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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 6  |  Issue : 3  |  Page : 254-264

Levels of nicotine dependency and its association with challenges to quit smoking among adult smokers in Malaysia 2021


1 Department of Community Medicine, Faculty of Medicine, University of Cyberjaya, Malaysia
2 Department of Public Health Medicine, Faculty of Medicine, UiTM, Malaysia
3 Department of Community Medicine, Faculty of Medicine, Asia Metropolitan University, Malaysia
4 Department of Community Medicine, Faculty of Medicine, SEGi University College, Malaysia

Date of Submission11-Apr-2022
Date of Decision29-Apr-2022
Date of Acceptance22-May-2022
Date of Web Publication31-Oct-2022

Correspondence Address:
Dr. Thin Mon Kyaw
University of Cyberjaya, Cyberjaya, Selangor
Malaysia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aip.aip_62_22

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  Abstract 


Background: The nicotine dependency is related to many factors in terms of sociodemographic and smoking practices. Objective: The aim of the study was to assess the levels of nicotine dependency among adult smokers in Malaysia and to identify the association of nicotine dependency with sociodemographic factors and with challenges to quit smoking, respectively, among adult smokers in Malaysia. Methodology: A cross-sectional electronic survey was conducted through an electronic survey including all adult smokers in Malaysia. Standard questionnaires such as 21-item Challenges to Stopping Smoking questionnaires to assess the challenges to quit smoking and the Fagerstrom test were used to assess the nicotine dependency. The validated electronic online questionnaires were distributed, which comprised sociodemographic characteristics, assessment on smoking status, challenges to quit smoking, and nicotine-dependence test. Multiple logistic regression was used to identify the association of nicotine dependency with the challenges to quit smoking, respectively, among adult smokers in Malaysia. Results: Regarding the levels of nicotine dependence among current smokers based on Fagerstrom Nicotine-Dependence Score (n = 830), a total of 345 (41.6%) respondents had low-to-moderate nicotine dependence, followed by 312 (37.6%) who had moderate nicotine dependence; 158 (19%) respondents had low nicotine dependence, and 15 respondents (1.8%) were found to have high nicotine dependence. Conclusion: Smoking cessation services should be designed and implemented with the degree of nicotine dependence and pattern usage in mind. There should be more public health education about the dangers of smoking as well as more focus on motivation among smokers and their families.

Keywords: Adults, challenges to quit smoking, Malaysia, nicotine dependency, smokers


How to cite this article:
Kyaw TM, Ismail Z, Selamat MI, A/L Arivanandan PK, Kyaw YW, Morgan LM, Latchumana K, Arasu K. Levels of nicotine dependency and its association with challenges to quit smoking among adult smokers in Malaysia 2021. Ann Indian Psychiatry 2022;6:254-64

How to cite this URL:
Kyaw TM, Ismail Z, Selamat MI, A/L Arivanandan PK, Kyaw YW, Morgan LM, Latchumana K, Arasu K. Levels of nicotine dependency and its association with challenges to quit smoking among adult smokers in Malaysia 2021. Ann Indian Psychiatry [serial online] 2022 [cited 2022 Dec 10];6:254-64. Available from: https://www.anip.co.in/text.asp?2022/6/3/254/360080




  Introduction Top


Globally, morbidity and mortality related to nicotine dependency is a huge general prosperity challenge in the world.[1] Consistently, about 3 million deaths are found, with 10 million deaths due to smoking-related diseases expected by 2030 globally.[1] Approximately 70% of this mortality are ordinary from underdeveloped nations caused by peak nicotine dependency. Malaysia hardly escaped from this smoking menace as annually 10,000 nicotine dependence-related deaths are enlisted, and illness caused by smoking has been identified as the leading cause to years of disability-adjusted living and years of life wasted by the Malaysian population.[2],[3]

There is a scarcity of literature on the effect of various administrative methodologies on nicotine addiction. Among grown-ups, an essential proof proposes that more prohibitive measures could be related to lower pervasiveness of smoking, in spite of the fact that there are critical exemptions, perhaps because of low administrative consistence in a variety of prohibited markets.[4] Distinguishing the subgroups of adolescents that are more likely than others to create nicotine addiction is a critical step toward forestalling smoking inception and reducing tobacco use.[5],[6]

Smoke is a perplexing combination of chemicals and the added substances, formed when tobacco is burned.[7] Tobacco smoke contains nicotine as well as a monoamine oxidase inhibitor, which gives it addictive and euphoric effects. Nicotine (alkaloid) is a central nervous system-stimulant compound that can be found in the tobacco plant.[8],[9],[10] The aim of the study is to assess nicotine dependency among adult smokers in Malaysia. More specifically, this article aims to identify the barriers of smoking cessation among adults' smokers in Malaysia, to examine the association between nicotine dependency and sociodemographic characteristics of adult smokers in Malaysia, and to evaluate the association between nicotine dependency and challenges to quit smoking among adult smokers in Malaysia.


  Methodology Top


Data

In this study, we used the primary data, in which questionnaires including sociodemographic characteristics, assessment of smoking status, 21-item Challenges to Stopping Smoking (CSS-21), and Fagerstrom nicotine-dependence test were distributed through online platforms such as Facebook, Twitter, E-mail, WhatsApp, and Instagram. The data were collected from the participants who voluntarily involved in our online survey by convenient sampling conducted in Malaysia. The survey was approved by the Asia Metropolitan University's Research and Ethics Committee (No. HEC2103FOM001).

Data collection

An electronic online survey was performed on available platforms such as social media sources (Twitter, Facebook, Instagram, and WhatsApp) and institutional sources including E-mails. All adult smokers aged 18 years and above residing in Malaysia were included in our study. However, participants who are aged below 18 years, those who are not resided in Malaysia, those who are not smokers, and those with incomplete information were excluded from our study.

According to previous literature, the sociodemographic variables included in our study were age, gender, nationality, race, religion, residential, education, marital status, employment, and household's monthly income.[11],[12] Smoking status was assessed by asking whether respondents currently consume cigarettes or other tobacco products.[13] Smoking status was examined using three-response options ranging from daily, less than daily, and not at all. How many cigarette smoke per day ranging from 10 or less, 11–20, and more than 20 and assessment of age that participant first started smoking ranging from under 18, 18–34, 35–44, 45–54, 55–64 and 65 above. However, participants who smoke daily and less than daily were considered “smokers” and those who do not smoke at all were considered “nonsmokers.” Standardized and validated Global Adult Tobacco Survey (GATS) questionnaire adopted from GATS, 2nd Edition, Atlanta, GA: Centers for Disease Control and Prevention, 2011. Standardized and validated CSS-21 questionnaires were used to access the challenges of smoking cessation among the participants.[14],[15] A 2-point Likert scale (yes or no) was used for recording the responses. The total score indicated the level of challenges faced by the smokers to quit smoking. An overall greater score indicated greater challenges that participants faced. The nine items of the first subscale were predominantly related to personal (physical, psychological, or cognitive) aspects of smoking cessation. Hence, the first subscale was labeled as “intrinsic factors.” The 12 items that were loaded on the second subscale were predominantly related to social or environmental aspects of smoking cessation. Hence, it was labeled as “extrinsic factors.” The two-dimensional 21-item scale was called the “CSS-21 scale.” Nicotine dependency was assessed using the standard validated Fagerstrom Test for Nicotine Dependence questionnaires, which was adapted from Fagerstrom Test for Nicotine Dependence: A revision of the Fagerstrom Tolerance Questionnaire. British Journal of Addictions 1991; 86:1119-27. In scoring the Fagerstrom Test for Nicotine Dependence, yes/no items were scored from 0 to 1 and multiple-choice items were scored from 0 to 3. The items were summed to yield a total score of 0–10. The higher the total Fagerström score, the more intense is the participants' dependence on nicotine. The score of 8 + was regarded as high nicotine dependence, 5–7 as moderate dependence, 3–4 as low-to-moderate dependence, and 0–2 as low dependence, respectively. Age was categorized into four groups: 16–20 years, 21–39 years, 40–59 years, and ≥60 years according to the WHO and “Asian Criteria” values, 2014.[18]

Sample size determination

The sample size was determined based on Mariliis Põld et al., 2020, which found that nicotine dependence and factors related to smoking cessation in Estonia response rate was 53.1%. By taking 95% confidence interval (CI) and 80% power, the minimum required sample size was 384. According to Mariliis Põld et al., 2020, the response rate was 53.1%, and therefore, considering the attrition rate of 46.9%, the minimum sample size required in the study was 564.[14] All adult smokers aged 18 years and above residing in Malaysia were included in our study. However, participants aged below 18 years, those who are not resided in Malaysia, those who are nonsmokers, and those with incomplete information were excluded from our study.

Statistical analysis

The data were analyzed using the SPSS (IBM Corp; Armonk, New York, US). The missing data were checked, and the continuous variable (i.e., age) was categorized into four groups: 18–20 years, 21–39 years, 40–59 years, and ≥60 years according to the WHO Western Pacific region 2014. For categorical variables, associations were evaluated using the χ2 test to compare nicotine dependence among participants. Simple logistic regression (SLogR) and multiple logistic regression (MLogR) (backward method) were used to analyze the significant factors associated with nicotine dependence. The data were presented as the crude and adjusted odds ratio (OR) with the 95% CI and their corresponding P values. P < 0.05 was considered statistically significant.


  Results Top


Sociodemographic data and smoking status [Table 1] and [Table 2]
Table 1: Sociodemographic variables among respondents (n=1019)

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Table 2: Smoking status among respondents (n=1019)

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A total of 1019 respondents were recruited in the study (833 [81.7%] were male and 186 [18.3%] were female). Majority of the respondents were Indians (426; 41.8%), followed by the Malays (337; 33.1%), Chinese (178; 17.5%), and others (78; 7.7%). The mean age of the respondents was 34.46 (11.8) years. More than half of the respondents were from urban areas (755; 74.1%), whereas the rest (264; 25.9%) were from rural areas. Most of them received secondary education (399; 39.2%), followed by tertiary education (203; 19.9%), postsecondary education (184; 18.1%), preuniversity (119; 11.7%), no formal education (60; 5.9%), and primary education (54; 5.3%). A total of 531 (52.1%) respondents had a full-time job, followed by 252 (24.7%) who worked part time, 167 (16.4%) were students, and 69 (6.8%) were either unemployed or being homemakers.

More than half (553; 54.1%) of the respondents were married, followed by 314 (30.8%) who were single, 109 (10.7%) divorcee, 25 (2.5%) widowed, and 18 (1.8%) being engaged. Majority of the respondents (763; 74.9%) had monthly income of below RM 4849, followed by 236 (23.2%) with income of between RM 4850 and 10,959 and 20 (2.0%) with income of RM 10,960 or more.

A total of 830 (81.5%) respondents said that they are current smokers, whereas the other 189 (18.5%) are not. About half of them (516; 50.6%) said that they are daily smokers, 325 (31.9%) said that they are less than daily smokers, and the other 178 (17.5%) are nonsmokers. More than half of the respondents (554; 54.4%) said that they smoke for <5 years, 261 (25.5%) smoke for less than a year, 127 (12.5%) smoke for <10 years, 57 (5.6%) smoke for more than 10 years, and 20 (2.0%) smoke for between 5 and 10 years. A number of 795 (78.0%) respondents said that they smoke <10 cigarettes per day, 171 (16.8%) smoke between 11 and 20 cigarettes per day, and 53 (5.2%) smoke more than 20 cigarettes in a day.

When asked about when did they tried to smoke cigarette, 531 (52.1%) respondents said that they did it between the age of 18 and 34 years old, 351 (34.4%) said they did it when they were under 18 years old, 95 (9.3%) did it between the age of 35 and 44 years old and the rest 42 (4.2%) did it at 45 years or older. About 513 (50.3%) said that they have a history of smoking in the past, 429 (42.1%) did not have that history, and the other 77 (7.6%) just do not know. When asked how soon they smoke their first cigarette after they wake up, 494 (48.5%) said after an hour, 355 (34.8%) between half to an hour, 92 (9.0%) within 5 min, and 78 (7.7%) between 5 and 30 min.

Challenges to quit smoking among current smokers [Table 3]
Table 3: Challenges to quit smoking among current smokers using 21-item challenges to stopping smoking questionnaire (n=830)

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Intrinsic factors

Those who have withdrawal symptoms such as depression, anxiety, restlessness, irritability, sleeplessness, and craving when trying to stop smoking were 654 respondents (78.8%). A total of 593 (71.4%) felt lost without cigarettes; 560 (67.5%) were addicted to cigarettes; 604 (72.8%) felt strong emotions or feelings such as anger or feeling upset when trying to stop smoking; 570 (68.7%) felt stressful when trying to stop smoking; 590 (71.1%) ever thought about never being able to smoke again after stop smoking; 588 (70.8%) felt getting bored when trying to stop smoking; and 595 (71.7%) ever tried to see things or people which reminded them of smoking. A number of 648 (78.1%) respondents said that cigarettes are easily available to them.

Extrinsic factors

Five hundred and seventy-nine (69.8%) respondents said that they had difficulty in finding someone to help them stop smoking; 600 (72.3%) felt lack of support or encouragement from health professionals to stop smoking; 566 (68.2%) said that expensive price of stop-smoking medicines such as nicotine replacement therapy stopped them to quit smoking; 602 (72.5%) had a fear of side effects from stop-smoking medicines; 576 (69.4%) felt lack of encouragement or help from family or friends to stop smoking; 571 (68.8%) had a fear of gaining weight if stop smoking; 546 (65.8%) said that family members or friends encouraged them to smoke; 569 (68.6%) said that they had a fear of failing to stop smoking; 589 (71%) believed that medicines to stop smoking do not work; 575 (69.3%) had a fear that stop smoking may interrupt social relationships; 648 (78.1%) believed that they can stop smoking in future, if they need to; and 591 (71.2%) said that they are also using other substances such as cannabis, alcohol, etc.

Levels of nicotine dependence among current smokers based on Fagerstrom Nicotine-Dependence Score (n = 830) [Table 4]
Table 4: Levels of nicotine dependence among current smokers based on Fagerstrom nicotine dependence score (n=830)

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A total of 345 (41.6%) respondents have low-to-moderate nicotine dependence, followed by 312 (37.6%) who have moderate nicotine dependence, 158 (19%) with low nicotine dependence, and 15 (1.8%) who have high nicotine dependence.

Association of low-to-moderate nicotine dependence with sociodemographic factors among current smokers using simple logistic regression (n = 830) [Table 5]
Table 5: Association of low-to-moderate nicotine dependence with sociodemographic factors among current smokers using simple logistic regression (n=830)

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Those in the 16–20 years' age group are significantly associated with low-to-moderate nicotine dependence (P < 0.001). Other significant associated factors include urban residency (P < 0.001), those of Chinese and Malay ethnicity (P < 0.001), those with no formal education (P = 0.002), those who are working full time (P = 0.006) or part time (P < 0.001), those who are in the B40 category with monthly income of less than RM 4849 (P = 0.004), and those in the T20 category with monthly income of more than RM 10,960 (P < 0.001).

Sociodemographic factors that are not associated with low-to-moderate nicotine dependence are gender and marital status.

Association of low-to-moderate nicotine dependence with challenges to quit smoking among participants using simple logistic regression (n = 830)

The intrinsic factors of having withdrawal symptoms such as depression, anxiety, restlessness, irritability, sleeplessness, and craving when trying to stop smoking; feeling lost without cigarettes; being addicted to cigarettes; feeling strong emotions or anger; or feeling upset when trying to stop smoking are all strongly associated with low-to-moderate nicotine dependence (P < 0.001). Other intrinsic factors that are associated with low-to-moderate nicotine dependence include having something stressful when trying to stop smoking (P = 0.002); ever thought about never being able to smoke again after stop smoking (P = 0.006); and ever try to see things or people which reminded them of smoking (P = 0.009). Intrinsic factors of feeling getting bored when trying to stop smoking and cigarettes easily available to the respondents are not significantly associated with low-to-moderate nicotine dependence.

Extrinsic factors that are significantly associated with low-to-moderate nicotine dependence are having difficulty in finding someone to help to stop smoking; felt lack of encouragement or help from family or friends to stop smoking; fear of gaining weight if stop smoking; and family members or friends encouraging them to smoke, with P < 0.001. Other extrinsic factors that are associated with low-to-moderate nicotine dependence include felt lack of support or encouragement from health professionals to stop smoking (P = 0.022); expensive price of stop-smoking medicines such as nicotine replacement therapy stopped them to quit smoking (P = 0.012); feel fear of failing to stop smoking (P = 0.041); believed that medicines to stop smoking do not work (P = 0.012); fear that stop smoking may interrupt social relationships (P = 0.002); and use of other substances such as cannabis and alcohol (P = 0.026). Extrinsic factors of fear of side effects from stop-smoking medicines and believed that they can stop smoking in future, if they need to, are not significantly associated with low-to-moderate nicotine dependence.

Association of low-to-moderate nicotine dependence with sociodemographic characteristics and challenges to quit smoking among current smokers using multiple logistic regression (n = 830) [Table 6] and [Table 7]
Table 6: Association of low-to-moderate nicotine dependence with challenges to quit smoking among participants using simple logistic regression (n=830)

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Table 7: Association of low-to-moderate nicotine dependence with sociodemographic characteristics and challenges to quit smoking among current smokers using multiple logistic regression (n=830)

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All the associated significant factors found during the analysis with SLogR, including those with P value of 0.25 and less, together with those considered as scientifically and theoretically important factors were further analyzed using MLogR to see their true predictive value.

The results show that those respondents in the category of T20 (monthly income of more than RM 10,960) and fear of gaining weight if stop smoking were found to be the predictive factors for low-to-moderate nicotine dependence with sociodemographic characteristics and challenges to quit smoking among current smokers with P = 0.006 and P = 0.049, respectively. Other factors were found to be not significant.

Those respondents in the category of T20 (monthly income of more than RM 10,960) are 1.58 times more likely to have low-to-moderate nicotine dependence compared to B40 category (monthly income of less than RM 4849). Those with fear of gaining weight if stop smoking were found to have 0.65 time likely of to have low-to-moderate nicotine dependence compared to those who do not have fear. Inversely, those who do not have a fear of gaining weight if stop smoking were 1.54 times likely to have low-to-moderate nicotine dependence compared to those who have fear. According to [Figure 1] ROC curve, the model discriminated 65.2% (95% CI: 61.8–68.7) of the predicted of having low–moderate nicotine dependence. We checked the influential outliers using Cook's influential statistics and the cutoff point was 0.25. In our data, none were more than 0.25. Therefore, there is no influential outlier. In our model, since P value was more than 0.05 (not significant), the model fitted well according to Hosmer and Lameshow test (0.448). Omnibus tests of model coefficients gave a Chi-square of 289.77 onf 145 df, significant beyond 0.001. Therefore, adding age, monthly income, fear of weight gain after quitting smoking, and interaction (age and place of residence, education level, and place of residence) significantly increased the ability to predict low–moderate nicotine dependence. Therefore, adding these variables including interaction into the model improves the model. Sensitivity has shown that this rule allowed to correctly classify 505/619 (81.6%) of the current smokers where the predicted low–moderate nicotine dependence was observed. Specificity shown that this rule allowed to correctly classify 234/400 (58.5%) of the current smokers where the predicted low–moderate nicotine dependence was not observed.


  Discussion Top


Globally, morbidity and mortality related to nicotine dependency is a huge general challenge in the world. As a developing country, Malaysia aims to be a nation working together toward better health. It is an undeniable fact that tobacco use is a major and most preventable cause to morbidity and mortality in Malaysia. The study conducted aimed to assess the levels of nicotine dependency among adult smokers in Malaysia and to identify the association of nicotine dependency with sociodemographic factors and with the challenges to quit smoking, respectively, among adult smokers in Malaysia. According to a qualitative study from the primary-care perspective on the barriers of smoking cessation, the authors highlighted the five themes of specific beliefs and practices prevented smokers from quitting and suggested that clinicians have to work on these identified categories to help patients overcome barriers on smoking cessation guided by the time frames recommended.[15] Corresponding to the qualitative study mentioned, the study serves to identify and support the barriers of smoking cessation.

The common core elements widely used to measure socioeconomic status (SES) are education, income, marital status, and employment and their influence on smoking habit in different communities. Furthermore, recent approaches developed to emphasize the intrinsic and extrinsic barriers of smoking cessation using the CSS-21 questionnaire. However, there is abundant literature studying the role of SES in tobacco use, yet many aspects of this relationship remain underexplored. The results augment the popular phenomenon that smoking and nicotine dependence were highly prevalent among men in Malaysia. There was a high prevalence among the urban regions and Indian races. It was found that individual educational level was inversely associated with the probability of nicotine dependence with a high prevalence among secondary school education. Moreover, our data indicate that full-time employment associated with high rate of cigarette consumption. Our findings were coherent with the results found in many Asian and Western studies.[16],[17]

In the current study, higher individual monthly income showed a significant negative association with nicotine dependence. In terms of the barriers of quitting smoking, the most frequent intrinsic barriers are those who have withdrawal symptoms such as depression, anxiety, restlessness, irritability, sleeplessness, and craving, when trying to stop smoking were 654 respondents (78.8%) and the easy availability to cigarettes (78.1%). On the other hand, the most frequent extrinsic barriers reported are the belief of capability of stopping smoking in future (78.1%) and the fear of having side effects after stopping smoking (72.5%). These findings are consistent with the results from some Western countries, but differed from a previous Chinese study, where individuals with lower incomes are more likely to be nicotine addicted.[18] Perhaps individuals with higher incomes are more likely to afford tobacco products and therefore consume more. Living in communities with higher overall educational levels and good income was associated with a decreased risk of nicotine dependence.[19] This may be because the people with higher levels of education tend to have a healthier lifestyle. The strong association between both contextual and individual educational level and risk of nicotine addiction in our study suggests that implementing robust smoking cessation programs to reduce tobacco use in Malaysia should focus on less educated people in parallel with those living in communities with lower levels of education.[7]

Relapse due to nicotine dependency is being reported as a reason for not quitting smoking, which is consistent with our finding where withdrawal symptoms were one of the challenges. Nicotine is highly addictive and is predicted that one in two long-term smokers will die from tobacco addiction.[20] One of the ways to combat this is using nicotine replacement therapies (NRTs) such as gum and transdermal patch, which are able to increase the rate of quitting by 50%–70%, by reducing the withdrawal symptoms.[21] To address these issues, it is critical to improve compliance. Furthermore, in retrospective studies, smokers consistently report that relapse to smoking often occurs in situations involving strong emotions such as anger or upset and that smokers who smoke more frequently in negative affect situations are more likely to relapse.[22] Moreover, Xu et al. found that surges in negative affect often began a few hours before a smoking relapse occurred.[23] Thus, acute stressor responses and the resulting increasingly growing negative affect may be the most important factors in relapse.[24] Finally, changes in negative affectivity seem consistently related to the persistence of the urge to smoke. Our study revealed that being addicted to cigarettes is the least barrier to smoking cessation. These findings were contradicted with Indian studies that revealed that a higher percentage of nicotine dependence was associated with the number of cigarettes being addicted in mixed form.[25],[26] To confirm nicotine dependence among smokers, future studies need to correlate between biomarkers of exposure to cigarette smoke and responses to the specific number of cigarettes being addicted.

The current study had the following limitations. First, it is based on self-reported questionnaire and may therefore be liable for recall bias. Second, the effects of SES on smoking dose or levels of tobacco consumption have been more challenging to be explored because SES is multifactorial construct that cannot be directly measured by a single indicator. Third, our results revealed a significant correlation between the intrinsic and extrinsic barrier scores; however, it is not deeply analyzed using regression modeling. In conclusion, the study depicts a high prevalence of smoking and nicotine dependence and low level of attempting to quit smoking among current smokers in Malaysia. In addition, nicotine dependence varies by both contextual and individual SES variables. These findings highlight the need for tobacco cessation interventions to target men who are full employed, less educated, and from poorer communities.


  Conclusion Top


Therefore, services for cessation of smoking should be designed and implemented with the degree of nicotine dependence and pattern usage in mind. There should be more public health education about the dangers of smoking as well as more focus on motivation among smokers and their families.

Acknowledgment

We would like to contribute our heartfelt thanks to the participants of the study. We also would like to thank to Center of Research and Development, Asia Metropolitan University, for the approval of our research ethics application.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

Appendices





Cook's influential statistics-cut off point is 0.25. In our data, none is more than 0.25. Therefore, there's no influential outlier.

Hosmer and Lameshow test – 0.448. In our model, since P value is more than 0.05 (not significant), the model fits well.

Cox and Snell R square – 0.248, Nagelkerke R square - 0.335

Omnibus test - Omnibus tests of model coefficients gave a Chi-square of 289.77 onf 145 df, significant beyond 0.001. Therefore, adding age, monthly income, fear of weight gain after quitting smoking, and interaction (age and place of residence, education level, and place of residence) significantly increased the ability to predict low–moderate nicotine dependence. Therefore, adding these variables including interaction into the model improves the model.

Sensitivity - 81.6, It is shown that this rule allowed to correctly classify 505/619 (81.6%) of the current smokers where the predicted low–moderate nicotine dependence was observed.

Specificity - 58.5. It shows that this rule allowed to correctly classify 234/400 (58.5%) of the current smokers where the predicted low–moderate nicotine dependence was not observed.



 
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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

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