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 (β^ = 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 (β^ = 0.03, 95%CI = 0.01, 0.06, p = 0.015 and β^ = 0.03, 95%CI = 0.01, 0.05, p = 0.013, respectively). Highest 3HC+COT sum levels were in children who were Black (β^ = 0.60, 95%CI = 0.04, 1.17, p = 0.039) and who had higher cumulative TSE (β^ = 0.03, 95%CI = 0.01, 0.06, p = 0.015). Lowest 3HC/COT ratios were in children who were Black (β^ = -0.42, 95%CI = -0.78, -0.07, p = 0.021) and female (β^ = -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.

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 (β = .161, p < .01), which predicated attitude change (β = .614, p < .001) and, in turn, behavior change (β = .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.

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.

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 (β^=0.307,p<0.05) independent of age, reported exposure, and home smoking bans. Cotinine (β^=0.010,p<0.05), NNAL (β^=0.012,p<0.05), and HN (β^=0.011,p<0.05) showed significant positive associations with reported exposure independent of race, age, and home smoking bans. NNAL (β^=-0.285,p<0.05) and HN (β^=-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.

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..

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.

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.

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.

Effects of Smoking on SARS-CoV-2 Positivity: A Study of 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.

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.

Prevalence and Income-Related Disparities in Thirdhand Smoke Exposure to Children

This cross-sectional study examines the prevalence of and income-related disparities associated with exposure to thirdhand smoke among children.

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.

Altered microbiomes in thirdhand smoke-exposed children and their home environments

INTRODUCTION

Tobacco smoke contains numerous toxic chemicals that accumulate in indoor environments creating thirdhand smoke (THS). We investigated if THS-polluted homes differed in children's human and built-environment microbiomes as compared to THS-free homes.

METHODS

Participants were n = 19 THS-exposed children and n = 10 unexposed children (≤5 years) and their caregivers. Environmental and biological samples were analyzed for THS pollutants and exposure. Swab samples were collected from the built-environment (floor, table, armrest, bed frame) and child (finger, nose, mouth, and ear canal), and 16S ribosomal RNA genes were analyzed for bacterial taxa using high-throughput DNA sequencing.

RESULTS

Phylogenetic α-diversity was significantly higher for the built-environment microbiomes in THS-polluted homes compared to THS-free homes (p < 0.014). Log2-fold comparison found differences between THS-polluted and THS-free homes for specific genera in samples from the built-environment (e.g., Acinetobacter, Bradyrhizobium, Corynebacterium, Gemella, Neisseria, Staphylococcus, Streptococcus, and Veillonella) and in samples from children (esp. Corynebacterium, Gemella, Lautropia, Neisseria, Rothia, Staphylococcus, and Veillonella).

CONCLUSION

When exposed to THS, indoor and children microbiomes are altered in an environment-specific manner. Changes are similar to those reported in previous studies for smokers and secondhand smoke-exposed persons. THS-induced changes in child and built-environmental microbiomes may play a role in clinical outcomes in children.

IMPACT

Despite smoking bans, children can be exposed to tobacco smoke residue (i.e., thirdhand smoke) that lingers on surfaces and in settled house dust. Thirdhand smoke exposure is associated with changes in the microbiomes of the home environment and of the children living in these homes. Thirdhand smoke is associated with increased phylogenetic diversity of the home environment and changes in the abundances of several genera of the child microbiome known to be affected by active smoking and secondhand smoke (e.g., Corynebacterium, Staphylococcus, Streptococcus). Thirdhand smoke exposure by itself may induce alterations in the microbiome that play a role in childhood pathologies.

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.

Differential associations of hand nicotine and urinary cotinine with children's exposure to tobacco smoke and clinical outcomes

BACKGROUND

Children's overall tobacco smoke exposure (TSE) consists of both inhalation of secondhand smoke (SHS) and ingestion, dermal uptake, and inhalation of thirdhand smoke (THS) residue from dust and surfaces in their environments.

OBJECTIVES

Our objective was to compare the different roles of urinary cotinine as a biomarker of recent overall TSE and hand nicotine as a marker of children's contact with nicotine pollution in their environments. We explored the differential associations of these markers with sociodemographics, parental smoking, child TSE, and clinical diagnoses.

METHODS

Data were collected from 276 pediatric emergency department patients (Median age = 4.0 years) who lived with a cigarette smoker. Children's hand nicotine and urinary cotinine levels were determined using LC-MS/MS. Parents reported tobacco use and child TSE. Medical records were reviewed to assess discharge diagnoses.

RESULTS

All children had detectable hand nicotine (GeoM = 89.7ng/wipe; 95 % CI = [78.9; 102.0]) and detectable urinary cotinine (GeoM = 10.4 ng/ml; 95%CI = [8.5; 12.6]). Although hand nicotine and urinary cotinine were highly correlated (r = 0.62, p < 0.001), urinary cotinine geometric means differed between racial groups and were higher for children with lower family income (p < 0.05), unlike hand nicotine. Independent of urinary cotinine, age, race, and ethnicity, children with higher hand nicotine levels were at increased risk to have discharge diagnoses of viral/other infectious illness (aOR = 7.49; 95%CI = [2.06; 27.24], p = 0.002), pulmonary illness (aOR = 6.56; 95%CI = [1.76; 24.43], p = 0.005), and bacterial infection (aOR = 5.45; 95%CI = [1.50; 19.85], p = 0.03). In contrast, urinary cotinine levels showed no associations with diagnosis independent of child hand nicotine levels and demographics.

DISCUSSION

The distinct associations of hand nicotine and urinary cotinine suggest the two markers reflect different exposure profiles that contribute differentially to pediatric illness. Because THS in a child's environment directly contributes to hand nicotine, additional studies of children of smokers and nonsmokers are warranted to determine the role of hand nicotine as a marker of THS exposure and its potential role in the development of tobacco-related pediatric illnesses.

Thirdhand smoke associations with the gut microbiomes of infants admitted to a neonatal intensive care unit: An observational study

INTRODUCTION

Microbiome differences have been found in adults who smoke cigarettes compared to non-smoking adults, but the impact of thirdhand smoke (THS; post-combustion tobacco residue) on hospitalized infants' rapidly developing gut microbiomes is unexplored. Our aim was to explore gut microbiome differences in infants admitted to a neonatal ICU (NICU) with varying THS-related exposure.

METHODS

Forty-three mother-infant dyads (household member[s] smoke cigarettes, n = 32; no household smoking, n = 11) consented to a carbon monoxide-breath sample, bedside furniture nicotine wipes, infant-urine samples (for cotinine [nicotine's primary metabolite] assays), and stool collection (for 16S rRNA V4 gene sequencing). Negative binomial regression modeled relative abundances of 8 bacterial genera with THS exposure-related variables (i.e., household cigarette use, surface nicotine, and infant urine cotinine), controlling for gestational age, postnatal age, antibiotic use, and breastmilk feeding. Microbiome-diversity outcomes were modeled similarly. Bayesian posterior probabilities (PP) ≥75.0% were considered meaningful.

RESULTS

A majority of infants (78%) were born pre-term. Infants from non-smoking homes and/or with lower NICU-furniture surface nicotine had greater microbiome alpha-diversity compared to infants from smoking households (PP ≥ 75.0%). Associations (with PP ≥ 75.0%) of selected bacterial genera with urine cotinine, surface nicotine, and/or household cigarette use were evidenced for 7 (of 8) modeled genera. For example, lower Bifidobacterium relative abundance associated with greater furniture nicotine (IRR<0.01 [<0.01, 64.02]; PP = 87.1%), urine cotinine (IRR = 0.08 [<0.01,2.84]; PP = 86.9%), and household smoking (IRR<0.01 [<0.01, 7.38]; PP = 96.0%; FDR p < 0.05).

CONCLUSIONS

THS-related exposure was associated with microbiome differences in NICU-admitted infants. Additional research on effects of tobacco-related exposures on healthy infant gut-microbiome development is warranted.

Thirdhand Smoke Contamination and Infant Nicotine Exposure in a Neonatal Intensive Care Unit: An Observational Study

INTRODUCTION

Thirdhand smoke (THS) is ultrafine particulate matter and residue resulting from tobacco combustion, with implications for health-related harm (eg, impaired wound healing), particularly among hospitalized infants. Project aims were to characterize nicotine (THS proxy) transported on neonatal intensive care unit (NICU) visitors and deposited on bedside furniture, as well as infant exposure.

METHODS

Cross-sectional data were collected from participants in a metropolitan NICU. Participants completed a survey and carbon monoxide breath sample, and 41.9% (n = 88) of participants (n = 210) were randomly selected for finger-nicotine wipes during a study phase when all bedside visitors were screened for nicotine use and finger-nicotine levels. During an overlapping study phase, 80 mother-infant dyads consented to bedside furniture-nicotine wipes and an infant urine sample (for cotinine analyses).

RESULTS

Most nonstaff visitors' fingers had nicotine above the limit of quantification (>LOQ; 61.9%). Almost all bedside furniture surfaces (93.8%) and infant cotinine measures (93.6%) had values >LOQ, regardless of household nicotine use. Participants who reported using (or lived with others who used) nicotine had greater furniture-nicotine contamination (Mdn = 0.6 [interquartile range, IQR = 0.2-1.6] µg/m2) and higher infant cotinine (Mdn = 0.09 [IQR = 0.04-0.25] ng/mL) compared to participants who reported no household-member nicotine use (Mdn = 0.5 [IQR = 0.2-0.7] µg/m2; Mdn = 0.04 [IQR = 0.03-0.07] ng/mL, respectively). Bayesian univariate regressions supported hypotheses that increased nicotine use/exposure correlated with greater nicotine contamination (on fingers/furniture) and infant THS exposure.

CONCLUSIONS

Potential furniture-contamination pathways and infant-exposure routes (eg, dermal) during NICU hospitalization were identified, despite hospital prohibitions on tobacco/nicotine use. This work highlights the surreptitious spread of nicotine and potential THS-related health risks to vulnerable infants during critical stages of development.

IMPLICATIONS

THS contamination is underexplored in medical settings. Infants who were cared for in the NICU are vulnerable to health risks from THS exposure. This study demonstrated that 62% of nonstaff NICU visitors transport nicotine on their fingers to the NICU. Over 90% of NICU (bedside) furniture was contaminated with nicotine, regardless of visitors' reported household-member nicotine use or nonuse. Over 90% of infants had detectable levels of urinary cotinine during NICU hospitalizations. Results justify further research to better protect infants from unintended THS exposure while hospitalized.

Nicotine, Cotinine, and Tobacco-Specific Nitrosamines Measured in Children's Silicone Wristbands in Relation to Secondhand Smoke and E-cigarette Vapor Exposure

INTRODUCTION

Simple silicone wristbands (WB) hold promise for exposure assessment in children. We previously reported strong correlations between nicotine in WB worn by children and urinary cotinine (UC). Here, we investigated differences in WB chemical concentrations among children exposed to secondhand smoke from conventional cigarettes (CC) or secondhand vapor from electronic cigarettes (EC), and children living with nonusers of either product (NS).

METHODS

Children (n = 53) wore three WB and a passive nicotine air sampler for 7 days and one WB for 2 days, and gave a urine sample on day 7. Caregivers reported daily exposures during the 7-day period. We determined nicotine, cotinine, and tobacco-specific nitrosamines (TSNAs) concentrations in WB, nicotine in air samplers, and UC through isotope-dilution liquid chromatography with triple-quadrupole mass spectrometry.

RESULTS

Nicotine and cotinine levels in WB in children differentiated between groups of children recruited into NS, EC exposed, and CC exposed groups in a similar manner to UC. WB levels were significantly higher in the CC group (WB nicotine median 233.8 ng/g silicone, UC median 3.6 ng/mL, n = 15) than the EC group (WB nicotine median: 28.9 ng/g, UC 0.5 ng/mL, n = 19), and both CC and EC group levels were higher than the NS group (WB nicotine median: 3.7 ng/g, UC 0.1 ng/mL, n = 19). TSNAs, including the known carcinogen NNK, were detected in 39% of WB.

CONCLUSIONS

Silicone WB show promise for sensitive detection of exposure to tobacco-related contaminants from traditional and electronic cigarettes and have potential for tobacco control efforts.

IMPLICATIONS

Silicone WB worn by children can absorb nicotine, cotinine, and tobacco-specific nitrosamines, and amounts of these compounds are closely related to the child's urinary cotinine. Levels of tobacco-specific compounds in the silicone WB can distinguish patterns of children's exposure to secondhand smoke and e-cigarette vapor. Silicone WB are simple to use and acceptable to children and, therefore, may be useful for tobacco control activities such as parental awareness and behavior change, and effects of smoke-free policy implementation.

Remediating Thirdhand Smoke Pollution in Multiunit Housing: Temporary Reductions and the Challenges of Persistent Reservoirs

INTRODUCTION

Toxic tobacco smoke residue, also known as thirdhand smoke (THS), can persist in indoor environments long after tobacco has been smoked. This study examined the effects of different cleaning methods on nicotine in dust and on surfaces.

AIMS AND METHODS

Participants had strict indoor home smoking bans and were randomly assigned to: dry/damp cleaning followed by wet cleaning 1 month later (N = 10), wet cleaning followed by dry/damp cleaning (N = 10) 1 month later, and dry/damp and wet cleaning applied the same day (N = 28). Nicotine on surfaces and in dust served as markers of THS and were measured before, immediately after, and 3 months after the cleaning, using liquid chromatography with triple quadrupole mass spectrometry (LC-MS/MS).

RESULTS

Over a 4-month period prior to cleaning, surface nicotine levels remained unchanged (GeoMean change: -11% to +8%; repeated measures r = .94; p < .001). Used separately, dry/damp and wet cleaning methods showed limited benefits. When applied in combination, however, we observed significantly reduced nicotine on surfaces and in dust. Compared with baseline, GeoMean surface nicotine was 43% lower immediately after (z = -3.73, p < .001) and 53% lower 3 months later (z = -3.96, p < .001). GeoMean dust nicotine loading declined by 60% immediately after (z = -3.55, p < .001) and then increased 3 months later to precleaning levels (z = -1.18, p = .237).

CONCLUSIONS

Cleaning interventions reduced but did not permanently remove nicotine in dust and on surfaces. Cleaning efforts for THS need to address persistent pollutant reservoirs and replenishment of reservoirs from new tobacco smoke intrusion. THS contamination in low-income homes may contribute to health disparities, particularly in children.

IMPLICATIONS

Administered sequentially or simultaneously, the tested cleaning protocols reduced nicotine on surfaces by ~50% immediately after and 3 months after the cleaning. Nicotine dust loading was reduced by ~60% immediately after cleaning, but it then rebounded to precleaning levels 3 months later. Cleaning protocols were unable to completely remove THS, and pollutants in dust were replenished from remaining pollutant reservoirs or new secondhand smoke intrusion. To achieve better outcomes, cleaning protocols should be systematically repeated to remove newly accumulated pollutants. New secondhand smoke intrusions need to be prevented, and remaining THS reservoirs should be identified, cleaned, or removed to prevent pollutants from these reservoirs to accumulate in dust and on surfaces.

Tobacco smoke is a likely source of lead and cadmium in settled house dust

INTRODUCTION

Environmental exposure to lead (Pb) and cadmium (Cd) are risk factors for adverse health outcomes in children and adults. This study examined whether thirdhand smoke residue contributes to Pb and Cd in settled house dust.

METHODS

Participants were 60 multiunit housing residents in San Diego, California. All had indoor smoking bans during the study period, and 55 were nonsmokers. Wipe samples from different surfaces and vacuum floor dust samples were analyzed for nicotine, a marker of thirdhand smoke, and for Pb and Cd using liquid chromatography-triple quadrupole mass spectrometry and inductively coupled plasma-mass spectrometry, respectively.

RESULTS

Examined in each sample type separately, Pb and Cd loadings were significantly correlated (r = 0.73, vacuum floor dust; 0.52, floor wipes; 0.72, window sill/trough wipes; all p < 0.0025). Pb and Cd loadings from different sample types were not correlated (all p > 0.30). Nicotine loading in dust was significantly correlated with Pb and Cd loading in dust (r = 0.49 for Pb; r = 0.39 for Cd, all p < 0.0025). Pb and Cd loadings on floor or window surfaces, showed no association with nicotine loading in dust, on floors, or on furniture (all p < 0.30).

CONCLUSIONS

Tobacco smoke is a likely source of Pb and Cd that accumulates in settled house dust in multiunit housing, suggesting that Pb and Cd are constituents of thirdhand smoke that lingers long after smoking has ended.

Electronic Health Record Classification of Tobacco Smoke Exposure and Cotinine Levels in Hospitalized Pediatric Patients

OBJECTIVES

Documentation of children's tobacco smoke exposure (TSE) in the electronic health record (EHR) can have important implications for clinical care. However, it may not be accurate if it is not based on biochemical assessment, the most reliable method of verifying TSE. Our objectives were to compare the accuracy of EHR classification of TSE with cotinine verification and to explore parent and child variables associated with biochemically verified TSE.

METHODS

Participants were 171 hospitalized pediatric patients (ages 0-17 years; mean age 5.1 [SD 3.7] years) who had EHR documentation of TSE and measured salivary cotinine. Children with cotinine levels >1 ng/mL were classified as having biochemical verification of TSE. Parents reported sociodemographic characteristics, and children's EHRs were abstracted for TSE status, past medical history, and diagnoses. We conducted χ² tests to assess the agreement between EHR classification of TSE status and cotinine levels. Then, we assessed the relationship between sociodemographic and clinical variables and cotinine using crude and adjusted logistic regression models.

RESULTS

Overall, 71% (121 of 171) of EHR classifications were correct on the basis of cotinine levels. Specificity analyses showed that 77% (53 of 69) were correctly identified as exposed to tobacco smoke. Sensitivity analyses showed that 67% (68 of 102) were correctly identified as unexposed. The negative predictive value was 0.61 (53 of 87); 39% (34 of 87) were misclassified as unexposed. The positive predictive value was 0.81 (68 of 84); 19% (16 of 84) were misclassified as exposed.

CONCLUSIONS

Almost 40% of children were misclassified in the EHR as unexposed to tobacco smoke. Biochemical verification should be used as part of universal TSE screening during pediatric hospitalizations.

Persistent tobacco smoke residue in multiunit housing: Legacy of permissive indoor smoking policies and challenges in the implementation of smoking bans

Secondhand smoke (SHS) is a common indoor pollutant in multiunit housing (MUH). It is also the precursor of thirdhand smoke (THS), the toxic mixture of tobacco smoke residue that accumulates in indoor environments where tobacco has been used. This study examined the levels, distribution, and factors associated with THS pollution in low-income MUH. Interviews were conducted 2016-2018 in a cross-sectional study of N = 220 MUH homes in San Diego, California. Two surface wipe samples were collected per home and analyzed for nicotine, a THS marker, using liquid chromatography-triple quadrupole mass spectrometry. Nicotine was detected in all homes of nonsmokers with indoor smoking bans (Geo Mean = 1.67 µg/m²; 95% CI = [1.23;2.30]) and smokers regardless of an indoor ban (Geo Mean = 4.80 µg/m²; 95% CI = [1.89;12.19]). Approximately 10% of nonsmokers' homes with smoking bans showed nicotine levels higher than the average level in homes of smokers without smoking bans from previous studies (≥30 µg/m²). Housing for seniors, smoking bans on balconies, indoor tobacco use, difficult to reach surfaces, and self-reported African-American race/ethnicity were independently associated with higher THS levels. Individual cases demonstrated that high levels of surface nicotine may persist in nonsmoker homes for years after tobacco use even in the presence of indoor smoking bans. To achieve MUH free of tobacco smoke pollutants, attention must be given to identifying and remediating highly polluted units and to implementing smoking policies that prevent new accumulation of THS. As THS is a form of toxic tobacco product waste, responsibility for preventing and mitigating harmful impacts should include manufacturers, suppliers, and retailers.

The Association of Environmental Tobacco Smoke Exposure and Inflammatory Markers in Hospitalized Children

Background: Environmental tobacco smoke (ETS) exposure is associated with altered cytokine levels in children. We sought to examine ETS exposure prevalence and the relationship between ETS exposure and cytokine levels in a sample of hospitalized children. (2) Methods: Inflammatory markers (IL-8, IL-1β, IL-10, and TNF-α) and cotinine were measured in saliva of hospitalized, nonsmoking children (N = 112). To assess the association between ETS exposure and immune system response, we built a multivariate regression model including the four inflammatory markers as the response variables and cotinine, age, sex, and discharge diagnosis as explanatory variables while assessing possible interaction effects. (3) Results: Mean age (SD) was 5.8(5.0) years; Geometric Mean (GeoM) cotinine = 1.8 [95% CI = 1.4–2.2]. Children with non-inflammatory other diagnoses had lower IL-10 (p = 0.003) and TNF-α (p = 0.009) levels than children with inflammatory other diagnoses. Children with asthma (p = 0.01) and bacterial illnesses and/or pneumonia (p = 0.002) had higher IL-8 levels. Independent of diagnosis, there was a significant curvilinear association between cotinine and IL-1β (p = 0.002) reflecting no association for cotinine levels <5 ng/mL and a positive association for >5 ng/mL. (4) Conclusions: Children with higher ETS exposure levels have higher IL-1β levels regardless of age, sex, and diagnosis. ETS exposure may increase pro-inflammatory immune responses in children and may interfere with native immune responses and the ability to heal and fight infection.

Nicotine in thirdhand smoke residue predicts relapse from smoking cessation: A pilot study

INTRODUCTION

Thirdhand smoke (THS) residue lingers for months in homes of former smokers and may play a role in relapse after smoking cessation. This study examined the association between THS pollution as measured by the level of nicotine in house dust and continued abstinence from smoking.

METHODS

Participants were 65 cigarette smokers who reported they were enrolled in any type of smoking cessation program, had set a specific date to quit, and had biochemical verification of continuous abstinence at 1-week (W1), 1-month (M1), 3-months (M3), or 6-months (M6) after their quit date. House dust samples collected at baseline before quitting were analyzed for nicotine concentration (μg/g) and nicotine loading (μg/m²) using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

Controlling for age, gender, overall and indoor smoking rates, and years lived in their home, dust nicotine concentration and loading predicted abstinence at W1, M1, M3, and M6. A 10-fold increase in dust nicotine loading and concentration were associated with approximately 50% lower odds of remaining abstinent.

CONCLUSIONS

Findings suggest nicotine in house dust may play a role in facilitating relapse after smoking cessation. Additional research is warranted to investigate the causal role of THS residue in homes of former smokers on cravings and continued abstinence.

Nicotine levels in silicone wristband samplers worn by children exposed to secondhand smoke and electronic cigarette vapor are highly correlated with child's urinary cotinine

Exposure assessment in children, especially young children, presents difficulties not found with adults. Simple silicone wristbands are passive samplers that have potential applicability in exposure studies of children. We investigated the performance of silicone wristbands as personal nicotine samplers in two wristbands worn by a child (n = 31) for 7 days and for 2 days (worn day 5 to day 7). We compared levels of nicotine in wristbands with urinary cotinine, a metabolite of nicotine, measured in the child's urine obtained on day 7. Children were recruited who were exposed to contaminants in tobacco smoke and/or vapor from electronic nicotine delivery systems (ENDS; commonly known as electronic cigarettes or EC) as well as children who lived in nonsmoking homes. Caregivers were interviewed to obtain reported measures of the child's exposure. Analysis was by liquid chromatography with triple quadrupole mass spectrometry and isotope dilution (LC-MS/MS). The nicotine detected in the wristbands worn for 2 days was highly correlated with urinary cotinine concentration (df = 29, r² = 0.741, p < 0.001), as was nicotine in wristbands worn for 7 days (df = 28, r² = 0.804, p < 0.001). The 2- and 7-day wristband nicotine amounts were also significantly correlated (df = 28, r² = 0.852, p < 0.001). Silicone wristbands may be a useful tool for epidemiological and intervention studies of tobacco product exposure in children.

Modifiable Predictors of Supported Employment Outcomes Among People With Severe Mental Illness

OBJECTIVE

Among people with severe mental illnesses, neuropsychological abilities may contribute to vocational outcomes, such as job attainment, job tenure, and wages earned. The current study aimed to determine the strongest neuropsychological and other modifiable predictors of work outcomes in 153 people with severe mental illness (schizophrenia, 38%; bipolar disorder, 24%; and major depression, 38%) who participated in a 2-year supported employment study.

METHODS

Assessments of neuropsychological performance, functional capacity, social skills, and psychiatric symptom severity were administered at baseline; work outcomes (job attainment, weeks worked, and wages earned) were collected weekly for 2 years.

RESULTS

Independent of education, diagnosis, and estimated intellectual functioning, more recent work history and less severe negative symptoms significantly predicted job attainment during the 2-year study. Among the 47% who obtained jobs, better global neuropsychological performance (i.e., lower global deficit score) was a significant predictor of greater weeks worked. Both global neuropsychological performance and more recent work history predicted higher wages earned.

CONCLUSIONS

Modifiable predictors of supported employment outcomes included cognitive functioning and negative symptom severity; thus, interventions to improve these factors may improve work outcomes and decrease the loss of productivity associated with severe mental illness.

Contribution of thirdhand smoke to overall tobacco smoke exposure in pediatric patients: study protocol

BACKGROUND

Thirdhand smoke (THS) is the persistent residue resulting from secondhand smoke (SHS) that accumulates in dust, objects, and on surfaces in homes where tobacco has been used, and is reemitted into air. Very little is known about the extent to which THS contributes to children's overall tobacco smoke exposure (OTS) levels, defined as their combined THS and SHS exposure. Even less is known about the effect of OTS and THS on children's health. This project will examine how different home smoking behaviors contribute to THS and OTS and if levels of THS are associated with respiratory illnesses in nonsmoking children.

METHODS

This project leverages the experimental design from an ongoing pediatric emergency department-based tobacco cessation trial of caregivers who smoke and their children (NIHR01HD083354). At baseline and follow-up, we will collect urine and handwipe samples from children and samples of dust and air from the homes of smokers who smoke indoors, have smoking bans or who have quit smoking. These samples will be analyzed to examine to what extent THS pollution at home contributes to OTS exposure over and above SHS and to what extent THS continues to persist and contribute to OTS in homes of smokers who have quit or have smoking bans. Targeted and nontargeted chemical analyses of home dust samples will explore which types of THS pollutants are present in homes. Electronic medical record review will examine if THS and OTS levels are associated with child respiratory illness. Additionally, a repository of child and environmental samples will be created.

DISCUSSION

The results of this study will be crucial to help close gaps in our understanding of the types, quantity, and clinical effects of OTS, THS exposure, and THS pollutants in a unique sample of tobacco smoke-exposed ill children and their homes. The potential impact of these findings is substantial, as currently the level of risk in OTS attributable to THS is unknown. This research has the potential to change how we protect children from OTS, by recognizing that SHS and THS exposure needs to be addressed separately and jointly as sources of pollution and exposure.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02531594 . Date of registration: August 24, 2015.

Medical staff contributions to thirdhand smoke contamination in a neonatal intensive care unit

INTRODUCTION

Non-smoking policies are strictly enforced in neonatal intensive care units (NICUs), which may still become contaminated by thirdhand smoke (THS), posing potential health risks to medically fragile infants. Study aims were to explore contamination routes by characterizing nicotine levels (THS proxy) found on the fingers of NICU medical staff and to assess finger-nicotine correlates.

METHODS

NICU medical staff were surveyed regarding smoking and electronic nicotine devices (ENDS) use/exposure, and household characteristics. Approximately 35% of staff were randomly selected for a finger-nicotine wipe. Three separate quantile regressions modeled percentiles associated with: presence of any finger nicotine, finger-nicotine levels above the median field blank level (i.e. 0.377 ng/wipe), and finger-nicotine levels two times the median blank.

RESULTS

The final sample size was 246 (n=260 approached; n=14 refusals). Over three-quarters (78.5%) reported some exposure to tobacco smoke or ENDS vapor/aerosols. After field-blank adjustments, the median nicotine level (ng/finger wipe) was 0.232 (IQR: 0.021–0.681) and 78.3% of medical staff had measurable finger-nicotine levels. Both being near smoking in friends’/family members’ homes and finger-surface area were related to elevated finger-nicotine levels (p<0.05) in the median blank model.

CONCLUSIONS

Almost four in five NICU staff had measurable finger nicotine, with finger surface area and frequency of reported exposure to tobacco smoke in friends’/family members’ homes emerging as important correlates. Future research will determine the impact of THS on NICU infants. Medical personnel working in a NICU should be cognizant of secondhand smoke and THS, particularly inside friends’/family members’ homes, to reduce potential NICU contamination and infant exposures.

Randomised controlled trial of real-time feedback and brief coaching to reduce indoor smoking

BACKGROUND

Previous secondhand smoke (SHS) reduction interventions have provided only delayed feedback on reported smoking behaviour, such as coaching, or presenting results from child cotinine assays or air particle counters.

DESIGN

This SHS reduction trial assigned families at random to brief coaching and continuous real-time feedback (intervention) or measurement-only (control) groups.

PARTICIPANTS

We enrolled 298 families with a resident tobacco smoker and a child under age 14.

INTERVENTION

We installed air particle monitors in all homes. For the intervention homes, immediate light and sound feedback was contingent on elevated indoor particle levels, and up to four coaching sessions used prompts and praise contingent on smoking outdoors. Mean intervention duration was 64 days.

MEASURES

The primary outcome was 'particle events' (PEs) which were patterns of air particle concentrations indicative of the occurrence of particle-generating behaviours such as smoking cigarettes or burning candles. Other measures included indoor air nicotine concentrations and participant reports of particle-generating behaviour.

RESULTS

PEs were significantly correlated with air nicotine levels (r=0.60) and reported indoor cigarette smoking (r=0.51). Interrupted time-series analyses showed an immediate intervention effect, with reduced PEs the day following intervention initiation. The trajectory of daily PEs over the intervention period declined significantly faster in intervention homes than in control homes. Pretest to post-test, air nicotine levels, cigarette smoking and e-cigarette use decreased more in intervention homes than in control homes.

CONCLUSIONS

Results suggest that real-time particle feedback and coaching contingencies reduced PEs generated by cigarette smoking and other sources.

TRIAL REGISTRATION NUMBER

NCT01634334; Post-results.

Nicotine on Children's Hands: Limited Protection of Smoking Bans and Initial Clinical Findings

Background:

Thirdhand smoke (THS) pollutants, such as nicotine, accumulate on the hands of children who live in homes with smokers and are exposed to secondhand smoke. Our objective was to examine whether levels of hand nicotine in exposed children are associated with demographics, environmental factors, and clinical findings.

Methods:

Participants were caregivers who smoke and children (mean age (SD) = 2.6 (3.7) years) who were part of an ongoing 2-group, randomized controlled trial of an emergency department–based tobacco cessation intervention (N = 104). The primary outcome measure was nicotine on the child’s hand. Caregivers reported demographics and smoking patterns; children’s medical records were abstracted for chief complaint, medical history, and diagnoses.

Results:

All children had detectable hand nicotine (geometric mean [GeoM] = 86.2 ng/wipe; range = 3.5-2, 190.4 ng/wipe). Children in the age group of 2 to 4 years old (GeoM = 185.6 ng/wipe) had higher levels than the children in the age groups of 0 to 1 (GeoM = 68.9 ng/wipe, P < .001), 5 to 9 (GeoM = 77.9 ng/wipe, P = .04), and 10 to 15 years old (GeoM = 74.2 ng/wipe, P = .048). Children whose caregivers smoked 6 to 14 (GeoM = 97.2 ng/wipe, P = .047) and 15 to 40 cigarettes/day (GeoM = 124.0 ng/wipe, P = .01) had higher levels than children whose caregivers smoked 1 to 5 cigarettes/day (GeoM = 59.7 ng/wipe). Children with 6 to 14 cigarettes/day (GeoM = 163.11 ng/wipe, P = .007) and 15 to 40 cigarettes/day (GeoM = 186.1, P = .003) smoked inside the home by all smokers had significantly higher levels than homes with 0 cigarettes (GeoM = 81.3 ng/wipe). Similar differences in hand nicotine levels were found for smoking frequency of all household members in any location. Children with complaints of cough/congestion (GeoM = 97.7 ng/wipe) had higher levels than those without cough/congestion (GeoM = 59.0 ng/wipe, P = .01).

Conclusions:

The high hand nicotine levels in children whose caregivers do not necessarily smoke indoor demonstrate that indoor smoking bans do not safeguard against THS exposure and the associations with increased home smoking activity indicate that hand wipes may be a noninvasive way to characterize children’s exposure. The findings of associated cough and congestion with higher THS levels need to be examined further.

Cotton pillows: A novel field method for assessment of thirdhand smoke pollution

Thirdhand smoke (THS) is the residue left behind by secondhand smoke (SHS) that accumulates in indoor environments. THS chemicals can persist long after smoking has ceased and can re-emit semivolatile compounds back into the air. Measuring tobacco smoke pollution in real-world field setting can be technically complex, expensive, and intrusive. This study placed pillows in homes of former smokers and examined how much nicotine adsorbed to them over a three-week period. Organic cotton pillows were placed in the homes of 8 former smokers following the first week after verified smoking cessation until the fourth week. For comparison, pillows were also placed in 4 homes of nonsmokers. Nicotine concentrations were determined in the pillow case, fabric, and cotton filling, using isotope-dilution liquid chromatography tandem mass spectrometry. Cotton pillows placed in homes of former smokers absorbed on average 21.5 μg of nicotine. Nicotine concentration per gram of material significantly differed between pillow components (p < 0.001) and was highest for the pillow case (257 ng/g), followed by the pillow fabric (97 ng/g), and the pillow filling (17 ng/g). Nicotine levels in pillows placed in nonsmokers' homes did not differ from laboratory blanks (p > 0.40), or between pillow components (p > 0.40). In the absence of any smoking activity, cotton pillows absorbed significant amounts of nicotine emitted from THS reservoirs in the homes of former smokers. Given the much higher concentrations of SHS in the homes of active smokers, fabrics found throughout the home of a smoker are likely to store a substantial mass of tobacco smoke toxicants. Cotton pillows present a novel method that could be of interest to researchers requiring robust and unobtrusive methods to examine tobacco smoke pollution in real-world field settings.

A framework for measurement and harmonization of pediatric multiple sclerosis etiologic research studies: The Pediatric MS Tool-Kit

Background:

While studying the etiology of multiple sclerosis (MS) in children has several methodological advantages over studying etiology in adults, studies are limited by small sample sizes.

Objective:

Using a rigorous methodological process, we developed the Pediatric MS Tool-Kit, a measurement framework that includes a minimal set of core variables to assess etiological risk factors.

Methods:

We solicited input from the International Pediatric MS Study Group to select three risk factors: environmental tobacco smoke (ETS) exposure, sun exposure, and vitamin D intake. To develop the Tool-Kit, we used a Delphi study involving a working group of epidemiologists, neurologists, and content experts from North America and Europe.

Results:

The Tool-Kit includes six core variables to measure ETS, six to measure sun exposure, and six to measure vitamin D intake. The Tool-Kit can be accessed online (www.maelstrom-research.org/mica/network/tool-kit).

Conclusion:

The goals of the Tool-Kit are to enhance exposure measurement in newly designed pediatric MS studies and comparability of results across studies, and in the longer term to facilitate harmonization of studies, a methodological approach that can be used to circumvent issues of small sample sizes. We believe the Tool-Kit will prove to be a valuable resource to guide pediatric MS researchers in developing study-specific questionnaire

Serum Cotinine and Hemoglobin A1c Among a National Sample of Adolescents Without Known Diabetes

Introduction

National data suggest tobacco smoke is positively associated with higher glycated hemoglobin (HbA1c) among adults. Our objective was to examine the association between serum cotinine and HbA1c among adolescents without known diabetes.

Methods

We assessed adolescents 12-19 years old (N = 11550) who participated in the 1999-2012 National Health and Nutrition Examination Survey. We applied sampling weights while performing multiple linear regression analyses.

Results

The prevalence of serum cotinine indicative of no tobacco smoke exposure (TSE, <0.05 ng/mL) was 43.2%, passive TSE (0.05-2.99 ng/mL) was 38.9%, and active TSE (>3 ng/mL) was 17.9% in our sample. Mean (± standard error) HbA1c in participants with no TSE was 5.16% (±0.01), passive TSE was 5.16% (±0.01), and active TSE was 5.14% (±0.01). No differences in HbA1c were found between TSE groups including sex, age, race/ethnicity, education, income, and physical activity or the fully adjusted model with waist circumference. We found cotinine × sex (p = .01) and cotinine × age (p = .02) interactions. There was an association between cotinine and HbA1c for males but not females. Within males, participants with cotinine ≥3 ng/mL (5.26 ± 0.02) had higher mean HbA1c than those with cotinine 0.05-2.99 ng/mL and <0.05 ng/mL (both 5.20 ± 0.01, p ≤ .02). The negative association between age and HbA1c was stronger for participants with cotinine ≥3 ng/mL than participants with cotinine <0.05 ng/mL.

Conclusion

No linear association was found between HbA1c and serum cotinine in adolescents overall after adjusting for potential confounders. Differences between TSE groups were found in males. Future research in adolescents should examine chronic TSE over time to examine the potential for development of type 2 diabetes.

Implications

TSE has been associated with increased risk for the development of type 2 diabetes among adults. It is unclear if this relationship holds in adolescents. We examined the association between serum cotinine and HbA1c in adolescents without known diabetes who completed the 1999-2012 National Health and Nutrition Examination Survey. Although no association was found between serum cotinine and HbA1c overall while controlling for potential confounding factors, we observed interaction effects that are indicative of TSE influencing HbA1c differentially by sex and age. Reducing TSE in adolescents should be a priority for future tobacco control efforts.

Effects of sleep on substance use in adolescents: a longitudinal perspective

Substance use (SU) and sleep problems appear interrelated, but few studies have examined the influence of adolescent sleep patterns on development of SU disorders. This study prospectively examined the influence of sleep habits on subsequent SU in youth who later transitioned into heavy drinking. At time 1 (T1), participants (n = 95) were substance-naive 12- to 14-year-olds. Path-analytic models examined whether the effects of T1 risk factors (familial SU disorder, inhibition control, and externalizing and internalizing traits) on time 3 (M = 19.8 years old) tobacco, alcohol, and cannabis were mediated by time 2 (M = 15.1 years old) sleep chronotype, daytime sleepiness, and erratic sleep/wake behaviors. Significant direct path effects of T1 risk factors and time 2 sleep behaviors on time 3 SU were found, Ps < 0.05. In models that examined the effect of each individual sleep behavior separately on SU, more erratic sleep/wake and greater daytime sleepiness predicted higher lifetime use events for all substances (Ps < 0.01). Higher evening chronotype tendencies predicted lower tobacco and higher alcohol and cannabis lifetime use events (Ps < 0.01). Erratic sleep/wake behaviors mediated the effect of inhibitory control on subsequent SU; less erratic sleep/wake behaviors predicted better inhibition control ( β̂= -0.20, P < 0.05). Early-mid adolescent psychiatric health and sleep behaviors prior to drinking onset predicted greater SU 5 years later. Participants were substance-naïve at baseline, allowing for the examination of temporal order in the relationship between sleep problems and alcohol use. Early adolescent sleep problems may be an important risk factor for SU in later life.

A Casino goes smoke free: a longitudinal study of secondhand and thirdhand smoke pollution and exposure

Background

Secondhand smoke (SHS) in US casinos is common, but little is known about the residue of tobacco smoke pollutants left behind in dust and on surfaces, commonly referred to as thirdhand smoke (THS). We examined SHS and THS pollution and exposure before and during a casino smoking ban and after smoking resumed.

Methods

A casino was visited nine times over a 15-month period to collect dust, surface and air samples in eight locations. Finger wipe and urine samples were collected from non-smoking confederates before and after a 4-hour casino visit. Samples were analysed for markers of SHS and THS pollution and exposure.

Results

Exceptionally high levels of THS were found in dust and on surfaces. Although the smoking ban led to immediate improvements in air quality, surface nicotine levels were unchanged and remained very high for the first month of the smoking ban. Surface nicotine decreased by 90% after 1 month (P<0.01), but nicotine and tobacco-specific nitrosamines in dust decreased more slowly, declining by 90% only after 3 months (P<0.01). Exposure was significantly reduced after the ban, but the benefits of the ban were reversed after smoking resumed.

Conclusions

Long-term smoking in a casino creates deep THS reservoirs that persist for months after a smoking ban. A complete smoking ban immediately improves air quality and significantly reduces exposure to SHS and THS. However, THS reservoirs contribute to continued low-level exposure to toxicants. To accelerate the effect of smoking bans, remediation efforts should address specific THS reservoirs, which may require intensive cleaning as well as replacement of carpets, furniture and building materials.

A relative bilingual advantage in switching with preparation: Nuanced explorations of the proposed association between bilingualism and task switching

Bilingual language switching may increase general switching efficiency, but the evidence on this question is mixed. We hypothesized that group differences in switching might be stronger at a long cue-target interval (CTI), which may better tap general switching abilities (Yehene & Meiran, 2007). Eighty Spanish-English bilinguals and 80 monolinguals completed a color-shape switching task, and an analogous language-switching task, varying CTI (short vs. long) in both tasks. With longer preparation time (long CTI), bilinguals exhibited significantly smaller task-switching costs than monolinguals, but only in the first half of trials. Group differences diminished with practice, though practice benefitted RTs on short CTI trials more than long, and bilinguals committed fewer errors with practice especially at short CTI. Groups did not differ in mixing costs; however, across CTIs and tasks, bilinguals and monolinguals alike, exhibited robust correlations between mixing costs, but not between switching costs. These results confirm an association between bilingualism and switching efficiency that may be magnified with manipulations that target general switching ability (or could reflect better ability to take advantage of preparation time). However, practice effects observed within experimental paradigms, and between task correlations in costs, may reflect cognitive mechanisms specific to laboratory tasks much more than associations with general switching ability and executive control mechanisms-for which more reliable and valid measures can hopefully be developed in future work. (PsycINFO Database Record

Hotel smoking policies and their implementation: a survey of California hotel managers

BACKGROUND

Most states in the U.S. permit hotels to allow smoking in some guest rooms, and only five (Indiana, Michigan, North Dakota, Vermont, and Wisconsin) require that all hotel and motel rooms be 100% smoke-free (State and local 100% smokefree hotel and motel guest room laws enacted as of July 3, 2017). Little is known, however, about how hotels' smoking policies have been implemented. This study examined hotels' smoking policies and their implementation.

METHODS

A telephone survey of a random sample of 383 California hotel managers was conducted.

RESULTS

Overall, 60.6% of hotels reported that smoking was prohibited in all guest rooms, and 4.7% reported that smoking was prohibited everywhere on their property. While California law permitted smoking in up to 65% of guest rooms, only 6.9% of rooms were reported as smoking-permitted. Over 90% of hotels had smoking rooms scattered among nonsmoking rooms, and about half of the smoking hotels reported that guests requesting either smoking or nonsmoking rooms were sometimes assigned to the other room type. When guests smoked in nonsmoking rooms fees could be substantial, but were often uncollected.

CONCLUSIONS

Hotel smoking policies and their implementation fall short of protecting nonsmoking guests and workers from exposure to secondhand and thirdhand smoke. Complete indoor smoking bans for all hotels are needed to close existing loopholes. Nonsmokers who wish to protect themselves from exposure to tobacco smoke should avoid hotels that permit smoking and instead stay in completely smoke-free hotels.

Earlier Alcohol Use Onset Predicts Poorer Neuropsychological Functioning in Young Adults

BACKGROUND

Neurodevelopment may be shaped by environmental factors such as alcohol intake. Over 20% of U.S. high school students begin drinking before age 14, and those who initiated drinking before age 14 are 4 times more likely to develop psychosocial, psychiatric, and substance use difficulties than those who began drinking after turning 20. Little is known, however, about how the age of alcohol use onset influences brain development.

METHODS

This study prospectively examined the effects of alcohol use onset age on neurocognitive functioning in healthy adolescent drinkers (N = 215). Youth were administered a neuropsychological battery before substance use initiation (M = 13.6 years, SD = 0.8) and on average 6.8 years later (M = 20.2 years, SD = 1.5). Hierarchical linear regressions examined if earlier ages of onset for first and regular (i.e., weekly) alcohol use adversely influenced neurocognition, above and beyond baseline neurocognition, substance use severity, and familial and social environment factors.

RESULTS

As hypothesized, an earlier age of first drinking onset (AFDO) predicted poorer performance in the domains of psychomotor speed and visual attention (ps<0.05, N = 215) and an earlier age of weekly drinking onset (AWDO) predicted poorer performances on tests of cognitive inhibition and working memory, controlling for baseline neuropsychological performance, drinking duration, and past-year marijuana use (ps<0.05, N = 127). No relationship between AFDO and AWDO was found with verbal learning and memory and visuospatial ability.

CONCLUSIONS

This is the first study to assess the association between age of adolescent drinking onset and neurocognitive performance using a comprehensive test battery. This study suggests that early onset of drinking increases risk for alcohol-related neurocognitive vulnerabilities and that initiation of any or weekly alcohol use at younger ages appears to be a risk factor for poorer subsequent neuropsychological functioning. Findings have important implications for public policies related to the legal drinking age and prevention programming. Further studies are needed to replicate these preliminary findings and better understand mediating processes and moderating conditions.

Preliminary evidence that high levels of nicotine on children's hands may contribute to overall tobacco smoke exposure

BACKGROUND

Dust and surfaces are important sources of lead and pesticide exposure in young children. The purpose of this pilot study was to investigate if third-hand smoke (THS) pollutants accumulate on the hands of children who live in environments where tobacco is used and if hand nicotine levels are associated with second-hand smoke (SHS), as measured by salivary cotinine.

METHODS

Participants were parents and children (n=25; age mean (SD)=5.4 (5.3) years) presenting to the emergency department with a potentially SHS-related illness. A convenience sample of participants were recruited at baseline from an ongoing two-group, randomised controlled trial of a SHS reduction and tobacco cessation intervention. Parents were current smokers; thus, all children were at risk of SHS and THS exposure to varying extents. Primary outcome measures, which were assessed in child participants only, were hand nicotine and salivary cotinine. Parents reported sociodemographics and smoking patterns; children's medical records were abstracted for chief complaint, medical history and discharge diagnosis.

RESULTS

All children had detectable hand nicotine (range=18.3-690.9 ng/wipe). All but one had detectable cotinine (range=1.2-28.8 ng/mL). Multiple linear regression results showed a significant positive association between hand nicotine and cotinine (p=0.009; semipartial r²=0.24), independent of child age.

DISCUSSION

The higher-than-expected nicotine levels and significant association with cotinine indicate that THS may play a role in the overall exposure of young children to tobacco smoke toxicants and that hand wipes could be a useful marker of overall tobacco smoke pollution and a proxy for exposure.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT02531594.

Thirdhand Smoke: New Evidence, Challenges, and Future Directions

Thirdhand smoke (THS) is the contamination that persists after secondhand tobacco smoke has been emitted into air. It refers to the tobacco-related gases and particles that become embedded in materials, such as the carpet, walls, furniture, blankets, and toys. THS is not strictly smoke, but chemicals that adhere to surfaces from which they can be released back into the air, undergo chemical transformations and/or accumulate. Currently, the hazards of THS are not as well documented as the hazards of secondhand smoke (SHS). In this Perspective, we describe the distribution and chemical changes that occur as SHS is transformed into THS, studies of environmental contamination by THS, human exposure studies, toxicology studies using animal models and in vitro systems, possible approaches for avoiding exposure, remediation of THS contamination, and priorities for further research.

When smokers quit: exposure to nicotine and carcinogens persists from thirdhand smoke pollution

BACKGROUND

Over a 6-month period, we examined tobacco smoke pollutants (also known as thirdhand smoke, THS) that remained in the homes of former smokers and the exposure to these pollutants.

METHODS

90 smokers completed study measures at baseline (BL). Measures were repeated among verified quitters 1 week (W1), 1 month (M1), 3 months (M3) and 6 months (M6) following cessation. Measures were analysed for THS pollutants on household surfaces, fingers and in dust (ie, nicotine, tobacco-specific nitrosamines) and for urinary markers of exposure (ie, cotinine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL)).

RESULTS

We observed significant short-term reduction of nicotine on surfaces (BL: 22.2 μg/m², W1: 10.8 μg/m²) and on fingers of non-smoking residents (BL: 29.1 ng/wipe, W1: 9.1 ng/wipe) without further significant changes. Concentrations of nicotine and nicotine-derived nitrosamine ketone (NNK) in dust did not change and remained near BL levels after cessation. Dust nicotine and NNK loadings significantly increased immediately following cessation (nicotine BL: 5.0 μg/m², W1: 9.3 μg/m²; NNK BL: 11.6 ng/m², W1: 36.3 ng/m²) before returning to and remaining at near BL levels. Cotinine and NNAL showed significant initial declines (cotinine BL: 4.6 ng/mL, W1: 1.3 ng/mL; NNAL BL: 10.0 pg/mL, W1: 4.2 pg/mL) without further significant changes.

CONCLUSIONS

Homes of smokers remained polluted with THS for up to 6 months after cessation. Residents continued to be exposed to THS toxicants that accumulated in settled house dust and on surfaces before smoking cessation. Further research is needed to better understand the consequences of continued THS exposure after cessation and the efforts necessary to remove THS.