Indian Journal of Psychological Medicine
Users Online: 600 
  About Us | Editorial Board | Search | Ahead of print | Current Issue | Archives | Instructions | Contact | Advertise | SubmissionLogin 
Wide layoutNarrow layoutFull screen layoutHome Print this page Email this page Small font sizeDefault font sizeIncrease font size


 
 Table of Contents    
REVIEW ARTICLE
Year : 2017  |  Volume : 39  |  Issue : 4  |  Page : 392-398  

Interrelations of level of urinary cotinine and score for fagerstrom test for nicotine dependence among beedi smokers, and smokeless tobacco users in India


1 Department of Psychiatric Nursing, Nitte Usha Institute of Nursing Sciences, Nitte University, Mangalore, Karnataka, India
2 Department of Oral Biology and Genomic Studies, A.B. Shetty Memorial Institute of Dental Sciences, Nitte University, Mangalore, Karnataka, India

Date of Web Publication28-Jul-2017

Correspondence Address:
Chitta Chowdhury
Department of Oral Biology and Genomic Studies, A.B. Shetty Memorial Institute of Dental Sciences, Nitte University, Deralakatte, Mangalore - 575 018, Karnataka
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0253-7176.211758

Rights and Permissions
   Abstract 

Background: Tobacco related diseases is largely preventable and can stop pre-mature death. According to World Health Organization (WHO), the prevalence rate of smoking is 28.6% (40% among males and 18.2% among females).[1] Beedismoking and tobacco chewing are the commonest forms of tobacco habits in India, and strongly associated with oral cancer in India.[2] There are methods to estimation of severity of tobacco dependency, of them FTND is identified. The score for FTND is used for cigarette smoking, but we do not know the FTND score of ST users and Beedi smokers in India. Therefore, keeping the study in plan, we aim a systemic review with the following objective.
Objectives: 1. To pursue a review of published researches on interrelations between Beedi smoking and FTND score. 2. To pursue a review of published researches on interrelations between consumption of ST and FTND score. Materials and Methods: A systematic search of published papers were examined from three different electronic databases namely Pubmed, Cochrane library, and ProQuest . The inclusion criteria and exclusion criteria was set based on commonality of the studies which was looked through the objectives. Total of four papers of its category were found, and those met the criteria for inclusion factors. Results: Seventy-one articles were screened initially and forty-three articles were excluded and twenty-eight articles were screened, out of which twenty articles were excluded based on inclusion criteria. The abstracts of remaining eight articles were reviewed and four were removed because of duplication of the data. Finally, four articles were included for review after three stages of screening. Review results revealed that out of four selected reviews, one research study finding was interrelated with FTND score and Beedi and ST users. This study results also revealed that there is not a set of research carried out on FTND score for Beedi smokers and ST users.

Keywords: Beedi smokers, Fagerstrom Test for Nicotine Dependence, smokeless form of tobacco users


How to cite this article:
Vinoth Kumar NM, Khijmatgar S, Chowdhury C. Interrelations of level of urinary cotinine and score for fagerstrom test for nicotine dependence among beedi smokers, and smokeless tobacco users in India. Indian J Psychol Med 2017;39:392-8

How to cite this URL:
Vinoth Kumar NM, Khijmatgar S, Chowdhury C. Interrelations of level of urinary cotinine and score for fagerstrom test for nicotine dependence among beedi smokers, and smokeless tobacco users in India. Indian J Psychol Med [serial online] 2017 [cited 2017 Oct 17];39:392-8. Available from: http://www.ijpm.info/text.asp?2017/39/4/392/211758


   Introduction Top


Smoking and smokeless form of tobacco (ST) consumption is common in India. Most tobacco users begin the habitat young age. Smoking forms include cigarette, beedi, hooka, and chutta. Tobacco consumption can cause various cancers and cardiovascular disease.[1] ST users are in high numbers in India. Cotinine is a major metabolite of nicotine in body fluids. Its concentration is high in urine than in blood because of its pH. Self-reported questionnaires likely to underestimate the prevalence of tobacco users.[2] Research studies have found that urinary cotinine level may be positively correlate with smokers who claimed to be nonsmokers. Assessing nicotine level among tobacco users is a challenging task to the tobacco researchers. Fagerstrom Test for Nicotine Dependence (FTND), heaviness of smoking index (HIS) score and urinary cotinine level can be used as a reliable method to assess nicotine dependent level among tobacco users.[3] The review evidence may help the researcher to identify the exact concurrence between the score of FTND and HSI among beedi smokers and ST users which may be different from others.


   materials and Methods Top


The method for this review was according to PRISMA guidelines (http://www.equator-network.org/reporting-guidelines/prisma/). The inclusion and exclusion criteria are highlighted in the [Table 1].
Table 1: Summary of the Inclusion and Exclusion Criteria

Click here to view


The authors performed a review of existing literature published till date using keywords as, FTND, HSI, urinary cotinine, Fagerstrom Test for Nicotine Dependence, Heaviness of Smoking Index, FTND and urinary cotinine, HSI and urinary cotinine, FTND and beedi, FTND and gutka, HSI and beedi, FTND and snuff, FTND and pan, HSI and tobacco users, HSI and urine Cotinine level, urinary cotinine and Fagerstrom Test for Nicotine Dependence or FTND and Heavy of Smoking Index or HSI, Urinary Cotinine and Fagerstrom Test for Nicotine Dependence or FTND and Heavy of Smoking Index or HSI India, smokers or smoker and Tobacco or smokers. Three data base were used to search review article by using above mentioned key words. The quantitative studies were included in order to improve study sensitivity.

The [Flowchart 1]: shows that processes which has been followed during the review.



Initially 71 articles [Flowchart 1] and [Table 1] were screened, out of which 43 articles were excluded based on inclusion and exclusion criteria. Twenty-five articles from Pubmed, 3 articles from Cochrane library. Total 28 article abstracts were screened out of which 7 articles from Pubmed, 1 article from Cochrane library were fully reviewed. Four articles were removed because of duplication of the data; ambiguity of the content and inadequate information. Finally, 4 articles were included for systematic review.

[Table 2] shows that details of the twenty five articles abstract which were reviewed during review process.
Table 2: Summary of the search strategy carried out in database

Click here to view


There were limited studies on score of FTND and HSI among Beedi, and ST users. Therefore the author included all the studies that measured FTND and HSI score as main outcome measures [Table 3].
Table 3: Articles included for abstract reviewing [1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25]

Click here to view


Data extraction and quality assessment

The authors adopted qualitative systematic review approach to find FTND and HSI score of beedi and ST users. Data were extracted from the original authors. The quality of the data was checked by predesigned criteria checklist developed by the authors. A formal review was done by the authors. We adopted qualitative systematic review approach to find FTND and HSI score of beedi and ST users. Data were extracted from the original authors. The quality of the selected articles data were checked by predesigned criteria checklist developed by the authors [Table 4].
Table 4: Summary of included articles for Systematic Review

Click here to view



   Results Top


Characteristics of included studies

[Table 5] shows the all selected four studies used FTND and HSI score to evaluate various outcomes like validating the amount of tobacco used by the individual, effectiveness of tobacco cessation programme, correlate FTND score with urinary cotinine level, and identifying intended to quit tobacco smoking behaviour. The selected study population comprised psychiatric patients, patients attending outpatient department of pulmonary medicine, and other two study population comprised healthy volunteers with personal habits.
Table 5: Risk of bias for every study

Click here to view



   Discussion Top


Beedi and ST users are common among low socioeconomic population in India. Using ST users are an accepted cultural behavior India. However, its ill effects on health are ignored. Tobacco consumption in the form of smoking or chewing leads to cancer and other chronic diseases.[4] FTND and HSI are universally accepted addiction index tools for cigarette smoking and ST. However, its relation with beedi and ST users are not well-established. This systematic review has focused research on cotinine level and score of FTND, HSI among smokers and ST users.

The study by Balhara et al., with year suggested that urinary cotinine and nicotine dependence level were interrelated; it was also revealed that there was a significant correlation between the socioeconomic status of smokers and smoking-related factors with respect of urinary cotinine levels and the FTND scores. The study also mentioned that FTND tool helps to assess physical dependence of tobacco use rather than assessing persistence of tobacco use. This finding was not directly supported by previous studies conducted in the field of tobacco research. Major limitation of this study was retrospective in nature and gender distribution among study subjects was not equal (women 7.6%). Self-administered questionnaire was used to collect data from subject, therefore information obtained from the study subjects were biased. The study recommended that future study should focus on broad utilization of urinary cotinine measurement.[5]

The study by Panaretto et al., with year focused on long-term patients who had been enrolled for tobacco cessation in a clinical setting. There was a correlation between HSI score and absence of vascular or other chronic diseases but no correlation between FTND score and history of alcohol consumption, previous quit attempt, and duration of tobacco use. This discrepancy between FTND and HSI score was unexpected. The study failed to correlate self-reported cessation assessment with biochemical validation. Therefore, there are chances for information bias. The study recommended that further studies need to be conducted to identify the predictors for quitting.[6] This study finding was supported by a study conducted by Park et al. which revealed that FTND score was more reliable in assessing low nicotine dependence. Perhaps HSI can be used as a good screening tool to assess high dependence level.[7]

Study by Kisely et al., with year results revealed that FTND score alone was significant with age and habit of use. The study recommended that multicenter studies need to be undertaken to identify other predictors of quitting behavior.[8] This study finding was contradictory to a study conducted by Bernstein et al. which revealed that people with low FTND score were found to be more interested to quit.[9]

A study by Modig et al., with year finding was contradictory with above-mentioned studies. This study found that FTND score was not directly correlated with urine cotinine level.[10] Falsification of data could have occurred due to self-report.

The data presented in the [Table 6] shows that main characteristic of selected studies for review process. The main outcome of the selected studies emphasized on relation between FTND and HSI score for bidi smokers, ST users and other nicotine dependence.
Table 6: Main characteristics of selected studies for systematic review

Click here to view


These systematic review findings reviewed that FTND and HSI indices were not widely used to assess nicotine level among beedi and ST users. They were widely used among cigarette smokers. Beedi and ST smokers are high in number in India compared to cigarette smokers. The above-mentioned study results have revealed that there was a significant difference in score of FTND and HSI among beedi and ST users. In this review, findings also indicated that HSI can be used as a reasonably good screening tool to identify daily smokers with high level of nicotine dependence than the subpopulation having low nicotine dependence. FTND score is more reliable when supported with the validity of using urinary cotinine levels for assessment of nicotine dependence in active smokers. There were no studies with randomized control trial included for review, hence we cannot use specific statistical test.

Limitations

  • The articles included for systematic review were different in its population size, outcome measures, type of tobacco
  • The authors have used only three databases and selected key words in the review process
  • The quality of the selected articles was screened by predesigned form prepared by the author.



   Conclusion Top


The outcome of this systematic review suggests that the FTND score is not available for ST users and beedi users which need quantification with further study; because not a single study has been carried out to find FTND for ST and beedi consumers. As India and regional countries are heavily loaded with those addictions, the possibility and pattern of tobacco-related disorder would be different. Therefore, the determination of urinary cotinine will be biomarker to establish FTND values for beedi smokers and ST users, and the score may be different from cigarette smokers. This helps to establishing awareness among the ST/beedi addicts in India.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.[25]

 
   References Top

1.
Jung HS, Kim Y, Son J, Jeon YJ, Seo HG, Park SH, et al. Can urinary cotinine predict nicotine dependence level in smokers? Asian Pac J Cancer Prev 2012;13:5483-8.  Back to cited text no. 1
[PUBMED]    
2.
Balhara YP, Jain R. A receiver operated curve-based evaluation of change in sensitivity and specificity of cotinine urinalysis for detecting active tobacco use. J Cancer Res Ther 2013;9:84-9.  Back to cited text no. 2
[PUBMED]    
3.
Flatz A, Casillas A, Stringhini S, Zuercher E, Burnand B, Peytremann-Bridevaux I. Assessing tobacco dependence among cannabis users smoking cigarettes. Int J Gen Med 2015;25:87-92.  Back to cited text no. 3
    
4.
Jain R, Balhara YP, Jhanjee S, Sethi H. Concordance between urinary cotinine levels and self-reported tobacco use among drug-dependent persons: A pilot study. Subst Abus 2012;33:99-102.  Back to cited text no. 4
[PUBMED]    
5.
Balhara YP, Jain R, Sundar SA, Sagar R. A comparative study of reliability of self report of tobacco use among patients with bipolar and somatoform disorders. J Pharmacol Pharmacother 2011;2:174-8.  Back to cited text no. 5
[PUBMED]  [Full text]  
6.
Panaretto KS, Mitchell MR, Anderson L, Gilligan C, Buettner P, Larkins SL, et al. Tobacco use and measuring nicotine dependence among urban indigenous pregnant women. Med J 2009;191:554-7.  Back to cited text no. 6
[PUBMED]    
7.
Park SM, Son KY, Lee YJ, Lee HC, Kang JH, Lee YJ, et al. A preliminary investigation of early smoking initiation and nicotine dependence in Korean adults. Drug Alcohol Depend 2004;74:197-203.  Back to cited text no. 7
[PUBMED]    
8.
Kisely SR, Wise M, Preston N, Malmgren S, Shannon P. A group intervention to reduce smoking in individuals with psychiatric disorder: Brief report of a pilot study. Aust N Z J Public Health 2003;27:61-3.  Back to cited text no. 8
[PUBMED]    
9.
Jayakrishnan R, Mathew A, Lekshmi K, Sebastian P, Finne P, Uutela A. Assessment of nicotine dependence among smokers in a selected rural population in Kerala, India. Asian Pac J Cancer Prev 2012;13:2663-7.  Back to cited text no. 9
[PUBMED]    
10.
Modig K, Silventoinen K, Tynelius P, Kaprio J, Rasmussen F. Genetics of the association between intelligence and nicotine dependence: a study of male Swedish twins. Addiction 2011;106:995-1002.  Back to cited text no. 10
[PUBMED]    
11.
Li S, Fang L, Zhou Y, Pan L, Yang X, Li H, et al. Mediation of smoking abstinence self-efficacy on the association of nicotine dependence with smoking cessation. Eur J Public Health 2015;25:200-4.  Back to cited text no. 11
[PUBMED]    
12.
Raja M, Saha S, Mohd S, Narang R, Reddy LV, Kumari M. Cognitive behavioural therapy versus basic health education for tobacco cessation among tobacco users: A randomized clinical trial. J Clin Diagn Res 2014;8:47-9.  Back to cited text no. 12
    
13.
Anzengruber D, Klump KL, Thornton L, Brandt H, Crawford S, Fichter MM, et al. Smoking in eating disorders. Eat Behav 2006;7:291-9.  Back to cited text no. 13
[PUBMED]    
14.
Islam K, Saha I, Saha R, Samim Khan SA, Thakur R, Shivam S. Predictors of quitting behaviour with special reference to nicotine dependence among adult tobacco-users in a slum of Burdwan district, West Bengal, India. Indian J Med Res 2014;139:638-42.  Back to cited text no. 14
[PUBMED]  [Full text]  
15.
Balhara YP, Jain R, Sundar AS, Sagar R. Use of cotinine urinalysis to verify self-reported tobacco use among male psychiatric out-patients. Lung India 2012;29:217-20.  Back to cited text no. 15
  [Full text]  
16.
Flatz A, Bélanger RE, Berchtold A, Marclay F, Surìs JC. Assessing tobacco dependence among cannabis users smoking cigarettes. Nicotine Tob Res 2013;15:557-61.  Back to cited text no. 16
    
17.
Jain R, Balhara YP, Jhanjee S, Sethi H. Concordance between urinary cotinine levels and self-reported tobacco use among drug-dependent persons: A pilot study. Subst Abus 2012;33:99-102.  Back to cited text no. 17
[PUBMED]    
18.
Balhara YP, Jain R, Sundar SA, Sagar R. A comparative study of reliability of self-report of tobacco use among patients with bipolar and somatoform disorders. J Pharmacol Pharmacother 2011;2:174-8.  Back to cited text no. 18
[PUBMED]  [Full text]  
19.
Panaretto KS, Mitchell MR, Anderson L, Gilligan C, Buettner P, Larkins SL, et al. Tobacco use and measuring nicotine dependence among urban indigenous pregnant women. Med J Aust 2009;191:554-7.  Back to cited text no. 19
[PUBMED]    
20.
Park SM, Son KY, Lee YJ, Lee HC, Kang JH, Lee YJ, et al. A preliminary investigation of early smoking initiation and nicotine dependence in Korean adults. Drug Alcohol Depend 2004;74:197-203.  Back to cited text no. 20
[PUBMED]    
21.
Park SM, Son KY, Lee YJ, Lee HC, Kang JH, Lee YJ, et al. A group intervention to reduce smoking in individuals with psychiatric disorder. Brief report of a pilot study. Drug Alcohol Depend 2004;74:197-203.  Back to cited text no. 21
[PUBMED]    
22.
Mony PK, Rose DP, Sreedaran P, D'Souza G, Srinivasan K. Tobacco cessation outcomes in a cohort of patients attending a chest medicine outpatient clinic in Bangalore city, Southern India. Indian J Med Res 2014;139:523-30.  Back to cited text no. 22
[PUBMED]  [Full text]  
23.
Pennanen M, Broms U, Korhonen T, Haukkala A, Partonen T, Tuulio-Henriksson A, et al. Smoking, nicotine dependence and nicotine intake by socio-economic status and marital status. Addict Behav 2014;39:1145-51.  Back to cited text no. 23
[PUBMED]    
24.
Schnoll RA, George TP, Hawk L, Cinciripini P, Wileyto P, Tyndale RF. The relationship between the nicotine metabolite ratio and three self-report measures of nicotine dependence across sex and race. Psychopharmacology (Berl) 2014;231:2515-23.  Back to cited text no. 24
[PUBMED]    
25.
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. 25
[PUBMED]    



 
 
    Tables

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



 

Top
 
 
  Search
 
  
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
    Abstract
   Introduction
    materials and Me...
   Results
   Discussion
   Conclusion
    References
    Article Tables

 Article Access Statistics
    Viewed730    
    Printed11    
    Emailed0    
    PDF Downloaded45    
    Comments [Add]    

Recommend this journal