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Nicotine, Carcinogen, and Toxin Exposure in Long-Term E-Cigarette
and Nicotine Replacement Therapy Users
A Cross-sectional Study
Lion Shahab, PhD; Maciej L. Goniewicz, PhD; Benjamin C. Blount, PhD; Jamie Brown, PhD; Ann McNeill, PhD; K. Udeni Alwis, PhD;
June Feng, PhD; Lanqing Wang, PhD; and Robert West, PhD
Background: Given the rapid increase in the popularity of
e-cigarettes and the paucity of associated longitudinal health-
related data, the need to assess the potential risks of long-term
use is essential.
Objective: To compare exposure to nicotine, tobacco-related
carcinogens, and toxins among smokers of combustible ciga-
rettes only, former smokers with long-term e-cigarette use only,
former smokers with long-term nicotine replacement therapy
(NRT) use only, long-term dual users of both combustible ciga-
rettes and e-cigarettes, and long-term users of both combustible
cigarettes and NRT.
Design: Cross-sectional study.
Setting: United Kingdom.
Participants: The following 5 groups were purposively recruit-
ed: combustible cigarette–only users, former smokers with long-
term (≥6 months) e-cigarette–only or NRT-only use, and long-
term dual combustible cigarette–e-cigarette or combustible
cigarette–NRT users (n= 36 to 37 per group; total n= 181).
Measurements: Sociodemographic and smoking characteris-
tics were assessed. Participants provided urine and saliva
samples and were analyzed for biomarkers of nicotine, tobacco-
specific N-nitrosamines (TSNAs), and volatile organic com-
pounds (VOCs).
Results: After confounders were controlled for, no clear
between-group differences in salivary or urinary biomarkers of
nicotine intake were found. The e-cigarette–only and NRT-only
users had significantly lower metabolite levels for TSNAs (includ-
ing the carcinogenic metabolite 4-(methylnitrosamino)-1-(3-
pyridyl)-1-butanol [NNAL]) and VOCs (including metabolites of
the toxins acrolein; acrylamide; acrylonitrile; 1,3-butadiene; and
ethylene oxide) than combustible cigarette–only, dual combusti-
ble cigarette–e-cigarette, or dual combustible cigarette–NRT us-
ers. The e-cigarette–only users had significantly lower NNAL lev-
els than all other groups. Combustible cigarette–only, dual
combustible cigarette–NRT, and dual combustible cigarette–e-
cigarette users had largely similar levels of TSNA and VOC
metabolites.
Limitation: Cross-sectional design with self-selected sample.
Conclusion: Former smokers with long-term e-cigarette–only or
NRT-only use may obtain roughly similar levels of nicotine com-
pared with smokers of combustible cigarettes only, but results
varied. Long-term NRT-only and e-cigarette–only use, but not
dual use of NRTs or e-cigarettes with combustible cigarettes, is
associated with substantially reduced levels of measured
carcinogens and toxins relative to smoking only combustible
cigarettes.
Primary Funding Source: Cancer Research UK.
Ann Intern Med. doi:10.7326/M16-1107 Annals.org
For author affiliations, see end of text.
This article was published at Annals.org on 7 February 2017.
E-cigarettes (1), which produce an aerosol by heating
a solvent (e-liquid) usually containing nicotine
through a battery-powered heating element, are be-
coming increasingly popular. Unlike smoked tobacco,
e-cigarettes can deliver nicotine to the respiratory tract
without combustion (2). Despite this possible advan-
tage, health concerns for e-cigarettes remain about po-
tential cytotoxicity; delivery of carcinogens (3), includ-
ing carbonyls (4, 5), tobacco-specific N-nitrosamines
(TSNAs) (6), and heavy metals (4); effects on cardiovas-
cular and respiratory function and inflammatory effects
(7); and nicotine delivery (8). Data on the long-term ef-
fects of e-cigarettes are needed to accurately assess
risk and inform health professionals encountering
e-cigarette users (9).
Most studies to date have examined toxin concen-
trations in e-liquids or aerosols (4, 6) using cell-line or
animal models (7). However, these models may not
provide accurate information because user characteris-
tics, together with device characteristics and their inter-
actions, determine actual body-level exposure and thus
potential health consequences (10). Three studies that
have assessed such exposure found lower levels for
carcinogens, including TSNAs, in recent former smok-
ers of e-cigarettes than in a historic sample of smokers
of combustible cigarettes (11); these studies also found
reductions in toxins over a 2- or 4-week period in smok-
ers switching to e-cigarettes with or without concurrent
use of combustible cigarettes (12, 13). However, none
of the studies involved long-term users, which is impor-
tant given observed learning effects in e-cigarette use
(14, 15), or included real-world control groups to re-
duce the risk for confounding when interpreting the
results of observational studies.
Users of nicotine replacement therapy (NRT) (which
includes chewing gum and adhesive patches), would
be an appropriate control. Dual use of combustible cig-
arettes and either e-cigarettes or NRT is common, and
long-term use of both types of products has been re-
ported (16, 17). They have been advocated to reduce
the harms and risks associated with combustible to-
bacco (18). However, unlike e-cigarettes, the NRT safety
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profile is well-established (19) and NRT effectiveness
for smoking cessation through initial partial (20) or
complete substitution (21) has been shown. Therefore,
NRT is recommended as a harm reduction strategy in
several countries (22).
Although longitudinal cohort studies and random-
ized, controlled trials will provide the best data to an-
swer questions about the safety and efficacy of
e-cigarettes for smoking cessation, these designs are
time- and resource-intensive. In the absence of long-
term data, a more pragmatic approach is to compare
smokers and former smokers with or without concur-
rent e-cigarette use in real-life settings. This study
aimed to address the gap in the literature by measuring
biomarker levels in long-term e-cigarette users
compared with an appropriate control—NRT users.
Specifically, this study assessed whether long-term e-
cigarette–only, NRT-only, dual combustible cigarette–
e-cigarette, or dual combustible cigarette–NRT use is
associated with differences in metabolites of nicotine,
TSNAs, and volatile organic compounds (VOCs) com-
pared with combustible cigarette–only use.
METHODS
Study Design and Procedure
This cross-sectional study was done in London,
United Kingdom, from January 2014 to June 2014. It
evaluated the range of toxin levels measured in smok-
ers and former smokers with or without concurrent
long-term use of e-cigarettes or NRT. The study meth-
odology has been described elsewhere (23). Briefly,
participants visited the laboratory for a single session,
lasting 30 minutes, after abstaining from eating, drink-
ing, or using combustible cigarettes or other nicotine
products for an hour before their visit to standardize
assessment. At the laboratory, after providing written
consent, participants completed a short questionnaire
assessing sociodemographic, smoking, and product
use characteristics and provided breath, saliva, and
urine samples. Exhaled air was assessed for carbon
monoxide with a breathalyzer (Micro IV Smokerlyzer,
Bedfont Scientific). In addition, 2 saliva samples were
collected with sterile dental rolls (Salivette, Sarstedt)
that participants were asked to gently chew for about 2
minutes or until saturated. Urine was collected in a seal-
able, sterilized cup by participants on site and trans-
ferred by staff into cryovials. Urine and saliva samples
were then kept frozen at ⫺20 °C until they were
shipped in dry ice to laboratories at Roswell Park Can-
cer Institute (Buffalo, New York) and the Centers for
Disease Control and Prevention (Atlanta, Georgia) for
analysis. All participants were reimbursed for time and
travel (£25). The study was approved by the University
College London Ethics Committee (project ID 0483/
002).
Participants
Participants were purposively recruited in the
greater London area using various methods to increase
sample diversity, including newspapers and online ad-
vertisements, posters in pharmacies, and the use of
marketing companies. They had to be ever smokers
and to meet the following eligibility criteria: Current
smokers had to smoke an average of 5 or more com-
bustible cigarettes per day for at least 6 months, and
former smokers had to have stopped using tobacco
products (including combustible cigarettes, water
pipes, cigars, and such smokeless products as snus or
chewing tobacco) for at least 6 months. Because we
sought to evaluate the effect of long-term use of
noncombustible nicotine delivery devices (NRT and
e-cigarettes), smokers (that is, dual combustible
cigarette–e-cigarette or combustible cigarette–NRT us-
ers) and former smokers (that is, e-cigarette–only or
NRT-only users) had to have been using these products
at least weekly for 6 months or more (users of nicotine-
free products, such as e-liquid without nicotine, were
excluded). In practice, however, participants used
products daily as indicated by latency to last product
use across groups (combustible cigarettes–only users,
1.4 hours; combustible dual cigarette–NRT users, 4.3
hours; combustible dual cigarette–e-cigarette users,
1.3 hours; NRT-only users, 24 hours; and e-cigarette–
only users, 5.4 hours). Product use was verified by ask-
ing participants to bring in the NRT or e-cigarette that
they were currently using, and smoking status was ver-
ified with carbon monoxide readings (10-ppm cutoff)
(24). We excluded persons who used both NRT and
e-cigarettes as well as those who were younger than 18
years; were pregnant; had a history of heart or lung
disease; or had bleeding gums, illness, or an active in-
fection within 24 hours of their scheduled appointment.
Measures
Biomarkers of Exposure
Level of nicotine exposure was measured to assess
effectiveness of nicotine delivery products by using 2
methods. Saliva samples were analyzed for nicotine,
and its major metabolite, cotinine, using an established
gas chromatography method (25, 26). Urine samples
were analyzed for main nicotine metabolites to derive
total nicotine equivalents and for minor tobacco alka-
loids using validated tandem mass spectrometry (27,
28).
Levels of urinary TSNA and VOC metabolites were
measured using either liquid chromatography/atmo-
spheric pressure ionization/tandem mass spectrometry
(29) or ultra-high performance liquid chromatography
coupled with electrospray ionization and tandem mass
spectrometry (30) to assess the potential risks of nico-
tine delivery products. Although we assessed a com-
prehensive battery of metabolites (Appendix Table 1,
available at Annals.org), we focus here on well-
established metabolites of compounds that are known
to contribute significantly to smoking-related toxico-
logic and carcinogenic risks (31–39) (Table 1). All uri-
nary and salivary biomarkers were analyzed by the Cen-
ters for Disease Control and Prevention and Roswell
Park Cancer Institute, respectively.
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Covariates
Sociodemographic characteristics (age, sex, ethnic-
ity, education, and marital status) were assessed in ad-
dition to self-reported recently resolved physical illness
(chest infection, cold or flu, sore throat, or fever) and
subjective well-being (happiness and satisfaction, both
assessed with established single-item measures) (40).
Salivary C-reactive protein level was used as a marker
of inflammation (and thus potential health problems)
and analyzed with an enzyme-linked immunosorbent
assay (Salimetrics Europe) (41). Smoking characteris-
tics, including current and past daily combustible ciga-
rette consumption as a measure of dependence for
smokers and former smokers, respectively; age at
which participants had started smoking; and the pro-
portion of family members or friends who smoke were
assessed to gauge environmental tobacco smoke
exposure.
Statistical Analysis
Because this was a cross-sectional study, exposure
biomarkers, including metabolites of known tobacco-
related carcinogens and toxins, were used as proxies for
future disease risk. Previous research on the association
of the carcinogenic metabolite 4-(methylnitrosamino)-
1-(3-pyridyl)-1-butanol (NNAL) with lung cancer sug-
gests that medium to large reductions in NNAL levels
(Cohen f= 0.25 to 0.40) would result in an appreciable
reduction in risk (42) and could thus be considered clin-
ically meaningful in magnitude and warrant further in-
vestigation (43). A priori power calculation showed that
180 participants (36 per group) would provide 90%
power to detect between-group differences of a me-
dium effect size (Cohen f= 0.3) in NNAL levels when
comparing 5 groups by using analysis of variance (44).
However, this calculation did not account for multiple
outcomes being tested, and based on 35 biomarker
outcomes reported here, power to detect such an ef-
fect size across all biomarkers would have been re-
duced to 54%. The sample size therefore only provided
sufficient power (≥80%) to detect effects at the upper
range of the estimate (Cohen f≥ 0.36) when multiple
comparisons were accounted for.
Analyses were conducted with SPSS, version 22.0
(IBM). In initial analysis of between-group differences
on covariates, 1-way analysis of variance was used for
continuous covariates and chi-square analysis was used
for categorical covariates. Before the main analysis, uri-
nary metabolites were standardized algebraically to ac-
count for individual differences in urine concentration
by dividing metabolite data by the ratio of observed
urinary metabolites to age-, sex-, and ethnicity-adjusted
creatinine levels. Creatinine (measured by standard col-
orimetric method at Roswell Park Cancer Institute) was
also included as a covariate in the analysis (45). Due to
nonnormal distribution of data, generalized linear mod-
els with a log link and
␥
distribution were used to assess
between-group differences in outcome measures,
which were adjusted for all covariates and latency to
product use. B coefficients were exponentiated to cal-
culate the percentage of change in biomarker levels in
all groups compared with combustible cigarette–only
smokers. For prespecified tests of the main effects of a
group, type I errors were controlled for by using the
false discovery rate (46) separately for sociodemo-
Table 1. Major Toxicants and Carcinogens Related to Tobacco Use
Parent Compound Biomarker/Metabolite Rationale for Inclusion
Tobacco-specific N-nitrosamines
4-(methylnitrosamino)-1-(3-pyridyl)-
1-butanone
4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol A potent lung carcinogen (40) and major contributor to
cancer risk (34); IARC group 1 carcinogen (39)*; and 1 of 9
toxins recommended for mandated reduction in tobacco
smoke on the WHO TobReg list (36)
Volatile organic compounds
Acrolein N-acetyl-S-(3-hydroxypropyl)-L-cysteine A major contributor to respiratory effects (34, 35); IARC
group 3 carcinogen (41)†; and 1 of 9 toxins recommended
for mandated reduction in tobacco smoke on the WHO
TobReg list (36)
Acrylamide N-acetyl-S-(2-carbamoylethyl)-L-cysteine IARC group 2A carcinogen (37)‡; a neurotoxin
Acrylonitrile N-acetyl-S-(2-cyanoethyl)-L-cysteine A major contributor to cancer risk (34) and highly specific
volatile organic compound biomarker for tobacco use (33);
IARC group 2B carcinogen (37)§; and 1 of 9 toxins
considered high priority for disclosure and monitoring on
the WHO TobReg list (36)
1,3-butadiene N-acetyl-S-(4-hydroxy-2-buten-1-yl)-L-cysteine兩兩 A major contributor to cancer risk (34, 35); IARC group 1
carcinogen (42)*; and 1 of 9 toxins recommended for
mandated reduction in tobacco smoke on the WHO
TobReg list (36)
Ethylene oxide N-acetyl-S-(2-hydroxyethyl)-L-cysteine¶ IARC group 1 carcinogen (37)*
IARC = International Agency for Research on Cancer; WHO TobReg = World Health Organization Study Group on Tobacco Product Regulation.
* Carcinogenic to humans.
† Not classifiable with regard to carcinogenicity to humans.
‡ Probably carcinogenic to humans.
§ Possibly carcinogenic to humans.
兩兩 More selective metabolite of parent compound than N-acetyl-S-(3,4-dihydroxybutyl)-L-cysteine (33).
¶ A major urinary metabolite of ethylene oxide exposure and a minor metabolite of acrylonitrile and vinyl chloride exposure (toxic tobacco smoke
constituents).
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graphic comparisons (n= 13) and biomarker compari-
sons (n= 35). Where overall omnibus effects were con-
sidered significant, the Sidak correction was used in
post hoc analysis to determine which (if any) between-
group differences persisted. Biomarker values below
the limit of detection (LOD) were imputed using stan-
dard methods (LOD divided by the square root of 2)
(47), and biomarkers with 50% or more values below
the LOD were not analyzed.
Role of the Funding Source
The funding source had no role in the study de-
sign, data collection, data analysis, data interpretation,
or writing of the report. Dr. Shahab had full access to all
study data and had final responsibility for the decision
to submit the manuscript for publication.
RESULTS
Overall, participants were relatively young, were
mainly men, were white, and had at least a high school
education; about half of them were single (Table 2). On
average, participants had started smoking nearly 1
pack of cigarettes per day in their late teens, and a
substantial proportion (16% to 51%) of their family
members or friends also smoked. Salivary C-reactive
protein levels were within the range observed for
healthy adults (0.05 to 64.3 μg/L) (48), and the reported
level of well-being was similar to that of representative
population samples (40). Between-group differences
included that the proportion of women varied from
19.4% in e-cigarette–only users to 61.1% in dual com-
bustible cigarette–NRT users, fewer e-cigarette–only us-
ers were women, NRT-only users started smoking the
latest, and e-cigarette–only users had the lowest pro-
portion of family members or friends who smoked.
Considerable variation in ethnicity, marital status, com-
bustible cigarette consumption, recent illness, and re-
ported happiness levels were also found (Table 2).
As previously reported, length of product use was
broadly similar across groups at around 17 months,
and mean daily NRT and e-cigarette use, measured by
self-reported nicotine dose, was higher for NRT-only
and e-cigarette–only users than for dual combustible
cigarette–NRT and combustible cigarette–e-cigarette
users (23). For the product type used, first-generation
“cig-a-likes,” with replaceable or disposable cartridges,
were most popular among dual combustible cigarette–
e-cigarette users (60.0%). Third- or fourth-generation
advanced personal vaporizers were most popular
among e-cigarette–only users (47.2 %). Refillable pen-
style, second-generation e-cigarettes were equally
popular among dual combustible cigarette–e-cigarette
(31.4%) and e-cigarette–only (36.1%) users. For both
dual combustible cigarette–NRT and NRT-only users,
gum (44.4% and 33.3%, respectively) and patches
(both 33.3%) were the most popular NRTs, and a similar
proportion (27.8%) used more than 1 NRT.
Table 2. Sociodemographic, Smoking, Physical Health, and Subjective Well-Being Characteristics of Study Participants
Characteristic Total
Participants
(nⴝ181)
Smokers Former Smokers PValue*
Cigarette-Only
Users (nⴝ37)
Dual Cigarette–NRT
Users (nⴝ36)
Dual Cigarette–EC
Users (nⴝ36)
NRT–Only Users
(nⴝ36)
EC-Only Users
(nⴝ36)
Mean age (SD), y37.8 (11.8) 34.4 (14.0) 36.4 (8.5) 39.3 (13.1) 40.3 (11.1) 38.5 (11.1) 0.27
Female, n (%) 71 (39.2) 16 (43.2) 22 (61.1) 11 (30.6) 15 (41.7) 7 (19.4) 0.024
White, n (%) 131 (72.4) 30 (81.1) 21 (58.3) 27 (75.0) 23 (63.9) 30 (83.3) 0.111
High school, n (%) 140 (77.3) 25 (67.6) 30 (83.3) 29 (80.6) 28 (77.8) 28 (77.8) 0.56
Single, n (%) 97 (53.6) 26 (70.3) 21 (58.3) 18 (50.0) 13 (36.1) 19 (52.8) 0.104
Mean age started
smoking (SD), y
17.8 (4.3) 16.6 (3.2) 18.2 (3.4) 17.3 (3.1) 20.3 (6.4) 16.6 (3.2) 0.012
Mean cigarettes per day
(SD), n†
13.3 (8.7) 13.9 (9.0) 10.8 (4.6) 11.9 (9.6) 14.7 (10.3) 15.9 (8.3) 0.104
Mean proportion of
friends/family who
smoke (SD)
35.6 (27.5) 50.9 (23.6) 39.8 (24.1) 38.0 (32.4) 33.2 (27.7) 15.6 (15.2) <0.001
Recent illness, n (%) 42 (23.2) 14 (37.8) 3 (8.3) 7 (19.4) 10 (27.8) 8 (22.2) 0.104
Geometric mean
salivary C-reactive
protein level (SD),
nmol/L‡
0.017 (3.32) 0.020 (2.99) 0.013 (3.48) 0.016 (3.15) 0.018 (3.20)§ 0.021 (3.78) 0.47
Mean global life
satisfaction (SD)兩兩
3.9 (1.0) 4.1 (0.9) 3.8 (1.1) 3.7 (1.1) 3.9 (0.9) 3.9 (1.1) 0.54
Mean happiness levels
(SD)¶
5.0 (1.5) 4.6 (1.7) 5.6 (1.1) 4.7 (1.7) 5.3 (1.3) 5.0 (1.6) 0.104
Cigarette = combustible cigarette; EC = e-cigarette; NRT = nicotine replacement therapy.
* Omnibus test result, adjusted for the reported comparisons in this table using the false discovery rate (46).
† Former smokers were asked about their typical past consumption levels.
‡ Statistical comparison conducted on log-transformed values (not shown).
§ Data are missing for 1 participant.
兩兩 Assessed by asking, “All things considered, how satisfied are you with your life as a whole?” Response options ranged from “very dissatisfied” (1)
to “very satisfied” (5).
¶ Assessed by asking, “Some people are very generally very happy. They enjoy life regardless of what is going on, getting the most out of
everything. To what extent does this characterization describe you?” Response options ranged from “not at all” (1) to “a great deal” (7).
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Nicotine Levels
Nicotine intake among the products was roughly
similar (Figure 1), with some variation across groups
(Appendix Table 1). For urinary biomarkers, users of all
products had levels of total nicotine equivalents at least
as high as combustible cigarette–only users in adjusted
analysis (Table 3). Findings related to salivary biomark-
ers varied. Dual combustible cigarette–NRT users had
relatively low nicotine and cotinine levels, and e-
cigarette–only users had relatively low nicotine
levels—at around half that of combustible cigarette–
only users—with other groups obtaining levels slightly
less or more than those from combustible cigarette–
only users (Table 3). The minor tobacco alkaloids
anabasine and anatabine, which are specific to tobacco
as opposed to nicotine exposure, were clearly distin-
guished between smokers and former smokers, with
significantly lower levels than combustible cigarette–
only, dual combustible cigarette–NRT, or dual combus-
tible cigarette–e-cigarette users (Appendix Table 1).
TSNA Levels
There were clear between-group differences in
NNAL levels (Figure 2). The NRT-only and e-cigarette–
only users had markedly lower NNAL levels than com-
bustible cigarette–only, dual combustible cigarette–
NRT, and dual combustible cigarette–e-cigarette users
(P< 0.001); e-cigarette–only users had significantly
lower NNAL levels than all other groups—equivalent to
a 97% reduction compared with the levels of combus-
tible cigarette–only users (Table 3). Compared with
combustible cigarette–only users, there were no large
differences in NNAL levels for dual combustible
cigarette–e-cigarette users but dual combustible
cigarette–NRT users had somewhat lower NNAL levels.
Results followed a similar, albeit less pronounced, pat-
tern for the other TSNAs measured (Appendix Table 1).
VOC Levels
Of the major urinary VOC metabolites, e-cigarette–
only users had the lowest levels overall, with acryloni-
trile levels as low as 2.9% for combustible cigarette–
only users; further, NRT-only users had the second
lowest levels overall, with acrylonitrile levels as low as
10.5% for combustible cigarette–only users (Table 3).
By contrast, dual combustible cigarette–NRT, dual
combustible cigarette–e-cigarette, and combustible
cigarette–only users all had very similar urinary VOC
metabolite levels (Figure 2). Compared with all other
groups, NRT-only and e-cigarette–only users had at
least half of the reference values of combustible
cigarette–only users (Table 3) and had significantly
lower levels of all major metabolites of selected toxic
and carcinogenic VOCs (all P< 0.001) (Appendix
Table 1).
Results were largely confirmed by reviewing other
VOC metabolites that were assessed. E-cigarette–only
users generally had the lowest levels, followed by NRT-
only users, with no detectable differences among dual
combustible cigarette–NRT, dual combustible cigarette–
e-cigarette, and combustible cigarette–only users
(Appendix Table 1). The only exceptions were metab-
Figure 1.
Urinary and salivary nicotine metabolite levels,
by group.
0
8000
7000
3000
2000
2500
1500
500
0
2000
1000
1000
0
Cigarette-
Only
Total Nicotine Equivalents, nmol/mg of creatinine*
Nicotine, ng/mL†Cotinine, ng/mL†
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
Cigarette-
Only
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
Cigarette-
Only
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
25
50
75
100
125
150
175
200
225
250
275
Boxplots show the median with interquartile range (25th percentile,
75th percentile). Error bars show Tukey's whiskers, and crosses indi-
cate arithmetic means (geometric means are provided in Appendix
Table 1). Circles indicate outliers. Cigarette = combustible cigarette;
EC = e-cigarette; NRT = nicotine replacement therapy.
* Measured in urine. Data are raw values divided by the ratio of ob-
served urinary metabolites to covariate-adjusted creatinine levels. Val-
ues below the limit of detection were imputed by the limit of detection
divided by square root of 2.
† Measured in saliva. There were no significant between-group
differences.
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olites of benzene (N-acetyl-S-(phenyl)-L-cysteine [PMA]
and muconic acid [MU]), carbon disulfide (2-
thioxothiazolidine-4-carboxylic acid [TTCA]), and sty-
rene (N-acetyl-S-(1- and 2-phenyl-2-hydroxyethyl)-L-
cysteine [PHEMA] and phenylglyoxylic acid [PGA]).
Dual combustible cigarette–e-cigarette users had
somewhat higher PMA, MU, and PHEMA levels, and
dual combustible cigarette–NRT and combustible
cigarette–e-cigarette users had somewhat higher PGA
levels than other groups (Appendix Table 1). There
were no appreciable between-group differences in
TTCA levels. However, these metabolites were either
nonspecific to the parent VOC measured (MU and
TTCA have dietary contributions, and PGA is a metab-
olite of ethylbenzene and styrene exposure) or had low
detection rates (PMA and PHEMA) (Appendix Table 2,
available at Annals.org).
DISCUSSION
To our knowledge, this is the first direct compari-
son of the metabolite levels of nicotine and important
carcinogens and toxins in long-term e-cigarette or NRT
users. We found that former smokers who had switched
to e-cigarette–only or NRT-only use obtained roughly
similar levels of nicotine compared with combustible
cigarette–only smokers, but results varied. Long-term
NRT-only use and especially e-cigarette–only use, but
not dual use of NRTs or e-cigarettes with combustible
cigarettes, were associated with lower levels of known
tobacco-related carcinogens and toxins measured in
this study compared with combustible cigarette–only
use.
The finding that NRT-only or e-cigarette–only use is
associated with roughly similar nicotine intake com-
pared with that of combustible cigarette–only use sup-
ports the view that users seek a particular level of nico-
tine intake, regardless of the delivery system (49), and
adjust product use accordingly (50). This finding is con-
sistent with more recent (51) but not older (8) studies
on nicotine delivery from e-cigarettes, which may re-
flect the improved design of newer generations of
e-cigarettes (52), and highlights the importance of fo-
cusing on experienced, long-term users rather than na-
ive, short-term users. Similarly, efficient nicotine intake
from NRT-only use has been observed in long-term (53)
but not short- or intermediate-term NRT users (54). Nic-
otine intake was largely similar for both groups, which
suggests that greater craving reductions observed in
e-cigarette–only users than in NRT-only users (23, 55)
may be due to factors other than nicotine delivery, such
as the greater behavioral similarity of e-cigarette use
(unlike NRT use) with smoking. This is consistent with
research on nonnicotine sensory factors that have been
shown to influence tobacco withdrawal (56). However,
this study was not powered to detect anything other
than relatively large effects, so results about smaller dif-
ferences in nicotine intake between e-cigarettes and
NRTs are indeterminate.
The lower levels of carcinogens and toxins associ-
ated with NRT-only and e-cigarette–only use in this
study confirm the known low risk for complications
from long-term NRT use (57). This finding also under-
scores the translation of greatly reduced concentra-
tions of some carcinogens and toxins from e-liquids
Table 3. Adjusted Biomarker Levels by Group as a Proportion of Cigarette-Only Smoker Levels*
Parent Compound Biomarker/Metabolite Smokers Former Smokers
Dual
Cigarette–NRT
Users (nⴝ36)
Dual
Cigarette–EC
Users (nⴝ36)
NRT-Only
Users (nⴝ36)
EC-Only
Users (nⴝ36)
Alkaloids
Nicotine Total nicotine equivalents† 104.2 (64.3–168.9) 156.8 (105.1–233.8) 121.6 (62.5–236.8) 126.9 (82.1–196.2)
Nicotine‡ 64.2 (39.2–104.9) 152.2 (90.7–255.1) 135.1 (68.1–268.0) 60.4 (35.8–101.8)
Cotinine‡ 46.8 (26.3–83.3) 69.7 (42.1–115.3) 82.1 (42.9–157.3) 75.1 (45.3–124.4)
Tobacco-specific N-nitrosamines
4-(methylnitrosamino)-1-(3-
pyridyl)-1-butanone
4-(methylnitrosamino)-
1-(3-pyridyl)-1-butanol
57.1 (33.1–98.4) 81.2 (49.7–132.8) 11.6 (6.3–21.3) 2.5 (1.5–4.2)
Volatile organic compounds
Acrolein N-acetyl-S-(3-hydroxypropyl)-
L-cysteine
107.1 (71.8–159.7) 91.2 (60.2–138.2) 35.3 (23.5–53.0) 33.3 (20.9–53.1)
Acrylamide N-acetyl-S-(2-carbamoylethyl)-
L-cysteine
80.2 (57.9–111.1) 115.9 (80.8–166.1) 45.4 (32.4–63.5) 42.9 (31.1–59.2)
Acrylonitrile N-acetyl-S-(2-cyanoethyl)-L-cysteine 85.6 (48.7–150.4) 102.7 (63.7–165.6) 10.5 (5.4–20.6) 2.9 (1.7–4.7)
1,3-butadiene N-acetyl-S-(4-hydroxy-2-buten-
1-yl)-L-cysteine
101.9 (64.6–160.7) 115.0 (73.2–180.6) 19.9 (12.8–30.7) 11.0 (7.5–16.1)
Ethylene oxide, acrylonitrile,
and vinyl chloride
N-acetyl-S-(2-hydroxyethyl)-
L-cysteine
86.6 (58.7–127.8) 104.0 (73.9–146.4) 54.2 (38.4–76.5) 43.5 (30.8–61.3)
Cigarette = combustible cigarette; EC = e-cigarette; NRT = nicotine replacement therapy.
* Levels as a proportion of cigarette-only smoker levels are estimated from a model that adjusted for all variables in Table 2, latency to product use,
and creatinine levels. For urinary metabolites, inputs to the model were divided by the ratio of observed to covariate-adjusted creatinine levels.
Values are percentages (95% CIs).
† Sum of cotinine, nicotine, trans-3'-hydroxycotinine, cotinine N-oxide, nicotine 1'-oxide, norcotinine, and nornicotine levels measured in urine.
‡ Measured in saliva (all other metabolites were measured in urine).
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and aerosols (4, 6, 58) to body-level exposure, contrary to worries that long-term e-cigarette use would result in
Figure 2.
Urinary metabolite levels for selected toxins and carcinogens, by group.
Cigarette-
Only
A
B
C
D
E
F
NNAL, pg/mg of creatinine
CYMA, ng/mg of creatinine
3HPMA, ng/mg of creatinine
MHBMA3, ng/mg of creatinine
AAMA, ng/mg of creatinine
HEMA, ng/mg of creatinine
0
100
200
300
400
500
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
Cigarette-
Only
0
100
200
400
500
600
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
300
Cigarette-
Only
0
1000
2000
4000
5000
6000
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
3000
Cigarette-
Only
0
100
200
300
400
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
Cigarette-
Only
0
100
200
400
500
600
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
300
Cigarette-
Only
0
4
6
10
12
Dual
Cigarette–
NRT
NRT-Only EC-OnlyDual
Cigarette–
EC
2
8
Data are raw values divided by ratio of observed urinary metabolites to covariate-adjusted creatinine levels. The levels below the limit of detection
were imputed by the limit of detection divided by square root of 2. Boxplots show the median with interquartile range (25th percentile, 75th
percentile). Error bars show Tukey's whiskers, and cross indicate arithmetic means (geometric means are provided in Appendix Table 1). Circles
indicate outliers. Significant pairwise comparisons are presented in Appendix Table 1. Cigarette = combustible cigarette; EC = e-cigarette; NRT =
nicotine replacement therapy. A. Tobacco-specific N-nitrosamine. NNAL = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol. B. Acrolein. 3HPMA =
N-acetyl-S-(3-hydroxypropyl)-L-cysteine. C. Acrylamide. AAMA = N-acetyl-S-(2-carbamoylethyl)-L-cysteine. D. Acrylonitrile. CYMA = N-acetyl-S-(2-
cyanoethyl)-L-cysteine. E. 1,3-butadiene. MHBMA3 = N-acetyl-S-(4-hydroxy-2-buten-1-yl)-L-cysteine. F. Ethylene oxide. HEMA = N-acetyl-S-
(2-hydroxyethyl)-L-cysteine.
E-Cigarettes and Toxin Exposure ORIGINAL RESEARCH
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substantial harmful exposure (59). Given the involve-
ment of these TSNAs and VOCs with cancer, cardiovas-
cular diseases, and pulmonary diseases (42, 60), our
results suggest that complete substitution of combusti-
ble cigarettes with e-cigarettes may reduce disease risk
and support the assertion that e-cigarette use may be
less harmful than smoking (2, 61–63). We found no ev-
idence that long-term e-cigarette–only use was associ-
ated with greater levels of carcinogens or toxins than
NRT-only use; on some measures, e-cigarette–only use
was associated with lower levels. Although this could
be due to occasional combustible cigarette smoking
lapses by long-term NRT-only users, it is unlikely to
have made a substantial contribution, given very low
levels of tobacco-specific (as opposed to nicotine-
specific) biomarkers for acrylonitrile, anabasine, and
anatabine (64, 65) in this group. Alternatively, these dif-
ferences may reflect typical low-level contamination in
these products (for example, with TSNAs from tobacco-
derived nicotine) (66), nonspecificity of the metabolite
for the toxin (for example, muconic acid for benzene)
(67), or non–smoking-related environmental sources of
toxin exposure (for example, for styrene) (68). Contrary
to findings from a recent short-term switching study
(12), dual combustible cigarette–NRT or combustible
cigarette–e-cigarette use was not associated with ap-
preciable reductions in carcinogen and toxin levels.
This may be because participants in our study may have
been even heavier smokers before starting concurrent
e-cigarette or NRT use, thus masking the benefit of po-
tential partial substitution in our cross-sectional study,
or because dual users used noncombustible products
to bridge times of nonsmoking and thus did not actu-
ally reduce combustible cigarette consumption. Alter-
natively, lack of notable reductions in carcinogens and
toxins after dual use may reflect either differences in
study design (for example, different use pattern in
long-term vs. short-term users) or our study's relatively
low power to detect smaller, yet meaningful, effects.
Further longitudinal research is needed to differentiate
among these explanations.
Our findings have several implications. Although
complete, long-term switching to e-cigarettes may pro-
duce a net benefit for the health outcomes of the smok-
ing population because e-cigarette–only use signifi-
cantly reduced exposure to known tobacco-related
carcinogens and toxins, we found that dual use of
e-cigarettes with combustible cigarettes did not reduce
exposure appreciably. Therefore, e-cigarettes are likely
to be beneficial only if complete cessation of combus-
tible cigarette smoking is achieved. Thus, dual users
should be encouraged to cease using combustible
products to reduce long-term health risks. Our results
also indicate that machine-derived and actual body-
level exposure to toxins can be very different, as shown,
for example, by greatly reduced aldehyde levels in
e-cigarette users in this study compared with report-
edly high levels in e-cigarette aerosols under certain
laboratory conditions (5, 69). Of note, although e-
cigarette–only and NRT-only use was associated with
marked reductions in carcinogens and toxins com-
pared with combustible cigarette–only use, use of
these products did not eliminate exposure (and thus
possible health risks) completely. Full cessation of all
nicotine products remains the best option to avoid
harm.
The study had several limitations. Although partic-
ipants were recruited through diverse methods, result-
ing in a sample broadly similar to the population of
NRT and e-cigarette users (16, 70), and we controlled
for important confounders, between-group differences
may not generalize and reflect self-selection. The sam-
ple was too small to allow more sophisticated analyses
to evaluate the association of different types of
e-cigarettes or NRTs (and other characteristics, such as
e-cigarette flavors) with intake, and we may not have
picked up on small but important differences in expo-
sure levels. In particular, the lack of between-group dif-
ferences in nicotine intake has to be interpreted cau-
tiously given the low power to detect smaller effects
and the variability across different urinary and salivary
measures. Lastly, we did not assess indirect exposure
and the analysis was limited by the number of biomark-
ers available and spot sampling, which can only pro-
vide a snapshot of exposure. However, given the lack of
long-term data, we chose this pragmatic design to
quickly evaluate potentially important associations of
e-cigarette use with intake of carcinogens and toxins to
inform further longitudinal work. Moreover, the rela-
tively slow pharmacokinetics of the assessed metabo-
lites provides stable estimates of recent exposure and
should militate against variations associated with differ-
ent patterns of use for different products. Future work
should sample a larger range of biomarkers over a lon-
ger period, including those of actual harm, such as lung
function measures, and evaluate the effect of potential
interactions of users with device characteristics on the
delivery of toxins to users and bystanders.
In conclusion, long-term NRT-only or e-cigarette–
only use among former smokers is associated with sub-
stantially reduced levels of selected carcinogens and
toxins compared with combustible cigarette smoking;
however, concurrent use of NRTs or e-cigarettes with
combustible cigarettes does not seem to offer this ben-
efit. We found no evidence that e-cigarette–only use
compared with NRT-only use is associated with greater
levels of carcinogens and toxins. Nicotine delivery of
e-cigarettes and NRTs, although variable, is roughly
similar to combustible cigarettes, but smaller meaning-
ful differences may exist.
From University College London and King's College, London,
United Kingdom; Roswell Park Cancer Institute, Buffalo, New
York; and Centers for Disease Control and Prevention, At-
lanta, Georgia.
Disclaimer: The content is solely the responsibility of the au-
thors and does not necessarily represent the official views of
the National Institutes of Health and the U.S. Food and Drug
Administration.
Acknowledgment: The authors thank Kate Sheals and Victoria
Nelson for their help with data collection and the Centers for
ORIGINAL RESEARCH E-Cigarettes and Toxin Exposure
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Disease Control and Prevention reviewers for providing a
thorough review of the manuscript.
Financial Support: This work was supported by Cancer Re-
search UK (grant C27061/A16929, with additional funding
from grants C1417/A14135 and C36048/A11654). Dr.
Brown's post is funded by a fellowship from the Society for the
Study of Addiction, and Cancer Research UK also provides
support (grants C1417/A7972 and C44576/A19501). Drs. Mc-
Neill and West are part of the UK Centre for Tobacco and
Alcohol Studies, which is a UK Clinical Research Collaboration
Public Health Research Centre of Excellence. Funding from
the Medical Research Council, British Heart Foundation, Can-
cer Research UK, Economic and Social Research Council, and
the National Institute for Health Research under the auspices
of the UK Clinical Research Collaboration is gratefully ac-
knowledged (grant MR/K023195/1). Dr. Goniewicz was sup-
ported by the National Institute on Drug Abuse and the Na-
tional Cancer Institute of the National Institutes of Health
(awards R01DA037446 and P30 CA016056, respectively) and
by an award from Roswell Park Alliance Foundation.
Disclosures: Dr. Shahab reports grants from Cancer Research
UK during the conduct of the study and grants from Pfizer
(unrestricted research funding to study smoking cessation)
and personal fees from Atlantis Health Care outside of the
submitted work. Dr. Goniewicz reports grants from Pfizer
(2011 GRAND [Global Research Awards for Nicotine Depen-
dence] recipient) and personal fees from Johnson & Johnson
(as a member of the advisory board) outside the submitted
work. Dr. Brown reports grants (unrestricted research funding
to study smoking cessation) from Pfizer outside the submitted
work. Dr. West reports grants, personal fees, and nonfinancial
support (that is, research grants, consultancy, travel, and hos-
pitality) from Pfizer, Johnson & Johnson, and GlaxoSmithKline
outside the submitted work; in addition, Dr. West's salary is
funded by Cancer Research UK and he is an advisor to the UK
National Centre for Smoking Cessation and Training. Authors
not named here have disclosed no conflicts of interest. Disclo-
sures can also be viewed at www.acponline.org/authors/icmje
/ConflictOfInterestForms.do?msNum=M16-1107.
Reproducible Research Statement: Study protocol: Not avail-
able. Statistical code and data set: Available from Dr. Shahab
(e-mail, lion.shahab@ucl.ac.uk).
Requests for Single Reprints: Lion Shahab, PhD, Department
of Epidemiology and Public Health, University College Lon-
don, 1-19 Torrington Street, London WC1E 7HB, United King-
dom; e-mail, lion.shahab@ucl.ac.uk.
Current author addresses and author contributions are avail-
able at Annals.org.
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E-Cigarettes and Toxin Exposure ORIGINAL RESEARCH
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Current Author Addresses: Drs. Shahab and West: Depart-
ment of Epidemiology and Public Health, University College
London, 1-19 Torrington Street, London WC1E 7HB, United
Kingdom.
Dr. Goniewicz: Department of Health Behavior, Roswell Park
Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263.
Drs. Blount, Alwis, Feng, and Wang: Tobacco and Volatiles
Branch, Division of Laboratory Sciences, National Center for
Environmental Health, Centers for Disease Control and Pre-
vention, 4770 Buford Highway, Atlanta, GA 30341.
Dr. Brown: Department of Clinical, Educational and Health
Psychology, University College London, 1-19 Torrington
Street, London WC1E 7HB, United Kingdom.
Dr. McNeill: Addictions Department, Institute of Psychiatry,
Psychology and Neuroscience, King's College London, 4
Windsor Walk, London SE5 8AF, United Kingdom.
Author Contributions: Conception and design: L. Shahab,
M.L. Goniewicz, J. Brown, A. McNeill, R. West.
Analysis and interpretation of the data: L. Shahab, M.L. Gonie-
wicz, B.C. Blount, J. Brown, J. Feng, L. Wang, R. West.
Drafting of the article: L. Shahab, B.C. Blount, A. McNeill, K.U.
Alwis, R. West.
Critical revision of the article for important intellectual con-
tent: L. Shahab, M.L. Goniewicz, B.C. Blount, J. Brown, A. Mc-
Neill, R. West.
Final approval of the article: L. Shahab, M.L. Goniewicz, B.C.
Blount, J. Brown, A. McNeill, R. West.
Statistical expertise: L. Shahab.
Obtaining of funding: L. Shahab, B.C. Blount, J. Brown.
Administrative, technical, or logistic support: L. Shahab, M.L.
Goniewicz.
Collection and assembly of data: L. Shahab, M.L. Goniewicz,
B.C. Blount, J. Feng.
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Appendix Table 1. Urinary and Saliva Biomarker Levels, by Group*
Parent Compound Biomarker/Metabolite Smokers Former Smokers PValue†
Cigarette-Only Users
(nⴝ37) Dual Cigarette–NRT
Users (nⴝ36) Dual Cigarette–EC Users
(nⴝ36) NRT-Only Users (nⴝ36) EC-Only Users (nⴝ36)
Tobacco alkaloids (saliva),
ng/mL
Nicotine Nicotine‡ 260.3 (189.1–358.4) 147.2 (102.1–212.0) 299.4 (193.2–464.0) 158.5 (97.1–258.6) 184.4 (125.2–271.6) 0.003§
Cotinine‡ 174.8 (105.1–290.8) 67.1 (39.1–115.1) 149.2 (95.8–232.3) 83.9 (45.8–153.7) 179.6 (118.1–273.0) 0.134
Tobacco alkaloids (urine)
Nicotine, nmol/mg of
creatinine Total nicotine equivalents‡ 21.1 (14.0–31.8) 8.5 (3.9–18.4) 28.8 (16.6–49.8) 6.3 (2.9–14.1) 25.0 (14.8–42.0) 0.204
trans-3'-Hydroxycotinine 8.5 (5.1–14.3) 3.2 (1.4–7.4) 10.9 (6–19.8) 2.8 (1.2–6.3) 11.4 (6.5–19.9) 0.442
Cotinine 5.9 (3.8–9.3) 1.8 (0.7–4.4) 8.2 (4.6–14.8) 1.4 (0.6–3.5) 7.5 (4.5–12.4) 0.188
Nicotine 1.9 (1.2–3.3) 1.2 (0.5–2.5) 4 (2.3–7.1) 0.8 (0.3–1.7) 2.5 (1.5–4.2) 0.088
Cotinine N-oxide 0.6 (0.4–1.0) 0.2 (0.1–0.5) 0.8 (0.5–1.4) 0.2 (0.1–0.4) 0.8 (0.5–1.3) 0.254
Nicotine 1'-oxide 0.7 (0.4–1.1) 0.4 (0.2–0.8) 1.3 (0.7–2.2) 0.2 (0.1–0.6) 0.9 (0.5–1.6) 0.166
Norcotinine 0.2 (0.1–0.3) 0.1 (0.1–0.2) 0.3 (0.2–0.5) 0.1 (0.1–0.1) 0.2 (0.1–0.3) 0.161
Nornicotine 0.2 (0.1–0.2) 0.1 (0.1–0.2) 0.2 (0.1–0.4) 0.1 (0.1–0.1) 0.1 (0.1–0.2) 0.022§
Anabasine, pmol/mg of
creatinine Anabasine 17.0 (11.2–25.8)兩兩¶ 11.1 (6.3–19.4) 25.5 (16.3–40.1)兩兩¶ 5.5 (3.5–8.7)**†† 6.2 (4.1–9.5)**†† <0.001
Anatabine, pmol per
milligram of creatinine Anatabine 26.0 (16.3–41.4)兩兩¶ 14.9 (7.6–29.2)兩兩 36.0 (22.0–59.1)兩兩¶ 3.8 (2.4–6.2)**††‡‡ 4.6 (2.8–7.6)**†† <0.001
Tobacco-specific
N-nitrosamines, pg/mg of
creatinine
4-(methylnitrosamino)-1-(3-
pyridyl)-1-butanone
(NNK)
4-(methylnitrosamino)-1-(3-pyridyl)-1-
butanol (NNAL)‡ 53.4 (36.6–77.8)兩兩¶ 24.4 (13.2–45.1)兩兩¶ 44.5 (28.5–69.4)兩兩¶ 4.83 (2.79–8.34)¶**††‡‡ 1.47 (1.02–2.12)兩兩**††‡‡ <0.001
N'-nitrosoanabasine N'-nitrosoanabasine (NAB) 6.17 (4.31–8.82)兩兩¶ 3.64 (2.20–6.02)兩兩¶ 6.02 (4.15–8.73)兩兩¶ 1.52 (1.09–2.12)**††‡‡ 1.07 (0.79–1.47)**††‡‡ <0.001
N'-nitrosoanatabine N'-nitrosoanatabine (NAT) 32.8 (20.5–52.5)兩兩¶ 11.8 (5.77–24.0)兩兩¶ 30.8 (18.5–51.1)兩兩¶ 2.95 (1.81–4.81)**††‡‡ 1.79 (1.21–2.67)**††‡‡ <0.001
Volatile organic
compounds, ng/mg of
creatinine
Acrolein N-acetyl-S-(2-carboxyethyl)-L-
cysteine (CEMA) 119.8 (88.2–162.9)兩兩¶ 136.1 (100.7–184)兩兩¶ 141.8 (106.7–188.4)兩兩¶ 67.8 (49.3–93.2)**††‡‡ 54.6 (41.7–71.4)**††‡‡ <0.001
N-acetyl-S-(3-hydroxypropyl)-L-
cysteine (3HPMA)‡ 488.4 (345.1–691.2)兩兩¶ 499.7 (350–713.5)兩兩¶ 574.5 (429.1–769.2)兩兩¶ 236.1 (168.1–331.6)**††‡‡ 175.3 (124–247.8)**††‡‡ <0.001
Acrylamide N-acetyl-S-(2-carbamoylethyl)-L-
cysteine (AAMA)‡ 65.6 (50.6–85.1)兩兩¶ 52.5 (40.4–68.4)兩兩¶ 82.4 (66.1–102.8)兩兩¶ 33.6 (25.8–43.7)**††‡‡ 29.3 (22.3–38.3)**††‡‡ <0.001
N-acetyl-S-(2-carbamoyl-2-
hydroxyethyl)-L-cysteine (GAMA) 18.5 (14.7–23.3)兩兩¶ 16.8 (13.1–21.5) 24.3 (19.6–30.2)兩兩¶ 12.1 (9.5–15.5)**†† 10.0 (7.6–13.2)**†† <0.001
Acrylonitrile N-acetyl-S-(2-cyanoethyl)-L-cysteine
(CYMA)‡ 49.2 (32.9–73.6)兩兩¶ 28.4 (15.6–51.9)兩兩¶ 51.6 (33.6–79.2)兩兩¶ 3.7 (2.1–6.5)**††‡‡ 1.4 (1.1–1.9)**††‡‡ <0.001
Benzene trans,trans-muconic acid (MU) 78.6 (58.2–106.2) 106.8 (72.7–157.0) 135.0 (102.3–178.1)¶ 131.8 (94.1–184.5) 55.2 (42.3–71.9)†† 0.002
N-acetyl-S-(phenyl)-L-cysteine (PMA) 0.64 (0.48–0.84)†† 0.44 (0.30–0.63)†† 1.43 (1.11–1.83)¶**‡‡ 0.52 (0.37–0.71) 0.74 (0.55–0.98)†† <0.001
1,3-butadiene N-acetyl-S-(3,4-dihydroxybutyl)-L-
cysteine (DHBMA) 202.7 (162.8–252.3)¶ 204.3 (162.3–257.3)¶ 294.9 (242.9–358.0)¶ 204.2 (156.9–265.9) 156.3 (126.0–193.8)**††‡‡ <0.001
N-acetyl-S-(4-hydroxy-2-buten-1-yl)-
L-cysteine (MHBMA3)‡ 29.8 (19.9–44.8)兩兩¶ 23.9 (15.1–37.9)兩兩¶ 36.6 (25.4–52.6)兩兩¶ 7.67 (5.08–11.6)**††‡‡ 4.44 (3.42–5.78)**††‡‡ <0.001
Continued on following page
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Appendix Table 1—Continued
Parent Compound Biomarker/Metabolite Smokers Former Smokers PValue†
Cigarette-Only Users
(nⴝ37) Dual Cigarette–NRT
Users (nⴝ36) Dual Cigarette–EC Users
(nⴝ36) NRT-Only Users (nⴝ36) EC-Only Users (nⴝ36)
Carbon disulfide 2-thioxothiazolidine-4-carboxylic acid
(TTCA) 6.03 (4.40–8.27) 13.8 (8.79–21.7) 9.95 (6.85–14.5) 13.4 (9.07–19.7) 6.84 (4.33–10.8) 0.015§
Crotonaldehyde N-acetyl-S-(3-hydroxypropyl-1-
methyl)-L-cysteine (HPMMA) 804.2 (563.8–1147.1)兩兩¶ 735.3 (495.2–1091.7)兩兩¶ 1199.5 (881.9–1631.6)兩兩¶ 366.3 (266.0–504.5)**††‡‡ 235.9 (179.1–310.7)**††‡‡ <0.001
Cyanide 2-aminothiazoline-4-carboxylic acid
(ATCA) 91.2 (69.6–119.5)¶ 107.1 (79.4–144.5)兩兩¶ 132.3 (97.8–179.0)兩兩¶ 102.0 (72.6–143.4) 55.3 (41.0–74.5)**††‡‡ 0.013
N,N-dimethylformamide N-acetyl-S-(N-methylcarbamoyl)-L-
cysteine (AMCC) 162.2 (120.6–218.1)¶ 138.5 (95.4–201.2)¶ 176.3 (129.1–240.5)¶ 100.2 (72.4–138.7) 60.8 (44.4–83.3)**††‡‡ <0.001
Ethylene oxide,
acrylonitrile, vinyl
chloride
N-acetyl-S-(2-hydroxyethyl)-L-
cysteine (HEMA)‡ 0.81 (0.61–1.07)兩兩¶ 0.81 (0.55–1.18) 1.15 (0.84–1.57)兩兩¶ 0.64 (0.48–0.84)**†† 0.42 (0.32–0.55)**††‡‡ <0.001
Propylene oxide N-acetyl-S-(2-hydroxypropyl)-L-
cysteine (2HPMA) 41.1 (30.4–55.6)¶ 47.3 (35.6–63.0)¶ 68.9 (52.6–90.4)兩兩¶ 37.4 (28.7–48.9)†† 29.3 (21.9–39.3)**††‡‡ <0.001
Styrene Mandelic acid (MA) 188.6 (147.4–241.2)¶ 198.7 (153.8–256.7)¶ 227.2 (181.1–284.9)¶ 173.0 (127.3–235.3) 100.8 (78.2–129.9)**††‡‡ <0.001
N-acetyl-S-(1 and
2-phenyl-2-hydroxyethyl)-L-
cysteine (PHEMA)
0.75 (0.57–0.98) 0.82 (0.56–1.18) 1.09 (0.8–1.48)¶ 0.75 (0.55–1.00) 0.48 (0.36–0.63)†† 0.001
Styrene, ethylbenzene Phenylglyoxylic acid (PGA) 88.0 (62.6–123.8) 129.9 (92.1–183.3)¶ 124.5 (91.1–170.0) 88.1 (60.6–128.2) 71.1 (53.7–94.1)‡‡ 0.007
Xylene 2-methylhippuric acid (2MHA) 41.9 (30.1–58.4)兩兩¶ 36.3 (23.9–55.2)兩兩¶ 56.9 (41.8–77.4)兩兩¶ 19.6 (13–29.7)**††‡‡ 10.5 (7.80–14.2) <0.001
3- + 4-methylhippuric acids (34MHA) 266.5 (182.1–390.1)兩兩¶ 181.1 (119.7–274.0)兩兩¶ 273.2 (201.1–371.0)兩兩¶ 76.3 (48.8–119.4)**††‡‡ 51.4 (38.5–68.6)**††‡‡ <0.001
Cigarette = combustible cigarette; EC = e-cigarette; NRT = nicotine replacement therapy.
* Data presented are log-transformed raw values (for urinary metabolites also standardized for creatinine). Statistical comparisons were carried out on nontransformed data and adjusted for all
variables in Table 2, latency to product use, and creatinine levels. Values are geometric means (95% CIs).
† Omnibus test result, adjusted for the number of reported comparisons in this table using the false discovery rate (46).
‡ Non–log-transformed data shown in Figures 1 and 2.
§ Overall differences but no significant (Sidak-corrected) difference in post hoc test.
兩兩 Indicates statistically significant (Sidak-corrected) difference (P< 0.05) for NRT-only users.
¶ Indicates statistically significant (Sidak-corrected) difference (P< 0.05) for EC-only users.
** Indicates statistically significant (Sidak-corrected) difference (P< 0.05) for cigarette-only smokers.
†† Indicates statistically significant (Sidak-corrected) difference (P< 0.05) for dual cigarette–EC users.
‡‡ Indicates statistically significant (Sidak-corrected) difference (P< 0.05) for dual cigarette–NRT users.
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Appendix Table 2. Proportion of Samples Below Limit of Detection, by Group and Across All Samples*
Biomarker/Metabolite† Limit of
Detection
All
Samples
Smokers Former Smokers
Cigarette-Only
Users (nⴝ37)
Dual
Cigarette–NRT
Users (nⴝ36)
Dual
Cigarette–EC
Users (nⴝ36)
NRT-Only
Users
(nⴝ36)
EC-Only
Users
(nⴝ36)
Nicotine‡ 10 ng/mL 1.1 0.0 0.0 2.8 2.8 0.0
Cotinine‡ 10 ng/mL 14.4 13.5 16.7 5.6 27.8 8.3
trans-3'-hydroxycotinine 0.03 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
Cotinine 0.03 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
Nicotine 10.5 ng/mL 11.0 2.7 13.9 5.6 30.6 2.8
Cotinine N-oxide 2 ng/mL 7.7 0.0 13.9 2.8 19.4 2.8
Nicotine 1'-oxide 2.5 ng/mL 8.8 0.0 13.9 2.8 25.0 2.8
Norcotinine 2.5 ng/mL 11.6 0.0 22.2 5.6 27.8 2.8
Nornicotine 1.1 ng/mL 17.7 5.4 30.6 11.1 33.3 8.3
Anabasine 0.5 ng/mL 29.3 10.8 36.1 13.9 55.6 30.6
Anatabine 0.4 ng/mL 29.3 5.4 27.8 11.1 61.1 41.7
N-acetyl-S-(2-carboxyethyl)-L-cysteine (CEMA) 8 ng/mL 2.8 0.0 2.8 0.0 5.6 5.6
N-acetyl-S-(3-hydroxypropyl)-L-cysteine (3HPMA) 13 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA) 2.2 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA) 9.4 ng/mL 30.9 16.2 25.0 19.4 41.7 52.8
N-acetyl-S-(2-cyanoethyl)-L-cysteine (CYMA) 0.5 ng/mL 2.2 0.0 0.0 0.0 2.8 8.3
trans,trans-muconic acid (MU) 20 ng/mL 6.6 2.7 2.8 2.8 5.6 19.4
N-acetyl-S-(phenyl)-L-cysteine (PMA) 0.6 ng/mL 56.9 37.8 94.4 30.6 86.1 36.1
N-acetyl-S-(3,4-dihydroxybutyl)-L-cysteine (DHBMA) 5 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
N-acetyl-S-(4-hydroxy-2-buten-1-yl)-L-cysteine (MHBMA3) 0.6 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
2-thioxothiazolidine-4-carboxylic acid (TTCA) 3.5 ng/mL 28.2 29.7 22.2 41.7 13.9 33.3
N-acetyl-S-(3-hydroxypropyl-1-methyl)-L-cysteine (HPMMA) 2 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
2-aminothiazoline-4-carboxylic acid (ATCA) 15 ng/mL 7.2 0.0 8.3 5.6 5.6 16.7
N-acetyl-S-(N-methylcarbamoyl)-L-cysteine (AMCC) 5.5 ng/mL 0.6 0.0 0.0 2.8 0.0 0.0
N-acetyl-S-(2-hydroxyethyl)-L-cysteine (HEMA) 0.6 ng/mL 48.6 32.4 41.7 27.8 61.1 80.6
N-acetyl-S-(2-hydroxypropyl)-L-cysteine (2HPMA) 1.3 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
Mandelic acid (MA) 12 ng/mL 1.1 0.0 0.0 0.0 2.8 2.8
N-acetyl-S-(1 and 2-phenyl-2-hydroxyethyl)-L-cysteine (PHEMA) 0.7 ng/mL 61.3 48.6 58.3 55.6 63.9 80.6
Phenylglyoxylic acid (PGA) 12 ng/mL 9.9 10.8 11.1 8.3 11.1 8.3
2-methylhippuric acid (2MHA) 5 ng/mL 0.0 0.0 0.0 0.0 0.0 0.0
3- + 4-methylhippuric acids (34MHA) 8 ng/mL 1.7 0.0 0.0 0.0 2.8 5.6
4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) 0.6 pg/mL 6.6 0.0 2.8 0.0 8.3 22.2
N'-nitrosoanabasine (NAB) 4.0 pg/mL 47.0 8.1 38.9 25.0 80.6 83.3
N'-nitrosoanatabine (NAT) 1.6 pg/mL 43.1 5.4 41.7 13.9 75.0 80.6
Cigarette = combustible cigarette; EC = e-cigarette; NRT = nicotine replacement therapy.
* Values are percentages.
† Urinary biomarkers unless otherwise indicated.
‡ Measured in saliva.
Annals of Internal Medicine www.annals.org
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