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

Thirdhand Smoke Knowledge, Beliefs and Behaviors among Parents and Families: A Systematic Review

Families play a primary role in protecting children. Thirdhand smoke (THS) is an underestimated public health issue, and health effects correlated to its exposition are emerging. The aim of this systematic review was to analyze papers focusing on knowledge, beliefs, and behaviors regarding THS among parents, families, and caregivers, published until May 2022 on MEDLINE, CINAHL, EMBASE, and the Cochrane Library. Critical appraisal of the included studies was conducted by two independent reviewers using the Joanna Briggs Institute Critical Appraisal tool. Out of the 97 articles, 8 were included in this review (two from the USA, one from Europe, and five from Asia). Although there were no restrictions on the date of publication, all the articles were published in the last 10 years, underlining that THS is an emerging concept. They were characterized by relevant heterogeneity in the study design and assessment tools. The results showed that percentages of parents who believed that THS is harmful ranged from 42.4% to 91%, but parental awareness was not always associated with the adoption of a home- and car-smoking ban or healthy behaviors. Further research is needed to understand the resistance and problems faced by parents who are aware of THS risks but unable to improve good practices.

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.

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.

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.