BackgroundTobacco use and the associated health burden is a cause of concern in India and globally. Despite several tobacco control policies in place, their sub-optimal and variable implementation across Indian states has remained a concern. Studies evaluating the real-world implementation of policies such as Cigarettes and Other Tobacco Products (COTPA) or National Tobacco Control Program (NTCP) in India and its association with reductions in tobacco use are limited. In this paper, we analyse data from a nationally representative survey to examine how policy implementation is associated with the tobacco use prevalence in India.MethodsWe analysed data from the Global Adult Tobacco Survey (GATS 2016–17) India using multivariable logistic regression. The dependent variables were the use of smoked tobacco, smokeless tobacco, and tobacco in any form. The independent variables were proxies of implementation of the COTPA and the NTCP. We followed a step-wise backward elimination technique to reach the best fit models.ResultsPeople exposed to no-smoking signages had lower odds of using tobacco (OR = 0.70, p < 0.001). People exposed to second-hand smoke (OR = 1.51, p < 0.001) and tobacco product advertisements (OR = 1.23, p < 0.001) had greater odds of using tobacco. Exposure to tobacco advertisements was associated with higher odds of using smokeless tobacco (OR = 1.23, p < 0.001), and smoked (OR = 1.33, p < 0.001) forms of tobacco.ConclusionWe find significant association between the implementation of tobacco control laws/programs and tobacco use in India. Our findings highlight the potential that policy implementation holds in reducing population-level tobacco use thus drawing attention towards the implementation phase of policies. The findings have implications on prioritising enforcement of specific tobacco control measures such as smokefree laws, modifying COTPA signages to encompass all tobacco products including against smokeless tobacco use and strengthening indirect advertising restrictions. Future research could focus on developing and validating predictors specific to policy implementation to support policy evaluation efforts.
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