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 Table of Contents  
ORIGINAL ARTICLE
Year : 2013  |  Volume : 1  |  Issue : 3  |  Page : 174-179

Risk factors associated with Fagerström status with nicotine dependence in referred smokers for cessation


1 Department of Biostatistics and Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
2 Health Center Number 2, Isfahan University of Medical Sciences, Isfahan, Iran
3 Department of Medical Science, Islamic Azad University, Najafabad Branch, Isfahan, Iran
4 Department of Medical Science, Islamic Azad University, Najafabad Branch; Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Date of Web Publication20-Mar-2014

Correspondence Address:
Rokhsareh Meamar
Isfahan, Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2347-9019.129162

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  Abstract 

Context: The most widely and classically used measures in tobacco dependence assessment is The Fagerström Test for Nicotine Dependence (FTND). There are few articles studying the factors associated with Fagerström test among Iranian smokers. Our aim in this study is the determination of the association between sociodemographic factors and FTND test. Materials and Methods: This cross-sectional study including 673 subjects was obtained from people who were referred to the health center for smoking cessation. The questionnaire included items on sociodemographic information and information on smoking cigarettes and history of cessation. Result: Mean ± SD of age and age of onset smoking were 39.7 ± 1.1 and 18.6 ± 5.5, respectively. Mean ± SD with scale ranging from consuming number of cigarettes per day and FTND of smokers, were 22.1 ± 11.5 with 2-90 and 7.4 ± 0.81 with 4-9, respectively. Association of demographic and some other characteristics with Fagerstrom status for Nicotine Dependence were studied in the smoking participants. The ORs [95% CI] were as follows: In primary education level 2.2 [1.1-4.9]; number of smoking per day 1.3 [1.2-1.4]; duration of smoking between 10-19, 20-29, and more than 30 years 2.5 [1.1-5.6], 2.2 [0.93-5.2], and 4.3 [1.7-10.7], respectively; without history of previous quit attempt 2.1 [1.1-4.1]; nicotine concentration more than 0.8 mg/pack 4.8 [2.7-8.4]; enjoying in routine activities 2.9 [1.3-6.2]. Conclusion: The above results suggest that there are significant associations between Fagerstrφm status and smokingrelated behaviors in the Iranian population, consistent with previous reports worldwide. These factors should be considered to have appropriate public health and policy response.

Keywords: Cigarette smoking, dependency, Fagerström test, sociodemographic


How to cite this article:
Maracy M, Etedali F, Safaie F, Ghasemi R, Meamar R. Risk factors associated with Fagerström status with nicotine dependence in referred smokers for cessation. Int J Health Syst Disaster Manage 2013;1:174-9

How to cite this URL:
Maracy M, Etedali F, Safaie F, Ghasemi R, Meamar R. Risk factors associated with Fagerström status with nicotine dependence in referred smokers for cessation. Int J Health Syst Disaster Manage [serial online] 2013 [cited 2024 Mar 28];1:174-9. Available from: https://www.ijhsdm.org/text.asp?2013/1/3/174/129162


  Introduction Top


Tobacco consumption is presented as one of the leading causes of preventable death and morbidities in the world. [1],[2] There are 1.3 billion smokers in the world [3] and tobacco-related deaths are expected to increase to 8.3 million until 2030, [4] whereas this rising trend is very apparent in the developing countries, so 80% of all will happen in these populations. [5]

There are over 7000 chemical substances and compounds in cigarette smoke but nicotine is the key chemical composition that induces and sustains cigarette addiction [1] and plays a key role in tobacco dependence. [6] Compared to the earlier designs and contents, the design and contents of tobacco products have been made more attractive and addictive. [7]

The most widely and classical used measure in tobacco dependence assessment is The Fagerström Test for Nicotine Dependence (FNTD). [8] A questionnaire was asked regarding number of cigarettes per day, time of first cigarette, difficulty withdrawing from smoking when ill or when prohibited, which cigarette would someone give up in disgust, and smoking frequency throughout the day. [8],[9] Their predictive validity among tobacco smokers. [8],[9],[10],[11] in various countries were generally used in the study. [12]

The important point in applying FNTD, is that the measured scale of nicotine dependency negatively influences the chances of successful smoking cessation and quit attempts approach. [13],[14] The value of FNTD has been determined as a predictor of smoking outcomes in England and Canada. [10],[15] On the other hand, smoking cessation still is a complex problem that not only smokers but also the total healthcare system has been involved. [16]

Iran recently presents 62% rise in the manufacturing of cigarettes from the period of 2000-2004 to 2005-2009. [17] This pronounced market was observed more in developing countries. [18] Also, in Iran the prevalence rate of current and daily cigarette smoking is 12.5% [23.4% males and 1.4% females; burden: 6.1 million] and 11.3% [21.4 males and 1.4 females; burden: 5.6 million], respectively. [19] Approximately, consumption of 30 billion cigarette sticks was estimated a year in Iran. [17] Although the public health concerns and government's support on smoking cessation have been developing, quitting smoking is a challenge in this country. The primary objective of this analysis was to use the FTND in the Iranian adult population and determine the association between sociodemographic factors and FTND test. Knowledge of the variables that will predict outcome can be used as a basis for preventive intervention, policy makers and future studies.


  Material and Methods Top


This is a cross-sectional study that was carried out from 2009 to 2011. Scientific and technical coordination of this study was performed by Health Center number 2 in Isfahan, Iran. The data selection of 673 subjects was obtained randomly from people who referred to the health center for smoking cessation. Detailed information is reported elsewhere. [20] This research study was carried out with descriptive and analytical aims. We included all cigarette smokers who referred to the cessation center during the period of study. However, those who were treated with methadone or were involved in psychiatric treatment or having addiction history to other addictive drugs were excluded from the study. Participants were informed about the aims of the study and provided consent. The interview was performed by an expert practitioner.

We asked participants to fill the questionnaire consisting of sociodemographic information and some other characteristics of smoking behavior. The questionnaire was structured with variables such as age, marital status, education, job, age of onset of smoking, [length] years of smoking, consuming number of cigarettes per day and its brand, number of cessations and its duration, nicotine concentration [mg/pack], knowledge of smoking, past medical history [heart, lung, gastrointestinal, and cancer] and other problems including sleep, mood, stress, joy, and entertainment. Marital status was divided into three groups as single; married and divorced. Due to the lower number of divorce participants, we combined this group with married smokers. Educational level was categorized as illiterate; primary; undergraduate; and graduate. Primary level included all sessions before high school who underwent high school even without receiving the diploma. Undergraduates were persons who passed the high school and continued their education in undergraduate position but not in a University. Graduates were people who passed the entrance exam of a University or graduated from University. We divided job status into four groups as employed that means people who work in offices and others like this, unemployed person is one who does not have a job, selfemployed means persons who are employed themselves, and worker which means person who works in industries. Medical history, other problems and knowledge of smoking filled by the patients' answers were [only yes/no]. The nicotine dependence of smokers was evaluated by the FTND. The 6-item FTND was used to assess physical dependence on tobacco smoking. Score of each item varied between 0, 1, 2 or 3. The scores were added in all of the items on the scale ranging from 0 to 10. Score of ≤ 4 was classified as 'mild dependence' while score of > 8 equate to 'very sever dependence' and between them was classified as moderate dependency. However, in our study the number of participants in mild dependence was very low so the mild and moderate groups were addressed as moderate dependency group.

To demonstrate the initial results, Chi-square test and t-test were carried out to assess the relationship between Fagerstrom status and sociodemographic information and some other characteristics of smoking behavior. A multiple logistic regression stepwise analysis were executed to detect adjusted effect of demographic and some other characteristics on Fagerstrom status in the smoking participants based on the ORs with 95% confidence intervals (CIs). Data were analyzed using SPSS software v. 18 (SPSS Inc. Chicago, Illinois). P value less than 0.05 were considered as significant level.


  Results Top


We found 99.2% of patients were men. Mean ± SD of age and age of onset smoking were 39.7 ± 1.1 and 18.6 ± 5.5, respectively. Mean ± SD with scale ranging consuming number of cigarettes per day and FTND of smokers were 22.1 ± 11.5 with 2-90 and 7.4 ± 0.81 with 4-9, respectively. [Table 1] demonstrates results of the unadjusted relationship between Fagerstrom status and some characteristics in the study population. Initial analysis revealed that there were statistically significant relationship between Fagerstrom status and age, marital status, and education status.

Being sever dependency based on FTND test was associated with smokers who had not history of cessation period, higher number and duration of cigarettes smoking, Iranian brand, high nicotine concentration, medical history of lung, sleep disorder and enjoyment and entertainment as routine activities.

[Table 2] presents association of demographic and some other characteristics with Fagerstrom status for Nicotine Dependence in the smoking participants using Multiple Logistic Regression model. The ORs [95% CI] were as follows: In primary education level 2.2 [1.1-4.9]; number of smoking per day 1.3 [1.2-1.4]; duration of smoking between 10-19, 20-29, and more than 30 years 2.5 [1.1-5.6], 2.2 [0.93-5.2], and 4.3 [1.7-10.7], respectively; without history of previous quit attempt 2.1 [1.1-4.1]; nicotine concentration more than 0.8 mg/pack 4.8 [2.7-8.4]; having enjoyment in routine activities 2.9 [1.3-6.2].
Table 1: Summary results of the unadjusted relationship between Fangeshtrom status and some characteristics in the study population

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Table 2: Effect of demographic and some other characteristics on Fangeshtrom status in the smoking participants using Logistic Regression model‡

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  Discussion Top


There are not many publications in Iran discussing factors that could influence on Fangeshtrom test" one of the important determinants of nicotine dependency". In our study, low education level and high number of smoking per day, higher years of smoking cigarettes, high nicotine concentration and participant without history of quit attempt and having enjoyed in routine activities were factors associated with sever Fangeshtrom status.

The mean ± SD FTND scores of smokers were measured 7.4 ± 0.81 in our population but this mean between adult smokers in the United States were 4.3-4.6. [21],[22],[23] and 2.8-3.4 in European countries. [24],[25],[26]

This discrepancy is explained that all of the precipitants in our study were referred to cessation center for quit smoking, in the other hand smokers in other countries was decided between adult smoker in general population.

FNTD is the scale of nicotine dependency as being more of a measure of physical than psychosocial addiction. Many previous studies showed that the smokers with severe nicotine dependence were less successful in quitting smoking. [27],[28],[29],[30],[31] Therefore, we could use FNTD assessment and factors that influence it for prediction of smoking cessation between tobacco smokers with different nicotine dependency.

In previous studies, the role of various factors such as age, sex, education, occupation, economic states, social relationships, smoking characteristics, psychological problems, physical or mental health have been surveyed, [28],[30],[31],[32],[33],[34] also in our research evaluated influence such and another items.

Like in other Asian countries, our result showed that the men attending smoking cessation clinic were far more than woman, which is probably due to negative cultural, religious and social attitudes toward women smoking [35],[36] whilst smoking by women is not socially formal in countries such as Iran. In mostly developing countries, women tend to have lower rates of smoking, start smoking in older age, and consume fewer daily cigarettes. [37] This may also explain the significantly higher number of Iranian male smokers in our study. Given the significantly higher prevalence of male smokers, cessation should focus more on males. In the other hand, in Muslim countries stopping smoking for religious reasons and recommendations may be customary and impress outcomes. [38]

Number of years consuming cigarettes and the number of cigarettes smoked per day are powerful risk factor for Fangeshtrom status. Like our survey, FTND scales correlated positively with cigarettes per day, increased frequency of smoking, longer lifetime use and negatively with time to first cigarette, provocation to quit and age at first smoking. [39],[40]

One early hypothesis of tobacco addiction is that firstly, psychological dependence developed then followed by conditioned responses related to reciprocating states, and finally physical dependence occurred. [41],[42] The data strongly support the theory that each subsequent stage in the progression of physical addiction especially number of cigarettes per day and duration of smoking in year induce an increase addiction in tobacco consumption.

In our investigation, the average number of cigarettes per day is 22.3; the number of cigarettes smoked per day increases with age to middle life and then reduces with advancing age, which are significantly higher than related studies [43],[44] and consistent with Birth Cohort analysis using NHIS. [44]

Although the number of cigarettes smoked per day was related strongly to the stages of FNTD states, participants without history of quiet attempt experience sever FNTD states than groups with cessation under 6 or more than 6 months.

In previous studies, it was reported that individuals in more advanced stages have shorter period of cessation experience. When physical addiction to tobacco in smokers was progressed, withdrawal symptoms were presented during prolonged abstinence, [45] for this reason, period of abstinence was shorter and more difficulty for individuals in more advanced stages.

In the other hand, contradictory results was reported for correlation between frequency of success to quick smoking with previous attempts to stop smoking, this relationship was illustrated both negatively and positively in some reports.

High nicotine dependence is associated with lower quality of life, lower work productivity, lower education; lack of health insurance and higher healthcare use. [46] In many previous studies, level of education is one of the important predictors for smoking cessation. [32],[47] Our results similar to previous studies. [48],[49] showed that lower educational levels have shown a significant association with higher prevalence of smoking and nicotine dependence. It seems with rising level of education between smokers, successful in smoking cessation and less of start smoking are more prevalent. [50]

In addition, we investigated number of baseline psychosocial factors such as mood, stress, sleep, enjoyment, and entertainment. In this current evaluation of Iranian smokers, only having pleasure in routine activities had a positive correlation with FNTD. Findings in the literature have also reported that smokers with psychiatric disorders not only have higher levels of nicotine dependence [51] but also higher cigarette consumption. [52]

Inappropriate sleep quality, depression [53],[54] and impaired cognitive function have been often reported. The possible mechanism may be due to the toxic effects of cigarette components for human brain. In addition, smokers with depression report higher rates of smoking [52] and nicotine dependence, [55] and was also associated with a lower chance of smoking of quitting smoking and avoiding relapse. [52] This controversy between our result and these reports should be defined that questionnaire used in our survey was filled only by self-report in the smokers, we did not have a strong documents about these data; however, we guess that having enjoyment in routine activities is a secondary event following tobacco smokers in sever Fangeshtrom status.

A potential limitation of this data is the possible biases induced by selfreporting. Second, FTND measures physical dependence do not consider other aspects of dependency, as defined by DSM-IV and ICD-10. Also, the ability of this test in predicting withdrawal symptoms and smoking cessation is not complete. [56] As regards the smoking cessation focused on psychosocial dependency that is not predicted only by measuring the level of dependence by FTND. [3]

Despite these limitations, these findings have clinical implications. Our study reports important findings relating to both the prevalence of smoking and nicotine dependence, factor related to them in Iran. It is important that similar cross-sectional epidemiological studies are carried out in the future, in order to determine the prevalence of smoking and nicotine dependence as regards that counseling services are less frequently available in developing counties such as Iran for designing appropriate and targeted intervention and cessation programs for more help to subgroups with the highest rates of smoking and nicotine dependence.

 
  References Top

1.Picco L, Subramaniam M, Abdin E, Vaingankar JA, Chong SA. Smoking and nicotine dependence in Singapore: Findings from a cross-sectional epidemiological study. Ann Acad Med Singapore 2012;41:325-34.  Back to cited text no. 1
    
2.Salameh P, Jomaa L, Farhat G, Zeghondi H, Gerges N, Issa C, et al. Lebanese National Conference for Health in Universities study group. The Young Adults′ Cigarette Dependence [YACD] score: An improved tool for cigarette dependence assessment in university students. Addict Behav 2013;38:2174-9.  Back to cited text no. 2
    
3.Franc J, Etter O. Comparing the validity of the Cigarette Dependence Scale and the Fagerstr¨om Test for Nicotine Dependence. Drug Alcohol Depend 2008;95:152-9.  Back to cited text no. 3
    
4.World Health Organization. Report on the global tobacco epidemic, 2008. The MPOWER package. Geneva: World Health Organization;2008.  Back to cited text no. 4
    
5.Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006; 3(11):e442. doi:10.1371/journal.pmed.0030442.  Back to cited text no. 5
    
6.Salameh P, Khayat G, Waked M. The Lebanese Cigarette Dependence [LCD] Score: A Comprehensive Tool for Cigarette Dependence Assessment. Int J Behav Med 2013.  Back to cited text no. 6
    
7.Rockville, US Department of Health and Human Services. A Report of the Surgeon General: How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-attributable Disease, 2010. Available from: http://www.surgeongeneral.gov/library/tobaccosmoke/report/full_report. pdf. [Last accessed on 2011 Dec 15].  Back to cited text no. 7
    
8.Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The Fagerström Test for Nicotine Dependence: A revision of the Fagerström Tolerance Questionnaire. Br J Addict 1991;86:1119-27.  Back to cited text no. 8
    
9.Fagerström KO, Schneider NG. Measuring nicotine dependence: A review of the Fagerström tolerance questionnaire. J Behav Med 1989;12:159-82.  Back to cited text no. 9
    
10.Kozlowski LT, Porter CQ, Orleans CT, Pope MA, Heatherton T. Predicting smoking cessation with self-reported measures of nicotine dependence: FTQ, FTND, and HSI. Drug Alcohol Depend 1994;34:211-6.  Back to cited text no. 10
    
11.Pinto RP, Abrams DB, Monti PM, Jacobus SI. Nicotine dependence and likelihood of quitting smoking. Addict Behav 1987;12:371-4.  Back to cited text no. 11
    
12.Meneses-Gaya IC, Zuardi AW, Loureiro SR, Crippa JA. Psychometric properties of the Fagerström Test for nicotine dependence. J Bras Pneumol 2009;35:73-82.  Back to cited text no. 12
    
13.Cosci F, Corlando A, Fornai E, Pistelli F, Paoletti P, Carrozzi L. Nicotine dependence, psychological distress and personality traits as possible predictors of smoking cessation. Results of a double-blind study with nicotine patch. Addict Behav 2009;34:28-35.  Back to cited text no. 13
    
14.Mooney ME, Jhnson EO, Breslau N, Bierut LJ, Hatsukami DK. Cigarette smoking reduction and changes in nicotine dependence. Nicotine Tob Res 2011;13:426-30.  Back to cited text no. 14
    
15.Fidler JA, Shahab L, West R. Strength of urges to smoke as a measure of severity of cigarette dependence: Comparison with the Fagerström Test for Nicotine Dependence and its components. Addiction 2011;106:631-8.  Back to cited text no. 15
    
16.Baddini-Martinez J, de Padua AI. Can an index of smokers′ emotional status predict the chances of success in attempts to quit smoking? Med Hypotheses 2013;80:722-5.  Back to cited text no. 16
    
17.Meysamie A, Ghaletaki R, Zhand N, Abbasi M. Anonymous: Industry and Mine group: A 62% increase in cigarette production in Iran. Iran J Public Health 2012;41:1-14.  Back to cited text no. 17
    
18.WHO report on the global tobacco epidemic: The empower package. Geneva: World Health Organization; 2008.  Back to cited text no. 18
    
19.Meysamie A, Ghaletaki R, Zhand N, Abbasi M. Cigarette smoking in Iran. Iran J Public Health 2012;41:1-14.  Back to cited text no. 19
    
20.Meamar R, Etedali F, Sereshti N, Sabour E, Samani MD, Ardakani MR, et al. Predictors of smoking cessation and duration: Implication for smoking prevention. Int J Prev Med 2013;4: S194-200.  Back to cited text no. 20
    
21.Furberg H, Sullivan PF, Maes H, Prescott CA, Lerman C, Bulik C, et al. The types of regular cigarette smokers: A latent class analysis. Nicotine Tob Res 2005;7:351-w60.  Back to cited text no. 21
    
22.Hellebush S. Committed Quitters Study: Q2 Marketing Research Inc; Cincinnati, OH: 1994.  Back to cited text no. 22
    
23.Shiffman S, Pillitteri JL, Burton SL, Rohay JM, Gitchell JG. Smokers′ beliefs about ′′Light′′ and ′′Ultra Light′′ cigarettes. Tob Control 2001;10:i17-23.  Back to cited text no. 23
    
24.John U, Meyer C, Hapke U, Rumpf HJ, Schumann A, Adam C, et al. The Fagerstrom test for nicotine dependence in two adult population samples-potential influence of lifetime amount of tobacco smoked on the degree of dependence. Drug Alcohol Depend 2003;71:1-6.  Back to cited text no. 24
    
25.Kraft P, Svendsen T, Hauknes A. Intention to stop smoking among Norwegian smokers: The role of nicotine dependence, type of cigarettes, and age at onset of daily smoking. Addict Behav 1998;23:133-7.  Back to cited text no. 25
    
26.LaGrue G, Grimaldi B, Demaria C, Loufrani E, Levalliant C. Epidemiologie de la depandance physique a la nicotine. J Depend Tabag 1989;40:2448-50.  Back to cited text no. 26
    
27.Abdullah AS, Ho LM, Kwan YH, Cheung WL, McGhee SM, Chan WH. Promoting smoking cessation among the elderly: What are the predictors of intention to quit and successful quitting? J Aging Health 2006;18:552-64.  Back to cited text no. 27
    
28.Duncan CL, Cummings SR, Hudes ES, Zahnd E, Coates TJ. Quitting smoking: Reasons for quitting and predictors of cessation among medical patients. J Gen Intern Med 1992;7:398-404.  Back to cited text no. 28
    
29.Hyland A, Li Q, Bauer JE, Giovino GA, Steger C, Cummings KM. Predictors of cessation in a cohort of current and former smokers followed over 13 years. Nicotine Tob Res 2004;6:S363-9.  Back to cited text no. 29
    
30.Hymowitz N, Cummings KM, Hyland A, Lynn WR, Pechacek TF, Hartwell TD. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tob Control 1997;6:S57-62.  Back to cited text no. 30
    
31.Sherman SE, Wang MM, Nguyen B. Predictors of success in a smoking cessation clinic. J Gen Intern Med 1996;11:702-4.  Back to cited text no. 31
    
32.Husten CG, Shelton DM, Chrismon JH, Lin YC, Mowery P, Powell FA. Cigarette smoking and smoking cessation among older adults: United States, 1965-94. Tob Control 1997;6:175-80.  Back to cited text no. 32
    
33.Kaplan MS, Newsom JT, McFarland BH. Older adults′ contact with health practitioners: Is there an association with smoking practices? J Gerontol A Biol Sci Med Sci 2002;57:M343-6.  Back to cited text no. 33
    
34.Lam TH, He Y, Shi QL, Huang JY, Zhang F, Wan ZH, et al. Smoking, quitting, and mortality in a Chinese cohort of retired men. Ann Epidemiol 2002;12:316-20.   Back to cited text no. 34
    
35.Lam TH, Li ZB, Ho SY, Chan WM, Ho KS, Tham MK, et al. Smoking, quitting and mortality in an elderly cohort of 56,000 Hong Kong Chinese. Tob Control 2007;16:182-9.  Back to cited text no. 35
    
36.Yang G, Fan L, Tan J, Qi G, Zhang Y, Samet JM, et al. Smoking in China: Findings of the 1996 National Prevalence Survey. JAMA 1999;282:1247-53.  Back to cited text no. 36
    
37.Memon A, Moody PM, Sugathan TN, el-Gerges N, al-Bustan M, al-Shatti A, et al. Epidemiology of smoking among Kuwaiti adults: Prevalence, characteristics, and attitudes. Bull World Health Organ 2000;78:1306-15.  Back to cited text no. 37
    
38.Ng N, Weinehall L, Ohman A. If I don′t smoke, I′m not a real man′- - Indonesian teenage boys′ views about smoking. Health Educ Res 2007;22:794-804.  Back to cited text no. 38
    
39.Rohsenow DJ, Martin RA, Tidey JW, Monti PM, Colby M. Comparison of the Cigarette Dependence Scale with four other measures of nicotine involvement: Correlations with smoking history and smoking treatment outcome in smokers with substance use disorders. Addict Behav 2013;38:2409-13.  Back to cited text no. 39
    
40.Difranza JR, Wellman RJ, Savageau JA. Does progression through the stages of physical addiction indicate increasing overall addiction to tobacco? Psychopharmacology (Berl) 2012;219:815-22.  Back to cited text no. 40
    
41.Russell MA. Cigarette dependence. I. nature and classification. Br Med J 1971 8;2:330-1.  Back to cited text no. 41
    
42.Russell MA. Cigarette smoking: Natural history of a dependence disorder. Br J Med Psychol 1971;44:1-16.  Back to cited text no. 42
[PUBMED]    
43.Tramacere I, Gallus S, Pacifici R, Zuccaro P, Colombo P, La Vecchia C. Smoking in young and adult population, Italy 2009. Tumori 2011;97:423-7.  Back to cited text no. 43
    
44.Burns DM, Major JM, Shanks TG. Changes in number of cigarettes smoked per day: Crosssectional and birth cohort analyses using NHIS. Smoking Tob Control Monogr 2003;15:83-99.  Back to cited text no. 44
    
45.Hughes JR. Effects of abstinence from tobacco: Valid symptoms and time course. Nicotine Tob Res 2007;9:315-27.  Back to cited text no. 45
[PUBMED]    
46.Schnoll RA, Goren A, Annunziata K, Suaya JA. The prevalence, predictors, and associated health outcomes of high nicotine dependence using three measures among US smokers. Addiction 2013;108:1989-2000.  Back to cited text no. 46
    
47.Zhu BP, Giovino GA, Mowery PD, Eriksen MP. The relationship between cigarette smoking and education revisited: Implications for categorizing persons′ educational status. Am J Public Health 1996;86:1582-9.  Back to cited text no. 47
    
48.Faseru B, Nollen NL, Mayo MS, Krebill R, Choi WS, Benowitz NL, et al. Predictors of cessation in African American light smokers enrolled in a bupropion clinical trial. Addict Behav 2013;38:1796-803.  Back to cited text no. 48
    
49.Chandola T, Head J, Bartley M. Sociodemographic predictors of quitting smoking: How important are household factors? Addiction 2004;99:770-7.  Back to cited text no. 49
    
50.Kim YN, Cho YG, Kim CH, Kang JH, Park HA, Kim KW, et al. Socioeconomic indicators associated with initiation and cessation of smoking among women in Seoul. Korean J Fam Med 2012;33:1-8.  Back to cited text no. 50
    
51.John U, Meyer C, Rumpf HJ, Hapke U. Smoking nicotine dependence and psychiatric comorbidity: A population-based study including smoking cessation after three years. Drug Alcohol Depend 2004;76:287-95.  Back to cited text no. 51
    
52.Lasser K, Boyd JW, Woolhandler S, Himmelstein DU, McCormick D, Bor DH. Smoking and mental illness: A population-based prevalence study. JAMA 2000;284:2606-10.  Back to cited text no. 52
    
53.Baker TB, Piper ME, McCarthy DE, Majeskie MR, Fiore MC. Addiction motivation reformulated: An affective processing model of negative reinforcement. Psychol Rev 2004;111:33-51.  Back to cited text no. 53
    
54.Kassel JD, Stroud LR, Paronis CA. Smoking, stress, and negative affect: Correlation, causation, and context across stages of smoking. Psychol Bull 2003;129:270-304.  Back to cited text no. 54
    
55.Grant BF, Hasin DS, Chou P, Stinson FS, Dawson DA. Nicotine dependence and psychiatric disorders in the United States: Results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry 2004;61:1107-15.  Back to cited text no. 55
    
56.Shiffman S, Waters A, Hickcox M. The nicotine dependence syndrome scale: A multi dimensional measure of nicotine dependence. Nicotine Tob Res 2004;6:327-48.  Back to cited text no. 56
    



 
 
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