Literature DB >> 36229149

Analysis of nicotine dependence among daily smokers in China: evidence from a cross-sectional study in Zhejiang Province.

XiuJing Hu1, Xuehai Zhang1, Yue Xu2, Shuiyang Xu2, Qingqing Wu2, Heni Chen2, Dingming Yao2.   

Abstract

OBJECTIVE: The current study aimed to assess the level of nicotine dependence and its influencing factors among daily smokers in Zhejiang, China.
SETTING: The 2020 Global Adult Tobacco Survey was conducted in Zhejiang, China. PARTICIPANTS: 1244 daily smokers aged ≥15 years. MEASURES: Respondents were asked questions regarding their age, sex, residence, education level, occupation, household income, age of starting daily smoking and nicotine dependence.
RESULTS: The findings revealed that 17.4% of daily smokers were highly dependent on nicotine, and the mean Fagerström Test for Nicotine Dependence score of daily smokers was (3.1±2.4). Age, educational level, occupation and age of starting daily smoking had significant effects on high nicotine dependence, whereas residence, sex and yearly household income were not significant factors. Compared with the age group ≥60 years, the proportion of respondents with a higher nicotine dependence level was lower in the age group of 15-39 years (OR=0.45). Daily smokers with a higher education level had a lower nicotine dependence level than those with a lower education level: primary or less (OR=3.07) and secondary (OR=2.62). Government institution staff (OR=4.02), unemployed persons (OR=3.08) and industrial workers (OR=2.46) had significantly higher nicotine dependence levels than did workers in the other occupation categories. People who started daily smoking at ≤18 years of age had a higher nicotine dependence level (OR=2.25) than those who started later.
CONCLUSIONS: This study elucidated that nearly one-fifth of daily smokers in Zhejiang, China, have high nicotine dependence levels. Improved health information on tobacco smoking is needed to encourage daily smokers to quit smoking, particularly among young males, unemployed persons and those with lower education levels. © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  China; FTND; daily smokers; nicotine dependence

Mesh:

Substances:

Year:  2022        PMID: 36229149      PMCID: PMC9562707          DOI: 10.1136/bmjopen-2022-062799

Source DB:  PubMed          Journal:  BMJ Open        ISSN: 2044-6055            Impact factor:   3.006


This is a population-based cross-sectional survey to study nicotine dependence in daily smokers. Our study includes the sufficiently large sample size and the high representativeness resulting from the well-established sampling method. The results of this study will provide a baseline for future research regarding nicotine dependence among daily smokers in China. The survey used respondent reports to provide information, which may be subject to recall bias due to social desirability. We use the Fagerström Test for Nicotine Dependence as an accurate indicator to measure the nicotine dependence; future investigations into biological indicators of nicotine dependence could be considered.

Introduction

China is the world’s largest consumer of tobacco products, with an estimated 308 million smokers.1 2 The annual number of deaths caused by tobacco use now exceeds 2.4 million and is expected to increase in the coming decades.3 Nicotine dependence contributes to the maintenance of tobacco use and difficulty with cessation. Nicotine dependence is a multidimensional phenomenon,4 which can be measured using the Fagerström Test for Nicotine Dependence (FTND).5 The FTND is a widely used six-item questionnaire that measures physical dependence on nicotine. The six items assess smoking rate, smoking soon after waking, smoking even when ill, difficulty refraining from smoking, reporting the first cigarette of the day as the most difficult to give up and smoking more heavily in the morning. The psychometric properties of the FTND have been validated among cigarette smokers in many countries,6 although evidence of its validity in Chinese language studies is scarce. Zhejiang is a small province in China, with a developed economy and dense population. Smoking is a very common societal phenomenon and an important social activity in Zhejiang.7 The local government has implemented tobacco control measures to reduce smoking in the population. In the provincial capital city, Hangzhou, the antismoking laws were revised in 2019 to ban smoking in all indoor public places. The local Center for Disease Control (CDC) launched a series of health promotion programmes targeting important populations for smoking prevention and control, such as males planning to conceive a baby with his partner8 and college students.9 Ninety-nine smoking cessation clinics10 were created in Zhejiang, and several campaigns were launched to provide knowledge about tobacco to the public and educate smokers about the risks of smoking. Although studies have indicated that these approaches played an important role in controlling tobacco use, the smoking rate was 21.9%11 in Zhejiang in 2019, higher than that in other developed countries.12 In 2020, the Global Adult Tobacco Survey was conducted, and 1244 daily smokers in Zhejiang completed the survey. We used the relevant data from this survey to analyse nicotine dependence and its influencing factors among daily adult smokers. The purpose of the study was to use the data related to this survey to assess the level of nicotine dependence among daily adult smokers and the factors influencing it to facilitate evidence-based strategies to help smokers quit.

Methods

Setting

Data were obtained from the 2020 Global Adult Tobacco Survey in Zhejiang, China. The survey was conducted between May and October 2020, and 1244 daily smokers completed the survey. Mapping and listing were conducted by local CDC staff to identify target households. The fieldwork was conducted in Mandarin through face-to-face interviews, and households were visited up to three times to interview the target person within that household. All survey interviewers and supervisors were trained, and written consent was obtained from all respondents, or from their parents or guardians in the case of minors prior to the visit.

Participants

A multistage stratified cluster sampling design was implemented in the survey. Ten regions were selected based on their geographic locations. Each region was partitioned into segments containing approximately 120 households (using mapping and listing to determine the number). Six segments were randomly selected, and every household in the selected segment was visited. One eligible household member aged ≥15 years from each participating household was randomly sampled for an interview. A total of 6562 residents completed the survey, among which 1244 were daily smokers and were included in our analysis.

Measures

High nicotine dependence

High nicotine dependence was the dependent variable measured using the FTND score. The FTND is a six-item self-reported measure of nicotine dependence. The test measures the time between waking up and the first cigarette (item 1: ‘How soon after you wake up do you smoke your first cigarette?’), difficulty refraining from smoking in places where smoking is forbidden (item 2: ‘Do you find it difficult to refrain from smoking in places where it is forbidden?’), difficulty quitting the first cigarette of the day (item 3: ‘Which cigarette would you hate most to give up?’), the number of cigarettes smoked per day (‘tem 4: ‘How many cigarettes per day do you smoke?’), morning smoking (item 5: ‘Do you smoke more frequently during the first hours after waking up than during the rest of the day?’) and smoking during sickness (item 6: Do you smoke when you are so ill that you are in bed most of the day?’). Table 1 presents the FTND items, response options and the value of each response option. The possible FTND scores range from 0 to 10, and the nicotine dependence level was defined by the scores as: 0–2=extremely low; 3–4=low; 5=medium; 6–7=high; 8–10=extremely high. The cut-off point for high nicotine dependence was an FTND score of 6 based on previous studies.13 14
Table 1

The Fagerström Test for Nicotine Dependence items, response options and scoring

ItemResponse optionsNumerical value
How soon after you wake up do you smoke your first cigarette?Within 5 min3
6–30 min2
31–60 min1
After 60 min0
Do you find it difficult to refrain from smoking in places where it is forbidden?No0
Yes1
Which cigarette would you hate most to give up?The first one in the morning1
Any other0
How many cigarettes per day do you smoke?10 or less0
11–201
21–302
31 or more3
Do you smoke more frequently during the first hours after waking up than during the rest of the day?No0
Yes1
Do you smoke when you are so ill that you are in bed most of the day?No0
Yes1
The Fagerström Test for Nicotine Dependence items, response options and scoring The self-reported independent variables included in the analysis were residence (urban, rural), sex (male, female), age group (15–39 years, 40–59 years, ≥ 60 years), education level (primary or less, secondary, high school, undergraduate or above), occupation (industrial worker, government institution staff, business/service worker, unemployed, retired, other, unknown), yearly household income (<50 000 yuan, 50 000–200 000 yuan, >200 000 yuan, unknown) and age of starting daily smoking (≤18 years, >18 years, unknown).

Statistical analysis

SPSS V.18.0 (SPSS Inc) was used for all analyses. Missing values need to be removed in order to clean the data. Standard descriptive statistics were conducted on the demographic variables and other parameters that might associate with high nicotine dependence. Logistic regression was applied to identify the factors associated with high nicotine dependence. P values <0.05 were considered statistically significant (two sided).

Patient and public involvement

Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Results

General information

The study was conducted in 10 counties/county-level cities; valid interviews were conducted with 1244 daily smokers (1224 males and 20 females). Our sample population had an average age of 56.0±14.2 (range: 21–96) years. There were 752 urban residents and 492 rural residents among the respondents. The most common education level was completed primary school or less (36.0%), followed by completed secondary school (38.8%), completed high school (15.1%) and completed college or above (10.1%). Regarding income levels, 34.2% reported yearly household income less than 50 000 yuan, 50.6% reported incomes between 50 000 to 200 000 yuan and 9.2% reported incomes more than 200 000 yuan. The average age at which the respondents started daily smoking was 22.2±6.1 years, and 22.8% started daily smoking when they were ≤18 years old (table 2).
Table 2

Survey respondents’ sociodemographic characteristics (n=1244)

Sociodemographic characteristicN%
Residence
 Urban75260.5
 Rural49239.6
Sex
 Male122498.4
 Female201.6
Age (years)
 15–3917414.0
 40–5956845.7
 ≥ 6050240.4
Education level
 Primary or less44736.0
 Secondary48238.8
 High school18715.1
 Undergraduate or above12610.1
Occupation
 Industrial worker37730.3
 Government institution staff483.9
 Business/service worker38030.6
 Unemployed836.7
 Retired987.9
 Other25220.3
 Unknown60.5
Yearly household income (yuan)
 <50 00042634.2
 50 000–200 00062950.6
 >200 0001159.2
 Unknown746.0
Age of starting daily smoking (years)
 ≤ 1828422.8
 >1895076.4
 Unknown100.8
 Overall1244
Survey respondents’ sociodemographic characteristics (n=1244)

Daily smokers’ nicotine dependence levels

This was a retrospective study that used data obtained using FTND questionnaires from 1244 daily smokers. Table 3 shows the response frequencies for each FTND item score. The mean FTND score was 3.1±2.4 (range: 0–10). The distribution of nicotine dependence among daily smokers ranged from: very low (46.9%), low (27.3%), medium (8.4%), high (12.4%) and very high (5.1%).
Table 3

The percentage response frequencies for each item of the Fagerström Test for Nicotine Dependence (FTND)

FTND itemPercentage of responses for each score (n=1244)
0123
Item 1: how soon after you wake up do you smoke your first cigarette?37.820.123.019.1
Item 2: do you find it difficult to refrain from smoking in places where it is forbidden?77.322.8
Item 3: which cigarette would you hate most to give up?64.435.6
Item 4: how many cigarettes per day do you smoke?31.953.46.28.5
Item 5: do you smoke more frequently during the first hours after waking up than during the rest of the day?83.416.6
Item 6: do you smoke when you are so ill that you are in bed most of the day?82.717.3
The percentage response frequencies for each item of the Fagerström Test for Nicotine Dependence (FTND) High nicotine dependence (FTND≥6) was observed in 17.4% of daily smokers. The prevalence of high nicotine dependence varied with age, education, occupation and age of starting daily smoking. The younger respondents tended to have a lower nicotine dependence level; among the youngest age group (≤39 years), 6.9% had high nicotine dependence. Education level was negatively associated with high nicotine dependence, which was observed in 24.4% of respondents with an education level of primary or less and 17.8% of respondents with secondary education. The unemployed respondents had the highest nicotine dependence level (28.9%). A high nicotine dependence level was observed in a higher proportion of respondents who began daily smoking at ≤18 years of age (27.1%) than those who began smoking at >18 years of age (14.7%) (table 4).
Table 4

Factors associated with high nicotine dependence

CovariatePercentageAdjusted OR95% CIP value
Residence
 Urban17.00.930.67 to 1.290.661
 Rural18.3Reference
Sex
 Male17.51.860.40 to 8.610.428
 Female20.0Reference
Age (years)
 15–396.90.450.20 to 0.990.047
 40–5915.90.890.60 to 1.340.584
 ≥ 6023.1Reference
Education level
 Primary or less24.43.071.15 to 8.180.025
 Secondary17.82.621.03 to 6.710.044
 High school8.61.260.45 to 3.550.655
 Undergraduate or above5.6Reference
Occupation
 Industrial worker25.72.461.45 to 4.150.001
 Government institution staff12.54.021.31 to 12.300.015
 Business/service worker12.61.680.95 to 2.990.075
 Unemployed28.93.081.56 to 6.050.001
 Retired16.31.540.71 to 3.320.271
 Others10.7Reference
Household yearly income (yuan)
 <50 00023.91.770.89 to 3.510.104
 50 000–200 00014.01.370.70 to 2.670.360
 >200 00010.4Reference
Age of starting daily smoking (years)
 ≤1827.12.251.59 to 3.17<0.001
 >1814.7Reference
Factors associated with high nicotine dependence

Factors associated with high nicotine dependence

A multivariate logistic regression analysis was conducted on seven factors (residence, sex, age, education level, occupation, yearly household income and age of starting daily smoking). Among these factors, age, education, occupation and age of starting daily smoking had significant effects on the nicotine dependence level, whereas the effects of residence, sex and yearly household income were not significant (table 4). Compared with the age group ≥60 years, the proportion of respondents with high nicotine dependence was lower in the age group of 15–39 years (OR=0.45). A lower nicotine dependence level was observed among people with a higher education level than among those with less education: primary or less (OR=3.07) and secondary (OR=2.62). In the occupation category, government institution staff (OR=4.02), unemployed persons (OR=3.08) and industrial workers (OR=2.46) had significantly higher nicotine dependence levels than did workers in the other occupations. Respondents who started daily smoking at ≤18 years of age had higher nicotine dependence levels than those who started daily smoking at >18 years of age (OR=2.25).

Discussion

We investigated nicotine dependence among daily smokers in Zhejiang, China, and its influencing factors. The average FTND score of daily smokers was 3.1, and more than one-sixth of respondents were highly dependent on nicotine. Age, educational level, occupation and age of starting daily smoking were strongly associated with high nicotine dependence. Nicotine addiction is the key driver of smoking. Exposure to nicotine in the form of tobacco smoking can be harmful to the nervous, respiratory, immune and cardiovascular systems and can impact human development.15 High levels of nicotine dependence are also associated with lower quality of life, lower work productivity as well as higher healthcare utilisation.16 The FTND scores obtained in this study are much higher than those reported in Germany and Norway (2.8)6 but lower than that reported in a survey conducted in China in 2008 (3.49).17 This decline may be related to the widespread implementation of tobacco control measures including the raising of taxes on tobacco and the implementation of tobacco control policies in public places. The Chinese government raised the tobacco excise tax in 2015, which led to a 7.8% decrease in annual cigarette sales.18 In addition, most cities in Zhejiang Province have regulated smoking in public places in recent years by including them in the legislation of Civilized Behavior Promotion Regulation, and the provincial capital city of Hangzhou implemented stricter Regulations on Smoking Control in Public Places in 2019 to further restrict smoking behaviour. The reduction in nicotine dependence among daily smokers may also be related to the promotion of standardised smoking cessation clinics in Zhejiang Province in recent years, and the next step is to explore the actual intervention effects of smoking cessation clinics on the level of nicotine dependence among heavy tobacco users through a controlled study. Aiming to optimise strategies to achieve smoking cessation among daily smokers, we analysed several sociodemographic characteristics of nicotine dependence. Results grouped by age showed that older adults were more likely to be highly dependent on nicotine, which is consistent with previous findings.19 The main reason may be that older people have been smoking longer and are more susceptible to addictive behaviours. To a certain extent, age confers more unrealistic optimism in older people, and the harms of smoking and the benefit from quitting are often underestimated by older age groups.20 Therefore, research into the characteristics of nicotine dependence in older people should be a priority to facilitate the development of targeted smoking cessation interventions. Moreover, the age analysis also showed that people who started daily smoking at ≤18 years of age were more likely to report high-level nicotine dependence. Studies have demonstrated that an earlier age of smoking initiation is independently associated with the formation of daily smoking habits and nicotine dependence.21 Thus, it is critical to implement effective interventions to delay or prevent tobacco exposure in adolescence. A survey of American adolescents found that those who first used tobacco at ages younger than 13 years were significantly more likely to develop nicotine dependence.22 The age threshold for adolescent tobacco exposure in the Chinese social context warrants further exploration, and implementing more stringent interventions for this priority population may lead to greater public health benefits. In general, smokers of low socioeconomic status are prone to a higher degree of nicotine dependence.23 In this survey, we found that nicotine dependence among daily smokers was significantly negatively associated with education level. Smokers with less education may not have sufficient health knowledge or may lack awareness of nicotine-related harms and health maintenance, which could lead to lower responsiveness to public tobacco control interventions. In addition, the prevalence of nicotine dependence varied by occupation, and the highest dependence levels were observed in unemployed persons and industrial workers. This finding is in line with previous results, which attributed more flexible Chinese tobacco prices18 to enable people of different occupations and income levels to afford cigarettes. However, it was notable that government institution staff also showed high levels of nicotine dependence. One possible explanation is that government workers, especially at the grassroots level, suffer from high levels of daily work stress. This survey was also conducted during the COVID-19 pandemic, which may have led this population to rely more on smoking to relieve stress. Further research on the possible psychological conditions that influence smoking and nicotine dependence in the context of the COVID-19 pandemic is warranted. Smoking is a social norm in China, where cigarette gifting and sharing are a prevalent part of Chinese customs and strongly contribute to smoking initiation. Nicotine dependence is considered to be one of the biggest barriers to successful smoking cessation. Evidence suggests that patients with higher levels of nicotine dependence are less likely to quit.24 Having baseline information on the level of nicotine dependence and influencing factors in daily smokers can help to develop more targeted and graded cessation intervention strategies, as well as early interventions that focus on nicotine-related factors in a timely manner. An example would be to focus more targeted tobacco control measures on young males, unemployed or less educated smokers. The strengths of this study include the sufficiently large sample size and the high representativeness resulting from the well-established sampling method. However, there were several limitations that need to be noted. First, the study is a cross-sectional survey only, which is incapable of causal inference. Second, the survey used respondent reports to provide information, which may be subject to recall bias due to social desirability. Third, nicotine dependence is relatively difficult to measure. The FTND, which we used, may also not be an accurate indicator of the extent of addiction among smokers. Future investigations into biological indicators of nicotine dependence could be considered.

Conclusions

In summary, a population-based cross-sectional survey was used to study nicotine dependence in daily smokers. The results showed that Chinese daily smokers had high nicotine dependence levels, particularly among young males, the unemployed and those with less education. Further tailored smoking cessation programmes will be developed and implemented according to the distribution of nicotine dependence and related factors.
  18 in total

1.  Nicotine addiction and its assessment.

Authors:  K O Fagerstrom; T F Heatherton; L T Kozlowski
Journal:  Ear Nose Throat J       Date:  1990-11       Impact factor: 1.697

2.  Quitting-related beliefs, intentions, and motivations of older smokers in four countries: findings from the International Tobacco Control Policy Evaluation Survey.

Authors:  Hua-Hie Yong; Ron Borland; Mohammad Siahpush
Journal:  Addict Behav       Date:  2005-05       Impact factor: 3.913

3.  Tobacco Dependence Predicts Higher Lung Cancer and Mortality Rates and Lower Rates of Smoking Cessation in the National Lung Screening Trial.

Authors:  Alana M Rojewski; Nichole T Tanner; Lin Dai; James G Ravenel; Mulugeta Gebregziabher; Gerard A Silvestri; Benjamin A Toll
Journal:  Chest       Date:  2018-05-21       Impact factor: 9.410

4.  A comparison of the Fagerström Test for Nicotine Dependence and smoking prevalence across countries.

Authors:  Karl Fagerström; Helena Furberg
Journal:  Addiction       Date:  2008-05       Impact factor: 6.526

5.  Prevalence of smoking in China in 2010.

Authors:  Qiang Li; Jason Hsia; Gonghuan Yang
Journal:  N Engl J Med       Date:  2011-06-23       Impact factor: 91.245

6.  Age of tobacco use initiation and association with current use and nicotine dependence among US middle and high school students, 2014-2016.

Authors:  Saida Sharapova; Carolyn Reyes-Guzman; Tushar Singh; Elyse Phillips; Kristy L Marynak; Israel Agaku
Journal:  Tob Control       Date:  2018-11-29       Impact factor: 7.552

7.  Nicotine dependence among Chinese city dwellers: a population-based cross-sectional study.

Authors:  Tingzhong Yang; Saul Shiffman; Ian R H Rockett; Xiaobo Cui; Ruoxiang Cao
Journal:  Nicotine Tob Res       Date:  2011-03-31       Impact factor: 4.244

8.  Smoking, nicotine dependence and nicotine intake by socio-economic status and marital status.

Authors:  Marjaana Pennanen; Ulla Broms; Tellervo Korhonen; Ari Haukkala; Timo Partonen; Annamari Tuulio-Henriksson; Tiina Laatikainen; Kristiina Patja; Jaakko Kaprio
Journal:  Addict Behav       Date:  2014-03-13       Impact factor: 3.913

9.  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.

Authors: 
Journal:  Lancet       Date:  2021-05-27       Impact factor: 202.731

10.  Association between secondhand smoke exposure at home and cigarette gifting and sharing in Zhejiang, China: a repeat cross-sectional study.

Authors:  Yue Xu; ShuiYang Xu; QingQing Wu; YuJie Guo
Journal:  BMJ Open       Date:  2016-03-03       Impact factor: 2.692

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