Faculty Bibliography

Objective/UNASSIGNED:To examine the association between state-level tobacco control measures and current use estimates of both e-cigarettes and cigarettes, while accounting for socio-demographic correlates. Methods/UNASSIGNED:Using the 2012-2013 and 2013-2014 National Adult Tobacco Survey (NATS), we assessed prevalence estimates of US adults' e-cigarette and cigarette current use. Four state groups were created based on the combined state-specific prevalence of both products: low cigarette/e-cigarette (n = 15), high cigarette/e-cigarette (n = 16), high cigarette/low e-cigarette (n = 11), and low cigarette/high e-cigarette) (n = 9). To evaluate the implementation of state-level tobacco control measures, Tobacco Control Index (TCI) was calculated using the State of Tobacco Control annual reports for 2012 and 2013. Multinomial logistic regression models were used to examine differences among the four groups on socio-demographic factors and TCI. Low cigarette/e-cigarette group was used as the referent group. Results/UNASSIGNED:Current use estimates of each product varied substantially by state; current e-cigarette use was highest in Oklahoma (10.3%) and lowest in Delaware (2.7%), and current cigarette use was highest in West Virginia (26.1%), and lowest in Vermont (12.6%). Compared to low cigarette/e-cigarette, all other US-state categories had significantly lower TCI scores (high cigarette/e-cigarette: adjusted Relative Risk Ratio [aRRR] = 0.61; 95% confidence interval [CI]: 0.60-0.61, high cigarette/low e-cigarette: aRRR = 0.74; 95% CI: 0.73-0.74, and low cigarette/high e-cigarette: aRRR = 0.72; 95% CI: 0.71-073). Conclusions/UNASSIGNED:Enforcing existing tobacco control measures likely interacts with e-cigarette use despite being cigarette-focused. Continuing to monitor e-cigarette use is critical to establish baseline use and evaluate future e-cigarette specific federal and state-level tobacco regulatory actions while accounting for the existing tobacco control environment. Implications/UNASSIGNED:This study investigates state-level current use estimates of e-cigarettes and cigarettes among US adults; and their association with four existing tobacco control measures. The overall score of these measures was negatively associated with state-level current use estimates such that states with low current e-cigarette and cigarette use had the highest mean overall score. This study assesses the potential relationship between existing state-level tobacco control measures and e-cigarette use and calls for improving the enforcement of the known-to-work tobacco control measures across all US states, while developing evidence-based regulations and interventions specific to e-cigarettes within the existing US tobacco use environment.

Purpose: Limited publications from Egypt have focused on prevalence of tobacco use and tobacco control policy. We used four waves of the Egypt Global Youth Tobacco Survey (GYTS) between 2001 and 2014 and a cigarette affordability measure, to evaluate the implementation of the World Health Organization"™s MPOWER recommendations. Findings: Despite Egypt"™s implementation of several MPOWER recommendations, the enforcement of laws and regulations may be limited, and therefore had little to no impact on youth current smoking prevalence through 2014. Notably, experimentation with cigarette smoking has significantly increased between waves 2001 and 2014. Summary: There is a missed opportunity for implementing evidence-based interventions for youth tobacco control in Egypt. There is a strong need for initiatives aiming at meaningful taxation, enforcement of smoking bans in public places, promoting smoke-free homes, appropriate mass media counter-advertising, and effective cessation activities.

Importance/UNASSIGNED:Prostate cancer imaging rates appear to vary by health care setting. With the recent extension of the Veterans Access, Choice, and Accountability Act, the government has provided funds for veterans to seek care outside the Veterans Health Administration (VA). It is important to understand the difference in imaging rates and subsequent differences in patterns of care in the VA vs a traditional fee-for-service setting such as Medicare. Objective/UNASSIGNED:To assess the association between prostate cancer imaging rates and a VA vs fee-for-service health care setting. Design, Setting, and Participants/UNASSIGNED:This cohort study included data for men who received a diagnosis of prostate cancer from January 1, 2004, through March 31, 2008, that were collected from the VA Central Cancer Registry, linked to administrate claims and Medicare utilization records, and the Surveillance, Epidemiology, and End Results Program database. Three distinct nationally representative cohorts were constructed (use of VA only, use of Medicare only, and dual use of VA and Medicare). Men older than 85 years at diagnosis and men without high-risk features but missing any tumor risk characteristic (prostate-specific antigen, Gleason grade, or clinical stage) were excluded. Analysis of the data was completed from March 2016 to February 2018. Exposures/UNASSIGNED:Patient utilization of different health care delivery systems. Main Outcomes and Measures/UNASSIGNED:Rates of prostate cancer imaging were analyzed by health care setting (Medicare only, VA and Medicare, and VA only) among patients with low-risk prostate cancer and patients with high-risk prostate cancer. Results/UNASSIGNED:Of 98 867 men with prostate cancer (77.4% white; mean [SD] age, 70.26 [7.48] years) in the study cohort, 57.3% were in the Medicare-only group, 14.5% in the VA and Medicare group, and 28.1% in the VA-only group. Among men with low-risk prostate cancer, the Medicare-only group had the highest rate of guideline-discordant imaging (52.5%), followed by the VA and Medicare group (50.9%) and the VA-only group (45.9%) (P < .001). Imaging rates for men with high-risk prostate cancer were not significantly different among the 3 groups. Multivariable analysis showed that individuals in the VA and Medicare group (risk ratio [RR], 0.87; 95% CI, 0.76-0.98) and VA-only group (RR, 0.79; 95% CI, 0.67-0.92) were less likely to receive guideline-discordant imaging than those in the Medicare-only group. Conclusions and Relevance/UNASSIGNED:The results of this study suggest that patients with prostate cancer who use Medicare rather than the VA for health care could experience more utilization of health care services without an improvement in the quality of care.

BACKGROUND:Smoking is the leading preventable cause of death in the United States, but evidence-based smoking cessation therapy is underutilized. Financial incentive strategies represent an innovative approach for increasing the use of counseling and pharmacotherapy. If effective, they could supplement or supplant resource-intensive policy options, particularly in populations for whom smoking has substantial societal costs. FIESTA (Financial IncEntives for Smoking TreAtment) will randomize hospitalized smokers to receive usual smoking cessation care alone or usual smoking care augmented with financial incentives. We aim to compare the impact of these two strategies on 1) smoking abstinence, 2) use of counseling and nicotine replacement therapy, and 3) quality of life of participants. We also will evaluate the short-term and long-term return on the investment of incentives. The FIESTA Oral Microbiome Substudy will compare the oral microbiome of smokers and nonsmokers to longitudinally assess whether smoking cessation changes oral microbiome composition. METHODS:We will enroll 182 inpatient participants from the Manhattan campus of the Veterans Affairs New York Harbor Healthcare System. All participants receive enhanced usual care, including screening for tobacco use, counseling while hospitalized, access to nicotine replacement therapy, and referral to a state Quitline. Patients in the financial incentive arm receive enhanced usual care and up to $550 for participating in the New York Smoker's Quitline, using nicotine replacement therapy (NRT), and achieving biochemically confirmed smoking cessation at 2 months and 6 months. In the microbiome substudy, we enroll nonsmoking control participants matched to each recruited smoker's hospital ward, sex, age, diabetes status, and antibiotic use. After discharge, participants are asked to complete periodic phone interviews at 2 weeks, 2 months, 6 months, and 12 months and provide expired carbon monoxide and saliva samples at 2 months, 6 months, and 12 months for cotinine testing and oral microbiome analysis. DISCUSSION/CONCLUSIONS:The incentive interventions of FIESTA may benefit hospitalized smokers, an objective made all the more critical because smoking rates among hospitalized patients are higher than those in the general population. Moreover, the focus of FIESTA on evidence-based therapy and bioconfirmed smoking cessation can help guide policy efforts to reduce smoking-related healthcare costs in populations with high rates of tobacco use and costly illnesses. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov, NCT02506829 . Registered on 1 July 2014.

Adults with medical multimorbidity (≥2 chronic conditions) present challenges for health care systems to provide coordinated care. Substance use can complicate the management of chronic medical conditions, but little research has focused on the intersection of medical multimorbidity and substance use. This study uses cross-sectional analysis of 115,335 adult respondents of the 2012-2014 administrations of the National Survey on Drug Use and Health to estimate the prevalence and correlates of past-year drug use among adults with multimorbidity. The prevalence of past-year drug use was compared between individuals reporting 0, 1, and ≥2 chronic medical conditions. We used multivariable logistic regression to determine correlates of past-year drug use among adults with ≥2 chronic medical conditions. 53.1% reported no chronic conditions, 29.5% reported one chronic condition, and 17.4% reported ≥2 chronic conditions. Past-year drug use was reported by 18.3% of those with no chronic conditions, 14.8% with 1 chronic condition, and 11.6% with ≥2 chronic conditions. Cannabis and opioid analgesics (nonmedical use) were the most common drugs used across all three groups. In the adjusted model, among adults with medical multimorbidity, adults with past-year drug use were more likely to be younger, male, have lower income, and report current tobacco use, alcohol dependence, past-year depression, and having received mental health treatment in the past year. In this national cohort, fewer adults with multimorbidity reported substance use compared to adults with no or one chronic condition, however, this population with high multimorbidity may be particularly vulnerable to the negative effects of drug use.

United States Veterans are at excess risk for type 2 diabetes, but population differentials in risk have not been characterized. We determined risk of type 2 diabetes in relation to prediabetes and dyslipidemic profiles in Veterans at the VA New York Harbor (VA NYHHS) during 2004-2014. Prediabetes was based on American Diabetes Association hemoglobin A1c (HbA1c) testing cut-points, one of several possible criteria used to define prediabetes. We evaluated transition to type 2 diabetes in 4,297 normoglycemic Veterans and 7,060 Veterans with prediabetes. Cox proportional hazards regression was used to relate HbA1c levels, lipid profiles, demographic, anthropometric and comorbid cardiovascular factors to incident diabetes (Hazard Ratio [HR] and 95% confidence intervals). Compared to normoglycemic Veterans (HbA1c: 5.0-5.6%; 31-38 mmol/mol), risks for diabetes were >2-fold in the moderate prediabetes risk group (HbA1c: 5.7-5.9%; 39-41 mmol/mol) (HR 2.37 [1.98-2.85]) and >5-fold in the high risk prediabetes group (HbA1c: 6.0-6.4%; 42-46 mmol/mol) (HR 5.59 [4.75-6.58]). Risks for diabetes were increased with elevated VLDL (≥40mg/dl; HR 1.31 [1.09-1.58]) and TG/HDL (≥1.5mg/dl; HR 1.34 [1.12-1.59]), and decreased with elevated HDL (≥35mg/dl; HR 0.80 [0.67-0.96]). Transition to diabetes in Veterans was related in age-stratified risk score analyses to HbA1c, VLDL, HDL and TG/HDL, BMI, hypertension and race, with 5-year risk differentials of 62% for the lowest (5-year risk, 13.5%) vs. the highest quartile (5-year risk, 21.9%) of the risk score. This investigation identified substantial differentials in risk of diabetes in Veterans, based on a readily-derived risk score suitable for risk stratification for type 2 diabetes prevention.

Introduction/UNASSIGNED:There is evidence suggesting that certain subgroups of people who use tobacco do not receive tobacco pharmacology as consistently as others. Methods/UNASSIGNED:This retrospective, cohort study examined the trend in the use of cessation pharmacotherapy from 2004 to 2013 using Veterans Health Administration (VHA) administrative data. Among Veterans who used tobacco in the fiscal year (FY) 2011 and had not received pharmacotherapy in the prior year, multivariable Cox regression was used to assess the independent associations between patient clinical and demographic characteristics and pharmacotherapy initiation in the 6-months follow-up period. Results/UNASSIGNED:Smoking cessation pharmacotherapy in the VHA increased from 13.8% in 2004 to 25.6% in 2013. In 2011, Veterans (N = 838309) who were more likely to newly receive pharmacotherapy included those with psychiatric disorders (depression, bipolar disorder, non-alcohol substance use disorder, other anxiety, and post-traumatic stress disorder), chronic pulmonary disease, peripheral vascular disorders, and younger Veterans (adjusted rate ratios (ARRs) ranged from 1.03 to 1.92, all p < .001). Veterans less likely to receive pharmacotherapy were those with schizophrenia or other psychosis, males, Hispanics, and those with a medical condition (uncomplicated diabetes, uncomplicated hypertension, fluid and electrolyte disorders, cardiac arrhythmia, valvular disease, hypothyroidism, acquired immunodeficiency syndrome/human immunodeficiency virus, deficiency anemia, renal failure, paralysis, coagulopathy, metastatic cancer, and other neurological disorders) (ARRs ranged from 0.74 to 0.93, all p < .001). Conclusions/UNASSIGNED:Although VHA cessation pharmacotherapy use nearly doubled from 13.8% in 2004 to 25.6% in 2013, reaching undertreated subgroups, especially those with medical comorbidities, may improve cessation outcomes. Implications/UNASSIGNED:Despite evidence that demographics influence the use of pharmacotherapy in smoking cessation, there is limited and contradictory information regarding how psychiatric and chronic medical illnesses affect pharmacotherapy use. Administrative data were used to determine trends and patient characteristics of those receiving pharmacotherapy to aid in smoking cessation in the Veterans Health Administration. From 2004 to 2013, pharmacotherapy use increased from 13.8% to 25.6% of current smokers. Factors associated with increased pharmacotherapy initiation were psychiatric disorders, chronic pulmonary disease, peripheral vascular disorders, and younger age. Veterans with schizophrenia or other psychosis, males, Hispanics, and most medical conditions were less likely to receive pharmacotherapy.

Cigarette smoking alters the oral microbiome; however, the effect of alternative tobacco products remains unclear. Middle Eastern tobacco products like dokha and shisha, are becoming globally widespread. We tested for the first time in a Middle Eastern population the hypothesis that different tobacco products impact the oral microbiome. The oral microbiome of 330 subjects from the United Arab Emirates Healthy Future Study was assessed by amplifying the bacterial 16S rRNA gene from mouthwash samples. Tobacco consumption was assessed using a structured questionnaire and further validated by urine cotinine levels. Oral microbiome overall structure and specific taxon abundances were compared, using PERMANOVA and DESeq analyses respectively. Our results show that overall microbial composition differs between smokers and nonsmokers (p = 0.0001). Use of cigarettes (p = 0.001) and dokha (p = 0.042) were associated with overall microbiome structure, while shisha use was not (p = 0.62). The abundance of multiple genera were significantly altered (enriched/depleted) in cigarette smokers; however, only Actinobacillus, Porphyromonas, Lautropia and Bifidobacterium abundances were significantly changed in dokha users whereas no genera were significantly altered in shisha smokers. For the first time, we show that smoking dokha is associated to oral microbiome dysbiosis, suggesting that it could have similar effects as smoking cigarettes on oral health.