Passive exposure to electronic cigarette aerosol in pregnancy: A case study of a family.

BACKGROUND: Passive exposure to the aerosols of electronic cigarettes (e-cigarettes) has been little studied. We assessed this exposure in late pregnancy in a woman and her 3-year-old child, exposed through e-cigarette use by another household member. METHODS: This prospective longitudinal case study involved a family unit consisting of an e-cigarette user, a pregnant woman who delivered an infant during the study, and the couple's older 3-year-old son. At 31, 36, and 40 weeks of the pregnancy, we measured biomarkers (nicotine metabolites, tobacco-specific nitrosamines, propanediols, glycerol, and metals) in the urine and hair of all three participants and in the saliva of the adults, in cord blood at delivery, and in the breast milk at the postpartum period. RESULTS: Samples from the e-cigarette user showed quantifiable concentrations of all analytes assessed (maximum urinary cotinine concentration, 4.9 ng/mL). Among samples taken from the mother, nicotine and its metabolites were found mainly in urine and also in saliva and hair, but not in cord blood. During the postpartum period, we found cotinine concentrations of 2.2 ng/mL in the mother's urine and 0.22 ng/mL in breast milk; 1,2-propanediol was generally detected in urine and saliva, but not in cord blood or breast milk. The maximum urinary cotinine concentration in the 3-year-old child was 2.6 ng/mL and propanediols also were detected in his urine. Nitrosamines were not detected in samples taken from the mother or the 3-year-old. Metals found in the refill liquid were detected at low levels in both the mother and the 3-year-old. CONCLUSIONS: We detected low but not negligible concentrations of e-cigarette-related analytes (including cord blood and breast milk) in an exposed pregnant non-user and in a 3-year-old child also living in the home. Passive exposure to e-cigarette aerosols cannot be disregarded and should be assessed in larger observational studies.

Determination of soluble angiotensin-converting enzyme 2 in saliva samples and its association with nicotine.

INTRODUCTION: The Angiotensin-Converting Enzyme 2 (ACE2) is the main receptor of the SARS-CoV-2. There is contradictory evidence on how the exposure to nicotine may module the concentration of soluble ACE2 (sACE2). The aim of this study was to assess the association between nicotine and sACE2 concentrations in saliva samples. METHODS: Pooled analysis performed with data retrieved from two studies (n = 634 and n = 302). Geometric mean (GM) concentrations of sACE2, both total and relative to the total amount of protein in the sample, were compared according to sociodemographic variables and variables associated to nicotine. Multivariable linear regression models were fitted to explore the associations of sACE2 with nicotine adjusting for sex, age and body mass index. Spearman's rank-correlation coefficients were estimated between the concentrations of nicotine and cotinine, and pack-years, the concentration of relative sACE2 and the isoforms of sACE2. RESULTS: We observed a significant increase of 0.108‰ and 0.087 ng/µl in the relative and absolute salivary sACE2 GM concentrations, respectively, between the lowest and highest nicotine levels. Similar results were observed for cotinine. These associations did not change in the multivariable linear models. There was a low correlation of nicotine and cotinine concentration with the concentration of relative salivary sACE2 (rs = 0.153 and rs = 0.132, respectively), pack-years (rs = 0.222 and rs = 0.235, respectively) and with the concentration of isoform 40 KDa (rs = 0.193 and rs = 0.140, respectively). CONCLUSION: Salivary nicotine concentration seems to be limitedly associated with the concentration of sACE2.

Secondhand Tobacco Smoke and Functional Impairments in Older Adults Living in the Community.

BACKGROUND/AIM: There has been no comprehensive examination of the potential association of SHS with broad functional limitation assessment in older adults, where functional limitations are burdensome and challenging. METHODS: We examined 2258 community-dwelling non-smoking older adults from the Seniors-Enrica-2-cohort. At baseline (2017) and follow-up (2019) grip strength was measured with a Jamar dynamometer, lower-extremity performance with the Short Physical Performance Battery (SPPB), overall physical function using the physical component summary (PCS) of the Spanish version of the SF-12, frailty with a Deficits Accumulation Index (DAI), and mobility limitations with the Rosow-Breslau scale. Baseline exposure to SHS was assessed by serum cotinine, and past exposure was self-reported. Cross-sectional analyses were performed using linear and logistic regression models, whereas functional performance changes were examined using repeated measures models with robust SE estimates. RESULTS: Overall, the median (IQR) serum cotinine concentration was 0.079 (0.035-0.175) ng/ml, with 20 participants presenting concentrations ≥3 ng/ml. Compared to the unexposed, fully-adjusted models showed that the highest exposure group (≥0.239 ng/ml) presented lower grip strength (mean difference: -1.05 kg; 95% CI = -1.80, -0.31) and higher DAI scores (1.52; 95% CI = 0.38, 2.66) at baseline. Similarly, in models of self-reported past exposure, never-smokers who had lived with ≥2 smokers or been exposed to higher SHS cumulative doses showed lower baseline SPPB values, higher DAI scores, and higher prevalence of mobility limitations. In prospective analyses, those in the highest quartile of baseline cotinine presented harmful SPPB [-0.24 (-0.46, -0.02)] and DAI [1.28 (0.00, 2.55)] changes, and higher risk of mobility limitations [hazard ratio: 1.64; 95% CI = 1.01, 2.68] than the unexposed. CONCLUSIONS: SHS exposure over the life-course and during old age may accelerate functional decline. IMPLICATIONS: This manuscript provides a comprehensive examination of the relationship between secondhand smoke exposure and a broad range of functional limitations in older adults. Results show that: (i) non-smokers who had been exposed to higher cumulative doses of SHS in adulthood show worse physical function than non-exposed. (ii) Exposure to SHS during old age, as measured with cotinine concentrations, is associated with accelerated short-term functional declines. (iii) The effects of SHS are stronger among older adults with chronic morbidities. (iv) Results suggest that more efforts are needed to protect older adults from passive smoking, especially to those with chronic conditions because of their potential greater vulnerability to the effects of SHS.

Objectively measured secondhand tobacco smoke and cognitive impairment in disability-free older adults.

Previous studies have suggested that exposure to secondhand smoke (SHS) may be associated with greater risk of cognitive impairment. However, no longitudinal study has examined the association of serum cotinine (as objective measure of SHS exposure) and cognitive function in older adults. We used data from 2087 non-smoking adults aged≥65 years participating in the ENRICA-2 cohort and free from limitations in Instrumental Activities of Daily Living. Cognitive function was assessed through the Mini-Mental State Examination (MMSE), the Digit Span Backwards subtest (DSBT), the Luria's motor series subtest from the Frontal Assessment Battery, the Trail Making Test A (TMT-A), the Free and Cued Selective Reminding Test (FCSRT), and the Categorical Verbal Fluency Test (CFT) of the 7 min test. Cross-sectional analyses were performed using multivariable logistic and ordered logistic models, while analyses on changes in cognition over time used multivariable repeated-measures mixed-effects models. Compared to the unexposed, those in the highest exposure group (≥0.161 ng/ml) were more likely to have cognitive impairment (MMSE<24) (odds ratio [OR]:1.64; 95% confidence interval [CI]:1.04-2.60) and lower DSBT scores (OR:1.25; 95%CI:1.00-1.57), as well as a non-significant higher odds of a lower score in the Luria test (OR:1.23; 95%CI:0.92-1.64) or episodic memory impairment (FCSRT<12, OR:1.38; 95%CI:0.90-2.11). In longitudinal analyses, those with baseline cotinine ≥0.161 ng/ml showed an increased risk of cognitive impairment (MMSE<24,OR:2.23; 95%CI:1.14-4.33; p-trend across cotinine categories = 0.028) and decreased DSBT (OR:1.23; 95%CI:1.01-1.51; p-trend across cotinine categories = 0.046). Findings show an increased risk of global cognitive impairment and declines in working memory performance in older adults exposed to SHS. More efforts are needed to protect older adults from SHS in areas not covered by smoke-free legislation.

Third-hand exposure at homes: Assessment using salivary cotinine.

BACKGROUND/OBJECTIVES: While exposure to secondhand smoke (SHS) is a well-established problem, exposure to third-hand smoke (THS) is scanty known and needs to be studied. The objective of this work is to characterize salivary cotinine concentrations among people who self-reported exposure to SHS and THS at home. METHODS: Cross-sectional study of a representative sample (n = 736) of the adult population (≥16 years) from the city of Barcelona carried out in 2013-2014. A questionnaire on tobacco use and passive exposure was administered, and a saliva sample was collected for cotinine determination. For this study, the information of the non-smoker participants who provided saliva sample (n = 519) was used. The geometric means (GM) and geometric standard deviations (GSD) of the cotinine concentration were compared according to the type of self-reported exposure at home: (1) Not exposed to SHS or THS; (2) Exposed to SHS and THS; and (3) Only exposed to THS. We used log-linear models to compare the cotinine concentration of each exposed group with respect to the unexposed group, adjusting for sex, age, educational level, and tobacco exposure in other settings. RESULTS: The GM of the salivary cotinine concentration was 0.34 ng/ml (GSD = 0.16) among individuals reporting SHS and THS exposure, 0.22 ng/ml (GSD = 0.15) among those reporting only THS exposure and 0.11 ng/ml (GSD = 0.04) among those who declared not to be exposed to SHS nor THS (p-value for trend <0.001). The regression model showed a statistically significant increase in cotinine concentration among those exposed to SHS and THS (188% higher, 95% CI: 153%; 223%), and only exposed to THS (106% higher, IC95. %: 74.5%; 137.0%) when comparing with the unexposed group. No statistically significant differences in cotinine concentration were observed between those exposed to SHS and THS compared to the THS group (-25.8%, 95% CI: -69.5%; 17.9%). CONCLUSIONS/RECOMMENDATIONS: People exposed to third-hand smoke at home had quantifiable cotinine levels in saliva. No differences in cotinine levels were found between those exposed to second-hand and third-hand smoke at home. The reduction of exposure to third-hand smoke at home should be put into the agenda of tobacco control.

Environmental and individual exposure to secondhand aerosol of electronic cigarettes in confined spaces: Results from the TackSHS Project†.

Secondhand electronic cigarette (e-cigarette) aerosol (SHA) might impair indoor air quality and expose bystanders. This study aims to investigate exposure to SHA in controlled conditions of enclosed settings simulating real-world scenario. An experiment was performed in a car and in a room, in which SHA was generated during a 30-minute ad libitum use of an e-cigarette. The experiment was replicated on five consecutive days in each setting. We measured PM2.5 , airborne nicotine concentrations, and biomarkers of exposure to SHA, such as nicotine metabolites, tobacco-specific nitrosamines, propylene glycol, and glycerol in bystanders' saliva samples before, during, and after the exposure period. Self-reported health symptoms related to exposure to SHA were also recorded. The results showed that the highest median PM2.5 concentration was recorded during the exposure period, being 21 µg/m3 in the room setting and 16 µg/m3 in the car setting-about twofold increase compared to the baseline. Most concentrations of the airborne nicotine and all biomarkers were below the limit of quantification in both settings. Bystanders in both settings experienced some short-term irritation symptoms, expressed as dry throat, nose, eyes, and phlegm. In conclusion, short-term use of an e-cigarette in confined spaces increased indoor PM2.5 level and caused some irritation symptoms in bystanders.

Comparison of TSNAs concentration in saliva according to type of tobacco smoked.

OBJECTIVE: To compare tobacco-specific nitrosamines (TSNAs) measured in saliva according to different types of tobacco smoked in a sample of smokers of the city of Barcelona (Spain). METHODS: We used data from a cross-sectional study of a sample of the adult smoking population of Barcelona, Spain in 2013-2014 (n = 165). We classified smokers in five groups according to the type of tobacco smoked: a) manufactured cigarettes only, b) roll-your-own (RYO) cigarettes only, c) dual smokers (both manufactured and RYO cigarettes), d) manufactured plus other types of tobacco products different from RYO and e) other types of tobacco products different from manufactured and RYO cigarettes. We calculated the geometric mean (GM) and geometric standard deviation (GSD) of TSNAs concentration in saliva (pg/mL), including N'-nitroaonornicotine (NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) according to the five tobacco groups. We also described all TSNAs concentration in each tobacco group stratified by the number of cigarettes smoked per day. RESULTS: Smokers from the RYO cigarette group had higher TSNAs concentration than smokers from the manufactured cigarette group: 13 pg/mL vs 4.9 pg/mL of NNN, 1.9 pg/mL vs 1.7 pg/mL in NNK and 1.1 pg/mL vs 0.9 pg/mL of NNAL. There were significant differences in NNN concentrations between smokers of RYO vs manufactured cigarettes. The higher the number of cigarettes smoked, the higher the TSNAs concentrations. After adjusted by number of cigarettes smoked, there were not statistically significant differences in TSNAs between RYO and manufactured cigarettes. CONCLUSIONS: Our data shows that RYO cigarette is at least as hazardous as manufactured cigarettes. Regulating RYO tobacco prices could be an effective strategy to control tobacco use.

Manufactured and roll-your-own cigarettes: A changing pattern of smoking in Barcelona, Spain.

AIMS: The objectives of the present study were to describe smoking prevalence and compare the smoking attributes of adult smokers according to the type of tobacco product consumed. METHODS: Repeated cross-sectional surveys (2004-2005 and 2011-2012) of a representative sample of the adult (≥16 years) population in Barcelona, Spain, were used to assess self-reported tobacco consumption, smoking attributes, and salivary cotinine concentration. The survey conducted in 2004-2005 included information on 1245 subjects and the survey in 2011-2012 on 1307 individuals. RESULTS: Smoking prevalence decreased over the study period (from 26.6% to 24.1% in self-reported daily smokers). The prevalence of daily smokers who reported the use of manufactured cigarettes declined from 23.7% in 2004-2005 to 17.3% in 2011-2012. The prevalence of roll-your-own cigarette users increased from 0.4% to 3.7%. According to data obtained in 2011-2012, the proportion of self-reported roll-your-own cigarette users was higher among men (19.8% vs. 9.5% of women), participants aged 16-44 years (22.9% vs. 5.8% of participants aged 45-65 years and 4.0% of participants aged ≥65 years), and participants with secondary and university education (17.7% and 18.5% vs. 7.9% of participants with less than primary and primary education). We did not observe differences in cotinine concentrations according to the type of tobacco product consumed. CONCLUSIONS: Systematic collection of data on smoking prevalence and smoker attributes from representative samples of the population is necessary for policymakers to develop efficient tobacco control interventions. Considering the increase of roll-your-own cigarette users and the unclear health consequences of their use, policymakers should aim to implement tax policies to equalize the prices of different types of tobacco products.

Assessment of tobacco specific nitrosamines (TSNAs) in oral fluid as biomarkers of cancer risk: A population-based study.

BACKGROUND: Smoke-free laws are expected to reduce smoking habits and exposure to secondhand smoke. The objective of this study was the measurement of tobacco specific carcinogens (TSNAs) in oral fluid to assess the most suitable biomarker of cancer risk associated with tobacco smoke. METHODS: TSNAs, N'-nitrosonornicotine (NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), as well as nicotine and cotinine were measured in oral fluid samples from 166 smokers and 532 non-smokers of the adult population of Barcelona, Spain. A simple method with an alkaline single liquid-liquid extraction with dichloromethane/isopropanol was used and lower limits of quantification for cotinine, NNN, NNK and NNAL were set at 0.10ng/mL, 1.0, 2.0 and 0.50pg/mL respectively. The NNN/cotinine ratio was also calculated. RESULTS: NNN was the most abundant TSNA present in oral fluid with a significant difference between smokers and non-smokers (mean concentrations of 118 and 5.3pg/mL, respectively, p<0.001). NNK and NNAL were detectable in fewer samples. NNN and cotinine concentrations had a moderate correlation within both groups (Spearman's rank correlation coefficient of 0.312, p<0.001 in smokers and 0.279, p=0.022 in non-smokers). NNN/cotinine ratio was significantly higher (p<0.001) in non-smokers than in smokers, in line with equivalent findings for the NNAL/cotinine ratio in urine. CONCLUSIONS: TSNAs are detectable in oral fluid of smokers and non-smokers. NNN is the most abundant, in line with its association with esophageal and oral cavity cancers. The NNN/cotinine ratio confirms the relative NNN increase in second hand smoke. Findings provide a new oral fluid biomarker of cancer risk associated with exposure to tobacco smoke.

High-throughput wide dynamic range procedure for the simultaneous quantification of nicotine and cotinine in multiple biological matrices using hydrophilic interaction liquid chromatography-tandem mass spectrometry.

A straightforward, high-throughput method was developed and fully validated for the simultaneous determination of the specific tobacco biomarkers nicotine and its main metabolite cotinine in a wide dynamic range and supporting the most common human biological matrices (urine, oral fluid and hair). Sample preparation was performed inside the very HPLC injection vials by pipetting 0.5 mL of the liquid samples, deuterated internal standards in alkaline solution and dichloromethane as extraction solvent. Solid samples (i.e. around 10 mg hair) were first submitted to alkaline digestion in the HPLC vials and processed accordingly. The organic phase (reached through the upper aqueous layer) was directly injected without further treatment. Instrumental analysis was performed using hydrophilic interaction (HILIC) ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Total chromatographic time was 2 min. The method covers a wide dynamic range making it fit-for-purpose for the analysis of samples covering entire populations, irrespective of the level of exposure or tobacco use. Calibration curves (r (2) > 0.995) covered the range 1-2000 ng/mL (or 0.05-100 ng/mg hair) for nicotine and 0.1-2000 ng/mL (or 0.005-100 ng/mg hair) for cotinine. Within-run and between-run precision and accuracy were typically below 10 %, and always below 20 % at the lower limit of quantification. The method was successfully applied to the analysis of samples from different projects involving multiple matrices.

Cigarettes vs. e-cigarettes: Passive exposure at home measured by means of airborne marker and biomarkers.

BACKGROUND: There is scarce evidence about passive exposure to the vapour released or exhaled from electronic cigarettes (e-cigarettes) under real conditions. The aim of this study is to characterise passive exposure to nicotine from e-cigarettes' vapour and conventional cigarettes' smoke at home among non-smokers under real-use conditions. METHODS: We conducted an observational study with 54 non-smoker volunteers from different homes: 25 living at home with conventional smokers, 5 living with nicotine e-cigarette users, and 24 from control homes (not using conventional cigarettes neither e-cigarettes). We measured airborne nicotine at home and biomarkers (cotinine in saliva and urine). We calculated geometric mean (GM) and geometric standard deviations (GSD). We also performed ANOVA and Student's t tests for the log-transformed data. We used Bonferroni-corrected t-tests to control the family error rate for multiple comparisons at 5%. RESULTS: The GMs of airborne nicotine were 0.74 µg/m(3) (GSD=4.05) in the smokers' homes, 0.13 µg/m(3) (GSD=2.4) in the e-cigarettes users' homes, and 0.02 µg/m(3) (GSD=3.51) in the control homes. The GMs of salivary cotinine were 0.38 ng/ml (GSD=2.34) in the smokers' homes, 0.19 ng/ml (GSD=2.17) in the e-cigarettes users' homes, and 0.07 ng/ml (GSD=1.79) in the control homes. Salivary cotinine concentrations of the non-smokers exposed to e-cigarette's vapour at home (all exposed ≥ 2 h/day) were statistically significant different that those found in non-smokers exposed to second-hand smoke ≥ 2 h/day and in non-smokers from control homes. CONCLUSIONS: The airborne markers were statistically higher in conventional cigarette homes than in e-cigarettes homes (5.7 times higher). However, concentrations of both biomarkers among non-smokers exposed to conventional cigarettes and e-cigarettes' vapour were statistically similar (only 2 and 1.4 times higher, respectively). The levels of airborne nicotine and cotinine concentrations in the homes with e-cigarette users were higher than control homes (differences statistically significant). Our results show that non-smokers passively exposed to e-cigarettes absorb nicotine.

Secondhand smoke exposure at home: assessment by biomarkers and airborne markers.

OBJECTIVE: We assessed and characterized the relationship among biomarkers of secondhand smoke (SHS) exposure in non-smokers according to their exposure at home as measured by airborne markers. METHODS: We conducted an observational study on exposure to SHS at home using airborne markers (nicotine and benzene) and biomarkers from the non-smokers living in these homes. We selected 49 non-smoking volunteers from different homes: 25 non-smokers living with at least one smoker and 24 non-smokers living in smoke-free homes. We installed two passive devices to measure nicotine and benzene concentrations in the main room of the house (i.e., the living room). One week later, the researcher returned to the volunteer's home to collect the two devices, obtain saliva and urine samples, and administer a SHS questionnaire. RESULTS: Salivary and urinary cotinine concentrations highly correlated with air nicotine concentrations measured at the volunteers'homes (rsp=0.738 and rsp=0.679, respectively). The concentrations of airborne markers of SHS and biomarkers in non-smokers increased with increasing self-reported intensity and duration of SHS exposure at home during the previous week (p<0.05). The multivariable regression model showed a significant association with nicotine in air at home (ß=0.126, p=0.002 for saliva and ß=0.115, p=0.010 for urine). CONCLUSIONS: Our findings suggest that, even in countries with comprehensive smoke-free legislation, exposure to SHS at home continues to be the main source of exposure for non-smokers who live in non-smoke-free homes. Therefore, public health policies should promote smoke-free homes.

Variation in Nicotine Metabolization According to Biological Factors and Type of Nicotine Consumer.

This study aims to describe the nicotine metabolite ratio among tobacco smokers and electronic cigarette (e-cigarette) users and nonusers. We analyzed pooled data from a longitudinal and a cross-sectional study of the adult population from the city of Barcelona. The final sample included information on 166 smokers, 164 e-cigarettes users with nicotine, 41 e-cigarette users without nicotine, 95 dual users (users of both products), and 508 nonusers. We used log-linear models to control for the potential confounding effect of the daily number of cigarettes smoked. Salivary nicotine metabolic rate assessment included the rate of nicotine metabolism (cotinine/nicotine) and the nicotine metabolite ratio (trans-3'-hydroxycotinine/cotinine). Exclusive users of e-cigarette without nicotine have the lowest rate of nicotine metabolism (Geometric mean: 0.08, p-values < 0.001) while cigarette smokers have the highest (Geometric mean: 2.08, p-values < 0.001). Nonusers have lower nicotine metabolic rate than cigarette smokers (Geometric means: 0.23 vs. 0.18, p-value < 0.05). Younger individuals (18−44 years) have a higher rate of nicotine metabolism than older individuals (45−64 years and 65−89) (Geometric means: 0.53 vs. 0.42 and 0.31, respectively, p-values < 0.01) and individuals with lower body mass index (21−25 kg/m2) have a higher rate of nicotine metabolism than the rest (26−30 kg/m2 and 31−60 kg/m2) (Geometric means: 0.52 vs. 0.35 and 0.36, respectively-values < 0.01). Nicotine metabolic rates are useful biomarkers when reporting smoking status and biological differences between individuals.

Specific biomarker comparison in current smokers, e-cigarette users, and non-smokers.

INTRODUCTION: This study aims to address the existing gap in the literature, while adding evidence, by comparing tobacco-specific biomarkers (cotinine and nitrosamines: NNK, NNAL, NNN), and other biomarkers of e-cigarette use (humectants: glycerol, 1,2-PD, 1,3-PD) according to five study groups. METHODS: A pooling analysis including two different studies was conducted. In both analyses, we took saliva samples from smokers (n = 409) and non-smokers (n = 154), dual tobacco and e-cig users (n = 92), exclusive e-cig user with nicotine (n = 158), and exclusive e-cig users without nicotine (n = 38). We analyzed and compared the geometric means (GM) and geometric standard deviations (GSD) of the concentration of tobacco-specific biomarkers, and e-cigarette biomarkers among groups. We used log-linear models adjusted for sex and age to model the change percentage and their 95% confidence intervals. RESULTS: Cotinine was significantly higher in nicotine consumers and in e-cigarette users without nicotine when compared to non-smokers. TSNAs were generally significantly lower in non-smokers and higher in nicotine consumers. NNN and NNAL were lower in e-cigarette users with nicotine comparted to smokers, and NNN was higher in e-cigarette users without nicotine when compared to non-smokers. No differences were found in humectant biomarkers between e-cigarette groups. CONCLUSIONS: Although there was a reduction in TSNAs in e-cigarette exclusive users compared to smokers, and a reduction of cotinine concentrations in e-cigarette exclusive users without nicotine compared to smokers, there are still high levels of these biomarkers when compared to non-smokers, which may be a clue towards the harmful effect of e-cigarettes.

Exposure to secondhand aerosol from electronic cigarettes at homes: A real-life study in four European countries.

Electronic cigarette (e-cigarette) use emits potentially hazardous compounds and deteriorates indoor air quality. Home is a place where e-cigarettes may frequently be used amid its increasing prohibition in public places. This study assessed the real-life scenario of bystanders' exposure to secondhand e-cigarette aerosol (SHA) at home. A one-week observational study was conducted within the TackSHS project in four countries (Greece, Italy, Spain, and the United Kingdom) in 2019 including: 1) homes of e-cigarette users living together with a non-user/non-smoker; and 2) control homes with no smokers nor e-cigarette users. Indoor airborne nicotine, PM2.5, and PM1.0 concentrations were measured as environmental markers of SHA. Biomarkers, including nicotine and its metabolites, tobacco-specific nitrosamines, propanediol, glycerol, and metals were measured in participants' saliva and urine samples. E-cigarette use characteristics, such as e-cigarette refill liquid's nicotine concentration, e-cigarette type, place of e-cigarette use at home, and frequency of ventilation, were also collected. A total of 29 e-cigarette users' homes and 21 control homes were included. The results showed that the seven-day concentrations of airborne nicotine were quantifiable in 21 (72.4 %) out of 29 e-cigarette users' homes; overall, they were quite low (geometric mean: 0.01 µg/m3; 95 % CI: 0.01-0.02 µg/m3) and were all below the limit of quantification in control homes. Seven-day concentrations of PM2.5 and PM1.0 in e-cigarette and control homes were similar. Airborne nicotine and PM concentrations did not differ according to different e-cigarette use characteristics. Non-users residing with e-cigarette users had low but significantly higher levels of cotinine, 3'-OH-cotinine and 1,2-propanediol in saliva, and cobalt in urine than non-users living in control homes. In conclusion, e-cigarette use at home created bystanders' exposure to SHA regardless of the e-cigarette use characteristics. Further studies are warranted to assess the implications of SHA exposure for smoke-free policy.

Changes in the salivary cotinine cut-offs to discriminate smokers and non-smokers before and after Spanish smoke-free legislation.

INTRODUCTION: High levels of cotinine in non-smokers indicate passive exposure to tobacco smoke. This study aims to evaluate variations in salivary cotinine cut-offs to discriminate smokers and non-smokers before and after the implementation of smoke-free legislation (Law 28/2005 and Law 42/2010) in a sample of the adult population of Barcelona, Spain. METHODS: This longitudinal study analyzes salivary cotinine samples and self-reported information from a representative sample (n = 676) of the adult population from Barcelona before and after the approval of smoke-free legislation. We calculated the receiver operating characteristic (ROC) curves, to obtain optimal cotinine cut-off points to discriminate between smokers and non-smokers overall, by sex and age, and their corresponding sensitivity, specificity, and area under the curve. We used linear mixed-effects models, with individuals as random effects, to model the percentage change of cotinine concentration before and after the implementation of both laws. RESULTS: The mean salivary cotinine concentration was significantly lower post-2010 law (-85.8%, p < 0.001). The ROC curves determined that the optimal cotinine cut-off points for discriminating non-smokers and smokers were 10.8 ng/mL (pre-2005 law) and 5.6 ng/mL (post-2010 law), with a post-2010 law sensitivity of 92.6%, specificity of 98.4%, and an area under the curve of 97.0%. The post-2010 law cotinine cut-off points were 5.6 ng/mL for males and 1.9 ng/mL for females. CONCLUSION: The implementation of Spanish smoke-free legislation was effective in reducing secondhand smoke exposure and, therefore, also in reducing the cut-off point for salivary cotinine concentration. This value should be used to better assess tobacco smoke exposure in this population.

Association between biomarkers of tobacco consumption and lung cancer risk among daily smokers.

BACKGROUND: Biomarkers of tobacco consumption may play a role in the lung cancer risk assessment. However, the role of salivary biomarkers has not been well studied. The aim of this study is to assess the use of salivary biomarkers of tobacco consumption as lung cancer screening criterion. RESEARCH DESIGN AND METHODS: Data came from the Determinants of cotinine phase 3 project (Barcelona, 2013-2014). We compared the concentrations of TSNAs, including NNAL, NNN and NNK, and cotinine, in saliva samples of 142 daily smokers from the general population according to their risk of lung cancer. High risk of lung cancer was defined as per the inclusion criteria in the US National Lung Screening Trial (NLST) and in the Dutch-Belgian lung cancer screening trial (NELSON). RESULTS: Among daily smokers accomplishing the age criterion for lung cancer screening, salivary concentrations of cotinine, NNAL and NNK adjusted for sex were significantly higher (p-value < 0.05) in daily smokers at high risk of lung cancer compared to smokers not at high risk according to both NELSON and NLST criteria. CONCLUSIONS: Saliva concentrations of cotinine, NNAL and NNK may be used as additional criteria for lung cancer screening. Further research on this topic is guaranteed.

Passive smoking in babies: the BIBE study (Brief Intervention in babies. Effectiveness).

BACKGROUND: There is evidence that exposure to passive smoking in general, and in babies in particular, is an important cause of morbimortality. Passive smoking is related to an increased risk of pediatric diseases such as sudden death syndrome, acute respiratory diseases, worsening of asthma, acute-chronic middle ear disease and slowing of lung growth.The objective of this article is to describe the BIBE study protocol. The BIBE study aims to determine the effectiveness of a brief intervention within the context of Primary Care, directed to mothers and fathers that smoke, in order to reduce the exposure of babies to passive smoking (ETS). METHODS/DESIGN: Cluster randomized field trial (control and intervention group), multicentric and open. SUBJECT: Fathers and/or mothers who are smokers and their babies (under 18 months) that attend pediatric services in Primary Care in Catalonia.The measurements will be taken at three points in time, in each of the fathers and/or mothers who respond to a questionnaire regarding their baby's clinical background and characteristics of the baby's exposure, together with variables related to the parents' tobacco consumption. A hair sample of the baby will be taken at the beginning of the study and at six months after the initial visit (biological determination of nicotine). The intervention group will apply a brief intervention in passive smoking after specific training and the control group will apply the habitual care. DISCUSSION: Exposure to ETS is an avoidable factor related to infant morbimortality. Interventions to reduce exposure to ETS in babies are potentially beneficial for their health.The BIBE study evaluates an intervention to reduce exposure to ETS that takes advantage of pediatric visits. Interventions in the form of advice, conducted by pediatric professionals, are an excellent opportunity for prevention and protection of infants against the harmful effects of ETS. TRIAL REGISTRATION: Clinical Trials.gov Identifier: NCT00788996.

Impact of the Spanish smoking law in smoker hospitality workers.

INTRODUCTION: A smoke-free law went into effect in Spain on 1 January 2006, affecting all enclosed workplaces except hospitality venues, where only partial bans were implemented. The objective was to evaluate the impact of the law among hospitality workers who smoke. METHODS: The study design is a before-and-after evaluation. We formed a cohort at baseline, during the 3 months before the law went into effect, with 431 hospitality workers (222 smokers). From them, 288 were successfully followed-up 12 months after the ban (118 were smokers at baseline). We analyzed the quit rate, the reduction in the number of cigarettes smoked per day, changes in the Fagerström Test for Nicotine Dependence (FTND) scores, and changes in salivary cotinine concentrations in smokers from baseline to 1 year after the ban. RESULTS: Among 118 smokers, six (5.1%) quit smoking. Among the 112 remaining smokers, the mean number of cigarettes smoked decreased by 8.9% after the ban (from 17.9 to 16.3 cigarettes/day, p < .01). The proportion of workers with a high nicotine dependence (FTND score >6) was reduced by half after the ban (19.5% vs. 9.7%, p = .03). Salivary cotinine decreased by 4.4% after the ban (geometric mean 104.3 vs. 99.7 ng/ml, p = .02). No meaningful differences were found in quit rates and the FTND scores according to type of regulation. DISCUSSION: The Spanish smoking law has had beneficial effects (reduction in number of cigarettes smoked, cotinine levels, and FTND score) among hospitality workers who smoke.