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OBJECTIVE: Adults with serious mental illness have high rates of tobacco use disorder and underuse pharmacotherapy for tobacco cessation. In a previous randomized controlled trial, participants receiving community health worker (CHW) support and education for their primary care providers (PCPs) had higher tobacco abstinence rates at 2 years, partly because of increased initiation of tobacco-cessation pharmacotherapy. The authors aimed to determine the association between CHW-participant engagement and tobacco abstinence outcomes. METHODS: The authors conducted a secondary, mixed-methods analysis of 196 participants in the trial's intervention arm. Effects of the number and duration of CHW visits, number of smoking-cessation group sessions attended, and number of CHW-attended PCP visits on initiation of tobacco-cessation pharmacotherapy and tobacco abstinence were modeled via logistic regression. Interviews with 12 CHWs, 17 patient participants, and 17 PCPs were analyzed thematically. RESULTS: Year 2 tobacco abstinence was significantly associated with CHW visit number (OR=1.85, 95% CI=1.29-2.66), visit duration (OR=1.51, 95% CI=1.00-2.28), and number of group sessions attended (OR=1.85, 95% CI=1.33-2.58); effects on pharmacotherapy initiation were similar. One to three CHW visits per month across 2 years were optimal for achieving abstinence. Interviews identified CHW-patient engagement facilitators (i.e., trust, goal accountability, skills reinforcement, assistance in overcoming barriers to treatment access, and adherence). Training and supervision facilitated CHW effectiveness; barriers included PCPs' and care teams' limited understanding of the CHW role. CONCLUSIONS: Greater CHW-participant engagement, within feasible dose ranges, was associated with tobacco abstinence among adults with serious mental illness. Implementation of CHW interventions may benefit from further CHW training and integration within clinical teams.
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OBJECTIVES: Some people who stop smoking experience improved mood, but few studies have examined this relationship after hospitalization or accounted for concomitant substance use and psychological factors. We examined associations between smoking abstinence after a hospital discharge and change in depression and anxiety symptoms. METHODS: We conducted a secondary analysis of data from the Helping HAND 4 smoking cessation trial, which enrolled people who used tobacco when admitted to three academic medical center general hospitals. Participants (n = 986) were categorized as continuously abstinent (CA) or not. We used linear and logistic regression to model continuous and binary measures of depression (Patient Health Questionnaire [PHQ-8] ≥/<10), and anxiety (Generalized Anxiety Disorder Assessment [GAD-7], ≥/<8) over 6 months, adjusting for baseline mood, psychological factors, and substance use. Binary outcomes were defined using established clinical thresholds to aid in the clinical interpretation of the results. RESULTS: Mean age was 52.3 years, 56.5% were female, and the baseline mean cigarettes/day was 16.2 (SD: 3.2). In the adjusted analyses, depression and anxiety scores improved more in CA than non-CA participants over 6 months (difference-in-improvement, 2.43 [95% CI: 1.50-3.36] for PHQ-8; 3.04 [95% CI: 2.16-3.93] for GAD-7). At 6 months, CA participants were more likely to have a PHQ-8 score <10 (aOR = 2.07 [95% CI: 1.36-3.16]) and a GAD-7 score <8 (aOR = 2.90 [95% CI: 1.91-4.39]). CONCLUSIONS: Individuals who were CA, compared to those who were not, had fewer depression and anxiety symptoms at 6 months, and were twice as likely to score below the population screening thresholds for major depression and anxiety disorders. Clinicians should emphasize the association between continuous abstinence and improved mood symptoms after hospital discharge.
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Typical quantitative evaluations of public policies treat policies as a binary condition, without further attention to how policies are implemented. However, policy implementation plays an important role in how the policy impacts behavioral and health outcomes. The field of policy-focused implementation science is beginning to consider how policy implementation may be conceptualized in quantitative analyses (e.g., as a mediator or moderator), but less work has considered how to measure policy implementation for inclusion in quantitative work. To help address this gap, we discuss four design considerations for researchers interested in developing or identifying measures of policy implementation using three independent NIH-funded research projects studying e-cigarette, food, and mental health policies. Mini case studies of these considerations were developed via group discussions; we used the implementation research logic model to structure our discussions. Design considerations include (1) clearly specifying the implementation logic of the policy under study, (2) developing an interdisciplinary team consisting of policy practitioners and researchers with expertise in quantitative methods, public policy and law, implementation science, and subject matter knowledge, (3) using mixed methods to identify, measure, and analyze relevant policy implementation determinants and processes, and (4) building flexibility into project timelines to manage delays and challenges due to the real-world nature of policy. By applying these considerations in their own work, researchers can better identify or develop measures of policy implementation that fit their needs. The experiences of the three projects highlighted in this paper reinforce the need for high-quality and transferrable measures of policy implementation, an area where collaboration between implementation scientists and policy experts could be particularly fruitful. These measurement practices provide a foundation for the field to build on as attention to incorporating measures of policy implementation into quantitative evaluations grows and will help ensure that researchers are developing a more complete understanding of how policies impact health outcomes.
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Food choices are closely linked to culture, social relationships, and health. Because many adults spend up to half their time at work, the workplace provides a venue for changing population health-related behaviors and norms. It is unknown whether the effects of a workplace intervention to improve health behaviors might spread beyond participating employees due to social influence. ChooseWell 365 was a randomized controlled trial testing a 12-month healthy eating intervention grounded in principles of behavioral economics. This intervention leveraged an existing cafeteria traffic-light labeling system (green = healthy; red = unhealthy) in a large hospital workplace and demonstrated significant improvements in healthy food choices by employees in the intervention vs. control group. The current study used data from over 29 million dyadic purchasing events during the trial to test whether social ties to a trial participant co-worker (n = 299 intervention, n = 302 control) influenced the workplace food choices of non-participants (n = 7900). There was robust evidence that non-participants who were socially tied to more intervention group participants made healthier workplace food purchases overall, and purchased a greater proportion of healthy (i.e., green) food and beverages, and fewer unhealthy (i.e., red) beverages and modest evidence that the benefit of being tied to intervention participants was greater than being tied to control participants. Although individual-level effect sizes were small, a range of consistent findings indicated that this light-touch intervention yielded spillover effects of healthy eating behaviors on non-participants. Results suggest that workplace healthy eating interventions could have population benefits extending beyond participants.
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Conducta de Elección , Dieta Saludable , Preferencias Alimentarias , Promoción de la Salud , Lugar de Trabajo , Humanos , Lugar de Trabajo/psicología , Lugar de Trabajo/normas , Femenino , Masculino , Promoción de la Salud/métodos , Preferencias Alimentarias/psicología , Adulto , Dieta Saludable/psicología , Dieta Saludable/métodos , Persona de Mediana Edad , Conductas Relacionadas con la SaludRESUMEN
INTRODUCTION: As access to effective antiretroviral therapy (ART) has improved globally, tobacco-related illnesses, including cardiovascular disease, cancer and chronic respiratory conditions, account for a growing proportion of deaths among people with HIV (PWH). We estimated the impact of tobacco smoking and smoking cessation on life expectancy among PWH in South Africa. METHODS: In a microsimulation model, we simulated 18 cohorts of PWH with virologic suppression, each homogenous by sex, initial age (35y/45y/55y) and smoking status (current/former/never). Input parameters were from data sources published between 2008 and 2022. We used South African data to estimate age-stratified mortality hazard ratios: 1.2-2.3 (females)/1.1-1.9 (males) for people with current versus never smoking status; and 1.0-1.3 (females)/1.0-1.5 (males) for people with former versus never smoking status, depending on age at cessation. We assumed smoking status remains unchanged during the simulation; people who formerly smoked quit at model start. Simulated PWH face a monthly probability of disengagement from care and virologic non-suppression. In sensitivity analysis, we varied smoking-associated and HIV-associated mortality risks. Additionally, we estimated the total life-years gained if a proportion of all virologically suppressed PWH stopped smoking. RESULTS: Forty-five-year-old females/males with HIV with virologic suppression who smoke lose 5.3/3.7 life-years compared to PWH who never smoke. Smoking cessation at age 45y adds 3.4/2.4 life-years. Simulated PWH who continue smoking lose more life-years from smoking than from HIV (females, 5.3 vs. 3.0 life-years; males, 3.7 vs. 2.6 life-years). The impact of smoking and smoking cessation increase as smoking-associated mortality risks increase and HIV-associated mortality risks, including disengagement from care, decrease. Model results are most sensitive to the smoking-associated mortality hazard ratio; varying this parameter results in 1.0-5.1 life-years gained from cessation at age 45y. If 10-25% of virologically suppressed PWH aged 30-59y in South Africa stopped smoking now, 190,000-460,000 life-years would be gained. CONCLUSIONS: Among virologically suppressed PWH in South Africa, tobacco smoking decreases life expectancy more than HIV. Integrating tobacco cessation interventions into HIV care, as endorsed by the World Health Organization, could substantially improve life expectancy.
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Infecciones por VIH , Esperanza de Vida , Cese del Hábito de Fumar , Fumar Tabaco , Humanos , Masculino , Femenino , Infecciones por VIH/tratamiento farmacológico , Infecciones por VIH/mortalidad , Sudáfrica/epidemiología , Adulto , Cese del Hábito de Fumar/estadística & datos numéricos , Persona de Mediana Edad , Fumar Tabaco/epidemiología , Simulación por ComputadorRESUMEN
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.
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Microbioma Gastrointestinal , Humanos , Femenino , Masculino , Persona de Mediana Edad , Adulto , Dieta Saludable , DietaRESUMEN
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.
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Diabetes Mellitus Tipo 2 , Estado Prediabético , Adulto , Humanos , Femenino , Masculino , Hemoglobina Glucada , Medicaid , Abastecimiento de Alimentos/métodos , Dieta , Inseguridad AlimentariaRESUMEN
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.
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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.
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Detección Precoz del Cáncer , Neoplasias Pulmonares , Anciano , Humanos , Estados Unidos , Medicare , Práctica Clínica Basada en la Evidencia , Toma de DecisionesRESUMEN
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.
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Obesidad Infantil , Programas de Reducción de Peso , Humanos , Niño , Obesidad Infantil/prevención & control , Escolaridad , Registros Electrónicos de Salud , Promoción de la SaludRESUMEN
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.
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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 67â¯098 Medicaid ACO enrollees from March 2020 to July 2021 (mean [SD] age, 28.8 [18.7] years), 38â¯442 (57.3%) completed at least 1 social needs screening; 10â¯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.
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Organizaciones Responsables por la Atención , COVID-19 , Adulto , Niño , Estados Unidos , Humanos , Femenino , Persona de Mediana Edad , Masculino , Medicaid , Inestabilidad de Vivienda , MassachusettsRESUMEN
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).
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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.
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Abastecimiento de Alimentos , Medicaid , Estados Unidos , Adulto , Humanos , Femenino , Masculino , Estudios Longitudinales , Estudios Transversales , Dieta , Inseguridad AlimentariaRESUMEN
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.
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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.
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Preferencias Alimentarias , Predisposición Genética a la Enfermedad , Humanos , Estudios Retrospectivos , Lugar de Trabajo , Nutrientes , CarbohidratosRESUMEN
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.
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Nicotina , Cese del Hábito de Fumar , Humanos , Adulto , Cese del Hábito de Fumar/métodos , Dispositivos para Dejar de Fumar Tabaco , Agentes para el Cese del Hábito de Fumar , Alta del Paciente , Cuidados Posteriores , Nicotina/metabolismo , Masculino , Femenino , Persona de Mediana EdadRESUMEN
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.
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Dieta Saludable , Preferencias Alimentarias , Humanos , Dieta , Alimentos , Lugar de TrabajoRESUMEN
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 2021â2022. RESULTS: There were 44,705 households with a record of residence in Massachusetts PHAs over 2009â2018. Over this period, despite increasing adoption of SFPs among the PHAs, rates of transition remained steady at around 5â8 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.