Genetic predisposition to macronutrient preference and workplace food choices.

Prior research identified genetic variants influencing macronutrient preference, but whether genetic differences underlying nutrient preference affect long-term food choices is unknown. Here we examined the associations of polygenic scores for carbohydrate, fat, and protein preference with 12 months' workplace food purchases among 397 hospital employees from the ChooseWell 365 study. Food purchases were obtained retrospectively from the hospital's cafeteria sales data for the 12 months before participants were enrolled in the ChooseWell 365 study. Traffic light labels, visible to employees when making purchases, measured the quality of workplace purchases. During the 12-month study period, there were 215,692 cafeteria purchases. Each SD increase in the polygenic score for carbohydrate preference was associated with 2.3 additional purchases/month (95%CI, 0.2 to 4.3; p = 0.03) and a higher number of green-labeled purchases (ß = 1.9, 95%CI, 0.5-3.3; p = 0.01). These associations were consistent in subgroup and sensitivity analyses accounting for additional sources of bias. There was no evidence of associations between fat and protein polygenic scores and cafeteria purchases. Findings from this study suggest that genetic differences in carbohydrate preference could influence long-term workplace food purchases and may inform follow-up experiments to enhance our understanding of the molecular mechanisms underlying food choice behavior.

A National Dental Practice-Based Research Network phase II, cluster-randomized clinical trial assessing nicotine replacement therapy sampling in dental settings: study protocol for the Free Samples for Health (FreSH) study.

BACKGROUND: Cigarette smoking has major detrimental effects on oral health. Tobacco interventions in dental settings are effective, but rarely delivered. The American Dental Hygienists Association recommends that oral health providers: Ask patients about tobacco use, Advise quitting tobacco use, and Refer to state quitlines (Ask-Advise-Refer; AAR). While AAR connects patients to counseling, it does not directly connect patients to medication. Nicotine replacement therapy sampling (NRTS) is an empirically supported intervention to provide starter packs of nicotine replacement therapy (NRT) to people who smoke. NRTS combined with AAR could be an effective tobacco treatment intervention for dental settings. METHODS: This manuscript describes the study protocol for the Free Samples for Health (FreSH) study, a group randomized clinical trial testing the effectiveness of NRTS + AAR vs. AAR alone on long-term smoking abstinence. Fifty dental practices in the Midwest and Northeast nodes of the National Dental Practice-Based Research Network are randomly assigned to provide AAR and either a 2-week supply of 14-mg nicotine patches and 4-mg nicotine lozenges (NRTS condition) or an electric toothbrush (ET condition). Approximately 1,200 patients who currently smoke-regardless of interest in quitting- are recruited during dental visits. Participants complete a baseline survey in-person, then after visit, 1-, 3-, and 6-month follow-up surveys remotely. The primary outcome is carbon monoxide-confirmed 7-day point prevalence abstinence from combustible tobacco measured at 6 months post-enrollment. Secondary outcomes include: 24-h intentional quit attempts, change in cigarettes smoked per day, NRT utilization, attitudes toward NRT, intention to use NRT, and intention to quit smoking. A key informant process evaluation and cost effectiveness analysis will provide information for future implementation of NRTS. DISCUSSION: This is the first clinical trial to assess the effectiveness of NRTS on promoting smoking cessation in dental settings. If effective, this treatment could be implemented to increase the provision of smoking cessation interventions in dental settings to provide an additional treatment access point for people who smoke. TRIAL REGISTRATION: Registered at ClincalTrials.gov (NCT05627596) on 11/25/2022.

Costs to Implement a Pediatric Weight Management Program Across 3 Distinct Contexts.

BACKGROUND: The Connect for Health program is an evidence-based program that aligns with national recommendations for pediatric weight management and includes clinical decision support, educational handouts, and community resources. As implementation costs are a major driver of program adoption and maintenance decisions, we assessed the costs to implement the Connect for Health program across 3 health systems that primarily serve low-income communities with a high prevalence of childhood obesity. METHODS: We used time-driven activity-based costing methods. Each health system (site) developed a process map and a detailed report of all implementation actions taken, aligned with major implementation requirements (eg, electronic health record integration) or strategies (eg, providing clinician training). For each action, sites identified the personnel involved and estimated the time they spent, allowing us to estimate the total costs of implementation and breakdown costs by major implementation activities. RESULTS: Process maps indicated that the program integrated easily into well-child visits. Overall implementation costs ranged from $77,103 (Prisma Health) to $84,954 (Denver Health) to $142,721 (Massachusetts General Hospital). Across implementation activities, setting up the technological aspects of the program was a major driver of costs. Other cost drivers included training, engaging stakeholders, and audit and feedback activities, though there was variability across systems based on organizational context and implementation choices. CONCLUSIONS: Our work highlights the major cost drivers of implementing the Connect for Health program. Accounting for context-specific considerations when assessing the costs of implementation is crucial, especially to facilitate accurate projections of implementation costs in future settings.

Can Treatment Support Mitigate Nicotine Metabolism-Based Disparities in Smoking Abstinence? Secondary Analysis of the Helping HAND 4 Trial.

INTRODUCTION: The nicotine metabolite ratio (NMR), a biomarker of CYP2A6-mediated nicotine metabolism, predicts the efficacy of nicotine replacement therapy (NRT), with fast metabolizers benefiting less than slow metabolizers. Whether treatment support to optimize NRT use (henceforth "treatment support") modifies this pharmacogenetic relationship is unknown. METHODS: Hospitalized adult daily smokers were assigned to one of two post-discharge smoking cessation interventions offering NRT and counseling: (1) Transitional Tobacco Care Management, which delivered enhanced treatment support via free combination NRT at discharge and automated counseling, and (2) a quitline-based approach representing usual care (UC). The primary outcome was biochemically verified 7-day point prevalence abstinence 6 months after discharge. Secondary outcomes were the use of NRT and counseling during the 3-month intervention period. Logistic regression models tested for interactions between NMR and intervention, controlling for sex, race, alcohol use, and BMI. RESULTS: Participants (N = 321) were classified as slow (n = 80) or fast (n = 241) metabolizers relative to the first quartile of NMR (0.012-0.219 vs. 0.221-3.455, respectively). Under UC, fast (vs. slow) metabolizers had lower odds of abstinence at 6 months (aOR 0.35, 95% CI 0.13-0.95) and similar odds of NRT and counseling use. Compared to UC, enhanced treatment support increased abstinence (aOR 2.13, 95% CI 0.98-4.64) and use of combination NRT (aOR 4.62, 95% CI 2.57-8.31) in fast metabolizers, while reducing abstinence in slow metabolizers (aOR 0.21, 95% CI 0.05-0.87; NMR-by-intervention interaction p = .004). CONCLUSIONS: Treatment support increased abstinence and optimal use of NRT among fast nicotine metabolizers, thereby mitigating the gap in abstinence between fast and slow metabolizers. IMPLICATIONS: In this secondary analysis of two smoking cessation interventions for recently hospitalized smokers, fast nicotine metabolizers quit at lower rates than slow metabolizers, but providing fast metabolizers with enhanced treatment support doubled the odds of quitting in this group and mitigated the disparity in abstinence between fast and slow metabolizers. If validated, these findings could lead to personalized approaches to smoking cessation treatment that improve outcomes by targeting treatment support to those who need it most.

Study protocol for a hybrid type 1 effectiveness-implementation trial testing virtual tobacco treatment in oncology practices [Smokefree Support Study 2.0].

BACKGROUND: Persistent smoking among patients diagnosed with cancer is associated with adverse clinical outcomes, yet an evidence-based tobacco use intervention has not been well-integrated into cancer care in community oncology settings. This paper describes the protocol of a nation-wide clinical trial conducted by the ECOG-ACRIN National Cancer Institute (NCI) Community Oncology Research Program (NCORP) Research Base to assess the effectiveness of a virtual tobacco treatment intervention and the process of implementing tobacco treatment in NCORP community oncology settings. METHODS/DESIGN: This two-arm, multisite (n: 49 NCORP sites) hybrid type 1 effectiveness-implementation randomized controlled trial compares the effectiveness of a Virtual Intervention Treatment (VIT) versus an Enhanced Usual Control (EUC) among English and Spanish speaking patients recently diagnosed with cancer, reporting current smoking and receiving care at a participating NCORP Community or Minority/Underserved Site. The VIT includes up to 11 virtual counseling sessions with a tobacco treatment specialist and up to 12 weeks of nicotine replacement therapy (NRT). The EUC arm receives a referral to the NCI Quitline. The primary study outcome is biochemically confirmed 7-day point prevalence smoking abstinence. Moderators of treatment effect will be assessed. The study evaluates implementation processes from participating NCORP site staff via survey, administrative, and focus group data, including reach, acceptability, appropriateness, fidelity, feasibility, adoption, cost and sustainability outcomes. DISCUSSION: This trial will generate findings about the effectiveness of an evidence-based virtual tobacco treatment intervention targeting patients diagnosed with cancer and illuminate barriers and facilitators that influence implementing tobacco treatment into community oncology settings nationally. In the era of COVID-19, virtual care solutions are vital for maximizing access and utilization of tobacco treatment delivery. TRIAL REGISTRATION: ClinicalTrials.gov (NCT03808818) on January 18th, 2019; Last update posted: May 21st, 2020.

Cigarette Smoking and Risk Perceptions During the COVID-19 Pandemic Reported by Recently Hospitalized Participants in a Smoking Cessation Trial.

BACKGROUND: Cigarette smoking is a risk factor for severe COVID-19 disease. Understanding smokers' responses to the pandemic will help assess its public health impact and inform future public health and provider messages to smokers. OBJECTIVE: To assess risk perceptions and change in tobacco use among current and former smokers during the COVID-19 pandemic. DESIGN: Cross-sectional survey conducted in May-July 2020 (55% response rate) PARTICIPANTS: 694 current and former daily smokers (mean age 53, 40% male, 78% white) who had been hospitalized pre-COVID-19 and enrolled into a smoking cessation clinical trial at hospitals in Massachusetts, Pennsylvania, and Tennessee. MAIN MEASURES: Perceived risk of COVID-19 due to tobacco use; changes in tobacco consumption and interest in quitting tobacco use; self-reported quitting and relapse since January 2020. KEY RESULTS: 68% (95% CI, 65-72%) of respondents believed that smoking increases the risk of contracting COVID-19 or having a more severe case. In adjusted analyses, perceived risk was higher in Massachusetts where COVID-19 had already surged than in Pennsylvania and Tennessee which were pre-surge during survey administration (AOR 1.56, 95% CI, 1.07-2.28). Higher perceived COVID-19 risk was associated with increased interest in quitting smoking (AOR 1.72, 95% CI 1.01-2.92). During the pandemic, 32% (95% CI, 27-37%) of smokers increased, 37% (95% CI, 33-42%) decreased, and 31% (95% CI, 26-35%) did not change their cigarette consumption. Increased smoking was associated with higher perceived stress (AOR 1.49, 95% CI 1.16-1.91). Overall, 11% (95% CI, 8-14%) of respondents who smoked in January 2020 (pre-COVID-19) had quit smoking at survey (mean, 6 months later) while 28% (95% CI, 22-34%) of former smokers relapsed. Higher perceived COVID-19 risk was associated with higher odds of quitting and lower odds of relapse. CONCLUSIONS: Most smokers believed that smoking increased COVID-19 risk. Smokers' responses to the pandemic varied, with increased smoking related to stress and increased quitting associated with perceived COVID-19 vulnerability.

Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial.

BACKGROUND: The influence of genetic risk for obesity on food choice behaviors is unknown and may be in the causal pathway between genetic risk and weight gain. The aim of this study was to examine associations between genetic risk for obesity and food choice behaviors using objectively assessed workplace food purchases. METHODS AND FINDINGS: This study is a secondary analysis of baseline data collected prior to the start of the "ChooseWell 365" health-promotion intervention randomized control trial. Participants were employees of a large hospital in Boston, MA, who enrolled in the study between September 2016 and February 2018. Cafeteria sales data, collected retrospectively for 3 months prior to enrollment, were used to track the quantity (number of items per 3 months) and timing (median time of day) of purchases, and participant surveys provided self-reported behaviors, including skipping meals and preparing meals at home. A previously validated Healthy Purchasing Score was calculated using the cafeteria traffic-light labeling system (i.e., green = healthy, yellow = less healthy, red = unhealthy) to estimate the healthfulness (quality) of employees' purchases (range, 0%-100% healthy). DNA was extracted and genotyped from blood samples. A body mass index (BMI) genome-wide polygenic score (BMIGPS) was generated by summing BMI-increasing risk alleles across the genome. Additionally, 3 polygenic risk scores (PRSs) were generated with 97 BMI variants previously identified at the genome-wide significance level (P < 5 × 10-8): (1) BMI97 (97 loci), (2) BMICNS (54 loci near genes related to central nervous system [CNS]), and (3) BMInon-CNS (43 loci not related to CNS). Multivariable linear and logistic regression tested associations of genetic risk score quartiles with workplace purchases, adjusted for age, sex, seasonality, and population structure. Associations were considered significant at P < 0.05. In 397 participants, mean age was 44.9 years, and 80.9% were female. Higher genetic risk scores were associated with higher BMI. The highest quartile of BMIGPS was associated with lower Healthy Purchasing Score (-4.8 percentage points [95% CI -8.6 to -1.0]; P = 0.02), higher quantity of food purchases (14.4 more items [95% CI -0.1 to 29.0]; P = 0.03), later time of breakfast purchases (15.0 minutes later [95% CI 1.5-28.5]; P = 0.03), and lower likelihood of preparing dinner at home (Q4 odds ratio [OR] = 0.3 [95% CI 0.1-0.9]; P = 0.03) relative to the lowest BMIGPS quartile. Compared with the lowest quartile, the highest BMICNS quartile was associated with fewer items purchased (P = 0.04), and the highest BMInon-CNS quartile was associated with purchasing breakfast at a later time (P = 0.01), skipping breakfast (P = 0.03), and not preparing breakfast (P = 0.04) or lunch (P = 0.01) at home. A limitation of this study is our data come from a relatively small sample of healthy working adults of European ancestry who volunteered to enroll in a health-promotion study, which may limit generalizability. CONCLUSIONS: In this study, genetic risk for obesity was associated with the quality, quantity, and timing of objectively measured workplace food purchases. These findings suggest that genetic risk for obesity may influence eating behaviors that contribute to weight and could be targeted in personalized workplace wellness programs in the future. TRIAL REGISTRATION: Clinicaltrials.gov NCT02660086.

Effectiveness of Lifestyle Intervention for Type 2 Diabetes in Primary Care: the REAL HEALTH-Diabetes Randomized Clinical Trial.

BACKGROUND: Intensive lifestyle interventions (LI) improve outcomes in obesity and type 2 diabetes but are not currently available in usual care. OBJECTIVE: To compare the effectiveness and costs of two group LI programs, in-person LI and telephone conference call (telephone LI), to medical nutrition therapy (MNT) on weight loss in primary care patients with type 2 diabetes. DESIGN: A randomized, assessor-blinded, practice-based clinical trial in three community health centers and one hospital-based practice affiliated with a single health system. PARTICIPANTS: A total of 208 primary care patients with type 2 diabetes, HbA1c 6.5 to < 11.5, and BMI > 25 kg/m2 (> 23 kg/m2 in Asians). INTERVENTIONS: Dietitian-delivered in-person or telephone group LI programs with medication management or MNT referral. MAIN MEASURES: Primary outcome: mean percent weight change. SECONDARY OUTCOMES: 5% and 10% weight loss, change in HbA1c, and cost per kilogram lost. KEY RESULTS: Participants' mean age was 62 (SD 10) years, 45% were male, and 77% were White, with BMI 35 (SD 5) kg/m2 and HbA1c 7.7 (SD 1.2). Seventy were assigned to in-person LI, 72 to telephone LI, and 69 to MNT. The mean percent weight loss (95% CI) at 6 and 12 months was 5.6% (4.4-6.8%) and 4.6% (3.1-6.1%) for in-person LI, 4.6% (3.3-6.0%) and 4.8% (3.3-6.2%) for telephone LI, and 1.1% (0.2-2.0%) and 2.0% (0.9-3.0%) for MNT, with statistically significant differences between each LI arm and MNT (P < 0.001) but not between LI arms (P = 0.63). HbA1c improved in all participants. Compared with MNT, the incremental cost per kilogram lost was $789 for in-person LI and $1223 for telephone LI. CONCLUSIONS: In-person LI or telephone group LI can achieve good weight loss outcomes in primary care type 2 diabetes patients at a reasonable cost. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02320253.

Effect of Sustained Smoking Cessation Counseling and Provision of Medication vs Shorter-term Counseling and Medication Advice on Smoking Abstinence in Patients Recently Diagnosed With Cancer: A Randomized Clinical Trial.

Importance: Persistent smoking may cause adverse outcomes among patients with cancer. Many cancer centers have not fully implemented evidence-based tobacco treatment into routine care. Objective: To determine the effectiveness of sustained telephone counseling and medication (intensive treatment) compared with shorter-term telephone counseling and medication advice (standard treatment) to assist patients recently diagnosed with cancer to quit smoking. Design, Setting, and Participants: This unblinded randomized clinical trial was conducted at Massachusetts General Hospital/Dana-Farber/Harvard Cancer Center and Memorial Sloan Kettering Cancer Center. Adults who had smoked 1 cigarette or more within 30 days, spoke English or Spanish, and had recently diagnosed breast, gastrointestinal, genitourinary, gynecological, head and neck, lung, lymphoma, or melanoma cancers were eligible. Enrollment occurred between November 2013 and July 2017; assessments were completed by the end of February 2018. Interventions: Participants randomized to the intensive treatment (n = 153) and the standard treatment (n = 150) received 4 weekly telephone counseling sessions and medication advice. The intensive treatment group also received 4 biweekly and 3 monthly telephone counseling sessions and choice of Food and Drug Administration-approved cessation medication (nicotine replacement therapy, bupropion, or varenicline). Main Outcome and Measures: The primary outcome was biochemically confirmed 7-day point prevalence tobacco abstinence at 6-month follow-up. Secondary outcomes were treatment utilization rates. Results: Among 303 patients who were randomized (mean age, 58.3 years; 170 women [56.1%]), 221 (78.1%) completed the trial. Six-month biochemically confirmed quit rates were 34.5% (n = 51 in the intensive treatment group) vs 21.5% (n = 29 in the standard treatment group) (difference, 13.0% [95% CI, 3.0%-23.3%]; odds ratio, 1.92 [95% CI, 1.13-3.27]; P < .02). The median number of counseling sessions completed was 8 (interquartile range, 4-11) in the intensive treatment group. A total of 97 intensive treatment participants (77.0%) vs 68 standard treatment participants (59.1%) reported cessation medication use (difference, 17.9% [95% CI, 6.3%-29.5%]; odds ratio, 2.31 [95% CI, 1.32-4.04]; P = .003). The most common adverse events in the intensive treatment and standard treatment groups, respectively, were nausea (n = 13 and n = 6), rash (n = 4 and n = 1), hiccups (n = 4 and n = 1), mouth irritation (n = 4 and n = 0), difficulty sleeping (n = 3 and n = 2), and vivid dreams (n = 3 and n = 2). Conclusions and Relevance: Among smokers recently diagnosed with cancer in 2 National Cancer Institute-designated Comprehensive Cancer Centers, sustained counseling and provision of free cessation medication compared with 4-week counseling and medication advice resulted in higher 6-month biochemically confirmed quit rates. However, the generalizability of the study findings is uncertain and requires further research. Trial Registration: ClinicalTrials.gov Identifier: NCT01871506.

Association of work-related and leisure-time physical activity with workplace food purchases, dietary quality, and health of hospital employees.

BACKGROUND: While leisure-time physical activity (PA) has been associated with reduced risk of cardiometabolic disease, less is known about the relationship between work-related PA and health. Work-related PA is often not a chosen behavior and may be associated with lower socioeconomic status and less control over job-related activities. This study examined whether high work-related PA and leisure-time PA reported by hospital employees were associated with healthier dietary intake and reductions in cardiometabolic risk. METHODS: This was a cross-sectional analysis of 602 hospital employees who used workplace cafeterias and completed the baseline visit for a health promotion study in 2016-2018. Participants completed the International Physical Activity Questionnaire and clinical measures of weight, blood pressure, HbA1c, and lipids. Healthy Eating Index (HEI) scores were calculated from two 24-h dietary recalls, and a Healthy Purchasing Score was calculated based on healthfulness of workplace food/beverage purchases. Regression analyses examined Healthy Purchasing Score, HEI, and obesity, hypertension, hyperlipidemia, and diabetes/prediabetes by quartile of work-related PA, leisure-time PA, and sedentary time. RESULTS: Participants' mean age was 43.6 years (SD = 12.2), 79.4% were female, and 81.1% were white. In total, 30.3% had obesity, 20.6% had hypertension, 26.6% had prediabetes/diabetes, and 32.1% had hyperlipidemia. Median leisure-time PA was 12.0 (IQR: 3.3, 28.0) and median work-related PA was 14.0 (IQR: 0.0, 51.1) MET-hours/week. Higher leisure-time PA was associated with higher workplace Healthy Purchasing Score and HEI (p's < 0.01) and lower prevalence of obesity, diabetes/prediabetes, and hyperlipidemia (p's < 0.05). Work-related PA was not associated with Healthy Purchasing Score, HEI, or cardiometabolic risk factors. Increased sedentary time was associated with lower HEI (p = 0.02) but was not associated with the workplace Healthy Purchasing Score. CONCLUSIONS: Employees with high work-related PA did not have associated reductions in cardiometabolic risk or have healthier dietary intake as did employees reporting high leisure-time PA. Workplace wellness programs should promote leisure-time PA and healthy food choices for all employees, but programs may need to be customized and made more accessible to meet the unique needs of employees who are physically active at work. TRIAL REGISTRATION: This trial was prospectively registered with clinicaltrials.gov (Identifier: NCT02660086) on January 21, 2016. The first participant was enrolled on September 16, 2016.

Association of E-Cigarette Use With Smoking Cessation Among Smokers Who Plan to Quit After a Hospitalization: A Prospective Study.

Background: Many smokers report using e-cigarettes to help them quit smoking, but whether e-cigarettes aid cessation efforts is uncertain. Objective: To determine whether e-cigarette use after hospital discharge is associated with subsequent tobacco abstinence among smokers who plan to quit and are advised to use evidence-based treatment. Design: Secondary data analysis of a randomized controlled trial. (ClinicalTrials.gov: NCT01714323 [parent trial]). Setting: 3 hospitals. Participants: 1357 hospitalized adult cigarette smokers who planned to stop smoking, received tobacco cessation counseling in the hospital, and were randomly assigned at discharge to a tobacco treatment recommendation (control) or free tobacco treatment (intervention). Measurements: Self-reported e-cigarette use (exposure) was assessed 1 and 3 months after discharge; biochemically validated tobacco abstinence (outcome) was assessed 6 months after discharge. Results: Twenty-eight percent of participants used an e-cigarette within 3 months after discharge. In an analysis of 237 propensity score-matched pairs, e-cigarette users were less likely than nonusers to abstain from tobacco use at 6 months (10.1% vs. 26.6%; risk difference, -16.5% [95% CI, -23.3% to -9.6%]). The association between e-cigarette use and quitting varied between intervention patients, who were given easy access to conventional treatment (7.7% vs. 29.8%; risk difference, -22.1% [CI, -32.3% to -11.9%]), and control patients, who received only treatment recommendations (12.0% vs. 24.1%; risk difference, -12.0% [CI, -21.2% to 2.9%]) (P for interaction = 0.143). Limitations: Patients self-selected e-cigarette use. Unmeasured confounding is possible in an observational study. Conclusion: During 3 months after hospital discharge, more than a quarter of smokers attempting to quit used e-cigarettes, mostly to aid cessation, but few used them regularly. This pattern of use was associated with less tobacco abstinence at 6 months than among smokers who did not use e-cigarettes. Additional study is needed to determine whether regular use of e-cigarettes aids or hinders smoking cessation. Primary Funding Source: National Heart, Lung, and Blood Institute.

Improvements in health-related quality of life among smokers who quit after hospitalization.

Few rigorous longitudinal assessments have examined health-related quality of life (HRQoL) changes after smoking cessation, especially among recently-hospitalized smokers. We compared the change in HRQoL between those who did or did not quit smoking 6 months after hospital discharge. Participants were 1357 smokers recruited for a cessation trial between 2012 and 2014 while hospitalized at two hospitals in Massachusetts and one in Pennsylvania. Cessation was defined as biochemically confirmed 7-day point prevalence abstinence at 6 months or as self-reported continuous abstinence at 1, 3, or 6 months post discharge. HRQoL measures included a single-item global health measure (SF1); the Patient Health Questionnaire for Depression and Anxiety (PHQ-4) screening tool for psychological distress; and the EQ-5D-5L health utilities measure. Multivariable models controlled for age, sex, race, education, insurance, study site, study arm, discharge diagnoses, and baseline HRQoL. Improvements in HRQoL were evident in the first month after discharge among those achieving abstinence compared to continuing smokers. At 6 months post-discharge, those with biochemically confirmed cessation were 30% more likely to report at least good health by the SF1 (aRR 95% CI 1.14-1.45), 19% less likely to screen positive for psychological distress (aRR, 95% CI 0.68-0.93), and had EQ-5D-5L health utility scores 0.05 points (95% CI 0.02-0.08) higher than continuing smokers. Results were similar when assessed as a function of self-reported cessation. Hospital-initiated smoking cessation is associated with rapid statistically and clinically significant improvements in a range of HRQoL measures, providing an additional tool clinicians and health systems could use to encourage smoking cessation.

Traffic-light labels and financial incentives to reduce sugar-sweetened beverage purchases by low-income Latino families: a randomized controlled trial.

OBJECTIVE: The objective of the present study was to test the effectiveness of financial incentives and traffic-light labels to reduce purchases of sugar-sweetened beverages in a community supermarket. DESIGN: In this randomized controlled trial, after a 2-month baseline period (February-March 2014), in-store traffic-light labels were posted to indicate healthy (green), less healthy (yellow) or unhealthy (red) beverages. During the subsequent five months (April-August 2014), participants in the intervention arm were eligible to earn a $US 25 in-store gift card each month they refrained from purchasing red-labelled beverages. SETTING: Urban supermarket in Chelsea, MA, USA, a low-income Latino community. SUBJECTS: Participants were customers of this supermarket who had at least one child living at home. A total of 148 customers (n 77 in the intervention group and n 71 in the control group) were included in the final analyses. RESULTS: Outcomes were monthly in-store purchases tracked using a store loyalty card and self-reported consumption of red-labelled beverages. Compared with control participants, the proportion of intervention participants who purchased any red-labelled beverages decreased by 9 % more per month (P=0·002). More intervention than control participants reduced their consumption of red-labelled beverages (-23 % v. -2 % for consuming ≥1 red beverage/week, P=0·01). CONCLUSIONS: Overall, financial incentives paired with in-store traffic-light labels modestly reduced purchase and consumption of sugar-sweetened beverages by customers of a community supermarket.

Interactive Voice Response Calls to Promote Smoking Cessation after Hospital Discharge: Pooled Analysis of Two Randomized Clinical Trials.

BACKGROUND: Hospitalization offers smokers an opportunity to quit smoking. Starting cessation treatment in hospital is effective, but sustaining treatment after discharge is a challenge. Automated telephone calls with interactive voice response (IVR) technology could support treatment continuance after discharge. OBJECTIVE: To assess smokers' use of and satisfaction with an IVR-facilitated intervention and to test the relationship between intervention dose and smoking cessation. DESIGN: Analysis of pooled quantitative and qualitative data from the intervention groups of two similar randomized controlled trials with 6-month follow-up. PARTICIPANTS: A total of 878 smokers admitted to three hospitals. All received cessation counseling in hospital and planned to stop smoking after discharge. INTERVENTION: After discharge, participants received free cessation medication and five automated IVR calls over 3 months. Calls delivered messages promoting smoking cessation and medication adherence, offered medication refills, and triaged smokers to additional telephone counseling. MAIN MEASURES: Number of IVR calls answered, patient satisfaction, biochemically validated tobacco abstinence 6 months after discharge. KEY RESULTS: Participants answered a median of three of five IVR calls; 70% rated the calls as helpful, citing the social support, access to counseling and medication, and reminders to quit as positive factors. Older smokers (OR 1.36, 95% CI 1.20-1.54 per decade) and smokers hospitalized for a smoking-related disease (OR 1.65, 95% CI 1.21-2.23) completed more calls. Smokers who completed more calls had higher quit rates at 6-month follow-up (OR 1.49, 95% CI 1.30-1.70, for each additional call) after multivariable adjustment for age, sex, education, discharge diagnosis, nicotine dependence, duration of medication use, and perceived importance of and confidence in quitting. CONCLUSIONS: Automated IVR calls to support smoking cessation after hospital discharge were viewed favorably by patients. Higher IVR utilization was associated with higher odds of tobacco abstinence at 6-month follow-up. IVR technology offers health care systems a potentially scalable means of sustaining tobacco cessation interventions after hospital discharge. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifiers NCT01177176, NCT01714323.

Delivering on the Promise of Smoke-Free Public Housing.

On November 30, 2016, the US Department of Housing and Urban Development (HUD) published a final rule mandating that public housing authorities it supports prohibit all smoking on their residential premises, including within residents' apartments. The primary rationale for this action was to protect nonsmoking residents from the harms of tobacco smoke exposure. Although the harms of secondhand smoke are clear and the potential for reducing nonsmoking residents' exposure is real, it will be no simple matter to successfully implement the policy requirements set down by HUD. Some challenges to policy implementation will apply to all public housing authorities, and others will be unique to specific settings. By being aware of the benefits of smoke-free public housing as well as the challenges inherent in complying with HUD's rule, public housing authorities stand the best chance of fulfilling the potential of this major policy initiative to significantly improve public health in a vulnerable population.

Cost-Effectiveness of a Health System-Based Smoking Cessation Program.

INTRODUCTION: Project CLIQ (Community Link to Quit) was a proactive population-outreach strategy using an electronic health records-based smoker registry and interactive voice recognition technology to connect low- to moderate-income smokers with cessation counseling, medications, and social services. A randomized trial demonstrated that the program increased cessation. We evaluated the cost-effectiveness of CLIQ from a provider organization's perspective if implemented outside the trial framework. METHODS: We calculated the cost, cost per smoker, incremental cost per additional quit, and, secondarily, incremental cost per additional life year saved of the CLIQ system compared to usual care using data from a 2011-2013 randomized trial assessing the effectiveness of the CLIQ system. Sensitivity analyses considered economies of scale and initial versus ongoing costs. RESULTS: Over a 20-month period (the duration of the trial) the program cost US $283 027 (95% confidence interval [CI] $209 824-$389 072) more than usual care in a population of 8544 registry-identified smokers, 707 of whom participated in the program. The cost per smoker was $33 (95% CI 28-40), incremental cost per additional quit was $4137 (95% CI $2671-$8460), and incremental cost per additional life year saved was $7301 (95% CI $4545-$15 400). One-time costs constituted 28% of costs over 20 months. Ongoing costs were dominated by personnel costs (71% of ongoing costs). Sensitivity analyses showed sharp gains in cost-effectiveness as the number of identified smokers increased because of the large initial costs. CONCLUSIONS: The CLIQ system has favorable cost-effectiveness compared to other smoking cessation interventions. Cost-effectiveness will be greatest for health systems with high numbers of smokers and with the high smoker participation rates. IMPLICATIONS: Health information systems capable of establishing registries of patients who are smokers are becoming more prevalent. This economic analysis illustrates the cost implications for health care systems adopting a proactive tobacco treatment outreach strategy for low- and middle-income smokers. We find that under many circumstances, the CLIQ system has a favorable cost-per-quit compared to other population-based tobacco treatment strategies. The strategy could be widely disseminable if health systems leverage economies of scale.

Choice architecture to promote fruit and vegetable purchases by families participating in the Special Supplemental Program for Women, Infants, and Children (WIC): randomized corner store pilot study.

OBJECTIVE: To conduct a pilot study to determine if improving the visibility and quality of fresh produce (choice architecture) in corner stores would increase fruit/vegetable purchases by families participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). DESIGN: Six stores were randomly assigned to choice architecture intervention or control. Store-level WIC sales data were provided by the state. Primary outcomes were WIC fruit/vegetable voucher and non-fruit/vegetable voucher sales, comparing trends from baseline (December 2012-October 2013) with the five-month intervention period (December 2013-April 2014). Secondary outcomes were differences in customer self-reported fruit/vegetable purchases between baseline and end of the intervention. SETTING: Chelsea, MA, USA, a low-income urban community. SUBJECTS: Adult customers (n 575) completing store exit interviews. RESULTS: During baseline, WIC fruit/vegetable and non-fruit/vegetable sales decreased in both intervention and control stores by $US 16/month. During the intervention period, WIC fruit/vegetable sales increased in intervention stores by $US 40/month but decreased in control stores by $US 23/month (difference in trends: $US 63/month; 95 % CI 4, 121 $US/month; P=0·036); WIC non-fruit/vegetable sales were not different (P=0·45). Comparing baseline and intervention-period exit interview responses by customers participating in WIC (n 134), intervention store customers reported increased fruit/vegetable purchases compared with control store customers (18 v. -2 %), but this did not achieve statistical significance (P=0·11). CONCLUSIONS: Placement of fruits/vegetables near the front of corner stores increased purchase of produce by customers using WIC. New policies that incentivize stores to stock and prominently display good-quality produce could promote healthier food choices of low-income families.

Social norms and financial incentives to promote employees' healthy food choices: A randomized controlled trial.

OBJECTIVE: Population-level strategies to improve healthy food choices are needed for obesity prevention. We conducted a randomized controlled trial of 2672 employees at the Massachusetts General Hospital who were regular customers of the hospital cafeteria with all items labeled green (healthy), yellow (less healthy), or red (unhealthy) to determine if social norm (peer-comparison) feedback with or without financial incentives increased employees' healthy food choices. METHODS: Participants were randomized in 2012 to three arms: 1) monthly letter with social norm feedback about healthy food purchases, comparing employee to "all" and to "healthiest" customers (feedback-only); 2) monthly letter with social norm feedback plus small financial incentive for increasing green purchases (feedback-incentive); or 3) no contact (control). The main outcome was change in proportion of green-labeled purchases at the end of 3-month intervention. Post-hoc analyses examined linear trends. RESULTS: At baseline, the proportion of green-labeled purchases (50%) did not differ between arms. At the end of the 3-month intervention, the percentage increase in green-labeled purchases was larger in the feedback-incentive arm compared to control (2.2% vs. 0.1%, P=0.03), but the two intervention arms were not different. The rate of increase in green-labeled purchases was higher in both feedback-only (P=0.04) and feedback-incentive arms (P=0.004) compared to control. At the end of a 3-month wash-out, there were no differences between control and intervention arms. CONCLUSIONS: Social norms plus small financial incentives increased employees' healthy food choices over the short-term. Future research will be needed to assess the impact of this relatively low-cost intervention on employees' food choices and weight over the long-term. TRIAL REGISTRATION: Clinical Trials.gov: NCT01604499.

Cost-Effectiveness of a Collaborative Care Depression and Anxiety Treatment Program in Patients with Acute Cardiac Illness.

OBJECTIVE: To use data from a randomized trial to determine the cost-effectiveness of a collaborative care (CC) depression and anxiety treatment program and to assess effects of the CC program on health care utilization. METHODS: The CC intervention's impact on health-related quality of life, depression-free days (DFDs), and anxiety-free days (AFDs) over the 24-week postdischarge period was calculated and compared with the enhanced usual care (EUC) condition using independent samples t tests and random-effects regression models. Costs for both the CC and EUC conditions were calculated on the basis of staff time, overhead expenses, and treatment materials. Using this information, incremental cost-effectiveness ratios were calculated. A cost-effectiveness acceptability plot was created using nonparametric bootstrapping with 10,000 replications, and the likelihood of the CC intervention's cost-effectiveness was assessed using standard cutoffs. As a secondary analysis, we determined whether the CC intervention led to reductions in postdischarge health care utilization and costs. RESULTS: The CC intervention was more costly than the EUC intervention ($209.86 vs. $34.59; z = -11.71; P < 0.001), but was associated with significantly greater increases in quality-adjusted life-years (t = -2.49; P = 0.01) and DFDs (t = -2.13; P = 0.03), but not AFDs (t = -1.92; P = 0.057). This translated into an incremental cost-effectiveness ratio of $3337.06 per quality-adjusted life-year saved, $13.36 per DFD, and $13.74 per AFD. Compared with the EUC intervention, the CC intervention was also associated with fewer emergency department visits but no differences in overall costs. CONCLUSIONS: This CC intervention was associated with clinically relevant improvements, was cost-effective, and was associated with fewer emergency department visits in the 24 weeks after discharge.