Investigation of Nicotine Dependence in Young Male Soldiers After High-altitude Exposure: a Cross- Sectional Study

Investigation of Nicotine Dependence in Young Male Soldiers After High-altitude Exposure: a Cross- Sectional Study | 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 Investigation of Nicotine Dependence in Young Male Soldiers After High-altitude Exposure: a Cross- Sectional Study Zhong-Ming Xiao, Yu Chen, Ke Ma, Shao-Ying Li, Bo Men, Ting Yu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3922646/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study was conducted as a cross-sectional survey using a questionnaire to analyze "demographic characteristics, nicotine dependence, and self-efficacy for smoking cessation" among healthy young adult male soldiers who are presently residing and training in high-altitude for a minimum period of 3 months. A total of 3307 questionnaires were distributed between January and August 2023 in the high-altitude areas (altitude approximately 1700m-3700m).The participants in the survey exhibited an average age of 24.5 ± 3.7 years. A notable 82% of the respondents migrated to the high-altitude from regions with an altitude below 1500m, while 12.5% of smokers had resided and worked in the high-altitude area for a duration of ≥6 months. A substantial 89.6% of participants shared living spaces with smoking roommates; 60.1% initiated smoking before reaching the age of 19; 75% of smokers maintained a smoking habit spanning 1-9 years; a predominant 94.2% manifested very low to moderate nicotine dependence, with the remaining 5.8% presenting high to very high dependence. A distinct correlation emerged between factors such as BMI, duration of residence and work at high altitudes, daily smoking quantity (in the last 6 months), maximum daily smoking amount, roommate smoking status, and smoking duration, and the heightened status of nicotine dependence. An impressive 82.1% of respondents conveyed a resolute intent to cease smoking, with pivotal determinants such as educational attainment, daily smoking quantity (in the last month), maximum daily smoking amount, and smoking duration significantly influencing the cessation intention. Nicotine dependence persists in young adult male soldier smokers post high-altitude exposure, with the majority expressing a strong desire to quit. Therefore, our focus should be on bolstering their willingness to quit, crafting a tailored cessation program, and elevating the success rate of smoking cessation. Biological sciences/Physiology/Respiration Earth and environmental sciences/Environmental social sciences/Psychology and behaviour Health sciences/Health care/Quality of life High-altitude FTND Nicotine dependence Young Smokers INTRODUCTION Smoking is prevalent among the global youth population. However, it may prematurely lead to various diseases or death [ 1 ] . The primary addictive substance in cigarettes is "nicotine," a highly addictive substance found in tobacco along with 4,000 other chemicals. The continued use of tobacco products leads to addiction in a significant percentage of the population [ 2 ] . Consequently, nicotine dependence is globally recognized as an addictive disease and a major public health threat [ 3 ] . Despite this, nicotine dependence is a complex syndrome involving psychological, physiological, and personal behavioral processes [ 4 ] , prevalent in individuals of all ages, particularly young and middle-aged males, significantly impacting physical and mental health [ 5 ] . China, with an estimated 308 million smokers, is the world's largest consumer of tobacco products [ 1 , 6 ] . Smoking-related deaths in China exceed 2.4 million annually and are expected to rise in the coming decades [ 7 ] , likely due to "nicotine dependence," making complete smoking cessation challenging. Therefore, smoking-induced nicotine dependence poses a severe public health problem in China [ 8 ] . An estimated over 100 million individuals, primarily young and middle-aged, migrate from low to high altitudes annually [ 9 ] . These individuals engage in labor-intensive activities in high-altitude regions, including infrastructure projects, military assignments, or sports-intensive tourism like skiing, ice skating, and mountain climbing [ 10 ] . Large-scale population-based studies on smoking and nicotine dependence in these short- to medium-term high-altitude exposed populations are lacking. Presently, the Fagerström Test for Nicotine Dependence [ 11 ] (FTND, Supplementary, Table S1 ) stands as the most widely employed international tool for assessing nicotine dependence. The psychometric properties of the FTND have been validated among smokers in numerous countries [ 12 ] , and it is applicable to the Chinese population, having been used in studies on nicotine dependence in smokers [ 13 – 14 ] . Assessing nicotine dependence among smokers in high-altitude areas is vital for understanding this issue among Chinese smokers. Hence, we employed this scale to assess nicotine dependence among young adult male soldiers in the high-altitude region. Between January and August 2023, over 3000 electronic questionnaires were distributed in the high-altitude area of China (approximately 1700m-3700m above sea level). The goal was to collect information on basic socio-demographic characteristics, altitude migration, working hours, willingness to quit smoking, and daily smoking status of young adult male soldiers in the high-altitude area. The study aimed to investigate "nicotine dependence" and its influencing factors among young and middle-aged male smokers in the high-altitude region. This effort seeks to provide insights for the development of smoking cessation strategies tailored to high-altitude area smokers, ultimately promoting the health of this population. METHODOLOGY Ethics approval and consent to participate The experimental protocol, methods, survey instruments, and data collection procedures utilized in this study were approved by the Ethical Review Committee of the 920th Hospital of the Joint Logistics Support Force. Moreover, all research methods were conducted in strict adherence to applicable guidelines and regulations. Additionally, the dataset utilized in this study did not include any confidential health-related information pertaining to the participants. Study design and population A population-based cross-sectional study was undertaken, encompassing robust young adult male military personnel who had undergone health assessments at the 920th Hospital of the Joint Logistics Force during the period from November 2021 to December 2022.The participants were presently stationed and undergoing training in an elevated terrain (≥1500 m above sea level) for a minimum duration of 3 months. Subsequent to reading and signing an informed consent form, participants willingly engaged in a questionnaire survey, expressing their consent to provide information regarding their smoking habits and nicotine dependence for subsequent research endeavors. A total of 825 questionnaires were excluded due to missing information or irregularities, alongside an additional 1005 questionnaires from individuals who had never smoked or had quit smoking. In the conclusive analyses, a total of 1,477 valid questionnaires were incorporated (Supplementary，Figure S1). Data collection and quality control The questionnaire we designed comprised three parts. The first part primarily aimed to collect information on the demographic characteristics of the respondents. The second part included a questionnaire on nicotine dependence, utilizing the FTND questionnaire, a standardized instrument developed by the CDC/WHO. The FTND has demonstrated sufficient validity and reliability and has been widely employed in various settings [15-18] . The third part encompassed an Assessment of Smokers' Self-Efficacy to Quit Smoking questionnaire, a component within the widely used Smoking Cessation Clinic Questionnaire in China. We created an electronic questionnaire encompassing these three parts to electronically gather information, ensuring the accuracy and timeliness of this study. Variables The electronic questionnaire comprehensively incorporates inquiries concerning demographic features, encompassing age, ethnicity, marital status, educational attainment, height, weight, mean daily smoking quantity over the preceding month and the last half-year, the smoking status of cohabitants, age at the initiation of smoking, the duration of smoking, along with additional details. As the survey predominantly focuses on youthful military personnel who engage in smoking activities within high-altitude regions, supplementary fundamental data was gathered. This encompassed "current altitude in the high-altitude area, duration of employment in the high-altitude area, original birthplace altitude, and altitude migration difference (altitude in the high-altitude area - original birthplace altitude, in meters)."Simultaneously, data pertaining to smoking behavior was amassed based on the six standard questions outlined in the FTND (Supplementary ，Table S1), encompassing inquiries such as "1. How soon after awakening do you engage in your initial cigarette consumption? 2. What quantity of cigarettes do you consume on a daily basis? 3. Do you encounter challenges in refraining from smoking in smoke-free public spaces? 4. Which cigarette proves most challenging to relinquish during cessation attempts? 5. Does the frequency of smoking within the initial hour post-awakening surpass that of other periods in the day? 6. Do you engage in smoking when indisposed, spending the majority of the day confined to bed?" Via this assessment, the respondents' nicotine dependence was ascertained, yielding a composite score spanning from 0 to 10. Scores of 0-2 denote exceedingly low nicotine dependence, 3-4 denote low dependence, 5 denotes moderate dependence, 6-7 denote high dependence, and 8-10 denote very high dependence (Supplementary, Table S2). For subsequent evaluation of nicotine dependence risk factors, we categorized 0≤FTND≤5 as indicative of very low to moderate dependence, and 6≤FTND≤10 as suggestive of high to very high dependence. Concurrently, we evaluated smokers' self-efficacy in the cessation of smoking by employing the subsequent inquiries: 1. Do you harbor earnest intentions of terminating smoking within the ensuing month? 2. How formidable do you appraise the challenge of smoking cessation to be (rated on a scale from 0-10, with elevated scores signifying diminished confidence)? 3. On a scale spanning 0-10, what degree of assurance do you possess in abstaining from smoking henceforth? 4. How frequently have you undertaken earnest endeavors to desist from smoking? 5. When did you last embark on a sincere endeavor to quit smoking? 6. Throughout your preceding endeavor to quit smoking, what was the duration during which you successfully refrained from smoking? 7. Which methodologies did you employ during that specific attempt to quit smoking? The objective of this assessment is to gauge the self-efficacy of smokers in the cessation endeavor. Data analysis Descriptive statistics were conducted for continuous and categorical variables, expressed as mean (Mean±SD), frequency, and percentage, respectively. Comparisons between count data in categorical variables utilized the four-cell χ2 test and the R×C table χ2 test to assess the population characteristics of smokers with very-low-moderate dependence on nicotine (0≤FTND≤5) and high-very-high dependence (6≤FTND≤10). Fisher's exact probability method was employed when the theoretical frequency T<1. Multivariate logistic regression models were applied to compare potential confounders under nicotine dependence status between the two groups. Statistical analyses were performed using SPSS V.26.0 (IBM, Armonk, New York, USA) software for data processing, with P<0.05 (two-tailed) considered statistically significant. RESULTS A total of 3307 questionnaires were distributed between January and August 2023 in the high-altitude areas (altitude approximately 1700m-3700m). Out of these, 2482 valid questionnaires were returned, resulting in a response rate of approximately 75.1% for this survey. Among the respondents, 1005 (40.5%) were either never smokers or had quit smoking, while 1477 (59.5%) were current smokers. Subsequent analyses were exclusively conducted on the group of current smokers. A risk assessment of nicotine dependence for male current smokers indicated that 937 (63.4%) had very low dependence, 373 (25.3%) had low dependence, 82 (5.6%) had moderate dependence, 74 (5%) had high dependence, and 11 (0.7%) had very high dependence (Supplementary ，Table S2). Supplementary，Table S3 provides a breakdown of the percentage of scores for each FTND item. Participant demographic characteristics The average age of the soldiers who were smoking was 24.5±3.7 years old. Out of the 1477 smokers, 1229 (83.2%) were Han Chinese, and 1452 (98.3%) were unmarried males with high school education or above. Among them, 1399 (94.7%) worked at altitudes between 1500 and 3500 m. Out of these, 1211 migrated to the high-altitude from places with altitudes less than 1500m, and the majority (1250, 84.6%) migrated from places with altitudes between 1500 and 3500 m. Additionally, 1293(87.5%) smokers had worked at the high-altitude for 3-6 months, and 184(12.5%) smokers had worked there for half a year or more. Over 45% of these smokers had a "daily maximum" of smoking. Smokers' maximum daily cigarette consumption, average daily cigarette consumption in the last month, and average daily cigarette consumption in the last 6 months were 5-14 cigarettes. Furthermore, 1324(89.6%) had a roommate who smoked, 888 (60.1%) of these smokers started smoking at ≤19 years of age, and 1,108(75%) smokers smoked between 1-9 years of age. Additional statistical characteristics of each demographic and smoking behavior are detailed in Table 1. Table1. The smoking behavior and demographic characteristics of current smokers Variable Mean±SD/N （%） Age 24.5±3.7 FTND 0-5 1.9±1.5 6-10 6.6±0.9 Nation Minority nationality 248（16.8） Han 1229（83.2） Marriage status Unmarried 1242（84.1） Married 229（15.5） Divorce 6（0.4） Education Junior high school 25（1.7） High school/Technical secondary school 679（46.0） Junior college 639（43.3） Bachelor's degree or above 134（9.0） BMI (kg/m 2 ) ≤21.7 576（39.0） >21.7 901（61.0） Work Altitude(m) 1500<h≤3500 1399（94.7） 3500<h≤5500 78（5.3） Hometown Altitude(m) ≤1500 1211（82.0） 1500<h≤3500 261（17.7） 3500<h≤5500 5（0.3） Altitude difference(m) ≤1500 213（14.4） 1500<h≤3500 1250（84.6） 3500<h≤5500 14（1.0） Working time (MTh) 3<T≤6 1293（87.5） 6<T≤12 43（2.9） 1224 99（6.7） Cigarettes per day (in the last 1 month) 1-4 502（34.0） 5-14 680（46.0） 15-24 145（9.8） 25-49 73（4.9） ≥50 77（5.2） Cigarettes per day (in the last 6 months) 1-4 482（32.6） 5-14 685（46.4） 15-24 155（10.5） 25-49 40（2.7） ≥50 115（7.8） Maximum cigarettes per day 1-4 320（21.7） 5-14 743（50.3） 15-24 332（22.5） 25-49 56（3.8） ≥50 26（1.8） Roommates smoking status No 153（10.4） Yes 1324（89.6） start smoking(age) ≤19 888（60.1） 20≤Age≤29 560（37.9） 30≤Age≤39 29（2.0） Smoking duration(years) <1 161（10.9） 1≤y≤9 1108（75.0） 10≤y≤19 203（13.7） 20≤y≤39 5（0.3） MTh: month. Results of univariate and multivariate analyses of nicotine dependence in current smokers In the analysis of smokers in the High-altitude areas, changes in marital status were found to significantly impact nicotine dependence. 94.9% of unmarried men were very low-moderately dependent on nicotine, while about 5.1% of unmarried men were highly-extremely dependent on nicotine. In contrast, 9.2% of married men were highly-extremely dependent on nicotine. Surprisingly, divorced men were 16.7% more likely to be highly-very highly dependent on nicotine (P=0.018). Regarding BMI, logistic regression analysis revealed (Supplementary，Figure S2) that when BMI≥21.7 (P=0.048, ROC=1.88, 95% CI: 1.102-4.231), it was a significant influencing factor for smokers to become dependent on nicotine. Multifactorial logistic regression analysis found that BMI (P=0.048, OR=1.88, 95% CI:1.01-3.51), working hours after high altitude exposure (P=0.033, OR=2.91, 95% CI: 1.37-6.19), average daily smoking (in the last 6 months) (P=0.031, OR=6.626, 95% CI: 1.04-37.78), and the maximum amount of cigarettes smoked in a single day (P<0.01, OR=17.90, 95% CI: 3.41-94.08), roommate smoking status (P=0.044, OR=8.71, 95% CI: 1.06-67.95), and smoking duration (P=0.029, OR=61.90, 95% CI: 2.26-1692.79) were significantly correlated with nicotine hyperdependence status. While marital status (P=0.018) and age of smoking initiation (P<0.01) showed a tendency for a relationship with nicotine high dependence status, they were not statistically significant in multifactor logistic regression analysis (Table 2). Table2. Univariate and multivariate analysis of smoking behavior and demographic characteristics based on FTND classification. Variable FTND Univariate analysis Multivariate analysis very low to moderate (N, %) high-very high (N, %) χ2 P OR（95% CI） P Nation 0.665 0.454 - - Minority nationality 231（93.1） 17（6.9） Han 1161（94.5） 68（5.5） Education 3.26 0.321 - - Junior high school 24（96.0） 1（4.0） High school/Technical secondary school 645（95.0） 34（5.0） Junior college 601（94.1） 38（5.9） Bachelor's degree or above 122（91.0） 12（9.0） Work Altitude(m) 0.570 0.449 - - 1500<h≤3500 1320(94.4） 79(5.6) 3500<h≤5500 72(92.3) 6(7.7) Hometown Altitude(m) 0.905 0.540 - - ≤1500 1144(94.5) 67(5.5) 1500<h≤3500 243(93.1) 18(6.9) 3500<h≤5500 5(100) 0 Altitude difference(m) 1.310 0.465 - - ≤1500 198(93.0) 15(7.0) 1500<h≤3500 1181(94.5) 69(5.5) 3500<h≤5500 13(92.9) 1(7.1) Marriage status 7.644 0.018 0.943 Unmarried 1179（94.9） 63（5.1） Ref - Married 208（90.8） 21（9.2） 1.05(0.51-2.16) 0.891 Divorce 5（83.3） 1（16.7） 1.52(0.12-19.65) 0.750 BMI (kg/m 2 ) 13.683 21.7 833(92.5) 68(7.5) 1.88(1.01-3.51) 0.048 Working time (MTh) 24.214 <0.01 0.033 3<T≤6 1234(95.4) 59(4.6) Ref - 6<T≤12 39(90.7) 4(9.3) 0.87(0.22-3.49) 0.845 1224 83(83.8) 16(16.2) 2.91(1.37-6.19) 0.005 Cigarettes per day (in the last 1 month) 89.072 <0.01 0.899 1-4 498(99.2) 4(0.8) Ref - 5-14 650(95.6) 30(4.4) 1.25(0.30-5.15) 0.755 15-24 124(85.5) 21(14.5) 1.34(0.27-6.62) 0.723 25-49 60(82.2) 13(17.8) 1.95(0.37-10.34) 0.435 ≥50 60(77.9) 17(22.1) 1.93(0.34-10.79) 0.455 Cigarettes per day (in the last 6 months) 103.919 <0.01 0.031 1-4 479(99.4) 3(0.6) Ref - 5-14 658(96.1) 27(3.9) 1.98(0.39-9.97) 0.407 15-24 136(87.7) 19(12.3) 2.70(0.46-15.75) 0.270 25-49 32(80.0) 8(20.0) 10.19(1.62-64.02) 0.013 ≥50 87(75.7) 28(24.3) 6.26(1.04-37.78) 0.045 Maximum cigarettes per day 140.533 <0.01 <0.01 1-4 317(99.1) 3(0.9) Ref - 5-14 728(98.0) 15(2.0) 1.02(0.31-4.65) 0.795 15-24 297(89.5) 35(10.5) 4.45(1.13-17.46) 0.032 25-49 38(67.9) 18(32.1) 13.40(3.13-57.35) 0.000 ≥50 12(46.2) 14(53.8) 17.90(3.41-94.08) 0.001 Roommates smoking status 8.198 <0.01 0.044 No 152(99.3） 1(0.7) Ref - Yes 1240(93.7) 84(6.3) 8.47(1.06-67.95) 0.044 start smoking(age) 8.632 <0.01 0.464 ≤19 824(92.8) 64(7.2) Ref - 20≤Age≤29 540(96.4) 20(3.6) 0.80(0.42-1.50) 0.482 30≤Age≤39 28(96.6) 1（3.4） 0.29(0.03-2.84) 0.286 Smoking duration（years） 40.877 <0.01 0.029 <1 160(99.4) 1(0.6) Ref - 1≤y≤9 1054(95.1) 54(4.9) 3.60(0.43-29.75) 0.235 10≤y≤19 176(86.7) 27(13.3) 6.85(0.76-61.92) 0.087 20≤y≤39 2(40.0) 3(60.0) 61.90(2.26-1692.79) 0.015 OR: Odds Ratios derived from multinomial regression; Ref: Reference; MTh: month. Demographic characteristics of current smokers' smoking cessation self-efficacy We conducted a survey on smoking cessation self-efficacy among young adult males who were currently smoking and found that 1,409 (95.4%) of them believed that there was no good way to quit. Additionally, 1,213(82.1%) had a clear intention to quit, 915(61.9%) had tried to quit at least once in the past month, 551(37.4%) had made at least two serious attempts to quit, 609(41.2%) had good confidence in quitting, and 267(18.1%) had remained non-smokers for at least one month since their last quit. Furthermore, 1,120 (75.8%) smokers did not think it was very difficult to quit smoking (Table 3). Table3. Characteristics of smoking cessation behavior among current smokers Variable Percentage of responses N（%） What method did you use to quit smoking at that time？ Never 459（31.1） No methods 950（64.3） Seek help 68（4.6） Are you willing to quit smoking？ Yes 1213（82.1） No 264（17.9） When was the last time you seriously quit smoking Never？ 562（38.1） 12 months 258（17.5） How many times have you tried to seriously quit smoking Confidence in never smoking again？ ≤1 times 926（67.2） 2-5 times 500（33.9） 6-10 times 51（3.5） ≤6 868（58.8） >6 609（41.2） When you last quit smoking, how long were you able to stay smoke-free？ Never 417（28.2） 6 357（24.2） Univariate and multivariate analysis of self-cessation efficacy among current smokers We found that those who had a "willingness to quit" had a relatively high level of education (P=0.018). Additionally, we observed that the willingness to quit was lower among those with higher average daily cigarette consumption in the last month (P=0.006) and maximum cigarette consumption in a single day (P=0.001). The willingness to quit was also weaker as the age of the smokers increased (P=0.004), and the proportion of those who were highly dependent on nicotine (P=0.006) was higher among those who were reluctant to quit smoking. In a multifactorial binary logistic regression analysis, we found that "smokers' education level (P=0.048, OR=2.84, CI: 1.18-6.81), average daily cigarette consumption (in the last month) (P=0.018, OR=0.42, CI: 0.25-0.72), maximum cigarette consumption in a single day (P=0.012, OR=0.29, CI: 0.11-0.76), and smoking age (P=0.013, OR=1.93, CI: 1.28-2.91)" may have an effect on the willingness to quit smoking (Table 4). Table4. Univariate and multivariate analysis of smoking behavior and demographic characteristics based on based on self-efficacy in quitting smoking Variable Do you seriously plan to quit smoking within the next month？ Univariate analysis Multivariate analysis Yes No χ2 P OR（95% CI） P Nation 0.618 0.468 - - Minority nationality 208（83.9） 40（16.1） Han 1005（81.8） 224（18.2） Marriage status 0.226 0.911 - - Unmarried 1018（82） 224（18） Married 190(83) 39(17) Divorce 5(83.3) 1(16.7) BMI (kg/m 2 ) 0.000 1 - - ≤21.7 473(82.1) 103(17.9) >21.7 740(82.1) 161(17.9) Work Altitude(m) 1147(82.0) 252(18.0) 0.348 0.650 - - 1500<h≤3500 66(84.6) 12(15.4) 3500<h≤5500 Hometown Altitude(m) 2.830 0.201 - - ≤1500 990(81.8) 221(18.2) 1500<h≤3500 220(84.3) 41(15.7) 3500<h≤5500 3(60) 2(40) Altitude difference(m) 1.184 0.560 - - ≤1500 180(84.5) 33(15.5) 1500<h≤3500 1022(81.8) 228(18.2) 3500<h≤5500 11(78.6) 3(21.4) Working time(MTh) 4.571 0.206 - - 3<T≤6 1056(81.7) 237(18.3) 6<T≤12 34(79.1) 9(20.9) 1224 89(89.9) 10(10.1) Cigarettes per day (in the last 6 months) 8.786 0.066 - - 1-4 408(84.6) 74(15.4) 5-14 565(82.5) 120(17.5) 15-24 117(75.5) 38(24.5) 25-49 34(85) 6(15) ≥50 89(77.4) 26(22.6) Roommates smoking status 2.681 0.118 - - No 133(86.9) 20(13.1) Yes 1080(81.6) 244(18.4) start smoking(age) 1.467 0.475 - - ≤19 721(81.2) 167(18.8) 20≤Age≤29 467(83.4) 93(16.6) 30≤Age≤39 25(86.2) 4(13.8) Education 9.863 0.018 0.048 Junior high school 16(64) 9(36) Ref - High school/Technical secondary school 555(81.7) 124(18.3) 2.30(0.96-5.51) 0.061 Junior college 539(84.4) 100(15.6) 2.84(1.18-6.81) 0.019 Bachelor's degree or above 103(76.9) 31(23.1) 1.87(0.73-4.80) 0.195 Cigarettes per day (in the last 1 moth) 14.37 0.006 0.018 1-4 425(84.7) 77(15.3) Ref - 5-14 565(83.1) 115(16.9) 0.90(0.62-1.31) 0.579 15-24 105(72.4) 40(27.6) 0.42(0.25-0.72) 0.001 25-49 60(82.2) 13(17.8) 0.86(0.43-1.70) 0.655 ≥50 58(75.3) 19(24.7) 0.71(0.37-1.37) 0.312 Maximum cigarettes per day 17.90 0.001 0.012 1-4 274(85.6) 46(14.4) Ref - 5-14 603(81.2) 140(18.8) 0.71(0.47-1.07） 0.100 15-24 277(83.4) 55(16.6) 1.02(0.60-1.72） 0.947 25-49 46(82.1) 10(17.9) 1.34(0.57-3.16） 0.507 ≥50 13(50) 13(50) 0.29(0.11-0.76) 0.012 Smoking duration (years) 12.90 0.004 0.013 <1 121(75.2) 40(24.8) Ref - 1≤T≤9 928(83.8) 180(16.2) 1.93(1.28-2.91) 0.002 10≤T≤19 162(79.8) 41(20.2) 1.66(0.96-2.86) 0.069 20≤T≤39 2(40) 3(60) 0.75(0.10-5.78) 0.782 FTND 8.179 0.006 0.117 0-5 1153(82.8) 239(17.2) Ref - 6-10 60(70.6) 25(29.4) 0.63(0.35-1.12) 0.117 OR: Odds Ratios derived from multinomial regression; Ref: Reference; MTh: month. DISCUSSION Currently, there have been studies on nicotine dependence among young smokers in China, but few studies have focused on the assessment of nicotine dependence and self-efficacy of quitting smoking among smokers in the high-altitude-exposed population. The present study aimed to investigate the nicotine dependence and willingness to quit among young adult male soldier smokers after high-altitude exposure. Female smokers were not included in this study, as previous studies have shown that smoking is overwhelmingly male, with a prevalence almost 10 times that of females [19] . Among the young adult male soldiers we surveyed, there were a total of 1,477 active smokers, with a smoking prevalence of 59.5%, which is higher than the results of the 2018 China Adult Tobacco Epidemiological Survey, which reported that the smoking prevalence among people ≥15 years of age was 26.6%, of which 50.5% were males [20] . A similar situation has been observed in other non-developed countries [21] , and this discrepancy has been observed in many Western countries before the tobacco industry targeted females [22] . Our study highlights the prevalence of smoking in the population and also reflects the importance and necessity of preventing the harms of smoking in young adults. Based on the FTND item scores, we found that 63.4%, 25.3%, 5.6%, 5%, and 0.7% of the young soldiers' population had very low, low, moderate, high, and very high nicotine dependence after high-altitude exposure, respectively. Although the psychometric properties of the FTND have been questioned in a small number of cases, it has become a useful tool associated with the successful validation of smoking cessation and nicotine dependence [23-25] . In our study, the mean overall FTND score was 2.1±1.8, while the mean FTND score for smokers with very low-moderate nicotine dependence was 1.9±1.5, and for smokers with high-very high nicotine dependence was 6.6±0.9. Although the mean overall FTND score was similar to those reported in Europe, such as in Germany and Norway(2.8), Spain and the Netherlands(2.9), England and Denmark(3.0), Italy(3.1), and France(3.4) [26] , the mean FTND score of highly-very highly nicotine-dependent individuals(6.6±0.9) was much higher than in these countries, such as Poland(3.6), Austria(3.6), Sweden(4.6), and the United States(4.3) [26] , indicating the urgent need to address high nicotine dependence for smoking cessation in China. Achieving high cessation rates in China will be a challenge, and many smokers may need and benefit from treatment. The FTND is associated with smoking cessation self-efficacy, and as FTND scores rise, smokers' confidence in quitting decreases. Notably, perhaps because of their confidence in their success, smokers with very low-moderate nicotine dependence were the most likely to take action to quit, seek help, and be willing to make multiple attempts to quit. Additionally, BMI exhibited a significant correlation with nicotine dependence, and our study suggests that young adult soldiers who smoke in high-altitude areas with high to very high nicotine dependence are more likely to have a BMI≥21.7. This may be related to living in high-altitude areas where physical activity is reduced, weight gain is common, and there is frequent congregation and smoking. Although studies have indicated a negative correlation between BMI and smoking intensity [27-28] , our results did not show a significant negative correlation between smoking status and BMI. The proportion of smokers with high-very high nicotine dependence increased with longer working time in the high-altitude region. This could be related to their challenges in accessing information about tobacco hazards after high-altitude exposure, lack of communication with loved ones, living in a different place, and feeling lonely. Some studies suggest that smokers are more likely to develop smoking-related psychological issues in negative environments, such as anxiety, loneliness, and stress, and addressing smokers' negative beliefs may enhance smoking cessation rates [29] . Additionally, the average daily cigarette consumption in the last 6 months and the maximum daily cigarette consumption are closely related to the degree of nicotine dependence. The degree of dependence on nicotine increases with higher cigarette consumption. Studies by Placzek and Dwyer et al [30-31] have shown that long-term exposure to high-dose nicotine may result in permanent changes in the brain, leading to addiction. This aligns with the notion that prolonged exposure to large quantities of nicotine contributes to higher levels of dependence. We also observed that whether co-residents smoked significantly affected smokers' nicotine dependence levels. Prolonged exposure to secondhand smoke may impede smoking cessation through physiological and psychosocial mechanisms [32] . Living with other smokers may make it more challenging for smokers planning to quit due to social norms, peer pressure, and camaraderie [33] . Being in smoking scenarios is associated with increased odds of smoking and relapse [34-35] , all contributing to smokers' high-maximal nicotine dependence and difficulties in quitting. The development of high nicotine dependence is closely linked to the age of smokers, strongly associated with early smoking initiation. Studies indicate that 80% of smokers start smoking at or before the age of 18 years [36] , leading to at least 20-25% of smokers becoming dependent on daily smoking [37-38] . Early smoking also results in a relatively longer smoking duration, contributing to higher nicotine dependence among smokers exposed to high doses of nicotine over an extended period. Our examination of smokers' self-efficacy to quit smoking, specifically "whether they seriously plan to quit smoking in the next month," revealed a strong association between smokers' self-efficacy to quit smoking and their education level. This association may stem from the fact that higher education levels correlate with greater awareness of the dangers of nicotine, heightened health consciousness, and a greater willingness to attempt smoking cessation in the future. In contrast, less educated smokers may lack sufficient health knowledge and awareness of nicotine-related harms, leading to reduced responsiveness to public tobacco control interventions [39] . However, we also observed a negative correlation between smokers' "average daily cigarette consumption in the last month, maximum daily cigarette consumption, and smoking age" and their self-cessation efficacy. This aligns with findings indicating that long-term heavy smoking is associated with an increased risk of nicotine dependence [36] . This correlation may be explained by the tendency of smokers who engage in heavy, prolonged smoking without experiencing smoking-related illnesses to be more resistant to quitting and, therefore, less willing to make cessation attempts. A crucial limitation inherent in this study is its cross-sectional design, rendering it incapable of establishing a direct causal relationship between the extent of nicotine dependence and the identified risk factors. Another constraint lies in the inability to conduct follow-ups with smokers to investigate subsequent smoking cessation. Furthermore, the questionnaire utilized in our study relied on data obtained through an electronic survey, where individuals self-reported their smoking status. The absence of biochemical validation, such as testing for exhaled carbon monoxide or urinary cotinine, has the potential to introduce bias to the study results. Moreover, the predominant composition of the study population comprised young males with an average age of 24.5±3.7 years. Subsequent investigations should encompass diverse age groups and incorporate females residing in high-altitude regions to foster a more comprehensive comprehension of nicotine dependence among smokers in this locale, thereby aiding in the development of more efficacious smoking cessation strategies. CONCLUSION Nicotine dependence remained prevalent among young adult male soldier smokers after high-altitude exposure. The degree of dependence was associated with factors such as smoker's BMI, time spent living and working in the high-altitude region, age of smoker, cohabitant smoking status, maximal smoking in a single day, and average daily smoking in the last 6 months. The majority (83.9%) of smokers expressed a clear intention to quit, while factors like smokers' education level, average daily cigarette consumption (in the last 1 month), maximum daily cigarette consumption, and smoking age may influence the intention to quit. This study establishes a foundation for researching factors related to nicotine dependence and smoking cessation self-efficacy among young male soldier smokers after high-altitude exposure. It also provides a rationale for tobacco control in the high-altitude region and efforts to enhance smokers' self-efficacy in quitting smoking. ABBREVIATIONS FTND Fagerström Test for Nicotine Dependence BMI Body Mass Index MTh Month Ref Reference OR Odds Ratios Declarations Data availability The datasets generated and/or analyzed during the current study are not publicly available due to military secrecy. However, they are available from the corresponding author (email: [email protected] ) upon reasonable request. AUTHORS’ CONTRIBUTIONS The paper's structure was crafted by Zhong-ming Xiao, Yu Chen, and Ke Ma, who also undertook data analysis, interpretation, and manuscript composition. Wen-ke Cai, Xin Zhang, and Gong-hao He played pivotal roles in gathering questionnaire data, refining interpretations, and editing the final draft. Shao-ying Li, Ting Yu, Bo Men, and Zi-xiong Nian coordinated the data organization. Every author participated in the meticulous revision and ultimate approval of the manuscript. FUNDING This study received support from the Young and Middle-aged Academic and Technical Leaders Reserve Talent Project of Yunnan Province (No.202405AC350037) and the Young and Middle-aged Academic and Technical Leaders Reserve Talent Project of Yunnan Province (No. 2019HB045). COMPETING INTERESTS No conflicts of interest exist. SUPPLEMENTARY MATERIAL Table S1, Table S2, Table S3，Figure S1 and Figure S2 are detailed in the Word and PDF document of the supplementary material. References Li Q, Hsia J, Yang G. Prevalence of smoking in China in 2010. N Engl J Med. 2011;364(25):2469-2470. doi:10.1056/NEJMc1102459. American Society of Addiction Medicine. Public Policy Statement on Nicotine Addiction and Tobacco. https://www.asam.org/advocacy/find-a-policy-statement/view-policy-statement/public-policy-statements/2011/ 12/15/nicotine-addiction-and-tobacco. Accessed 15 June 2017. Subedi, K, Shrestha, A, Bhagat, T. Assessment of nicotine dependence among tobacco users visiting outreach programs in Dharan, Nepal: a cross-sectional study. BMC Public Health. 2021; 21 (1): 1515. doi: 10.1186/s12889-021-11535-9 Shadel, WG, Shiffman, S, Niaura, R, et al. Current models of nicotine dependence: what is known and what is needed to advance understanding of tobacco etiology among youth. DRUG ALCOHOL DEPEN. 2000; 59 Suppl 1 S9-22. doi: 10.1016/s0376-8716(99)00162-3. Nicotine Addiction in Young People NEW ENGL J MED. 1995; 333 (15): 1018-1018. doi: 10.1056/nejm199510123331526. Chinese Center for Disease Control and Prevention.China adult tobacco survey 2018 fact sheet 2018. GBD 2019 Tobacco Collaborators.Spatial,temporal,and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019:a systematic analysis from the global burden of disease study 2019.Lancet 2021;397:2337–60. Yang, T, Shiffman, S, Rockett, IR, et al. 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Graham,H.(1996).Smoking prevalence among women in the European Community 1950–1990.Social Science and Medicine, 43,243–254.doi:10.1016/0277-9536(95)00369–X. Fagerström,K.O.,Kunze,M.,Schoberger,R.,Breslau,N.,Hughes,J.R.,Hurt,R.D.,et al.(1996).Nicotine dependence versus smoking prevalence:Comparisons among countries and categories of smokers.Tobacco Control,5,52–56.doi:10.1136/tc.5.1.52. Haddock,C.K.,Lando,H.,Klesges,R.C.,Talcott,G.W.,&Renaud,E.A.(1999).A study of the psychometric and predic tive properties of the Fagerstrom Test for Nicotine Dependence in a population of young smokers.Nicotine and Tobacco Research,1,59 –66.doi:10.1080/ 14622299050011161. Piper,M.E.,McCarthy,D.E.,&Baker,T.B.(2006).Assessing tobacco dependence:A guide to measure evaluation and selec tion.Nicotine and Tobacco Research,8,339–351.doi:10.1080/14622200600672765. Fagerström,K.,&Furberg,H.(2008).A comparison of the Fag erström Test for Nicotine Dependence and smoking prevalence across countries.Addiction,103,841–845.doi:10.1111/j.1360–0443.2008.02190.x. Oh HS, Seo WS. The compound relationship of smoking and alcohol consumption with obesity. Yonsei Med J. 2001;42(5):480–7 Heishman SJ. Behavioral and cognitive effects of smoking: relationship to nicotine addiction. Nicotine Tob Res. 1999;1 Suppl 2:S143–7. discussion S65-6. BORLAND R, YONG H H, BALMFORD J, et al. Do riskminimizing beliefs about smoking inhibit quitting？Findings from the international tobacco control （ITC） four-country survey［J］.Prev Med，2009，49（2/3）：219-223. Placzek AN, Zhang TA, Dani JA. Age dependent nicotinic influences over dopamine neuron synaptic plasticity. Biochem Pharmacol 2009;78:686-92. Dwyer JB, McQuown SC, Leslie FM. The dynamic effects of nicotine on the developing brain. Pharmacol Ther 2009;122:125-39. Mai, ZM, Ho, SY, Wang, MP, et al. Living with Smoker(s) and Smoking Cessation in Chinese Adult Smokers: Cross-Sectional and Prospective Evidence from Hong Kong Population Health Survey. Int J Environ Res Public Health. 2018; 15 (1): doi: 10.3390/ ijerph 15010074. Tai, Z.X.; Tao, S.P.; Hung, Y.J. Peer influence and smoking relapse among active-duty military personnel in Taiwan. Tob. Control 2011, 20, 444–445. World Health Organization. Smoke-Free Movies: From Evidence to Action, 3rd ed.; WHO: Geneva, Switzerland, 2009. Wong, D.C.; Chan, S.S.; Ho, S.Y.; Fong, D.Y.; Lam, T.H. Predictors of intention to quit smoking in Hong Kong secondary school children. J. Public Health 2009, 32, 360–371. The nature of nicotine addiction. In: Lynch BS, Bonnie RJ, eds. Growing up tobacco free — preventing nicotine addiction in children and youths. Washington, DC: National Academy Press, 1994:28-68. Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the future: national survey results on drug use, 1975–2006. Bethesda, MD: National Institute on Drug Abuse, 2007. (NIH publication no.07-6205.) Kandel D, Schaffran C, Griesler P, Samuolis J, Davies M, Galanti R. On the measurement of nicotine dependence in adolescence: comparisons of the mFTQ and a DSM-IV-based scale. J Pediatr Psychol 2005;30:319-32. Xu, Y, Xu, S, Wu, Q, et al. Analysis of nicotine dependence among daily smokers in China: evidence from a cross-sectional study in Zhejiang Province. BMJ Open. 2022; 12 (10): e062799. doi: 10.1136/bmjopen-2022-062799. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterialforallfigures.pdf Supplementarymaterialforallforms.docx Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-3922646","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":274338714,"identity":"4e669e7f-631e-470b-9c5c-507ecfaf0d02","order_by":0,"name":"Zhong-Ming Xiao","email":"","orcid":"","institution":"920th Hospital of Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Zhong-Ming","middleName":"","lastName":"Xiao","suffix":""},{"id":274338715,"identity":"3478ec93-4877-4c89-a9b4-3164b2166b42","order_by":1,"name":"Yu Chen","email":"","orcid":"","institution":"920th Hospital of Joint Logistics Support 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Study\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSmoking is prevalent among the global youth population. However, it may prematurely lead to various diseases or death\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. The primary addictive substance in cigarettes is \"nicotine,\" a highly addictive substance found in tobacco along with 4,000 other chemicals. The continued use of tobacco products leads to addiction in a significant percentage of the population\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Consequently, nicotine dependence is globally recognized as an addictive disease and a major public health threat\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Despite this, nicotine dependence is a complex syndrome involving psychological, physiological, and personal behavioral processes\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, prevalent in individuals of all ages, particularly young and middle-aged males, significantly impacting physical and mental health\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. China, with an estimated 308\u0026nbsp;million smokers, is the world's largest consumer of tobacco products\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Smoking-related deaths in China exceed 2.4\u0026nbsp;million annually and are expected to rise in the coming decades\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, likely due to \"nicotine dependence,\" making complete smoking cessation challenging. Therefore, smoking-induced nicotine dependence poses a severe public health problem in China\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAn estimated over 100\u0026nbsp;million individuals, primarily young and middle-aged, migrate from low to high altitudes annually\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. These individuals engage in labor-intensive activities in high-altitude regions, including infrastructure projects, military assignments, or sports-intensive tourism like skiing, ice skating, and mountain climbing\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Large-scale population-based studies on smoking and nicotine dependence in these short- to medium-term high-altitude exposed populations are lacking.\u003c/p\u003e \u003cp\u003ePresently, the Fagerstr\u0026ouml;m Test for Nicotine Dependence\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e (FTND, Supplementary, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) stands as the most widely employed international tool for assessing nicotine dependence. The psychometric properties of the FTND have been validated among smokers in numerous countries\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, and it is applicable to the Chinese population, having been used in studies on nicotine dependence in smokers\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Assessing nicotine dependence among smokers in high-altitude areas is vital for understanding this issue among Chinese smokers. Hence, we employed this scale to assess nicotine dependence among young adult male soldiers in the high-altitude region.\u003c/p\u003e \u003cp\u003eBetween January and August 2023, over 3000 electronic questionnaires were distributed in the high-altitude area of China (approximately 1700m-3700m above sea level). The goal was to collect information on basic socio-demographic characteristics, altitude migration, working hours, willingness to quit smoking, and daily smoking status of young adult male soldiers in the high-altitude area. The study aimed to investigate \"nicotine dependence\" and its influencing factors among young and middle-aged male smokers in the high-altitude region. This effort seeks to provide insights for the development of smoking cessation strategies tailored to high-altitude area smokers, ultimately promoting the health of this population.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe experimental protocol, methods, survey instruments, and data collection procedures utilized in this study were approved by the Ethical Review Committee of the 920th Hospital of the Joint Logistics Support Force. Moreover, all research methods were conducted in strict adherence to applicable guidelines and regulations. Additionally, the dataset utilized in this study did not include any confidential health-related information pertaining to the participants.\u003c/p\u003e\n\u003cp\u003eStudy design and population\u003c/p\u003e\n\u003cp\u003eA population-based cross-sectional study was undertaken, encompassing robust young adult male military personnel who had undergone health assessments at the 920th Hospital of the Joint Logistics Force during the period from November 2021 to December 2022.The participants were presently stationed and undergoing training in an elevated terrain (\u0026ge;1500 m above sea level) for a minimum duration of 3 months. Subsequent to reading and signing an informed consent form, participants willingly engaged in a questionnaire survey, expressing their consent to provide information regarding their smoking habits and nicotine dependence for subsequent research endeavors. A total of 825 questionnaires were excluded due to missing information or irregularities, alongside an additional 1005 questionnaires from individuals who had never smoked or had quit smoking. In the conclusive analyses, a total of 1,477 valid questionnaires were incorporated (Supplementary，Figure S1).\u003c/p\u003e\n\u003cp\u003eData collection and quality control\u003c/p\u003e\n\u003cp\u003eThe questionnaire we designed comprised three parts. The first part primarily aimed to collect information on the demographic characteristics of the respondents. The second part included a questionnaire on nicotine dependence, utilizing the FTND questionnaire, a standardized instrument developed by the CDC/WHO. The FTND has demonstrated sufficient validity and reliability and has been widely employed in various settings\u003csup\u003e[15-18]\u003c/sup\u003e. The third part encompassed an Assessment of Smokers\u0026apos; Self-Efficacy to Quit Smoking questionnaire, a component within the widely used Smoking Cessation Clinic Questionnaire in China. We created an electronic questionnaire encompassing these three parts to electronically gather information, ensuring the accuracy and timeliness of this study.\u003c/p\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003cp\u003eThe electronic questionnaire comprehensively incorporates inquiries concerning demographic features, encompassing age, ethnicity, marital status, educational attainment, height, weight, mean daily smoking quantity over the preceding month and the last half-year, the smoking status of cohabitants, age at the initiation of smoking, the duration of smoking, along with additional details. As the survey predominantly focuses on youthful military personnel who engage in smoking activities within high-altitude regions, supplementary fundamental data was gathered. This encompassed \u0026quot;current altitude in the high-altitude area, duration of employment in the high-altitude area, original birthplace altitude, and altitude migration difference (altitude in the high-altitude area - original birthplace altitude, in meters).\u0026quot;Simultaneously, data pertaining to smoking behavior was amassed based on the six standard questions outlined in the FTND (Supplementary\u0026nbsp;，Table S1), encompassing inquiries such as \u0026quot;1. How soon after awakening do you engage in your initial cigarette consumption? 2. What quantity of cigarettes do you consume on a daily basis? 3. Do you encounter challenges in refraining from smoking in smoke-free public spaces? 4. Which cigarette proves most challenging to relinquish during cessation attempts? 5. Does the frequency of smoking within the initial hour post-awakening surpass that of other periods in the day? 6. Do you engage in smoking when indisposed, spending the majority of the day confined to bed?\u0026quot; Via this assessment, the respondents\u0026apos; nicotine dependence was ascertained, yielding a composite score spanning from 0 to 10. Scores of 0-2 denote exceedingly low nicotine dependence, 3-4 denote low dependence, 5 denotes moderate dependence, 6-7 denote high dependence, and 8-10 denote very high dependence (Supplementary, Table S2). For subsequent evaluation of nicotine dependence risk factors, we categorized 0\u0026le;FTND\u0026le;5 as indicative of very low to moderate dependence, and 6\u0026le;FTND\u0026le;10 as suggestive of high to very high dependence. Concurrently, we evaluated smokers\u0026apos; self-efficacy in the cessation of smoking by employing the subsequent inquiries: 1. Do you harbor earnest intentions of terminating smoking within the ensuing month? 2. How formidable do you appraise the challenge of smoking cessation to be (rated on a scale from 0-10, with elevated scores signifying diminished confidence)? 3. On a scale spanning 0-10, what degree of assurance do you possess in abstaining from smoking henceforth? 4. How frequently have you undertaken earnest endeavors to desist from smoking? 5. When did you last embark on a sincere endeavor to quit smoking? 6. Throughout your preceding endeavor to quit smoking, what was the duration during which you successfully refrained from smoking? 7. Which methodologies did you employ during that specific attempt to quit smoking? The objective of this assessment is to gauge the self-efficacy of smokers in the cessation endeavor.\u003c/p\u003e\n\u003cp\u003eData analysis\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were conducted for continuous and categorical variables, expressed as mean (Mean\u0026plusmn;SD), frequency, and percentage, respectively. Comparisons between count data in categorical variables utilized the four-cell \u0026chi;2 test and the R\u0026times;C table \u0026chi;2 test to assess the population characteristics of smokers with very-low-moderate dependence on nicotine (0\u0026le;FTND\u0026le;5) and high-very-high dependence (6\u0026le;FTND\u0026le;10). Fisher\u0026apos;s exact probability method was employed when the theoretical frequency T\u0026lt;1. Multivariate logistic regression models were applied to compare potential confounders under nicotine dependence status between the two groups. Statistical analyses were performed using SPSS V.26.0 (IBM, Armonk, New York, USA) software for data processing, with P\u0026lt;0.05 (two-tailed) considered statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 3307 questionnaires were distributed between January and August 2023 in the high-altitude areas (altitude approximately 1700m-3700m). Out of these, 2482 valid questionnaires were returned, resulting in a response rate of approximately 75.1% for this survey. Among the respondents, 1005 (40.5%) were either never smokers or had quit smoking, while 1477 (59.5%) were current smokers. Subsequent analyses were exclusively conducted on the group of current smokers. A risk assessment of nicotine dependence for male current smokers indicated that 937 (63.4%) had very low dependence, 373 (25.3%) had low dependence, 82 (5.6%) had moderate dependence, 74 (5%) had high dependence, and 11 (0.7%) had very high dependence (Supplementary\u0026nbsp;，Table S2). Supplementary，Table S3 provides a breakdown of the percentage of scores for each FTND item.\u003c/p\u003e\n\u003cp\u003eParticipant demographic characteristics\u003c/p\u003e\n\u003cp\u003eThe average age of the soldiers who were smoking was 24.5\u0026plusmn;3.7 years old. Out of the 1477 smokers, 1229 (83.2%) were Han Chinese, and 1452 (98.3%) were unmarried males with high school education or above. Among them, 1399 (94.7%) worked at altitudes between 1500 and 3500 m. Out of these, 1211 migrated to the high-altitude from places with altitudes less than 1500m, and the majority (1250, 84.6%) migrated from places with altitudes between 1500 and 3500 m. Additionally, 1293(87.5%) smokers had worked at the high-altitude for 3-6 months, and 184(12.5%) smokers had worked there for half a year or more. Over 45% of these smokers had a \u0026quot;daily maximum\u0026quot; of smoking. Smokers\u0026apos; maximum daily cigarette consumption, average daily cigarette consumption in the last month, and average daily cigarette consumption in the last 6 months were 5-14 cigarettes. Furthermore, 1324(89.6%) had a roommate who smoked, 888 (60.1%) of these smokers started smoking at\u0026nbsp;\u0026le;19 years of age, and 1,108(75%) smokers smoked between 1-9 years of age. Additional statistical characteristics of each demographic and smoking behavior are detailed in Table 1.\u003c/p\u003e\n\u003cp\u003eTable1. The smoking behavior and demographic characteristics of current smokers\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"591\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eMean\u0026plusmn;SD/N\u0026nbsp;（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e24.5\u0026plusmn;3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eFTND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e0-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1.9\u0026plusmn;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e6-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e6.6\u0026plusmn;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eMinority nationality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e248（16.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1229（83.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eMarriage status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1242（84.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e229（15.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eDivorce\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e6（0.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e25（1.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eHigh school/Technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e679（46.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eJunior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e639（43.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eBachelor\u0026apos;s degree or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e134（9.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026le;21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e576（39.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026gt;21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e901（61.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eWork Altitude(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1399（94.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e78（5.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eHometown Altitude(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026le;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1211（82.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e261（17.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e5（0.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eAltitude difference(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026le;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e213（14.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1250（84.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e14（1.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eWorking time (MTh)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e3\u0026lt;T\u0026le;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1293（87.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e6\u0026lt;T\u0026le;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e43（2.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e12\u0026lt;T\u0026le;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e42（2.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e99（6.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCigarettes per day (in\u0026nbsp;the last 1 month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e502（34.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e680（46.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e145（9.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e73（4.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e77（5.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCigarettes per day (in the last 6 months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e482（32.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e685（46.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e155（10.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e40（2.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e115（7.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eMaximum cigarettes per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e320（21.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e743（50.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e332（22.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e56（3.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e26（1.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eRoommates smoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e153（10.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1324（89.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003estart smoking(age)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026le;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e888（60.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e20\u0026le;Age\u0026le;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e560（37.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e30\u0026le;Age\u0026le;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e29（2.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eSmoking duration(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e161（10.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e1\u0026le;y\u0026le;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e1108（75.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e10\u0026le;y\u0026le;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e203（13.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e20\u0026le;y\u0026le;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e5（0.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMTh: month.\u003c/p\u003e\n\u003cp\u003eResults of univariate and multivariate analyses of nicotine dependence in current smokers\u003c/p\u003e\n\u003cp\u003eIn the analysis of smokers in the High-altitude areas, changes in marital status were found to significantly impact nicotine dependence. 94.9% of unmarried men were very low-moderately dependent on nicotine, while about 5.1% of unmarried men were highly-extremely dependent on nicotine. In contrast, 9.2% of married men were highly-extremely dependent on nicotine. Surprisingly, divorced men were 16.7% more likely to be highly-very highly dependent on nicotine (P=0.018). Regarding BMI, logistic regression analysis revealed (Supplementary，Figure S2) that when BMI\u0026ge;21.7 (P=0.048, ROC=1.88, 95% CI: 1.102-4.231), it was a significant influencing factor for smokers to become dependent on nicotine. Multifactorial logistic regression analysis found that BMI (P=0.048, OR=1.88, 95% CI:1.01-3.51), working hours after high altitude exposure (P=0.033, OR=2.91, 95% CI: 1.37-6.19), average daily smoking (in the last 6 months) (P=0.031, OR=6.626, 95% CI: 1.04-37.78), and the maximum amount of cigarettes smoked in a single day (P\u0026lt;0.01, OR=17.90, 95% CI: 3.41-94.08), roommate smoking status (P=0.044, OR=8.71, 95% CI: 1.06-67.95), and smoking duration (P=0.029, OR=61.90, 95% CI: 2.26-1692.79) were significantly correlated with nicotine hyperdependence status. While marital status (P=0.018) and age of smoking initiation (P\u0026lt;0.01) showed a tendency for a relationship with nicotine high dependence status, they were not statistically significant in multifactor logistic regression analysis (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable2. Univariate and multivariate analysis of smoking behavior and demographic characteristics based on FTND classification.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1000\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" rowspan=\"2\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.56943056943057%\" colspan=\"2\" style=\"width: 43.9365%;\"\u003e\n \u003cp\u003eFTND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.486513486513486%\" colspan=\"2\" style=\"width: 9.4585%;\"\u003e\n \u003cp\u003eUnivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\" colspan=\"2\" style=\"width: 12.2046%;\"\u003e\n \u003cp\u003eMultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.188630490956072%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003every low to moderate (N, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.34625322997416%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003ehigh-very high (N, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.2299741602067185%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.41343669250646%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eOR（95% CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.857881136950905%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eNation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"3\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"3\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" rowspan=\"3\" valign=\"top\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eMinority nationality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e231（93.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e17（6.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1161（94.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e68（5.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"5\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"5\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" rowspan=\"5\" valign=\"top\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e24（96.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e1（4.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eHigh school/Technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e645（95.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e34（5.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eJunior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e601（94.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e38（5.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eBachelor\u0026apos;s degree or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e122（91.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e12（9.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eWork Altitude(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"3\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"3\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" rowspan=\"3\" valign=\"top\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1320(94.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e79(5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e72(92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e6(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eHometown Altitude(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"4\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"4\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" rowspan=\"4\" valign=\"top\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026le;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1144(94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e67(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e243(93.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e18(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e5(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eAltitude difference(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"4\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e1.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"4\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" rowspan=\"4\" valign=\"top\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026le;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e198(93.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e15(7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1181(94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e69(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.27993254637437%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.655986509274875%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e13(92.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.9460370994941%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e1(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2158516020236085%\" valign=\"top\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eMarriage status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"4\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e7.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"4\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1179（94.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e63（5.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e208（90.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e21（9.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.05(0.51-2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.891\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eDivorce\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e5（83.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e1（16.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.52(0.12-19.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.750\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"3\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e13.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"3\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026le;21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e559(97.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e17(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026gt;21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e833(92.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e68(7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.88(1.01-3.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.048\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eWorking time (MTh)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"5\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e24.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"5\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e3\u0026lt;T\u0026le;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1234(95.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e59(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e6\u0026lt;T\u0026le;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e39(90.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e4(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e0.87(0.22-3.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.845\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e12\u0026lt;T\u0026le;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e36(85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e6(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e2.01(0.57-7.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.280\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026gt;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e83(83.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e16(16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e2.91(1.37-6.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eCigarettes per day (in the last 1 month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"6\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e89.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"6\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e498(99.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e4(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e650(95.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e30(4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.25(0.30-5.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.755\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e124(85.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e21(14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.34(0.27-6.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.723\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e60(82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e13(17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.95(0.37-10.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.435\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e60(77.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e17(22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.93(0.34-10.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.455\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eCigarettes per day (in the last 6 months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"6\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e103.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"6\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e479(99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e3(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e658(96.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e27(3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.98(0.39-9.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.407\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e136(87.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e19(12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e2.70(0.46-15.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.270\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e32(80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e8(20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e10.19(1.62-64.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.013\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e87(75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e28(24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e6.26(1.04-37.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.045\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eMaximum cigarettes per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"6\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e140.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"6\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e317(99.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e3(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e728(98.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e15(2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e1.02(0.31-4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.795\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e297(89.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e35(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e4.45(1.13-17.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.032\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e38(67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e18(32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e13.40(3.13-57.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e12(46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e14(53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e17.90(3.41-94.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eRoommates smoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"3\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e8.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"3\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e152(99.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e1(0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1240(93.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e84(6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e8.47(1.06-67.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.044\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003estart smoking(age)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"4\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e8.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"4\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026le;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e824(92.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e64(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e20\u0026le;Age\u0026le;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e540(96.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e20(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e0.80(0.42-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.482\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e30\u0026le;Age\u0026le;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e28(96.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e1（3.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e0.29(0.03-2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.286\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.677322677322678%\" valign=\"top\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003eSmoking duration（years）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.383616383616385%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.185814185814186%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.593406593406593%\" rowspan=\"5\" valign=\"top\" style=\"width: 5.4921%;\"\u003e\n \u003cp\u003e40.877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.893106893106893%\" rowspan=\"5\" valign=\"top\" style=\"width: 3.9665%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4975024975024973%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.784215784215784%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.488511488511488%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e160(99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e1(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e1\u0026le;y\u0026le;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e1054(95.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e54(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e3.60(0.43-29.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.235\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e10\u0026le;y\u0026le;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e176(86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e27(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e6.85(0.76-61.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.087\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.212471131639724%\" style=\"width: 32.7489%;\"\u003e\n \u003cp\u003e20\u0026le;y\u0026le;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.937644341801384%\" style=\"width: 23.6972%;\"\u003e\n \u003cp\u003e2(40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.397228637413395%\" style=\"width: 20.2392%;\"\u003e\n \u003cp\u003e3(60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.886836027713626%\" style=\"width: 0.6102%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.244803695150114%\" style=\"width: 7.933%;\"\u003e\n \u003cp\u003e61.90(2.26-1692.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.27944572748268%\" valign=\"top\" style=\"width: 4.2716%;\"\u003e\n \u003cp\u003e0.015\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds Ratios derived from multinomial regression; Ref: Reference; MTh: month.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDemographic characteristics of current smokers\u0026apos; smoking cessation self-efficacy\u003c/p\u003e\n\u003cp\u003eWe conducted a survey on smoking cessation self-efficacy among young adult males who were currently smoking and found that 1,409 (95.4%) of them believed that there was no good way to quit. Additionally, 1,213(82.1%) had a clear intention to quit, 915(61.9%) had tried to quit at least once in the past month, 551(37.4%) had made at least two serious attempts to quit, 609(41.2%) had good confidence in quitting, and 267(18.1%) had remained non-smokers for at least one month since their last quit. Furthermore, 1,120 (75.8%) smokers did not think it was very difficult to quit smoking (Table 3).\u003c/p\u003e\n\u003cp\u003eTable3. Characteristics of smoking cessation behavior among current smokers\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"569\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\" valign=\"top\"\u003e\n \u003cp\u003ePercentage of responses\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003eN（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" valign=\"top\"\u003e\n \u003cp\u003eWhat method did you use to quit smoking at that time？\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e459（31.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eNo methods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e950（64.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eSeek help\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e68（4.6）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" valign=\"top\"\u003e\n \u003cp\u003eAre you willing to quit smoking？\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e1213（82.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e264（17.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" valign=\"top\"\u003e\n \u003cp\u003eWhen was the last time you seriously quit smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eNever？\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e562（38.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026lt;1 month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e222（15）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e1-6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e328（22.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e7-12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e107（7.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026gt;12 months\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e258（17.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" valign=\"top\"\u003e\n \u003cp\u003eHow many times have you tried to seriously quit smoking Confidence in never smoking again？\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026le;1 times\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e926（67.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e2-5 times\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e500（33.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e6-10 times\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e51（3.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026le;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e868（58.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026gt;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e609（41.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" valign=\"top\"\u003e\n \u003cp\u003eWhen you last quit smoking, how long were you able to stay smoke-free？\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e417（28.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026lt;1 day\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e160（10.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e1-30 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e633（42.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e1-6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e179（12.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e6-12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e88（6.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\" valign=\"top\"\u003e\n \u003cp\u003eDifficulty in quitting smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026le;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e1120（75.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"58.274647887323944%\"\u003e\n \u003cp\u003e\u0026gt;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.725352112676056%\"\u003e\n \u003cp\u003e357（24.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eUnivariate and multivariate analysis of self-cessation efficacy among current smokers\u003c/p\u003e\n\u003cp\u003eWe found that those who had a \u0026quot;willingness to quit\u0026quot; had a relatively high level of education (P=0.018). Additionally, we observed that the willingness to quit was lower among those with higher average daily cigarette consumption in the last month (P=0.006) and maximum cigarette consumption in a single day (P=0.001). The willingness to quit was also weaker as the age of the smokers increased (P=0.004), and the proportion of those who were highly dependent on nicotine (P=0.006) was higher among those who were reluctant to quit smoking. In a multifactorial binary logistic regression analysis, we found that \u0026quot;smokers\u0026apos; education level (P=0.048, OR=2.84, CI: 1.18-6.81), average daily cigarette consumption (in the last month) (P=0.018, OR=0.42, CI: 0.25-0.72), maximum cigarette consumption in a single day (P=0.012, OR=0.29, CI: 0.11-0.76), and smoking age (P=0.013, OR=1.93, CI: 1.28-2.91)\u0026quot; may have an effect on the willingness to quit smoking (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable4. Univariate and multivariate analysis of smoking behavior and demographic characteristics based on based on self-efficacy in quitting smoking\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"918\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.279171210468924%\" colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 47.4693%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.083969465648856%\" colspan=\"2\" style=\"width: 29.9167%;\"\u003e\n \u003cp\u003eDo you seriously plan to quit smoking within the next month？\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.86586695747001%\" colspan=\"2\" style=\"width: 8.1691%;\"\u003e\n \u003cp\u003eUnivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9629225736095965%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.408942202835334%\" colspan=\"2\" style=\"width: 11.5913%;\"\u003e\n \u003cp\u003eMultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.92776886035313%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.964686998394864%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e\u0026chi;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.964686998394864%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.889245585874799%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003eOR（95% CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eNation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eMinority nationality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e208（83.9）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e40（16.1）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1005（81.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e224（18.2）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eMarriage status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1018（82）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e224（18）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e190(83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e39(17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eDivorce\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e5(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e1(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026le;21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e473(82.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e103(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026gt;21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e740(82.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e161(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eWork Altitude(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1147(82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e252(18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e66(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e12(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eHometown Altitude(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e2.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026le;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e990(81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e221(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e220(84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e41(15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e3(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eAltitude difference(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e1.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026le;1500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e180(84.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e33(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1500\u0026lt;h\u0026le;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1022(81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e228(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e3500\u0026lt;h\u0026le;5500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e11(78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e3(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eWorking time(MTh)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e4.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"5\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e3\u0026lt;T\u0026le;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1056(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e237(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e6\u0026lt;T\u0026le;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e34(79.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e9(20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e12\u0026lt;T\u0026le;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e34(81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e8(19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026gt;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e89(89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e10(10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eCigarettes per day (in the last 6 months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e8.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"6\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e408(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e74(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e565(82.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e120(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e117(75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e38(24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e34(85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e6(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e89(77.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e26(22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eRoommates smoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e2.681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e133(86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e20(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1080(81.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e244(18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003estart smoking(age)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e1.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" rowspan=\"4\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026le;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e721(81.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e167(18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e20\u0026le;Age\u0026le;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e467(83.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e93(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.14090019569472%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e30\u0026le;Age\u0026le;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.784735812133073%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.199608610567516%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e25(86.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.046966731898237%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e4(13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.522504892367906%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e9.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e16(64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e9(36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eHigh school/Technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e555(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e124(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e2.30(0.96-5.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eJunior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e539(84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e100(15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e2.84(1.18-6.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eBachelor\u0026apos;s degree or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e103(76.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e31(23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e1.87(0.73-4.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eCigarettes per day (in the last 1 moth)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e14.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e425(84.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e77(15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e565(83.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e115(16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.90(0.62-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e105(72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e40(27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.42(0.25-0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e60(82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e13(17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.86(0.43-1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e58(75.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e19(24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.71(0.37-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eMaximum cigarettes per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e17.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"6\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e274(85.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e46(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e5-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e603(81.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e140(18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.71(0.47-1.07）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e277(83.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e55(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e1.02(0.60-1.72）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e25-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e46(82.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e10(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e1.34(0.57-3.16）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026ge;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e13(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e13(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.29(0.11-0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eSmoking duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e12.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"5\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e121(75.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e40(24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e1\u0026le;T\u0026le;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e928(83.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e180(16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e1.93(1.28-2.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e10\u0026le;T\u0026le;19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e162(79.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e41(20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e1.66(0.96-2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e20\u0026le;T\u0026le;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e3(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.75(0.10-5.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.76822633297062%\" valign=\"top\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003eFTND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.44069640914037%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.119695321001089%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.922742110990207%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e8.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.466811751904244%\" rowspan=\"3\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.9586507072905333%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.731229597388467%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e0-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e1153(82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e239(17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.02013422818792%\" style=\"width: 39.8521%;\"\u003e\n \u003cp\u003e6-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7114093959731544%\" style=\"width: 7.6172%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.483221476510067%\" style=\"width: 15.8967%;\"\u003e\n \u003cp\u003e60(70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.006711409395972%\" style=\"width: 14.02%;\"\u003e\n \u003cp\u003e25(29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.4161073825503356%\" valign=\"top\" style=\"width: 0.6624%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 7.5068%;\"\u003e\n \u003cp\u003e0.63(0.35-1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.704697986577182%\" valign=\"top\" style=\"width: 4.0846%;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds Ratios derived from multinomial regression; Ref: Reference; MTh: month.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eCurrently, there have been studies on nicotine dependence among young smokers in China, but few studies have focused on the assessment of nicotine dependence and self-efficacy of quitting smoking among smokers in the high-altitude-exposed population. The present study aimed to investigate the nicotine dependence and willingness to quit among young adult male soldier smokers after high-altitude exposure. Female smokers were not included in this study, as previous studies have shown that smoking is overwhelmingly male, with a prevalence almost 10 times that of females\u003csup\u003e[19]\u003c/sup\u003e. Among the young adult male soldiers we surveyed, there were a total of 1,477 active smokers, with a smoking prevalence of 59.5%, which is higher than the results of the 2018 China Adult Tobacco Epidemiological Survey, which reported that the smoking prevalence among people\u0026nbsp;\u0026ge;15 years of age was 26.6%, of which 50.5% were males\u003csup\u003e[20]\u003c/sup\u003e. A similar situation has been observed in other non-developed countries\u003csup\u003e[21]\u003c/sup\u003e, and this discrepancy has been observed in many Western countries before the tobacco industry targeted females\u003csup\u003e[22]\u003c/sup\u003e. Our study highlights the prevalence of smoking in the population and also reflects the importance and necessity of preventing the harms of smoking in young adults.\u003c/p\u003e\n\u003cp\u003eBased on the FTND item scores, we found that 63.4%, 25.3%, 5.6%, 5%, and 0.7% of the young soldiers\u0026apos; population had very low, low, moderate, high, and very high nicotine dependence after high-altitude exposure, respectively. Although the psychometric properties of the FTND have been questioned in a small number of cases, it has become a useful tool associated with the successful validation of smoking cessation and nicotine dependence\u003csup\u003e[23-25]\u003c/sup\u003e. In our study, the mean overall FTND score was 2.1\u0026plusmn;1.8, while the mean FTND score for smokers with very low-moderate nicotine dependence was 1.9\u0026plusmn;1.5, and for smokers with high-very high nicotine dependence was 6.6\u0026plusmn;0.9. Although the mean overall FTND score was similar to those reported in Europe, such as in Germany and Norway(2.8), Spain and the Netherlands(2.9), England and Denmark(3.0), Italy(3.1), and France(3.4)\u003csup\u003e[26]\u003c/sup\u003e, the mean FTND score of highly-very highly nicotine-dependent individuals(6.6\u0026plusmn;0.9) was much higher than in these countries, such as Poland(3.6), Austria(3.6), Sweden(4.6), and the United States(4.3)\u003csup\u003e[26]\u003c/sup\u003e, indicating the urgent need to address high nicotine dependence for smoking cessation in China. Achieving high cessation rates in China will be a challenge, and many smokers may need and benefit from treatment. The FTND is associated with smoking cessation self-efficacy, and as FTND scores rise, smokers\u0026apos; confidence in quitting decreases. Notably, perhaps because of their confidence in their success, smokers with very low-moderate nicotine dependence were the most likely to take action to quit, seek help, and be willing to make multiple attempts to quit.\u003c/p\u003e\n\u003cp\u003eAdditionally, BMI exhibited a significant correlation with nicotine dependence, and our study suggests that young adult soldiers who smoke in high-altitude areas with high to very high nicotine dependence are more likely to have a BMI\u0026ge;21.7. This may be related to living in high-altitude areas where physical activity is reduced, weight gain is common, and there is frequent congregation and smoking. Although studies have indicated a negative correlation between BMI and smoking intensity\u003csup\u003e[27-28]\u003c/sup\u003e, our results did not show a significant negative correlation between smoking status and BMI. The proportion of smokers with high-very high nicotine dependence increased with longer working time in the high-altitude region. This could be related to their challenges in accessing information about tobacco hazards after high-altitude exposure, lack of communication with loved ones, living in a different place, and feeling lonely. Some studies suggest that smokers are more likely to develop smoking-related psychological issues in negative environments, such as anxiety, loneliness, and stress, and addressing smokers\u0026apos; negative beliefs may enhance smoking cessation rates\u003csup\u003e[29]\u003c/sup\u003e. Additionally, the average daily cigarette consumption in the last 6 months and the maximum daily cigarette consumption are closely related to the degree of nicotine dependence. The degree of dependence on nicotine increases with higher cigarette consumption. Studies by Placzek and Dwyer et al\u003csup\u003e[30-31]\u003c/sup\u003e have shown that long-term exposure to high-dose nicotine may result in permanent changes in the brain, leading to addiction. This aligns with the notion that prolonged exposure to large quantities of nicotine contributes to higher levels of dependence. We also observed that whether co-residents smoked significantly affected smokers\u0026apos; nicotine dependence levels. Prolonged exposure to secondhand smoke may impede smoking cessation through physiological and psychosocial mechanisms\u003csup\u003e[32]\u003c/sup\u003e. Living with other smokers may make it more challenging for smokers planning to quit due to social norms, peer pressure, and camaraderie\u003csup\u003e[33]\u003c/sup\u003e. Being in smoking scenarios is associated with increased odds of smoking and relapse\u003csup\u003e[34-35]\u003c/sup\u003e, all contributing to smokers\u0026apos; high-maximal nicotine dependence and difficulties in quitting. The development of high nicotine dependence is closely linked to the age of smokers, strongly associated with early smoking initiation. Studies indicate that 80% of smokers start smoking at or before the age of 18 years\u003csup\u003e[36]\u003c/sup\u003e, leading to at least 20-25% of smokers becoming dependent on daily smoking\u003csup\u003e[37-38]\u003c/sup\u003e. Early smoking also results in a relatively longer smoking duration, contributing to higher nicotine dependence among smokers exposed to high doses of nicotine over an extended period.\u003c/p\u003e\n\u003cp\u003eOur examination of smokers\u0026apos; self-efficacy to quit smoking, specifically \u0026quot;whether they seriously plan to quit smoking in the next month,\u0026quot; revealed a strong association between smokers\u0026apos; self-efficacy to quit smoking and their education level. This association may stem from the fact that higher education levels correlate with greater awareness of the dangers of nicotine, heightened health consciousness, and a greater willingness to attempt smoking cessation in the future. In contrast, less educated smokers may lack sufficient health knowledge and awareness of nicotine-related harms, leading to reduced responsiveness to public tobacco control interventions\u003csup\u003e[39]\u003c/sup\u003e. However, we also observed a negative correlation between smokers\u0026apos; \u0026quot;average daily cigarette consumption in the last month, maximum daily cigarette consumption, and smoking age\u0026quot; and their self-cessation efficacy. This aligns with findings indicating that long-term heavy smoking is associated with an increased risk of nicotine dependence\u003csup\u003e[36]\u003c/sup\u003e. This correlation may be explained by the tendency of smokers who engage in heavy, prolonged smoking without experiencing smoking-related illnesses to be more resistant to quitting and, therefore, less willing to make cessation attempts.\u003c/p\u003e\n\u003cp\u003eA crucial limitation inherent in this study is its cross-sectional design, rendering it incapable of establishing a direct causal relationship between the extent of nicotine dependence and the identified risk factors. Another constraint lies in the inability to conduct follow-ups with smokers to investigate subsequent smoking cessation. Furthermore, the questionnaire utilized in our study relied on data obtained through an electronic survey, where individuals self-reported their smoking status. The absence of biochemical validation, such as testing for exhaled carbon monoxide or urinary cotinine, has the potential to introduce bias to the study results. Moreover, the predominant composition of the study population comprised young males with an average age of 24.5\u0026plusmn;3.7 years. Subsequent investigations should encompass diverse age groups and incorporate females residing in high-altitude regions to foster a more comprehensive comprehension of nicotine dependence among smokers in this locale, thereby aiding in the development of more efficacious smoking cessation strategies.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eNicotine dependence remained prevalent among young adult male soldier smokers after high-altitude exposure. The degree of dependence was associated with factors such as smoker\u0026apos;s BMI, time spent living and working in the high-altitude region, age of smoker, cohabitant smoking status, maximal smoking in a single day, and average daily smoking in the last 6 months. The majority (83.9%) of smokers expressed a clear intention to quit, while factors like smokers\u0026apos; education level, average daily cigarette consumption (in the last 1 month), maximum daily cigarette consumption, and smoking age may influence the intention to quit. This study establishes a foundation for researching factors related to nicotine dependence and smoking cessation self-efficacy among young male soldier smokers after high-altitude exposure. It also provides a rationale for tobacco control in the high-altitude region and efforts to enhance smokers\u0026apos; self-efficacy in quitting smoking.\u003c/p\u003e"},{"header":"ABBREVIATIONS","content":"\u003cp\u003eFTND Fagerstr\u0026ouml;m Test for Nicotine Dependence \u003c/p\u003e\n\u003cp\u003eBMI Body Mass Index \u003c/p\u003e\n\u003cp\u003eMTh Month\u003c/p\u003e\n\u003cp\u003eRef Reference\u003c/p\u003e\n\u003cp\u003eOR Odds Ratios \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eData availability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to military secrecy. However, they are available from the corresponding author (email: [email protected]) upon reasonable request.\u003c/p\u003e\n\u003cp\u003eAUTHORS\u0026rsquo;\u0026nbsp;CONTRIBUTIONS\u003c/p\u003e\n\u003cp\u003eThe paper\u0026apos;s structure was crafted by Zhong-ming Xiao, Yu Chen, and Ke Ma, who also undertook data analysis, interpretation, and manuscript composition. Wen-ke Cai, Xin Zhang, and Gong-hao He played pivotal roles in gathering questionnaire data, refining interpretations, and editing the final draft. Shao-ying Li, Ting Yu, Bo Men, and Zi-xiong Nian coordinated the data organization. Every author participated in the meticulous revision and ultimate approval of the manuscript.\u003c/p\u003e\n\u003cp\u003eFUNDING\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study received support from the Young and Middle-aged Academic and Technical Leaders Reserve Talent Project of Yunnan Province (No.202405AC350037) and the Young and Middle-aged Academic and Technical Leaders Reserve Talent Project of Yunnan Province (No. 2019HB045).\u003c/p\u003e\n\u003cp\u003eCOMPETING INTERESTS\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo conflicts of interest exist.\u003c/p\u003e\n\u003cp\u003eSUPPLEMENTARY MATERIAL\u003c/p\u003e\n\u003cp\u003eTable S1, Table S2, Table S3，Figure S1 and Figure S2 are detailed in the Word and PDF document of the supplementary material.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLi Q, Hsia J, Yang G. Prevalence of smoking in China in 2010. 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Nicotine dependence among Chinese city dwellers: a population-based cross-sectional study. NICOTINE TOB RES. 2011; 13 (7): 556-64. doi: 10.1093 /ntr/ntr 040.\u003c/li\u003e\n \u003cli\u003eWang Chen, Xiao Dan, Chi Hui Summary of the 2020 China Report on the Hazards of Smoking to Health [J]. Chinese Journal of Circulation, 2021, 36 (10): 937-952.\u003c/li\u003e\n \u003cli\u003eJha,P.,Ranson,M.K.,Nguyen,S.N.,\u0026amp;Yach,D.(2002).Estimates of global and regional smoking prevalence in 1995,by age and sex.American Journal of Public Health ,92 ,1002\u0026ndash;Doi:10.2105/AJPH.92.6.1002.\u003c/li\u003e\n \u003cli\u003eGraham,H.(1996).Smoking prevalence among women in the European Community 1950\u0026ndash;1990.Social Science and Medicine, 43,243\u0026ndash;254.doi:10.1016/0277-9536(95)00369\u0026ndash;X.\u003c/li\u003e\n \u003cli\u003eFagerstr\u0026ouml;m,K.O.,Kunze,M.,Schoberger,R.,Breslau,N.,Hughes,J.R.,Hurt,R.D.,et al.(1996).Nicotine dependence versus smoking prevalence:Comparisons among countries and categories of smokers.Tobacco Control,5,52\u0026ndash;56.doi:10.1136/tc.5.1.52.\u003c/li\u003e\n \u003cli\u003eHaddock,C.K.,Lando,H.,Klesges,R.C.,Talcott,G.W.,\u0026amp;Renaud,E.A.(1999).A study of the psychometric and predic tive properties of the Fagerstrom Test for Nicotine Dependence in a population of young smokers.Nicotine and Tobacco Research,1,59\u0026nbsp;\u0026ndash;66.doi:10.1080/ 14622299050011161.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePiper,M.E.,McCarthy,D.E.,\u0026amp;Baker,T.B.(2006).Assessing tobacco dependence:A guide to measure evaluation and selec tion.Nicotine and Tobacco Research,8,339\u0026ndash;351.doi:10.1080/14622200600672765.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFagerstr\u0026ouml;m,K.,\u0026amp;Furberg,H.(2008).A comparison of the Fag erstr\u0026ouml;m Test for Nicotine Dependence and smoking prevalence across countries.Addiction,103,841\u0026ndash;845.doi:10.1111/j.1360\u0026ndash;0443.2008.02190.x.\u003c/li\u003e\n \u003cli\u003eOh HS, Seo WS. 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Washington, DC: National Academy Press, 1994:28-68.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJohnston LD, O\u0026rsquo;Malley PM, Bachman JG, Schulenberg JE. Monitoring the future: national survey results on drug use, 1975\u0026ndash;2006. Bethesda, MD: National Institute on Drug Abuse, 2007. (NIH publication no.07-6205.)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKandel D, Schaffran C, Griesler P, Samuolis J, Davies M, Galanti R. On the measurement of nicotine dependence in adolescence: comparisons of the mFTQ and a DSM-IV-based scale. J Pediatr Psychol 2005;30:319-32.\u003c/li\u003e\n \u003cli\u003eXu, Y, Xu, S, Wu, Q, et al. Analysis of nicotine dependence among daily smokers in China: evidence from a cross-sectional study in Zhejiang Province. BMJ Open. 2022; 12 (10): e062799. doi: 10.1136/bmjopen-2022-062799.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"High-altitude, FTND, Nicotine dependence, Young Smokers","lastPublishedDoi":"10.21203/rs.3.rs-3922646/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3922646/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study was conducted as a cross-sectional survey using a questionnaire to analyze \"demographic characteristics, nicotine dependence, and self-efficacy for smoking cessation\" among healthy young adult male soldiers who are presently residing and training in high-altitude for a minimum period of 3 months. A total of 3307 questionnaires were distributed between January and August 2023 in the high-altitude areas (altitude approximately 1700m-3700m).The participants in the survey exhibited an average age of 24.5 ± 3.7 years. A notable 82% of the respondents migrated to the high-altitude from regions with an altitude below 1500m, while 12.5% of smokers had resided and worked in the high-altitude area for a duration of ≥6 months. A substantial 89.6% of participants shared living spaces with smoking roommates; 60.1% initiated smoking before reaching the age of 19; 75% of smokers maintained a smoking habit spanning 1-9 years; a predominant 94.2% manifested very low to moderate nicotine dependence, with the remaining 5.8% presenting high to very high dependence. A distinct correlation emerged between factors such as BMI, duration of residence and work at high altitudes, daily smoking quantity (in the last 6 months), maximum daily smoking amount, roommate smoking status, and smoking duration, and the heightened status of nicotine dependence. An impressive 82.1% of respondents conveyed a resolute intent to cease smoking, with pivotal determinants such as educational attainment, daily smoking quantity (in the last month), maximum daily smoking amount, and smoking duration significantly influencing the cessation intention. Nicotine dependence persists in young adult male soldier smokers post high-altitude exposure, with the majority expressing a strong desire to quit. Therefore, our focus should be on bolstering their willingness to quit, crafting a tailored cessation program, and elevating the success rate of smoking cessation.\u003c/p\u003e","manuscriptTitle":"Investigation of Nicotine Dependence in Young Male Soldiers After High-altitude Exposure: a Cross- Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-23 09:06:01","doi":"10.21203/rs.3.rs-3922646/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e12faf56-6d6b-4539-8876-16a43e16d1a2","owner":[],"postedDate":"February 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28931056,"name":"Biological sciences/Physiology/Respiration"},{"id":28931057,"name":"Earth and environmental sciences/Environmental social sciences/Psychology and behaviour"},{"id":28931058,"name":"Health sciences/Health care/Quality of life"}],"tags":[],"updatedAt":"2024-05-17T16:03:57+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-23 09:06:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3922646","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3922646","identity":"rs-3922646","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}