Exposure to Secondhand Smoke: Inconsistency between Self-Response and Urine Cotinine Biomarker Based on Korean National Data during 2009-2018

The effect of healthy eating on the development of stomach and colorectal cancer by the smoking and drinking status: Results from the Korean National Cancer Center (KNCC) community cohort study

BACKGROUND

Determining the effect of dietary factors on cancer is a crucial issue when accounting for the effect of other major risks, such as smoking and drinking.

METHOD

A total of 15,563 adults from the Korean National Cancer Center Community Cohort were analyzed to determine and to compare the effect of dietary factors on stomach and colorectal cancer in overall and in the subgroup of non-smokers (or urinary cotinine concentrations <5 ng/mg) and non-drinkers with Cox proportional-hazard models.

RESULTS

During the mean follow-up (13.7 years), 469 and 299 cases of stomach and colorectal cancer were identified, respectively. The preventive effect of vegetable, fish, and soybean/tofu intake on colorectal cancer was found in women after adjustment for smoking, drinking, BMI, and sociodemographic factors. In the subgroup analysis of non-smokers and non-drinkers, the effect on colorectal cancer was increased in women (≥1 time/week vs. almost never, vegetables: hazard ratio (HR) 0.30, 95% confidence interval (CI) 0.13-0.69; fish: HR 0.46, 95% CI 0.26-0.83), and the fresh fish intake effect on stomach cancer was newly identified in men (HR 0.36, 95% CI 0.15-0.86). These effects were more pronounced and additionally shown in other dietary factors such as soybean or tofu in women and vegetables and fish in men, when subjects with <5 ng/mg urinary cotinine concentrations applied.

CONCLUSION

The protective effect of healthy eating on the risk of stomach and colorectal cancer were different by smoking and drinking status. Rigorous control of smoking and drinking effects is necessary when measuring the effect of dietary factors on cancer, properly.

Nicotine exposure from packaged cigarettes in tobacco retail settings

BACKGROUND

Although many studies on exposure to environmental tobacco smoke from passive smoking have been conducted, most of such studies have only focused on the chemicals produced by active combustion. The current study examined the extent to which uncombusted and packaged cigarettes in cigarette racks at retail stores diffuse airborne nicotine.

METHODS

Airborne nicotine samples were collected for 15 days on passive monitors mounted near the indoor cigarette racks (Point 1) and farthest point from the cigarette racks (Point 2) in tobacco retailer stores (N=95) in South Korea (5 months, data collection from January to May in 2022.

RESULTS

The average airborne nicotine level was 0.0908 ug/m3 at Point 1 and 0.0345 ug/m3 at Point 2. We found a positive correlation (r=0.647, p <0.001) in nicotine concentration between the two measurement points. The interior size of the target stores was positively correlated (r=0.334, p <0.001) with the within-store difference in nicotine concentration between the two measurement points. The airborne nicotine concentration at Point 1 was statistically significantly higher than at Point 2 (z=-2.326, p=0.020, effect size: 0.2215), especially at larger stores.

CONCLUSIONS

Our findings indicate that packaged, unopened, and uncombusted cigarettes in cigarette racks at tobacco retailers emits airborne nicotine, which is a previously unrecognized source of nicotine exposure. This result has implications for policy considerations, such as the potential installation of ventilation systems on cigarette racks or the exploration of alternative packaging methods.

Simultaneous Measurement and Distribution Analysis of Urinary Nicotine, Cotinine, Trans-3'-Hydroxycotinine, Nornicotine, Anabasine, and Total Nicotine Equivalents in a Large Korean Population

Measurement of multiple nicotine metabolites and total nicotine equivalents (TNE) might be a more reliable strategy for tobacco exposure verification than measuring single urinary cotinine alone. We simultaneously measured nicotine, cotinine, 3-OH cotinine, nornicotine, and anabasine using 19,874 urine samples collected from the Korean National Health and Nutrition Examination Survey. Of all samples, 18.6% were positive for cotinine, 17.4% for nicotine, 17.3% for nornicotine, 17.6% for 3-OH cotinine, and 13.2% for anabasine. Of the cotinine negative samples, less than 0.3% were positive for all nicotine metabolites, but not for anabasine (5.7%). The agreement of the classification of smoking status by cotinine combined with nicotine metabolites was 0.982-0.994 (Cohen's kappa). TNE3 (the molar sum of urinary nicotine, cotinine, and 3-OH cotinine) was most strongly correlated with cotinine compared to the other nicotine metabolites; however, anabasine was less strongly correlated with other biomarkers. Among anabasine-positive samples, 30% were negative for nicotine or its metabolites, and 25% were undetectable. Our study shows that the single measurement of urinary cotinine is simple and has a comparable classification of smoking status to differentiate between current smokers and non-smokers relative to the measurement of multiple nicotine metabolites. However, measurement of multiple nicotine metabolites and TNE3 could be useful for monitoring exposure to low-level or secondhand smoke exposure and for determining individual differences in nicotine metabolism. Geometric or cultural factors should be considered for the differentiation of tobacco use from patients with nicotine replacement therapy by anabasine.

Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

Objective

To reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.

Methods

We used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.

Results

Following the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.

Conclusion

Strengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK.

Concordance assessment through comparison with urine cotinine: Does self-report adequately reflect passive smoking?

INTRODUCTION

There is a paucity of studies evaluating passive smoking (PS) by comparing self-report (SR) and biomarkers. Our study aimed to confirm whether SR could accurately reflect PS compared to biomarkers, a golden standard for assessing the exposure of non-smokers.

METHODS

We used the 2014-2020 Korea National Health and Nutrition Examination Survey data and selected 29622 non-smokers aged >19 years as the study participants. The PS rate by SR was assessed during the last 7 days, and participants were interviewed to investigate their exposure at home, work, indoors, and in public places. In addition, participants having a limit of detection ≥0.5 ng/mL in urine cotinine (UC) was defined as the exposure group. All analyses reflected the weights of complex sampling. We first compared the rates of PS using biomarkers and SR, and then the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated based on biomarkers.

RESULTS

PS exposure by UC was the highest (44.4%), and the exposure by SR was significantly lower (5.1-29.5%). Kappa and sensitivity in PS in the indoor home (HPS) were lower than those in indoor workplaces (WPS) and indoor public places (PPS). Moreover, overall sensitivity and PPV were lower, and specificity and NPV were relatively higher in accuracy. Lastly, the sensitivity was poor, and the specificity was relatively good, which means that measurement by SR would identify people who were actually exposed to PS as non-exposed.

CONCLUSIONS

Despite exposure to PS, the use of the SR method is more likely to classify participants in the non-exposed group. Hence, to overcome measurement error in SR and reflect exposure in any place and setting, biomonitoring and SR should be performed.

Smoke Exposure Reduces the Protective Effect of Physical Activity on Hypertension: Evidence from the National Health and Nutrition Examination Survey (NHANES) 2013-2018

The joint effects between smoke exposure (SE) and physical activity (PA) on hypertension are still unclear, and the effect of SE is still debated. To explore associations and joint effects of SE and PA on hypertension, the data of 14,456 selected participants from the NHANES (2013-2018) were used for analyses. SE status was divided by serum cotinine concentrations. Moderate-to-vigorous intensity PA (MVPA) and insufficient or no PA (INPA) were divided by the Global Physical Activity Questionnaire. Hypertension was assessed by blood pressure and questionnaires. Survey logistic multivariable regression models were conducted for data analyses. In fully adjusted models, hypertension risk among SE participants increased (OR = 1.175, 95% CI: 1.036-1.332), especially those who were <40 years or female. However, the risk among MVPA participants decreased (OR = 0.747, 95% CI: 0.663-0.841), especially those who were ≥40 years. Additionally, the OR for MVPA participants without SE when compared with INPA ones without SE was 0.740 (95% CI: 0.654-0.837), especially those who were <60 years. However, the OR for MVPA participants with SE was 0.880 (95% CI: 0.747-1.037). For INPA participants, we did not observe significant ORs for SE compared with non-SE participants (p > 0.150). In conclusion, SE increased the risk of hypertension and MVPA reduced it, but SE could reduce such protective effect.

Differences between Self-Report and Biomarkers in Smoking Indicators: The Necessity of Biomonitoring in Global Surveillance

Tobacco causes premature death through cardiovascular disease, cancer, and respiratory disease [...].

Diagnostic Performance Evaluation of the Novel Index Combining Urinary Cotinine and 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol in Smoking Status Verification and Usefulness for Trend Monitoring of Tobacco Smoking Exposure

During the last decade in Korea, urinary cotinine concentrations in non-current smokers have decreased, making it difficult to distinguish secondhand smoke (SHS) exposure from nonsmokers because of overlapping values between non-current smokers with and without SHS exposure. Additionally, the importance of smoking status verification to avoid misclassification is increasing with the increased use of e-cigarettes. We developed a novel index combining urinary cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and evaluated its diagnostic performance for the classification of smoking status using the KNHANES VII dataset. A total of 10,116 and 5575 Korean participants aged >19 years with measured urinary cotinine concentrations were enrolled in a training set and validation set, respectively. When using 4.0 as the cutoff value for distinguishing current smokers from non-current smokers, urinary cotinine∙NNAL showed a better diagnostic performance than urinary cotinine or urinary NNAL. Among e-cigarette users, urinary cotinine∙NNAL showed more accurate classification rates than urinary NNAL. Furthermore, urinary cotinine∙NNAL had measurable values in non-current smokers, whereas urinary cotinine had unmeasurable values in one-fourth of all participants. This study shows that urinary cotinine∙NNAL might be a useful biomarker for smoking status verification and trend monitoring of tobacco smoking exposure with increased use of e-cigarettes.

Effect of Second-Hand Smoke Exposure on Establishing Urinary Cotinine-Based Optimal Cut-Off Values for Smoking Status Classification in Korean Adults

Regulations for banning smoking in indoor public places and workplaces have increased worldwide in recent years. A consecutive Korean National Health and Nutrition Examination Survey (KNHANES) between 2008 and 2018 showed a trend toward significant decreases in self-reported tobacco smoke exposure and measured urinary cotinine concentrations. We established and compared each optimal cut-off value for assessing the effect of second-hand smoke (SHS) exposure on establishing urinary cotinine-based cut-off values for smoking status classification in a population setting controlled for racial and cultural diversity, using four KNHANES datasets consisting of the 2008, 2011, 2014, and 2018 surveys. A total of 18,229 Korean participants aged >19 years with measured urinary cotinine concentrations were enrolled. Self-reports of current smoking status showed that the prevalence of current smokers decreased from 22.9% to 18.2% between 2008 and 2018. During this period, the median value of urinary cotinine in nonsmokers decreased from 5.86 µg/L to 0.48 µg/L, whereas the median value showed no remarkable decrease in current smokers. The AUC-based optimal cut-off values of urinary cotinine concentration for distinguishing current smokers from nonsmokers decreased from 86.5 µg/L to 11.5 µg/L. Our study showed that decreased SHS exposure would result in decreased optimal cut-off values for distinguishing current smokers from nonsmokers. In addition, the study suggests that the range of urinary cotinine concentration to define SHS exposure for the trend monitoring of populationof SHS exposure is appropriate between 0.30 µg/L and 100 µg/L. In addition, our study showed the importance of determination of cotinine concentration, which would have allowed us to avoid mistakes in qualification to the study group in an increased use of e-cigarette setting.

Evaluation of Thirdhand Smoke Exposure after Short Visits to Public Facilities (Noraebang and Internet Cafés): A Prospective Cohort Study

We aimed to evaluate the degree of thirdhand smoke (THS) caused by short-term exposure to smoking-related substances. To this end, we evaluated the change in concentration of a smoking-related urine biomarker in volunteers before and after visiting public spaces where there is likely THS exposure. We hypothesized that a visit to such public spaces would result in an increase in such biomarkers. Participants visited one of the predetermined facilities (noraebang, PC café) and revisited the same facility after 24 h, spending around 2 h per visit. We selected creatinine-corrected urine cotinine (CUC) as a biomarker to evaluate THS. In addition, we collected nicotine-derived nitrosamine ketone (NNK) from surface dust at each site with cotton swabs (diameter of 2.5 cm). We examined whether CUC concentration significantly changed across three time points (baseline, first visit, and second visit) via repeated-measures analysis of variance (RM-ANOVA). Moreover, we analyzed the interaction to determine whether cigarette smell affects the CUC concentration. Finally, CUC and dust NNK were analyzed with Pearson’s correlation. The CUC concentration did not increase from baseline to the first visit, but increased from the baseline to the second visit (Diff = Ln [0.565] ng/mg, P < 0.01). Further, the CUC concentration increased from the first to the second visit (Diff = Ln [0.393] ng/mg, p < 0.01). In the case of the interaction effect, there were statistically significant differences in CUC concentration depending on the smell of smoke in the facility (Diff = Ln [0.325], F value = 4.438, p value = 0.041). The change in CUC concentration from baseline to the second visit (r = 0.562, p < 0.001) and from the first to the second visit (r = 0.544, p < 0.001) were correlated with NNK concentration. We evaluated whether a short stay in a facility with smoke-related substances that adhere to the surrounding environment would expose individuals to THS even if they do not smell or are directly exposed to cigarette smoke. We confirmed that even two relatively short stays (approximately 2 h each) in a facility in which people had previously smoked can lead to THS exposure.

Association between Serum Cotinine Levels and Bone Mineral Density: An Analysis of the National Health and Nutrition Examination Survey (NHANES)

PURPOSE

To investigate the relationship between serum cotinine and lumbar bone mineral density (BMD) among 7905 participants aged 30 years and over.

METHOD

A total of 3945 men and 3960 women from the National Health and Nutrition Examination Survey 2011-2018 were included in this cross-sectional analysis. Independent variable was serum cotinine, which is a biomarker of cigarette exposure. The outcome variable was lumbar BMD. We investigated the associations of serum cotinine levels and lumbar BMD using multivariable linear regression models.

RESULTS

Serum cotinine concentration was negatively associated with lumbar BMD after adjustment of relevant covariables (β = -0.039, 95% CI: -0.078 to -0.014, P = 0.005). However, in the subgroup analysis stratified by gender, this negative association remained only in women (β = -0.072, 95% CI: -0.132 to -0.012, P = 0.019).

CONCLUSION

Our study suggested that elevated serum cotinine level correlated with decreased lumbar BMD, especially in women. This finding indicated that reducing cigarette exposure and maintaining serum cotinine at a low level may be beneficial to bone health for adults.