Association of Cannabis Use With Cardiovascular Outcomes Among US Adults.

BACKGROUND: We examined the association between cannabis use and cardiovascular outcomes among the general population, among never-tobacco smokers, and among younger individuals. METHODS AND RESULTS: This is a population-based, cross-sectional study of 2016 to 2020 data from the Behavioral Risk Factor Surveillance Survey from 27 American states and 2 territories. We assessed the association of cannabis use (number of days of cannabis use in the past 30 days) with self-reported cardiovascular outcomes (coronary heart disease, myocardial infarction, stroke, and a composite measure of all 3) in multivariable regression models, adjusting for tobacco use and other characteristics in adults 18 to 74 years old. We repeated this analysis among nontobacco smokers, and among men <55 years old and women <65 years old who are at risk of premature cardiovascular disease. Among the 434 104 respondents, the prevalence of daily and nondaily cannabis use was 4% and 7.1%, respectively. The adjusted odds ratio (aOR) for the association of daily cannabis use and coronary heart disease, myocardial infarction, stroke, and the composite outcome (coronary heart disease, myocardial infarction, and stroke) was 1.16 (95% CI, 0.98-1.38), 1.25 (95% CI, 1.07-1.46), 1.42 (95% CI, 1.20-1.68), and 1.28 (95% CI, 1.13-1.44), respectively, with proportionally lower log odds for days of use between 0 and 30 days per month. Among never-tobacco smokers, daily cannabis use was also associated with myocardial infarction (aOR, 1.49 [95% CI, 1.03-2.15]), stroke (aOR, 2.16 [95% CI, 1.43-3.25]), and the composite of coronary heart disease, myocardial infarction, and stroke (aOR, 1.77 [95% CI, 1.31-2.40]). Relationships between cannabis use and cardiovascular outcomes were similar for men <55 years old and women <65 years old. CONCLUSIONS: Cannabis use is associated with adverse cardiovascular outcomes, with heavier use (more days per month) associated with higher odds of adverse outcomes.

Categorizing Vaping Intensity among Youth.

INTRODUCTION: Increasing electronic cigarette use among youth has led to a need for a novel intensity measure of e-cigarette use and its association with nicotine addiction variables. METHODS: Using a cross sectional study of the 2018-2019 PATH Wave 5 Youth survey, a new intensity metric of e-cigarette use, the average number of puffs per month as a function of frequency (days of use per month), number of uses per day and number of puffs per use, was developed for adolescent e-cigarette users. Using logistic regression, standard addiction measures were tested for association with higher quartile (Q) of e-cigarette intensity: Q1 (1-5 puffs), Q2 (6-50 puffs), Q3 (51-528 puffs), and Q4 (529+ puffs). RESULTS: Among 1,051 current youth e-cigarette users, cravings were associated with greater intensity of use (Q2: aOR= 1.90, 95% CI: 0.94-3.87; Q3: aOR = 6.91, 95% CI: 3.25-14.69; Q4: aOR =21.48, 95% CI 10.03-45.97). Craving associations exceeded the corresponding aORs for the identical regression using frequency of use. Higher intensity was significantly associated with being an older adolescent (aOR=1.85), best friend use (aOR: 3.35), not thinking about quitting (aOR: 2.51), and lower perceived addiction (aOR: 1.95). CONCLUSIONS: This study found that an intensity metric (puffs per month) was strongly associated with cravings, best friend use, harm perception, and lack of intention to quit. This metric provides a more accurate picture of the intensity of youth e-cigarette use than other commonly used measures and may be important for understanding the current and future impact of the youth e-cigarette epidemic. IMPLICATIONS: Adolescent addiction to e-cigarettes affects learning, memory, and attention. However, it is unknown whether intensity of use, puffs per month, differs from frequency, days of use per month, in relation to addiction measures. This study provides evidence that high intensity use characterized by puffs per month has a stronger association to cravings compared to frequency, which suggests puffs per month may be a better measure of nicotine exposure. This new intensity metric may give insights into youth e-cigarette use patterns, addiction, and appropriate treatment of intense but intermittent users.

Sociodemographic Characteristics Associated With and Prevalence and Frequency of Cannabis Use Among Adults in the US.

Importance: Cannabis use has increased, but there are few studies on frequent and daily cannabis use among US adults. Individuals who engage in higher frequency use may suffer more health consequences. Objective: To examine frequency of cannabis use and associated factors among US adults. Design, Setting, and Participants: This survey study included data from 21 US states and 2 US territories reported in the Behavioral Risk Factor Surveillance System surveys from 2016 to 2019. Cross-sectional data on US adults ages 18 years and older were used to estimate demographic, socioeconomic, and behavioral risk factors for cannabis use, taking into account the survey strata and sampling weights for the 4 years of combined data. Using a multivariable ordinal logistic analysis, the association of demographic, socioeconomic status, and behavioral risk factors with past month cannabis frequency were examined. Exposures: Sociodemographic characteristic, ie, age, gender, race and ethnicity, educational attainment, employment status, and annual household income. Main Outcomes and Measures: Ordinal categorization of number of days of cannabis use in the past 30 days in terms of nonuse, infrequent use (1-5 days), frequent use (6-29 days), and daily use. Results: Among the 387 179 respondents, 58 009 (27.9%) were ages 18 to 34 years, 186 923 (50.3%) were ages 35 to 64 years, and 142 225 (21.8%) were age 65 years or older (mean [SD] age, 48.3 [0.1] years). The sample included 28 345 (9.8%) Black, 36 697 (22.6%) Hispanic, and 292 210 (57.3%) White respondents. Smoking was the most common form of cannabis use. The frequency of cannabis use varied significantly by age, gender, race, marital status, education, and employment. Higher frequency cannabis use was associated with younger age (ages 18-34 years: adjusted odds ratio [aOR],4.12; 95% CI, 3.63-4.68; ages 35-64 years: aOR,2.22; 95% CI, 1.98-2.49), Black (aOR, 1.46; 95% CI, 1.33-1.71) and Native American (aOR, 1.25; 95% CI, 1.04-1.52) race, and less educational attainment (high school or less: aOR,1.09; 95% CI, 1.02-1.17; some college: aOR,1.27; 95% CI, 1.19-1.35). Being married (aOR, 0.54; 95% CI, 0.51-0.58) or identifying as Asian (aOR, 0.60; 95% CI, 0.51-0.71) or Hispanic (aOR, 0.71; 95% CI, 0.65-0.77) was associated with lower-frequency cannabis use after accounting for other baseline factors. Conclusions and Relevance: This nationally based study found that higher-frequency cannabis use is more common among young and racial minority populations, as well as respondents with low socioeconomic status. Given the known and emerging negative health effects of cannabis use, more attention may need to be paid to high-frequency use among underserved populations in the form of screening, risk stratification, and treatment.

Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS.

Purpose To compare three metrics of breast density on full-field digital mammographic (FFDM) images as predictors of future breast cancer risk. Materials and Methods This institutional review board-approved study included 125 women with invasive breast cancer and 274 age- and race-matched control subjects who underwent screening FFDM during 2004-2013 and provided informed consent. The percentage of density and dense area were assessed semiautomatically with software (Cumulus 4.0; University of Toronto, Toronto, Canada), and volumetric percentage of density and dense volume were assessed automatically with software (Volpara; Volpara Solutions, Wellington, New Zealand). Clinical Breast Imaging Reporting and Data System (BI-RADS) classifications of breast density were extracted from mammography reports. Odds ratios and 95% confidence intervals (CIs) were estimated by using conditional logistic regression stratified according to age and race and adjusted for body mass index, parity, and menopausal status, and the area under the receiver operating characteristic curve (AUC) was computed. Results The adjusted odds ratios and 95% CIs for each standard deviation increment of the percentage of density, dense area, volumetric percentage of density, and dense volume were 1.61 (95% CI: 1.19, 2.19), 1.49 (95% CI: 1.15, 1.92), 1.54 (95% CI: 1.12, 2.10), and 1.41 (95% CI: 1.11, 1.80), respectively. Odds ratios for women with extremely dense breasts compared with those with scattered areas of fibroglandular density were 2.06 (95% CI: 0.85, 4.97) and 2.05 (95% CI: 0.90, 4.64) for BI-RADS and Volpara density classifications, respectively. Clinical BI-RADS was more accurate (AUC, 0.68; 95% CI: 0.63, 0.74) than Volpara (AUC, 0.64; 95% CI: 0.58, 0.70) and continuous measures of percentage of density (AUC, 0.66; 95% CI: 0.60, 0.72), dense area (AUC, 0.66; 95% CI: 0.60, 0.72), volumetric percentage of density (AUC, 0.64; 95% CI: 0.58, 0.70), and density volume (AUC, 0.65; 95% CI: 0.59, 0.71), although the AUC differences were not statistically significant. Conclusion Mammographic density on FFDM images was positively associated with breast cancer risk by using the computer assisted methods and BI-RADS. BI-RADS classification was as accurate as computer-assisted methods for discrimination of patients from control subjects. © RSNA, 2016.