Cancer worry and its impact on self-reported depressive symptoms among adult males and females in the US: a nationwide sample study.

OBJECTIVE: With cancer the second deadliest disease in the world, worry about cancer can have mental health or psychiatric implications. This study examines the prevalence, differences, and influence of cancer worry (CW), its interaction effect with age, and other confounders on self-reported depressive symptoms (SRDS) among adult males and females in the US. METHODS: We utilized a nationally representative sample data of 2,950 individuals (males = 1,276; females = 1,674) from Cycle 4 of the Health Information National Trends Survey 5 (HINTS 5) 2020. Using frequencies, bivariate chi-square test, and multivariate logistic regression, we examined the prevalence, difference, and association of CW with SRDS, adjusting for confounders. RESULTS: The prevalence rate of SRDS was found to be 32% among females and 23.5% among males. Among individuals with CW, females had a higher prevalence of SRDS compared to males (40.5% vs. 35.1%). However, there was a significant difference in the likelihood of experiencing SRDS between males and females with CW, with males having 84% increased risk compared to females. Across all age groups, the multivariate analysis of the relationship between CW and SRDS revealed that both males and females showed a significantly decreased likelihood of SRDS compared to those aged 18-34 years. However, males aged 35 years or older exhibited an even more pronounced decrease in likelihood compared to females in the same age group. Nonetheless, when examining the interaction of age and CW, we observed a significantly increased likelihood of SRDS across all age groups. Males, in particular, had a higher increased likelihood of SRDS compared to females across all ages, except for those aged 75 years and older. CONCLUSION: The findings of this study highlight the significant influence of CW on individuals' SRDS and the modifying effect of age, particularly among males. These results are important for a better understanding of the risk of CW on mental health, which can be a preventive strategy or control mechanism.

Projection expectile regression for sufficient dimension reduction.

Many existing sufficient dimension reduction methods are designed for regression with predictors that are elliptically distributed, which limits their application in real data analyses. Projection expectile regression (PER) is proposed as a new linear sufficient dimension reduction method for handling complex predictor structures, which includes continuous, discrete, and mixed predictor variables. PER requires the link function between the response and the predictor to be monotone, but not necessarily smooth, which makes it suitable for handling stratified response surfaces. By design, PER does not involve matrix inversion or high-dimensional smoothing. Thus, PER is ideal for controlling problems associated with multicollinearity, high dimensionality, and sparsity in the predictor. An extensive simulation study demonstrates the performance of projection expectile regression in synthetic data. A real data analysis of health insurance charges in the United States is also provided. The asymptotic properties of the PER estimator are included as well.

News events and their relationship with US vape sales: an interrupted time series analysis.

OBJECTIVE: News coverage around vaping-related events may have furthered misconceptions regarding the relative harms of vapes. Such information may influence the decisions of individuals who smoke, around switching to vaping, potentially affecting the overall tobacco mortality burden. Thus, it is prudent to study how news events (e.g., 2019 vaping illness epidemic) are associated with vape sales in the United States, to possibly reduce the tobacco mortality burden. METHODS: We used weekly retail sales data for e-cigarettes (30 December 2018 - 28 December 2019) from the US retail scanner data compiled by the Nielsen Company. We used an interrupted time series design with segmented regression analysis to determine immediate and longer-term impacts of individual news events (e.g. Trump administration's planned ban on some flavored vaping products) on vape sales, controlling for pre-existing trends. RESULTS: Unexpectedly, we noted a statistically significant positive relationship between vape sales and the CDC announcing an investigation into vaping-related illnesses (Change: 6.59%, Estimate: 0.066; 95% CI: 0.036, 0.092; P < 0.001). We also observed a similar positive association between vape sales and the CDC's announcement on the link between Vitamin E acetate and EVALI (Change: 2.93%, Estimate: 0.029; 95% CI: 0.003, 0.055; P < 0.05). There was a steep decline in sales after these events. CONCLUSIONS: News events may be associated with US vape sales. Findings have implications for the management of risk perceptions around vaping to improve health outcomes of tobacco users. Information-based policy instruments can be applied to balance the effects of news events that may influence vape sales.

Intersection of the Web-Based Vaping Narrative With COVID-19: Topic Modeling Study.

BACKGROUND: The COVID-19 outbreak was designated a global pandemic on March 11, 2020. The relationship between vaping and contracting COVID-19 is unclear, and information on the internet is conflicting. There is some scientific evidence that vaping cannabidiol (CBD), an active ingredient in cannabis that is obtained from the hemp plant, or other substances is associated with more severe manifestations of COVID-19. However, there is also inaccurate information that vaping can aid COVID-19 treatment, as well as expert opinion that CBD, possibly administered through vaping, can mitigate COVID-19 symptoms. Thus, it is necessary to study the spread of inaccurate information to better understand how to promote scientific knowledge and curb inaccurate information, which is critical to the health of vapers. Inaccurate information about vaping and COVID-19 may affect COVID-19 treatment outcomes. OBJECTIVE: Using structural topic modeling, we aimed to map temporal trends in the web-based vaping narrative (a large data set comprising web-based vaping chatter from several sources) to indicate how the narrative changed from before to during the COVID-19 pandemic. METHODS: We obtained data using a textual query that scanned a data pool of approximately 200,000 different domains (4,027,172 documents and 361,100,284 words) such as public internet forums, blogs, and social media, from August 1, 2019, to April 21, 2020. We then used structural topic modeling to understand changes in word prevalence and semantic structures within topics around vaping before and after December 31, 2019, when COVID-19 was reported to the World Health Organization. RESULTS: Broadly, the web-based vaping narrative can be organized into the following groups or archetypes: harms from vaping; Vaping Regulation; Vaping as Harm Reduction or Treatment; and Vaping Lifestyle. Three archetypes were observed prior to the emergence of COVID-19; however, four archetypes were identified post-COVID-19 (Vaping as Harm Reduction or Treatment was the additional archetype). A topic related to CBD product preference emerged after COVID-19 was first reported, which may be related to the use of CBD by vapers as a COVID-19 treatment. CONCLUSIONS: Our main finding is the emergence of a vape-administered CBD treatment narrative around COVID-19 when comparing the web-based vaping narratives before and during the COVID-19 pandemic. These results are key to understanding how vapers respond to inaccurate information about COVID-19, optimizing treatment of vapers who contract COVID-19, and possibly minimizing instances of inaccurate information. The findings have implications for the management of COVID-19 among vapers and the monitoring of web-based content pertinent to tobacco to develop targeted interventions to manage COVID-19 among vapers.