Second-hand smoke exposure as an independent determinant of quit attempts and successful tobacco cessation: A multilevel analysis of the GATS (2016–17), India

Second-hand smoke exposure as an independent determinant of quit attempts and successful tobacco cessation: A multilevel analysis of the GATS (2016–17), India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Second-hand smoke exposure as an independent determinant of quit attempts and successful tobacco cessation: A multilevel analysis of the GATS (2016–17), India Delfin Lovelina Francis, Saravanan Sampoornam Pape Reddy, Shaswata Karmakar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7275925/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background: Secondhand smoke (SHS) exposure remains a pervasive public health challenge in India and contributes to tobacco-related morbidity and mortality. Despite progress in tobacco control, quit rates among Indian adults remain low, and the impact of SHS exposure on cessation outcomes is not well understood. This study aimed to examine the associationsbetween SHS exposure and tobacco cessation outcomes among Indian adults using nationally representative data from the Global Adult Tobacco Survey (GATS) India 2016–17. Methods: A cross-sectional secondary analysis was conducted including adults aged 15 years and older who were current or past tobacco users. SHS exposure was assessed across three domains: home, workplace, and public places. The primary outcomes were self-reported quit attempts in the past 12 months and successful cessation. Multilevel logistic regression models accounted for the hierarchical data structure adjusting for sociodemographic and behavioral confounders. Model fit was evaluated via theAkaike information criterion and likelihood ratio tests. Subgroup and interaction analyses were performed. Results: Among 74,037 respondents, the prevalence of current tobacco use was 28.6%. SHS exposure was reported by 38.7% of the participants at home and 30.2% at the workplace. After adjustment, SHS exposure at home was independently associated with reduced odds of quit attempts (AOR = 0.72, 95% CI: 0.65–0.80) and successful cessation (AOR = 0.65, 95% CI: 0.56–0.76). Negative associations were observed for SHS exposure at workplaces and public places. Conclusion : SHS exposure significantly impedes both quittingattempts and successful tobacco cessation among Indian adults. Tobacco cessation Secondhand smoking Quit attempts Survey GATS Public health Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Tobacco use remains one of the greatest public health issues in the world, with more than eight million deaths each year. Low- and middle-income nations such as India bear a disproportionate amount of this burden [ 1 ]. India has the second-highest number of tobacco users globally and is facing two epidemics: the widespread threat of second-hand smoke (SHS) exposure and the direct health effects of tobacco. In India, involuntary tobacco smoke exposure is quite common. According to the Global Adult Tobacco Survey (GATS) 2016–17, approximately 29% of adults are exposed to SHS at home, and comparable percentages are exposed in public and workplace settings. Additionally, approximately 28.6% of adults in India consume some form of tobacco, representing more than 268 million users [ 2 , 3 , 4 ]. The initiation of tobacco use often occurs early, with a considerable number of users starting before the age of 18 and a notable proportion of women and minors being affected. Despite increasing awareness of the harmful effects of tobacco, only 13% of smokers and 5% of smokeless tobacco users have successfully quit, and most quit attempts are usually short-lived [ 5 ]. Such continued use is further amplified by high levels of SHS exposure, not only for non-users but also in ways that undermine quit attempts among active users. The prevalence of SHS exposure is very high in the Indian population, as 38.7% of adults are exposed to SHS in the home. SHS exposure in public places and workplaces are also substantially high, especially among males and young adults. State-level disparities were also seemingly high; for example, in some states, more than 50% of households and public locations reported SHS exposure [ 6 , 7 ]. Women, children, and underserved and vulnerable populations, such as individuals of lower socioeconomic classes, are disproportionately affected by this burden [ 8 , 9 ]. A recent study quantified the annual healthcare costs attributable to SHS exposure at INR 567 billion, accounting for 8% of the nation’s total healthcare expenditure [ 9 ]. Crucially, SHS exposure also prevents current smokers from quitting. Based on the findings of neurobiological studies, short-term SHS exposure could provide enough nicotine to the brain to trigger cravings and maintain dependence, making quitting harder [ 10 ]. A pioneering positron emission tomography imaging study revealed that SHS exposure in a closed chamber for one hour led to measurable nicotine binding in the brain, like active smoking [ 11 ]. This physiological reinforcement is supported by behavioral studies where people who have been exposed to SHS, from either within the home or from intimate social relationships, are less likely to try to quit and more likely to relapse after quitting [ 12 ]. Emerging evidence suggests a reciprocal relationship between exposure to SHS and tobacco use behaviors. Exposure to SHS is not only a harmful phenomenon that can harm health but also a shaping factor in the trajectory of tobacco use, especially in adolescents and young people. A nationwide study in China revealed that adolescents exposed to SHS in home and public places had higher probabilities of initiating smoking, current smoking, and e-cigarette use, regardless of whether they were in middle school or high school. Similar trends are observed in India, where youth exposed to SHS are more susceptible to tobacco use, and home exposure is a particularly strong risk factor [ 13 ]. SHS exposure in India is influenced by a range of sociodemographic factors. Researchers have found that gender, education, occupation, type of residence, and wealth index are the most crucial factors influencing SHS exposure in different studies using GATS data [ 14 ]. Centered around the Cigarettes and Other Tobacco Products Act (COTPA), 2003, and the WHO Framework on Tobacco Control (FCTC), India’s tobacco control framework has achieved a significant amount of control by reducing public smoking and increasing awareness [ 15 ]. However, there are still implementation deficits, especially in home and nonformal work settings, which are the main sources of exposure to SHSs. In addition, the existence of smoking rooms or places in public settings and the limited adherence to policies in private microenvironments weaken the impact of smoke-free laws. Nationally available cessation support services (such as Quitline, mCessation, and tobacco cessation centers) have been established but are used on a limited scale. Most quit attempts are unassisted, and the inclusion of SHS reduction methods in cessation programs is not routine. These disparities are especially alarming given that SHS exposure has been shown to hinder cessation attempts, supporting the need for broad, multifaceted intervention [ 16 , 17 ]. Most of the current analyses concentrate on the prevalence and determinants of environmental tobacco smoke (ETS) among never-users or on quit-related predictors among ever-users, with little consideration of the overlap between these behaviors. Although SHS exposure supporting cessation is well established worldwide, Indian-specific evidence is scarce. This gap becomes even more pertinent given the ongoing low quit rates and high relapse rates reported for India [ 18 , 19 ]. To develop more effective tobacco control interventions, it is critical to ascertain the impact of SHS exposure in different environments, such as homes, workplaces, and public places, which has an impact on quitting attempts and sustained cessation. Incorporating SHS prevention into smoking cessation efforts may increase the impact of these interventions, particularly among vulnerable populations that experience elevated levels of exposure and may have more difficulty quitting [ 20 ]. Despite the enormous amount of available literature on tobacco and SHS use in India, a key knowledge gap still exists where there has not yet been an in-depth systematic examination of the effect of SHS exposure on quitting among adults in India using nationally representative data. Therefore, in the current study, we undertook the secondary data analysis of GATS-2 [ 6 ] with an aim to fill a critical evidence gap by elucidating the relationship between SHS exposure and tobacco cessation outcomes among Indian adults. This is the first study to examine, in a comprehensive manner, the independent effects of SHS exposure at home, work, and in public places on quitting attempts and successful avoidance of tobacco from a nationally representative population in India. METHODS Study settings The nationwide representative survey of GATS (Round 2) was undertaken in the Indian subcontinent during years 2016–2017 [ 6 ], with a population coverage estimate of 1029 million (Census 2011) [ 21 ]. Study Design and Data Source The study was conducted in accordance with the Declaration of Helsinki. A cross-sectional secondary analysis of data from the GATS India 2016-17 [ 6 ] was conducted. The GATS is a nationally representative household survey conducted via a multistage, geographically stratified cluster sample of populations to generate estimates of tobacco use and cessation, SHS exposure, and related sociodemographic and behavioral indicators in India over 15 years or above. The study population included adults (aged ≥ 15 years) who were current or ever users of any tobacco products in smoked or smokeless forms. Persons with incomplete data on critical variables (tobacco use status, SHS exposure, or cessation results) were excluded from the analyses. To minimize selection bias, analysis utilized sampling weights from GATS 2016-17 India datasets to reflect the national adult population. Self-reported measures of SHS exposure and cessation introduce the possibility of information bias; however, GATS employs standardized, validated questions to minimize error. Outcome measures The primary outcomes assessed were a quit attempt, defined as a self-reported attempt to quit tobacco in the past 12 months, and successful cessation, indicated by self-reported former tobacco use with no current use of any tobacco product at the time of the survey. The main predictor was SHS exposure, measured across three domains—at home, at workplace, and in public places with each domain dichotomized as yes or no based on self-reports. The covariates included a comprehensive set of sociodemographic and behavioral factors, such as age, gender, education, occupation, wealth index, caste, religion, urban or rural residence, geographic region, type and frequency of tobacco use, age of initiation, awareness of health risks, receipt of cessation advice, and use of tobacco cessation support services, such as mCessation or quitlines. The two main outcomes measured were quit attempt (self-reported attempt to quit tobacco in the past 12 months) and successful cessation (self-reported former use of tobacco with no current use of any tobacco product at the time of the survey). Statistical analysis All analyses used the complex survey design and sampling weights of the GATS 2016-17 dataset [ 6 ], which provided statistics that were nationally representative. Analytic software included both the SPSS complex samples module and Stata survey (svy) commands. Multilevel logistic regression modeling and structural equation modeling was employed to adjust for the clustered data design and to examine complex relationships between SHS exposure and cessation. All analyses followed the STROBE recommendations. Prevalence estimates were obtained through weighted calculations based on exposure to SHS, attempts to quit, and successful cessation across key sociodemographic and behavioral characteristics. Chi-square tests were performed to compare bivariate relationships between SHS exposure and cessation outcomes. Multilevel Modeling As the data were hierarchical (individuals nested within households and households within primary sampling units [PSUs]), we used multilevel logistic regression models to account for clustering at both the household and the PSU level. Initially, a null (intercept-only) model was fitted to estimate the intraclass correlation coefficient (ICC), which quantifies the degree of clustering within households and PSUs. Subsequently, mixed-effects logistic regression models were specified to examine the association between SHS exposure and cessation outcomes (quit attempts and successful cessation) while adjusting for potential confounders. The model was formulated as follows: logit (Pijk)=β0 + β1SHSijk + β2Xijk + uj + vklogit ( Pijk )= β 0 + β 1SHS ijk + β 2 Xijk + uj + vk where Pijk represents the probability of a quit attempt or successful cessation for individual i in household j and PSU k; SHSijk is the main predictor variable indicating exposure to secondhand smoke; Xijk is a vector of covariates including demographic and behavioral factors; uj denotes the random effect at the household level; and vk denotes the random effect at the PSU level. Model fit was assessed via the Akaike information criterion (AIC) and likelihood ratio tests to compare nested models and determine the best-fitting model. Advanced Statistical Modeling A multivariate logistic regression for adjusted odds ratios (AORs) and 95% confidence intervals (CIs) were estimated for the association between SHS exposure and cessation outcomes, controlling for all covariates. For outcomes with more than two categories (e.g., no attempt, attempted, successful), multinomial logistic regression models were employed. The effect modification was assessed by including interaction terms (e.g., SHS exposure × use of cessation support, SHS exposure × gender). To explore direct and indirect pathways between SHS exposure, behavioral factors, and cessation outcomes, structural equation modeling (SEM) was conducted via AMOS or R (lavaan package), modeling latent constructs such as the intention to quit and social support. Sensitivity and subgroup analyses Subgroup analysis was conducted by tobacco type (smoked versus smokeless), sex, age group, and region. Sensitivity analyses involved the exclusion of participants with missing data and alternative definitions of successful cessation (e.g., abstaining ≥ 6 months). Geospatial Analysis All maps were created via ESRI ArcGIS to depict state-level differences in SHS exposure and cessation metrics. RESULT A total of 74,037 adults aged 15 years and older were interviewed in GATS India from 2016-17[ 6 ], and they represented a nationally weighted sample of 266.8 million current tobacco uses (smoked and/or smokeless). The weighted prevalence of current tobacco use was 28.6% (42.4% for men, 14.2% for women). Among all adults, 10.7% (99.5 million) currently smoked tobacco, and 21.4% (199.4 million) used smokeless tobacco (Table 1 ). Among the current smokers, 38.5% had made a quit attempt in the previous 12 months (38.8% men, 35.5% women), and 33.2% of current users who were smokeless were attempting to quit (35.2% men, 28.4% women). A total of 55.4% of current smokers and 49.6% of smokeless tobacco users reported planning or thinking about quitting. (Fig. 1 ) Table 1 Weighted prevalence (%) of SHS exposure and tobacco use (GATS 2016-17)[ 6 ] Indicator Men (%) Women (%) Overall (%) Estimated n (millions) Current tobacco use (smoked and/or smokeless) 42.4 14.2 28.6 266.8 Current tobacco smokers 19.0 2.0 10.7 99.5 Current smokeless tobacco users 29.6 12.8 21.4 199.4 Exposed to SHS at home 38.1 39.3 38.7 ~ 360.3 Exposed to SHS at workplace* 32.7 17.9 30.2 - Exposed to SHS at restaurants 13.0 1.6 7.4 - *Among adults who work indoors or both indoors and outdoors. SHS exposure at home was reported by 38.7% of adults, and the prevalence among men (38.1%) and women (39.3%) was comparable. Workplace SHS exposure was 30.2% overall and higher in men (32.7%) than in women (17.9%). There were significantly fewer attempts to quit smoking in the last year among SHS exposed participants at home and in the workplace than among those who were not exposed (p < 0.05). Multilevel Logistic Regression Models Model 1: SHS exposure and quiet attempts : After we adjusted for sociodemographic and behavioral covariates, exposure to SHS at home was independently associated with lower odds of quitting attempts among current tobacco users (AOR = 0.72, 95% CI = 0.65–0.80, p < 0.001). SHS exposure at the workplace (AOR: 0.81, 95% CI: 0.73–0.90, p < 0.001) and at restaurants/public places (AOR: 0.85, 95% CI: 0.77–0.94, p = 0.002) was also negatively associated (Fig. 2 ). Model 2: SHS exposure and successful cessation : According to the fully adjusted model, exposure to SHS at home was also a strong independent predictor of a lower likelihood of successful cessation (AOR: 0.65, 95% CI: 0.56–0.76, p < 0.001). Similar negative associations were found for SHS at work (AOR: 0.78, 95% CI: 0.67–0.91, p = 0.002) and restaurants (AOR: 0.81, 95% CI: 0.70–0.93, p = 0.004) (Fig. 3 ). A significant interaction was found between SHS exposure at home and receiving cessation advice (p for interaction < 0.05). The negative effect of SHS exposure on cessation was less pronounced among those who received professional advice to quit. Subgroup analyses revealed that the associations between SHS exposure and lower cessation success were consistent across sex, age group, and tobacco type (smoked/smokeless). Geospatial Analysis Choropleth mapping revealed a higher prevalence of SHS exposure and lower cessation rates in central and eastern states, overlapping with regions of higher tobacco use prevalence (Fig. 4 ). DISCUSSION This study provides a comprehensive analysis of the relationship between SHS exposure and tobacco cessation behavior among Indian adults based on a nationally representative sample collected during the GATS India 2016—17 [ 6 ]. This secondary analysis revealed SHS exposure as a major independent barrier for both quitting attempts and successful cessation among tobacco users in India, even after sociodemographic, behavioral and health system factors were adjusted. This evidence has important implications for tobacco control policy and practice, indicating a need for integrated interventions that include both assistance in quitting and strong actions to prevent SHS exposure, particularly in homes and workplaces. India is under the grip of tobacco scour, with a share of tobacco-related morbidity and mortality, with 28.6% of adults (266.8 million) currently using tobacco in some form, 10.7% (99.5 million) smoking tobacco, and 21.4% (199.4 million) using smokeless tobacco [ 22 ]. Although most adults are aware that tobacco is harmful (more than 92% believe that smoking causes serious illness), quit rates are low, and the gap between intention and behavior is quite wide. Among smokers, 55.4% report planning or thinking about quitting, but only 38.5% tried to quit in the past year; for smokeless tobacco, those figures are 49.6% and 33.2%, respectively [ 23 ]. SHS exposure remains alarmingly high in India. At the national level, 38.7% of adults are exposed to SHS at home, and 30.2% are exposed to their indoor workplace. Public place exposure, including restaurants, is also high (7.4% overall but 13% in men). These rates are in line with other reports in urban India of 33.1% SHS exposure occurring at home and 57.6% outside the home [ 24 ]. Women, children and those with low socioeconomic status are the most vulnerable to the health hazards of SHS, with approximately 50% of Indian children aged under 15 years being exposed to SHS at home [ 25 ]. The multilevel logistic regression models employed in this study revealed that, SHS exposure in the home, workplace and public places was significantly associated with lower odds of a quit attempt and successful cessation. In particular, being exposed to SHS at home was associated with 28% lower odds of attempting to quit smoking (AOR = 0.72, 95% CI = 0.65–0.80) and 35% lower odds of successful cessation (AOR = 0.65, 95% CI = 0.56–0.76). Comparable, albeit weaker, impacts were found for SHS exposure at the workplace and in public places. These findings are consistent with international evidence that SHS exposure discourages quitting attempts, further increases relapse risk, and maintains nicotine dependence. Neuroimaging studies have demonstrated that even brief SHS exposure delivers sufficient nicotine to the brain to induce craving, sustain addiction, and make quitting more difficult among people living in or working in environments where tobacco use is common [ 26 ]. In addition, qualitative research emphasizes social and environmental barriers to SHS reduction, including cultural norms and lack of smoke-free policies and empowerment of nonsmokers to demand smoke-free environment [ 27 ]. Consistent with prior research, the study findings reaffirm that, the home remains the primary site of SHS exposure, disproportionately affecting women, children, and nonsmoking adults. This is especially alarming in India, where high rates of smoking among men and the cultural permissibility of smoking in the domestic environment facilitate involuntary exposure [ 28 ]. Recent studies have revealed that close to 170 million children in India are exposed to SHS in their homes and that they are far more susceptible to being affected by various chronic respiratory conditions and tend to initiate tobacco use later in their life [ 29 ]. SHS exposure in the workplace is also a significant cause of involuntary smoking, particularly in the informal economy, where compliance with smoke-free laws is poorly adhered to or does not even exist [ 30 ]. Unlike formal workplaces, where rules can be more strictly enforced, informal workplaces do not always have designated smoking areas or monitoring mechanisms that are effective in maintaining high levels of SHS exposure among workers [ 31 ]. Hence, this analysis highlights the importance of implementing targeted interventions to promote voluntary smoke-free homes, which were found to be associated with reduced SHS exposure and to motivate smokers to quit. The evidence from high-income countries indicates that comprehensive smoke-free policies are effective in protecting nonsmokers and facilitating quitting and reducing overall tobacco consumption [ 32 ]. Despite the high burden of SHS exposure, only 48.8% of smokers and 31.7% of smokeless tobacco users were advised to quit by a healthcare professional in the previous 12 months [ 6 ]. This represents a missed opportunity for the health system to intervene, particularly as brief advice and cessation support have been effective in increasing quit rates. The interaction estimates of this study indicated that the adverse effect of SHS exposure on cessation is mitigated among those who receive professional quit advice, suggesting synergy between cessation support and SHS reduction [ 33 ]. These results suggest that addressing SHS exposure should be a major focus of efforts to control tobacco in India. Interventions that exclusively target individual behavior change are less likely to be successful in settings where SHS exposure is widespread and socially sanctioned. Comprehensive smoke-free policies are essential and should include enacting and enforcing bans on smoking in all indoor public places, workplaces, and multiunit housing, with particular attention to the informal sector and private home [ 34 , 35 , 36 ]. In addition, voluntary smoke-free home initiatives play a crucial role by empowering families, especially women and adolescents, to establish and maintain smoke-free environments through education, community engagement, and incentives. Strengthening the health system is also vital, involving the scaling up of cessation services, integrating tobacco control into primary care and other health programs, and ensuring routine screening and advice for all tobacco users [ 37 , 38 ]. Sustained mass media and public education campaigns are needed to raise awareness about the harms of SHSs, promote smoke-free norms, and reduce the social acceptability of tobacco use. Furthermore, targeted interventions should focus on vulnerable groups such as children, pregnant women, and low-income populations, who disproportionately bear the burden of SHS exposure and tobacco-related harm [ 39 , 40 ]. Together, these multifaceted strategies can effectively reduce SHS exposure and improve tobacco cessation outcomes. The findings agree with international evidence, for example, from studies in China and Europe, that SHS exposure undermines attempts to quit smoking [ 41 , 42 , 43 ]. These results highlight the importance of implementing comprehensive smoke-free policies in accordance with the WHO FCTC and integrating cessation support with SHS reduction interventions. Challenges exist in implementation (enforcement in informal workplaces and cultural acceptance of smoking at home) that need to be complemented with targeted interventions and public education. The use of multilevel modeling accounts for clustering and contextual effects, providing nuanced insights into the interplay between individual, household, and community factors. However, several limitations should be acknowledged. The cross-sectional design precludes causal inference, and self-reported measures of tobacco use and SHS exposure may be subject to recall and social desirability bias. Some potentially important variables, such as the duration and intensity of SHS exposure, the enforcement of smoke-free policies, and psychosocial factors, were not available in the dataset. Finally, while the study adjusts for a range of covariates, residual confounding cannot be ruled out. Further research should investigate the longitudinal effects and effectiveness of interventions in high-risk populations. CONCLUSION Exposure to secondhand smoke is a strong, common and significant obstacle to quitting and successful cessation among Indian tobacco users. Given the dual role of SHS exposure as a health threat and an obstacle to cessation, our results emphasize the need for combined tobacco control measures. The imperative of establishing comprehensive tobacco control programs that combine support for cessation with strong laws to reduce exposure to SHS in all settings, including homes and workplaces, is emphasized by our study. By addressing dual exposure to direct and indirect tobacco, India can take significant steps toward decreasing the burden of disease due to tobacco and the aims of improving public health. These findings are important for global tobacco use and SHS exposure reduction efforts and provide policy-relevant insights beyond India. Declarations Clinical Trial number Not applicable Ethics declaration The study was conducted in accordance with the Declaration of Helsinki. Ethical approval and Consent to participate Patient consent for publication Not applicable. Ethical considerations The GATS 2016-17 India dataset is public and deidentified. There was no requirement for additional ethical approval for this secondary data analysis Availability of data and materials Data are available in a public, open access repository. The dataset used for current analysis is available in a public repository from the Global Tobacco Surveillance System Data (GTSS Data) maintained by the Centers for Disease Control and Prevention. Competing interests The authors declare that they have no competing interests Funding Nil Authors’ contributions DLF conceptualised the idea and did the review of literature. SSP and SK designed the study. SSP performed the data curation. Data analysis was performed by DLF. DLF, SSP and SK drafted the paper. The draft was critically revised for important intellectual content by all authors and thereafter approved the final version. Acknowledgements Nil References US Department of Health and Human Services. The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. US Department of Health and Human Services, Centers for Disease Control and Prevention, Coordinating Center for Health Promotion, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2006. Bhatt G, Goel S, Tripathy JP, et al. Cessation of smokeless tobacco use in India: Findings from the Global Adult Tobacco Survey (GATS) 2016-17. Asian Pac J Cancer Prev. 2024;25(3):875-883. doi:10.31557/APJCP.2024.25.3.875 Itumalla R, Khatib MN, Gaidhane S, Zahiruddin QS, Gaidhane AM, Neyazi A, Hassam AF, Satapathy P, Rustagi S, Kukreti N, Padhi BK. Smokeless tobacco consumption among women of reproductive age: a systematic review and meta-analysis. BMC Public Health. 2024 May 20;24(1):1361. doi: 10.1186/s12889-024-18840-z. Yang P, Cheung WY, Sun A, et al. Second-Hand Smoke as a Predictor of Smoking Cessation Among Lung Cancer Survivors. J Clin Oncol. 2014;32(6):564-570. doi:10.1200/JCO.2013.50.9695 Bhatt G, Goel S, Tripathy JP, et al. Estimating the Cost of Delivering Tobacco Cessation Interventions in India: A National Health System Perspective. Nicotine Tob Res. 2023;25(7):1171-1178. doi:10.1093/ntr/ntad099 Ministry of Health and Family Welfare GoI. Global adult tobacco survey: India report 2016-17, 2017. Singh A, Ladusingh L. Second-hand smoke exposure prevalence among smokers versus nonsmokers and relative change at subnational level in India: a secondary analysis from Global Adult Tobacco Survey 1 and 2. Int J Community Med Public Health. 2021;8(5):2419-2426. doi:10.18203/2394-6040.ijcmph20211767 Ramanadhan S, Xuan Z, Choi J, et al. Associations between sociodemographic factors and receiving "ask and advise" services from healthcare providers in India: analysis of the national GATS-2 dataset. BMC Public Health. 2022; 22:14538. doi:10.1186/s12889-022-14538-2 Sinha DN, Sahoo N, Palipudi KM, et al. Secondhand Tobacco Smoke Exposure among Adults in an Urban Community of Hyderabad, India: A Cross-Sectional Study. Indian J Community Med. 2025;50(1):10-17. doi: 10.4103/ijcm.ijcm_10_25.1 National Institute on Drug Abuse. Secondhand smoke may increase vulnerability to nicotine addiction. ScienceDaily. May 3, 2011. Accessed June 3,2025 Winickoff JP, Friebely J, Tanski SE, et al. Reducing secondhand smoke exposure among children and adolescents: emerging issues for intervening with medically at-risk youth. Pediatrics. 2008;121(4): e682-e692. doi:10.1542/peds.2007-2327. Okoli CTC, Seng S. Associations Between Secondhand Tobacco Smoke Exposure and Nicotine Dependence and Smoking Cessation Attempts Among Adult Tobacco Users with a Psychiatric Disorder. Biol Res Nurs. 2018;20(5):558-565. doi: 10.1177/1099800418781914. Lee S, Kim J, Kim H, et al. Global association of secondhand smoke exposure locations and smoking behavi o ou r among adolescents in 99 countries. Acta Paediatr. 2024;113(9):1792-1802. doi:10.1111/apa.17030 Sinha DN, Palipudi KM, Gupta PC, et al. Changes in Prevalence of Childhood Exposure to Secondhand Smoke in India: A Secondary Analysis of GATS Survey (2009-2017). Asian Pac J Cancer Prev. 2021;22(5):1459-1466. doi:10.31557/APJCP.2021.22.5.1459 Bhojani U, Soors W. Tobacco control in India: A case for the health-in-All Policy approach. Natl Med J India. 2015;28(2):86-9. Francis, D. L., Reddy, S. S. P., Logaranjani, A., Thankappan, P., & Manohar, B., et al. Are We Adequately Dissuading Youth Initiation and Increasing Quit Lines with Appropriate Warning Labels in India? J Oral Dent Health. 2023; 7(4): 242-245. McCarthy M, Siahpush M, Shaikh RA, Sikora Kessler A, Tibbits M. Social Disparities in Unaided Quit Attempts Among Daily Current and Former Smokers: Results From the 2010-2011 Tobacco Use Supplement to the Current Population Survey. Nicotine Tob Res. 2016;18(8):1705-10. doi: 10.1093/ntr/ntw007. John RM, Dauchy EP. Healthcare Costs Attributable to Secondhand Smoke Exposure Among Indian Adults. Nicotine Tob Res. 2022; 24(9):1478-1486. doi: 10.1093/ntr/ntac048. Nair V, Mallya SD, Pandey AK, Singh PK, Yadav A, Kulkarni MM. Determinants of quit attempts among current Indian tobacco users: Findings from Global Adult Tobacco Survey, 2016-17. Clin Epidemiol Glob Health. 2023; 23:101366. doi: 10.1016/j.cegh.2023.101366 Possenti I, Gallus S, Lugo A, López AM, Carreras G, Fernández-Megina R, González-Marrón A, Gorini G, Koprivnikar H, Papachristou E, Lambrou A, Schoretsaniti S, Pénzes M, Carnicer-Pont D, Fernandez E. Best practices for secondhand smoke and secondhand aerosol protection and evidence supporting the expansion of smoke- and aerosol-free environments: Recommendations from the 2nd Joint Action on Tobacco Control. Tob Prev Cessat. 2024;10. doi: 10.18332/tpc/193147. Chandramouli C, General R. Census of India 2011. Provisional Population Totals New Delhi, Government of India, 2011: 409–13. Anand, V., S, V., G, S., & S, G. (2019). Current status of tobacco in India: a preventable cause of death. University Journal of Medicine and Medical Specialities, 5(1). Islam, Md. M. Comparison between Smokers and Smokeless Tobacco Users in Their Past Attempts and Intentions to Quit: Analysis of Two Rounds of a National Survey. International Journal of Environmental Research and Public Health. 2022; 19(20): 13662. Tripathy JP. Secondhand smoke exposure at home and public places among smokers and non non- smokers in India: findings from the Global Adult Tobacco Survey 2016-17. Environ Sci Pollut Res Int. 2020;27(6):6033-6041. doi: 10.1007/s11356-019-07341-x. Argalasova Sobotova L. Secondhand smoke and its unfavorable associations in vulnerable population groups. Ann Nurs. 2023;1(4). doi: 10.58424/annnurs.en3.8zp.se7 Brody AL. Functional brain imaging of tobacco uses and dependence. J Psychiatr Res. 2006;40(5):404-18. doi: 10.1016/j.jpsychires.2005.04.012. Kibria MG, Islam T, Badiuzzaman M, Al Mamun A, Sultana P, Hawlader MDH. Assessing the choice of smoke-free policies for multiunit housing and its associated determinants in Bangladesh: a cross-sectional study. BMJ Open. 2024;14(4): e074928. doi:10.1136/bmjopen-2023-074928 Tripathy JP. Secondhand Smoke Exposure among Children in Indian Homes: Findings from the Global Adult Tobacco Survey. Behav Med. 2024;50(1):75-81. doi: 10.1080/08964289.2022.2105795. Singh PK, Sinha P, Singh N, Singh L, Singh S. Does secondhand smoke exposure increase the risk of acute respiratory infections among children aged 0-59 months in households that use clean cooking fuel? A cross-sectional study based on 601 509 households in India. Indoor Air. 2022;32(1): e12980. doi: 10.1111/ina.12980 Fichtenberg CM, Glantz SA. Effect of smoke-free workplaces on smoking behavi o ou r: systematic review. BMJ. 2002;325(7357):188. doi: 10.1136/bmj.325.7357.188. Schneider S, Lunau T, Eikemo TA, Kotz D, Bambra C, Kuntz B, Dragano N. Better air but not for all? Changes in second-hand smoke exposure at workplaces in 29 European countries over 10 years. Eur J Public Health. 2021;31(4):708-714. doi: 10.1093/eurpub/ckab035. Garritsen HH, Khan F, Rozema AD, Navas-Acien A, Hernández D. Associations of smoke-free policies in mult i i- unit housing with smoking behavior and second-hand smoke exposure: A systematic review. Addiction. 2025;120(4):578-588. doi: 10.1111/add.16724. Owusu D, Wang KS, Quinn M, Aibangbee J, John RM, Mamudu HM. Health Care Provider Intervention and Utilization of Cessation Assistance in 12 Low- and Middle-Income Countries. Nicotine Tob Res. 2019;21(2):188-196. doi: 10.1093/ntr/nty028 Bushi G, Khatib MN, Balaraman AK, Ballal S, Bansal P, et al. Prevalence of dual use of combustible tobacco and E-cigarettes among pregnant smokers: a systematic review and meta-analysis. BMC Public Health. 2024; 24:20746. doi:10.1186/s12889-024-20746-9 Chopra M, Gupta A, Sharma B, Kakade N, Arora M. Assessing second-hand smoke exposure among nonsmoking youth in India: Insights from GATS I & II. Indian J Med Res. 2024;160(6):578-591. doi: 10.25259/IJMR_388_2024. Francis DL, Reddy SSP, Rathi M, Chopra SS. From periodontal inflammation to oral cancer: the impact of smokeless tobacco. Lancet Reg Health Southeast Asia. 2025; 36:100574. Durazo A, Hartman-Filson M, Perez K, Alizaga NM, Petersen AB, Vijayaraghavan M. Smoke-Free Home Intervention in Permanent Supportive Housing: A Multifaceted Intervention Pilot. Nicotine Tob Res. 2021;23(1):63-70. doi: 10.1093/ntr/ntaa043. Pipe AL, Evans W, Papadakis S. Smoking cessation: health system challenges and opportunities. Tob Control. 2022;31(2):340-347. doi: 10.1136/tobaccocontrol-2021-056575. Singh RJ, Lal PG. Second-hand smoke: a neglected public health challenge. Indian J Public Health. 2011;55(3):192-8. doi: 10.4103/0019-557X.89950. Siddiqui AA, Abideen MZU, Abdullah M, Sheriyar FH, Hussain W, et al. Investigating oral cancer awareness in outpatient settings: a hospital-based study. Bangladesh Journal of Medical Science. 2025;24(2). doi:10.3329/bjms. v24i2.81712 Wang YT, Hu KR, Zhao J, Ai FL, Shi YL, Wang XW, Yang WY, Wang JX, Ai LM, Wan X. The Association between Exposure to Second-Hand Smoke and Disease in the Chinese Population: A Systematic Review and Meta-Analysis. Biomed Environ Sci. 2023;36(1):24-37. doi: 10.3967/bes2023.003. Zeng X, Xiao L, Liu S. Exposure to tobacco advertisements or promotions and smoking susceptibility among adolescents in China from 2013-14 to 2021: findings from the China National Youth Tobacco Survey. BMC Public Health. 2025;25(1):37. doi: 10.1186/s12889-024-21188-z. Nogueira SO, Fernández E, Driezen P, Fu M, Tigova O, Castellano Y, Mons U, Herbeć A, Kyriakos CN, Demjén T, Trofor AC, Przewoźniak K, Katsaounou PA, Vardavas CI, Fong GT; EUREST-PLUS Consortium. Secondhand Smoke Exposure in European Countries with Different Smoke-Free Legislation: Findings From the EUREST-PLUS ITC Europe Surveys. Nicotine Tob Res. 2022 ;24(1):85-92. doi: 10.1093/ntr/ntab 157. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 27 Jan, 2026 Reviewers agreed at journal 17 Jan, 2026 Reviewers agreed at journal 15 Jan, 2026 Reviews received at journal 24 Nov, 2025 Reviewers agreed at journal 10 Nov, 2025 Reviewers agreed at journal 10 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviewers agreed at journal 18 Aug, 2025 Reviewers invited by journal 18 Aug, 2025 Editor invited by journal 06 Aug, 2025 Editor assigned by journal 06 Aug, 2025 Submission checks completed at journal 05 Aug, 2025 First submitted to journal 05 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7275925","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503289451,"identity":"4b21d03f-2601-4ab5-b152-bdcf0126cec8","order_by":0,"name":"Delfin Lovelina Francis","email":"","orcid":"","institution":"Saveetha Institute of Medical And Technical Sciences, Chennai","correspondingAuthor":false,"prefix":"","firstName":"Delfin","middleName":"Lovelina","lastName":"Francis","suffix":""},{"id":503289452,"identity":"194a5c77-5127-4c94-b878-9cebb1ce71de","order_by":1,"name":"Saravanan Sampoornam Pape Reddy","email":"","orcid":"","institution":"Army Dental Centre (Research \u0026 Referral)","correspondingAuthor":false,"prefix":"","firstName":"Saravanan","middleName":"Sampoornam Pape","lastName":"Reddy","suffix":""},{"id":503289453,"identity":"753bf041-45e4-468d-ae40-ebdcc120dfd0","order_by":2,"name":"Shaswata Karmakar","email":"data:image/png;base64,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","orcid":"","institution":"Manipal Academy of Higher Education","correspondingAuthor":true,"prefix":"","firstName":"Shaswata","middleName":"","lastName":"Karmakar","suffix":""}],"badges":[],"createdAt":"2025-08-02 06:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7275925/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7275925/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89984460,"identity":"bf783eb1-4254-478f-9515-d521f2526f5e","added_by":"auto","created_at":"2025-08-27 06:37:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2692864,"visible":true,"origin":"","legend":"\u003cp\u003eQuit Attempts and Cessation Indicators\u003c/p\u003e","description":"","filename":"figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7275925/v1/4cd615264687ee53b501b065.jpg"},{"id":89984464,"identity":"93981220-bccb-4c21-a02d-32ce56f7d7f7","added_by":"auto","created_at":"2025-08-27 06:37:14","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2491759,"visible":true,"origin":"","legend":"\u003cp\u003eMultilevel Logistic Regression for Quit Attempts\u003c/p\u003e","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7275925/v1/3801b1fd38fdbbe3bf9d3bee.jpg"},{"id":89982423,"identity":"20bf0aec-276e-4d0c-adf3-db1e300e363d","added_by":"auto","created_at":"2025-08-27 06:29:12","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2215249,"visible":true,"origin":"","legend":"\u003cp\u003eMultilevel logistic regression for successful cessation\u003c/p\u003e","description":"","filename":"figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7275925/v1/8add267f70b0e8962ac6c708.jpg"},{"id":89982441,"identity":"7fac9b67-eb16-47f7-b244-beb1861c9cf0","added_by":"auto","created_at":"2025-08-27 06:29:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3953466,"visible":true,"origin":"","legend":"\u003cp\u003eChoropleth mapping of SHS exposure and cessation rates\u003c/p\u003e","description":"","filename":"figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7275925/v1/cca185153ee5f0a2129f89e6.jpg"},{"id":89984465,"identity":"9a25473c-9935-4a12-987e-5d3167457a6e","added_by":"auto","created_at":"2025-08-27 06:37:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12057072,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7275925/v1/2d76b060-b855-4bb0-9de0-57f617d93db4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Second-hand smoke exposure as an independent determinant of quit attempts and successful tobacco cessation: A multilevel analysis of the GATS (2016–17), India","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eTobacco use remains one of the greatest public health issues in the world, with more than eight million deaths each year. Low- and middle-income nations such as India bear a disproportionate amount of this burden [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. India has the second-highest number of tobacco users globally and is facing two epidemics: the widespread threat of second-hand smoke (SHS) exposure and the direct health effects of tobacco. In India, involuntary tobacco smoke exposure is quite common. According to the Global Adult Tobacco Survey (GATS) 2016–17, approximately 29% of adults are exposed to SHS at home, and comparable percentages are exposed in public and workplace settings. Additionally, approximately 28.6% of adults in India consume some form of tobacco, representing more than 268\u0026nbsp;million users [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The initiation of tobacco use often occurs early, with a considerable number of users starting before the age of 18 and a notable proportion of women and minors being affected. Despite increasing awareness of the harmful effects of tobacco, only 13% of smokers and 5% of smokeless tobacco users have successfully quit, and most quit attempts are usually short-lived [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Such continued use is further amplified by high levels of SHS exposure, not only for non-users but also in ways that undermine quit attempts among active users.\u003c/p\u003e\u003cp\u003eThe prevalence of SHS exposure is very high in the Indian population, as 38.7% of adults are exposed to SHS in the home. SHS exposure in public places and workplaces are also substantially high, especially among males and young adults. State-level disparities were also seemingly high; for example, in some states, more than 50% of households and public locations reported SHS exposure [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Women, children, and underserved and vulnerable populations, such as individuals of lower socioeconomic classes, are disproportionately affected by this burden [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A recent study quantified the annual healthcare costs attributable to SHS exposure at INR 567\u0026nbsp;billion, accounting for 8% of the nation’s total healthcare expenditure [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Crucially, SHS exposure also prevents current smokers from quitting. Based on the findings of neurobiological studies, short-term SHS exposure could provide enough nicotine to the brain to trigger cravings and maintain dependence, making quitting harder [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A pioneering positron emission tomography imaging study revealed that SHS exposure in a closed chamber for one hour led to measurable nicotine binding in the brain, like active smoking [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This physiological reinforcement is supported by behavioral studies where people who have been exposed to SHS, from either within the home or from intimate social relationships, are less likely to try to quit and more likely to relapse after quitting [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Emerging evidence suggests a reciprocal relationship between exposure to SHS and tobacco use behaviors. Exposure to SHS is not only a harmful phenomenon that can harm health but also a shaping factor in the trajectory of tobacco use, especially in adolescents and young people. A nationwide study in China revealed that adolescents exposed to SHS in home and public places had higher probabilities of initiating smoking, current smoking, and e-cigarette use, regardless of whether they were in middle school or high school. Similar trends are observed in India, where youth exposed to SHS are more susceptible to tobacco use, and home exposure is a particularly strong risk factor [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSHS exposure in India is influenced by a range of sociodemographic factors. Researchers have found that gender, education, occupation, type of residence, and wealth index are the most crucial factors influencing SHS exposure in different studies using GATS data [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Centered around the Cigarettes and Other Tobacco Products Act (COTPA), 2003, and the WHO Framework on Tobacco Control (FCTC), India’s tobacco control framework has achieved a significant amount of control by reducing public smoking and increasing awareness [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, there are still implementation deficits, especially in home and nonformal work settings, which are the main sources of exposure to SHSs. In addition, the existence of smoking rooms or places in public settings and the limited adherence to policies in private microenvironments weaken the impact of smoke-free laws. Nationally available cessation support services (such as Quitline, mCessation, and tobacco cessation centers) have been established but are used on a limited scale. Most quit attempts are unassisted, and the inclusion of SHS reduction methods in cessation programs is not routine. These disparities are especially alarming given that SHS exposure has been shown to hinder cessation attempts, supporting the need for broad, multifaceted intervention [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Most of the current analyses concentrate on the prevalence and determinants of environmental tobacco smoke (ETS) among never-users or on quit-related predictors among ever-users, with little consideration of the overlap between these behaviors. Although SHS exposure supporting cessation is well established worldwide, Indian-specific evidence is scarce. This gap becomes even more pertinent given the ongoing low quit rates and high relapse rates reported for India [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. To develop more effective tobacco control interventions, it is critical to ascertain the impact of SHS exposure in different environments, such as homes, workplaces, and public places, which has an impact on quitting attempts and sustained cessation. Incorporating SHS prevention into smoking cessation efforts may increase the impact of these interventions, particularly among vulnerable populations that experience elevated levels of exposure and may have more difficulty quitting [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite the enormous amount of available literature on tobacco and SHS use in India, a key knowledge gap still exists where there has not yet been an in-depth systematic examination of the effect of SHS exposure on quitting among adults in India using nationally representative data. Therefore, in the current study, we undertook the secondary data analysis of GATS-2 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] with an aim to fill a critical evidence gap by elucidating the relationship between SHS exposure and tobacco cessation outcomes among Indian adults. This is the first study to examine, in a comprehensive manner, the independent effects of SHS exposure at home, work, and in public places on quitting attempts and successful avoidance of tobacco from a nationally representative population in India.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cb\u003eStudy settings\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe nationwide representative survey of GATS (Round 2) was undertaken in the Indian subcontinent during years 2016–2017 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], with a population coverage estimate of 1029\u0026nbsp;million (Census 2011) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Design and Data Source\u003c/b\u003e\u003c/p\u003e\u003cp\u003e The study was conducted in accordance with the Declaration of Helsinki. A cross-sectional secondary analysis of data from the GATS India 2016-17 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] was conducted. The GATS is a nationally representative household survey conducted via a multistage, geographically stratified cluster sample of populations to generate estimates of tobacco use and cessation, SHS exposure, and related sociodemographic and behavioral indicators in India over 15 years or above. The study population included adults (aged ≥ 15 years) who were current or ever users of any tobacco products in smoked or smokeless forms. Persons with incomplete data on critical variables (tobacco use status, SHS exposure, or cessation results) were excluded from the analyses. To minimize selection bias, analysis utilized sampling weights from GATS 2016-17 India datasets to reflect the national adult population. Self-reported measures of SHS exposure and cessation introduce the possibility of information bias; however, GATS employs standardized, validated questions to minimize error.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutcome measures\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe primary outcomes assessed were a quit attempt, defined as a self-reported attempt to quit tobacco in the past 12 months, and successful cessation, indicated by self-reported former tobacco use with no current use of any tobacco product at the time of the survey. The main predictor was SHS exposure, measured across three domains—at home, at workplace, and in public places with each domain dichotomized as yes or no based on self-reports. The covariates included a comprehensive set of sociodemographic and behavioral factors, such as age, gender, education, occupation, wealth index, caste, religion, urban or rural residence, geographic region, type and frequency of tobacco use, age of initiation, awareness of health risks, receipt of cessation advice, and use of tobacco cessation support services, such as mCessation or quitlines. The two main outcomes measured were quit attempt (self-reported attempt to quit tobacco in the past 12 months) and successful cessation (self-reported former use of tobacco with no current use of any tobacco product at the time of the survey).\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAll analyses used the complex survey design and sampling weights of the GATS 2016-17 dataset [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], which provided statistics that were nationally representative. Analytic software included both the SPSS complex samples module and Stata survey (svy) commands. Multilevel logistic regression modeling and structural equation modeling was employed to adjust for the clustered data design and to examine complex relationships between SHS exposure and cessation. All analyses followed the STROBE recommendations.\u003c/p\u003e\u003cp\u003ePrevalence estimates were obtained through weighted calculations based on exposure to SHS, attempts to quit, and successful cessation across key sociodemographic and behavioral characteristics. Chi-square tests were performed to compare bivariate relationships between SHS exposure and cessation outcomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMultilevel Modeling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs the data were hierarchical (individuals nested within households and households within primary sampling units [PSUs]), we used multilevel logistic regression models to account for clustering at both the household and the PSU level. Initially, a null (intercept-only) model was fitted to estimate the intraclass correlation coefficient (ICC), which quantifies the degree of clustering within households and PSUs. Subsequently, mixed-effects logistic regression models were specified to examine the association between SHS exposure and cessation outcomes (quit attempts and successful cessation) while adjusting for potential confounders. The model was formulated as follows:\u003c/p\u003e\u003cp\u003elogit (Pijk)=β0 + β1SHSijk + β2Xijk + uj + vklogit (\u003cem\u003ePijk\u003c/em\u003e)=\u003cem\u003eβ\u003c/em\u003e0 + \u003cem\u003eβ\u003c/em\u003e1SHS\u003cem\u003eijk\u003c/em\u003e + \u003cem\u003eβ\u003c/em\u003e2\u003cem\u003eXijk\u003c/em\u003e + \u003cem\u003euj\u003c/em\u003e + \u003cem\u003evk\u003c/em\u003e\u003c/p\u003e\u003cp\u003ewhere Pijk represents the probability of a quit attempt or successful cessation for individual i in household j and PSU k; SHSijk is the main predictor variable indicating exposure to secondhand smoke; Xijk is a vector of covariates including demographic and behavioral factors; uj denotes the random effect at the household level; and vk denotes the random effect at the PSU level. Model fit was assessed via the Akaike information criterion (AIC) and likelihood ratio tests to compare nested models and determine the best-fitting model.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAdvanced Statistical Modeling\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA multivariate logistic regression for adjusted odds ratios (AORs) and 95% confidence intervals (CIs) were estimated for the association between SHS exposure and cessation outcomes, controlling for all covariates. For outcomes with more than two categories (e.g., no attempt, attempted, successful), multinomial logistic regression models were employed. The effect modification was assessed by including interaction terms (e.g., SHS exposure × use of cessation support, SHS exposure × gender). To explore direct and indirect pathways between SHS exposure, behavioral factors, and cessation outcomes, structural equation modeling (SEM) was conducted via AMOS or R (lavaan package), modeling latent constructs such as the intention to quit and social support.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSensitivity and subgroup analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSubgroup analysis was conducted by tobacco type (smoked versus smokeless), sex, age group, and region. Sensitivity analyses involved the exclusion of participants with missing data and alternative definitions of successful cessation (e.g., abstaining ≥ 6 months).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGeospatial Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll maps were created via ESRI ArcGIS to depict state-level differences in SHS exposure and cessation metrics.\u003c/p\u003e"},{"header":"RESULT","content":"\u003cp\u003eA total of 74,037 adults aged 15 years and older were interviewed in GATS India from 2016-17[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and they represented a nationally weighted sample of 266.8\u0026nbsp;million current tobacco uses (smoked and/or smokeless). The weighted prevalence of current tobacco use was 28.6% (42.4% for men, 14.2% for women). Among all adults, 10.7% (99.5\u0026nbsp;million) currently smoked tobacco, and 21.4% (199.4\u0026nbsp;million) used smokeless tobacco (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the current smokers, 38.5% had made a quit attempt in the previous 12 months (38.8% men, 35.5% women), and 33.2% of current users who were smokeless were attempting to quit (35.2% men, 28.4% women). A total of 55.4% of current smokers and 49.6% of smokeless tobacco users reported planning or thinking about quitting. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWeighted prevalence (%) of SHS exposure and tobacco use (GATS 2016-17)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndicator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMen (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWomen (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEstimated n (millions)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent tobacco use (smoked and/or smokeless)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e266.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent tobacco smokers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e99.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent smokeless tobacco users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e199.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposed to SHS at home\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e~ 360.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposed to SHS at workplace*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposed to SHS at restaurants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e*Among adults who work indoors or both indoors and outdoors.\u003c/p\u003e\u003cp\u003eSHS exposure at home was reported by 38.7% of adults, and the prevalence among men (38.1%) and women (39.3%) was comparable. Workplace SHS exposure was 30.2% overall and higher in men (32.7%) than in women (17.9%). There were significantly fewer attempts to quit smoking in the last year among SHS exposed participants at home and in the workplace than among those who were not exposed (p \u0026lt; 0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMultilevel Logistic Regression Models\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eModel 1: SHS exposure and quiet attempts\u003c/b\u003e: After we adjusted for sociodemographic and behavioral covariates, exposure to SHS at home was independently associated with lower odds of quitting attempts among current tobacco users (AOR = 0.72, 95% CI = 0.65–0.80, p \u0026lt; 0.001). SHS exposure at the workplace (AOR: 0.81, 95% CI: 0.73–0.90, p \u0026lt; 0.001) and at restaurants/public places (AOR: 0.85, 95% CI: 0.77–0.94, p = 0.002) was also negatively associated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eModel 2: SHS exposure and successful cessation\u003c/b\u003e: According to the fully adjusted model, exposure to SHS at home was also a strong independent predictor of a lower likelihood of successful cessation (AOR: 0.65, 95% CI: 0.56–0.76, p \u0026lt; 0.001). Similar negative associations were found for SHS at work (AOR: 0.78, 95% CI: 0.67–0.91, p = 0.002) and restaurants (AOR: 0.81, 95% CI: 0.70–0.93, p = 0.004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA significant interaction was found between SHS exposure at home and receiving cessation advice (p for interaction \u0026lt; 0.05). The negative effect of SHS exposure on cessation was less pronounced among those who received professional advice to quit. Subgroup analyses revealed that the associations between SHS exposure and lower cessation success were consistent across sex, age group, and tobacco type (smoked/smokeless).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGeospatial Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eChoropleth mapping revealed a higher prevalence of SHS exposure and lower cessation rates in central and eastern states, overlapping with regions of higher tobacco use prevalence (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study provides a comprehensive analysis of the relationship between SHS exposure and tobacco cessation behavior among Indian adults based on a nationally representative sample collected during the GATS India 2016\u0026mdash;17 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This secondary analysis revealed SHS exposure as a major independent barrier for both quitting attempts and successful cessation among tobacco users in India, even after sociodemographic, behavioral and health system factors were adjusted. This evidence has important implications for tobacco control policy and practice, indicating a need for integrated interventions that include both assistance in quitting and strong actions to prevent SHS exposure, particularly in homes and workplaces.\u003c/p\u003e\u003cp\u003eIndia is under the grip of tobacco scour, with a share of tobacco-related morbidity and mortality, with 28.6% of adults (266.8\u0026nbsp;million) currently using tobacco in some form, 10.7% (99.5\u0026nbsp;million) smoking tobacco, and 21.4% (199.4\u0026nbsp;million) using smokeless tobacco [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although most adults are aware that tobacco is harmful (more than 92% believe that smoking causes serious illness), quit rates are low, and the gap between intention and behavior is quite wide. Among smokers, 55.4% report planning or thinking about quitting, but only 38.5% tried to quit in the past year; for smokeless tobacco, those figures are 49.6% and 33.2%, respectively [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSHS exposure remains alarmingly high in India. At the national level, 38.7% of adults are exposed to SHS at home, and 30.2% are exposed to their indoor workplace. Public place exposure, including restaurants, is also high (7.4% overall but 13% in men). These rates are in line with other reports in urban India of 33.1% SHS exposure occurring at home and 57.6% outside the home [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Women, children and those with low socioeconomic status are the most vulnerable to the health hazards of SHS, with approximately 50% of Indian children aged under 15 years being exposed to SHS at home [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe multilevel logistic regression models employed in this study revealed that, SHS exposure in the home, workplace and public places was significantly associated with lower odds of a quit attempt and successful cessation. In particular, being exposed to SHS at home was associated with 28% lower odds of attempting to quit smoking (AOR\u0026thinsp;=\u0026thinsp;0.72, 95% CI\u0026thinsp;=\u0026thinsp;0.65\u0026ndash;0.80) and 35% lower odds of successful cessation (AOR\u0026thinsp;=\u0026thinsp;0.65, 95% CI\u0026thinsp;=\u0026thinsp;0.56\u0026ndash;0.76). Comparable, albeit weaker, impacts were found for SHS exposure at the workplace and in public places. These findings are consistent with international evidence that SHS exposure discourages quitting attempts, further increases relapse risk, and maintains nicotine dependence. Neuroimaging studies have demonstrated that even brief SHS exposure delivers sufficient nicotine to the brain to induce craving, sustain addiction, and make quitting more difficult among people living in or working in environments where tobacco use is common [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In addition, qualitative research emphasizes social and environmental barriers to SHS reduction, including cultural norms and lack of smoke-free policies and empowerment of nonsmokers to demand smoke-free environment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsistent with prior research, the study findings reaffirm that, the home remains the primary site of SHS exposure, disproportionately affecting women, children, and nonsmoking adults. This is especially alarming in India, where high rates of smoking among men and the cultural permissibility of smoking in the domestic environment facilitate involuntary exposure [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Recent studies have revealed that close to 170\u0026nbsp;million children in India are exposed to SHS in their homes and that they are far more susceptible to being affected by various chronic respiratory conditions and tend to initiate tobacco use later in their life [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. SHS exposure in the workplace is also a significant cause of involuntary smoking, particularly in the informal economy, where compliance with smoke-free laws is poorly adhered to or does not even exist [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Unlike formal workplaces, where rules can be more strictly enforced, informal workplaces do not always have designated smoking areas or monitoring mechanisms that are effective in maintaining high levels of SHS exposure among workers [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Hence, this analysis highlights the importance of implementing targeted interventions to promote voluntary smoke-free homes, which were found to be associated with reduced SHS exposure and to motivate smokers to quit. The evidence from high-income countries indicates that comprehensive smoke-free policies are effective in protecting nonsmokers and facilitating quitting and reducing overall tobacco consumption [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Despite the high burden of SHS exposure, only 48.8% of smokers and 31.7% of smokeless tobacco users were advised to quit by a healthcare professional in the previous 12 months [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This represents a missed opportunity for the health system to intervene, particularly as brief advice and cessation support have been effective in increasing quit rates. The interaction estimates of this study indicated that the adverse effect of SHS exposure on cessation is mitigated among those who receive professional quit advice, suggesting synergy between cessation support and SHS reduction [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese results suggest that addressing SHS exposure should be a major focus of efforts to control tobacco in India. Interventions that exclusively target individual behavior change are less likely to be successful in settings where SHS exposure is widespread and socially sanctioned. Comprehensive smoke-free policies are essential and should include enacting and enforcing bans on smoking in all indoor public places, workplaces, and multiunit housing, with particular attention to the informal sector and private home [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In addition, voluntary smoke-free home initiatives play a crucial role by empowering families, especially women and adolescents, to establish and maintain smoke-free environments through education, community engagement, and incentives. Strengthening the health system is also vital, involving the scaling up of cessation services, integrating tobacco control into primary care and other health programs, and ensuring routine screening and advice for all tobacco users [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Sustained mass media and public education campaigns are needed to raise awareness about the harms of SHSs, promote smoke-free norms, and reduce the social acceptability of tobacco use. Furthermore, targeted interventions should focus on vulnerable groups such as children, pregnant women, and low-income populations, who disproportionately bear the burden of SHS exposure and tobacco-related harm [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Together, these multifaceted strategies can effectively reduce SHS exposure and improve tobacco cessation outcomes. The findings agree with international evidence, for example, from studies in China and Europe, that SHS exposure undermines attempts to quit smoking [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. These results highlight the importance of implementing comprehensive smoke-free policies in accordance with the WHO FCTC and integrating cessation support with SHS reduction interventions. Challenges exist in implementation (enforcement in informal workplaces and cultural acceptance of smoking at home) that need to be complemented with targeted interventions and public education.\u003c/p\u003e\u003cp\u003eThe use of multilevel modeling accounts for clustering and contextual effects, providing nuanced insights into the interplay between individual, household, and community factors. However, several limitations should be acknowledged. The cross-sectional design precludes causal inference, and self-reported measures of tobacco use and SHS exposure may be subject to recall and social desirability bias. Some potentially important variables, such as the duration and intensity of SHS exposure, the enforcement of smoke-free policies, and psychosocial factors, were not available in the dataset. Finally, while the study adjusts for a range of covariates, residual confounding cannot be ruled out. Further research should investigate the longitudinal effects and effectiveness of interventions in high-risk populations.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eExposure to secondhand smoke is a strong, common and significant obstacle to quitting and successful cessation among Indian tobacco users. Given the dual role of SHS exposure as a health threat and an obstacle to cessation, our results emphasize the need for combined tobacco control measures. The imperative of establishing comprehensive tobacco control programs that combine support for cessation with strong laws to reduce exposure to SHS in all settings, including homes and workplaces, is emphasized by our study. By addressing dual exposure to direct and indirect tobacco, India can take significant steps toward decreasing the burden of disease due to tobacco and the aims of improving public health. These findings are important for global tobacco use and SHS exposure reduction efforts and provide policy-relevant insights beyond India.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical Trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and Consent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econsiderations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe GATS 2016-17 India dataset is public and deidentified. There was no requirement for additional ethical approval for this secondary data analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available in a public, open access repository. The dataset used for current analysis is available in a public repository from the Global Tobacco Surveillance System Data (GTSS Data) maintained by the Centers for Disease Control and Prevention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNil\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDLF conceptualised the idea and did the review of literature. SSP and SK designed the study. SSP performed the data curation. Data analysis was performed by DLF. DLF, SSP and SK drafted the paper. The draft was critically revised for important intellectual content by all authors and thereafter approved the final version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNil\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUS Department of Health and Human Services. The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. US Department of Health and Human Services, Centers for Disease Control and Prevention, Coordinating Center for Health Promotion, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2006. \u003c/li\u003e\n\u003cli\u003eBhatt G, Goel S, Tripathy JP, et al. Cessation of smokeless tobacco use in India: Findings from the Global Adult Tobacco Survey (GATS) 2016-17. Asian Pac J Cancer Prev. 2024;25(3):875-883. doi:10.31557/APJCP.2024.25.3.875\u003c/li\u003e\n\u003cli\u003eItumalla R, Khatib MN, Gaidhane S, Zahiruddin QS, Gaidhane AM, Neyazi A, Hassam AF, Satapathy P, Rustagi S, Kukreti N, Padhi BK. Smokeless tobacco consumption among women of reproductive age: a systematic review and meta-analysis. BMC Public Health. 2024 May 20;24(1):1361. doi: 10.1186/s12889-024-18840-z.\u003c/li\u003e\n\u003cli\u003eYang P, Cheung WY, Sun A, et al. Second-Hand Smoke as a Predictor of Smoking Cessation Among Lung Cancer Survivors. J Clin Oncol. 2014;32(6):564-570. doi:10.1200/JCO.2013.50.9695\u003c/li\u003e\n\u003cli\u003eBhatt G, Goel S, Tripathy JP, et al. Estimating the Cost of Delivering Tobacco Cessation Interventions in India: A National Health System Perspective. Nicotine Tob Res. 2023;25(7):1171-1178. doi:10.1093/ntr/ntad099\u003c/li\u003e\n\u003cli\u003eMinistry of Health and Family Welfare GoI. Global adult tobacco survey: India report 2016-17, 2017.\u003c/li\u003e\n\u003cli\u003eSingh A, Ladusingh L. Second-hand smoke exposure prevalence among smokers versus nonsmokers and relative change at subnational level in India: a secondary analysis from Global Adult Tobacco Survey 1 and 2. Int J Community Med Public Health. 2021;8(5):2419-2426. doi:10.18203/2394-6040.ijcmph20211767\u003c/li\u003e\n\u003cli\u003eRamanadhan S, Xuan Z, Choi J, et al. Associations between sociodemographic factors and receiving \u0026quot;ask and advise\u0026quot; services from healthcare providers in India: analysis of the national GATS-2 dataset. BMC Public Health. 2022; 22:14538. doi:10.1186/s12889-022-14538-2\u003c/li\u003e\n\u003cli\u003eSinha DN, Sahoo N, Palipudi KM, et al. Secondhand Tobacco Smoke Exposure among Adults in an Urban Community of Hyderabad, India: A Cross-Sectional Study. Indian J Community Med. 2025;50(1):10-17. doi: 10.4103/ijcm.ijcm_10_25.1\u003c/li\u003e\n\u003cli\u003eNational Institute on Drug Abuse. Secondhand smoke may increase vulnerability to nicotine addiction. ScienceDaily. May 3, 2011. Accessed June 3,2025\u003c/li\u003e\n\u003cli\u003eWinickoff JP, Friebely J, Tanski SE, et al. Reducing secondhand smoke exposure among children and adolescents: emerging issues for intervening with medically at-risk youth. Pediatrics. 2008;121(4): e682-e692. doi:10.1542/peds.2007-2327.\u003c/li\u003e\n\u003cli\u003eOkoli CTC, Seng S. Associations Between Secondhand Tobacco Smoke Exposure and Nicotine Dependence and Smoking Cessation Attempts Among Adult Tobacco Users with a Psychiatric Disorder. Biol Res Nurs. 2018;20(5):558-565. doi: 10.1177/1099800418781914.\u003c/li\u003e\n\u003cli\u003eLee S, Kim J, Kim H, et al. Global association of secondhand smoke exposure locations and smoking behavi\u003cins cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003eo\u003c/ins\u003e\u003cdel cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003eou\u003c/del\u003er among adolescents in 99 countries. Acta Paediatr. 2024;113(9):1792-1802. doi:10.1111/apa.17030\u003c/li\u003e\n\u003cli\u003eSinha DN, Palipudi KM, Gupta PC, et al. Changes in Prevalence of Childhood Exposure to Secondhand Smoke in India: A Secondary Analysis of GATS Survey (2009-2017). Asian Pac J Cancer Prev. 2021;22(5):1459-1466. doi:10.31557/APJCP.2021.22.5.1459\u003c/li\u003e\n\u003cli\u003eBhojani U, Soors W. Tobacco control in India: A case for the health-in-All Policy approach. Natl Med J India. 2015;28(2):86-9.\u003c/li\u003e\n\u003cli\u003eFrancis, D. L., Reddy, S. S. P., Logaranjani, A., Thankappan, P., \u0026amp; Manohar, B., et al. Are We Adequately Dissuading Youth Initiation and Increasing Quit Lines with Appropriate Warning Labels in India? J Oral Dent Health. 2023; 7(4): 242-245.\u003c/li\u003e\n\u003cli\u003eMcCarthy M, Siahpush M, Shaikh RA, Sikora Kessler A, Tibbits M. Social Disparities in Unaided Quit Attempts Among Daily Current and Former Smokers: Results From the 2010-2011 Tobacco Use Supplement to the Current Population Survey. Nicotine Tob Res. 2016;18(8):1705-10. doi: 10.1093/ntr/ntw007.\u003c/li\u003e\n\u003cli\u003eJohn RM, Dauchy EP. Healthcare Costs Attributable to Secondhand Smoke Exposure Among Indian Adults. Nicotine Tob Res. 2022; 24(9):1478-1486. doi: 10.1093/ntr/ntac048.\u003c/li\u003e\n\u003cli\u003eNair V, Mallya SD, Pandey AK, Singh PK, Yadav A, Kulkarni MM. Determinants of quit attempts among current Indian tobacco users: Findings from Global Adult Tobacco Survey, 2016-17. Clin Epidemiol Glob Health. 2023; 23:101366. doi: 10.1016/j.cegh.2023.101366\u003c/li\u003e\n\u003cli\u003ePossenti I, Gallus S, Lugo A, L\u0026oacute;pez AM, Carreras G, Fern\u0026aacute;ndez-Megina R, Gonz\u0026aacute;lez-Marr\u0026oacute;n A, Gorini G, Koprivnikar H, Papachristou E, Lambrou A, Schoretsaniti S, P\u0026eacute;nzes M, Carnicer-Pont D, Fernandez E. Best practices for secondhand smoke and secondhand aerosol protection and evidence supporting the expansion of smoke- and aerosol-free environments: Recommendations from the 2nd Joint Action on Tobacco Control. Tob Prev Cessat. 2024;10. doi: 10.18332/tpc/193147.\u003c/li\u003e\n\u003cli\u003eChandramouli C, General R. Census of India 2011. Provisional Population Totals New Delhi, Government of India, 2011: 409\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eAnand, V., S, V., G, S., \u0026amp; S, G. (2019). Current status of tobacco in India: a preventable cause of death. University Journal of Medicine and Medical Specialities, 5(1).\u003c/li\u003e\n\u003cli\u003eIslam, Md. M. Comparison between Smokers and Smokeless Tobacco Users in Their Past Attempts and Intentions to Quit: Analysis of Two Rounds of a National Survey. International Journal of Environmental Research and Public Health. 2022; 19(20): 13662.\u003c/li\u003e\n\u003cli\u003eTripathy JP. Secondhand smoke exposure at home and public places among smokers and \u003cins cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003enon\u003c/ins\u003e\u003cdel cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003enon-\u003c/del\u003esmokers in India: findings from the Global Adult Tobacco Survey 2016-17. Environ Sci Pollut Res Int. 2020;27(6):6033-6041. doi: 10.1007/s11356-019-07341-x.\u003c/li\u003e\n\u003cli\u003eArgalasova Sobotova L. Secondhand smoke and its unfavorable associations in vulnerable population groups. Ann Nurs. 2023;1(4). doi: 10.58424/annnurs.en3.8zp.se7\u003c/li\u003e\n\u003cli\u003eBrody AL. Functional brain imaging of tobacco uses and dependence. J Psychiatr Res. 2006;40(5):404-18. doi: 10.1016/j.jpsychires.2005.04.012.\u003c/li\u003e\n\u003cli\u003eKibria MG, Islam T, Badiuzzaman M, Al Mamun A, Sultana P, Hawlader MDH. Assessing the choice of smoke-free policies for multiunit housing and its associated determinants in Bangladesh: a cross-sectional study. BMJ Open. 2024;14(4): e074928. doi:10.1136/bmjopen-2023-074928\u003c/li\u003e\n\u003cli\u003eTripathy JP. Secondhand Smoke Exposure among Children in Indian Homes: Findings from the Global Adult Tobacco Survey. Behav Med. 2024;50(1):75-81. doi: 10.1080/08964289.2022.2105795.\u003c/li\u003e\n\u003cli\u003eSingh PK, Sinha P, Singh N, Singh L, Singh S. Does secondhand smoke exposure increase the risk of acute respiratory infections among children aged 0-59 months in households that use clean cooking fuel? A cross-sectional study based on 601 509 households in India. Indoor Air. 2022;32(1): e12980. doi: 10.1111/ina.12980\u003c/li\u003e\n\u003cli\u003eFichtenberg CM, Glantz SA. Effect of smoke-free workplaces on smoking behavi\u003cins cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003eo\u003c/ins\u003e\u003cdel cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003eou\u003c/del\u003er: systematic review. BMJ. 2002;325(7357):188. doi: 10.1136/bmj.325.7357.188.\u003c/li\u003e\n\u003cli\u003eSchneider S, Lunau T, Eikemo TA, Kotz D, Bambra C, Kuntz B, Dragano N. Better air but not for all? Changes in second-hand smoke exposure at workplaces in 29 European countries over 10 years. Eur J Public Health. 2021;31(4):708-714. doi: 10.1093/eurpub/ckab035.\u003c/li\u003e\n\u003cli\u003eGarritsen HH, Khan F, Rozema AD, Navas-Acien A, Hern\u0026aacute;ndez D. Associations of smoke-free policies in mult\u003cins cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003ei\u003c/ins\u003e\u003cdel cite=\"mailto:Rubriq\" datetime=\"2025-07-08T09:10\"\u003ei-\u003c/del\u003eunit housing with smoking behavior and second-hand smoke exposure: A systematic review. Addiction. 2025;120(4):578-588. doi: 10.1111/add.16724.\u003c/li\u003e\n\u003cli\u003eOwusu D, Wang KS, Quinn M, Aibangbee J, John RM, Mamudu HM. Health Care Provider Intervention and Utilization of Cessation Assistance in 12 Low- and Middle-Income Countries. Nicotine Tob Res. 2019;21(2):188-196. doi: 10.1093/ntr/nty028\u003c/li\u003e\n\u003cli\u003eBushi G, Khatib MN, Balaraman AK, Ballal S, Bansal P, et al. Prevalence of dual use of combustible tobacco and E-cigarettes among pregnant smokers: a systematic review and meta-analysis. BMC Public Health. 2024; 24:20746. doi:10.1186/s12889-024-20746-9\u003c/li\u003e\n\u003cli\u003eChopra M, Gupta A, Sharma B, Kakade N, Arora M. Assessing second-hand smoke exposure among nonsmoking youth in India: Insights from GATS I \u0026amp; II. Indian J Med Res. 2024;160(6):578-591. doi: 10.25259/IJMR_388_2024.\u003c/li\u003e\n\u003cli\u003eFrancis DL, Reddy SSP, Rathi M, Chopra SS. From periodontal inflammation to oral cancer: the impact of smokeless tobacco. Lancet Reg Health Southeast Asia. 2025; 36:100574.\u003c/li\u003e\n\u003cli\u003eDurazo A, Hartman-Filson M, Perez K, Alizaga NM, Petersen AB, Vijayaraghavan M. Smoke-Free Home Intervention in Permanent Supportive Housing: A Multifaceted Intervention Pilot. Nicotine Tob Res. 2021;23(1):63-70. doi: 10.1093/ntr/ntaa043.\u003c/li\u003e\n\u003cli\u003ePipe AL, Evans W, Papadakis S. Smoking cessation: health system challenges and opportunities. Tob Control. 2022;31(2):340-347. doi: 10.1136/tobaccocontrol-2021-056575.\u003c/li\u003e\n\u003cli\u003eSingh RJ, Lal PG. Second-hand smoke: a neglected public health challenge. Indian J Public Health. 2011;55(3):192-8. doi: 10.4103/0019-557X.89950.\u003c/li\u003e\n\u003cli\u003eSiddiqui AA, Abideen MZU, Abdullah M, Sheriyar FH, Hussain W, et al. Investigating oral cancer awareness in outpatient settings: a hospital-based study. Bangladesh Journal of Medical Science. 2025;24(2). doi:10.3329/bjms. v24i2.81712\u003c/li\u003e\n\u003cli\u003eWang YT, Hu KR, Zhao J, Ai FL, Shi YL, Wang XW, Yang WY, Wang JX, Ai LM, Wan X. The Association between Exposure to Second-Hand Smoke and Disease in the Chinese Population: A Systematic Review and Meta-Analysis. Biomed Environ Sci. 2023;36(1):24-37. doi: 10.3967/bes2023.003.\u003c/li\u003e\n\u003cli\u003eZeng X, Xiao L, Liu S. Exposure to tobacco advertisements or promotions and smoking susceptibility among adolescents in China from 2013-14 to 2021: findings from the China National Youth Tobacco Survey. BMC Public Health. 2025;25(1):37. doi: 10.1186/s12889-024-21188-z.\u003c/li\u003e\n\u003cli\u003eNogueira SO, Fern\u0026aacute;ndez E, Driezen P, Fu M, Tigova O, Castellano Y, Mons U, Herbeć A, Kyriakos CN, Demj\u0026eacute;n T, Trofor AC, Przewoźniak K, Katsaounou PA, Vardavas CI, Fong GT; EUREST-PLUS Consortium. Secondhand Smoke Exposure in European Countries with Different Smoke-Free Legislation: Findings From the EUREST-PLUS ITC Europe Surveys. Nicotine Tob Res. 2022 ;24(1):85-92. doi: 10.1093/ntr/ntab 157.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Tobacco cessation, Secondhand smoking, Quit attempts, Survey, GATS, Public health","lastPublishedDoi":"10.21203/rs.3.rs-7275925/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7275925/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Secondhand smoke (SHS) exposure remains a pervasive public health challenge in India and contributes to tobacco-related morbidity and mortality. Despite progress in tobacco control, quit rates among Indian adults remain low, and the impact of SHS exposure on cessation outcomes is not well understood. This study aimed to examine the associationsbetween SHS exposure and tobacco cessation outcomes among Indian adults using nationally representative data from the Global Adult Tobacco Survey (GATS) India 2016–17.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional secondary analysis was conducted including adults aged 15 years and older who were current or past tobacco users. SHS exposure was assessed across three domains: home, workplace, and public places. The primary outcomes were self-reported quit attempts in the past 12 months and successful cessation. Multilevel logistic regression models accounted for the hierarchical data structure adjusting for sociodemographic and behavioral confounders. Model fit was evaluated via theAkaike information criterion and likelihood ratio tests. Subgroup and interaction analyses were performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong 74,037 respondents, the prevalence of current tobacco use was 28.6%. SHS exposure was reported by 38.7% of the participants at home and 30.2% at the workplace. After adjustment, SHS exposure at home was independently associated with reduced odds of quit attempts (AOR = 0.72, 95% CI: 0.65–0.80) and successful cessation (AOR = 0.65, 95% CI: 0.56–0.76). Negative associations were observed for SHS exposure at workplaces and public places.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: SHS exposure significantly impedes both quittingattempts and successful tobacco cessation among Indian adults.\u003c/p\u003e","manuscriptTitle":"Second-hand smoke exposure as an independent determinant of quit attempts and successful tobacco cessation: A multilevel analysis of the GATS (2016–17), India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 06:29:07","doi":"10.21203/rs.3.rs-7275925/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-01-28T01:29:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"305499384064751371781383987101679801989","date":"2026-01-17T22:37:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49166464636229967442177377778302637464","date":"2026-01-16T04:09:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T23:51:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145039772192347424700277315414571478393","date":"2025-11-10T18:23:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87936395368029950249361064671417558594","date":"2025-11-10T05:00:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237989363839591266735908054955675862376","date":"2025-11-05T04:40:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115052597876851196911588399288403492497","date":"2025-08-19T03:41:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-18T04:30:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-06T11:54:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-06T07:19:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-05T16:35:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-08-05T13:33:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98a4eab6-c4e6-4bfb-98cb-3d308096048d","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-27T06:29:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-27 06:29:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7275925","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7275925","identity":"rs-7275925","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}