Perception of harm is strongly associated with complete ban on in-home cannabis smoking: a cross-sectional study.

BACKGROUND: Perception of health risk can influence household rules, but little is known about how the perception of harm from cannabis secondhand smoke (cSHS) is related to having a complete ban on in-home cannabis smoking. We examined this association among a nationally representative sample of United States adults. METHODS: Respondents were 21,381 adults from the cross-sectional Marijuana Use and Environmental Survey recruited from December 2019-February 2020. Perceived harm of cSHS exposure (extremely harmful, somewhat harmful, mostly safe, or totally safe) and complete ban of cannabis smoking anywhere in the home (yes or no) were self-reported. Logistic regression for survey-weighted data estimated covariate-adjusted odds ratios (OR) and 95% confidence intervals (CI) for the association between perceived harm of cSHS and complete ban on in-home cannabis smoking. Stratified subgroup analyses (by cannabis smoking status, cannabis use legalization in state of residence, and children under age 6 living in the home) were conducted to quantify effect measure modification of the association between perception of harm and complete ban. RESULTS: A complete ban on in-home cannabis smoking was reported by 71.8% of respondents. Eight percent reported cSHS as "totally safe"; 20.5% "mostly safe"; 38.3% "somewhat harmful"; and 33.0% "extremely harmful". Those who reported cSHS as "extremely harmful" had 6 times the odds of a complete ban on in-home cannabis smoking (OR = 6.0, 95%CI = 4.9-7.2) as those reporting smoking as "totally safe". The odds of a complete ban were higher among those reporting cSHS as "somewhat harmful" (OR = 2.6, 95%CI = 2.2-3.1) or "mostly safe" (OR = 1.4, 95%CI = 1.2-1.7) vs those reporting cSHS as "totally safe". In each subgroup of cannabis smoking status, state cannabis use legalization, and children under the age of 6 living in the home, perceived harm was associated with a complete ban on in-home cannabis smoking. CONCLUSIONS: Our study demonstrates perceiving cSHS as harmful is strongly associated with having a complete in-home cannabis smoking ban. With almost a third of US adults perceiving cSHS as at least "mostly safe", there is strong need to educate the general population about potential risks associated with cSHS exposure to raise awareness and encourage adoption of household rules prohibiting indoor cannabis smoking.

Novel chemical contaminants associated with thirdhand smoke in settled house dust.

Thirdhand smoke (THS) is the persistent and toxic residue from tobacco smoke in indoor environments. A comprehensive understanding of the chemical constituents of THS is necessary to assess the risks of long-term exposure and to establish reliable THS tracers. The objective of this study was to investigate compounds associated with THS through nontargeted analysis (NTA) of settled house dust samples from smokers' and non-smokers' homes, using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOF-MS). Compounds that were either only present in dust from smokers' homes or that had significantly larger abundance than in non-smokers' homes were termed qualified compounds. We identified 140 qualified compounds, and of these, 42 compounds were tentatively identified by searching matching mass spectra in NIST electron impact (EI) mass spectral library including 20 compounds confirmed with their authentic standards. Among the 42 compounds, 26 compounds were statistically more abundant (p < 0.10) in dust from homes of smokers; seven were tobacco-specific compounds, two of which (nornicotyrine, 3-ethenylpyridine) have not been reported before in house dust. Two compounds, tris (2-chloroethyl) phosphate (a toxic compound used as a flame retardant and reported in tobacco) and propanoic acid, 2-methyl-, 1-(1,1-dimethylethyl)-2-methyl-1,3-propanediyl ester (highly abundant and reported in exhaled air of smokers), were found in dust from all smokers' homes and in zero non-smokers' homes, making these potential THS tracers, possibly associated with recent smoking. Benzyl methyl ketone was significantly higher in dust in smokers' homes, and was previously reported not as a product of tobacco but rather as a form of methamphetamine. This compound was recently reported in mainstream tobacco smoke condensate through NTA as well. These identified potential tracers and chemical components of THS in this study can be further investigated for use in developing THS contamination and exposure assessments.

Inflammatory marker levels in children with tobacco smoke exposure.

BACKGROUND: Tobacco smoke exposure (TSE) has inflammatory and immunosuppressive effects which may be associated with altered levels of inflammatory markers and pediatric illnesses. OBJECTIVE: The primary objective was to examine the associations of cotinine-confirmed and parent-reported child TSE patterns and discharge diagnoses with C-reactive protein (CRP), IL-8, and IL-10 in 0-11-year-old pediatric emergency department (PED) patients who lived with ≥ 1 smoker. METHODS: Saliva samples were obtained from 115 children with a mean (SD) age of 3.5 (3.1) years during the PED visit (T0). Saliva was analyzed for cotinine, CRP, IL-8, and IL-10. Parents self-reported their children's TSE patterns; children's medical records were reviewed to identify and categorize discharge diagnoses. Linear regression models were utilized to find T0 associations of cotinine-confirmed and parent-reported child TSE patterns, and PED diagnoses with each inflammatory marker. All models were adjusted for child race/ethnicity, child sex, annual household income, and housing type. The TSE models also adjusted for child discharge diagnosis. RESULTS: At T0, the geometric mean (GeoM) of cotinine was 4.1 ng/ml [95 %CI = 3.2-5.2]; the GeoMs of CRP, IL-8, and IL-10 were 3,326 pg/ml [95 %CI = 2,696-4,105], 474 pg/ml [95 %CI = 386-583], and 1.1 pg/ml [95 %CI = 0.9-1.3], respectively. Parent-reported child TSE patterns were positively associated with ln-transformed CRP levels, while adjusting for the covariates (ß^ = 0.012 [95 %CI:0.004-0.020], p = 0.037). In the parent-reported child TSE pattern model, there were significant positive associations between the covariate of child age with CRP and IL-8 levels (p = 0.028 and p < 0.001, respectively). Children with a bacterial diagnosis had higher IL-8 levels (p = 0.002) compared to the other diagnosis groups. CONCLUSIONS: Results indicate that parent-reported child TSE increases the expression of CRP in ill children and supports prior work demonstrating that IL-8 is higher in children with TSE who have bacterial infections. These findings should be examined in future research with ill children with and without TSE.

Contamination of surfaces in children's homes with nicotine and the potent carcinogenic tobacco-specific nitrosamine NNK.

BACKGROUND: Tobacco smoke exposure (TSE) through secondhand and thirdhand smoke is a modifiable risk factor that contributes to childhood morbidity. Limited research has assessed surface TSE pollution in children's environments as a potential source of thirdhand smoke exposure, and none have examined levels of the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) on surfaces. OBJECTIVE: This study measured surface NNK and nicotine in children's homes and associations with sociodemographics and parent-reported TSE behaviors. We assessed correlations of surface NNK and nicotine with dust NNK, dust nicotine, and child cotinine. METHODS: Home surface wipe NNK and nicotine data from 84 children who lived with smokers were analyzed. Tobit and simple linear regression analyses were conducted to assess associations of surface NNK and nicotine with child characteristics. Spearman's (ρ) correlations assessed the strength of associations between environmental markers and child cotinine. RESULTS: Nearly half (48.8%) of children's home surfaces had detectable NNK and 100% had detectable nicotine. The respective geometric means (GMs) of surface NNK and nicotine loadings were 14.0 ng/m2 and 16.4 µg/m2. Surface NNK positively correlated with surface nicotine (ρ = 0.54, p < 0.001) and dust NNK (ρ = 0.30, p = 0.020). Surface nicotine positively correlated with dust NNK (ρ = 0.42, p < 0.001) and dust nicotine (ρ = 0.24, p = 0.041). Children with household incomes ≤$15,000 had higher surface NNK levels (GM = 18.7 ng/m2, p = 0.017) compared to children with household incomes >$15,000 (GM = 7.1 ng/m2). Children with no home smoking bans had higher surface NNK (GM = 18.1 ng/m2, p = 0.020) and surface nicotine (GM = 17.7 µg/m2, p = 0.019) levels compared to children with smoking bans (GM = 7.5 ng/m2, 4.8 µg/m2, respectively). IMPACT: Although nicotine on surfaces is an established marker of thirdhand smoke pollution, other thirdhand smoke contaminants have not been measured on surfaces in the homes of children living with smokers. We provide evidence that the potent carcinogenic tobacco-specific nitrosamine NNK was detectable on surfaces in nearly half of children's homes, and nicotine was detectable on all surfaces. Surface NNK was positively correlated with surface nicotine and dust NNK. Detectable surface NNK levels were found in homes with indoor smoking bans, indicating the role of NNK as a persistent thirdhand smoke pollutant accumulating on surfaces as well as in dust.

Changes and stability of hand nicotine levels in children of smokers: Associations with urinary biomarkers, reported child tobacco smoke exposure, and home smoking bans.

BACKGROUND: Exposure to thirdhand smoke (THS) residue takes place through inhalation, ingestion, and dermal transfer. Hand nicotine levels have been proposed to measure THS pollution in the environment of children, but little is known about its variability and stability over time and correlates of change. OBJECTIVES: The goal was to determine the stability of hand nicotine in comparison to urinary biomarkers and to explore factors that influence changes in hand nicotine. METHODS: Data were collected from 0 to 11-year-old children (Mean age = 5.9) who lived with ≥1 tobacco smokers (N = 129). At a 6-week interval, we collected repeated measures of hand nicotine, four urinary biomarkers (cotinine, trans-3'-hydroxycotinine, nicotelline N-oxides, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol), and parent-reported child tobacco smoke exposure (TSE). Dependent sample t-tests, correlations, and multivariable regression analyses were conducted to examine the changes in child TSE. RESULTS: Hand nicotine levels (r = 0.63, p < 0.001) showed similar correlations between repeated measures to urinary biomarkers (r = 0.58-0.71; p < 0.001). Different from urinary biomarkers, mean hand nicotine levels increased over time (t(113) = 3.37, p < 0.001) being significantly higher in children from homes without smoking bans at Time 2 (p = 0.016) compared to Time 1 (p = 0.003). Changes in hand nicotine correlated with changes in cotinine and trans-3'-hydroxycotinine (r = 0.30 and r = 0.19, respectively, p < 0.05). Children with home smoking bans at Time 1 and 2 showed significantly lower hand nicotine levels compared to children without home smoking bans. DISCUSSION: Findings indicate that hand nicotine levels provide additional insights into children's exposure to tobacco smoke pollutants than reported child TSE and urinary biomarkers. Changes in hand nicotine levels show that consistent home smoking bans in homes of children of smokers can lower THS exposure. Hand nicotine levels may be influenced by the environmental settings in which they are collected.

Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants.

Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhand and thirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.

The Associations of Trans-3'-Hydroxy Cotinine, Cotinine, and the Nicotine Metabolite Ratio in Pediatric Patients with Tobacco Smoke Exposure.

(1) Background: Trans-3'-hydroxy cotinine (3HC) and cotinine (COT) are tobacco smoke exposure (TSE) biomarkers and the 3HC/COT ratio is a marker of CYP2A6 activity, an enzyme which metabolizes nicotine. The primary objective was to assess the associations of these TSE biomarkers with sociodemographics and TSE patterns in children who lived with ≥1 smoker. (2) Methods: A convenience sample of 288 children (mean age (SD) = 6.42 (4.8) years) was recruited. Multiple linear regression models were built to assess associations of sociodemographics and TSE patterns with urinary biomarker response variables: (1) 3HC, (2) COT, (3) 3HC+COT sum, and (4) 3HC/COT ratio. (3) Results: All children had detectable 3HC (Geometric Mean [GeoM] = 32.03 ng/mL, 95%CI = 26.97, 38.04) and COT (GeoM = 10.24 ng/mL, 95%CI = 8.82, 11.89). Children with higher cumulative TSE had higher 3HC and COT (ß^ = 0.03, 95%CI = 0.01, 0.06, p = 0.015 and ß^ = 0.03, 95%CI = 0.01, 0.05, p = 0.013, respectively). Highest 3HC+COT sum levels were in children who were Black (ß^ = 0.60, 95%CI = 0.04, 1.17, p = 0.039) and who had higher cumulative TSE (ß^ = 0.03, 95%CI = 0.01, 0.06, p = 0.015). Lowest 3HC/COT ratios were in children who were Black (ß^ = -0.42, 95%CI = -0.78, -0.07, p = 0.021) and female (ß^ = -0.32, 95%CI = -0.62, -0.01, p = 0.044). (4) Conclusion: Results indicate that there are racial and age-related differences in TSE, most likely due to slower nicotine metabolism in non-Hispanic Black children and in younger children.

Distinguishing Exposure to Secondhand and Thirdhand Tobacco Smoke among U.S. Children Using Machine Learning: NHANES 2013-2016.

While the thirdhand smoke (THS) residue from tobacco smoke has been recognized as a distinct public health hazard, there are currently no gold standard biomarkers to differentiate THS from secondhand smoke (SHS) exposure. This study used machine learning algorithms to assess which combinations of biomarkers and reported tobacco smoke exposure measures best differentiate children into three groups: no/minimal tobacco smoke exposure (NEG); predominant THS exposure (TEG); and mixed SHS and THS exposure (MEG). Participants were 4485 nonsmoking 3-17-year-olds from the National Health and Nutrition Examination Survey 2013-2016. We fitted and tested random forest models, and the majority (76%) of children were classified in NEG, 16% were classified in TEG, and 8% were classified in MEG. The final classification model based on reported exposure, biomarker, and biomarker ratio variables had a prediction accuracy of 95%. This final model had prediction accuracies of 100% for NEG, 88% for TEG, followed by 71% for MEG. The most important predictors were the reported number of household smokers, serum cotinine, serum hydroxycotinine, and urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). In the absence of validated biomarkers specific to THS, comprehensive biomarker and questionnaire data for tobacco smoke exposure can distinguish children exposed to SHS and THS with high accuracy.

Evaluation of a Social Media Campaign Designed to Increase Awareness of Thirdhand Smoke among California Adults.

Despite a growing body of research outlining the harms of thirdhand smoke (THS), the public remains generally unaware of risks and exposure routes. This project built on past tobacco prevention campaigns and the tenants of McGuire's input-output model to implement and evaluate a seven-month Facebook-disseminated campaign seeking to improve THS awareness among California adults (n = 1087). Multilinear regression showed that THS-related knowledge (χ2[6] = 19.31, p < .01), attitude (χ2[6] = 13.88, p < .05), and efficacy (χ2[6] = 13.81, p < .05) significantly increased by the campaign's end, with messages highlighting children's health (r = .110, p < .05), pets (r = .145, p < .01), and dust reservoirs (r = .144, p < .01) as the most persuasive. Path analysis modeling found campaign recall to be associated with changes in knowledge (ß = .161, p < .01), which predicated attitude change (ß = .614, p < .001) and, in turn, behavior change (ß = .149, p < .05). Findings suggest social media campaigns should continue to educate diverse populations about new tobacco risks and that tobacco control advocates should consider integrating educational THS messages.

When Hotel Guests Complain About Tobacco, Electronic Cigarettes, and Cannabis: Lessons for Implementing Smoking Bans.

We analyzed reviews on tripadvisor.com from a random sample of N = 477 hotels in ten large cities in the US to examine how well existing policies protect guests from exposure to tobacco, electronic cigarette, and cannabis (TEC) smoke. We examined the association between complaints per 100 reviews with hotel smoking policies, star rating, cost, brand, and location. Of all TEC complaints, 80% were associated with thirdhand smoke residue lingering in hotels from previous guests. Compared to the hotel brands with the best records, the two worst-performing brands had 3.4- and 3.6-times higher complaint rates (P < .001). Hotels with ≤2-star ratings had twice the complaints as higher-rated hotels (P < .001). Compared to 100% smokefree hotels, those offering designated smoking rooms had a 35% higher rate of complaints (P < .05). The success of some hotel brands demonstrates it is feasible to protect guests by fully committing to, implementing, and enforcing 100% smokefree building policies.

Hand nicotine as an independent marker of thirdhand smoke pollution in children's environments.

BACKGROUND: Hand nicotine (HN) levels measure children's exposure to tobacco smoke pollutants from thirdhand and secondhand smoke. HN is associated with urinary and salivary cotinine, but the associations of HN with other tobacco smoke exposure (TSE) markers remain unknown. OBJECTIVES: We compared levels of HN and four urinary TSE biomarkers: cotinine, trans-3'-hydroxycotinine (3HC), nicotelline N-oxides, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and children's sociodemographic and TSE patterns. We also examined if HN is a plausible pathway for children's exposure to active smoking. METHODS: Data were collected from 175 non-smoking patients (Mean (SD) age = 5.4 (3.4) years) who lived with ≥1 cigarette smoker(s). HN and TSE biomarker levels were determined using LC-MS/MS. Multivariate and multivariable regression analyses were conducted to examine associations between TSE markers and parent-reported measures, controlling for sociodemographics. RESULTS: Of the five markers of TSE, cotinine (R2 = 0.221; p = 0.003) and HN (R2 = 0.247; p = 0.001) showed the strongest overall associations. Of the five markers, only cotinine showed significantly higher levels among Black children (ß^=0.307,p<0.05) independent of age, reported exposure, and home smoking bans. Cotinine (ß^=0.010,p<0.05), NNAL (ß^=0.012,p<0.05), and HN (ß^=0.011,p<0.05) showed significant positive associations with reported exposure independent of race, age, and home smoking bans. NNAL (ß^=-0.285,p<0.05) and HN (ß^=-0.336,p<0.05), but not cotinine, 3HC, and N-oxides, showed significantly lower levels among children who lived in homes with smoking bans. Child age, hand surface area, home smoking ban, and reported exposure independently accounted for 21 % of the variance in HN levels (p = 0.002). HN accounted for 30 % of the variance in cotinine independent of child race and child age. DISCUSSION: HN levels were associated with modifiable tobacco-related behaviors and shows promise as a marker of sources of THS pollution in a child's environment not captured by measurement of urinary cotinine alone. HN levels provide additional information about TSE, complementing other biomarkers when assessing children's overall TSE.

Effects of Smoking on SARS-CoV-2 Positivity: A Study of a Large Health System in Northern and Central California.

Introduction: COVID-19 continues to impact vulnerable populations disproportionally. Identifying modifiable risk factors could lead to targeted interventions to reduce infections. The purpose of this study is to identify risk factors for testing positive for SARS-CoV-2. Methods: Using electronic health records collected from a large ambulatory care system in northern and central California, the study identified patients who had a test for SARS-CoV-2 between 2/20/2020 and 3/31/2021. The adjusted effect of active and passive smoking and other risk factors on the probability of testing positive for SARS-CoV-2 were estimated using multivariable logistic regression. Analyses were conducted in 2021. Results: Of 556 690 eligible patients in our sample, 70 564 (12.7%) patients tested positive for SARS-CoV-2. Younger age, being male, racial/ethnic minorities, and having mild major comorbidities were significantly associated with a positive SARS-CoV-2 test. Current smokers (adjusted OR: 0.69, 95% CI: 0.66-0.73) and former smokers (adjusted OR: 0.92, 95% CI: 0.89-0.95) were less likely than nonsmokers to be lab-confirmed positive, but no statistically significant differences were found when comparing passive smokers with non-smokers. The patients with missing smoking status (25.7%) were more likely to be members of vulnerable populations with major comorbidities (adjusted OR ranges from severe: 2.52, 95% CI = 2.36-2.69 to mild: 3.28, 95% CI = 3.09-3.48), lower income (adjusted OR: 0.85, 95% CI: 0.85-0.86), aged 80 years or older (adjusted OR: 1.11, 95% CI: 1.07-1.16), have less access to primary care (adjusted OR: 0.07, 95% CI: 0.07-0.07), and identify as racial ethnic minorities (adjusted OR ranges from Hispanic: 1.61, 95% CI = 1.56-1.65 to Non-Hispanic Black: 2.60, 95% CI = 2.5-2.69). Conclusions: Our findings suggest that the odds of testing positive for SARS-CoV-2 were significantly lower in smokers compared to nonsmokers. Other risk factors include missing data on smoking status, being under 18, being male, being a racial/ethnic minority, and having mild major comorbidities. Since those with missing data on smoking status were more likely to be members of vulnerable populations with higher smoking rates, the risk of testing positive for SARS-CoV-2 among smokers may have been underestimated due to missing data on smoking status. Future studies should investigate the risk of severe outcomes among active and passive smokers, the role that exposure to tobacco smoke constitutes among nonsmokers, the role of comorbidities in COVID-19 disease course, and health disparities experienced by disadvantaged groups.

High Levels of the Carcinogenic Tobacco-Specific Nitrosamine NNAL and Associated Findings in Children of Smokers: A Case Series.

High levels of NNAL, the tobacco smoke exposure (TSE) biomarker of the carcinogen 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), indicate future cancer risk. A prior study of smokers' children revealed NNAL levels as high as active smokers. Therefore, we conducted a case series to examine the sociodemographics, TSE and clinical patterns, and other TSE biomarker levels in 9 children with extreme NNAL levels of >200 pg/ml to generate hypotheses and explore potential causes and implications. We identified 0 to 4-year-olds who presented to an emergency setting and lived with ⩾1 smoker who were part of a parental tobacco cessation trial (n = 461). Of these children, 52 had urinary NNAL, cotinine, and N-oxides results (n = 52). Nine children (17.3%) had NNAL levels >200 pg/ml, ranging from 206.4 to 1399.0 pg/ml (Median (Mdn) = 489.2 pg/ml; Interquartile Range (IQR) = 222.7-1289.3 pg/ml). The cotinine Mdn (IQR) was 38.5 (10.3-102.2) ng/ml and the N-oxides Mdn (IQR) = 93.8 (24.7-109.6) pg/ml. While all biomarker levels were alarmingly high, these young children would not have been flagged for very high cancer risk based on urinary cotinine levels alone. This underscores the critical role of comprehensive TSE biomarker measurement in capturing different TSE exposure patterns and assessing children's future risk for cancer and other TSE-related morbidities.

Thirdhand Exposures to Tobacco-Specific Nitrosamines through Inhalation, Dust Ingestion, Dermal Uptake, and Epidermal Chemistry.

Tobacco-specific nitrosamines (TSNAs) are emitted during smoking and form indoors by nitrosation of nicotine. Two of them, N'-nitrosonornicotine (NNN) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), are human carcinogens with No Significant Risk Levels (NSRLs) of 500 and 14 ng day-1, respectively. Another TSNA, 4-(methylnitrosamino)-4-(3-pyridyl) butanal (NNA), shows genotoxic and mutagenic activity in vitro. Here, we present additional evidence of genotoxicity of NNA, an assessment of TSNA dermal uptake, and predicted exposure risks through different pathways. Dermal uptake was investigated by evaluating the penetration of NNK and nicotine through mice skin. Comparable mouse urine metabolite profiles suggested that both compounds were absorbed and metabolized via similar mechanisms. We then investigated the effects of skin constituents on the reaction of adsorbed nicotine with nitrous acid (epidermal chemistry). Higher TSNA concentrations were formed on cellulose and cotton substrates that were precoated with human skin oils and sweat compared to clean substrates. These results were combined with reported air, dust, and surface concentrations to assess NNK intake. Five different exposure pathways exceeded the NSRL under realistic scenarios, including inhalation, dust ingestion, direct dermal contact, gas-to-skin deposition, and epidermal nitrosation of nicotine. These results illustrate potential long-term health risks for nonsmokers in homes contaminated with thirdhand tobacco smoke.

A systematic review of the use of silicone wristbands for environmental exposure assessment, with a focus on polycyclic aromatic hydrocarbons (PAHs).

BACKGROUND: Exposure assessment is critical for connecting environmental pollutants to health outcomes and evaluating impacts of interventions or environmental policies. Silicone wristbands (SWBs) show promise for multi-pollutant exposure assessment, including polycyclic aromatic hydrocarbons (PAHs), a ubiquitous class of toxic environmental pollutants. OBJECTIVE: To review published studies where SWBs were worn on the wrist for human environmental exposure assessments and evaluate the ability of SWBs to capture personal exposures, identify gaps which need to be addressed to implement this tool, and make recommendations for future studies to advance the field of exposure science through utilization of SWBs. METHODS: We performed a systematic search and a cited reference search in Scopus and extracted key study descriptions. RESULTS: Thirty-nine unique studies were identified, with analytes including PAHs, pesticides, flame retardants, and tobacco products. SWBs were shipped under ambient conditions without apparent analyte loss, indicating utility for global exposure and health studies. Nineteen articles detected a total of 60 PAHs in at least one SWB. Correlations with other concurrent biological and air measurements indicate the SWB captures exposure to flame retardants, tobacco products, and PAHs. SIGNIFICANCE: SWBs show promise as a simple-to-deploy tool to estimate environmental and occupational exposures to chemical mixtures, including PAHs.

Thirdhand Smoke Knowledge, Attitudes, and Behavior: Development of Reliable and Valid Self-report Measures.

INTRODUCTION: This study sought to provide essential tobacco control tools by testing the reliability and validity of new self-report scales developed to assess thirdhand smoke (THS) (ie, toxic tobacco residue) related knowledge, attitudes, and behavior (KAB). AIMS AND METHODS: Items for the KAB scales were adapted from established secondhand smoke (SHS) measures, reviewed to support face validity, and tested in a longitudinal online survey evaluating THS health messages. Participants were California adults at risk of THS exposure. For 7 months, the three KAB scales were completed monthly, and data from the first (n = 1086), third (n = 315), and seventh (n = 301) month surveys were used in these analyses. RESULTS: All three scales demonstrated consistent reliability and single-factor loading at all three timepoints for knowledge (αrange: .87-.90), attitude (αrange: .84-.87), and behavior (αrange: .80-.86). Similarly, analyses supported scale convergent validity (scale correlations rrange: .45-.85; all p values <.001), discriminant validity between smokers and nonsmokers (knowledge Cohen's drange: .57-.61, all p values <.001; attitude Cohen's drange: .78-.82, all p values <.001; behavior Cohen's drange: .90-.99, all p values <.001), and predictive validity (range R2KAB: .41-.48; all p values <.001). CONCLUSIONS: KAB scales about THS provide new opportunities for tobacco control advocates and scholars to identify gaps in knowledge, misperceptions, and obstacles to behavior change in order to guide the design of novel tobacco control policies and interventions. IMPLICATIONS: Numerous scales have been vetted as reliable and valid measures for assessing SHS-related KABs. Currently, standard measures of THS KABs are not available. This study tested three THS scales to fill this gap. The present findings provide tobacco control advocates, scholars, and practitioners tools for assessing KABs related to THS. This information is critical to development, implementation, and evaluation of novel tobacco control strategies.

Handwashing Results in Incomplete Nicotine Removal from Fingers of Individuals who Smoke: A Randomized Controlled Experiment.

OBJECTIVE: Tobacco residue, also known as third-hand smoke (THS), contains toxicants and lingers in dust and on surfaces and clothes. THS also remains on hands of individuals who smoke, with potential transfer to infants during visitation while infants are hospitalized in neonatal intensive care units (NICUs), raising concerns (e.g., hindered respiratory development) for vulnerable infants. Previously unexplored, this study tested handwashing (HW) and sanitization efficacy for finger-nicotine removal in a sample of adults who smoked and were visiting infants in an NICU. STUDY DESIGN: A cross-sectional sample was recruited to complete an interview, carbon monoxide breath samples, and three nicotine wipes of separate fingers (thumb, index, and middle). Eligible participants (n = 14) reported current smoking (verified with breath samples) and were randomly assigned to 30 seconds of HW (n = 7) or alcohol-based sanitization (n = 7), with the order of finger wipes both counterbalanced and randomly assigned. After randomization, the first finger was wiped for nicotine. Participants then washed or sanitized their hands and finger two was wiped 5 minutes later. An interview assessing tobacco/nicotine use and exposure was then administered, followed by a second breath sample and the final finger wipe (40-60 minutes after washing/sanitizing). RESULTS: Generalized linear mixed models found that HW was more effective than sanitizer for nicotine removal but failed to completely remove nicotine. CONCLUSIONS: Without proper protections (e.g., wearing gloves and gowns), NICU visitors who smoke may inadvertently expose infants to THS. Research on cleaning protocols are needed to protect vulnerable medical populations from THS and associated risks. KEY POINTS: · NICU infants may be exposed to THS via visitors.. · THS is not eliminated by HW or sanitizing.. · THS removal protections for NICU infants are needed..

Comparison of Levels of Three Tobacco Smoke Exposure Biomarkers in Children of Smokers.

Objectives: Cotinine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and N-oxides are biomarkers of tobacco smoke exposure (TSE) used to assess short- and longer-term TSE. The objective of this study was to assess the associations between these TSE biomarkers, sociodemographics, parental smoking, and child TSE patterns among 0-17-year-olds. Methods: A convenience sample of 179 pediatric patients (mean (SD) age = 7.9 (4.3) years) who lived with ≥1 smoker and who had parental assessments completed and urine samples analyzed for the three TSE biomarkers of interest were included. Biomarker levels were log-transformed, univariate regression models were built and Pearson correlations were assessed. Results: In total, 100% of children had detectable levels of cotinine and >96% had detectable NNAL and N-oxide levels. The geometric means of cotinine, NNAL, and N-oxide levels were 10.1 ng/mL, 25.3 pg/mL, and 22.9 pg/mL, respectively. The mean (SD) number of daily cigarettes smoked by parents was 10.6 (6.0) cigarettes. Child age negatively correlated with urinary cotinine (r = -0.202, p = 0.007) and log NNAL levels (r = -0.275, p < 0.001). The highest log-cotinine levels were in children who were younger, of African American race, and whose parents had a lower education, an annual income ≤USD15,000, and no smoking bans. The highest log-NNAL and N-oxide levels were in children whose parents had a lower education, had no smoking bans, and were around higher numbers of cigarettes. Conclusion: Children of smokers who were younger, African American, and had no smoking bans had the highest TSE biomarker levels. Targeted interventions are needed to reduce TSE levels among high-risk children.

Hand Nicotine and Cotinine In Children Exposed to Cigars: A Pilot Study.

OBJECTIVES: Past research has not examined secondhand and thirdhand smoke (THS) exposure in children of cigar smokers. We examined hand nicotine and cotinine levels in children of cigar smokers to explore the contribution of cigar smoke to tobacco smoke exposure (TSE). METHODS: Participants were children (N = 24; mean (SD) age = 6.5 (3.6) years) whose parents smoked cigars only or poly-used cigars and/or cigarettes. Primary outcomes were hand nicotine and urinary cotinine levels. RESULTS: All children had detectable hand nicotine (range: 7.6-312.5ng/wipe) and cotinine (range: 0.3-100.3ng/ml). Positive correlations were found between hand nicotine and cotinine (r = 0.693, p = .001), hand nicotine and parents who also smoked cigarettes (r = 0.407, p = .048), and hand nicotine and number of smokers around the child (r = 0.436, p = .03). Hand nicotine (r = -0.464, p = .02), but not cotinine (r = -0.266, p = .26), was negatively correlated with child age. Multiple regression results indicated a positive association between hand nicotine and cotinine (p = .002; semi-partial r2 = 0.415), irrespective of child age. CONCLUSIONS: The significant association of hand nicotine with urinary cotinine suggests that THS pollution should be assessed in evaluating children's overall TSE to cigars and other tobacco products, and hand nicotine may be a proxy for overall TSE. Younger children may have increased THS pollutant uptake.