What question did this study set out to answer?

To assess how different geographic factors influence smoking and smokeless tobacco use among young men in India.

April 6, 2026Open Access

Multilevel geographic determinants of smoking and smokeless tobacco use among young men in India: evidence for targeted addiction prevention policies

Key Points

To assess how different geographic factors influence smoking and smokeless tobacco use among young men in India.
Analyzed data from 31,070 young men aged 15-24 from the National Family Health Survey (NFHS-5).
Employed four-level random intercept logistic regression models for smoked and smokeless tobacco use.
Quantified geographic variation using variance partitioning coefficients with confidence intervals.
Overall tobacco use prevalence was 22.5%, with rural areas showing higher rates.
Community-level factors accounted for 58.2% of variation in smoked tobacco use.
State-level factors dominated smokeless tobacco use (53.1% variation).

Abstract

• One in five young Indian men (22.5%) used tobacco in 2019–21. • Community-level factors dominated smoking variation. • State-level factors dominated smokeless tobacco variation. • First multilevel study quantifying relative importance of state vs. district vs. community factors for tobacco among Indian youth. Tobacco use among youth in low- and middle-income countries (LMICs), particularly India, remains a critical public health challenge. However, limited research has examined how different geographic determinants distinctly contribute to smoked and smokeless tobacco use among young men in India. This study utilized data of 31,070 young men aged 15–24 years (urban = 7,784, rural = 23,286) from the National Family Health Survey (NFHS-5, 2019–21). Four-level random intercept logistic regression models (individual, community, district, state) were employed separately for smoked tobacco, smokeless tobacco (SLT), and any tobacco use. Variance partitioning coefficients (VPC) with 95% confidence intervals quantified the proportion of variation attributable to each geographic level, adjusting for background characteristics. Sampling weights were applied for prevalence estimation. Overall prevalence was 22.5% for any tobacco, 15.2% for SLT, and 11.6% for smoked tobacco, with higher rates in rural areas (25.1%, 17.8%, 12.2% respectively). State-level variation was substantial, ranging from 1.4% (Puducherry) to 49.0% (Meghalaya) for any tobacco use. Variance partitioning revealed distinct geographic patterns: PSU-level factors dominated for smoked tobacco (VPC = 58.2%, 95% CI: 55.1–61.2%), while state-level factors predominated for SLT (VPC = 53.1%, 95% CI: 50.3–55.9%). Urban-rural differences showed stronger PSU influence in urban areas for smoking (VPC = 62.0% vs. 51.0% rural), and stronger state-level influence in rural areas for SLT (VPC = 55.4% vs. 48.2% urban). Tobacco use among young Indian men exhibits substantial multilevel geographic variation with distinct patterns for smoked versus smokeless products. Effective youth tobacco control requires coordinated multi-level strategies—community-based programs for smoking prevention and state-level policies for SLT control—rather than one-size-fits-all approaches.

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