INTRODUCTION
Tobacco smoking is a preventable human behavior and has been identified to play a critical role in the pathogenesis of various malignant cancers1 and pulmonary diseases such as chronic obstructive pulmonary disease (COPD)2. Nicotine dependence (ND) is a maladaptive pattern of tobacco smoking with withdrawal symptoms similar to other drug addictive disorders; and has been defined by the Diagnosis and Statistical Manual of Mental Disorders—edition IV (DSM-IV)3. In China, the smoking rate of men (53.3%, 95% CI: 51.4–55.2) is much higher than that of women (2.5%, 95% CI: 1.9–3.0) (p<0.05)4. Moreover, the proportion of smoking quitters in China is low, and the awareness of quitting is weak4. Previous studies have shown that different behaviors are closely related to smoking status change and cigarette consumption5. Caffeine withdrawal makes it more difficult to quit smoking6. Alcohol and nicotine dependence are likely to co-occur, resulting in a lower likelihood of smoking cessation7,8. People with behaviors that do not influence nicotine dependence, including exercise and enough sleep, may consume fewer cigarettes daily and have a lower nicotine dependence9-12. Influencing behaviors are those that can increase smoking or increase the level of nicotine dependence. Non-influencing behaviors are those that have no influence on smoking cigarettes or nicotine dependence. Moreover, it is very common in clinical practice that smokers have different degrees of nicotine dependence with the same tobacco consumption. Therefore, we investigated, by recording smokers’ behaviors as medical history, whether there is a relationship between influencing and non-influencing behaviors of nicotine dependence and high nicotine dependence. However, so far there is no evidence showing that influencing behaviors increase the risk of high ND or vice versa.
METHODS
Information on the lifestyle factors of 343 smokers who came to our clinic to quit smoke were recorded from April 2010 to January 2020 in the Affiliated Hospital of Medical School of Ningbo University. All research subjects provided informed consent, and the research study was approved by the Ethics Committee of the Affiliated Hospital. All methods were carried out following NCCN Clinical Practice Guidelines in Oncology of Smoking Cessation13.
Survey design
Clinical characteristics and lifestyle behaviors
Demographic (age, gender, BMI) data were recorded as clinical characteristics. We recorded the lifestyle behaviors of smokers before providing personalized treatment plans to patients in the smoking cessation clinic. We selected smokers’ lifestyle behaviors, as identified in previous studies, that could influence cigarette consumption and nicotine dependence level. Moreover, these behaviors are easy to adjust or change during the progress of smoking cessation. Behaviors that have no effect on nicotine dependence were recorded as follows: exercise more than three times a week and each time more than 30 minutes9,10; sleep time ≥8 hours; taking an afternoon nap; and any type of fruit consumption ≥3 times/week. In contrast, behaviors that can have an influence on nicotine dependence were regarded as the following: sleep time <8 hours; alcohol consumption more than 50 mL ≥3 times/week (40% alcohol), caffeine drink intake >200 mL every day; and mental activities after dinner before sleep14 (e.g. gambling, overtime work, video games, studying or other mental activities). All information was recorded on our self-designed form (Supplementary file).
Measurement of nicotine dependence
Nicotine dependence was measured by the Fagerström test for nicotine dependence (FTND)15,16. The FTND score was classified across five levels of dependence: 0–2 very low, 3–4 low , 5 moderate, 6–7 high, and 8–10 very high17. We dichotomized the level of dependence into high (FTND >5) and low (FTND ≤5).
Statistical analysis
The behaviors information and results for 343 patients were included in the statistics. The t-test and mean ± standard deviation (SD) were used in comparisons of age and BMI (kg/m2). Gender distribution and lifestyle behaviors across the two groups (FTND ≤5 and FTND >5) were calculated by chi-squared analysis. Binary logistic analysis was used to estimate all independent or interaction effects of behaviors. The analysis was conducted using IBM SPSS Statistics 21.0, and p<0.05 was considered as statistically significant.
RESULTS
Demographics of the study population are shown in Table 1. There were no differences noted in age, gender and BMI between the high and low nicotine dependence smokers. Influencing and non-influencing behaviors were differently distributed in the FTND >5 group (Table 2) (p=0.002), indicating that exercise, sleep, sleep time ≥8 h and fruit consumption were not associated with high nicotine dependence, neither independently nor combined (Table 3). Results in Table 4 show that caffeine drinking combined with mental activities after dinner were associated with high nicotine dependence (OR=1.939; 95% CI: 1.154–3.258, p=0.012). Three unhealthy interaction-behaviors (sleep time <8 hours, caffeine drinking and mental activities after dinner) were associated with high nicotine dependence (OR=2.208; 95% CI: 1.032–4.737, p=0.042.
Table 1
Clinical characteristics of low (FTND ≤5) and high (FTND >5) nicotine dependence smokers, China (N=343)
| Characteristics | FTND ≤5 (n=151) | FTND >5 (n=192) | p |
|---|---|---|---|
| Age (years) | |||
| Mean±SD | 42.6±11.0 | 43.1±11.1 | 0.664 |
| Gender (n) | |||
| Male | 141 | 176 | 0.682 |
| Female | 10 | 16 | |
| BMI (kg/m2) | |||
| Mean±SD | 23.5±2.7 | 23.6±7.7 | 0.796 |
Table 2
Co-existence of both nicotine dependence influencing and non-influencing behaviors among low and high dependence smokers
| Number of combined nicotine influencing behaviors and number of smokers with FTND ≤5 | p | ||||||
|---|---|---|---|---|---|---|---|
| Number of combined nicotine dependence non-influencing behaviors among FTND ≤5 smokers | 0 | 1 | 2 | 3 | 4 | 0.139 | |
| 0 | 0 | 4 | 14 | 3 | 0 | ||
| 1 | 11 | 18 | 24 | 7 | 1 | ||
| 2 | 7 | 9 | 20 | 8 | 2 | ||
| 3 | 3 | 11 | 4 | 1 | 0 | ||
| 4 | 0 | 2 | 2 | 0 | 0 | ||
| Number of combined nicotine dependence influencing behaviors and number of smokers with FTND >5 | p | ||||||
| Number of combined nicotine dependence non-influencing behaviors among FTND >5 smokers | 0 | 1 | 2 | 3 | 4 | 0.002* | |
| 0 | 0 | 7 | 13 | 14 | 3 | ||
| 1 | 8 | 30 | 27 | 7 | 3 | ||
| 2 | 8 | 19 | 20 | 7 | 0 | ||
| 3 | 6 | 7 | 7 | 1 | 0 | ||
| 4 | 1 | 3 | 1 | 0 | 0 | ||
Table 3
The association between nicotine dependence non-influencing behaviors and high (FTND >5) nicotine dependence
Table 4
The association between nicotine dependence influencing behaviors and high (FTND >5) nicotine dependence
| Behaviors | OR (95% CI) | p |
|---|---|---|
| Sleep time <8 h | 1.061 (0.691–1.628) | 0.787 |
| Alcohol consumption more than 50 mL ≥3 times/week | 0.748 (0.425–1.318) | 0.315 |
| Caffeine drink intake >200 mL every day | 0.869 (0.566–1.336) | 0.523 |
| Mental activities after dinner (e.g. gambling, overtime work, video games, studying or other mental activities) | 1.475 (0.956–2.275) | 0.079 |
| Sleep time <8 h + alcohol consumption | 1.236 (0.561–2.725) | 0.599 |
| Sleep time <8 h + caffeine drink | 1.011 (0.622–1.645) | 0.964 |
| Sleep time <8 h + mental activities after dinner | 1.142 (0.671–1.945) | 0.624 |
| Alcohol consumption + caffeine drink | 0.675 (0.338–1.349) | 0.266 |
| Alcohol consumption + mental activities after dinner | 0.481 (0.202–1.144) | 0.098 |
| Caffeine drink + mental activities after dinner | 1.939 (1.154–3.258) | 0.012* |
| Sleep time <8 h + alcohol consumption + caffeine drink | 1.494 (0.581–3.843) | 0.405 |
| Sleep time <8 h + alcohol consumption + mental activities after dinner | 0.914 (0.301–2.780) | 0.875 |
| Sleep time <8 h + caffeine drink + mental activities after dinner | 2.208 (1.032–4.737) | 0.042* |
| Alcohol consumption + caffeine drink + mental activities after dinner | 0.676 (0.240–1.909) | 0.46 |
| Sleep time <8 h + alcohol consumption + caffeine drink + mental activities after dinner | 1.591 (0.391–6.470) | 0.516 |
DISCUSSION
Nicotine dependence is a maladaptive pattern of tobacco smoking with withdrawal symptoms like other drug addictive disorders. Many behaviors may change the daily consumption of cigarettes or smoking status5. People with non-influencing behaviors such as exercising and adequate sleep have lower nicotine dependence9,18. Previous studies have demonstrated that influencing behaviors such as insufficient sleep duration11,18, caffeine drink consumption6,19, alcohol dependence7,8, and mental activities (e.g. gambling20,21, video games22, overtime working23) increase cigarette consumption and can change ex-smokers or non-smokers into smokers. However, one needs to take into account the smokers’ lifestyle. There are few studies that have investigated the influence of combined lifestyle behaviors on high nicotine dependence. To our knowledge, our research is first to reveal the association between nicotine dependence influencing and non-influencing behaviors and high ND. Importantly, we showed that the interaction of mental activities after dinner, caffeine drinking and sleep time <8 hours are associated with high ND.
During the night without smoking, a decrease in nicotine level can recover nicotinic-acetylcholine receptors. It may contribute to the development of withdrawal symptoms in the morning when craving for cigarettes24 . Further, inadequate sleep duration decreases positive mood and increases negative mood11 and the dopamine caused by the calming effect of nicotine relieves this bad mood25.Therefore, high nicotine dependence smokers view the first few cigarettes of the day as the most pleasant and are thus not willing to quit smoking. We can also understand why sleep duration is associated with high ND.
Mental activities after dinner14 (e.g. gambling, overtime work, video games, studying or other mental activities) and smoking may be related to environment factors such as colleagues, classmates, gambling and video game playing patterns. Moreover, tobacco is used so that dopamine can alleviate anxiety and allow one to cope with stress in these situations26-28. Furthermore, coffee or caffeine intake is also a choice for dealing with tiredness by low-cost addictive products that are available anywhere and anytime. The prevalence of drinking caffeine beverages and smoking happen during mental activities after dinner or in the morning without adequate sleep time. Caffeine withdrawal symptoms increase the difficulty of smoking cessation19. So, the synergistic effect of mental activities after dinner, caffeine drinking and inadequate sleep duration increases the risk of high nicotine dependence.
Our data show that nicotine dependence non-influencing habits are not associated with high ND. This result is different from previous studies that showed that smokers who exercise have lower nicotine dependence and lower tobacco consumption9,10. The main reason for the difference is that we chose smokers of all ages who exercise more than 3 times a week and each time more than 30 minutes. This inclusion criterion can be used for all high nicotine dependence smokers. We also showed that afternoon napping was not associated with high nicotine dependence; there are few studies showing the relationship between napping and nicotine dependence. Therefore, we suggest that smokers who come to the clinic for cessation help with high nicotine dependence should fully consider an individualized treatment, no matter their nicotine dependence influencing and non-influencing behaviors, instead of avoiding only influencing behaviors or developing non-influencing behaviors only.
We did not investigate education and occupation situation in this study, for two reasons. Firstly, in many studies, education and occupation were not found to be associated with higher cigarette consumption and higher nicotine dependence level. Secondly, we did not investigate these two factors because smokers need more feasible plans to assist in smoking cessation and improve the success rate of quitting smoking. Compared with change in lifestyle behaviors, it is more difficult to improve education or change jobs in order to quit smoking. Moreover, there are few studies about improving education or finding new jobs in order to change smoking status.
Limitations
We have one limitation in our research: the cigarette daily consumption and FTND should be investigated or studied in the future. This would help to better ascertain whether lifestyle behaviors can influence both cigarette consumption and nicotine dependence level. Furthermore, in China, the smoking rates of men are higher than the rates of women4 and awareness about quitting smoking is generally weak4. Therefore, information records on female smokers are few.
CONCLUSIONS
The interactive effects of mental activities after dinner and caffeine drinking were found to be associated with high nicotine dependence. Sleeping less than 8 hours combined with mental activities after dinner and caffeine drinking also indicated a similar association. Avoiding these behaviors may decrease the likelihood for high nicotine addiction and may help increase the possibility for smoking cessation. Smokers should decrease mental activities and caffeine drinking at night, which may contribute to a decrease in nicotine dependence. Individualized treatment for smokers should fully consider both healthy and unhealthy lifestyles.
