Epidemiologic relationship between alcohol flushing and smoking in the Korean population: the Korea National Health and Nutrition Examination Survey

Epidemiologic relationship between alcohol flushing and smoking in the Korean population: the Korea National Health and Nutrition Examination Survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Epidemiologic relationship between alcohol flushing and smoking in the Korean population: the Korea National Health and Nutrition Examination Survey Hwa Jung Yook, Gyu-Na Lee, Ji Hyun Lee, Kyungdo Han, Young Min Park This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3807149/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Although facial flushing after drinking alcohol (alcohol flushing response) is common in Asian populations, the epidemiological features in a large sample have been investigated in only a few studies. This study assessed the epidemiologic characteristics and risk factors of alcohol flushing in a Korean population. This study was based on data collected during the 2019 Korea National Health and Nutrition Examination Survey (KNHANES). A total of 5,572 Korean adults was included in the general population group, and the alcohol flushing group consisted of 2,257 participants. Smoking and physical activity were evaluated as possible risk factors for alcohol flushing. The overall prevalence of alcohol flushing was estimated at 40.56% of the general population (43.74% in males and 37.4% in females), and the prevalence was highest at 60–69 years of age and lowest in individuals older than 80 years. Occasional, frequent, and persistent alcohol flushing was reported by 11.9%, 3.7%. and 15.0% of current flushers, among whom persistent flushers consumed the least amount of alcohol. The risk of alcohol flushing increased with current smoking status (adjusted OR 1.525, 95% CI 1.2–1.938), and smoking history of 20–29 pack-years (PYs) showed the highest association (adjusted OR 1.725, 95% CI 1.266–2.349) with alcohol flushing after adjustment for confounders. In contrast, significant association was not found between physical activity and alcohol flushing. The results demonstrated that current smoking could increase the risk of alcohol flushing, and that current smokers with a history of smoking > 20 PYs had a higher risk of alcohol flushing than non-smokers or ex-smokers. Health sciences/Health care/Public health/Epidemiology Health sciences/Health care/Patient education Figures Figure 1 Figure 2 Figure 3 Introduction Flushing refers to temporary reddening of the skin, particularly on the face, neck, upper chest, and other areas, accompanied by a feeling of warmth 1 , 2 . Flushing and blushing are caused by physiological transient cutaneous vasodilatation. Although these terms are often used interchangeably, a blush represents a psychosocial response to an emotion, whereas a flush is due to a thermoregulatory response to elevated body temperature 2 . Alcohol flushing response, known as drinking-related flushing, is mainly caused by the accumulation of acetaldehyde caused by alcohol metabolism 3 , and acetaldehyde is then metabolized to acetate by aldehyde dehydrogenase enzymes, mainly aldehyde dehydrogenase 2 (ALDH2) 4 , 5 . Alcohol flushing and ALDH gene polymorphism are common among East Asian populations including Japanese, Chinese, and Korean 6 , and the term “Asian flush syndrome” or “Oriental flushing” have been used to describe facial flushing, headache, nausea, dizziness, and cardiac palpitations after consumption of alcoholic beverages 2 . Therefore, facial flushing after alcohol intake is regarded as a predictor of inactive ALDH2 5,7 . In previous epidemiologic studies including Japanese subjects, questionnaires concerning alcohol flushing as a surrogate marker of inactive ALDH genotype have been used 8 ,9 10 . To date, the primary focus in previous research was on comorbidities associated with alcohol flushing. Kim et al. 11 suggested that some Korean male drinkers who experience an alcohol flushing response have a higher risk of metabolic syndrome and hypertension with less alcohol consumption than non-flushers 12 . In addition, flushers were reported to have an increased risk of coronary spastic angina as well as esophageal, pharyngolaryngeal, and bladder cancer 5 , 6 , 13 , 14 , 15 . Yokoyama et al. 16 reported that never or former flushing and genotype combinations were independent strong risk factors of alcohol dependence in Japanese men and women. Because the clinical importance of an alcohol flushing response is emphasized in various medical fields 5 , 12 , 15 , 17 ; however, the epidemiology and risk factors of alcohol flushing have not been sufficiently investigated. This study aims to investigate the epidemiologic characteristics of alcohol flushing and to identify the possible risk factors of alcohol flushing in the Korean population using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Furthermore, subgroup analyses stratified based on drinking and flushing status were performed to clarify the association between the two variables. Results Epidemiologic characteristics and prevalence of alcohol flushing Table 1 shows the demographic characteristics of the study population based on drinking and alcohol flushing. The age- and sex-standardized prevalence of alcohol flushing is shown in Fig. 2 . The overall prevalence of alcohol flushing was estimated at 40.56% of the general population (43.74% in males and 37.4% in females), and the prevalence was highest when subjects were 60–69 years of age and lowest in individuals > 80 years of age. Table 1 General characteristics of the study population based on drinking and alcohol flushing status (n = 5,572) Non-drinker Drinker p-value a p-value b Non-flusher Flusher n 577 2,738 2,257 Age (years) 61.85 (1.1) 45.37 (0.45) 46.96 (0.49) < 0.0001 0.0005 Sex < 0.0001 0.1225 Male 22.91 (2.18) 51.08 (1.08) 53.72 (1.07) Female 77.09 (2.18) 48.92 (1.08) 46.28 (1.07) Low income 35.04 (2.61) 11.77 (0.83) 13.54 (1.02) < 0.0001 0.0825 Low educational level 49.57 (2.81) 84.26 (1.02) 81.57 (1.24) < 0.0001 0.0115 Smoking status < 0.0001 0.0213 Non-smoker 87.06 (1.77) 58.31 (1.22) 53.98 (1.26) Ex-smoker 7.12 (1.29) 21.99 (0.92) 22.99 (0.97) Current smoker 5.82 (1.47) 19.7 (0.97) 23.03 (1.21) Physical activity 36.78 (2.45) 47.64 (1.32) 45.79 (1.2) 0.0005 0.2462 Diabetes mellitus 21.01 (1.92) 10.55 (0.66) 11.95 (0.82) < 0.0001 0.1361 Hypertension 47.53 (2.58) 24.77 (1.1) 26.01 (1.26) < 0.0001 0.3838 Hypercholesterolemia 31.61 (2.37) 21.31 (0.97) 20.52 (0.97) < 0.0001 0.5237 BMI 24 (0.17) 23.93 (0.1) 23.91 (0.09) 0.8883 0.849 Waist circumference 84.19 (0.5) 83.48 (0.29) 83.81 (0.28) 0.4304 0.4272 Systolic BP 125.34 (0.94) 117.14 (0.39) 117.74 (0.44) < 0.0001 0.249 Diastolic BP 74.41 (0.58) 76.32 (0.26) 75.94 (0.3) 0.0071 0.2804 Serum glucose 103.01 (1.08) 99.44 (0.47) 100.18 (0.71) 0.0095 0.3533 Total cholesterol 189.08 (1.93) 194.25 (0.82) 192.46 (0.94) 0.0342 0.1608 Serum HDL 50.93 ± 0.6) 53.9 (0.34) 52.04 (0.34) < 0.0001 < 0.0001 Data are expressed as the mean (SD) or n (%) Acronyms: BP, blood pressure; SD, standard deviation; BMI, body mass index; HDL, high-density lipoprotein a indicates comparison of three groups: non-drinker, non-flusher, and flusher b indicates comparison between two groups: non-flusher and flusher In male and female subjects, 3.81% (n = 108) and 12.73% (n = 469) were non-drinkers, 52.45% (n = 1,265) and 49.87% (n = 1,473) were non flushers, 5.04% (n = 121) and 5.29% (n = 155) were new-onset flushers, 11.94% (n = 323) and 12.66% (n = 408) were former flushers, and 26.76% (n = 655) and 19.45% (n = 595) were consistent flushers, respectively (Fig. 3 ). Collectively, 2,738 (54.8%) and 731 (14.6%) individuals were non flushers and former flushers, respectively. Among 1,526 (30.6%) current flushers, 593 (11.9%), 183 (3.7%), and 750 (15.0%) participants reported having alcohol flushing responses occasionally, frequently, and always, respectively. To determine whether the drinking amount differed based on flushing group, more segmented ranges of the amount of alcohol consumed were measured. Among the current occasional flushers, 71.5%, 7.4%, and 21.1% consumed 30 g per day of alcohol, respectively. Among the current frequent flushers, 85.4%, 6.4%, and 8.2% consumed 30 g per day of alcohol, respectively. In addition, among current always flushers, 92.6%, 4.1%, and 3.3% consumed 30 g per day of alcohol, respectively. These results demonstrated the lowest alcohol consumption in the current always group ( Fig.S1 ). Smoking and physical activity as risk factors of alcohol flushing Table 2 shows the OR of current status of alcohol flushing based on smoking status. Before adjustment, current smokers had a higher risk of alcohol flushing (OR 1.629, 95% CI 1.354–1.96). When adjusting for variables, the risk of alcohol flushing increased with current smoking status (OR 1.525, 95% CI 1.2–1.938 for the current smokers, model 3) compared with ex-smokers and non-smokers. In particular, subjects with 20–29 PYs showed a stronger tendency toward alcohol flushing than those with other PYs (OR 1.725, 95% CI 1.266–2.349 for PYs of 20–29 years, model 3). Then, the effect of a combination of smoking status and PYs on the risk of alcohol flushing experience was assessed. Current smokers and ≥ 20 PYs had a higher risk of alcohol flushing than non-smokers (OR 1.623, 95% CI 1.138–2.315 for a combination of smoking status and PYs, model 3). Notably, among subjects within the same category of PYs, current smokers had a higher OR for alcohol flushing than ex-smokers. Table 2 Current status of alcohol flushing based on smoking status and/or PYs in multivariate logistic regression Adjusted OR (95% CI) % (SE) Crude OR (95% CI) p-value Model 1 p-value Model 2 p-value Model 3 p-value Smoking status Non-smoker 25.25 (0.9) 1 (ref) < 0.0001 1 (ref) 0.0089 1 (ref) 0.0015 1 (ref) 0.0015 Ex-smoker 31.11 (1.86) 1.336 (1.108–1.612) 1.27 (1.026–1.572) 1.323 (1.073–1.632) 1.325 (1.076–1.631) Current smoker 35.5 (1.91) 1.629 (1.354–1.96) 1.398 (1.12–1.745) 1.529 (1.204–1.943) 1.525 (1.2–1.938) PYs Non 25.25 (0.9) 1 (ref) < 0.0001 1 (ref) 0.0027 1 (ref) 0.0007 1 (ref) 0.0008 < 10 PYs 38.62 (2.35) 1.863 (1.502–2.31) 1.469 (1.164–1.854) 1.548 (1.219–1.965) 1.549 (1.221–1.965) 10–20 PYs 28.36 (2.04) 1.172 (0.949–1.447) 1.063 (0.839–1.347) 1.135 (0.888–1.45) 1.144 (0.896–1.46) 20–30 PYs 35.01 (2.82) 1.594 (1.229–2.068) 1.613 (1.187–2.193) 1.751 (1.283–2.389) 1.725 (1.266–2.349) ≥ 30 PYs 26.35 (3.26) 1.059 (0.758–1.479) 1.096 (0.736–1.63) 1.207 (0.811–1.797) 1.187 (0.797–1.768) Smoking status in PYs Non-smoker 25.25 (0.9) 1 (ref) < 0.0001 1 (ref) 0.0268 1 (ref) 0.005 1 (ref) 0.0058 Ex-smoker, < 20 PYs 31.04 (2.3) 1.332 (1.063–1.67) 1.201 (0.942–1.531) 1.234 (0.971–1.569) 1.238 (0.974–1.572) Ex-smoker, ≥ 20 PYs 28.79 (2.05) 1.197 (0.978–1.464) 1.356 (1.042–1.766) 1.44 (1.109–1.869) 1.434 (1.106–1.859) Current smoker, < 20 PYs 36.91 (2.24) 1.732 (1.403–2.137) 1.392 (1.102–1.759) 1.509 (1.178–1.932) 1.513 (1.18–1.94) Current smoker, ≥ 20 PYs 32.2 (3.1) 1.406 (1.056–1.872) 1.496 (1.059–2.113) 1.665 (1.168–2.372) 1.623 (1.138–2.315) Model 1 adjusted for age and sex Model 2 adjusted for Model 1 + low income, heavy drinking, and regular physical activity Model 3 adjusted for Model 2 + presence of hypertension, diabetes mellitus, and hypercholesterolemia Acronyms: PYs, pack-years; SE, standard error; OR, odds ratio; CI, confidence interval The OR for current alcohol flushing during different types of physical activity was analyzed based on age- and sex-specific groups as shown in Table S1. After adjustment for household income, drinking amount, hypertension, DM, and hypercholesterolemia, discernible differences were not observed in the ORs. Although the unadjusted analysis showed a significant positive relationship between aerobic exercise and the prevalence of alcohol flushing in current alcohol flushers (OR 1.175, 95% CI 1.02–1.353, p = 0.0259), this relationship was lost after adjusting for multiple variables. Similarly, a significant relationship was not observed between the prevalence of alcohol flushing and other physical activities such as walking and strength training. Discussion Alcohol flushing affects all ethnic groups, and the estimated prevalence of alcohol flushing is 2–29% in Caucasians, from 10%-80% in Native Americans, and relatively higher in East Asians than in other ethnic groups 18 . In a study using Korean Community Health Survey data, the prevalence was 34.8% 19 ; alcohol flushing was shown to affect approximately 36–50% of East Asians (Koreans, Chinese, and Japanese) in previous studies 13 , 18 , 20 . In the present study using a nationwide population-based data, the mean annual prevalence of alcohol flushing was 40.56%, similar to previous reports. The high prevalence of alcohol flushing among East Asians has been explained in several studies. Yokoyama et al. 16 reported that flushing responses after drinking a small amount of alcohol were mainly attributable to high acetaldehyde exposure and influenced by ALDH2 and ADH1B genotypes. Thus, this phenomenon is predominantly due to an inherited deficiency in the ALDH2 enzyme, and genetic factors associated with discrepancies in ALDH2 haplotypes between ethnic groups might lead to differences in prevalence 2 . When measured based on sex and age, the prevalence of alcohol flushing was higher in males, which was consistent with a previous study 19 . Notably, in the present study, 11.94% of males and 12.66% of females were former flushers, and 5.04% of males and 5.29% of females transitioned into new-onset flushers. Jeon et al. 19 reported that, among participants in the Korean Community Health Survey, 4.1% were former flushers and 34.8% were current flushers. According to Yokoyama et al. 21 , alcohol flushing decreases in intensity due to the development of tolerance to acetaldehyde in blood by higher-risk persons with a long or heavy drinking history. Acquired etiologies have been reported to include use of topical tacrolimus or liver-metabolized drugs, which can aid in alcohol catabolism 22 , 23 . In the present study, smoking and physical activity were investigated as possible factors associated with alcohol flushing because they previously showed a statistical demographic difference among flushers, non-flushers, and non-drinkers. Consequently, smoking was a strong independent risk factor for alcohol flushing regardless of sex. Conversely, significant association was not found between alcohol flushing and physical activity. Furthermore, current smoking could increase alcohol flushing. Specifically, the risk of alcohol flushing was highest in current smokers with a smoking history ≥ 20 PYs. Although the adjusted OR for alcohol flushing did not proportionally correlate with PYs, further analysis showed a similar trend of higher alcohol flushing risk as smoking duration increased. In addition, current smokers with the same PYs had a higher OR for alcohol flushing than ex-smokers. Therefore, smoking status possibly has a greater effect on alcohol flushing than the duration of smoking. To the best of our knowledge, this is the first study in which a positive relationship between smoking and alcohol flushing was demonstrated; however, this correlation may have been postulated in other research. Reportedly, acetaldehyde can produce angiogenesis and telangiectasia through the expression of vascular endothelial growth factor (VEGF), as experimentally demonstrated in the chick embryo chorioallantoic membrane model 24 , and nicotine provokes dry flushing via vasodilation action of prostaglandins on vascular smooth muscle 25 . Flushers may have excessive acetaldehyde accumulation with low alcohol consumption, and such mechanisms could affect these individuals after minimal alcohol use 13 , 26 . Further biological research is needed to fully understand this relationship. However, the results of the present study revealed that individuals who experience alcohol flushing usually consume alcohol less frequently and in smaller quantities compared with subjects who do not experience these symptoms, with most drinking < 10 g of alcohol per day. This observation is in agreement with earlier studies that have shown people with inactive ALDH2 to be more likely to refrain from drinking 19 , 27 . Because the focus in the present study was on self-reported alcohol flushing status, the accuracy of alcohol flushing status determined solely through self-reported symptoms compared with genetic testing cannot be ensured. Although the use of genetic variants may provide a more reliable measure, based on the available data, whether the responses obtained for alcohol flushing accurately reflect the deficiency of the alcohol-metabolizing enzyme cannot be determined 28 , 29 . In addition, although the alcohol flushing response is mainly explained due to an inactive ALDH2, with a sensitivity of 95.1% and specificity of 76.5% 30 , individuals exhibiting this response may have characteristics different from subjects with an active ALDH2. The flushing response can be influenced by factors other than an inactive ALDH2, such as environmental factors or other genetic traits 9 . Despite these limitations, the relationships were investigated in a nationally representative sample of Koreans, producing sufficient statistical power. Furthermore, relevant confounding factors were considered. Based on our current understanding, this is the first study in which the risk factors for alcohol flushing were evaluated using nationally representative data. In addition, the KNHANES survey includes central laboratory data and a standardized questionnaire administered by a trained examiner. In conclusion, the results of the present study demonstrated that current smoking could increase the risk of alcohol flushing, and current smokers with > 20 PYs of smoking history have a higher risk of alcohol flushing than non-smokers or ex-smokers. Methods Data source and study population This study included data collected during the 2019 KNHANES, a survey designed to accurately assess national health and nutrition levels and a nationwide study of non‑institutionalized civilians that uses a stratified and multi‑stage probability sampling design with a rolling survey‑sampling model. A total of 8,110 participants completed this survey. Individuals < 20 years of age were excluded because this age group is not allowed to drink. After further exclusion of subjects with missing data on alcohol flushing or lifestyle, comorbidities, and laboratory results, 5,572 participants were available for analysis (2,472 males and 3,100 females; Fig. 1) . The participants were stratified based on sex and age. A detailed description of the plan and operation of the survey is available on the KNHANES website (www. knhanes.kdca.go.kr). Data collection All participants were questioned regarding their demographic variables, socioeconomic characteristics, and medical history. The subjects also answered questions regarding history of smoking, drinking, and physical activity through a self-administered questionnaire. Smoking status was categorized as current, ex-, or non-smoker. Ex-smokers had smoked in the past but did not smoke at the time of the interview. Period (years) and amount (in terms of packs) of smoking were included in the questions for ex- and current smokers. Pack-years (PYs) smoked were estimated by multiplying average daily cigarette smoking by smoking duration and was categorized as follows: 30 PYs. In addition, PYs were categorized in 20-year intervals with current smoking status. Similarly, drinking status was categorized as current drinker, ex-drinker, or non-drinker. Data on frequency and amount of alcohol consumed per day were also collected and categorized based on daily consumption. The low-income category corresponded to the lowest quartile of annual household income. The educational level of the subject was classified as high if the participant had completed 10 years of education. Physical activity (aerobic, walking, and strength training) at the time of survey was also assessed. The participant’s height, weight, and waist circumference were measured. Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared (kg/m 2 ). Waist circumference was measured parallel to the floor from the iliac crest in the resting position. Blood samples were collected from the antecubital vein of each participant after fasting for > 8 hours to measure concentrations of serum fasting plasma glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides. Assessment of alcohol consumption and alcohol flushing Alcohol consumption was assessed by questioning the subjects regarding their drinking behavior, including the average amount consumed and drinking frequency, in the year before the interview. A standard drink was defined as a single glass of liquor, wine, or the Korean traditional distilled liquor So-ju. One bottle of beer (355 mL) was counted as 1.6 standard drinks. The amount of alcohol consumed per standard drink was calculated as 10 g, and the average daily alcohol intake was assessed. An average consumption ≥ 30 g per day, a level of exposure associated with health risks, was considered heavy alcohol drinking. In the survey, the question on alcohol flushing status was divided into two parts. First, respondents were asked, “During the first 1-2 years when you started drinking alcohol, did you have facial flushing after consuming a small amount of alcohol?” Response options included 1) yes, 2) no, 3) non-applicable (ex. non-drinker), and 4) unknown or no response. Second, respondents were asked, " Do you currently experience facial flushing after consuming a small amount of alcohol?" Response options included 1) no, 2) occasionally, 3) frequently, and 4) always. Individuals were categorized as "non-flusher" if they never experienced alcohol flushing, "new onset" if they recently started experiencing alcohol flushing, "former" if they used to experience alcohol flushing but do not currently, and "consistent flusher" if they consistently experienced alcohol flushing in the past and present. Statistical analysis All analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) to reflect the complex sampling design and sampling weights of the KNHANES and to provide nationally representative prevalence estimates. The mean ± standard error (SE) for continuous variables or the percentage for categorical variables was calculated. A one-way ANOVA or a Chi-square test was used to compare the groups. Multiple logistic regression analyses were used to estimate the prevalence odds ratio (OR) and 95% confidence interval (CI) of alcohol flushing. Several models were applied to evaluate the potential mediation effects of modifiable behaviors such as drinking or exercise as well as the effects of known risk factors such as comorbidities. 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ALDH2, ADH1B, and ADH1C genotypes in Asians: a literature review. Alcohol Res Health 30 , 22-27 (2007). Yokoyama, A., Yokoyama, T. & Omori, T. Past and current tendency for facial flushing after a small dose of alcohol is a marker for increased risk of upper aerodigestive tract cancer in Japanese drinkers. Cancer Sci 101 , 2497-2498; author reply 2499-2500 (2010). https://doi.org:10.1111/j.1349-7006.2010.01709.x Milingou, M., Antille, C., Sorg, O., Saurat, J. H. & Lubbe, J. Alcohol intolerance and facial flushing in patients treated with topical tacrolimus. Arch Dermatol 140 , 1542-1544 (2004). https://doi.org:DOI 10.1001/archderm.140.12.1542-b Weathermon, R. & Crabb, D. W. Alcohol and medication interactions. Alcohol Res Health 23 , 40-54 (1999). Gu, J. W., Bailey, A. P., Sartin, A., Makey, I. & Brady, A. L. Ethanol stimulates tumor progression and expression of vascular endothelial growth factor in chick embryos. 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Alcohol Consumption and Cigarette Smoking among Young Adults: An Instrumental Variable Analysis Using Alcohol Flushing. Int J Environ Res Public Health 18 (2021). https://doi.org:10.3390/ijerph182111392 Shin, C. M., Kim, N., Cho, S. I., Sung, J. & Lee, H. J. Validation of Alcohol Flushing Questionnaires in Determining Inactive Aldehyde Dehydrogenase-2 and Its Clinical Implication in Alcohol-Related Diseases. Alcohol Clin Exp Res 42 , 387-396 (2018). https://doi.org:10.1111/acer.13569 Supplemental File Note Supplemental Table 1 and Supplemental Figure 1 are not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Apr, 2024 Reviews received at journal 14 Apr, 2024 Reviewers agreed at journal 04 Apr, 2024 Reviews received at journal 26 Feb, 2024 Reviewers agreed at journal 15 Feb, 2024 Reviewers invited by journal 13 Feb, 2024 Editor assigned by journal 06 Feb, 2024 Editor invited by journal 27 Dec, 2023 Submission checks completed at journal 27 Dec, 2023 First submitted to journal 26 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3807149","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":264447088,"identity":"5d0fb344-3bef-4efb-8b6f-b42a87585500","order_by":0,"name":"Hwa Jung Yook","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hwa","middleName":"Jung","lastName":"Yook","suffix":""},{"id":264447089,"identity":"ee40b22e-a44c-4fa9-be15-0275a9b629ab","order_by":1,"name":"Gyu-Na Lee","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gyu-Na","middleName":"","lastName":"Lee","suffix":""},{"id":264447090,"identity":"96745c75-8173-4464-b999-bbaf0595504e","order_by":2,"name":"Ji Hyun Lee","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ji","middleName":"Hyun","lastName":"Lee","suffix":""},{"id":264447091,"identity":"ea0934ab-5f86-49a9-84f9-beea9a7033e7","order_by":3,"name":"Kyungdo Han","email":"","orcid":"","institution":"Soongsil University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kyungdo","middleName":"","lastName":"Han","suffix":""},{"id":264447092,"identity":"4b44afa3-c167-4e65-8f1d-8650411c7f65","order_by":4,"name":"Young Min Park","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACfvbGhsM/ftjU9yPE2PBrkew5fPAwY08a48wGYrUY3HBLPszAdohxwwHitfAYHC7gOcBsfPx04ufCNgY58wa2tA94HXa7x+DwDIs7bGZncjdLz2xjMJY5wHZ4Bj4tfHfOGBzg4XnGY3aDdxszbxtD4gwG9mb8LruRA9TCdljCeAaxWgRupCUcBmoxMJCAa2E7jFcLMJAPHJzZk5YgAfILzzkJYwlmtmS8WoBR2fzhww+bBP72sxs/85TZyEmwtxnj9wsakGBgYCZJwygYBaNgFIwCbAAAfFRJgLRX61oAAAAASUVORK5CYII=","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Young","middleName":"Min","lastName":"Park","suffix":""}],"badges":[],"createdAt":"2023-12-26 08:44:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3807149/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3807149/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49080430,"identity":"97894165-bc70-4b4a-92a8-786bace419f1","added_by":"auto","created_at":"2024-01-02 19:56:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35255,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of study subject selection. (KNHANES, Korea National Health and Nutrition Examination Survey)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3807149/v1/1234a8ef4788decafea5fc10.png"},{"id":49080429,"identity":"1d64e09e-ccca-4c46-85eb-77949ae028bb","added_by":"auto","created_at":"2024-01-02 19:56:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24306,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of alcohol flushing based on age and sex\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3807149/v1/6c5792193a7721a76f8861d9.png"},{"id":49081550,"identity":"16305a6b-886b-4f19-b1f7-e9008fed3691","added_by":"auto","created_at":"2024-01-02 20:04:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22542,"visible":true,"origin":"","legend":"\u003cp\u003ePast and current alcohol flushing status\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3807149/v1/7ff6796a2466bea09614fefd.png"},{"id":49082299,"identity":"7aa17539-8acb-4ced-b5fd-2b2cdfa7d27d","added_by":"auto","created_at":"2024-01-02 20:12:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":391048,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3807149/v1/79ebce21-9b5d-4132-8443-ce33e9c2d2d6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiologic relationship between alcohol flushing and smoking in the Korean population: the Korea National Health and Nutrition Examination Survey","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFlushing refers to temporary reddening of the skin, particularly on the face, neck, upper chest, and other areas, accompanied by a feeling of warmth \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Flushing and blushing are caused by physiological transient cutaneous vasodilatation. Although these terms are often used interchangeably, a blush represents a psychosocial response to an emotion, whereas a flush is due to a thermoregulatory response to elevated body temperature \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Alcohol flushing response, known as drinking-related flushing, is mainly caused by the accumulation of acetaldehyde caused by alcohol metabolism \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, and acetaldehyde is then metabolized to acetate by aldehyde dehydrogenase enzymes, mainly aldehyde dehydrogenase 2 (ALDH2) \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Alcohol flushing and ALDH gene polymorphism are common among East Asian populations including Japanese, Chinese, and Korean \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, and the term \u0026ldquo;Asian flush syndrome\u0026rdquo; or \u0026ldquo;Oriental flushing\u0026rdquo; have been used to describe facial flushing, headache, nausea, dizziness, and cardiac palpitations after consumption of alcoholic beverages \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Therefore, facial flushing after alcohol intake is regarded as a predictor of inactive ALDH2 \u003csup\u003e5,7\u003c/sup\u003e. In previous epidemiologic studies including Japanese subjects, questionnaires concerning alcohol flushing as a surrogate marker of inactive ALDH genotype have been used \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,9 10\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo date, the primary focus in previous research was on comorbidities associated with alcohol flushing. Kim et al. \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e suggested that some Korean male drinkers who experience an alcohol flushing response have a higher risk of metabolic syndrome and hypertension with less alcohol consumption than non-flushers \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In addition, flushers were reported to have an increased risk of coronary spastic angina as well as esophageal, pharyngolaryngeal, and bladder cancer \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Yokoyama et al. \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e reported that never or former flushing and genotype combinations were independent strong risk factors of alcohol dependence in Japanese men and women. Because the clinical importance of an alcohol flushing response is emphasized in various medical fields \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e; however, the epidemiology and risk factors of alcohol flushing have not been sufficiently investigated. This study aims to investigate the epidemiologic characteristics of alcohol flushing and to identify the possible risk factors of alcohol flushing in the Korean population using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Furthermore, subgroup analyses stratified based on drinking and flushing status were performed to clarify the association between the two variables.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEpidemiologic characteristics and prevalence of alcohol flushing\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the demographic characteristics of the study population based on drinking and alcohol flushing. The age- and sex-standardized prevalence of alcohol flushing is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The overall prevalence of alcohol flushing was estimated at 40.56% of the general population (43.74% in males and 37.4% in females), and the prevalence was highest when subjects were 60\u0026ndash;69 years of age and lowest in individuals\u0026thinsp;\u0026gt;\u0026thinsp;80 years of age.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral characteristics of the study population based on drinking and alcohol flushing status (n\u0026thinsp;=\u0026thinsp;5,572)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eDrinker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-flusher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFlusher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e61.85 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.37 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.96 (0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e22.91 (2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.08 (1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.72 (1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e77.09 (2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.92 (1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.28 (1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e35.04 (2.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.77 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.54 (1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow educational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e49.57 (2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.26 (1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.57 (1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e87.06 (1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.31 (1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.98 (1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e7.12 (1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.99 (0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.99 (0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5.82 (1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.7 (0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.03 (1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e36.78 (2.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.64 (1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.79 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e21.01 (1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.55 (0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.95 (0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e47.53 (2.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.77 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.01 (1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypercholesterolemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e31.61 (2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.31 (0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.52 (0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5237\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e24 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.93 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.91 (0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e84.19 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.48 (0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.81 (0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e125.34 (0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117.14 (0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117.74 (0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e74.41 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.32 (0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.94 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2804\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e103.01 (1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.44 (0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.18 (0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3533\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e189.08 (1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e194.25 (0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e192.46 (0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum HDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e50.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.9 (0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.04 (0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eData are expressed as the mean (SD) or n (%)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAcronyms: BP, blood pressure; SD, standard deviation; BMI, body mass index; HDL, high-density lipoprotein\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e indicates comparison of three groups: non-drinker, non-flusher, and flusher\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003e indicates comparison between two groups: non-flusher and flusher\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn male and female subjects, 3.81% (n\u0026thinsp;=\u0026thinsp;108) and 12.73% (n\u0026thinsp;=\u0026thinsp;469) were non-drinkers, 52.45% (n\u0026thinsp;=\u0026thinsp;1,265) and 49.87% (n\u0026thinsp;=\u0026thinsp;1,473) were non flushers, 5.04% (n\u0026thinsp;=\u0026thinsp;121) and 5.29% (n\u0026thinsp;=\u0026thinsp;155) were new-onset flushers, 11.94% (n\u0026thinsp;=\u0026thinsp;323) and 12.66% (n\u0026thinsp;=\u0026thinsp;408) were former flushers, and 26.76% (n\u0026thinsp;=\u0026thinsp;655) and 19.45% (n\u0026thinsp;=\u0026thinsp;595) were consistent flushers, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Collectively, 2,738 (54.8%) and 731 (14.6%) individuals were non flushers and former flushers, respectively. Among 1,526 (30.6%) current flushers, 593 (11.9%), 183 (3.7%), and 750 (15.0%) participants reported having alcohol flushing responses occasionally, frequently, and always, respectively. To determine whether the drinking amount differed based on flushing group, more segmented ranges of the amount of alcohol consumed were measured. Among the current occasional flushers, 71.5%, 7.4%, and 21.1% consumed\u0026thinsp;\u0026lt;\u0026thinsp;10 g per day, 10\u0026ndash;20 g per day, and \u0026gt;\u0026thinsp;30 g per day of alcohol, respectively. Among the current frequent flushers, 85.4%, 6.4%, and 8.2% consumed\u0026thinsp;\u0026lt;\u0026thinsp;10 g per day, 10\u0026ndash;20 g per day, and \u0026gt;\u0026thinsp;30 g per day of alcohol, respectively. In addition, among current always flushers, 92.6%, 4.1%, and 3.3% consumed\u0026thinsp;\u0026lt;\u0026thinsp;10 g per day, 10\u0026ndash;20 g per day, and \u0026gt;\u0026thinsp;30 g per day of alcohol, respectively. These results demonstrated the lowest alcohol consumption in the current always group (\u003cb\u003eFig.S1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSmoking and physical activity as risk factors of alcohol flushing\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the OR of current status of alcohol flushing based on smoking status. Before adjustment, current smokers had a higher risk of alcohol flushing (OR 1.629, 95% CI 1.354\u0026ndash;1.96). When adjusting for variables, the risk of alcohol flushing increased with current smoking status (OR 1.525, 95% CI 1.2\u0026ndash;1.938 for the current smokers, model 3) compared with ex-smokers and non-smokers. In particular, subjects with 20\u0026ndash;29 PYs showed a stronger tendency toward alcohol flushing than those with other PYs (OR 1.725, 95% CI 1.266\u0026ndash;2.349 for PYs of 20\u0026ndash;29 years, model 3). Then, the effect of a combination of smoking status and PYs on the risk of alcohol flushing experience was assessed. Current smokers and \u0026ge;\u0026thinsp;20 PYs had a higher risk of alcohol flushing than non-smokers (OR 1.623, 95% CI 1.138\u0026ndash;2.315 for a combination of smoking status and PYs, model 3). Notably, among subjects within the same category of PYs, current smokers had a higher OR for alcohol flushing than ex-smokers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCurrent status of alcohol flushing based on smoking status and/or PYs in multivariate logistic regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c10\" namest=\"c5\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% (SE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrude OR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.25 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.11 (1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.336 (1.108\u0026ndash;1.612)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27 (1.026\u0026ndash;1.572)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.323 (1.073\u0026ndash;1.632)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.325 (1.076\u0026ndash;1.631)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.5 (1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.629 (1.354\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.398 (1.12\u0026ndash;1.745)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.529 (1.204\u0026ndash;1.943)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.525 (1.2\u0026ndash;1.938)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePYs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.25 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.62 (2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.863 (1.502\u0026ndash;2.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.469 (1.164\u0026ndash;1.854)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.548 (1.219\u0026ndash;1.965)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.549 (1.221\u0026ndash;1.965)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;20 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.36 (2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.172 (0.949\u0026ndash;1.447)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.063 (0.839\u0026ndash;1.347)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.135 (0.888\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.144 (0.896\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;30 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.01 (2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.594 (1.229\u0026ndash;2.068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.613 (1.187\u0026ndash;2.193)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.751 (1.283\u0026ndash;2.389)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.725 (1.266\u0026ndash;2.349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.35 (3.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.059 (0.758\u0026ndash;1.479)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.096 (0.736\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.207 (0.811\u0026ndash;1.797)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.187 (0.797\u0026ndash;1.768)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status in PYs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.25 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker, \u0026lt; 20 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.04 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.332 (1.063\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.201 (0.942\u0026ndash;1.531)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.234 (0.971\u0026ndash;1.569)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.238 (0.974\u0026ndash;1.572)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker, \u0026ge; 20 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.79 (2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.197 (0.978\u0026ndash;1.464)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.356 (1.042\u0026ndash;1.766)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.44 (1.109\u0026ndash;1.869)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.434 (1.106\u0026ndash;1.859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker, \u0026lt; 20 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.91 (2.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.732 (1.403\u0026ndash;2.137)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.392 (1.102\u0026ndash;1.759)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.509 (1.178\u0026ndash;1.932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.513 (1.18\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker, \u0026ge; 20 PYs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.2 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.406 (1.056\u0026ndash;1.872)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.496 (1.059\u0026ndash;2.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.665 (1.168\u0026ndash;2.372)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.623 (1.138\u0026ndash;2.315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 1 adjusted for age and sex\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 2 adjusted for Model 1\u0026thinsp;+\u0026thinsp;low income, heavy drinking, and regular physical activity\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eModel 3 adjusted for Model 2\u0026thinsp;+\u0026thinsp;presence of hypertension, diabetes mellitus, and hypercholesterolemia\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eAcronyms: PYs, pack-years; SE, standard error; OR, odds ratio; CI, confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe OR for current alcohol flushing during different types of physical activity was analyzed based on age- and sex-specific groups as shown in Table S1. After adjustment for household income, drinking amount, hypertension, DM, and hypercholesterolemia, discernible differences were not observed in the ORs. Although the unadjusted analysis showed a significant positive relationship between aerobic exercise and the prevalence of alcohol flushing in current alcohol flushers (OR 1.175, 95% CI 1.02\u0026ndash;1.353, p\u0026thinsp;=\u0026thinsp;0.0259), this relationship was lost after adjusting for multiple variables. Similarly, a significant relationship was not observed between the prevalence of alcohol flushing and other physical activities such as walking and strength training.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlcohol flushing affects all ethnic groups, and the estimated prevalence of alcohol flushing is 2\u0026ndash;29% in Caucasians, from 10%-80% in Native Americans, and relatively higher in East Asians than in other ethnic groups \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In a study using Korean Community Health Survey data, the prevalence was 34.8% \u003csup\u003e19\u003c/sup\u003e; alcohol flushing was shown to affect approximately 36\u0026ndash;50% of East Asians (Koreans, Chinese, and Japanese) in previous studies \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In the present study using a nationwide population-based data, the mean annual prevalence of alcohol flushing was 40.56%, similar to previous reports. The high prevalence of alcohol flushing among East Asians has been explained in several studies. Yokoyama et al. \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e reported that flushing responses after drinking a small amount of alcohol were mainly attributable to high acetaldehyde exposure and influenced by ALDH2 and ADH1B genotypes. Thus, this phenomenon is predominantly due to an inherited deficiency in the ALDH2 enzyme, and genetic factors associated with discrepancies in ALDH2 haplotypes between ethnic groups might lead to differences in prevalence \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. When measured based on sex and age, the prevalence of alcohol flushing was higher in males, which was consistent with a previous study \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Notably, in the present study, 11.94% of males and 12.66% of females were former flushers, and 5.04% of males and 5.29% of females transitioned into new-onset flushers. Jeon et al. \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e reported that, among participants in the Korean Community Health Survey, 4.1% were former flushers and 34.8% were current flushers. According to Yokoyama et al. \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, alcohol flushing decreases in intensity due to the development of tolerance to acetaldehyde in blood by higher-risk persons with a long or heavy drinking history. Acquired etiologies have been reported to include use of topical tacrolimus or liver-metabolized drugs, which can aid in alcohol catabolism \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the present study, smoking and physical activity were investigated as possible factors associated with alcohol flushing because they previously showed a statistical demographic difference among flushers, non-flushers, and non-drinkers. Consequently, smoking was a strong independent risk factor for alcohol flushing regardless of sex. Conversely, significant association was not found between alcohol flushing and physical activity. Furthermore, current smoking could increase alcohol flushing. Specifically, the risk of alcohol flushing was highest in current smokers with a smoking history\u0026thinsp;\u0026ge;\u0026thinsp;20 PYs. Although the adjusted OR for alcohol flushing did not proportionally correlate with PYs, further analysis showed a similar trend of higher alcohol flushing risk as smoking duration increased. In addition, current smokers with the same PYs had a higher OR for alcohol flushing than ex-smokers. Therefore, smoking status possibly has a greater effect on alcohol flushing than the duration of smoking. To the best of our knowledge, this is the first study in which a positive relationship between smoking and alcohol flushing was demonstrated; however, this correlation may have been postulated in other research. Reportedly, acetaldehyde can produce angiogenesis and telangiectasia through the expression of vascular endothelial growth factor (VEGF), as experimentally demonstrated in the chick embryo chorioallantoic membrane model \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, and nicotine provokes dry flushing \u003cem\u003evia\u003c/em\u003e vasodilation action of prostaglandins on vascular smooth muscle \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Flushers may have excessive acetaldehyde accumulation with low alcohol consumption, and such mechanisms could affect these individuals after minimal alcohol use \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Further biological research is needed to fully understand this relationship.\u003c/p\u003e \u003cp\u003eHowever, the results of the present study revealed that individuals who experience alcohol flushing usually consume alcohol less frequently and in smaller quantities compared with subjects who do not experience these symptoms, with most drinking\u0026thinsp;\u0026lt;\u0026thinsp;10 g of alcohol per day. This observation is in agreement with earlier studies that have shown people with inactive ALDH2 to be more likely to refrain from drinking \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBecause the focus in the present study was on self-reported alcohol flushing status, the accuracy of alcohol flushing status determined solely through self-reported symptoms compared with genetic testing cannot be ensured. Although the use of genetic variants may provide a more reliable measure, based on the available data, whether the responses obtained for alcohol flushing accurately reflect the deficiency of the alcohol-metabolizing enzyme cannot be determined \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e,\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In addition, although the alcohol flushing response is mainly explained due to an inactive ALDH2, with a sensitivity of 95.1% and specificity of 76.5% \u003csup\u003e30\u003c/sup\u003e, individuals exhibiting this response may have characteristics different from subjects with an active ALDH2. The flushing response can be influenced by factors other than an inactive ALDH2, such as environmental factors or other genetic traits \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Despite these limitations, the relationships were investigated in a nationally representative sample of Koreans, producing sufficient statistical power. Furthermore, relevant confounding factors were considered. Based on our current understanding, this is the first study in which the risk factors for alcohol flushing were evaluated using nationally representative data. In addition, the KNHANES survey includes central laboratory data and a standardized questionnaire administered by a trained examiner.\u003c/p\u003e \u003cp\u003eIn conclusion, the results of the present study demonstrated that current smoking could increase the risk of alcohol flushing, and current smokers with \u0026gt;\u0026thinsp;20 PYs of smoking history have a higher risk of alcohol flushing than non-smokers or ex-smokers.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData source and study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included data collected during the 2019 KNHANES, a survey designed to accurately assess national health and nutrition levels and a nationwide study of non‑institutionalized civilians that uses a stratified and multi‑stage probability sampling design with a rolling survey‑sampling model. A total of 8,110 participants completed this survey. Individuals \u0026lt; 20 years of age were excluded because this age group is not allowed to drink. After further exclusion of subjects with missing data on alcohol flushing or lifestyle, comorbidities, and laboratory results, 5,572 participants were available for analysis (2,472 males and 3,100 females; \u003cstrong\u003eFig. 1)\u003c/strong\u003e. The participants were stratified based on sex and age. A detailed description of the plan and operation of the survey is available on the KNHANES website (www. knhanes.kdca.go.kr).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants were questioned regarding their demographic variables, socioeconomic characteristics, and medical history. The subjects also answered questions regarding history of smoking, drinking, and physical activity through a self-administered questionnaire. Smoking status was categorized as current, ex-, or non-smoker. Ex-smokers had smoked in the past but did not smoke at the time of the interview. Period (years) and amount (in terms of packs) of smoking were included in the questions for ex- and current smokers. Pack-years (PYs) smoked were estimated by multiplying average daily cigarette smoking by smoking duration and was categorized as follows: \u0026lt; 10 PYs, 10–20 PYs, 20–30 PYs, or \u0026gt; 30 PYs. In addition, PYs were categorized in 20-year intervals with current smoking status.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, drinking status was categorized as current drinker, ex-drinker, or non-drinker. Data on frequency and amount of alcohol consumed per day were also collected and categorized based on daily consumption. The low-income category corresponded to the lowest quartile of annual household income. The educational level of the subject was classified as high if the participant had completed 10 years of education. Physical activity (aerobic, walking, and strength training) at the time of survey was also assessed. The participant’s height, weight, and waist circumference were measured. Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared (kg/m\u003csup\u003e2\u003c/sup\u003e). Waist circumference was measured parallel to the floor from the iliac crest in the resting position. Blood samples were collected from the antecubital vein of each participant after fasting for \u0026gt; 8 hours to measure concentrations of serum fasting plasma glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of alcohol consumption and alcohol flushing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlcohol consumption was assessed by questioning the subjects regarding their drinking behavior, including the average amount consumed and drinking frequency, in the year before the interview. A standard drink was defined as a single glass of liquor, wine, or the Korean traditional distilled liquor So-ju. One bottle of beer (355 mL) was counted as 1.6 standard drinks. The amount of alcohol consumed per standard drink was calculated as 10 g, and the average daily alcohol intake was assessed. An average consumption ≥ 30 g per day, a level of exposure associated with health risks, was considered heavy alcohol drinking. In the survey, the question on alcohol flushing status was divided into two parts. First, respondents were asked, “During the first 1-2 years when you started drinking alcohol, did you have facial flushing after consuming a small amount of alcohol?” Response options included 1) yes, 2) no, 3) non-applicable (ex. non-drinker), and 4) unknown or no response. Second, respondents were asked, \" Do you currently experience facial flushing after consuming a small amount of alcohol?\" Response options included 1) no, 2) occasionally, 3) frequently, and 4) always.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIndividuals were categorized as \"non-flusher\" if they never experienced alcohol flushing, \"new onset\" if they recently started experiencing alcohol flushing, \"former\" if they used to experience alcohol flushing but do not currently, and \"consistent flusher\" if they consistently experienced alcohol flushing in the past and present.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) to reflect the complex sampling design and sampling weights of the KNHANES and to provide nationally representative prevalence estimates. The mean ± standard error (SE) for continuous variables or the percentage for categorical variables was calculated. A one-way ANOVA or a Chi-square test was used to compare the groups. Multiple logistic regression analyses were used to estimate the prevalence odds ratio (OR) and 95% confidence interval (CI) of alcohol flushing. Several models were applied to evaluate the potential mediation effects of modifiable behaviors such as drinking or exercise as well as the effects of known risk factors such as comorbidities. Thus, model 1 was adjusted for age and sex; model 2 was further adjusted for household income, heavy drinking, and regular physical activity; model 3 was further adjusted for hypertension, diabetes mellitus (DM), and hypercholesterolemia. P \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Board of The Catholic Medical Center approved the study protocol (KC23ZASI0282).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.J.Y and J.H.L wrote the main manuscript text and G.N.L and K.D.H prepared statistical data. All authors especially Y.M.P reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWilkin, J. K. The red face: flushing disorders. \u003cem\u003eClin Dermatol\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 211-223 (1993). https://doi.org:10.1016/0738-081x(93)90057-j\u003c/li\u003e\n \u003cli\u003eSadeghian, A., Rouhana, H., Oswald-Stumpf, B. \u0026amp; Boh, E. Etiologies and management of cutaneous flushing: Nonmalignant causes. \u003cem\u003eJ Am Acad Dermatol\u003c/em\u003e \u003cstrong\u003e77\u003c/strong\u003e, 391-402 (2017). https://doi.org:10.1016/j.jaad.2016.12.031\u003c/li\u003e\n \u003cli\u003eEwing, J. A., Rouse, B. A. \u0026amp; Pellizzari, E. D. 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Facial flushing response to alcohol and the risk of esophageal squamous cell carcinoma: A comprehensive systematic review and meta-analysis. \u003cem\u003eCancer Epidemiol\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 31-38 (2016). https://doi.org:10.1016/j.canep.2015.10.011\u003c/li\u003e\n \u003cli\u003eShibuya, A., Yasunami, M. \u0026amp; Yoshida, A. 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The alcohol flushing response: an unrecognized risk factor for esophageal cancer from alcohol consumption. \u003cem\u003ePLoS Med\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, e50 (2009). https://doi.org:10.1371/journal.pmed.1000050\u003c/li\u003e\n \u003cli\u003eYu, C.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Association of low-activity ALDH2 and alcohol consumption with risk of esophageal cancer in Chinese adults: A population-based cohort study. \u003cem\u003eInt J Cancer\u003c/em\u003e \u003cstrong\u003e143\u003c/strong\u003e, 1652-1661 (2018). https://doi.org:10.1002/ijc.31566\u003c/li\u003e\n \u003cli\u003eMasaoka, H.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Alcohol consumption and bladder cancer risk with or without the flushing response: The Japan Public Health Center-based Prospective Study. \u003cem\u003eInt J Cancer\u003c/em\u003e \u003cstrong\u003e141\u003c/strong\u003e, 2480-2488 (2017). https://doi.org:10.1002/ijc.31028\u003c/li\u003e\n \u003cli\u003eYokoyama, A., Yokoyama, T., Kimura, M., Matsushita, S. \u0026amp; Yokoyama, M. Combinations of alcohol-induced flushing with genetic polymorphisms of alcohol and aldehyde dehydrogenases and the risk of alcohol dependence in Japanese men and women. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, e0255276 (2021). https://doi.org:10.1371/journal.pone.0255276\u003c/li\u003e\n \u003cli\u003eMizuno, Y.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e East asian variant of aldehyde dehydrogenase 2 is associated with coronary spastic angina: possible roles of reactive aldehydes and implications of alcohol flushing syndrome. \u003cem\u003eCirculation\u003c/em\u003e \u003cstrong\u003e131\u003c/strong\u003e, 1665-1673 (2015). https://doi.org:10.1161/CIRCULATIONAHA.114.013120\u003c/li\u003e\n \u003cli\u003eThomasson, H. R., Crabb, D. W., Edenberg, H. J. \u0026amp; Li, T. K. Alcohol and aldehyde dehydrogenase polymorphisms and alcoholism. \u003cem\u003eBehav Genet\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 131-136 (1993). https://doi.org:10.1007/BF01067417\u003c/li\u003e\n \u003cli\u003eJeon, S., Kang, H., Cho, I. \u0026amp; Cho, S. I. The alcohol flushing response is associated with the risk of depression. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 12569 (2022). https://doi.org:10.1038/s41598-022-16276-2\u003c/li\u003e\n \u003cli\u003eEng, M. Y., Luczak, S. E. \u0026amp; Wall, T. L. ALDH2, ADH1B, and ADH1C genotypes in Asians: a literature review. \u003cem\u003eAlcohol Res Health\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 22-27 (2007).\u003c/li\u003e\n \u003cli\u003eYokoyama, A., Yokoyama, T. \u0026amp; Omori, T. Past and current tendency for facial flushing after a small dose of alcohol is a marker for increased risk of upper aerodigestive tract cancer in Japanese drinkers. \u003cem\u003eCancer Sci\u003c/em\u003e \u003cstrong\u003e101\u003c/strong\u003e, 2497-2498; author reply 2499-2500 (2010). https://doi.org:10.1111/j.1349-7006.2010.01709.x\u003c/li\u003e\n \u003cli\u003eMilingou, M., Antille, C., Sorg, O., Saurat, J. H. \u0026amp; Lubbe, J. Alcohol intolerance and facial flushing in patients treated with topical tacrolimus. \u003cem\u003eArch Dermatol\u003c/em\u003e \u003cstrong\u003e140\u003c/strong\u003e, 1542-1544 (2004). https://doi.org:DOI 10.1001/archderm.140.12.1542-b\u003c/li\u003e\n \u003cli\u003eWeathermon, R. \u0026amp; Crabb, D. W. Alcohol and medication interactions. \u003cem\u003eAlcohol Res Health\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 40-54 (1999).\u003c/li\u003e\n \u003cli\u003eGu, J. W., Bailey, A. P., Sartin, A., Makey, I. \u0026amp; Brady, A. L. Ethanol stimulates tumor progression and expression of vascular endothelial growth factor in chick embryos. \u003cem\u003eCancer\u003c/em\u003e \u003cstrong\u003e103\u003c/strong\u003e, 422-431 (2005). https://doi.org:10.1002/cncr.20781\u003c/li\u003e\n \u003cli\u003eWilkin, J. K. Why is flushing limited to a mostly facial cutaneous distribution? \u003cem\u003eJ Am Acad Dermatol\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 309-313 (1988). https://doi.org:10.1016/s0190-9622(88)70177-2\u003c/li\u003e\n \u003cli\u003eMizoi, Y.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Relationship between facial flushing and blood acetaldehyde levels after alcohol intake. \u003cem\u003ePharmacol Biochem Behav\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 303-311 (1979). https://doi.org:10.1016/0091-3057(79)90105-9\u003c/li\u003e\n \u003cli\u003eCrabb, D. W., Matsumoto, M., Chang, D. \u0026amp; You, M. Overview of the role of alcohol dehydrogenase and aldehyde dehydrogenase and their variants in the genesis of alcohol-related pathology. \u003cem\u003eProc Nutr Soc\u003c/em\u003e \u003cstrong\u003e63\u003c/strong\u003e, 49-63 (2004). https://doi.org:10.1079/pns2003327\u003c/li\u003e\n \u003cli\u003eLivingston, M. D., Xu, X. \u0026amp; Komro, K. A. Predictors of Recall Error in Self-Report of Age at Alcohol Use Onset. \u003cem\u003eJ Stud Alcohol Drugs\u003c/em\u003e \u003cstrong\u003e77\u003c/strong\u003e, 811-818 (2016). https://doi.org:10.15288/jsad.2016.77.811\u003c/li\u003e\n \u003cli\u003eJee, Y., Park, S., Yuk, E. \u0026amp; Cho, S. I. Alcohol Consumption and Cigarette Smoking among Young Adults: An Instrumental Variable Analysis Using Alcohol Flushing. \u003cem\u003eInt J Environ Res Public Health\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e (2021). https://doi.org:10.3390/ijerph182111392\u003c/li\u003e\n \u003cli\u003eShin, C. M., Kim, N., Cho, S. I., Sung, J. \u0026amp; Lee, H. J. Validation of Alcohol Flushing Questionnaires in Determining Inactive Aldehyde Dehydrogenase-2 and Its Clinical Implication in Alcohol-Related Diseases. \u003cem\u003eAlcohol Clin Exp Res\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 387-396 (2018). https://doi.org:10.1111/acer.13569\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplemental File Note","content":"\u003cp\u003eSupplemental Table 1 and Supplemental Figure 1 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3807149/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3807149/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough facial flushing after drinking alcohol (alcohol flushing response) is common in Asian populations, the epidemiological features in a large sample have been investigated in only a few studies. This study assessed the epidemiologic characteristics and risk factors of alcohol flushing in a Korean population. This study was based on data collected during the 2019 Korea National Health and Nutrition Examination Survey (KNHANES). A total of 5,572 Korean adults was included in the general population group, and the alcohol flushing group consisted of 2,257 participants. Smoking and physical activity were evaluated as possible risk factors for alcohol flushing. The overall prevalence of alcohol flushing was estimated at 40.56% of the general population (43.74% in males and 37.4% in females),\u003cstrong\u003e \u003c/strong\u003eand the prevalence was highest at 60–69 years of age and lowest in individuals older than 80 years. Occasional, frequent, and persistent alcohol flushing was reported by 11.9%, 3.7%. and 15.0% of current flushers, among whom persistent flushers consumed the least amount of alcohol. The risk of alcohol flushing increased with current smoking status (adjusted OR 1.525, 95% CI 1.2–1.938), and smoking history of 20–29 pack-years (PYs) showed the highest association (adjusted OR 1.725, 95% CI 1.266–2.349) with alcohol flushing after adjustment for confounders. In contrast, significant association was not found between physical activity and alcohol flushing. The results demonstrated that current smoking could increase the risk of alcohol flushing, and that current smokers with a history of smoking \u0026gt; 20 PYs had a higher risk of alcohol flushing than non-smokers or ex-smokers.\u003c/p\u003e","manuscriptTitle":"Epidemiologic relationship between alcohol flushing and smoking in the Korean population: the Korea National Health and Nutrition Examination Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 19:56:15","doi":"10.21203/rs.3.rs-3807149/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-16T05:56:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-14T22:23:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5e9f9a71-9ac6-4cfd-9e7c-94b63b33342d","date":"2024-04-04T12:35:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-26T11:02:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6b37b8b6-31fe-4898-b172-2cdc19e849ea","date":"2024-02-15T07:54:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-13T07:53:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-06T11:37:58+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-12-27T06:37:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-27T06:35:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2023-12-26T08:42:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a73f0b52-4208-4c92-bbbd-7f913697cd82","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":27873053,"name":"Health sciences/Health care/Public health/Epidemiology"},{"id":27873054,"name":"Health sciences/Health care/Patient education"}],"tags":[],"updatedAt":"2024-07-02T06:08:03+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-02 19:56:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3807149","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3807149","identity":"rs-3807149","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}