MONITORING TOBACCO PRODUCT USE IN THE U.S.
Explore trends in tobacco product sales and use in the United States using our interactive data visualization tools. The tools feature retail sales data for e-cigarettes and related products, rigorously reviewed at the national and state levels. This website also presents survey results on e-cigarette use and our latest published research on tobacco product sales and use.
E-Cigarette Sales by State
To view detailed sales data graphs and relevant policy information for individual states, click on each state’s shape on the map or select the state’s name from the list below. States included in our data briefs are shaded green and included states are shaded gold if they have passed a comprehensive statewide flavor restriction or a statewide flavored e-cigarette restriction.
National Trends – Key Findings
Articles & Publications
| Read our project publications below to learn more about nicotine and tobacco product trends in the United States. |
E-Cigarette Directory Laws, Sales, and Product Availability From 3 Early-Adopting US States
- This is the first study to rigorously evaluate the impact of directory laws on e-cigarette sales and product availability.
- Directory laws did not result in sustained declines in sales of unauthorized flavored e-cigarettes in Alabama, Oklahoma or Louisiana.
- Evidence-based tobacco control strategies remain critical to achieve sustained reductions in e-cigarette sales; directory laws may divert resources from these strategies
Sales of Unauthorized E-Cigarettes in the United States, December 2025
- Nearly 70% of e-cigarette products sold in brick-and-mortar stores are not authorized by the FDA.
- Disposable e-cigarettes in flavors that appeal to youth comprise the majority of the unauthorized sales in brick-and-mortar stores.
- More complete data on authorized products and on sales in untracked channels, such as vape shops, could better inform monitoring and enforcement efforts.
Automatic detection of e-cigarette screens using object detection and vision language models
- This study used a vision-language model (VLM), a type of AI, to analyze e-cigarette images from an open-source dataset and augmented them with images obtained from five online sites selling e-cigarettes.
- An AI-based object detection model was trained on approximately 7,000 images of e-cigarette devices and tested on 3,920 additional images to ensure accuracy.
- In total, 2,401 images were predicted by the object detection model to contain an e-cigarette and the VLM was able to analyze the text descriptions of e-cigarette devices to determine if screens were present with 90% accuracy.
- This study provides a scalable and efficient framework for monitoring emerging features in the online e-cigarette market, including those that appeal to youth.
Our Partners
| Funded with support from Bloomberg Philanthropies. Current partners include the CDC Foundation, Campaign for Tobacco-Free Kids, Truth Initiative, and Economics for Health at the Johns Hopkins Bloomberg School of Public Health. Past partners include the CDC Office on Smoking and Health. |