Despite the significant success of India’s COVID-19 vaccination program, a sizeable proportion of the adult population remains unvaccinated or has received a single dose of the vaccine. Despite the recommendations of the Government of India for the two doses of the COVID-19 vaccine and the precautionary booster dose, many people were still hesitant towards the COVID-19 full vaccination. Hence, this study aimed to identify the primary behavioral and psychological factors contributing to vaccine hesitancy. Cross-sectional data was collected via a multi-stage sampling design by using a scheduled sample survey in the Gorakhpur district of Uttar Pradesh, India, between 15 July 2022 to 30 September 2022. This study has utilized three health behavior models—theHealth Belief Model (HBM), theTheory of Planned Behavior (TPB), and the5C Psychological Antecedentsof vaccination, and employed bivariate and multivariable binary logistic regression model to assess the level of vaccine hesitancy and predictive health behavior of the respondents. Results indicate that among the constructs of the HBM and 5C Antecedents models, "perceived benefits", "confidence" and "collective responsibility" showed a lesser likelihood of COVID-19 vaccine hesitancy. However, in the TPB model constructs, a ‘negative attitude towards the vaccine’ showed a four times higher likelihood of COVID-19 vaccine hesitancy. From the future policy perspective, this study suggested that addressing the issue of ‘negative attitudes towards the vaccine’ and increasing the trust or confidence for the vaccine through increasing awareness about the benefits of the vaccination in India may reduce vaccine hesitancy.

The purpose of this data article is to describe the data and provide the methodological notes on the construction of availability, accessibility, and overall Water, Sanitation and Hygiene (WASH) performance index using a set of thirteen indicators for six metro cities in India. It also presents the details on survey design and the nature of data collected on WASH indicators in India Human Development Survey for 2004-05 (IHDS-I) and 2011-12 (IHDS-II). The principal component analysis (PCA) procedure was used in the construction of the WASH indices. The IHDS is the only survey that provides comprehensive data on WASH indicators for six metro cities in India (Delhi, Mumbai, Kolkata, Chennai, Hyderabad, & Bangalore). The IHDS has been jointly conducted by researchers from the National Council of Applied Economic Research (NCAER), New Delhi and the University of Maryland, the United States of America (USA). The database is hosted in the public repository at the Inter-University Consortium for Political and Social Research (ICPSR) and the reference number for IHDS-I and IHDS-II are ICPSR 22626 and ICPSR 36151 respectively. The data are publicly available through ICPSR. Interpretation of the present data can be found in the research article titled "Availability, accessibility, and inequalities of water, sanitation, and hygiene (WASH) services in Indian metro cities" (Saroj et al., 2019) [9].

Background: India ranks second globally in tobacco consumption, with marked disparities across socially stratified caste groups. Despite tobacco control efforts, Scheduled Tribes (ST) and Scheduled Castes (SC)—historically marginalized communities—exhibit elevated tobacco use. This study examines caste-based disparities in smoked and smokeless tobacco (SLT) use and identifies factors contributing to these inequalities. Methods: We analyzed nationally representative data from the Global Adult Tobacco Survey (GATS) 2016−17, comprising 74,037 adults aged ≥15 years. Social groups were classified as ST, SC, Other Backward Classes (OBC), and General categories. We estimated prevalence rates, used multivariable logistic regression to assess associations with socio-demographic factors, and employed multivariate decomposition analysis to quantify contributors to inter-group disparities. Results: Overall tobacco use prevalence was 28.6%, with substantial variation: ST (36.0%), SC (28.9%), OBC (29.1%), and General (23.1%). SLT use was particularly high among ST (27.7%) and SC (20.7%) compared to General (16.0%). Men had 16-fold higher odds of SLT use (AOR: 16.4; 95%CI:15.2-17.7) and 23-fold higher odds of smoking [Adjusted Odds Ratio (AOR): 23.1; 95%CI:20.8-25.6] compared to women, with similar patterns within each social group. Lower education, older age, disrupted marriage, rural residence, and poor wealth status were independently associated with higher tobacco use. Decomposition analyses revealed that sex (38%), education (24%), and region (18%) explained most between-group differences, with substantial tobacco use concentrated in Eastern, Central, and Northeastern states. Conclusions: Pronounced caste-based tobacco use disparities persist in India, disproportionately affecting socioeconomically disadvantaged ST and SC populations, particularly older, less-educated in rural areas. Achieving Sustainable Development Goal 3.a requires targeted interventions addressing these structural inequalities through culturally appropriate cessation programs, enhanced health education, and region-specific tobacco control policies.

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 = 7784, 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.