|Ahead of print publication
Tobacco use and its association with adverse childhood experiences in adolescents: A cross-sectional study from a school in Central India
Shrinidhi Sanjay Datar1, P Savithri Devi1, Simran Raka2, Cheryl Mankar2, Priyadarsh Ture1, Abhishek V Raut2
1 Shaheed Hopital, Dallirajhara, Chattisgarh, India
2 Department of Community Medicine, MGIMS, Sewagram, Wardha, Maharashtra, India
|Date of Submission||25-Jun-2021|
|Date of Decision||27-Jan-2022|
|Date of Acceptance||30-Jan-2022|
|Date of Web Publication||11-Apr-2022|
Abhishek V Raut,
Department of Community Medicine, MGIMS, Sewagram, Wardha - 442 102, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Tobacco use is the most important modifiable determinant for prevention of noncommunicable diseases. Tobacco use is often initiated during adolescence, and understanding the factors associated with it is vital to prevent initiation. Our objective was to assess the prevalence of tobacco use and its association with adverse childhood experiences (ACE). Materials and Methods: An analytical cross-sectional study was conducted on 200 randomly selected students from a rural school. The World Health Organization (WHO) Alcohol, Smoking and Substance Involvement Screening Test tool and WHO ACE international questionnaire were used to assess ever users of tobacco and ACE, respectively. Results: The prevalence of “ever” and “current” use of tobacco was 20.5% (95% confidence interval [CI] = 14.8–26.2) and 14.5% (95%CI = 9.5–19.5), respectively. Majority (65.9%) of the tobacco users had moderate level of tobacco addiction, whereas around 15% had severe addiction. All (100%) the participants had replied in affirmative to at least one of the questions related to the ACEs. On bivariate analysis, male students (prevalence odds ratio [POR] = 10.62, 95% CI = 3.62–31.21]), mothers with <10th grade education (POR = 2.19, 95% CI = 1.08–4.42), parental awareness regarding free time (POR = 0.21, 95% CI = 0.10–0.42), parents not giving enough food even when possible (POR = 5.28, 95% CI = 1.53–18.29), problem drinker in family (POR = 2.12, 95% CI = 1.05–4.29), having divorced or separated parents (POR = 3.26, 95% CI = 1.22–8.74), and being in a physical fight (POR = 2.41, 95% CI = 1.19–4.87) had significantly higher odds of tobacco use. Adolescent boys (adjusted odds ratios [AOR] = 8.42, 95% CI = 2.6–26.6) and parental awareness regarding free time (AOR = 0.40, 95% CI = 0.17–0.94) were the significant predictors for tobacco consumption (P < 0.05) on binary logistic regression. Conclusions: Tobacco use is prevalent among adolescents and is significantly associated with experiencing ACEs.
Keywords: Addiction, adolescents, child development, health promotion, tobacco
|How to cite this URL:|
Datar SS, Devi P S, Raka S, Mankar C, Ture P, Raut AV. Tobacco use and its association with adverse childhood experiences in adolescents: A cross-sectional study from a school in Central India. Int J Adv Med Health Res [Epub ahead of print] [cited 2022 May 22]. Available from: https://www.ijamhrjournal.org/preprintarticle.asp?id=342827
| Introduction|| |
Noncommunicable diseases (NCDs) have become a public health priority for many low- and middle-income countries, including India. NCDs contribute to approximately 15 million deaths worldwide, 11 million of which are from developing countries. Furthermore, NCDs are now becoming more common in the younger population. NCDs will account for around 60% of proportional mortality in India by 2025.
The key to NCD prevention is health promotion against the known common modifiable shared risk factors with significant attributable fraction such as tobacco use (9%), physical inactivity (6%), and obesity (5%). NCDs in later life can be attributed to prevalent risk factors during childhood and adolescence, thereby highlighting the need for health promotion during this phase. Health promotion in young age is the cornerstone to a life-course approach to primary prevention and control of NCDs.
Tobacco causes about 6 million deaths per year globally. Most tobacco users start early in life., Therefore, it becomes vital to prevent tobacco use during the school-going or adolescent age group.
For this, it is imperative to understand the reasons why adolescents may take up to tobacco. Routinely studied determinants include sociodemographic determinants such as gender, education, residence, socioeconomic status, caste/religion, taxation on tobacco, and social customs.,,,,, The other set of studied determinants are the more proximal factors such as peer pressure, parental addiction, influence of media/films, ignorance about harmful effects of tobacco, effect on mood/stress, relieving some health-related complaints, and lack of de-addiction services.,,,,,,, However, there is a definite need to study other modifiable determinants beyond these commonly studied proximal determinants, that may prime adolescents and increase their vulnerability to peer pressure and other proximal determinants.
Adverse childhood experiences (ACEs) are an important contributor to stress and include various types of abuse, neglect, violence, or other serious family- or community-level dysfunction. Available evidence suggests that experiencing ACEs has a long-term impact on an individual's health and well-being. ACEs can lead to many health-related problems such as heart diseases, depression, substance abuse, cancer, and other chronic diseases.,,, However, all these evidence-generating studies were conducted in the Western context and at the time of conduction of this study, despite thorough literature search, we were not able to find out studies from rural Indian context that will help us to understand the nature of ACEs experienced by rural adolescents and their association with tobacco use from an Indian perspective. Therefore, the present research was conducted with a primary objective to find out the prevalence of ever use of tobacco among adolescents and a secondary objective to estimate the burden of ACEs and its association with tobacco use.
| Materials and Methods|| |
This was an analytical cross-sectional study conducted in June–July, 2017.
Our institute runs a School Health Education Program (SHEP) in 15 different schools of the district. The present study was carried out in one of the secondary schools where the SHEP is already being implemented. The school in which this work was conducted is a government-aided school managed by a charitable trust and is located in a rural area. The school has more than 600 adolescent students from nearby 15–20 villages including Tribal padas (hamlets) in a radius of around 15 km. The school was selected considering the feasibility of implementation.
Adolescents (10–19 years) of either gender studying from Class V to Class X were included in the study. This was because tobacco use has been shown to be common among both adolescent boys and girls.
Sample size and sampling strategy
A sample size of 196 adolescents was estimated using the OpenEpi software Version 3.01 (developed by Rollins School of Public Health, Emory University, Atlanta, Georgia, US), assuming a 39% prevalence of ever tobacco use, 95% confidence level, a relative precision of 20%, a noneligibility/consent refusal rate of 15%, and 10% loss of data due to incomplete or poor quality data considering the sensitive nature of ACE questionnaire. Therefore, it was decided to recruit 200 adolescents for the study purpose. Based on their school attendance register, a list of all students from Class V to Class X was made and 200 students were selected by simple random sampling with replacement by generating random numbers using the OpenEpi software. Confidentiality of the study participants was ensured by assigning them a unique identification number. Data were collected through personal interviews of each participant ensuring confidentiality and privacy that also helped to probe for and understand the profile of tobacco use and issues associated with it.
Operational definitions for exposure, outcome, and confounding variables
Dependent variable was tobacco use and was classified as either “ever user” or “current user” depending on the use of tobacco in any form and quantity at any point in their life or in the last 3 months, respectively. Tobacco use and the associated health risk assessment due to it was done using the tobacco component of the World Health Organization's The Alcohol, Smoking and Substance Involvement Screening Test (WHO ASSIST) tool.
Independent variables were ACEs and background sociodemographic characteristics namely age, gender and education of students, education of parents, socioeconomic status, and type of family. For the measurement of ACEs, a questionnaire based on the WHO ACE international questionnaire was used. If a participant had experienced the respective ACE even once at any point in their lifetime, it was considered as “Yes,” and if they had never experienced the respective ACE, then it was considered as “No.”
Parental education level was considered based on the highest educational grade completed, as reported by respective adolescents. Socioeconomic status was ascertained based on the color of family ration card as reported by the students – yellow for below poverty line (BPL) families and orange/white for above poverty line families. The family was classified as nuclear (only a single couple and/or their dependent children) or joint (more than one married couple and their children staying in the same household).
Data entry and analysis
Filled questionnaires were cross-checked for incomplete and/or invalid information before initiating data entry. If necessary, the study participants were again contacted to fill missing variables and to clarify recorded data. Data entry was done in Microsoft excel and analysis was done using Statistical Package for the Social Sciences (SPSS) software version 12.0 (SPSS Inc., Chicago, USA). Validation checks were applied during data entry to prevent missing fields and wrong data entry. The prevalence of tobacco use was reported using proportion with 95% confidence interval (CI), whereas association had been studied using prevalence odds ratio (POR) with 95% CI. We used binary logistic regression analysis to determine predictors of tobacco use and estimate the adjusted odds ratio (AOR). All variables found to be statistically significant on bivariate analysis were entered in model by using ENTER method in SPSS. Omnibus test for model coefficients (significant at P < 0.05) and Hosmer–Lemeshow goodness-of-fit test (nonsignificant at P > 0.05) were assessed to check if the model fits the data. All the variables entered in the model were checked for collinearity and variance inflation factor for any of the variables which was not more than 1.2.
The study was initiated only upon approval of the study protocol and informed consent forms from the Institutional Ethics Committee (Ref. No. MGIMS/IEC/COMMED/20/2017 dated 06/03/2017). A sensitization meeting was arranged with the principal of the school and other teachers to explain to them about the study in detail. A written informed consent was obtained from the principal. Passive consent was obtained from the parents of the students. An informed consent form containing all the necessary details about the study was sent to the students for reference of their parents. The parents were required to send back the duly signed consent form within a period of 7 days only if they did not want their child to participate in the study. If they were willing to allow their child to be a part of the study, then the parent/s did not have to send back the consent form. A verbal assent was obtained from all the students before including them in the study. At the time of seeking assent, students were inquired regarding the passive consent form sent for their parents, and a nonreceipt of signed consent form from the parents was considered as their willingness for their child's participation in the study., The study participants who were found indulging in tobacco use were referred for counseling and/or treatment depending on their severity level.
| Results|| |
[Table 1] summarizes the background characteristics of the study participants. There were more boys (55.5%) among the study participants compared to girls. It was observed that majority of the study participants were studying in secondary school (56.5%). The participants mostly belonged to a nuclear family (around 63%), and the average family size was 5.1. Majority of the participants (around 69%) were BPL or belonging to poor socioeconomic status. Most of the students' parents had received more than 10th grade of education; only 2% of the parents were illiterate.
|Table 1: Sociodemographic characteristics of the study participants (n=200)|
Click here to view
[Table 2] summarizes the profile of tobacco use among the study participants. The prevalence of “ever” and “current” use of tobacco was 20.5% (95% CI = 14.8–26.2) and 14.5% (95% CI = 9.5–19.5), respectively. Smokeless tobacco in the form of locally available Kharra (a mix of betel nut, tobacco, lime, cardamom, catechu powder, etc.) was the most commonly consumed product. Dependence was observed in around 66% of the current users experiencing a daily strong urge for tobacco use. Similarly, around 25% of the current users admitted to having faced social (arguments or quarrels with friends and/or kharra shop owners) or financial problems (borrowing or stealing of money) because of their habit of tobacco use. Similarly, around 20% of the current users were not able to concentrate on the given tasks. Preoccupation with thoughts about how to avail kharra was reported as the prime reason for not being able to perform their desired social role as students. Around 50% of the ever users reported that, at some point in their life, either someone from their family or friends had expressed genuine concern regarding their habit of tobacco consumption. Around 30% of the ever users confessed to having made an unsuccessful attempt to quit tobacco use in the last 3 months.
[Table 3] depicts the level of tobacco addiction among the study participants based on the WHO ASSIST scores. Around 15% of the ever tobacco users had severe level of dependence for tobacco use and would require intensive treatment to help them quit tobacco use. Majority (65.9%) of the ever tobacco users would need brief intervention to help them give up the habit of tobacco use.
|Table 3: Level of tobacco addiction among ever tobacco users based on the World Health Organization's the Alcohol, Smoking and Substance Involvement Screening test scores (n=41)|
Click here to view
[Table 4] summarizes the association of tobacco use with background sociodemographic characteristics. Only education of mother and gender of students were significantly associated with ever tobacco use. Male students had significantly higher odds of tobacco use (POR = 10.62, 95% CI = 3.62–31.21). Similarly, adolescents whose mothers were educated till <10th grade had significantly higher odds of tobacco use (POR = 2.19, 95% CI = 1.08–4.42). Other variables such as type of family, being BPL, education of father, and age and education of students were not found to be significantly associated as depicted by CI that contained the null value.
|Table 4: Association of tobacco use with background characteristics (n=200)|
Click here to view
[Table 5] summarizes the magnitude of ACE among the study participants. All participants had replied in the affirmative to at least one of the questions related to the ACEs. Thirty-seven (18.5%) participants had experienced being bullied at some point or the other. Among those who had experienced bullying, 12 (32.4%) participants were hit, kicked, pushed, shoved around, or locked indoors. Twelve (32.4%) participants had experienced being made fun of because of their religion and/or color, 9 (24.3%) participants were made fun of because of how their body or face looked, while 4 (10.8%) participants had to face sexual jokes, comments, gestures, or were intentionally left out of activities on purpose or completely ignored. The number of participants who had answered in the affirmative to at least one of the ACE questions was 2 (1%), while 3 (1.5%) participants had answered in the affirmative to 20 ACE questions. The number of participants who had answered in the affirmative to 2, 3, 4, and 5 questions were 35 (17.5%), 37 (18.5%), 37 (18.5%), and 29 (14.5%), respectively.
|Table 5: Magnitude of adverse childhood experiences among the study participants (n=200)|
Click here to view
[Table 6] gives the association between tobacco use and ACEs. The study participants whose parents really knew regarding their free time had significantly lower odds of tobacco use (POR = 0.21, 95% CI = 0.10–0.42). Furthermore, students whose parents did not give them enough food at least once even when possible (POR = 5.28, 95% CI = 1.53–18.29), who were kept deprived from school at least once (POR = 4.18, 95% CI = 1.10–17.5), who had a problem drinker in family (POR = 2.12, 95% CI = 1.05–4.29), whose parents were either divorced or separated (POR = 3.26, 95% CI = 1.22–8.74), and who had indulged in physical fights (POR = 2.41, 95% CI = 1.19–4.87) had significantly higher odds for tobacco use. Other ACE variables had higher POR for tobacco use but did not reach statistical significance.
|Table 6: Association of tobacco use with adverse childhood experiences (n=200)|
Click here to view
[Table 7] summarizes predictors for “ever” use of tobacco among the study participants. Significant predictors were gender of students and parental awareness regarding free time; both were significant at P < 0.05. The Nagelkerke R Square of the model was 0.362, indicating that 36% of the variation in tobacco use can be explained by these two independent predictor variables. Adolescent boys had significantly higher adjusted odds for indulging in tobacco (AOR = 8.42, 95% CI = 2.6–26.6). Adolescent students whose parents were mostly aware regarding their free time had significantly lower adjusted odds for indulging in tobacco use (AOR = 0.40, 95% CI = 0.17–0.94).
|Table 7: Predictors for tobacco consumption among the study participants (n=200)|
Click here to view
| Discussion|| |
This present study was conducted among 200 school-going adolescent students. The prevalence of “ever” and “current” use of tobacco was 20.5% and 14.5%, respectively. Almost all the ever tobacco users indulged in consumption of smokeless tobacco. Locally available product kharra was the most commonly consumed product. Our study results fall within the broader range of the Global Youth Tobacco Survey (GYTS) findings to estimate tobacco use among adolescents. In GYTS, the current use of any tobacco product varied from as low as 3.3% in Goa to as high as 62.8% in Nagaland.
In a study by Dongre et al. from rural Wardha, the overall prevalence of tobacco use was found to be 39%. This difference in finding could be attributed to the study setting as the present study was conducted in a school where the SHEP is already being implemented as compared to the community-based study conducted by Dongre et al. Finding of kharra being the most commonly consumed tobacco product by Dongre et al. is in concurrence with the findings of the present study. A study conducted from rural area of West Bengal by Mukherjee et al. found that the prevalence of using smokeless tobacco was 8.1% among boys. The easy availability of kharra at a reasonably cheaper rate, as well as its acceptance as a community norm are in all probability, the drivers for universal nature of its use as a favoured tobacco product.
A study by Narayan et al. found that the prevalence of tobacco consumption in tribal Maharashtra by adolescents was 45.42%, with consumption of smokeless form of tobacco being most favored. This finding of smokeless tobacco being the most common form of tobacco used is consistent with the findings of our study. The easy availability of smokeless form of tobacco, cultural acceptance, and affordable prices of such local products could be the possible reasons for smokeless tobacco use being more preferred in rural and tribal areas. The higher prevalence among tribal adolescents can probably be attributed to lesser literacy levels and, in particular, the health literacy levels.
Narain et al. found that prevalence of tobacco use in school students was 11.2% in Noida. These figures are again lower than our study which may be because of geographical differences in the study settings and urban and rural disparities. A study conducted to estimate the prevalence of tobacco use in Kerala found that the prevalence of tobacco use among adolescents, i.e., participants who have ever used tobacco, was 6.9%. Such a low prevalence of tobacco use may be because the particular study was conducted in the state of Kerala which has almost 100% literacy rate, good public health indicators, and high health awareness among the people.
To find the association between tobacco addiction and ACE, we used the WHO ACE tool. The tools used and findings of the present study are similar to a recently published cVEDA cohort study from India by Fernandes et al. Similar to the cVEDA cohort study, the present study also attempted to capture ACEs at all the four levels – individual, family, community, and societal level. We found that the child who has experienced various types of ACE had higher odds of being addicted to tobacco in future, with certain variables showing statistically significant association with tobacco use. The predictors for tobacco use were gender of the students and parent's awareness about free time of their children. In the cVEDA cohort, 50% of the participants reported child maltreatment ACEs and family-level ACEs. Both of these showed a significant association with substance misuse. The almost universal nature of experiencing ACEs in the present study could be due to the differences in the methods of data analysis (affirmative answer to any of the questions vs. estimating binary ACE score) and variations in background sociodemographic characteristics among the study participants as the cVEDA cohort included participants from Imphal (Manipur); Asansol (West Bengal); Mysore (Karnataka); Bengaluru (Karnataka); Chandigarh (Punjab and Haryana), and Rishi Valley (Madanapelle, Andhra Pradesh), but none from the central India (Vidarbha, Madhya Pradesh, Chhattisgarh) region of India. This also highlights the importance of understanding the nature of ACEs in different regions of India given the widely varying socioeconomic and cultural contexts; this will also inform the customization of interventions.
The results of the present study reemphasize the findings on the association of ACEs with addictions available from other countries. Soares et al., in a study from Brazil, studied the prevalence and related factors for ACEs among Brazilian adolescents. They assessed different types of ACEs, namely physical abuse, neglect (physical and emotional), sexual abuse, domestic violence, parental separation, and/or death. Around 85% of the adolescents had experienced at least one ACE, which is very similar to the universal nature of ACEs experienced in the present study. The most common ACE reported by Soares et al. were parental separation, emotional neglect, and domestic violence.
Mate. in their study found that early ACEs produce various neurobiological abnormalities, giving rise to substance abuse. Their study effectively demonstrates how abandonment, neglect, or abuse in any form can alter physical stress mechanisms, thereby making the child more reactive to stress throughout their life. A retrospective cohort study was done in San Diego, USA, by Anda et al. which intended to assess the relationship between ACE and smoking behaviors. They found that different categories of ACE were significantly associated with smoking. There was a strong and graded relationship between smoking behavior and the number of ACEs. Similarly, another study conducted among American adults showed that experiences during ones childhood were causally linked to future addictions; further, there was a dose–response relationship between addictions and ACEs.
The findings in our study are congruent with evidence from other countries. Tobacco addiction has deeper roots linked to adverse experiences during childhood. Such ACEs prime the adolescents and increase their vulnerability to future tobacco use. A seemingly simple act of parents being aware regarding leisure time activities of their children significantly lowered the child's odds of indulging in tobacco use. Health promotion efforts, under the current policy framework against tobacco in India, do not focus on ACE. Exposure to any ACE needs to be considered while planning behavioral change strategies at an individual and community level. Our findings can be used to sensitize caregivers in the community regarding the importance of not exposing their children to adverse experiences during childhood.
The present study has several limitations. The sample was restricted to adolescents from a single school and may not be representative of all adolescents from the general population. Despite our best efforts, because the questionnaire included some sensitive questions about tobacco use and ACE, the possibility of underreporting cannot be denied.
| Conclusions|| |
From the present study, it can be concluded that tobacco use is an important health problem among adolescents and has significant association with ACE. This calls for inquiring about ACEs while counseling against tobacco-related addictions. It also highlights the importance of sensitizing caregivers to not expose their children to adverse experiences during childhood if we intend to prevent our adolescents from future tobacco use.
- We thank the principal of the school, the teachers of the school, and the students of the school for cooperation and participation in the research
- We thank Professor and Head, Department of Community Medicine, MGIMS Sevagram, for allowing us to use departmental infrastructure to conduct the research
- We thank the medical social workers under the Department of Community Medicine, MGIMS, Sevagram, for their help
- We thank the students of White Coat Army who helped in completing the research project.
Financial support and sponsorship
This research project was done as part of Indian Council of Medical Research's Short Term Studentship (ICMR-STS) program (ICMR STS Reference ID-2017-02459).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Reddy KS. Prevention and Control of Non-Communicable Diseases: Status and Strategies. Working paper; 2003. Available from: http://icrier.org/pdf/WP104.pdf
. [Last accessed on 2021 Feb 10].
Cranwell J, Murray R, Lewis S, Leonardi-Bee J, Dockrell M, Britton J. Adolescents' exposure to tobacco and alcohol content in YouTube music videos. Addiction 2015;110:703-11.
Dongre A, Deshmukh P, Murali N, Garg B. Tobacco consumption among adolescents in rural Wardha: Where and how tobacco control should focus its attention? Indian J Cancer 2008;45:100-6.
] [Full text]
Kumar R, Salve H, Misra P. Determinants of tobacco use and perception, attitude about an antitobacco act in rural Haryana, North India. Int J Med Public Health 2014;4:367-70. [Full text]
Majumdar R, Raje SS, Dandekar A. Socio demographic factors associated with tobacco use in rural Maharashtra. Med J DY Patil Univ 2013;6:161. [Full text]
Thakur JS, Paika R. Determinants of smokeless tobacco use in India. Indian J Med Res 2018;148:41-5.
] [Full text]
Sharma D, Goel S, Lal P. Education differential in relation to tobacco use and its predictors across different regions of India. Indian J Cancer 2017;54:584-8.
] [Full text]
Singh A, Ladusingh L. Prevalence and determinants of tobacco use in India: Evidence from recent Global Adult Tobacco Survey data. PLoS One 2014;9:e114073.
Rani M, Bonu S, Jha P, Nguyen SN, Jamjoum L. Tobacco use in India: Prevalence and predictors of smoking and chewing in a national cross sectional household survey. Tob Control 2003;12:e4.
Vargas LS, Lucchese R, Silva AC, Guimarães RA, Vera I, Castro PA. Determinants of tobacco use by students. Rev Saude Publica 2017;51:36.
Anda RF, Croft JB, Felitti VJ, Nordenberg D, Giles WH, Williamson DF, et al.
Adverse childhood experiences and smoking during adolescence and adulthood. JAMA 1999;282:1652-8.
Felitti VJ. Origins of addictive behavior: Evidence from a study of stressful chilhood experiences. Prax Kinderpsychol Kinderpsychiatr 2003;52:547-59.
Soares AL, Howe LD, Matijasevich A, Wehrmeister FC, Menezes AM, Gonçalves H. Adverse childhood experiences: Prevalence and related factors in adolescents of a Brazilian birth cohort. Child Abuse Negl 2016;51:21-30.
Humeniuk R, Henry-Edwards S, Ali R, Poznyak V, Monteiro MG. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) Manual for Use in Primary Care. Geneva: World Health Organization; 2010. Available from: https://www.who.int/management-of-substance-use/assist/
. [Last accessed on 2021 Feb 17].
Office of the Registrar General and Census Commissioner. Census India 2011. New Delhi: Ministry of Home Affairs. Government of India; 2012.
Park K. Medicine and Social Sciences. Park's Textbook of Preventive Medicine. 22nd
ed. Jabalpur: M/s Banarsidas Bhanot Publishers; 2013. p. 620-53.
Severson H, Biglan A. Rationale for the use of passive consent in smoking prevention research: Politics, policy, and pragmatics. Prev Med 1989;18:267-79.
Spence S, White M, Adamson AJ, Matthews JN. Does the use of passive or active consent affect consent or completion rates, or dietary data quality? Repeat cross-sectional survey among school children aged 11-12 years. BMJ Open 2015;5:e006457.
The Global Youth Tobacco Survey Collaborative Group. Tobacco use among youth: A cross country comparison (Special report). Tob Control 2002;11:252-70.
Mukherjee A, Sinha A, Taraphdar P, Basu G, Chakrabarty D. Tobacco abuse among school going adolescents in a rural area of West Bengal, India. Indian J Public Health 2012;56:286-9.
] [Full text]
Narayan DD, Dhondibarao GR, Ghanshyam KC. Prevalence of tobacco consumption among the adolescents of the tribal areas in Maharashtra. Journal of Clinical and Diagnostic Research 2011;5:1060-3.
Narain R, Sardana S, Gupta S, Sehgal A. Age at initiation and prevalence of tobacco use among school children in Noida, India: A cross-sectional questionnaire based survey. The Indian Journal of Medical Research. 2011;133:300.
Jaisoorya TS, Beena KV, Beena M, Jose DC, Ellangovan K, Thennarasu K, et al.
Prevalence & correlates of tobacco use among adolescents in Kerala, India. Indian J Med Res 2016;144:704-11.
] [Full text]
Fernandes GS, Spiers A, Vaidya N, Zhang Y, Sharma E, Holla B, et al.
Adverse childhood experiences and substance misuse in young people in India: Results from the multisite cVEDA cohort. BMC Public Health 2021;21:1920.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]