Association between Smoking Cannabis and Quitting Cigarettes in a Large American Cancer Society Cohort.

BACKGROUND: Cannabis use is increasing, including among smokers, an at-risk population for cancer. Research is equivocal on whether using cannabis inhibits quitting cigarettes. The current longitudinal study investigated associations between smoking cannabis and subsequently quitting cigarettes. METHODS: Participants were 4,535 adult cigarette smokers from a cohort enrolled in the American Cancer Society's Cancer Prevention Study-3 in 2009-2013. Cigarette quitting was assessed on a follow-up survey in 2015-2017, an average of 3.1 years later. Rates of quitting cigarettes at follow-up were examined by retrospectively assessed baseline cannabis smoking status (never, former, recent), and by frequency of cannabis smoking among recent cannabis smokers (low: ≤3 days/month; medium: 4-19 days/month; high: ≥20 days/month). Logistic regression models adjusted for sociodemographic factors, smoking- and health-related behaviors, and time between baseline and follow-up. RESULTS: Adjusted cigarette quitting rates at follow-up did not differ significantly by baseline cannabis smoking status [never 36.2%, 95% confidence interval (CI), 34.5-37.8; former 34.1%, CI, 31.4-37.0; recent 33.6%, CI, 30.1-37.3], nor by frequency of cannabis smoking (low 31.4%, CI, 25.6-37.3; moderate 36.7%, CI, 30.7-42.3; high 34.4%, CI, 28.3-40.2) among recent baseline cannabis smokers. In cross-sectional analyses conducted at follow-up, the proportion of cigarette smokers intending to quit smoking cigarettes in the next 30 days did not differ by cannabis smoking status (P = 0.83). CONCLUSIONS: Results do not support the hypothesis that cannabis smoking inhibits quitting cigarette smoking among adults. IMPACT: Future longitudinal research should include follow-ups of >1 year, and assess effects of intensity/frequency of cannabis use and motivation to quit on smoking cessation.

Cancer-related problems, sleep quality, and sleep disturbance among long-term cancer survivors at 9-years post diagnosis.

OBJECTIVE: To estimate the prevalence of sleep difficulties in a large cohort of long-term cancer survivors (>5 years) and examine associations with four domains of cancer-related problems. METHODS: This study analyzed a nationwide sample (N = 1903) of cancer survivors (31% Breast; 20% prostate) at nine years (m = 8.9 sd = 0.6) post-diagnosis with a mean age of 64.5 years. Sleep quality and sleep disturbance were assessed by the Pittsburgh Sleep Quality Index. Multivariable logistic regression models examined associations between cancer-related problems (physical distress, emotional distress, economic distress, and fear of recurrence) and sleep difficulty (poor vs. low sleep quality and high vs. low sleep disturbance). Odds ratios (OR) and 95% confidence intervals (CI) were estimated, adjusting for medico-demographics, behavioral factors, and sleep medication use. RESULTS: In sum, 20% percent of the sample reported poor sleep quality, 51% reported high sleep disturbance and 17% reported both. Sleep medication use was reported by 28% of the total sample. All four domains of cancer-related problems were significantly associated with poor sleep quality and high sleep disturbance. Above median cancer-related physical distress had the strongest association with both poor sleep quality (OR = 3.42; 95% CI = 2.44-4.79) and high sleep disturbance (OR = 4.06; 95% CI = 3.09-5.34). CONCLUSIONS: Among nine-year cancer survivors, multiple domains of cancer-related health problems were associated with sleep difficulties. Knowledge of the relationship between cancer-related problems and sleep may aid clinicians during the evaluation and treatment of sleep problems in long-term cancer survivors. Future research should utilize prospective data to better understand the causal nature of the associations.

The Burden of Pulmonary Nontuberculous Mycobacterial Disease in the United States.

RATIONALE: State-specific case numbers and costs are critical for quantifying the burden of pulmonary nontuberculous mycobacterial disease in the United States. OBJECTIVES: To estimate and project national and state annual cases of nontuberculous mycobacterial disease and associated direct medical costs. METHODS: Available direct cost estimates of nontuberculous mycobacterial disease medical encounters were applied to nontuberculous mycobacterial disease prevalence estimates derived from Medicare beneficiary data (2003-2007). Prevalence was adjusted for International Classification of Diseases, 9th Revision, undercoding and the inclusion of persons younger than 65 years of age. U.S. Census Bureau data identified 2010 and 2014 population counts and 2012 primary insurance-type distribution. Medical costs were reported in constant 2014 dollars. Projected 2014 estimates were adjusted for population growth and assumed a previously published 8% annual growth rate of nontuberculous mycobacterial disease prevalence. MEASUREMENTS AND MAIN RESULTS: In 2010, we estimated 86,244 national cases, totaling to $815 million, of which 87% were inpatient related ($709 million) and 13% were outpatient related ($106 million). Annual state estimates varied from 48 to 12,544 cases ($503,000-$111 million), with a median of 1,208 cases ($11.5 million). Oceanic coastline states and Gulf States comprised 70% of nontuberculous mycobacterial disease cases but 60% of the U.S. population. Medical encounters among individuals aged 65 years and older ($562 million) were twofold higher than those younger than 65 years of age ($253 million). Of all costs incurred, medications comprised 76% of nontuberculous mycobacterial disease expenditures. Projected 2014 estimates resulted in 181,037 national annual cases ($1.7 billion). CONCLUSIONS: For a relatively rare disease, the financial cost of nontuberculous mycobacterial disease is substantial, particularly among older adults. Better data on disease dynamics and more recent prevalence estimates will generate more robust estimates.