ImportanceResearch demonstrates that policies aimed at retailers who sell to minors must be strongly enforced to have an impact on youth usage rates.ObjectivesIn the USA, the Food and Drug Administration (FDA) conducts compliance checks, issues fines, and can order retailers to stop selling tobacco products (ie, no-tobacco-sale orders (NTSOs)) to enforce the Family Smoking Prevention and Tobacco Control Act. We sought to assess FDA’s utilisation of NTSOs.MethodsWe conducted a quantitative content analysis of FDA’s enforcement actions for inspections decided between 1 October 2015 and 29 March 2019. From the 536 134 inspection records we identified 148 NTSOs and 249 720 unique retailer locations, of which 2095 had three or more violations. We randomly sampled NTSOs (n=76) and retail locations (n=152) with frequent violations. We calculated the proportion of NTSOs that could have been issued earlier by FDA. We then calculated the proportion of retailers that could have been issued an NTSO, and the proportion actually issued an NTSO using FDA’s approach and a more stringent approach.ResultsAmong NTSOs, 94.7% (95% CI: 89.8% to 97.4%) of NTSOs could have been issued earlier under a more stringent approach. On average, when an NTSO could have been issued earlier, it could have been issued 453 days earlier (95% CI: 418 to 489; range: 89–1159). Among frequently violating retail locations, 73.6% (95% CI: 66.0% to 80.0%) were eligible for an NTSO. Of those, 1.9% (95% CI: 0.5% to 7.0%) had received an NTSO.ConclusionsThe FDA’s failure to fully leverage its powers to address retailers’ underage sales of tobacco products has weakened efforts to curb the youth e-cigarette epidemic.

Implementing tobacco-free policies on university campuses has become increasingly common. However, promoting policy compliance remains a challenge. It is important to develop strategies that can overcome barriers to successful policy implementation and promote compliance. This Practice Note presents a case study of a practical strategy for addressing poor implementation of a newly adopted tobacco-free policy. Following principles of advocacy research, a team of student researchers and a faculty advisor developed a protocol to identify tobacco-related signage and environmental cues for tobacco use (e.g., cigarette-butt receptacles, designated smoking areas) on campus. Ten months after a tobacco-free campus policy went into effect, we identified 153 signs and 65 environmental cues. Of these, only two signs accurately described the current policy. Mapping signage and cues to use tobacco on campus can be an important advocacy tool to improve the implementation of tobacco-free campus policies. Increased adherence to new policies can be achieved through advocacy and outreach to university administrators.

Statement of Significance: This study aimed to assess geographic trends in COVID-19 cases and deaths across North Carolina (NC). Our study found that population-adjusted COVID-19 cases and deaths were lower in the coastal region of NC during the study period, independent of demographic composition and population-density within the region. This represents an interesting finding regarding COVID-19 transmission that deserves further investigation. One possible explanation for this finding is differing environmental conditions between the inland and coastal region. Background: Existing literature has explored the geographic and spatial variations in COVID-19 prevalence. Some studies suggest that the transmission and total prevalence of COVID-19 is diminished in areas with low levels of air pollution, high humidity, and more sunlight. The coastal regions of NC are more likely to have these environmental characteristics than the inland regions. Given these trends, we analyzed and compared population-adjusted COVID-19 case and death counts in the coastal and inland regions of NC. Methods: Time series data displaying the prevalence of population adjusted COVID-19 case and death counts from 15 March 2020 to 15 August 2020 were plotted for a variety of North Carolina regional and population density classifications. A local regression analysis was computed to further assess the observed relationships. Basic demographic characteristics were also compared for the coastal versus inland region. Results: There were fewer population-adjusted COVID-19 cases and deaths in the coastal region (889 cases/100,000; 12.5 deaths/100,000) than in the inland region (1426 cases/100,000; 23.5 deaths/100,000) at the endpoint of this study. This trend is observed even when controlling for population density, and in the absence of significant demographic differences between the two regions. Conclusions: The prevalence of population-adjusted COVID-19 cases and deaths was lower in coastal versus inland NC during this study period. Given that the NC coastal region is associated with lower pollution, higher humidity, and more exposure to sunlight, our findings suggest that more research should be done to explore the correlation between environmental variables and the spread of COVID-19.