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. Author manuscript; available in PMC: 2026 Aug 19.
Published in final edited form as: Addict Behav. 2025 May 11;169:108381. doi: 10.1016/j.addbeh.2025.108381

Biomarkers of Secondhand Smoke and Vaping Exposure among U.S. Adolescents

Hongying Daisy Dai a,*, Amber K Brown Keebler b, Brian Young a,c
PMCID: PMC13485149  NIHMSID: NIHMS2202931  PMID: 40378612

Abstract

Background:

Despite reductions in smoking use among adults and adolescents, e-cigarette use has increased, raising a new public health concern.

Methods:

We analyzed Wave 4 (2016–2018) data from the Population Assessment of Tobacco and Health (PATH) Study to assess biomarkers of exposure to secondhand smoke and vaping aerosols among U.S. adolescents (age range 12–17). Participants with no current tobacco use in the past 30 days were divided into four mutually exclusive groups: no exposure, exposure to secondhand smoke (SHS) only, exposure to secondhand aerosol (SHA) only, and dual exposure to both (SHD).

Results:

Among 2,379 adolescents (mean[SD] of age=14.4[0.02]), 1.5% reported SHA, 18.3% reported SHS, and 2.8% reported SHD. Mean concentrations of cotinine were significantly higher among those exposed to SHA only (0.5 ng/mg creatinine, p=0.04), SHS (3.0,p<.0001), or SHD (2.5,p<.0001) than among those with no exposure (0.2). As compared to the no-exposure group, both SHS and SHD groups also had higher mean concentrations of carcinogen, NNAL (4.1 and 2.8 pg/mg creatinine, respectively, vs. 0.9, p<.0001) and exposure to SHS had a higher level of CYMA (1.8 vs. 1.1 ng/mg creatinine, p<.0001). In comparison with the SHA group, the SHS and SHD groups had 6.8 and 3.6 times higher levels of cotinine and 4.6 and 2.2 times higher levels of NNAL, respectively; the SHS group also had higher levels of AAMA and CYMA.

Conclusions:

Secondhand vaping aerosol poses a lower exposure risk to youth non-tobacco users than combustible cigarette smoke. The distinct exposure patterns emphasize the importance of implementing tobacco-free policies to reduce youth exposure to environments where combustible tobacco or e-cigarette use occurs.

Introduction

Although the overall prevalence of cigarette smoking has declined in the last few decades, e-cigarette use is gaining popularity among U.S. adults and youth (Cornelius et al., 2023; Dai & Leventhal, 2019; Gentzke et al., 2022). In 2021, an estimated 11.5% of U.S. adults reported currently smoking cigarettes and 4.5% reported current use of e-cigarettes. The prevalence of current (past 30-day) e-cigarette use among teens increased from 11.7% in 2017 to 20.2% in 2019 before starting to decline (Gentzke et al., 2019; Wang et al., 2018). In 2023, an estimated 7.7% of U.S. youth reported current e-cigarette use, including 10.0% of U.S. high school students (around 1.56 million) and 4.5% of middle school students (around 550,000) (Birdsey et al., 2023), coupled with evidence pointing to nicotine dependence among adolescent e-cigarette users, with the median frequency of vaping increasing from 3–5 days per month during 2014–2018, to 6–9 days per month during 2019–2020, and 10–19 days per month in 2021 (Glantz, Jeffers, & Winickoff, 2022). The growing popularity of e-cigarettes among both adults and youth raises public health concerns about adolescent exposure to secondhand vaping aerosols.

There could be different profiles of toxic exposure between secondhand exposure to cigarette smoking versus vaping aerosol. Secondhand smoke exposure occurs when bystanders inhale the toxic chemicals released into the air by the combustion of tobacco in cigarettes, which could reach a temperature exceeding 1,000°C. This smoke contains thousands of chemicals, many of which are harmful and carcinogenic (Soleimani, Dobaradaran, De-la-Torre, Schmidt, & Saeedi, 2022). E-cigarettes are battery-powered devices that release aerosol via a heating element, providing a smoking-like sensation without burning tobacco. Secondhand exposure to e-cigarettes can include aerosol from e-liquids with varying ingredients and particles emitted from the heating device, introducing unique concerns absent in traditional cigarette smoke. The heating coil, typically made of nickel, chromium, and other alloys, can degrade during use, releasing small metals and other byproducts into the aerosol (Eshraghian & Al-Delaimy, 2021).

Exposure to secondhand tobacco occurs in many settings for adolescents, including at home, in vehicles, in the school setting, and in other public places. A prior study using the National Youth Tobacco Survey (NYTS) data found that the prevalence of exposure to secondhand aerosol (SHA) among U.S. middle and high school students increased from 25.2% in 2015 to 33.2% in 2018 while the exposure to secondhand smoke (SHS) was relatively stable during this period (Dai, 2020). Exposure to secondhand tobacco is particularly higher among racial minorities, those with low socioeconomic status, those living in rural areas, and states with weak smoke/vaping-free laws (U.S. Department of Health and Human Services, 2006; US Department of Health and Human Services, 2024).

The harmful effects of exposure to secondhand smoke are well documented and the 2006 U.S. Surgeon General’s report concluded that no amount of exposure to secondhand smoke from combustible cigarettes is safe (U.S. Department of Health and Human Services, 2006). Given that e-cigarettes are relatively new to the market, the long-term health effects of e-cigarette use are still under investigation (U.S. Department of Health and Human Services, 2016). Currently, there is a dearth of literature to describe the differential effects of secondhand smoke and aerosol exposure from e-cigarettes among U.S. adolescents at the population level. Biomarkers serve as valuable tools for detecting both secondhand smoke and secondhand vaping aerosol exposure in adolescents. Specifically, the metabolites of NNAL (a tobacco-specific nitrosamine) and cotinine (a nicotine metabolite) can be used to assess exposure to tobacco and nicotine, respectively (US Food and Drug Administration, 2012). In addition to biomarkers used to measure exposure to nicotine and tobacco metabolites, other harmful compounds resulting from e-cigarette aerosols can be measured. Of particular concern are carcinogenic volatile organic compounds (VOCs) such as acrylonitrile, acrolein, and crotonaldehyde, which have been detected in the excretions of adolescents who use e-cigarettes (Rubinstein, Delucchi, Benowitz, & Ramo, 2018).

This study utilizes data from Wave 4 of the Population Health Assessment of Tobacco and Health (PATH) Study to compare urinary biomarker levels across various secondhand tobacco exposure groups, including adolescents exposed exclusively to secondhand aerosol (SHA), exclusively to secondhand smoke (SHS), dual exposure to both (SHD), and those with no exposure. By analyzing these distinct groups of participants who are not current users of any tobacco products, the study aims to provide evidence on the differential biomarker profiles associated with each type of secondhand exposure and the potential health implications for U.S. adolescents.

Methods

Data

Data were obtained from Wave 4 of the PATH Study, a longitudinal cohort study among a nationally representative sample of U.S. civilian, non-institutionalized individuals (United States Department of Health and Human Services, 2017). Wave 4, collected between December 2016 and January 2018, is the first wave in which youth were asked to provide urine specimens. Of the 14,798 respondents who completed the youth interview at Wave 4, 13,097 (88.5 percent) provided a urine specimen. A stratified probability sample of 3,508 Wave 4 Cohort youth ages 12 to 17 who completed the Wave 4 youth interview and provided a sufficient amount of urine for the planned laboratory analyses were selected from a diverse mix of five tobacco product use groups representing never, current, and recent former users of tobacco products. Details of biospecimen collection and laboratory procedures were provided elsewhere (United States Department of Health and Human Services, 2022). This study linked biomarker data from the Restricted Use Files (RUFs) with PATH Youth Survey data through the unique ID.

Measures

Biomarkers of exposure to toxicants (outcomes).

We selected a panel of biomarkers (n=12) that are most relevant to the health effects of tobacco exposure (Chang et al., 2017; Dai & Khan, 2020; Goniewicz et al., 2018; International Agency for Research on Cancer, 2004; US Food and Drug Administration, 2012) from five groups of harmful and potentially harmful constituent classes: 1) nicotine metabolites (Cotinine [COTT], trans-3′-hydroxycotinine [3-HC]), 2) Tobacco Specific Nitrosamine (TSNA, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol [NNAL]), 3) metals (cadmium [UCD], and lead [UPB]), 4) Polycyclic Aromatic Hydrocarbons (PAHs, 2-Naphthol or 2-Hydroxynaphthalene [2-NAP], 2-Hydroxyfluorene (2-FLU), 1-Hydroxyphenanthrene [1-PHE], 1-Hydroxypyrene [1-PYR]), and 5) Volatile Organic Compounds (VOCs, N-Acetyl-S-(2-carbamoylethyl)-L-cysteine [AAMA]), N-Acetyl-S-(2-carboxyethyl)-L-cysteine [CEMA], N-Acetyl-S-(2-cyanoethyl)-L-cysteine [CYMA]). These select BOEs are clinically relevant to addiction (e.g., COTT, 3-HC), cancer (e.g., NNAL, cadmium, lead, 2-NAP, CYMA), developmental health (e.g., COTT, cadmium, lead), cardiovascular diseases (e.g., lead, AAMA), and respiratory diseases (e.g., cadmium, 2-NAP, CEMA, CYMA) (Goniewicz et al., 2018; US Food and Drug Administration, 2012). Biomarker concentrations below the limit of detection (LOD) were imputed using a standard substitution formula (the LOD divided by the square root of 2) (Hornung & Reed, 1990).

Tobacco use status:

Those who reported using tobacco products (i.e. cigarettes, e-cigarettes, cigars, pipes, hookah, smokeless tobacco, dissolvable tobacco, bidi, kretek) ≥1 day in the past 30 days were classified as current tobacco users, who were excluded from the analytical sample.

Exposure to secondhand tobacco use (exposure).

Participants were asked “Not including yourself, does anyone who lives with you now do any of the following? Choose all that apply.” with response options of “Smoke cigarettes,” “Use e-cigarettes or other electronic nicotine products,” “Use snus,” “Use other types of smokeless tobacco such as dip, spit, or chew,” “Smoke traditional cigars, cigarillos, or filtered cigars,” “Smoke hookah,” and “Use any other form of tobacco.” Those who only marked “Smoke cigarettes” were classified as exposed to secondhand smoke only (SHS) and those who only marked “Use e-cigarettes or other electronic nicotine products” were classified as exposed to secondhand vaping aerosol only (SHA). Those who endorsed both cigarettes and e-cigarettes were categorized as exposed to secondhand dual use (SHD), and those who did not endorse any options were categorized as having no exposure to tobacco use. To avoid any confounding effects, we removed those who reported exposure to tobacco use other than cigarettes and e-cigarettes (e.g., cigar, hookah, smokeless, and snus).

Demographic covariates included age (continuous, ranging from 13–17 years old), sex (male and female), race, and ethnicity (non-Hispanic [NH] White, NH Black, Hispanic, and NH-Other) as social constructs rather than as generic or biological categories, parental education (less than high school, high school graduates, some college or college graduates), annual household income (<$50,000 and ≥$50,000).

Statistical Analysis

Weighted sociodemographic characteristics were reported, overall, and by exposure to tobacco use status (i.e., no exposure, exposure to SHA only, exposure to SHS only, and exposure to both). Group differences were assessed using the Rao-Scott Chi-square test for categorical variables and linear regression for continuous variables.

Urinary biomarkers were calculated as a normalized ratio to urinary creatinine concentration to correct for the hydration of participants. Due to the skewness in the distribution, BOE data were transformed using a natural log. Analyses applied urinary sample weight, 100 replicated weights, and the balanced repeated replication method with Fay’s adjustment = 0.3 to account for the PATH Study’s complex design.

Multivariable regressions were conducted to assess pairwise group effects, using no exposure and exposure to SHA only as the respective reference groups for comparison. Covariates included age, sex, and race/ethnicity. The geometric mean and 95% confidence interval (CIs) of creatinine-corrected biomarkers were reported were reported. The adjusted geometric mean ratio (GMR) between groups was calculated by exponentiating the beta coefficient from a model based on log-transformed BOE levels. To further assess whether BOEs differed by age group, we further examined the differences in cotinine levels by age group (12–15 vs. 16–17 years) and exposure to secondhand tobacco (no vs. yes) in the exploratory analysis. Analysis was conducted in SAS 9.4 with p<0.05 (2-tailed) for statistical significance.

Results

Figure 1 illustrates the selection process for participants in the final analytical sample. The original PATH Study Wave 4 Youth survey included 14,798 participants, of whom 3,508 provided urine samples for biomarker analysis. After excluding individuals with creatinine levels outside acceptable limits (≤10 mg/dL or >370 mg/dL, n=86), current tobacco users (n=730), and those exposed to other forms of tobacco (n=313), the final sample comprised 2,379 adolescents divided into four mutually exclusive exposure groups: no exposure (n=1,635), SHA only (n=52), SHS only (n=594), and dual exposure (n=98).

Figure 1.

Figure 1.

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Flow Chart for Participants Included in the Analytical Sample

Demographic characteristics of the 2,379 participants are summarized in Table 1 with a mean age of 14.4 years. Among them, 49.6% were female, 51.0% were non-Hispanic White, 77.4% reported no exposure, 1.5% reported exclusive SHA exposure, 18.3% reported exclusive SHS exposure, and 2.8% reported dual exposure (SHD). Adolescents from lower-income households (<$50,000 vs. ≥$50,000) were more likely to report SHS, SHA, and SHD exposure (p<0.001). Differences in parental education were also observed, with adolescents reporting SHS exposure less likely to come from households where parents had some college or a college degree compared to those whose parents had high school or less than a high school education (p<0.001).

Table 1.

Sample Characteristics by Secondhand Vaping and Smoke Exposure, 2016–2018 PATHa

Overall (n=2379) No exposure (n=1635) Exposure to SHA Only (n=52) Exposure to SHS Only (n=594) Exposure to Both (n=98) p-valuec
Weighted % 100% 77.4% 1.5% 18.3% 2.8%
Age, Mean (SE) in years 14.4 (0.02) 14.4 (0.03) 14.3 (0.3) 14.5 (0.1) 14.6 (0.22) 0.26
Sexb 0.17
Male 1268 (50.4) 890 (51.2) 30 (67.7) 299 (47.9) 49 (36.0)
Female 1104 (49.6) 739 (48.8) 22 (32.3) 294 (52.1) 49 (64.0)
Race/ethnicityb 0.17
Non-Hispanic White 972 (51.0) 632 (50.1) 26 (70.7) 254 (50.8) 60 (67.8)
Non-White 1113 (49.0) 811 (49.9) 18 (29.3) 260 (49.2) 24 (32.2)
Parental Educationb <.0001
Less than high school 387 (13.3) 236 (12.6) 3 (5.6) 141 (17.9) 7 (4.8)
High School 614 (23.8) 383 (20.6) 17 (33.2) 191 (35.9) 23 (27.6)
Some College or College graduate 1360 (62.9) 1004 (66.8) 32 (61.1) 257 (46.2) 67 (67.6)
Annual Household Incomeb <.0001
<$50,000 1252 (47.4) 770 (41.9) 23 (52.7) 402 (68.6) 57 (53.1)
>=$50,000 1027 (52.6) 791 (58.1) 27 (47.3) 170 (31.4) 39 (46.9)
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a:

All analyses applied urinary sample weight, 100 replicated weights, and the balanced repeated replication method with Fay’s adjustment = 0.3 to account for the PATH Study’s complex design.

b

n(weighted column %)

c

P-values were from Rao-Scott χ2 test for categorical variables and linear regression for continuous variables to compare differences among all groups.

Table 2 compares biomarker differences in the exposure groups (SHS, SHA, SHD) to the non-exposure group. Mean concentration levels of cotinine (ng/mg creatinine) were significantly elevated for the SHA group (mean [95%CI]=0.5[0.3–1.1], GMR[95%CI]=2.2[1.1–4.4], p =0.04), SHS group (mean[95%CI]=3.0[2.2–4.0], GMR[95%CI]=12.1[8.6–17.1], p<0.0001), and SHD group (mean[95%CI]=2.5[1.6–4.0], GMR[95%CI]=8.6[5.0–14.8], p<0.0001), when compared to the non-exposure group (mean[95%CI]=0.2[0.2–0.3]). Mean concentration levels of 3-HC (ng/mg creatinine) were significantly higher in the SHS (mean[95%CI]=4.9[3.6–6.6], GMR[95%CI]=10.3[7.3–14.6], p<0.0001), and SHD (mean[95%CI]=4.8[3.2–7.2], GMR[95%CI]=9.3[5.7–15.3], p<0.0001) groups compared to the non-exposure group (mean [95% CI]=0.4[0.4–0.5]). NNAL levels (pg/mg creatinine) were significantly elevated for both the SHS (mean[95%CI]=4.1[3.4–4.9], GMR[95%CI]=4.5[3.6–5.6], p<0.0001) and SHD group (mean[95%CI]=2.8[1.9–4.1], GMR[95%CI]=2.8[1.8–4.3], p<0.0001) compared to the non-exposure group (mean[95%CI]=0.9[0.8–0.9]). Additionally, the mean concentration level of CYMA (Acrylonitrile, ng/mg creatinine) was higher in the SHS group compared to the non-exposure group (mean[95%CI]=1.8[1.6–2.2] vs 1.1[1.1–1.2], GMR[95%CI]=1.6[1.3–1.9], p<0.0001).

Table 2.

Differences in Biomarkers of Secondhand Vaping and Smoke among U.S. Adolescents, 2016–2018 PATH

No Exposure (n=1635) Exposure to SHA Only (n=52) Exposure to SHS Only (n=594) Exposure to Both (n=98)
Geometric Mean and 95% CI Geometric Mean and 95% CI GMR with no usea adj p-valueb Geometric Mean and 95% CI GMR with no usea adj p-valueb Geometric Mean and 95% CI GMR with no usea adj p-valueb
Urinary Nicotine Metabolites (ng/mg creatinine)
Cotinine (COTT) 0.2 (0.2–0.3) 0.5 (0.3–1.1) 2.2 (1.1–4.4) 0.04 3.0 (2.2–4.0) 12.1 (8.6–17.1) <.0001 2.5 (1.6–4.0) 8.6 (5.0–14.8) <.0001
3-HC 0.4 (0.4–0.5) 0.8 (0.4–1.8) 1.8 (0.8–4.1) 0.17 4.9 (3.6–6.6) 10.3 (7.3–14.6) <.0001 4.8 (3.2–7.2) 9.3 (5.7–15.3) <.0001
Tobacco Specific Nitrosamines (TSNAs) (pg/mg creatinine)
NNAL 0.9 (0.8–0.9) 0.9 (0.5–1.6) 1.1 (0.6–2.0) 0.77 4.1 (3.4–4.9) 4.5 (3.6–5.6) <.0001 2.8 (1.9–4.1) 2.8 (1.8–4.3) <.0001
Heavy Metals (ng/mg creatinine)
Cadmium (UCD) 0.1 (0.1–0.1) 0.1 (0.0–0.1) 1.0 (0.7–1.3) 0.82 0.1 (0.1–0.1) 0.9 (0.8–1.0) 0.12 0.1 (0.1–0.1) 1.0 (0.8–1.3) 0.95
Lead (UPB) 0.2 (0.2–0.2) 0.2 (0.2–0.3) 1.0 (0.7–1.4) 0.85 0.2 (0.2–0.2) 1.0 (0.9–1.1) 0.81 0.2 (0.2–0.2) 0.9 (0.7–1.2) 0.49
Polycyclic Aromatic Hydrocarbons (ng/mg creatinine) - - -
2-NAP 0.01 (0.01–0.01) 0.01 (0.00–0.01) 1.1 (0.7–1.7) 0.80 0.01 (0.01–0.01) 1.0 (0.9–1.2) 0.97 0.01 (0.01–0.01) 1.1 (0.8–1.4) 0.58
2-FLU 0.2 (0.2–0.2) 0.2 (0.1–0.3) 1.1 (0.8–1.6) 0.53 0.2 (0.2–0.2) 1.1 (0.9–1.2) 0.31 0.2 (0.1–0.2) 1.0 (0.8–1.3) 0.91
1-PHE 0.1 (0.1–0.1) 0.1 (0.1–0.1) 0.9 (0.6–1.3) 0.51 0.1 (0.1–0.1) 0.9 (0.8–1.1) 0.35 0.1 (0.1–0.1) 0.9 (0.6–1.1) 0.25
1-PYR 0.1 (0.1–0.1) 0.1 (0.1–0.1) 0.9 (0.7–1.2) 0.37 0.12 (0.1–0.13) 1.1 (0.9–1.2) 0.41 0.1 (0.1–0.1) 0.9 (0.7–1.1) 0.22
Volatile Organic Compounds (VOC) (ng/mg creatinine)
AAMA (Acrylamide) 54.8 (52.1–57.8) 45.7 (37.1–56.2) 0.8 (0.6–1.0) 0.08 58.8 (54.6–63.3) 1.1 (1.0–1.2) 0.08 50.6 (42.9–59.7) 1.0 (0.9–1.2) 0.88
CEMA (Acrolein) 80.5 (77.4–83.7) 78.3 (65–94.4) 1.0 (0.8–1.2) 0.84 83.1 (76.9–89.9) 1.0 (0.9–1.1) 0.55 76.7 (64.7–90.9) 1.0 (0.8–1.2) 0.96
CYMA (Acrylonitrile) 1.1 (1.1–1.2) 1.1 (0.8–1.4) 1.0 (0.7–1.3) 0.91 1.8 (1.6–2.2) 1.6 (1.3–1.9) <.0001 1.5 (1.2–1.9) 1.3 (1.0–1.7) 0.07
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Abbreviation, GMR, geometric mean ratio. trans-3’-Hydroxycotinine (3-HC), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), 2-Naphthol or 2-Hydroxynaphthalene (2-NAP), 2-Hydroxyfluorene (2-FLU), 1-Hydroxyphenanthrene (1-PHE), 1-Hydroxypyrene (1-PYR), N-Acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA), N-Acetyl-S-(2-carboxyethyl)-L-cysteine (CEMA), N-Acetyl-S-(2-cyanoethyl)-L-cysteine (CYMA).

a

Unadjusted ratio and 95% CI for geometric means of pairwise comparisons between groups were reported.

b

P-values were from multivariable regressions adjusted by age, sex, and race/ethnicity. Bold font denotes p-values less than 0.05.

Table 3 presents differences in the exposure groups with the SHA being the reference group. Both SHS (GMR[95%CI]=6.8[3.2–14.1], p<0.0001) and SHD (GMR[95%CI]=3.6[1.4–9.0], p=0.007) groups had higher mean concentrations of cotinine levels than the SHA groups. For 3-HC, SHS (GMR[95%CI]=7.1[3.3–15.2], p<0.0001) and SHD (GMR[95%CI]=5.5[2.2–14.0], p=0.0001) groups exhibited higher mean concentration levels than the SHA groups. NNAL levels were significantly higher among the SHS (GMR[95%CI]=4.6[2.4–8.9], p<0.0001) and SHD (GMR[95%CI]=2.2[1.0–4.6, p=0.045) groups as compared to the SHA group. The SHS groups also had significantly higher mean concentration levels of AAMA (Acrylamide, GMR[95%CI]=1.4[1.1–1.7], p=0.007) and CYMA (Acrylonitrile, GMR[95%CI]=1.7[1.2–2.3, p=0.001) than the SHA group.

Table 3.

Differences in Biomarkers of Secondhand Vaping versus Secondhand Smoke among U.S. Adolescents

Exposure to SHA only (n=52) Exposure to SHS Only (n=594) Exposure to Both (n=98)
Geometric Mean and 95% CI Geometric Mean and 95% CI GMR with SHA Onlya adj p-valuea Geometric Mean and 95% CI GMR with SHA Onlya adj p-valueb
Urinary Nicotine Metabolites (ng/mg creatinine)
Cotinine (COTT) 0.5 (0.3–1.1) 3.0 (2.2–4.0) 6.8 (3.2–14.1) <.0001 2.5 (1.6–4.0) 3.6 (1.4–9.0) 0.007
3-HC 0.8 (0.4–1.8) 4.9 (3.6–6.6) 7.1 (3.3–15.2) <.0001 4.8 (3.2–7.2) 5.5 (2.2–14.0) .0001
Tobacco Specific Nitrosamines (TSNAs) (pg/mg creatinine)
NNAL 0.9 (0.5–1.6) 4.1 (3.4–4.9) 4.6 (2.4–8.9) <.0001 2.8 (1.9–4.1) 2.2 (1.0–4.6) .045
Heavy Metals (ng/mg creatinine)
Cadmium (UCD) 0.1 (0.0–0.1) 0.1 (0.1–0.1) 1.0 (0.7–1.3) 0.93 0.1 (0.1–0.1) 1.0 (0.7–1.5) 0.90
Lead (UPB) 0.2 (0.2–0.3) 0.2 (0.2–0.2) 1.1 (0.8–1.6) 0.58 0.2 (0.2–0.2) 1.0 (0.7–1.3) 0.92
Polycyclic Aromatic Hydrocarbons (ng/mg creatinine)
2-NAP 0.01 (0–0.01) 0.01 (0.01–0.01) 1.0 (0.6–1.7) 1.00 0.01 (0.01–0.01) 1.0 (0.6–1.7) 0.91
2-FLU 0.2 (0.1–0.3) 0.2 (0.2–0.2) 1.0 (0.7–1.4) 0.88 0.2 (0.1–0.2) 0.9 (0.6–1.3) 0.62
1-PHE 0.1 (0.1–0.1) 0.1 (0.1–0.1) 1.2 (0.8–1.7) 0.48 0.1 (0.1–0.1) 1.0 (0.6–1.6) 1.00
1-PYR 0.1 (0.1–0.1) 0.12 (0.1–0.13) 1.2 (0.9–1.6) 0.15 0.1 (0.1–0.1) 1.0 (0.7–1.4) 0.94
Volatile Organic Compounds (VOC) (ng/mg creatinine)
AAMA (Acrylamide) 45.7 (37.1–56.2) 58.8 (54.6–63.3) 1.4 (1.1–1.7) 0.01 50.6 (42.9–59.7) 1.3 (1.0–1.6) 0.11
CEMA (Acrolein) 78.3 (65.0–94.4) 83.1 (76.9–89.9) 1.0 (0.8–1.3) 0.68 76.7 (64.7–90.9) 1.0 (0.8–1.3) 0.82
CYMA (Acrylonitrile) 1.1 (0.8–1.4) 1.8 (1.6–2.2) 1.7 (1.2–2.3) 0.001 1.5 (1.2–1.9) 1.2 (0.8–1.8) 0.42
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Abbreviation, GMR, geometric mean ratio. trans-3’-Hydroxycotinine (3-HC), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), 2-Naphthol or 2-Hydroxynaphthalene (2-NAP), 2-Hydroxyfluorene (2-FLU), 1-Hydroxyphenanthrene (1-PHE), 1-Hydroxypyrene (1-PYR), N-Acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA), N-Acetyl-S-(2-carboxyethyl)-L-cysteine (CEMA), N-Acetyl-S-(2-cyanoethyl)-L-cysteine (CYMA).

a

Unadjusted ratio and 95% CI for geometric means of pairwise comparisons between groups were reported.

b

P-values were from multivariable regressions adjusted by age, sex, and race/ethnicity. Bold font denotes p-values less than 0.05.

Appendix Figure 1 shows the differences in the geometric mean concentration of cotinine levels by age group and exposure to secondhand tobacco. Among those not exposed to secondhand tobacco, older adolescents (16–17 years vs. younger adolescents, 12–15 years) had higher concentrations of cotinine (0.3 vs. 0.2 ng/mg creatinine, p=0.04). Similarly, among those exposed to secondhand tobacco, older adolescents exhibited higher cotinine levels than their younger peers (3.6 vs. 0.2 ng/mg creatinine, p=0.02).

Discussion

The detrimental health effects of exposure to secondhand smoke are well-established and it is estimated that more than 19,000 deaths are attributable to exposure to secondhand tobacco smoke (U.S. Department of Health and Human Services, 2006). The tobacco use landscape has changed in recent years with more adults and adolescents reporting the use of e-cigarette products. Unlike combustible cigarette smoking, e-cigarettes do not generate sidestream aerosol between puffs and e-cigarette users might retain the nicotine produced during vaping (St Helen, Havel, Dempsey, Jacob, & Benowitz, 2016). Evidence shows that e-cigarette aerosol is generally less toxic than combustible cigarette smoking (Balfour et al., 2021; Goniewicz et al., 2018; National Academies of Sciences Engineering and Medicine, 2018). Prior adult studies (Goniewicz et al., 2018; National Academies of Sciences Engineering and Medicine, 2018) reported that exclusive e-cigarette users had lower levels of biomarkers of toxicant exposure (including TSNAs), PAHs, and most VOCs, compared with exclusive cigarette smokers. However, the knowledge about the harmful effects of exposure to secondhand vapor is relatively limited. A recent study examining the 2017–2020 National Health and Nutrition Examination Survey (NHANES)(Tattan-Birch, Brown, Jackson, Jarvis, & Shahab, 2024) assessed nicotine absorption and found that it was significantly lower in children exposed to secondhand vapor compared to secondhand smoke, yet higher than in children with no exposure to either. However, this study is limited to children aged 3 to 11 years, and the biomarker outcome only included serum cotinine concentration without examining other tobacco-related toxicants.

As one of the first studies that analyzed a nationally representative adolescent sample to report biomarker outcomes associated with exposure to SHA only, SHS only, and SHD, our study highlights significantly higher exposure to some tobacco-related toxicants in adolescents exposed to SHS compared to those only exposed to SHA. Notably, the urinary nicotine metabolite levels, as measured by cotinine and 3-HC, were nearly 6 times higher among the SHS groups as compared to the SHA group. In other words, exposure to SHA poses approximately 83% lower nicotine absorption than those exposed to SHS. This finding is aligned with previous studies that reported about 84% lower nicotine exposure in the 2017–2020 NHANES sample (Tattan-Birch et al., 2024) and 88% lower using silicone wristbands(Quintana et al., 2021) when comparing children exposed to SHA only with those exposed to SHS only. In addition to nicotine absorption, our study found significantly higher levels of carcinogen (NNAL), acrylamide (AAMA), and acrylonitrile (CYMA) among adolescents exposed to SHS than those exposed to SHA. For instance, acrylonitrile is a byproduct of combustion and has been associated with serious respiratory issues, particularly in young populations (US Food and Drug Administration, 2012). NNAL, a tobacco-specific nitrosamine linked to carcinogenic risk, further reinforces the dangers of SHS exposure. Therefore, completely switching from combustible cigarette smoking to e-cigarette use may not only serve as a harm-reduction alternative (National Academies of Sciences Engineering and Medicine, 2018) but also substantially reduce children’s exposure to secondhand exposure to nicotine and other tobacco-related toxicants.

Dual use of electronic cigarettes and combustible cigarettes is prevalent among U.S. adults and youth (Kasza et al., 2017). Approximately 40.8% of adult e-cigarette users in the United States also smoke cigarettes (Owusu et al., 2019). Previous studies reported comparable levels of exposure to multiple tobacco-related toxicants between dual users and exclusive cigarette smokers (Dai et al., 2022; Goniewicz et al., 2018). To the best of our knowledge, this is the first study to report the biomarker outcomes among children exposed to both secondhand smoke and secondhand aerosol. Our findings suggest similar nicotine exposure between SHS and SHD groups and significantly higher levels of carcinogens among those exposed to SHD than those with no exposure. While the levels of exposure are likely influenced by the frequency of indoor use of e-cigarettes and combustible cigarettes, our study findings suggest that dual users might pose similar levels of harmful toxicants to children living with them. Therefore, it is important for dual users to quit smoking completely and, ultimately, quit vaping completely.(Piper, Stein, & Lasser, 2024) Some adults may believe that they are mitigating exposure risks by using cigarettes at specific times and e-cigarettes at others, such as when children are around. However, our data indicate that adolescents in dual-exposure households still experience significant levels of nicotine and NNAL.

Our study found similar toxicant exposure levels between adolescents exposed solely to SHA and those with no exposure, except for a 2.3-fold higher mean cotinine concentration in the SHA-exposed group compared to those unexposed. Nicotine in tobacco is highly addictive. Acute nicotine increases brain reward function through its effects on dopamine release,(Benowitz, 1996, 2009), and chronic nicotine exposure can induce increased numbers of central nerve system nicotine acetylcholine receptors (nAChRs) in animals and human smokers in vivo (Sabbagh, Lukas, Sparks, & Reid, 2002; Swan & Lessov-Schlaggar, 2007). Therefore, adults should avoid vaping indoors when children are present to minimize the potential harm to youth since no amount of exposure to secondhand tobacco is safe. Our exploratory analysis revealed that older adolescents exhibited higher cotinine levels compared to younger adolescents, particularly among those exposed to secondhand tobacco. This difference is likely attributable to older adolescents being more frequently exposed to secondhand tobacco outside the home (e.g., at school) compared to their younger peers (Dai, 2021). Additionally, older adolescents may experience prolonged exposure to secondhand tobacco, leading to increased nicotine levels.

This study has limitations. First, exposure to secondhand tobacco and current tobacco use status are self-reported and they are subject to social desirability and recall bias. Second, most biomarkers analyzed in the study have a short half-life (e.g., nicotine metabolites) and might not be able to capture nicotine exposure from intermittent use. Additionally, some biomarker measures (e.g., metals) have a long half-life and they may come from other sources (Chang et al., 2017). Thirdly, it is worth noting that Wave 4 of the PATH Study was collected between October 2016 and January 2018, before the uptick in disposable e-cigarette devices with high nicotine concentrations.(Diaz, Silver, Bertrand, & Schillo, 2023) For instance, the percentage of e-cigarette sales with products containing ≥5% nicotine strength increased from 5.1% in January 2017 to 80.9% in March 2022.(Ali, Seaman, Crane, Schillo, & King, 2022) Nicotine exposure from secondhand aerosol might be elevated with these new generations of vaping products and future studies should monitor the changes with more recent data. Finally, exposure to secondhand tobacco was based on cohabitation with specific tobacco users, without data on whether these products were actually used indoors. Moreover, the study lacked measures about secondhand tobacco exposure in other settings (e.g., schools or public places), potentially leading to an underestimation of overall exposure.

Despite these limitations, this national study found elevated exposure to tobacco-related toxicants (e.g., nicotine metabolites, carcinogens) among adolescents exposed to SHS and SHD compared to those exposed to SHA. Exposure to secondhand aerosol might pose reduced harm than exposure to secondhand smoke but is not harmless with higher nicotine exposure than no exposure. Continuous monitoring of toxicant exposure among e-cigarette users is warranted and a comprehensive tobacco-free home is needed to protect adolescents from adverse health outcomes.

Highlights.

  • Secondhand exposure to combustible smoke poses harm to youth.

  • Exposure to secondhand vaping aerosol might pose reduced harm than exposure to secondhand smoke but is not harmless.

  • It is important to implement tobacco-free policies to reduce youth exposure in environments.

Acknowledgments

Funding:

Research reported in this publication was supported by the National Institute on Drug Abuse under Award Number R01DA060466 (PI: Dai). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Role of Funder:

The funding agency had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Abbreviations:

OR

odds ratio

CI

confidence interval

BOE

biomarker of exposure

PATH

Population Assessment of Tobacco and Health study

NH

Non-Hispanic

Appendix Figure 1. Differences in Geometric Mean Concentration Levels of Cotinine by Secondhand Tobacco Exposure and Age Groups

graphic file with name nihms-2202931-f0002.jpg

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Footnotes

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

Conflicts of Interest:

The authors have no conflicts of interest to disclose.

Data Availability:

The PATH Study data are available at https://www.icpsr.umich.edu/web/NAHDAP/studies/36231

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Associated Data

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

Data Availability Statement

The PATH Study data are available at https://www.icpsr.umich.edu/web/NAHDAP/studies/36231

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