend to quit after a few years; among youth who continue to smoke as adults, one-half will die prematurely from smoking (Peto et al. 1994; CDC 1996; Hahn et al. 2002; Doll et al. 2004). Surgeon General’s reports have also emphasized the critical role of environmental determinants of tobacco use, including the causal roles of the tobacco industry’s advertising and promotional activities and of the peer social environment (USDHHS 2012).

The 2014 Surgeon General’s report included a chapter that addressed the numerous adverse consequences of nicotine other than addiction (USDHHS 2014). The review documented the broad biological activity of nicotine, which can activate multiple biological pathways, and the adverse effects of nicotine exposure during pregnancy on fetal development and during adolescence on brain development. Of concern with regard to current trends in e-cigarette use among youth and young adults, the evidence suggests that exposure to nicotine during this period of life may have lasting deleterious consequences for brain development, including detrimental effects on cognition (USDHHS 2014).

Finally, the aerosol from e-cigarettes may include other components that have been addressed in previous Surgeon General’s reports, such as tobacco-specific nitrosamines (TSNAs), acrolein, and formaldehyde (USDHEW 1979; USDHHS 2010). Aerosols generated with vaporizers contain up to 31 compounds, including nicotine, nicotyrine, formaldehyde, acetaldehyde glycidol, acrolein, acetol, and diacetyl (Sleiman et al. 2016). Glycidol is a probable carcinogen not previously identified in the vapor, and acrolein is a powerful irritant (Sleiman et al. 2016). Although these constituents have been identified in e-cigarette aerosol, current evidence is unclear on whether typical user dosages achieve levels as high as conventional cigarettes, or at harmful or potentially harmful levels. More information will be available in the coming years as e-cigarette manufacturers begin reporting harmful or potential harmful constituents in compliance with the Tobacco Control Act.

Health Effects of E-Cigarette Use

The potential adverse health effects for youth who inhale e-cigarette aerosol include those on the body from acute administration of nicotine, flavorants, chemicals, other particulates, and additional effects, such as (1) nicotine addiction; (2) developmental effects on the brain from nicotine exposure, which may have implications for cognition, attention, and mood; (3) e-cigarette influence initiating or supporting the use of conventional cigarettes and dual use of conventional cigarettes and e-cigarettes; (4) e-cigarette influence on subsequent illicit drug use; (5) e-cigarette effects on psychosocial health, particularly among youth with one or more comorbid mental health disorders; and (6) battery explosion and accidental overdose of nicotine.

Effects of Aerosol Inhalation by the E-Cigarette User

Determining the potential health effects of inhaling e-cigarette aerosol is challenging due to the number of possible combinations of customizable options (Seidenberg et al. 2016), including battery power, nicotine concentration, e-liquids (Goniewicz et al. 2015; Buettner-Schmidt et al. 2016), and use behaviors and puff topography (Dawkins et al. 2016; Lopez et al. 2016). The amount of nicotine, flavorants, and other e-liquid constituents in e-cigarettes available for consumers to purchase varies widely, and the aerosolized constituents delivered vary by the type and voltage of the e-cigarette device being used (Cobb et al. 2015). Studies of commercial products have shown that e-liquids can contain as little as 0 milligrams/milliliter (mg/mL) to as much as 36.6 mg/mL of nicotine (Goniewicz et al. 2015); can be mislabeled (Peace et al. 2016); can vary by propylene glycol (PG)/vegetable glycerin (VG) ratio; and can contain one or more of several thousand available flavorants (Zhu et al. 2014b). Some liquids intended for use in e-cigarettes contain adulterants not named on ingredient lists (Varlet et al. 2015), and under at least some user conditions, the aerosolization process, which involves heating, produces additional toxicants that may present health risks (Talih et al. 2015). The sections that follow comprehensively cover the effects of inhaling aerosolized nicotine and then consider what is known about solvents (i.e., PG and VG, flavorants, and other chemicals) added to e-cigarettes, adulterants in e-liquids formed in the nicotine extraction process (e.g., N-nitrosonornicotine), and toxicants formed during the heating and aerosolization process (e.g., acrolein and formaldehyde) (Sleiman et al. 2016).

Dose and Effects of Inhaling Aerosolized Nicotine

Nicotine addiction via e-cigarette use is a primary public health concern due to the exponential growth in e-cigarette use among youth. The potential for widespread nicotine addiction among youth is high, as are the harmful consequences of nicotine on fetal development and the developing adolescent brain (USDHHS 2014). Nicotine, a psychomotor stimulant drug, is the primary psychoactive and addictive constituent in the smoke of conventional cigarettes and an important determinant in maintaining smoking dependence (e.g., USDHHS 2014). E-liquids typically contain nicotine, although in more widely variable concentrations than those found in conventional cigarettes (Trehy et al. 2011; Cameron et al. 2014; Cheng 2014; Goniewicz et al. 2015; Marsot and Simon 2016). The concentration of liquid nicotine is only one factor that influences the amount of aerosolized nicotine available for inhalation (Lopez et al. 2016); other factors include the power of the device being used (e.g., battery voltage, heater resistance) and user behavior (e.g., puff duration, interpuff interval) (Shihadeh and Eissenberg 2015; Talih et al. 2016; Etter 2016). The interplay of these factors may help to explain the variability in plasma nicotine concentration when adults use e-cigarettes under controlled conditions which can be higher (Ramôa et al. 2016), lower (Bullen et al. 2010; Vansickel et al. 2010, ²⁰¹²; Farsalinos et al. 2014b; Nides et al. 2014; Oncken et al. 2015; Yan and D’Ruiz 2015), or similar to those obtained by smoking conventional cigarettes (Vansickel and Eissenberg 2013; Spindle et al. 2015; St. Helen et al. 2016; see Figure 3.1). Generalization across studies is difficult due to variations in devices, e-liquids, and e-cigarette use behavior within the study sample. As demonstrated in Figure 3.1, in studies where a variety of products were used under similar laboratory conditions (i.e., blood sampling before and immediately after a 10-puff episode), there was wide variability in nicotine delivery between devices, with “cigalike” products (cigarette-like products) delivering less nicotine than “tank” products (Farsalinos et al. 2014b; Yan and D’Ruiz 2015), and low-resistance, dual-coil “cartomizer” products having the capacity to deliver less or more nicotine than a conventional cigarette, depending on the concentration of liquid nicotine (Ramôa et al. 2016).

Figure 3.1

Plasma nicotine concentration from different human laboratory studies and four different products with blood sampled before and immediately after a 10-puff bout with the products. Source: Vansickel et al. (2010); Farsalinos et al. (2014b); Yan and D’Ruiz (more...)

When the device type and liquid dose were held constant in a controlled session in one study, plasma nicotine concentrations (in this case in nanograms [ng]/mL) varied considerably across participants (0.8 to 8.5 ng/mL) (Nides et al. 2014). This variation was likely attributable to the manner in which the users puffed when using e-cigarettes, or that person’s “puff topography,” which includes the number of puffs, the intake volume and duration, the interpuff interval, and the flow rate (Zacny and Stitzer 1988; Blank et al. 2009).

Available data suggest that puff durations among adult cigarette smokers who are new e-cigarette users are comparable to those observed with conventional cigarettes (at least about 2 seconds [sec]) (Farsalinos et al. 2013b; Hua et al. 2013; Norton et al. 2014). However, puff durations during e-cigarette use among experienced e-cigarette users may be twice as long (~4 sec) (Farsalinos et al. 2013b; Hua et al. 2013; Spindle et al. 2015) as puff duration during conventional cigarette use. Puff duration is directly related to the nicotine content of the e-cigarette aerosol (i.e., the yield or dose) (Talih et al. 2016), suggesting that smokers of conventional cigarettes who switch to e-cigarettes may increase the duration of their puffs when using the new product in an attempt to extract more nicotine. Research also suggests that cigarette smokers may learn to alter other aspects of their puffing behavior when using an e-cigarette (Spindle et al. 2015). Relative to smokers of conventional cigarettes (Kleykamp et al. 2008), experienced e-cigarette users were found to have puff volumes that were significantly higher (101.4 mL vs. 51.3 mL) and puff flow rates that were significantly lower (24.2 mL/sec vs. 37.9 mL/sec) (Spindle et al. 2015). In a different study, adult cigarette smokers who had never used e-cigarettes but switched to e-cigarettes showed significantly increased puff durations and decreased puff flow rates within 1 week (Lee et al. 2015). Elsewhere, adult cigarette smokers given an e-cigarette appeared to show an enhanced ability to extract nicotine from their device after 4 weeks of use (Hajek et al. 2015). Thus, the health effects of aerosolized nicotine in e-cigarette users may depend on a variety of factors, including the e-liquid used, the user’s behavior, and the user’s experience with the product.

Aerosolized Nicotine and Cardiovascular Function

Smoking is a major cause of death from cardiovascular disease (USDHHS 2014), and exposure to nicotine has been identified as a potential initiating factor in the atherogenic process (Lee et al. 2011; Santanam et al. 2012; Benowitz and Burbank 2016). Acute administration of nicotine causes a variety of well-characterized, dose- and route-dependent effects in adults, including cardiovascular effects, such as increases in heart rate and blood pressure (BP) and greater cardiac output, leading to an increase in myocardial oxygen demand (Rosenberg et al. 1980; USDHHS 2014). Reports from cell biology and animal studies have established biologic plausibility between nicotine alone and negative cardiovascular effects (Hanna 2006; Santanam et al. 2012). These studies have shown that nicotine induces the production of various inflammatory mediators involved with atherosclerotic pathogenesis (Lau and Baldus 2006), and that at the cellular level, nicotine induces C-reactive protein (CRP) expression in macrophages that contribute pro-inflammatory and pro-atherosclerotic effects (Mao et al. 2012).

Long-term studies on the safety of nicotine-only exposure (e.g., as with using e-cigarettes rather than smoking conventional cigarettes) among youth have not been conducted, and little is known about the cardiovascular effects of e-cigarette use among adults. However, when e-cigarettes are accompanied by a measurable increase in plasma nicotine concentration, it increases heart rate (Vansickel et al. 2012; Vansickel and Eissenberg 2013; Nides et al. 2014; Yan and D’Ruiz 2015), and diastolic BP rises.

Given the paucity of long-term data on the impact of e-cigarette smoking in relation to cardiovascular disease, other nicotine products offer a useful analogy. A meta-analysis reported that replacing the consumption of conventional cigarettes with nicotine replacement therapy (NRT) reduces cardiovascular risk among former smokers without significant adverse consequences (compared with current smokers) (Greenland et al. 1998; Moore et al. 2009). However, most NRT use is temporary (<26 months), and the adverse consequences of longer term NRT therapy are unknown.

Elsewhere, investigators examined the relationship between the use of Swedish-type moist snuff (or “snus”), which contains high levels of nicotine and low levels of TSNAs, and the incidence of acute myocardial infarction among men with a mean age of 35 years who had never smoked cigarettes. The researchers, who pooled data from eight prospective cohort studies, found no support for any association between the use of snus and the development of acute myocardial infarction (Hansson et al. 2012), regardless of timing, intensity, duration, or period of use among the men who were followed for 4–29 years.

In summary, despite overwhelming epidemiologic evidence linking the use of conventional cigarettes with cardiovascular disease, the precise components of cigarette smoke responsible for this relationship and the mechanisms by which they exert their effects have not yet been fully explained (Hanna 2006). For e-cigarettes, biological data support a potential association with cardiovascular disease, and short-term use of these products is accompanied by a measurable increase in plasma nicotine concentrations in adults as well as increases in heart rate and blood pressure. Much more research is needed, but the limited data available suggest the typical cardiovascular effects exerted by nicotine are also exerted by e-cigarettes (Benowitz and Burbank 2016; Bhatnagar 2016).

Aerosolized Nicotine and Dependence

Although a great deal is known about self-administration of nicotine and the development of nicotine dependence among adults (USDHHS 2014) and youth (Colby et al. 2000; USDHHS 2012; O’Loughlin et al. 2014; Yuan et al. 2015), more research is needed on nicotine dependence in youth and young adults as a result of using e-cigarettes. Nicotine dependence, also referred to as nicotine addiction (USDHHS 2010) or tobacco use disorder (American Psychiatric Association [APA] 2013), is defined as a neurobiological adaptation to repeated drug exposure that is manifested behaviorally by highly controlled or compulsive use; psychoactive effects such as tolerance, physical dependence, and pleasant effect; and nicotine-reinforced behavior, including an inability to quit despite harmful effects, a desire to quit, and repeated cessation attempts (USDHHS 1988; APA 2013). In tobacco-dependent users of conventional cigarettes, a predictable consequence of short-term abstinence (e.g., for more than a few hours) is the onset of withdrawal symptoms indicated by self-reported behavioral, cognitive, and physiological symptoms and by clinical signs (USDHHS 2010). Subjective withdrawal symptoms are manifested by affective disturbance, including irritability and anger, anxiety, and depressed mood. The behavioral symptoms include restlessness, sleep disturbance, and increased appetite. Cognitive disturbances usually center on difficulty in concentrating (USDHHS 2010).

Early studies of conventional cigarette smokers using e-cigarettes reported poor nicotine delivery with little to no increase in blood nicotine levels after puffing (Eissenberg 2010; Vansickel et al. 2010). Later studies reported that the effect on serum cotinine levels among new e-cigarette users can be similar to that generated by conventional cigarettes (Flouris et al. 2013; Lopez et al. 2016). Studies examining this discrepancy found that e-cigarette users require longer puffs to deliver equivalent nicotine doses (Lee et al. 2015), and within a week, inexperienced e-cigarette users adjust their puffing patterns after switching (Hua et al. 2013b; Lee et al. 2015; Talih et al. 2015).

In more experienced e-cigarette users, blood nicotine levels appear to be influenced by puffing patterns, such as puff length. Volume and frequency and plasma nicotine levels ranging from 2.50 to 13.4 ng/mL have been observed after 10 puffs of an e-cigarette (Dawkins and Corcoran 2014). Dawkins and colleagues (2016) used 24 mg/mL nicotine strength liquid and observed high blood nicotine levels that were achieved very quickly, matching and even exceeding those reported in conventional cigarette smokers. St. Helen and colleagues (2016) conducted a similar study and reported that e-cigarettes can deliver levels of nicotine that are comparable to or higher than conventional cigarettes. Finally, Etter (2016) reported cotinine levels among experienced e-cigarette users similar to levels usually observed in conventional cigarette smokers. Figure 3.1 and Table A3.1-1 in Appendix 3.1 summarize studies on aerosolized nicotine from e-cigarettes and dependence using dependency criteria.

The ability of e-cigarettes to deliver comparable or higher amounts of nicotine compared to conventional cigarettes raises concerns about e-cigarette use generating nicotine dependence among young people (Dawkins et al. 2016; Etter 2016; St. Helen et al. 2016). The reported blood levels of nicotine, or cotinine, in e-cigarette users is likely to cause physiological changes in nicotinic acetylcholine receptors in the brain that would sustain nicotine addiction (Kandel and Kandel 2014; Yuan et al. 2015). This is particularly concerning for adolescents and young adults, given that early exposure to nicotine increases the severity of future nicotine dependence (St. Helen et al. 2016; USDHHS 2014).

Symptoms of nicotine dependence can occur soon after the initiation of conventional smoking, and even before established use, among adolescents and young adults (DiFranza et al. 2002; O’Loughlin et al. 2003; Dierker et al. 2007; Ramôa et al. 2016). Furthermore, some adolescents have reported nicotine dependence symptoms while using tobacco as little as 1–3 days per month (Rose et al. 2010). Using the National Comorbidity Survey-Adolescent dataset, Dierker and colleagues (2012) reported that nicotine dependence in adolescents was likely to occur within 1 year of the initiation of weekly or daily smoking, regardless of sociodemographic variables. Importantly, when smoking onset began at a younger age, the transition to weekly and daily smoking was more rapid, indicating a youthful neurobiological sensitivity to nicotine (Dierker et al. 2012). Zhan and colleagues (2012) found that symptoms of nicotine dependence could be detected among teenagers before they had smoked even 100 cigarettes.

Because few validated measures exist for assessing dependence on e-cigarette use, some researchers have adapted those originally developed to measure dependence in smokers of conventional cigarettes. Among adults, scores on these measures have been consistently lower in e-cigarette users than in smokers of conventional cigarettes (Farsalinos et al. 2013a; Etter and Eissenberg 2015; Foulds et al. 2015). Still, scores for e-cigarette dependence among former cigarette smokers were positively associated with the nicotine concentration of the e-cigarette liquid and the type of device used (Etter 2015; Etter and Eissenberg 2015; Foulds et al. 2015). Research in this area is challenging to interpret because measurement of youth e-cigarette dependence has not been standardized and there is a wide variation in device/e-liquid combinations, which allow for adjustable nicotine delivery among study participants. Regardless, among 766 adults, who were daily users of e-cigarettes (with nicotine) and who were either former cigarette smokers (83%) or current cigarette smokers (17%), 30.7% indicated that they would likely be unable to stop using e-cigarettes, 28.2% that they would find it “very difficult” or “impossible” to stop using e-cigarettes, and 27.5% that they were unable to stop e-cigarette use (Etter and Eissenberg 2015). However, it is important to note that e-cigarettes were less addictive than conventional cigarettes in this sample (Etter and Eissenberg 2015).

In summary, the addictive liability of e-cigarettes has the potential to be at least equivalent to that of conventional cigarettes, given nicotine dose levels produced by these products, particularly among experienced users operating new-generation devices (Ramôa et al. 2016). More generally, the delivery of nicotine in sufficient doses and blood concentration would be expected to produce and maintain dependence in e-cigarette users. Further work would be useful to determine the natural course and history of e-cigarette use among smokers of conventional cigarettes, former smokers, and never smokers and to more accurately determine the nicotine addiction liability of e-cigarette use. Unfortunately, these issues have not been explored in adolescents, although the prevalence of e-cigarette use has increased considerably in that population since 2011 (see Chapter 2).

Effects of Nicotine in Youth Users

Nicotine is the prime psychoactive substance in conventional cigarettes (Yuan et al. 2015), and given that the developing adolescent brain is immature and vulnerable to neurobiological insults (Bernheim et al. 2013; Lydon et al. 2014), it is important to understand how nicotine delivered by e-cigarette use affects adolescent brain development and how responses to nicotine in adolescents differ from those seen in adults. Substantial evidence suggests that nicotine can negatively influence both adolescent and prenatal brain development (USDHHS 2014). For example, Weiss and colleagues (2008) reported a strong mechanistic link among early nicotine exposure (younger than 16 years of age), common genes related to the severity of nicotine addiction (CHRNA5-A3-B4 haplotypes), and adult nicotine addiction in three independent populations of European origins. Although much of the literature on nicotine addiction arises from studies of nicotine exposure among adults, and with combustible tobacco products (see Table A3.1-2 in Appendix 3.1), there is a growing body of biological mechanistic literature from animal studies that model the effects of nicotine in doses equivalent to those for humans (see Table A3.1-3 in Appendix 3.1). These animal and human studies, taken together with studies of rising e-cigarette prevalence in youth (see Chapter 2), point to an age-dependent susceptibility to nicotine as a neurobiological insult.

Limited direct human experimental data exist on the effects of nicotine exposure from e-cigarettes on the developing adolescent brain, but experimental laboratory data have been found to be relevant in animal models to contextualize effects in humans (Stevens and Vaccarino 2015). Even if the full complexity of human brain development and behavioral function during adolescence cannot be completely modeled in other species, the similarities across adolescents of different species support the use of animal models of adolescence when examining neural and environmental contributors to adolescent-characteristic functioning (Spear 2010).

Animal studies provide an effective method to examine the persistent effects of prenatal, child, and adolescent nicotine exposure, in addition to human epidemiologic data. When considering an epidemiologic causal argument of exposure (risk factor) to health outcome (disease), one should note that animal models lend biological plausibility when experimentation with humans is not possible (or ethical) (Rothman et al. 2008). Furthermore, animal studies offer significant advantages compared to human studies—with the ability to control for many confounding factors, to limit nicotine exposure to differing levels of physical and neural development—and are pivotal for understanding the neural substrates associated with adolescence. The validity of any causal argument when examining animal models requires careful consideration, and yet in combination with epidemiologic data—such as prevalence, incidence, and strength of association between exposure and outcome—a causal argument can be constructed with literature from animal models representing biologic plausibility. Using a variety of study designs and research paradigms including humans and animals, research in this area provides evidence for neuroteratogenic and neurotoxic effects on the developing adolescent brain (Lydon et al. 2014; England et al. 2015).

The brain undergoes significant neurobiological development during adolescence and young adulthood, which are critical periods of sensitivity to neurobiological insults (such as nicotine) and experience-induced plasticity (Spear 2000; Dahl 2004; Gulley and Juraska 2013). Although maturation occurs in different regions of the brain at different rates, a similar progression occurs in all areas characterized by a rapid formation of synaptic connections in early childhood, followed by a loss of redundant or unnecessary synapses (called pruning) and the formation of myelin. Myelination is the process by which a fatty layer, called myelin, accumulates around nerve cells (neurons). Because of myelin, nerve cells can transmit information faster, allowing for more complex brain processes. Pruning allows for more focused concentration, and myelination allows for faster electrical and neural signaling; both allow for more efficient cognitive processing. During adolescence and into young adulthood, myelination occurs rapidly in the frontal lobe, a place in the brain that controls executive functioning, reasoning, decision-making skills, self-discipline, and impulse control. Plasticity refers to the current understanding that the brain continues to change throughout life, not only because of normal, maturational neural growth and development but also because of changes in environmental neurobiological exposures (such as nicotine), injuries, behaviors, thinking, and emotions (Mills and Tamnes 2014).

Across species, and in humans, adolescence is a key period of increased plasticity and rapid growth of brain circuits that regulate social, emotional, and motivational processes and decision making (Spear 2000, ²⁰¹¹; Nelson et al. 2005; Ernst and Fudge 2009; Counotte et al. 2011). The prefrontal cortex, which is involved in higher level regulatory control of complex behaviors (such as planning, impulse control, and working memory), continues normal structural and functional development into young adulthood, to about 25 years of age (Giedd and Rapoport 2010; Somerville and Casey 2010). Because of the immaturity and rapid growth of the prefrontal cortex, adolescents and young adults normally exhibit moody, risk-taking, and unpredictable impulsive behaviors. The combination of delayed maturation of frontal cognitive control and increased reactivity of subcortical reward-related and emotion-processing systems may lead to increased risk-taking behavior and a greater susceptibility to initiating substance use and the development of dependence (Steinberg 2008; Ernst and Fudge 2009; Counotte et al. 2011; Spear 2011). Thus, myelination is vitally important to the healthy functioning of the central nervous system, and any exposure that significantly interferes with the myelination process can cause mild-to-severe cognitive and learning problems (Brady et al. 2012).

Brain development in juvenile rodents has been reported to display patterns that resemble those of human beings, suggesting that the rodent model might be relevant to studying the neurobiological underpinnings of brain maturation in teenagers (Spear 2000). Studies across species have revealed unique characteristics of adolescent nonhuman brain structure, mechanisms, and function that provide biological plausibility to the hypothesis that human adolescents are particularly vulnerable to nicotine uptake (O’Loughlin et al. 2015; Yuan et al. 2015). There is evidence for rapid growth of gray matter, followed by activity-dependent synaptic pruning (the process of synapse elimination that occurs between early childhood and the onset of puberty) and increasing myelination throughout the brain (Casey et al. 2005; Lenroot and Giedd 2006; Giedd and Rapoport 2010; Counotte et al. 2011).

Nicotine has more significant and durable damaging effects on adolescent brains compared to adult brains, the former suffering more harmful effects. Preclinical animal studies have shown that in rodent models, nicotinic acetylcholine receptor (nAChR) signaling is still actively changing during adolescence, with higher expression and functional activity of nAChRs in the forebrain of adolescent rodents compared to their adult counterparts (Britton et al. 2007; Kota et al. 2007; Doura et al. 2008). Furthermore, in rodent models, nicotine actually enhances neuronal activity in several reward-related regions and does so more robustly in adolescents than in adults (Schochet et al. 2005; Shram et al. 2007; Dao et al. 2011). This increased sensitivity to nicotine in the reward pathways of adolescent rats is associated with enhanced behavioral responses, such as strengthening the stimulus-response reward for administration of nicotine. In conditioned place-preference tests—where reward is measured by the amount of time animals spend in an environment where they receive nicotine compared to an environment where nicotine is not administered—adolescent rodents have shown an increased sensitivity to the rewarding effects of nicotine at very low doses (0.03 mg/kg) (Vastola et al. 2002; Belluzzi et al. 2004; Brielmaier et al. 2007; Kota et al. 2007; Natarajan et al. 2011) and exhibited a unique vulnerability to oral self-administration during the early-adolescent period (Adriani et al. 2002). Adolescent rodents also have shown higher levels of nicotine self-administration than adults (Levin et al. 2003; Chen et al. 2007; Natividad et al. 2013), decreased sensitivity to the aversive effects of nicotine (Adriani et al. 2002; Shram et al. 2006; Torres et al. 2008), and less prominent withdrawal symptoms following chronic nicotine exposure (O’Dell et al. 2006). This characteristic in rodent models of increased positive and decreased negative short-term effects of nicotine during adolescence (versus adult-hood) highlights the possibility that human adolescents might be particularly vulnerable to developing dependency to and continuing to use e-cigarettes. These biological mechanisms are of great public health importance as exposure to nicotine grows among nonsmoking youth through the increasing prevalence of e-cigarette use.

Beyond their unique vulnerability to nicotine use, and thus smoking uptake, human adolescents may be particularly vulnerable to the detrimental consequences of nicotine exposure, including an increase in drug-seeking behaviors (Kandel and Kandel 2014), deficits in attention and cognition, and mood disorders (Yuan et al. 2015). In animal models, chronic nicotine exposure during adolescence has been shown to produce long-lasting, unique effects that are not observed in mature adult animals. Moreover, animal models have provided substantial evidence that the limbic system—which controls cognition, emotion, and drug-reward—is actively maturing during adolescence and during this age is vulnerable to long-term modification by nicotine.

Reward-Seeking Behaviors. A very strong argument can be made about the association between adolescent exposure to nicotine by smoking conventional cigarettes and the subsequent onset of using other dependence-producing substances. Strong, temporal, and dose-dependent associations have been reported (Isensee et al. 2003; John et al. 2004b; Bronisch et al. 2008; Kandel and Kandel 2015), and a plausible biological mechanism (via rodent and human modeling) suggests that long-term changes in the neural reward system take place as a result of adolescent smoking (Lewinsohn et al. 1999; Huang et al. 2013; Kandel and Kandel 2014). Adolescent smokers of conventional cigarettes have disproportionately high rates of comorbid substance abuse (Kandel et al. 1992; Lai et al. 2000; Hanna et al. 2001), and longitudinal studies have suggested that early adolescent smoking may be a starting point or “gateway” for substance abuse later in life (Kandel et al. 1992; Lewinsohn et al. 1999; Wagner and Anthony 2002; Brook et al. 2007), with this effect more likely for persons with attention deficit hyperactivity disorder (ADHD) (Biederman et al. 2006; Wilens et al. 2008). Although factors such as genetic comorbidity, innate propensity for risk taking, and social influences may underlie these findings (Lindsay and Rainey 1997; Smith et al. 2015), both human neuroimaging and animal studies suggest a neurobiological mechanism also plays a role. In addition, behavioral studies in adolescent and young adult smokers have revealed an increased propensity for risk taking, both generally and in the presence of peers, and neuroimaging studies have shown altered frontal neural activation during a risk-taking task as compared with nonsmokers (Lejuez et al. 2005; Cavalca et al. 2013; Galvan et al. 2013). Rubinstein and colleagues (2011b) used neuroimaging to show decreased brain response to a natural reinforcer (pleasurable food cues) in adolescent light smokers (1–5 cigarettes per day), with their results high-lighting the possibility of neural alterations consistent with nicotine dependence and altered brain response to reward even in adolescent low-level smokers.

Nicotine exposure in rodents at an age of physical development corresponding to human adolescence has been found to increase the reinforcing effects of other drugs of abuse, including cocaine, methamphetamine, and alcohol, without having a major impact on responding for other rewards, thus providing further evidence in support of nicotine as an initiation toward other substance use and abuse (McQuown et al. 2007; Dao et al. 2011; Dickson et al. 2014; Pipkin et al. 2014; Kandel and Kandel 2014). In several rodent studies, treatment with very low doses of nicotine for a few days during early adolescence, but not in late adolescence or adulthood, produced lasting changes in D2 and D3 dopamine receptors and in the self-administration of other abused drugs (McQuown et al. 2007; Dao et al. 2011; Mojica et al. 2014). Nicotine exposure in adolescent rats also induced rapid and long-lasting dendritic remodeling in the nucleus accumbens shell, a critical component of reward learning and addiction, via a D1 dopamine receptor-mediated mechanism (Ehlinger et al. 2016). This persistent form of nicotine-induced neuroplasticity has the potential to alter synaptic connectivity within reward-processing centers and enhance the addictive effects of drugs of abuse.

Attention and Cognition. Both cognitive improvements (Jasinska et al. 2014) and cognitive deficits (Hall et al. 2014) have been reported after nicotine exposure in healthy human adults, while smoking during adolescence impairs cognition and attention processes. Results of a genetically sensitive, longitudinal “concordant” and “discordant” twin study from the Netherlands Twin Registry indicated a larger increase in attention problems from adolescence to adulthood in twins who smoked than in their never-smoking co-twins (Treur et al. 2015). In another study, adolescent smokers were found to have chronic impairments in the accuracy of their working memory (e.g., in processing information from two sensory modalities simultaneously), which were more severe with an earlier age of onset of smoking (Jacobsen et al. 2005). Functional imaging studies have shown that 24-hour smoking abstinence in adolescent smokers causes acute impairments of verbal memory and working memory, along with chronic decrements in cognitive performance (Jacobsen et al. 2007a). In another study, adolescent users of conventional cigarettes showed decreased prefrontal cortex activation (versus never smokers) during attention tasks, and duration of smoking (in years) was directly correlated with the extent of reduction in prefrontal cortical activity (Musso et al. 2007).

Thus, longitudinal and imaging studies in humans provide support for the hypothesis that adolescent use of conventional cigarettes has both acute and long-term effects on attention and memory. Although nicotine exposure cannot be cited as the sole cause of cognitive defects (or even one of several combined effects in humans), other studies have shown that adolescent nicotine exposure in rats induces lasting synaptic changes in the prefrontal cortical regions critical for normal attention, memory, and cognition that likely underlie observed impairments in attentional and cognitive function (Bergstrom et al. 2008). Adolescent nicotine exposure in rats has induced impairments in stimulus-response-discrimination-learning processes but not in abstract rule-learning processes, which are dependent on dissociable cognitive systems, thus showing the selective effects of nicotine (Pickens et al. 2013). In addition, adolescent, but not postadolescent, treatment of rats with nicotine resulted in diminished attention span and enhanced impulsivity in adulthood (Counotte et al. 2009, 2011). The biological causes of these cognitive disturbances (reduced attention span and impulse control) were associated with reduced regulation of prefrontal cortex excitatory synapses function in metabotropic glutamate receptor 2 (mGluR2) (Counotte et al. 2011; Goriounova and Mansvelder 2012). In addition, hippocampal function, which is critical for memory, was altered in adult mice by nicotine exposure during adolescence. Contextual fear conditioning—a hippocampus-dependent task in which animals learn and remember to associate a fearful stimulus (e.g., a foot shock) with a particular context—was disrupted in adult mice that had been treated during adolescence with chronic nicotine but not following chronic treatment with nicotine in adulthood (Portugal et al. 2012). Rodent studies have implications for human adolescents, suggesting that exposure to tobacco during youth may lead to long-lasting changes in behavioral and neuronal plasticity into adulthood.

Mood Disorders. Adolescents with symptoms of mental health disorders (e.g., anxiety, aggressive and disruptive behaviors, mood disorders) are at increased risk for initiation of conventional cigarette use and long-term nicotine dependence compared with those without such disorders (Gehricke et al. 2007; Morris et al. 2011). Although this risk may reflect a common genetic predisposition, or the use of nicotine to self-medicate in the hope of improving mental health symptoms, the question arises of whether the smoking of conventional cigarettes by adolescents contributes to the development of mood disorders. A meta-analysis of existing studies showed consistent evidence that both tobacco use and dependence on tobacco products among adolescents indeed increased their risk of anxiety disorders (Moylan et al. 2012). Other studies have shown that an early onset of smoking is associated with a shorter time to first onset of an anxiety disorder (Jamal et al. 2011), and there is a positive association between adolescent smoking, particularly through a nicotine pathway, and anxiety in early adulthood (Moylan et al. 2013). Bidirectional relationships between adolescent smoking and disruptive disorders (e.g., ADHD; oppositional defiant disorder [ODD] [Griesler et al. 2011]) as well as depression (Tjora et al. 2014) also have been reported, while a longitudinal birth cohort found evidence to support a causal relationship between teen smoking and onset of depression (Boden et al. 2010). Although these findings are complex and warrant further study using comparisons of genetic polymorphisms associated with smoking or twin and sibling discordant/concordant studies (Munafo and Araya 2010; Leventhal and Zvolensky 2015), they do suggest that nicotine exposure during adolescence could contribute to long-term mental health disorders.

Findings of animal studies support the theory that adolescent nicotine exposure results in long-term alterations in emotional response, specifically enhanced anxiety and fear (Slawecki et al. 2003; Smith et al. 2006), and in persistent alterations in serotonin systems involved in mediating mood disorders by reprogramming the future response of 5-HT systems to nicotine (Slotkin and Seidler 2009). Even a single day of nicotine treatment in adolescent rats can enhance sensitivity to aversive stimuli later in life and result in a depression-like state in adulthood that is normalized by treatment with nicotine or antidepressants (Iniguez et al. 2009).

In summary, given the existing evidence from human and animal studies of the detrimental impact of nicotine exposure on adolescent brain development, the use of e-cigarettes by youth should be avoided and actively discouraged. Both preadolescence and adolescence are developmental periods associated with increased vulnerability to nicotine addiction, and exposure to nicotine during these periods may lead to long-lasting changes in behavioral and neuronal plasticity. Studies reveal that for most tobacco users, initial use begins before 18 years of age. Moreover, in some adolescents, symptoms of nicotine dependence can develop after exposure to very low levels of nicotine—less than 100 cigarettes. Cross-species studies have identified characteristics of the adolescent brain that may render it vulnerable at this age to nicotine uptake in the form of equivalent doses via nonsmoking administration mechanisms. In addition, animal models of nicotine exposure in adolescence reveal neural and behavioral alterations consistent with an increased likelihood of future nicotine use, increased activation of reward pathways and, unlike in adult animals, decreased aversive effects. Regarding e-cigarettes, data demonstrate adolescent use of these devices is associated with use of tobacco, alcohol, and other drugs (Dutra and Glantz 2014; Kristjansson et al. 2015; Wills et al. 2015a, b; Schneider and Diehl 2016). Finally, animal and human studies suggest a bidirectional relationship between the smoking of conventional cigarettes and exposure to nicotine during adolescence and factors related to disruptive disorders, such as ADHD and ODD that impair academic performance, as well as to depression. Because the adolescent brain is still developing, nicotine use during adolescence can disrupt the formation of brain circuits that control attention, learning, and susceptibility to addiction. Further research is warranted to more fully understand the effects of e-cigarette use on youth.

Nicotine Exposure from Maternal Nicotine Consumption: Prenatal and Postnatal Health Outcomes

Prenatal nicotine exposure through maternal cigarette use during pregnancy is one of the most widespread perinatal insults in the world (Levin and Slotkin 1998; Xiao et al. 2008; USDHHS 2014). Despite medical and societal sanctions and ongoing public health campaigns, the prevalence of maternal cigarette use during pregnancy in the United States was estimated to be 11–15% in 2013 (Tong et al. 2013). Smoking rates were even higher among women who were poor, young, or less educated, with rates as high as 25–30%, indicating that infants born to mothers who are poor have disproportionately higher exposure to nicotine (Dietz et al. 2011; Hamilton et al. 2012; Tong et al. 2013). Despite these adverse consequences, an estimated one-half of pregnant smokers continue to smoke into the third trimester (Osterman et al. 2013; Tong et al. 2013).

Because adults who use e-cigarettes can achieve plasma nicotine concentrations similar to those found among smokers of equivalent amounts of conventional cigarettes (Vansickel et al. 2010; Lopez et al. 2016; St. Helen et al. 2016), it is important that research continues in this area. Nicotine has been shown to cross the placenta and has been found in placental tissue as early as 7 weeks of embryonic gestation, and nicotine concentrations are higher in fetal fluids than in maternal fluids (Luck et al. 1985; Jauniaux et al. 1999). nAChRs are widely distributed in the fetal brain. As has been clearly demonstrated in animal models, acetylcholine acts on nAChRs to modulate functional connections during critical periods of development when regions are most sensitive to environmental input (Dwyer et al. 2008). When nicotine in the maternal bloodstream crosses the placental barrier, it binds to these receptors (Pentel et al. 2006; Wong et al. 2015), and in rodents this can result in long-term changes in neural structure and function. Results from animal studies show consistent associations between prenatal nicotine exposure and upregulation of nAChRs associated with disruption of fetal brain cell replication and differentiation (Slotkin 1998). Highlighting the role of nicotine in the effects of maternal smoking during pregnancy, nAChRs have been shown to be present in the human embryonic brain from 5 weeks of gestation (Hellstrom-Lindahl et al. 1998), and their normal maturation is altered in a region- and receptor subtype-dependent fashion by maternal cigarette smoking during pregnancy (Falk et al. 2005; Duncan et al. 2008). In those brainstem nuclei important for arousal, prenatal nicotine exposure decreases [³H]-nicotine binding (Duncan et al. 2008) and prevents normal age-related increases in α4 and α7 mRNA (Falk et al. 2005).

Prenatal nicotine exposure also has been associated with dysregulation of catecholaminergic, serotonergic, and other neurotransmitter systems. In addition, animal work suggests significant adverse effects of nicotine alone at levels commensurate with exposure to secondhand smoke (10-fold below those seen in active smokers), and that the non-nicotine components of tobacco smoke can exacerbate nicotine’s teratogenic effects (Slotkin et al. 2015). Offermann (2015) concluded that e-cigarettes emit many harmful chemicals into the air and that indirect exposure to nicotine exceeded exposure-level standards for noncarcinogenic health effects established by the California Environmental Protection Agency. No safe level of prenatal nicotine exposure has been established (England et al. 2015).

Airborne nicotine exposure through secondhand aerosol from e-cigarettes has been observed, as has salivary cotinine concentrations of nonsmokers in the homes of e-cigarette users (Ballbe et al. 2014; Czogala et al. 2014). Ballbe and colleagues (2014) reported the geometric means of airborne nicotine were 0.74 μg/m3 in the homes of smokers, 0.13 μg/m3 in the homes of e-cigarette users, and 0.02 μg/m3 in the homes of nonsmoking controls. While airborne nicotine exposure from combustible cigarette smoke was 5.7 (Ballbe et al. 2014) to 10 times higher (Czogala et al. 2014) than e-cigarette aerosol, one study reported only a twofold increase in salivary cotinine (0.38 ng/ml in the homes of smokers versus 0.19 ng/ml in the homes of e-cigarette users) (Ballbe et al. 2014), and another study found that exposure to cigarette smoke and exposure to e-cigarette aerosol had similar effects on the serum cotinine levels of bystanders (Flouris et al. 2013). Thus, the passive exposure to nicotine from e-cigarette smoking has been reported to be just as large (Flouris et al. 2013; Grana et al. 2013) or lower than (Czogala et al. 2014) conventional cigarettes, but exposure to nicotine from e-cigarette smoking is not negligible and is higher than in nonsmoking environments. This evidence suggests the importance of avoiding secondhand exposure of e-cigarette vapor and secondhand smoke during pregnancy (Flouris et al. 2013; Grana et al. 2013; Czogala et al. 2014).

Of the components of tobacco smoke, nicotine has been cited as the most important toxicant in terms of interfering with fetal development. Because of the health risks to the developing fetus associated with nicotine exposure during pregnancy, the U.S. Food and Drug Administration (FDA) (2015) recommends that pregnant women seek medical approval before using NRT, and the American College of Obstetricians and Gynecologists (2011) recommends consideration of NRT only if a woman fails behavioral interventions to quit smoking conventional cigarettes and has discussed the potential harms and benefits of NRT with her physician. NRT is most often used during pregnancy as a last resort to avoid exposing the fetus to the other toxic ingredients found in conventional tobacco smoke (Fiore et al. 2008). A Cochrane Database systematic review concluded that both the effectiveness and safety of NRT during pregnancy are unclear (Coleman et al. 2012). Table A3.1-4 in Appendix 3.1 presents a summary of studies in humans on the effects of tobacco exposure on fetal brain development.

Even with a firm understanding of the negative health consequences of nicotine on the developing fetus (Fiore et al. 2008; USDHHS 2014; Ekblad et al. 2015), little is known about the prevalence of e-cigarette use among pregnant women or the direct harmful effects on their fetus by other toxicants delivered by the aerosol from e-cigarettes (England et al. 2015; Suter et al. 2015). In one of the few studies identified, a survey of 316 pregnant women in a Maryland clinic found that the majority had heard of e-cigarettes, 13% had ever used them, and 0.6% were current daily users (Mark et al. 2015). These findings are of concern because the dose of nicotine delivered by e-cigarettes can be as high or higher than that delivered by conventional cigarettes. Therefore, plasma nicotine concentrations delivered while using e-cigarettes have the potential to harm the developing fetus. Furthermore, in 2013 in the United States, there were 26.5 births for every 1,000 adolescent females (15–19 years of age), or 273,105 babies born to females in this age group (Hamilton et al. 2013). Currently, the rate of e-cigarette use among pregnant adolescents is unknown, but the effects of nicotine and the potential for harm by other e-cigarette toxicants indicate that the use of e-cigarettes is a fetal risk factor among pregnant adolescent girls.

As outlined below, the specific effects of nicotine on prenatal development and postnatal outcomes include sudden infant death syndrome (SIDS) and may include altered development of the corpus callosum, deficits in auditory processing, and alterations in appetitive behavior, attention, and cognition.

SIDS. SIDS is the sudden and unexplained death of an infant younger than 1 year of age (Krous 2014). Maternal smoking and infant exposure to secondhand smoke have been causally associated with SIDS, with 20–29% of deaths from SIDS attributable to maternal smoking of conventional cigarettes during pregnancy (Dietz et al. 2010; Zhang and Wang 2013; USDHHS 2014). Prenatal exposure to cigarettes and to smokeless tobacco have been associated with increased risk for apnea events, which have been linked to increased risk for SIDS (Gunnerbeck et al. 2011; Zhang and Wang 2013; Inamdar et al. 2015).

Although the mechanistic pathways underlying SIDS remain largely unknown, nicotine has effects on pathways that could be related to SIDS and is related to known risk factors, particularly lung and respiratory development (England et al. 2015; Holbrook 2016; Spindel and McEvoy 2016). Evidence from animal models supports the hypothesis that prenatal nicotine exposure alters both fetal autonomic function and arousal, which could increase the risk of SIDS (Slotkin 1998; Task Force on Sudden Infant Death Syndrome and Moon 2011). In humans, a dose–response relationship between cotinine (the major nicotine metabolite) and altered arousal patterns has been shown in preterm infants (Richardson et al. 2009), and this relationship is suggestive of nicotine’s role in arousal deficits that could be linked to SIDS. There is widespread distribution of nAChRs in the brainstem nuclei in both humans and animals that control cardiopulmonary integration and arousal in the newborn (Dwyer et al. 2008). In some animal studies, prenatal exposure to nicotine has increased mortality in newborns that were exposed to reduced oxygen (Slotkin et al. 1995; Fewell and Smith 1998). Prenatal exposure to nicotine is also associated with altered serotonin signaling in the brainstem in the rat model, leading to an exaggerated trigeminocardiac reflex and resulting in bradycardia, hypotension, and apnea (Gorini et al. 2013).

Altered Development of the Corpus Callosum. The corpus callosum, the largest white matter structure in the brain, facilitates communication between the left and right cerebral hemispheres. Several human studies have revealed alterations in the structure of the corpus callosum in offspring following their exposure to maternal cigarette use during pregnancy (Jacobsen et al. 2007b; Paus et al. 2008). In animal models, prenatal exposure to nicotine has been shown to result in widespread alterations in gene expression in the brains of adolescent offspring (Cao et al. 2011, ²⁰¹³; Wei et al. 2011). In particular, the expression of a number of genes involved in myelination—the formation of white matter via the addition of protective myelin sheaths to axons—is altered in a sex-dependent manner, with upregulation in males and downregulation in females (Cao et al. 2013). Such changes in the expression profiles of myelin-related genes may influence the structure and function of white matter, and both hypermyelination and hypomyelination have been associated with cognitive deficits (Quaranta et al. 2002; Sokolov 2007).

Deficits in Auditory Processing. A number of human studies, using a variety of methods, have investigated the effects of maternal cigarette smoking during pregnancy on auditory processing from the fetal period through childhood (Jacobson and Morehouse 1984; Kristjansson et al. 1989; McCartney et al. 1994; Franco et al. 1999; Leech et al. 1999; Cowperthwaite et al. 2007). Deficits in auditory processing in fetuses are of concern because they affect later language development (Kisilevsky and Davies 2007; Kisilevsky et al. 2014). Various studies in infants have investigated the brain’s physiological activity response to auditory stimuli (the cochlea translates sound into nerve impulses to be sent to the brain), neuroelectric activity of the auditory nerve, and cochlear response (Key et al. 2007; Korres et al. 2007; Kable et al. 2009; Peck et al. 2010; Katbamna et al. 2013). Key and colleagues (2007) reported prenatal exposure to cigarette use (compared with nonexposed infants) to be associated with alterations in hemispheric asymmetry and suboptimal brain activity related to speech processing in otherwise healthy new-borns at least 2 days of age. Korres and associates (2007) found altered cochlear responses to auditory stimuli in newborns that were exposed to maternal cigarette smoking (n = 200) compared with those that were unexposed (n = 200), regardless of degree of cigarette exposure. Similar findings were reported by Durante and colleagues (2011) in two case-control studies.

Two additional studies investigated effects of maternal cigarette use during pregnancy on auditory brainstem responses in newborns (≤2 days old) (Peck et al. 2010) and infants (6 months old) (Kable et al. 2009). Both studies found greater neuroelectric response to sound stimuli, a phenomenon that may disrupt an infant’s ability to encode auditory information, potentially leading to deficits in language development. Furthermore, both studies demonstrated dose–response relationships between altered auditory processing and maternal cotinine levels. Finally, in a study of a small sample of newborns that sought to understand the direct biological pathway, maternal smoking during pregnancy produced changes in newborn cochlear and auditory brainstem functions and changes in placental gene expression in genes that appear to modulate the motility of cochlear hair cells (Katbamna et al. 2013). Thus, all three studies indicate effects based on consumption of conventional cigarettes, and they high-light the possibility of a mediating role of maternal nicotine use in altered infant auditory processing, although further work must rule out confounding effects and effect modification by other constituents (e.g., arsenic, benzene, and cadmium).

A study using functional magnetic resonance imaging (fMRI) in older offspring exposed to tobacco in utero assessed response to auditory and visual attention tasks in adolescent smokers (Jacobsen et al. 2007a). Teens whose mothers smoked during pregnancy exhibited decreased accuracy in the tasks, with greater activation of both the temporal lobe and the occipital lobe, regions of the brain that are critical for auditory and visual processing. Additive effects of maternal cigarette use during pregnancy and of adolescent smoking on activation of the temporal and occipital lobes also emerged, indicative of reduced coordination among brain regions during auditory attention tasks.

Animal studies have shown that nAChRs play a critical developmental role in establishing synaptic connections between sensory thalamic afferents and those cortical targets that are necessary for normal sensory processing (Table A3.1-5 in Appendix 3.1). Brief nicotine exposure during this critical postnatal period of sensory cortex development disrupts glutamate transmission (Aramakis et al. 2000) and eliminates nAChR regulation of signal processing in the adult auditory cortex, inhibiting normal auditory learning (Liang et al. 2006). Animals that are prenatally exposed to nicotine also exhibit deficits in cognitive processing in response to an auditory cue, which appears to be mediated by a loss of function of the nAChR β2 subunit (Liang et al. 2006; Horst et al. 2012).

Appetitive and Consummatory Behaviors. Clinical studies and animal studies have linked prenatal exposure to nicotine to subsequent appetitive behaviors (an active searching process that is performed consciously) and consummatory behaviors (such as ingestion of food or drugs) in offspring. Associations have been demonstrated in humans between maternal cigarette use during pregnancy and risk to the child of smoking uptake/nicotine dependence, drug abuse, and obesity; parallel relationships have been shown in animal models between prenatal exposure to nicotine and similar appetitive behaviors of offspring.

Parental use of tobacco is one of many well-known risk factors for offspring initiation of tobacco, progression to heavy use, and nicotine dependence. Tobacco use by parents influences their children through social, environmental, cognitive, and genetic mechanisms (USDHHS 2012). As a subset of these influences, mothers’ use of tobacco during pregnancy has been studied as an independent risk factor and has been associated with offspring susceptibility, initiation, regular use, and dependence (Kandel et al. 1994; Griesler et al. 1998; Kandel and Udry 1999; Buka et al. 2003; Lieb et al. 2003; Oncken et al. 2004; Al Mamun et al. 2006; O’Callaghan et al. 2009; Tehranifar et al. 2009; Agrawal et al. 2010; Rydell et al. 2012; Weden and Miles 2012; Stroud et al. 2014; Shenassa et al. 2015). Wakschlag and colleagues (2010, 2011) suggest that maternal smoking during pregnancy has a teratologic effect with abnormalities stemming from the in utero environment which disrupt neural (Kandel et al. 1994; Jacobsen et al. 2006) and dopamine systems that promote sensitivity to nicotine dependence (Kandel et al. 1994; Selya et al. 2013). For example, nicotinic receptors of laboratory animals exposed to nicotine in utero are upregulated, suggesting a latent vulnerability to nicotine dependence among animals exposed to nicotine in utero (Slotkin et al. 2006, 2015).

At issue with all human studies investigating maternal use of tobacco during pregnancy and offspring use of tobacco is isolating the independent effect on the fetus in relation to the other social, environmental, and cognitive factors that also predict offspring tobacco use. After controlling for maternal smoking during the offspring’s childhood, several studies have reported that maternal smoking during pregnancy is associated with higher nicotine dependence in offspring (Kardia et al. 2003; Lieb et al. 2003; Selya et al. 2013; Shenassa et al. 2015), increased or earlier smoking initiation, and heavier smoking among adolescent girls and adult offspring (Kandel et al. 1994; Cornelius et al. 2005). However, the association was attenuated and nonsignificant among several studies that controlled for a variety of environmental, social, and cognitive confounders between maternal cigarette use during pregnancy and initiation of offspring smoking (but not nicotine dependence) (Cornelius et al. 2005; Roberts et al. 2005; Munafo et al. 2006; Kandel et al. 2007; D’Onofrio et al. 2012; Rydell et al. 2014; Taylor et al. 2014), leaving speculation for the independent effect. In summary, evidence from animal models offers a biologic mechanism for, and human evidence is suggestive of, an association between maternal tobacco use during pregnancy with offspring smoking and nicotine dependence, but is insufficient to infer causation. Further research and longitudinal studies that examine these outcomes while assessing the full spectrum of environmental, social, and cognitive mediating pathways are needed to disentangle these issues.

A smaller set of literature has documented associations between maternal cigarette smoking during pregnancy and use of other substances by the child (Fergusson et al. 1998; Weissman et al. 1999; Porath and Fried 2005; Nomura et al. 2011). In utero exposure to nicotine also affects behavioral responses for drug rewards in both adolescent and adult experimental animals. Prenatal exposure to nicotine increases the preference of adolescents for a saccharin solution containing nicotine compared with saccharin alone (Klein et al. 2003), and it results in self-administration of nicotine either during acquisition of the task (Chistyakov et al. 2010) or after forced abstinence (Levin et al. 2006). Prenatal exposure to nicotine also increases subsequent oral intake of alcohol (Chang et al. 2013), and intravenous self-administration of both cocaine and methamphetamine is enhanced in a dose-dependent manner in adolescent rats (Franke et al. 2008) and adult rats (Lacy et al. 2014).

In contrast, in a study that used a discordant sibling pair design to reduce confounding by genetic and environmental factors, initial associations between prenatal smoking and alcohol use disorder were attenuated and were no longer statistically significant (D’Onofrio et al. 2012). In a large longitudinal study that spanned 40 years, Shenassa and colleagues (2015) found evidence to support effects on nicotine dependence among children of mothers who smoked during pregnancy, but no effects on their progression to marijuana dependence were observed. A possible explanation for these discordant findings is suggested by a study that found significant effects from prenatal smoking of conventional cigarettes on drug use among adolescents, but showed that these effects were restricted to a genetic subpopulation of carriers of a specific α6 nAChR gene (rs2304297) polymorphism (Lotfipour et al. 2010). In sum, a number of studies have documented associations between cigarette use by the mother during pregnancy and smoking initiation, heavy use, and nicotine dependence among her children, although control of confounding reduces this association. In addition, the literature is sparse and inconsistent regarding a connection between maternal cigarette use during pregnancy and the use of nontobacco substances by the child.

A large body of literature has demonstrated effects of maternal cigarette use during pregnancy on weight levels and obesity in childhood. For example, three meta-analytic reviews found a 47–64% increased risk of obesity in children following exposure to maternal cigarette smoking during pregnancy (Oken et al. 2008; Ino 2010; Weng et al. 2012; Behl et al. 2013). Additional systematic reviews (Bruin et al. 2010) and other studies (Harrod et al. 2015; La Merrill et al. 2015; Mourtakos et al. 2015; Bao et al. 2016) have all concluded that prenatal exposure to nicotine likely acts as a developmental obesogen in humans. However, unmeasured residual confounding or confounding by familial factors, which have not been fully explored, could attenuate the observed associations (Gilman et al. 2008; Iliadou et al. 2010). Animal studies support the epidemiologic literature suggesting a potentially causal relationship here by defining biologic pathways (Wong et al. 2015). Fetal and neonatal exposure to nicotine in rodents has resulted in neurochemical, neurobehavioral, and metabolic changes in the children that are consistent with obesity and type 2 diabetes (Williams and Kanagasabai 1984; Newman et al. 1999; Grove et al. 2001; Chen and Kelly 2005; Gao et al. 2005; Holloway et al. 2005).

In humans, studies involving structural MRI and fMRI have shown alterations in the size and sensitivity of brain reward centers in the teenage offspring of maternal smokers. Several of these studies revealed a thinning of the orbitofrontal cortex among persons who were prenatally exposed to maternal cigarette smoking, a thinning that was associated with drug use and experimentation during adolescence (Toro et al. 2008; Lotfipour et al. 2009); decreased amygdalar volume, which is associated with increased fat intake (Haghighi et al. 2013); and altered response to reward anticipation in the ventral striatum, an area associated with risk taking and drug use (Muller et al. 2013). In addition, highlighting the role of altered nicotinic pathways in the disruption of neural circuits from prenatal tobacco exposure, changes in striatal volume, and a propensity for drug use in adolescent offspring have been linked to interactions between prenatal exposure to cigarette smoking and a polymorphism in the gene encoding the α6 nAChR (Lotfipour et al. 2010). Structural alterations in the orbital frontal cortex have also been shown to result from interactions between maternal cigarette smoking during pregnancy and polymorphisms of brain-derived neurotrophic factor, a growth factor that regulates growth and differentiation of new neurons and supports existing neurons (Lotfipour et al. 2009). Although these clinical findings are specific to conventional cigarettes, they converge with results of animal studies of the effects of prenatal nicotine on brain reward centers and thus highlight the potential pernicious effects of e-cigarettes in pregnant women.

Animal studies have shown that the dopamine system, which is critically involved in satisfaction-seeking or appetitive behaviors, is modulated by nAChRs from the fetal period to adulthood (Azam et al. 2007). Prenatal nicotine exposure alters dopamine’s content, turnover, release, and receptor expression in forebrain regions, which are important for motor and cognitive functions (Navarro et al. 1988; Richardson and Tizabi 1994; Muneoka et al. 1999; Zhu et al. 2012) and for assigning motivational value to natural and drug rewards (Kohlmeier 2015; McNair and Kohlmeier 2015). Prenatal exposure to nicotine also modifies the structure of dendritic targets of dopamine innervations in the nucleus accumbens (a critical component of reward learning and addiction) (Mychasiuk et al. 2013) and alters neuronal signaling that affects dopamine function (Chang et al. 2013; Morgan et al. 2013).

Prenatal exposure to nicotine has been shown in a variety of animal studies to induce complex effects on behavioral response to natural rewards. Although adolescent offspring of nicotine-exposed mothers show an initial decrease in motivation to work for sucrose reward (Franke et al. 2008), they exhibit enhanced sensitivity to the rewarding effects as the task becomes harder (Lacy et al. 2012). Prenatal exposure to nicotine also results in enhanced intake of fatty foods, with no change in the intake of normal chow (Chang et al. 2013).

Attention and Cognition. Numerous human studies have investigated the effects of maternal cigarette use during pregnancy on disruptive behavior and attention deficits in the child. The 2014 Surgeon General’s report included results of a systematic review of effects of maternal cigarette use during pregnancy on disruptive-behavior disorders—including ADHD, conduct disorder, and ODD—in offspring (USDHHS 2014). The evidence for effects of maternal cigarette use during pregnancy on disruptive-behavior disorders, and ADHD in particular, was suggestive but not sufficient to infer a causal relationship. Several systematic reviews using meta-analyses have found evidence for associations between exposure to maternal cigarette use during pregnancy and ADHD in offspring, including dose–response relationships between number of cigarettes smoked per day and ADHD symptoms (Linnet et al. 2003; Langley et al. 2005; Latimer et al. 2012; Massey et al. 2016). However, similar to effects on nicotine dependence and obesity in offspring, the possibility of unmeasured confounding remains (D’Onofrio et al. 2008; Thapar et al. 2009; Langley et al. 2012). Evidence for associations with maternal cigarette use during pregnancy is perhaps more consistent for offspring conduct disorders than it is for ADHD. In particular, although some studies that used a gene–environment interaction design or a propensity score-matching approach to exposure to control for confounding, they found no effect of maternal cigarette smoking during pregnancy on conduct disorders (D’Onofrio et al. 2008; Gilman et al. 2008; Boutwell and Beaver 2010; Lavigne et al. 2011). However, several other studies—including a meta-analytic review across three studies using “genetically sensitive”² research designs—have suggested a direct causal relationship between maternal smoking during pregnancy and conduct disorders in offspring (McCrory and Layte 2012; Gaysina et al. 2013; Kuja-Halkola et al. 2014; Estabrook et al. 2015; Paus and Pausova 2015).

To explore the potential role of nicotine exposure in these associations, a small number of studies have included a prospective measure of confirmed tobacco exposure, maternal cotinine levels, in addition to maternal report of smoking, to study relationships with disruptive behaviors among offspring (Wakschlag et al. 2011; O’Brien et al. 2013; Massey et al. 2016). Wakschlag and colleagues (2011) found associations between maternal cigarette smoking and aggression and noncompliance among offspring. Studies have also shown alterations in the structure and function of the orbital frontal cortex, a region important for emotional regulation and cognition, in relation to maternal cigarette smoking during pregnancy (Toro et al. 2008; Bennett et al. 2009). Consistent with animal models of altered dopamine regulation, two studies have shown interactions of maternal cigarette smoking during pregnancy with dopamine regulation genotype (DAT1) in influencing disruptive-behavior phenotypes in offspring (Wakschlag et al. 2011; O’Brien et al. 2013). In another study, Wakschlag and colleagues (2010) demonstrated a sex-dependent interaction of maternal smoking during pregnancy with monoamine oxidase A (MAOA) genotype, which is associated with the development of antisocial behavior. In this study, maternal smoking during pregnancy further increased the risk for conduct disorder. In sum, although issues of confounding remain, much evidence from human studies is suggestive of a causal association between maternal cigarette smoking during pregnancy and disruptive behaviors among offspring. This was confirmed by the 2014 Surgeon General’s report on tobacco (USDHHS 2014). Since then, newer studies, controlling for personal and genetic confounders, have reported significant associations as well as nonsignificant, attenuated associations. Biologic evidence of nicotine-induced alterations in dopamine regulation also provides a possible mechanism for the role of nicotine in these outcomes.

Animal studies have shown that cholinergic modulation of prefrontal cortex function, via nAChRs, is essential for attention and cognition (Poorthuis and Mansvelder 2013; Proulx et al. 2014). Prenatal exposure to nicotine alters the morphology and nAChR functional response of prefrontal cortical neurons (Mychasiuk et al. 2013; Bailey et al. 2014). When tested as adolescents, animals that were exposed prenatally to nicotine show some behaviors characteristic of ADHD. For example, exposed offspring were found in two studies to show less impulse control and/or slower learning acquisition on two cognitive tests that tax attentional processes (Sorenson et al. 1991; Schneider et al. 2012). In addition, some studies have found hyperactivity in exposed offspring (Pauly et al. 2004; Schneider et al. 2012; Zhu et al. 2012), which was found in another study to be transmitted via maternal lineage from one generation to the next and to be ameliorated by methylphenidate treatment across all generations, showcasing the long-term impact of prenatal nicotine exposure (Zhu et al. 2014a). This transgenerational transmission of prenatal nicotine-induced hyperactivity must reflect long-term changes to the epigenome (Leslie 2013). Finally, emerging animal studies suggest that prenatal exposure to nicotine affects the proliferation and maturation of progenitor cells to glutamatergic neurons during neurodevelopment in the medial prefrontal cortex, resulting in behavioral impairments in attentional function and behavioral flexibility in adulthood (Aoyama et al. 2016; Poon and Leibowitz 2016; Powell et al. 2016).

Summary

Because of the rising prevalence of e-cigarette use, there is potential for widespread nicotine exposure to youth and young adults, resulting in nicotine addiction and related harmful consequences associated with exposure to nicotine. During pregnancy, there is neural sensitivity to the number and volume of substances, including nicotine, transported through the placenta. From prenatal development through adolescence and early adulthood, exposure to nicotine poses a serious threat, because these are critical times for brain development and brain plasticity. Furthermore, youth and young adults are more vulnerable than adults to the long-term consequences of nicotine exposure, including susceptibility to nicotine addiction and potentially reduced impulse control, deficits in attention and cognition, and mood disorders. An additional public health concern is exposure to e-cigarettes among persons who have never used conventional tobacco products. If the prevalence of e-cigarette use continues to rise among those who do not use conventional tobacco products, the harmful consequences of exposure to nicotine will rise accordingly.

The 2014 Surgeon General’s report (USDHHS 2014) states there is sufficient evidence to infer that: (a) nicotine activates multiple biological pathways through which smoking increases risk for disease; (b) nicotine exposure during fetal development, a critical window for brain development, has lasting adverse consequences for brain development; (c) nicotine adversely affects maternal and fetal health during pregnancy, contributing to multiple adverse outcomes such as preterm delivery and stillbirth; and (d) nicotine exposure during adolescence, a critical window for brain development, may have lasting adverse consequences for brain development and cognition. The literature presented in this section attempts to differentiate the risks to fetal and child health associated with nicotine in tobacco versus nicotine alone or in e-cigarettes. Evidence is sufficient to conclude tobacco use increases the risk of SIDS (USDHHS 2014), but further research is necessary with regard to nicotine alone or nicotine in e-cigarettes. The review finds evidence that tobacco is associated with structural brain changes and alterations in cognition, attention, and appetitive behaviors in human offspring. Less well known is the role that nicotine plays in mediating these associations, although animal models provide support for a role for nicotine in these outcomes. nAChRs, the chief receptor targets for nicotine, are widely expressed in the fetal brain, and their normal functioning is negatively affected by smoking and, in animals, by prenatal exposure to nicotine through experimental treatment. Furthermore, both human genetic studies and animal studies implicate a neurotoxic effect of fetal nicotine exposure. Pregnant women and women intending to become pregnant should be cautioned against using e-cigarettes to avoid unnecessary nicotine exposure to their baby.

Effects Not Involving Inhalation of Aerosol by the E-Cigarette User

Health effects not attributable to direct inhalation of e-cigarette aerosol include explosion or fire associated with malfunctioned devices, poisoning through contact exposure or intentional or unintentional ingestion of e-liquid, and exposure to secondhand aerosol or its condensate.

Health Effects Attributable to Explosions and Fires Caused by E-Cigarettes

Most reports of explosions and fires caused by e-cigarettes have appeared in print and online media and on televised programs. From August 2009 to March 2014, a search of U.S. media by the U.S. Fire Administration (2014) found 25 reports of e-cigarette explosions or fires. These data suggest that the number of such events is small when compared with the number of e-cigarette users. Of the 25 incidents found in the search, 2 caused serious harm, and there were no deaths attributable to explosions. In most cases, the resulting fires did not spread far from the site of the explosion. However, in one case an entire bedroom was lost to fire (U.S. Fire Administration 2014). As for explosions, several have occurred during an e-cigarette’s use, causing severe facial damage or injuries to bodies and hands (Brennan 2015; Corona and Marcus 2015; Duranty 2015; Fox 5 Digital Team 2015; Goff and Schwartz 2015; Jablow and Sexton 2015; Shastry and Langdorf 2016), but most occurred while the device’s batteries were being charged. Overcharging lithium batteries can lead to thermal run-away, causing the e-cigarette battery or container to be propelled, often with portions catching fire (U.S. Fire Administration 2014; Bohr et al. in press).

Health Effects Caused by Ingestion of E-Cigarette Liquids

The liquids in both e-cigarettes and the containers used to refill them can cause nicotine poisoning. Consequences of nicotine intoxication in the e-liquid include nausea, vomiting, headaches, dizziness, and diarrhea at low doses; seizures; tachycardia; abdominal pain; confusion; and even death (Cervellin et al. 2013). The amount of nicotine needed to cause death in humans is uncertain and, according to a reevaluation, may be higher than previously thought (Mayer 2014). The total amount of nicotine in refill liquids varies and can be as high as 1,000 mg/10 mL in do-it-yourself bottles (Davis et al. 2015), which could be lethal if consumed (Mayer 2014).

The increase in poisonings prompted enactment of the Child Nicotine Poisoning Prevention Act of 2015 (2016) in January 2016. This law requires any container of liquid nicotine sold, manufactured, distributed, or imported into the United States be placed in special packaging that is difficult to open by children under 5 years of age. Although labels may indicate the concentrations of nicotine, such labels can be incomplete, confusing, or inaccurate (Trtchounian and Talbot 2011; Cameron et al. 2014), and some bottles have not been labeled at all (Davis et al. 2015). Of most concern, some bottles of e-cigarette refill liquids labeled “no nicotine” have been found to contain significant amounts of that substance (e.g., 25.6 mg/mL; Trehy et al. 2011). Regardless, many e-cigarette users may not be aware of the toxic effects of nicotine and may not know that refill liquids should be kept away from toddlers and children. These liquids are often sold in colorful bottles with flavors that are attractive to children (Bahl et al. 2012). The liquids usually come in small dropper bottles that can be mistaken for bottles containing food dye or eye drops. Finally, many refill liquids are made in local “vape shops,” which have only recently come under FDA regulation (Federal Register 2016), with no uniform training process for mixers, a lack of standards and protections, and unknown concentrations of nicotine.

The rapid growth in popularity of e-cigarettes and the ease with which refill liquids can be purchased have made e-cigarettes an increasingly common item in many households, thereby elevating the possibility of accidental nicotine poisoning. Instances of related case reports, often involving children or infants, are increasing. For example, an 18-month-old girl was treated at an emergency room for hypertension and tachycardia after drinking about 2 mL of refill liquid from a bottle on a nightstand (Shawn and Nelson 2013). Unintentional exposure to nicotine can occur through ingestion, absorption through the skin, inhalation, or dropping refill liquids into one’s eyes (Cantrell 2014).

Figure 3.2 shows data from 2011 to 2016 on exposures to e-cigarettes or liquid nicotine (i.e., any contact with e-cigarettes or liquid nicotine, not necessarily resulting in any health effects) (American Association of Poison Control Centers 2016). These data show a dramatic increase in exposures through 2014 with a slight reduction of exposures in 2015. Fifty-one percent of the calls to poison control centers regarding exposures to e-cigarettes involved children 5 years of age or younger (CDC 2014). Increased e-cigarette exposures have also been reported by state and local poison centers (Banerji et al. 2014; Cantrell 2014; Guttenburg et al. 2014; Lee et al. 2014; California Department of Public Health 2015).

Figure 3.2

Data showing exponential increase in the number of cases of human exposure to e-cigarette products and liquid nicotine between 2011 and 2016. Source: American Association of Poison Control Centers (2016). Note: These numbers reflect the closed human exposures (more...)

Secondhand Exposure to the Constituents of E-Cigarette Aerosol

Exposure to secondhand smoke from combustible tobacco products is a known cause of morbidity and mortality (USDHHS 2006). Secondhand smoke, a mixture of the sidestream smoke from a smoldering cigarette and the mainstream smoke exhaled by a smoker, is known to contaminate both indoor and outdoor environments. In addition, when the constituents of smoke deposit on surfaces, nonsmokers can be exposed to them via touch, ingestion, or inhalation. These deposited constituents of combustible smoke are known as “thirdhand smoke” (Matt et al. 2011; Protano and Vitali 2011). E-cigarettes represent another potential source of exposure to toxicants for nonusers, via secondhand or thirdhand exposure to aerosol.

Exposure to Nonusers

In contrast to combustible tobacco products, e-cigarettes do not produce sidestream emissions; aerosol is produced during activation of the device. Some of this aerosol is subsequently exhaled into the environment where nonusers may be exposed through inhalation, ingestion, or dermal contact. As previously described in this chapter, constituents of the emissions may include nicotine, carbonyl compounds, VOCs, polyaromatic hydrocarbons, TSNAs, heavy metals, and glycols. It is not clear how much of inhaled e-cigarette aerosol is exhaled into the environment where nonusers can be exposed. Some studies have used machines to produce e-cigarette aerosols and measured the pollutants emitted (McAuley et al. 2012; Czogala et al. 2014; Geiss et al. 2015); others have involved the use by one or more persons of an e-cigarette and measured the change in pollutants in either a room or a test chamber after use (Schripp et al. 2013; Schober et al. 2014). One study measured airborne nicotine in the homes of e-cigarette users (Ballbe et al. 2014). The concentration of e-cigarette aerosol in a given microenvironment depends primarily on the strength of the source or the number of e-cigarettes used and the emission rate of the aerosol for that device. E-cigarettes, however, are heterogeneous in their design and in the liquids used, and the specific product combination significantly affects the second-hand emissions (Kosmider et al. 2014; Geiss et al. 2015). The number of puffs and depth of inhalation may be particularly relevant to the amount exhaled by the user and may also affect e-cigarette emissions (Talih et al. 2016).

Movement of E-Cigarette Aerosol

Similar to the case with secondhand tobacco smoke, e-cigarette aerosol is an inherently dynamic mixture that changes over time in terms of constituents and concentrations. Czogala and colleagues (2014) demonstrated a significant signal from a laser photometer indicating the presence of ambient aerosol in a room after e-cigarette use. However, this aerosol disappeared in just seconds to a few minutes as it either evaporated to the gas phase or deposited on surfaces in the room. In contrast, in the same study, secondhand cigarette smoke exhibited a particulate phase that stayed suspended in the room at high concentrations for more than 30 minutes. For the VOCs in e-cigarette aerosol, such as formaldehyde, acrolein, and acetaldehyde, the source strength and ventilation rate will largely determine their concentration in indoor air. Semi-VOCs, such as nicotine and TSNAs, are also largely affected by sorption on and subsequent desorption from surfaces and dust in a room (Singer et al. 2002, ²⁰⁰³; Goniewicz and Lee 2015). The extent of this type of thirdhand contamination from e-cigarettes in real-world settings has not been established but would be of particular concern for children living in homes of e-cigarette users, as they spend more time indoors, are in proximity to and engage in greater activity in areas where dust collects and may be resuspended (e.g., carpets on the floor), and insert non-food items in their mouths more frequently (EPA 2008; Matt et al. 2011).

Exposure to E-Cigarette Aerosol and Considerations of Dose

A large body of studies has measured exposure to secondhand and thirdhand smoke from conventional cigarettes using personal or area air monitoring, surface testing, and dust testing. Studies of the exposure of e-cigarette aerosol to nonusers, however, are limited. Schripp and colleagues (2013) observed small increases of fine and ultrafine particles and some VOCs, including PG, flavoring substances, and nicotine, indicating passive inhalation of e-cigarette aerosols by nonusers in the presence of e-cigarette users. Those authors demonstrated that the distribution in the sizes of the aerosol’s component particles changes in the lungs and results in the exhalation of smaller particles, likely caused by the evaporation of the liquid particles in the lungs and in the environment after exhalation. Schober and colleagues (2014) found substantially higher amounts of PG, VG, particulate matter (PM), and nicotine in a 45-m³ chamber during e-cigarette use sessions with volunteers compared to controlled sessions. They also found a 20% increase in the level of polycyclic aromatic hydrocarbons (PAHs) and a 2.4-fold increase in aluminum concentrations.

Williams and colleagues (2013) demonstrated contamination by metal and silicate particles in e-liquid and its aerosol using scanning electron microscopy. In a different study measuring machine-generated secondhand e-cigarette aerosol in an emission chamber, Geiss and colleagues (2015) found significant levels of PG, VG, and nicotine in the chamber’s air. Carbonyl compounds of concern (e.g., formaldehyde, acetaldehyde, acrolein, and acetone) were below the limits of detection in this study. O’Connell and colleagues (2015), who assessed secondhand e-cigarette emissions in a small meeting room (12.8 m²) with three e-cigarette users during a 165-minute session, found a significant increase in PG but did not see the expected increase in VG or nicotine. This study reported no increase in PAHs, trace metals, TSNAs, or acrolein, but did find an increase in total VOCs, formaldehyde, and acetaldehyde. However, the compounds were found at levels below guidelines for the quality of indoor air from the World Health Organization or European Union. Ruprecht and colleagues (2014) found significantly lower concentrations and counts for particles from an e-cigarette used in a 50-m³ room compared with conventional cigarettes. Interestingly, they also found that nicotine-free e-cigarettes produced higher particle levels than e-cigarettes containing nicotine. Saffari and colleagues (2014) found that total particulate exposure was 10-fold lower in e-cigarettes than it was in conventional cigarettes. Emissions of heavy metals from e-cigarettes were also dramatically less, with the exception of nickel, zinc sulfide, and silver, which showed higher emission rates from e-cigarettes. PAH levels were not elevated by e-cigarette use in this study.

Concentrations of PM, especially PM_2.5, which is fine PM, and nicotine are the two most common markers used to measure exposure to secondhand smoke (Avila-Tang et al. 2010; Apelberg et al. 2013). Indirect measures of the mass concentration of PM from secondhand smoke using real-time particle monitors are well validated in terms of the accuracy of these measurements in relation to other constituents of secondhand smoke and to health effects (Hyland et al. 2008; Apelberg et al. 2013). These same types of particle monitors are often used in studies of e-cigarette aerosol to compare PM levels from conventional cigarettes with those from e-cigarettes, though PM findings may not directly relate to the short- and long-term health effects of each product (Czogala et al. 2014; Schober et al. 2014).

Caution is warranted when interpreting the results of PM measurements comparing e-cigarettes with conventional cigarettes. The aerosols produced are fundamentally different, with the former resulting from aerosolization of liquid and the latter resulting from combustion of organic matter. The true PM_2.5 mass concentration of e-cigarette aerosol from commonly used light-scattering instruments (Czogala et al. 2014) cannot be determined without calibrating the device to a reference standard for the aerosol in question. Even this calibration would be questionable given the highly volatile nature of e-cigarette aerosol, making it difficult to capture and accurately determine the mass. Real-time PM_2.5 measurements such as this are useful, however, to determine the presence of an aerosol and to see the relative changes in this aerosol over time and under various conditions, such as changing source strength. Figure 3.3 shows the significant increase in aerosol concentration from e-cigarettes after about 1 hour and the subsequent rapid decline, presumably from initial aerosolization and deposition of this aerosol. There may still be significant amounts of this e-cigarette aerosol in the environment, but the particle monitor can no longer measure it, as it is either in the aerosol phase or deposited on surfaces. For these reasons, it is important not to rely solely on PM mass concentrations for determining exposure to e-cigarette aerosol and for making comparisons with conventional cigarettes. Measurement of the individual toxicants of concern in the aerosol phase and on surfaces is warranted.

Figure 3.3

Changes in aerosol particle PM_2.5 concentrations during experiment of e-cigarette use and tobacco cigarette smoking in an exposure chamber. Source: Czogala et al. (2014). Note: PM = particulate matter.

Health Effects of Secondhand Exposure to E-Cigarette Aerosols

Flouris and colleagues (2012, 2013) conducted two clinical studies of the health effects of secondhand exposure to e-cigarette aerosol. The researchers found no short-term change in markers of complete blood count after 1 hour of exposure to e-cigarette aerosol in a group of 15 non-smokers (Flouris et al. 2012). Similarly, the same exposure caused no significant change in short-term lung function, although the results were of borderline statistical significance (Flouris et al. 2013). However, these studies demonstrated that passive exposure to e-cigarettes causes an increase in serum cotinine that is similar to that from passive exposure to cigarette smoke, suggesting the need to examine the impact of passive aerosolized nicotine inhalation on long-term lung function. Furthermore, limited effects would likely occur in the short exposure observed through the methodologies used by Flouris and colleagues (2012, 2013), as these studies did not account for prolonged and persistent passive exposure to e-cigarette aerosols.

Several researchers have modeled the health risks of passive exposure to e-cigarettes (Colard et al. 2015) on the basis of the limited exposure data available and have come to various conclusions. Offermann (2015) concluded that, for indirect exposure, two chemicals—nicotine and PG—exceeded California EPA exposure level standards for noncarcinogenic health effects. Burstyn (2014), who compared e-cigarette aerosol exposure to workplace exposure standards, concluded that only PG and VG warrant attention in e-cigarette users while, for bystanders, none of the constituents of e-cigarette aerosol pose apparent concern. It is important to note that standards for workplace exposure are typically not appropriate to apply to the population as a whole, as they are intended for a healthy working population during a typical work day, not accounting for the risks to children, pregnant women, or those with preexisting health conditions. Further, standards for workplace exposure are very different in concentration and duration than what is to be expected from e-cigarette use.

An additional consideration for regulating e-cigarettes in indoor environments is the potential for allergic reactions in nonusers. Dermal and oral PG exposures are known causes of dermatitis and allergic sensitization (Warshaw et al. 2009; Al Jasser et al. 2011). Several e-liquids contain flavorants derived from nuts and in fact have labels cautioning persons who have nut allergies not to use these products. Research has not evaluated whether nonusers can have allergic reactions from these potential allergens in e-cigarette aerosol, but this is a risk that should be explored as 8% of U.S. children have food allergies (Gupta et al. 2011).

Evidence Summary

E-cigarette use among youth and young adults in the United States has increased considerably in recent years (see Chapter 2). There is little doubt that the use of e-cigarettes by youth and young adults represents self-administration of the drug nicotine, and this self-administration of nicotine puts youth at risk for addiction and many related harmful consequences. Animal research indicates adolescent brains are particularly sensitive to nicotine’s effects, such that subsequent self-administration is more likely, and that same literature indicates that this age group is at risk for a constellation of nicotine-induced neural and behavioral alterations. Studies of the effects of maternal smoking of conventional cigarettes during pregnancy, coupled with preclinical literature examining the effects of maternal self-administration of nicotine during pregnancy, suggest that e-cigarette use by mothers during pregnancy presents a wide variety of risks to fetal, infant, and child brain development.

Users of e-cigarettes risk respiratory exposure to a variety of aerosolized chemicals, including solvents and flavorants added intentionally to e-liquids, adulterants added unintentionally, and other toxicants produced during the heating/aerosolization process. The health impacts of frequent exposure to the toxicants in e-cigarette aerosol are not well understood, though several are known carcinogens. As highlighted previously in this chapter, the detection and level of these carcinogens depend on several factors, including the concentration of the e-liquid and the strength of the heating device. Although e-cigarettes have been used as a cessation device, the evidence supporting the effectiveness of e-cigarettes as an aid for quitting conventional cigarettes remains extremely weak for adults (Bullen et al. 2013; Caponnetto et al. 2013; Grana et al. 2014; Kalkhoran and Glantz 2016) and untested and nonexistent among youth.

Further research is warranted to focus on the characteristics of e-cigarette devices, the constituents of e-liquids, and the user behaviors that can influence the yield of nicotine and other toxicants (Shihadeh and Eissenberg 2015). This close focus includes providing details of devices (e.g., voltage of the power supply, heating element resistance) and components of e-liquids (e.g., propylene glycol, vegetable glycerin, other additives), and measuring user puff topography. Standardization of procedures for producing and delivering the aerosol is likely a necessary component of at least some in vivo and in vitro work. Preclinical work examining the effects of e-cigarette aerosols is a clear research need and, again, the standardization of procedures for production and delivery of the aerosol is necessary. To enhance relevance, the parameters of aerosol production should span the range of those seen with humans (Shihadeh and Eissenberg 2011).

The huge variety of products of different origin and design, the rapid emergence of new products, and the varied ways in which consumers use these products make the development of standard measurement conditions challenging (Famele et al. 2015). Accordingly, research is needed to understand how different design features relate to potential toxicity—for example, if the compounds in e-cigarettes are affected by heating, changes in chemical composition, or pH; if these compounds are absorbed into the bloodstream; and how additives to the e-liquid affect the bioavailability of these compounds, among other considerations. Research is also needed to understand whether potential health risks may be ameliorated by changes in product engineering.

Conclusions

1. Nicotine exposure during adolescence can cause addiction and can harm the developing adolescent brain.
2. Nicotine can cross the placenta and has known effects on fetal and postnatal development. Therefore, nicotine delivered by e-cigarettes during pregnancy can result in multiple adverse consequences, including sudden infant death syndrome, and could result in altered corpus callosum, deficits in auditory processing, and obesity.
3. E-cigarettes can expose users to several chemicals, including nicotine, carbonyl compounds, and volatile organic compounds, known to have adverse health effects. The health effects and potentially harmful doses of heated and aerosolized constituents of e-cigarette liquids, including solvents, flavorants, and toxicants, are not completely understood.
4. E-cigarette aerosol is not harmless “water vapor,” although it generally contains fewer toxicants than combustible tobacco products.
5. Ingestion of e-cigarette liquids containing nicotine can cause acute toxicity and possibly death if the contents of refill cartridges or bottles containing nicotine are consumed.

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