• 보건행정학회지
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• 제30권4호
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• pp.505-512
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• 2020

Background: In monitoring exposure to environmental smoke (ETS), biomarkers can overcome the subjectivity and inaccuracy of self-reporting measurements, and have the advantage of reflecting ETS exposure in all places. This study aims to evaluate the effectiveness of ETS exposure measurement using biomarkers such as urine cotinine. Methods: This study used the Korea National Health and Nutrition Survey data from 2009 to 2018. A total of 28,574 non-smokers with urine cotinine data were selected for the study. The cotinine concentration and ETS exposure rate using urine cotinine was estimated and then compared with the self-reporting measurements. The degree of agreement among measurements of ETS exposure was confirmed. Results: As a result of measuring ETS exposure with urine cotinine, 23,594 (83.8%) out of 28,574 subjects were classified as to exposure groups. This estimate differs significantly from measurements made by self-reporting. In addition, the average concentration of cotinine in non-smokers has decreased to a 10th level over the past 10 years. Based on the biomarker, the sensitivity of the self-reporting was 8.5%-29.0%, the specificity was 16.4%-19.5%, and the kappa value was 2.0%-5.8%. Conclusion: The findings of our study show that self-reporting measurement does not well reflect the extent to which non-smoker's exposure to smoking materials. Whereas cotinine concentration has decreased significantly over the past 10 years, the ETS exposure rate has not reduced. It strongly suggests the need for intervention in the group of non-smokers exposed to low concentrations of smoke. Therefore, an assessment using biomarkers such as cotinine-based measurement should be made in the Health Plan 2030.

• 한국연초학회지
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• 제23권1호
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• pp.71-76
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• 2001

This study was conducted to determine the urinary nicotine and cotinine concentration in 126 smokers and 143 nonsmokers. While urine samples were being collected, personal characteristics related to smoking habit such as sex, age, number of years since a person has been a smoker, average number of cigarettes consumed per day, and number of smokers in the family were surveyed. Urinary nicotine and cotinine concentration were analyzed by GC/NPD. The smokers smoked an average 17.0 cigarettes per day and the average concentration of nicotine and cotinine was 3.88 $\mu\textrm{g}$/ml and 3.64 $\mu\textrm{g}$/ml, respectively. The average number of smokers in the family was 0.72 persons and the average concentration of nicotine and cotinine were 0.11 $\mu\textrm{g}$/ml and 0.02 $\mu\textrm{g}$/ml in the urine of non-smokers, respectively. The concentration of nicotine and cotnine in smoker\`s urine was dependent on the number of cigarettes smoked per day(p<0.01). The number of years since a person had been a smoker, and the number of smokers in the family were not associated with the concentration of nicotine and cotinine. Also there was no significant effects of passive smoking on the family of smokers by the level of nicotine and cotinine concentration. We describe the relationship between smoking habit as assessed by urinary nicotine and cotinine excretion. This study provides an evidence for the assessment of active and passive exposure to tobacco smoke.

• Asian Pacific Journal of Cancer Prevention
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• 제13권11호
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• pp.5483-5488
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• 2012

Background: Although nicotine dependence plays a role as a main barrier for smoking cessation, there is still a lack of solid evidence on the validity of biomarkers to determine nicotine dependence in clinical settings. This study aimed to investigate whether urinary cotinine levels could reflect the severity of nicotine dependence in active smokers. Materials and Methods: Data regarding general characteristics and smoking status was collected using a self-administered smoking questionnaire. The Fagerstr$\ddot{o}$m test for nicotine dependence (FTND) was used to determine nicotine dependence of the participants, and a total of 381 participants were classified into 3 groups of nicotine dependence: low (n=205, 53.8%), moderate (n=127, 33.3%), and high dependence groups (n=49, 12.9%). Stepwise multiple linear regression model and receiver operating characteristic (ROC) curves analyses were used to determine the validity of urinary cotinine for high nicotine dependence. Results: In correlation analysis, urinary cotinine levels increased with FTND score (r=0.567, P<0.001). ROC curves analysis showed that urinary cotinine levels predicted the high-dependence group with reasonable accuracy (optimal cut-off value=1,000 ng/mL; AUC=0.82; P<0.001; sensitivity=71.4%; specificity=74.4%). In stepwise multiple regression analysis, the total smoking period (${\beta}$=0.042, P=0.001) and urinary cotinine levels (${\beta}$=0.234, P<0.001) were positively associated with nicotine dependence, whereas an inverse association was observed between highest education levels (>16 years) and nicotine dependence (${\beta}$=-0.573, P=0.034). Conclusions: The results of this study support the validity of using urinary cotinine levels for assessment of nicotine dependence in active smokers.

• 한국환경보건학회지
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• 제46권2호
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• pp.214-223
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• 2020

Objectives: The aim of this study is to identify temporal trends in urinary cotinine levels and exposure factors among Non-smokers in Korean adults. Methods: Biological samples and questionnaire data were collected from representative Korean adults recruited in the Korean National Environmental Health Survey from 2009 to 2017. Multiple regression analysis was performed to determine the factors affecting urinary cotinine concentrations of non-smokers. Results: The urinary cotinine levels of Korean non-smokers decreased in Cycle 2 (1.04 ㎍/L, 2012-2014) compared to Cycle 1 (1.93 ㎍/L, 2009-2011) but increased slightly in Cycle 3 (1.37 ㎍/L, 2015-2017). Among the diverse variables, the main factors of cotinine exposure were secondhand smoke exposure and the presence of smokers in the family. Conclusions: The results of this study identified temporal trends in cotinine exposure among non-smokers in the Korean adult population. These findings will be used to develop further assessment and environmental health policies on secondhand smoke exposure.

• Environmental Analysis Health and Toxicology
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• 제5권3_4호
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• pp.47-56
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• 1990

Smoking damages nonsmoker's health who have been exposed to passive smoking as well as smoker's own health. Passive smoking can cause serious health damage to particular groups, such as the old aged, children and pregnant women. The purpose of this study is to investigate the relationship between nicotine concentrations in environmental tobacco smoke (ETS) and urinary cotinine concentrations of nonsmokers exposed to ETS, and to provide basic information related to health risk assessment. The results of this study were summarized as follows: 1. When 180 cigarrette were smoked during S hours (high concentrations exposure) in 132 m$^3$chamber, mean concentrations of nicotine in ETS showed 263.52 $\mu\textrm{g}$/m$^3$${\pm}$51.93. When 45 cigarretts were smoked (low concentrations exposure), it was 69.43${\pm}$8.96 $\mu\textrm{g}$/m$^3$. 2. The urinary cotinine concentrations of each times (0, 2.5, 5, 17 and 24 hours) in nonsmokers ranged from 0.27∼12.52 ng/ml in high concentrations exposure and 0.22∼2.28 ng/ml in low concentrations exposure. Mean while the total urinary cotinine concentrations during 24 hours ranged from 11.62∼31.65 ng/ml in high concentrations exposure and 3.45∼5.64 ng/ml in low concentrations exposure. 3. The correlation equation and coefficient between cotinine concentrations in nonsmokers' urine (y) and nicotine concentrations in ETS (x) was y=0.421+0.0171x and 0:875 (p<0.01) respectively, 4. The quantity of nonsmokers' smoking exposure by passive smoking can be assumed as based on the estimation of nicotine concentrations in ETS by measuring cotinine concentrations of nonsmokers' urine.

• 한국환경보건학회지
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• 제28권2호
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• pp.173-182
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• 2002

Exposure to environmental tobacco smoke(ETS) increases the risk of lung cancer and other diverse health effect for nonsmokers. Health risk assessment of nonsmokers related to ETS exposure requires large and exact data of ETS exposure to nonsmokers. This study presented the data of ETS exposure to workers at three category of restaurants(Korean restaurant, coffee shop, wine shop) in Seoul. Markers of ETS exposure measured in this study were area and personal NO$_2$, area and urine nicotine, area respiratory suspended particulate(RSP) and urine cotinine. The mean concentration of RSP and nicotine of all restaurant indoor samples was 177.8$\mu\textrm{g}$/㎥(range:75.3~317.0$\mu\textrm{g}$/㎥) and 7.8$\mu\textrm{g}$/㎥(range:0~57.3$\mu\textrm{g}$/㎥). The mean concentration of urine cotinine measured for the biomarker of ETS exposure was 77.3ng/mL(range:17.3~174.6ng/mL). In all measurements, the concentration of ETS markers at the wine shop was higher than those at other restaurants. The correlation coefficient among the ETS markers measured in the study was significant between area RSP and nicotine concentration and between area NO$_2$and nicotine concentration.

• 한국연초학회:학술대회논문집
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• 한국연초학회 2003년도 27회 정기총회 및 49회 학술발표회
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• pp.35-35
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• 2003

• 한국환경보건학회지
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• 제35권2호
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• pp.100-115
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• 2009

Secondhand smoke (SHS) is one of major public health threats. Since secondhand smoke is complex mixture of toxic chemicals, there has been no standardized method to measure SHS quantitatively. The purpose of this manuscript was to review various quantitative methods to measure SHS. There are two different methods: air monitoring and biological monitoring. Air monitoring methods include exhaled carbon monoxide level, ambient fine particulates, nicotine and 3-ethenylpyridine. Measurement of fine particulates has been utilized due to presence of real-time monitor, while fine particulates can have multiple indoor sources other than SHS. Ambient nicotine and 3-EP are more specific to SHS, although there is no real-time monitor for these chemicals. Biological monitoring methods include nicotine in hair, cotinine in urine, NNK in urine and DNA adducts. Nicotine in hair can provide chronic internal dose, while cotinine in urine can provide acute dose. Since biological monitoring can provide total internal dose, identification of specific exposure source may be difficult. NNK in urine can indicate carcinogenicity of the SHS exposure. DNA adducts can provide overall cancer causing exposure, but not specific to SHS. While there are many quantitative methods to measure SHS, selection of appropriate method should be based on purposes of assessment. Application of accurate and appropriate exposure assessment method is important for understanding health effects and establishing appropriate control measures.

• 한국환경보건학회지
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• 제40권6호
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• pp.492-501
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• 2014

Objectives: The purpose of this study was to assess the validity of self-reported cigarette smoking status and investigate factors associated with the accuracy self-reported and measured urinary cotinine in Korean adults. Methods: We used data from the $1^{st}$ Korean National Environmental Health Survey (2009-2011) among adults aged ${\geq}19$ years (N=6,246). The survey examined self-reported smoking status, and urinary cotinine was regarded as the biomarker of exposure to tobacco smoke. Urinary cotinine was analyzed using a gas chromatography-mass spectrometry (GC/MS) and data analysis was conducted using IBM SPSS version 20.0, which uses the sample weight and calculates variance estimates to adjust for the unequal probability of selection into the survey. Results: We calculated a cut-off point (53.3 ug/L) by using a ROC (Receiver Operating Characteristic) curve. The smoking prevalence was 24.6% based on self-reported data and 28.2% based on urinary cotinine concentrations. When we assessed the agreement between self-reported and urinary cotinine, we found an average agreement of 97.7% among self-reported smokers and 94.5% among self-reported non-smokers. Among self-reported smokers, factors affected the discrepancy were age, household economic status and average number of cigarettes smoked per day. On the other hand, gender, former smoking experience, and exposure to SHS (second hand smoke) were associated with discrepancies among self-reported non-smokers. Conclusion: These results suggest that self-reported data on smoking status provide a valid estimate of actual smoking status. In future research, we will conduct a continuous monitoring study for reliability verification of the data to reduce potential interpretation errors.

• Asian Pacific Journal of Cancer Prevention
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• 제13권3호
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• pp.1003-1010
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• 2012

Background: This study examined the influence of body mass index (BMI), subjective body perception (SBP), and the differences between BMI and SBP influence on smoking among women. Methods: This study used the Korea National Health and Nutrition Examination Survey IV-2, 3 2008-2009. A urinary cotinine test was administered to 5485 women at least 19 years of age. Individuals whose cotinine level was at least 50 ng/mL were categorized as smokers. A multiple logistic regression analysis was performed to estimate the extent to which body-related variables affect female smoking. Results: Women with a lower BMI who perceived themselves to be normal or very fat were 2.09 times (1.14-3.83) more likely to smoke than women with a normal BMI and SBP. Women who were never married with a low BMI and thin SBP were 3.11 times (1.47-6.55) more likely to smoke than women with a normal BMI and SBP. Married women with a high BMI who considered themselves very fat were 0.63 times (0.43-0.94) less likely to smoke than women with a normal BMI and SBP. In contrast, divorced and widowed women with a low or normal BMI who considered themselves very fat were 26.1 times (1.35-507.3) more likely to smoke. Conclusions: Discrepancies between the objective physical condition (BMI) and the subjective body image (SBP) influence the female smoking rate. To reduce the number of female smokers, public education on the association between smoking behavior and weight issues is needed, especially among women with low BMI and distorted weight perception.