Association of food insecurity with changes in diet quality, weight, and glycemia over two years in adults with prediabetes and type 2 diabetes on medicaid.

Little is known about longitudinal associations between food insecurity (FI) and diet, weight, and glycemia in people with prediabetes and type 2 diabetes (T2D). In a secondary analysis of Medicaid-enrolled health center patients with prediabetes or T2D in Boston, Massachusetts (N = 188), we examined associations between food security (FS) and measures of diet quality, weight, and hyperglycemia. FS (10-item USDA FS module) was ascertained at baseline, 1-year, and 2-year follow-up and categorized as persistently secure, intermittently insecure, or persistently insecure. Associations between FS category and changes in Healthy Eating Index-2020 (HEI-20), body mass index (BMI), and hemoglobin A1c (A1c) from baseline to year 2 were assessed using multivariate generalized linear models. Participants had median (p25, p75) age of 52 (42, 57); 71.8% were female and 62.8% Hispanic. Over follow-up, 32.4% were persistently food secure, 33.0% intermittently insecure, and 34.5% persistently insecure. Baseline mean (SD) HEI-20, BMI, and A1c were 55.8 (14.5), 35.9 (8.7) kg/m2, 7.1% (1.6) and did not differ by FS category. FS category was not associated with changes in HEI-20, BMI, and A1c at 2 years (all p > 0.05). Results suggest that Medicaid-enrolled adults with prediabetes or T2D, regardless of FS status, would benefit from dietary and weight management interventions.

Workplace food purchases, dietary intake, and gut microbial metabolites in a secondary analysis of the ChooseWell 365 study.

BACKGROUND: Dietary choices can affect human health through alterations in gut microbial metabolism, and gut microbial metabolites could serve as biomarkers for disease risk conferred by dietary intake. However, self-reported dietary intake may not reflect true intake. OBJECTIVES: We identified circulating metabolites, including gut microbiome-related metabolites, associated with adherence to a healthy diet in the ChooseWell 365 study. In this randomized clinical trial, the dietary choices of hospital employees were assessed over 24 mo using not only 24-h dietary recalls but also electronic records of hospital cafeteria purchases. METHODS: Plasma metabolites were profiled from 470 participants. Two targeted metabolomics methods were developed and implemented to expand detection coverage for metabolites related to gut microbial activity. Linear regression models were used to associate metabolites with Healthy Purchasing Scores (HPSs) derived from cafeteria purchases and Healthy Eating Index-2015 (HEI-15) scores derived from dietary recalls. RESULTS: Fourteen metabolites were concordantly associated with the HPS and HEI-15 scores in multivariable models adjusted for age, gender, and race, including the gut microbiome-related metabolites indole-3-propionic acid (HPS, ß: 0.16, 95% CI: 0.07, 0.26, P = 7.32 × 10-4; HEI-15, ß: 0.16, 95% CI: 0.07, 0.25, P = 6.79 × 10-4), hippuric acid (HPS, ß: 0.11, 95% CI: 0.02, 0.21, P = 1.97 × 10-2; HEI-15, ß: 0.10, 95% CI: 0.01, 0.19, P = 3.14 × 10-2), and indoxyl sulfate (HPS, ß = -0.13, 95% CI: -0.23, -0.03, P = 8.21 × 10-3; HEI-15, ß: -0.12, 95% CI: -0.22, -0.03, P = 8.50 × 10-3). These gut microbial metabolites were associated with the intake of specific food groups, such as whole fruits. These metabolites were also associated with clinical variables, including blood pressure, diabetes or prediabetes, and body mass index. CONCLUSIONS: In a secondary analysis of the ChooseWell 365 study, associations between circulating gut microbiome-related metabolites and a healthy diet were confirmed using both objective and subjective measures of consumption. Accurate identification of diet-associated metabolites may help guide dietary or microbiome-based interventions aimed at disease prevention.

Implementation of Community Health Worker Support for Tobacco Cessation: A Mixed-Methods Study.

Objective: Adults with serious mental illness have high tobacco use disorder rates and underutilization of first-line tobacco cessation pharmacotherapy. In a randomized trial, participants offered community health worker (CHW) support and primary care provider (PCP) education had higher tobacco abstinence rates at two years, partly through increased tobacco cessation pharmacotherapy initiation. This study determined the association between participant-CHW engagement and tobacco abstinence outcomes. Methods: This was a secondary, mixed-methods analysis of 196 participants in the trial's intervention arm. Effects of CHW visit number and duration, CHW co-led smoking cessation group sessions attended, and CHW-attended PCP visit number on tobacco use disorder pharmacotherapy initiation and tobacco abstinence were modeled using logistic regression. Interviews with 12 CHWs, 16 participants, and 17 PCPs were analyzed thematically. Results: Year-two tobacco abstinence was associated with CHW visit number (OR=1.85, 95% CI=[1.29, 2.66]) and duration (OR=1.85, 95% CI=[1.33, 2.58]) and number of groups attended (OR=1.51, 95% CI=[1.00, 2.28]); effects on pharmacotherapy initiation were similar. 1-3 CHW visits per month over two years was optimal for achieving abstinence. Interviews identified engagement facilitators, including CHWs establishing trust, providing goal accountability, skills reinforcement, and assistance overcoming barriers to treatment access and adherence related to social determinants of health and illness factors. Robust training and supervision facilitated CHW effectiveness. Barriers included PCPs' and care teams' limited understanding of the CHW role. Conclusions: Feasible CHW engagement was associated with tobacco abstinence in adults with serious mental illness. CHW implementation may benefit from promoting CHW training and integration within clinical teams.

Budget impact analysis for implementation decision making, planning, and financing.

Shelley et al. (in Accelerating integration of tobacco use treatment in the context of lung cancer screening: relevance and application of implementation science to achieving policy and practice. Transl Behav Med 2022;12:1076-1083) laid out how implementation science frameworks and methods can advance the delivery of tobacco use treatment services during lung cancer screening services, which until recently was mandated by the Centers for Medicare and Medicaid Services. Their discussion provides an important overview of the full process of implementation and highlights the vast number of decisions that must be made when planning for implementation of an evidence-based practice such as tobacco use treatment: what specific tobacco use treatment services to deliver, when to deliver those services within the lung cancer screening process, and what implementation strategies to use. The costs of implementation play a major role in decision making and are a key implementation determinant discussed in major implementation frameworks. When making decisions about what and how to implement, budget impact analyses (BIAs) can play an important role in informing decision making by helping practitioners understand the overall affordability of a given implementation effort. BIAs can also inform the development of financing strategies to support the ongoing sustainment of tobacco use treatment service provision. More attention is needed by the research community to produce high-quality, user-friendly, and flexible BIAs to inform implementation decision making in health system and community settings. The application of BIA can help ensure that the considerable time and effort spent to develop and evaluate evidence-based programs has the best chance to inform implementation practice.

Integrating the provision of tobacco use treatment services during lung cancer screening can increase the benefits of lung cancer screening. Shelley et al. lay out how implementation science can be leveraged to facilitate this integration and to highlight the vast array of decisions that must be made to plan for implementation. Practitioners must choose which tobacco use treatment services to deliver, when to deliver those services within the process of lung cancer screening, and how to implement services. The resources associated with these choices are a key determinant of decision making and successful implementation. We discuss how budget impact analyses (BIAs) can help organizations understand the likely costs of what it would take to get tobacco treatment services into place and sustain them over time, accounting for context-specific differences like wage rates or available resources. Researchers should strive to develop high-quality, user-friendly, and flexible BIAs to inform decision making around the integration of tobacco use treatment services during lung cancer screening in health system and community settings. Applications of BIAs extend beyond tobacco; regardless of substantive area, building BIAs is a collaborative effort that requires a team science approach.

Association of Food Insecurity with Changes in Diet Quality, Weight, and Glycemia Over Two Years in Adults with Prediabetes and Type 2 Diabetes on Medicaid.

Little is known about longitudinal associations between food insecurity (FI) and diet, weight, and glycemia in people with prediabetes and type 2 diabetes (T2D). In a secondary analysis of Medicaid-enrolled health center patients with prediabetes or T2D in Boston, Massachusetts (N = 188), we examined associations between food security (FS) and measures of diet quality, weight, and hyperglycemia. FS (10-item USDA FS module) was ascertained at baseline, 1-year, and 2-year follow-up and categorized as persistently secure, intermittently insecure, or persistently insecure. Associations between FS category and changes in Healthy Eating Index-2020 (HEI-20), body mass index (BMI), and hemoglobin A1c (A1c) from baseline to year 2 were assessed using multivariate generalized linear models. Participants had median (p25, p75) age of 52 (42, 57); 71.8% were female and 62.8% Hispanic. Over follow-up, 32.4% were persistently food secure, 33.0% intermittently insecure, and 34.5% persistently insecure. Baseline mean (SD) HEI-20, BMI, and A1c were 55.8 (14.5), 35.9 (8.7) kg/m2, 7.1% (1.6) and did not differ by FS category. FS category was not associated with changes in HEI-20, BMI, and A1c at 2 years (all p > 0.05). Results suggest that Medicaid-enrolled adults with prediabetes or T2D, regardless of FS status, would benefit from dietary and weight management interventions.

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.

Challenges and recommendations for measuring time devoted to implementation and intervention activities in health equity-focused, resource-constrained settings: a qualitative analysis.

BACKGROUND: There is little guidance for conducting health equity-focused economic evaluations of evidence-based practices in resource-constrained settings, particularly with respect to staff time use. Investigators must balance the need for low-touch, non-disruptive cost data collection with the need for data on providing services to priority subpopulations. METHODS: This investigation took place within a pilot study examining the implementation of a bundled screening intervention combining screening for social determinants of health and colorectal cancer at four federally qualified health centers (FQHCs) in the Boston metropolitan area. Methods for collecting data on personnel costs for implementation and intervention activities, including passive (automatic) and active (non-automatic, requiring staff time and effort) data collection, as well as three alternate wordings for self-reporting time-use, were evaluated qualitatively using data collected through interviews with FQHC staff (including clinicians, population health staff, and community health workers) and assessments of data completeness. RESULTS: Passive data collection methods were simple to execute and resulted in no missing data, but missed implementation and intervention activities that took place outside planned meetings. Active cost data collection using spreadsheets was simple for users when applied to care processes already tracked in this fashion and yielded accurate time use data. However, for tasks where this was not typical, and when tasks were broken up over multiple sessions, spreadsheets were more challenging to use. Questions asking about time use for a typical rather than specific time period, and for typical patients, yielded the most reliable and actionable data. Still, even the best-performing question had substantial variability in time use estimates. Participants noted that patient characteristics of interest for equity-focused research, including language spoken, adverse social determinants of health, and issues related to poverty or mental health, all contributed significantly to this variability. CONCLUSIONS: Passively collected time use data are the least burdensome and should be pursued in research efforts when possible, but should be accompanied by qualitative assessments to ensure the data are an accurate reflection of effort. When workflows are already tracked by active data collection, these are also strong data collection methods. Self-reported time use will be most accurate when questions inquire about "typical" tasks and specific types of patients.

Assessment of the Massachusetts Flexible Services Program to Address Food and Housing Insecurity in a Medicaid Accountable Care Organization.

Importance: Health systems are increasingly addressing health-related social needs. The Massachusetts Flexible Services program (Flex) is a 3-year pilot program to address food insecurity and housing insecurity by connecting Medicaid accountable care organization (ACO) enrollees to community resources. Objective: To understand barriers and facilitators of Flex implementation in 1 Medicaid ACO during the first 17 months of the program. Design, Setting, and Participants: This mixed-methods qualitative evaluation study from March 2020 to July 2021 used the Reach, Efficacy, Adoption, Implementation, Maintenance/Practical, Robust Implementation, and Sustainability Model (RE-AIM/PRISM) framework. Two Mass General Brigham (MGB) hospitals and affiliated community health centers were included in the analysis. Quantitative data included all MGB Medicaid ACO enrollees. Qualitative interviews were conducted with 15 members of ACO staff and 17 Flex enrollees. Main Outcomes and Measures: Reach was assessed by the proportion of ACO enrollees who completed annual social needs screening (eg, food insecurity and housing insecurity) and the proportion and demographics of Flex enrollees. Qualitative interviews examined other RE-AIM/PRISM constructs (eg, implementation challenges, facilitators, and perceived effectiveness). Results: Of 67 098 Medicaid ACO enrollees from March 2020 to July 2021 (mean [SD] age, 28.8 [18.7] years), 38 442 (57.3%) completed at least 1 social needs screening; 10 730 (16.0%) screened positive for food insecurity, and 7401 (11.0%) screened positive for housing insecurity. There were 658 (1.6%) adults (mean [SD] age, 46.6 [11.8] years) and 173 (0.7%) children (<21 years; mean [SD] age, 10.1 [5.5]) enrolled in Flex; of these 831 people, 613 (73.8%) were female, 444 (53.4%) were Hispanic/Latinx, and 172 (20.7%) were Black. Most Flex enrollees (584 [88.8%] adults; 143 [82.7%] children) received the intended nutrition or housing services. Implementation challenges identified by staff interviewed included administrative burden, coordination with community organizations, data-sharing and information-sharing, and COVID-19 factors (eg, reduced clinical visits). Implementation facilitators included administrative funding for enrollment staff, bidirectional communication with community partners, adaptive strategies to identify eligible patients, and raising clinician awareness of Flex. In Flex enrollee interviews, those receiving nutrition services reported increased healthy eating and food security; they also reported higher program satisfaction than Flex enrollees receiving housing services. Enrollees who received nutrition services that allowed for selecting food based on preferences reported higher satisfaction than those not able to select food. Conclusions and Relevance: This mixed-methods qualitative evaluation study found that to improve implementation, Medicaid and health system programs that address social needs may benefit from providing funding for administrative costs, developing bidirectional data-sharing platforms, and tailoring support to patient preferences.

Chronotype Polygenic Score and the Timing and Quality of Workplace Cafeteria Purchases: Secondary Analysis of the ChooseWell 365 Randomized Controlled Trial.

Background: Studies on the link between chronotype (i.e., propensity for morning or evening preference) and dietary intake have relied on self-reported data, estimating consumption, and chronotype from questionnaires. Objectives: This study examined the associations between genetically proxied evening chronotype, objectively estimated workplace dietary choices, and the effectiveness of a behavioral intervention in hospital employees enrolled in the ChooseWell 365 study. Methods: ChooseWell 365 was a randomized trial of a 12-mo automated, personalized intervention to prevent weight gain and improve diet. Cafeteria sales data were used to measure the timing and healthfulness of workplace food purchases of employees during the 12-mo-long baseline, intervention, and postintervention follow-up periods. A genome-wide polygenic score for evening chronotype was calculated for all participants and the population was divided into quartiles; the highest quartile indicated the most evening chronotype. Associations between polygenic score quartiles and workplace purchases at baseline, 12 mo, and 24 mo and changes from baseline at 12 and 24 mo were tested using adjusted multivariable linear regression models. Results: At baseline, the highest chronotype quartile was associated with self-reported breakfast skipping. Over the 24-mo study, the highest quartile was associated with later timing of the first workplace purchase, but not with the healthfulness of purchases. There were no differences by the chronotype quartile in the effectiveness of the ChooseWell 365 intervention in improving employees' healthy food choices at work. Conclusions: A chronotype polygenic score was associated with breakfast skipping and later workplace mealtimes of hospital employees, but not with the nutritional quality of objectively measured workplace food purchases. In addition, employees across the chronotype spectrum benefited from the workplace healthy eating intervention.This trial was registered at clinicaltrials.gov as NCT02660086 (https://clinicaltrials.gov/ct2/show/NCT02660086?cond=NCT02660086&draw=2&rank=1).

Food Insecurity and Diet Quality Among Adults on Medicaid With and Without a Mental Illness Diagnosis.

BACKGROUND: Adults with mental illnesses are more likely to have low income and diet-related chronic diseases. OBJECTIVE: This study examined associations of mental illness diagnosis status with food insecurity and diet quality and whether the relationship between food security status and diet quality differed by mental illness diagnosis status in adult Medicaid beneficiaries. DESIGN: This was a secondary cross-sectional analysis of baseline (2019-2020) data collected as part of the LiveWell study, a longitudinal study evaluating a Medicaid food and housing program. PARTICIPANTS/SETTING: Participants were 846 adult Medicaid beneficiaries from an eastern Massachusetts health system. MAIN OUTCOME MEASURES: Food security was measured with the 10-item US Adult Food Security survey module (0 = high food security, 1-2 = marginal food security, 3-10 = low/very low food security). Mental illness diagnoses included health record-documented anxiety, depression, or serious mental illness (eg, schizophrenia, bipolar disorder). Healthy Eating Index (HEI-2015) scores were calculated from 24-hour dietary recalls. STATISTICAL ANALYSES: Multivariable regression analyses adjusted for demographics, income, and survey date. RESULTS: Participants' mean (standard deviation) age was 43.1 (11.3) years, and 75% were female, 54% Hispanic, 33% non-Hispanic White, and 9% non-Hispanic Black. Fewer than half (43%) of participants reported high food security, with almost one third (32%) reporting low or very low food security. The 341 (40%) participants with one or more mental illness diagnosis had greater odds of low/very low food security (adjusted odds ratio [OR], 1.94; 95% confidence interval [CI], 1.38-2.70) and had similar mean HEI-2015 scores (53.1 vs 56.0; P = 0.12) compared with participants with no mental illness diagnosis. Mean adjusted HEI-2015 scores did not significantly differ by high vs low/very low food security for those without a mental illness diagnosis (57.9 vs 54.9; P = 0.052) or those with a mental illness diagnosis (53.0 vs 52.9; P = 0.99). CONCLUSION: In a cohort of adults with Medicaid, those with mental illness diagnoses had higher odds of experiencing food insecurity. Overall, diet quality among adults in this sample was low but did not differ by mental illness diagnosis or food security status. These results highlight the importance of augmenting efforts to improve both food security and diet quality among all Medicaid participants.

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.

Employees' Baseline Food Choices and the Effect of a Workplace Intervention to Promote Healthy Eating: Secondary Analysis of the ChooseWell 365 Randomized Controlled Trial.

BACKGROUND: Little is known about whether the effectiveness of workplace wellness programs differs by employees' baseline health behaviors. OBJECTIVE: This study examined the association of baseline cafeteria food choices with the effect of a workplace intervention on cafeteria food choices, dietary quality, and body mass index (BMI). DESIGN: This was a secondary analysis of the ChooseWell 365 randomized controlled trial, testing a set of behavioral interventions to improve diet and prevent weight gain. PARTICIPANTS/SETTING: Participants were 602 employees of a Boston, MA, hospital who had purchased food from cafeterias, which used traffic-light food labeling. Data were collected in 2016-2020. INTERVENTION: The 12-month intervention (plus 12 months' follow-up) involved financial incentives and personalized feedback on cafeteria purchases. The control group received monthly letters with generic healthy eating and exercise tips. MAIN OUTCOME MEASURES: Healthy purchasing scores (HPS) were calculated by weighting color categories (red = 0, yellow = 0.5, green = 1) and scaling from 0 to 100 (healthiest); employees were categorized into baseline (pre-intervention) HPS tertiles (T1 = least healthy, T3 = healthiest). Healthy eating index (HEI-2015) scores were calculated from two 24-hour dietary recalls. Intervention effects on 12- and 24-month changes in HPS (primary outcome), HEI-2015 score, and BMI were compared among tertiles. Subgroup analyses examined whether changes by tertile varied with financial rewards received. STATISTICAL ANALYSES: Adjusting for baseline characteristics, multivariable linear regression assessed intervention effects across baseline HPS tertiles. RESULTS: Compared with T3, T1 employees had lower education; higher obesity, hypertension, and pre-diabetes; and lower HEI-2015 scores. The intervention increased HPS, but no change was observed in HEI-2015 scores or BMI; the intervention effect did not differ among tertiles at 12 or 24 months. Financial incentives were associated with a larger effect on 12-month HPS changes for T1 than for T2/T3 (P-interaction < 0.001). CONCLUSION: Compared with employees with healthier baseline food choices, employees with the least healthy food choices and highest cardiometabolic risk had similar improvements in the nutritional quality of cafeteria purchases as a result of the behavioral intervention, and they appeared to be more responsive to financial incentives.

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.

Tobacco-Related Disease, Health Beliefs, and Post-hospital Tobacco Abstinence.

INTRODUCTION: Most hospitalized patients who smoke resume after discharge. Associations of tobacco-related disease and health beliefs with post-hospitalization abstinence were examined. METHODS: This was a cohort study using data from a 2018-2020 multicenter trial of hospitalized adults who smoked and wanted to quit. Tobacco-related disease was defined using primary discharge diagnosis codes. Baseline health beliefs included (1) smoking caused hospitalization, (2) quitting speeds recovery, and (3) quitting prevents future illness. Outcomes included self-reported 7-day point prevalence abstinence 1, 3, and 6 months after discharge. Separate logistic regression models for each of the three health beliefs were constructed. Models stratified by tobacco-related disease explored effect modification. Analysis was performed in 2022-2023. RESULTS: Of 1,406 participants (mean age 52 years, 56% females, 77% non-Hispanic White), 31% had tobacco-related disease, 42% believed that smoking caused hospitalization, 68% believed that quitting speeds recovery, and 82% believed that quitting prevents future illness. Tobacco-related disease was associated with higher 1-month point prevalence abstinence in each health belief model (AOR=1.55, 95% CI=1.15, 2.10; 1.53, 95% CI=1.14, 2.05; and 1.64, 95% CI=1.24, 2.19, respectively) and higher 6-month point prevalence abstinence in models including health beliefs 2 and 3. Quitting speeds recovery was the only belief associated with higher 1-month point prevalence abstinence (AOR=1.39, 95% CI=1.05, 1.85). Among patients with tobacco-related disease, the belief that quitting prevents future illness was associated with higher 1-month point prevalence abstinence (AOR=2.00, 95% CI=1.06, 3.78). CONCLUSIONS: Tobacco-related disease predicts abstinence 1 and 6 months after hospitalization independent of health beliefs. Beliefs that quitting speeds recovery and prevents future illness may serve as targets for smoking-cessation interventions.

Smoke-Free Policies and Resident Turnover: An Evaluation in Massachusetts Public Housing From 2009‒2018.

INTRODUCTION: Smoke-free policies (SFP) in multi-unit housing are a promising tool for reducing exposure to tobacco smoke among residents. Concerns about increased housing instability due to voluntary or involuntary transitions induced by SFPs have been a primary barrier to greater widespread adoption. The impact of SFP implementation on transitions out of public housing in federally funded public housing authorities in Massachusetts was evaluated. METHODS: Tenancy data from the Department of Housing and Urban Development were used to determine the time from admission to transitioning out of public housing based on a cohort study design. Periods of exposure to SFPs were defined based on dates of SFP implementation at each PHA. Multi-level Cox regression models were fit to estimate the effects of SFPs on the hazard of transitioning, adjusting for household- and PHA-level characteristics. Analyses were conducted in 2021‒2022. RESULTS: There were 44,705 households with a record of residence in Massachusetts PHAs over 2009‒2018. Over this period, despite increasing adoption of SFPs among the PHAs, rates of transition remained steady at around 5‒8 transitions per 1,000 household-months. There was no overall association between exposure to SFPs and transitions among the full sample (adjusted HR=0.99, 95% CI=0.95, 1.04, p=0.794). However, the association varied significantly by age group, race/ethnicity, timing of SFP adoption, and era of admission. CONCLUSIONS: Adoption of SFPs in public housing had a minimal overall impact on turnover for households in Massachusetts, though disparities in the impact were observed between different demographic and PHA-level subgroups.

Underlying patterns of the co-occurrence of tobacco use and mental health among youth.

We aimed to examine how bidirectional relationships between mental health problems and tobacco use are formed over time by types of tobacco use in recent samples of U.S. youth. Data were drawn from Waves 1-4 of the Population Assessment of Tobacco and Health Study (N = 10,082) and analyzed using cross-lagged panel models. A high level of internalizing problems at Wave 1 predicted conventional cigarette smoking (adjusted odds ratio [AOR] = 1.19, 95% CI = 1.06-1.34) and e-cigarette use (AOR = 1.25, 95% CI = 1.09-1.43) at Wave 2, but not vice versa. Both cigarette smoking and e-cigarette use at Wave 2 tended to persist into Wave 3, which, in turn, increased the risk of subsequent internalizing problems in late adolescence or young adulthood (Wave 4). The bidirectional relationship between tobacco use and internalizing problems seems to begin as a procession from internalizing problems to tobacco use, and then from persistent tobacco use to exacerbated internalizing problems over time.

The association of impulsivity with effects of the ChooseWell 365 workplace nudge intervention on diet and weight.

Impulsivity is associated with unhealthy food choices. Nudge interventions in the food environment may be particularly helpful for individuals with high impulsivity. To examine if trait, choice, and action impulsivity were associated with the effectiveness of a workplace-based nudge intervention to improve diet and weight. This was a planned secondary analysis of 487 participants of ChooseWell 365, a randomized controlled trial that tested a 12-month nudge intervention to improve cafeteria purchases among hospital employees. Trait impulsivity was measured with the Barratt Impulsiveness Scale. Choice and action impulsivity were assessed with delay discounting and response inhibition tasks, respectively. Tertiles were generated for each measure. Multivariable regression models examined the association of impulsivity with cafeteria purchases [Healthy Purchasing Score (HPS)] over 12 months, dietary intake [Healthy Eating Index-2015 (HEI) score], and body mass index (BMI) measured at 12 months. Interaction terms tested differences in intervention effect by level of impulsivity. Participants with higher trait (p = .02) and choice (p < .001) impulsivity had lower baseline HPS than those with lower impulsivity. Employees of all impulsivity levels increased healthy eating, but higher trait impulsivity was associated with smaller increase in HPS over 12 months (p = .03). In the highest action impulsivity tertile, 12-month BMI increased less for intervention vs. control participants (0.3 vs. 0.5 kg/m2; p-interaction = .04). There were no interaction effects for trait or choice impulsivity. A workplace nudge intervention improved food choices among employees of all impulsivity levels and attenuated weight gain in those with higher action impulsivity.

Impulsivity is an individual trait characterized by the tendency to make quick or rash decisions. High impulsivity is associated with less healthy food choices and poorer health outcomes, including obesity. "Nudges", which are small interventions that steer people towards healthy choices without removing other options, may be particularly helpful for individuals with high impulsivity. Our study tested whether trait impulsivity (i.e., impulsive personality tendencies), choice impulsivity (i.e., preference for immediate vs. later rewards), and action impulsivity (i.e., low behavioral inhibition) were associated with the effectiveness of a workplace nudge intervention to increase healthy food choices and slow weight gain among hospital employees. We found that higher trait and choice impulsivity were associated with less healthy food purchases in the study population at baseline, but employees of all levels of impulsivity improved their food purchases in response to the intervention. The intervention may have helped slow weight gain in individuals with high action impulsivity.

Trends in cigarette use and health insurance coverage among US adults with mental health and substance use disorders.

AIMS: To estimate recent trends in cigarette use and health insurance coverage for United States adults with and without mental health and substance use disorders (MH/SUD). DESIGN: Event study analysis of smoking and insurance coverage trends among US adults with and without MH/SUD using 2008-19 public use data from the National Survey on Drug Use and Health, an annual, cross-sectional survey. SETTING: USA. PARTICIPANTS: A nationally representative sample of non-institutionalized respondents aged 18-64 years (n = 448 762). MEASUREMENTS: Outcome variables were three measures of recent cigarette use and one measure of past-year health insurance coverage. We compared outcomes between people with and without MH/SUD (MH disorder: past-year mental illness, predicted from Kessler-6 and the World Health Organization-Disability Assessment Schedule impairment scale; SUD: met survey-based DSM-IV criteria for past-year alcohol, cannabis, cocaine or heroin use disorder) and over time. FINDINGS: Comparing pooled data from 2008 to 2009 and from 2018 to 2019, current smoking rates of adults with MH/SUD decreased from 37.9 to 27.9% while current smoking rates of adults without MH/SUD decreased from 21.4 to 16.3%, a significant difference in decrease of 4.9 percentage points (pts) [95% confidence interval (CI) = 3.3-6.6 pts]. Daily smoking followed similar patterns (difference in decrease of 3.9 pts (95% CI = 2.3-5.4 pts). Recent smoking abstinence rates for adults with MH/SUD increased from 7.4 to 10.9%, while recent smoking abstinence rates for adults without MH/SUD increased from 9.6 to 12.0%, a difference in increase of 1.0 pts (95% CI = -3.0 to 0.9 pts). In 2018-19, 11% of net reductions in current smoking, 12% of net reductions in daily smoking and 12% of net increases in recent smoking abstinence coincided with greater gains in insurance coverage for adults with MH/SUD compared to those without MH/SUD. CONCLUSIONS: Improvements in smoking and abstinence outcomes for US adults with mental health and substance use disorders appear to be associated with increases in health insurance coverage.

A Pragmatic Cluster-Randomized Trial of Provider Education and Community Health Worker Support for Tobacco Cessation.

OBJECTIVE: Individuals with serious mental illness have a high prevalence of tobacco use disorder and related early mortality but underutilize smoking cessation medication. The authors determined whether clinician-delivered education to primary care providers regarding safety, efficacy, and importance of cessation medication (provider education [PE]) alone or combined with community health worker (CHW) support would increase tobacco abstinence in this population, compared with usual care. METHODS: All adult current tobacco smokers receiving psychiatric rehabilitation for serious mental illness through two community agencies in Greater Boston were eligible, regardless of readiness to quit smoking. Primary care clinics were cluster randomized to PE or usual care, with a nested, participant-level randomization to CHW or no CHW in PE-assigned clinics. The primary outcome was blindly assessed, biochemically verified tobacco abstinence at year 2. RESULTS: Overall, 1,010 eligible participants were enrolled. PE was delivered to providers in 53 of 55 assigned clinics; 220 of 336 CHW-assigned participants consented to CHW support. Year 2 abstinence rates were significantly higher among participants assigned to PE+CHW versus usual care (12% vs. 5%; adjusted odds ratio [AOR]=2.40, 95% confidence interval [CI]=1.20-4.79) or PE alone (12% vs. 7%; AOR=1.84, 95% CI=1.04-3.24). No effect of PE alone on abstinence was detected. Compared with participants assigned to usual care, those assigned to PE+CHW had greater odds of varenicline use (OR=2.77, 95% CI=1.61-4.75), which was associated with higher year 2 abstinence (OR=1.97, 95% CI=1.16-3.33). CONCLUSIONS: Combined PE and CHW tobacco cessation support increased tobacco abstinence rates among adults with serious mental illness.