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Climate change and transportation are both “wicked problems” characterized by their complexity, interconnectedness, and the dynamic nature of how potential solutions are evaluated and compared. They both also have broad, multidisciplinary implications for society, ranging from health to financial to environmental injustice. While multidimensional in nature, solutions to these twin challenges are often not evaluated multidimensionally, with cost-benefit analyses exclusively comparing, for example, environmental impacts to infrastructure costs or transportation travel time savings to project costs, with health implications ignored. Health impact assessments can be an effective way to include quantifiable health implications in cost-benefit analyses or even introduce health impacts into the policy discourse when they might have otherwise been overlooked. Transportation trips in the United States are dominated by single-occupancy vehicles, with implications for emissions, physical activity, and land use. Transitioning trips to active forms of transport, like walking and cycling, has the potential to reduce Transportation trips in the United States are dominated by single-occupancy vehicles, with implications for emissions, physical activity, and land use. Transitioning trips to active forms of transport, like walking and cycling, has the potential to reduce congestion, improve air quality, reduce greenhouse gas emissions, increase physical activity, open land to alternative uses, and improve health. It also has the potential to increase traffic fatalities, as these modes are more vulnerable than automobiles. However, typically these types of projects are evaluated from a policy perspective solely on the implications for the transportation system (e.g., travel time, congestion, wear and tear on roadways). Urban climate action plans, on the other hand, by their nature focus on mitigating greenhouse gas emissions that cause climate change and adapting urban areas to better manage the effects of a changing climate. However, because the sources of greenhouse gas emissions tend to also be sources of air pollution, these policies and interventions have the potential to affect local air quality and, with it, human health. In both cases – active transport polices and urban climate action plans – health effects are important “co-benefits” even if they are not the primary objective. In this dissertation, we conduct three health impact assessments to quantify health co-benefits of policy measures not primarily targeting health. Chapter 2 focuses on the physical activity health co-benefits of transportation policy that is primarily focused on reducing greenhouse gas emissions and is implemented at the county-level across the East Coast. We used modeled shifts in total walking and cycling miles traveled to estimate the net mortality impacts of nine cap-and-invest scenarios that might have been implemented across 13 states in the Transportation Climate Initiative. We found that all scenarios modeled would reduce net mortality in all 378 counties included; however, impacts would be concentrated in urban areas along the I-95 corridor. The monetized value of mortality benefits was estimated to exceed the infrastructure costs of walking and cycling improvements for all scenarios. Chapter 3 focuses on estimating the mortality impacts of shifting to more walking and cycling in the Greater Boston Area under different scenarios implemented at the individual level. We used data from the Massachusetts Travel Survey and the National Health and Nutrition Examination Survey to estimate baseline individual total physical activity for ~3 million residents of the Greater Boston Area. We then estimated mortality impacts from three different scenario concepts: 1) all residents meet the Surgeon General’s recommended activity level; 2) all residents increase activity by 15, 30, and 60 minutes more walking and cycling; and, 3) the City of Boston trip mode share shifts to match Amsterdam. We found that all scenarios had likely positive net mortality benefits. We found that scenarios that targeted the least active population had greater health impacts due to the non-linear nature of epidemiological concentration response functions used. We believe this suggests that individual modeling is helpful compared to aggregated population-level modeling when conducting similar studies. Informed by the challenge of increased traffic fatalities associated with walking and cycling activity in Chapters 2 and 3, Chapter 4 describes the disparities by race/ethnicity in traffic fatalities per mile-traveled for walking, cycling, and driving. We found disparities in fatality rates across all modes, with Black and Hispanic Americans dying at higher rates per mile-traveled than White or Asian Americans. Our findings suggest that disparities are greater than previously reported, including in official federal documents, due to our novel adjustment for differential miles traveled by race/ethnicity. As a policy consideration, we suggest that policymakers consider ways to address both systematic racism and road safety with recently approved federal transportation infrastructure resources. In the third health impact assessment (Chapter 5), we used air quality modeling to predict how fine particulate matter and ozone concentrations might shift across the region if only Boston eliminated emissions. We also estimated the mortality and morbidity health effects using U.S. EPA’s BenMAP program. We found that fine particulate matter would likely decrease across the region if Boston emissions were eliminated. Ozone concentrations, however, would likely increase in some areas and decrease in others, due to ozone’s more complex relationship with nitrogen dioxide. The net health impacts of eliminating Boston emissions would likely be large, and concentrated in non-Hispanic Black communities due to the environmental injustices present in current air quality. Overall, this dissertation contributes to the growing evidence base that documents the health co-benefits of transportation and climate action. We believe our findings suggest that policymakers would benefit from requiring consideration of how potential policies and programs affect the public’s health, even when health impacts are ancillary to primary policy or programmatic objectives.

The quality of human service delivery, in the fields of social welfare, health, and education, is influenced by the quality of the interpersonal relationships between the service provider and the client. Achieving programmatic outcomes in human services requires high-quality social interactions. Early childhood education is a human service delivery model in which workplace functioning requires intensive human interaction. The quality of the social interactions among staff members and between staff and clients (children and their families) is a key factor in how successful these programs are in achieving their goals. Head Start, the nation’s largest publicly-funded early childhood education program, is based on a service model that provides educational, social, and health services through center-based classrooms and/or home visits to low-income children, from gestation through 5 years of age. Despite the importance of interpersonal relationships in Head Start achieving its programmatic goals, little is known about what factors are associated with high levels of functioning as it pertains the interpersonal relationships among staff in Head Start. This dissertation examines the association between dispositional mindfulness and work-related functioning outcomes designed to capture dimensions of or characteristics that promote high interpersonal relationship quality in three distinct Head Start staff types. The implications of the findings for Head Start and other human service delivery models are discussed. / Public Health

ABSTRACT Introduction: The present study examined whether social support served as a mediator (i.e., an apparent causal mechanism) for the relationship between mental illness (MI) and drug and/or alcohol abuse (SA). Objective: This study’s objective was to determine the role of social support as a potential mediator in the relationship between mental illness and drug and/or alcohol abuse. Methods: We utilized data from a randomized controlled trial (RCT), conducted on individuals at risk for HIV in Philadelphia jails by following 600 study participants coming out of jails. Out of these 600 individuals, data was selected for individuals with mental illness and drug and/or alcohol abuse. In the parent study, these individuals were identified by asking questions about their mental illness, and drug and/or alcohol abuse problems. They also answered Norbeck Social Support Questionnaire about social support. They provided demographic data on their age, race, gender, religion, marital status and education level, which was collected as part of a face-to-face demographic interview conducted during the baseline assessment. Results: Data was analyzed using negative binomial regression method to test for mediation effect. Results indicated that social support mediated the relationship between mental illness and drug abuse. We ran two generalized linear and one general linear regression models. In the first model, we looked at the total effect of mental illness on drug abuse (c); we found that the incidence rate for drug abuse (SA) would be expected to increase by a factor of 1.387, (IRR,1.387; CI,1.270-1.515; P =0.000) for every one-unit increase in mental illness (M1), while holding all other variables in the model constant. In the second model we adjusted our mediator, social support (SS) and looked at the direct effect of mental illness on drug abuse (c’). We interpreted that for every one-unit increase in mental illness, the incidence rate for drug abuse would be expected to increase by a factor of 2.717, (IRR,2.717; 95% CI,1.629 - 4.532; P = .000). For every one-unit increase in social support, the incidence rate for drug abuse is expected to decrease by a factor of .498, (IRR,.498; 95% CI,.443 - .560; P = .000). In the third model we found, for every one-unit increase in mental illness, there is an associated increase by 2.495 units in social support, P= .000. There was an inconsistent mediation in our model. Effect size for mediation by Percent mediation (Pm) method was found to be 0.64, it is the proportion of the effect that is mediated by our mediator social support. Sobel test showed the significance of mediation with a test statistic of 4.8282 at a significance level of 0.000. Conclusion: Our data supported an alternative theory of inconsistent mediation. We found that social support mediates the relationship between mental illness and drug abuse, where positive social support has a stimulator effect on mental illness and a suppressor effect on drug abuse. Mental illness may have direct unfavorable effects on the drug abuse (outcome) and positive social network has beneficial effects on this outcome. We conclude that positive support allows betterment of mental health of patients and prevents involvement in drug abuse. Further, there is a need to consider both the positive and negative effects of social support while keeping in mind these associations may differ among sociodemographic groups. / Public Health

Introduction Obesity continues to overwhelm health care in the US with 33.1% of adults overweight, and 35.7% of adults obese.1 Obesity causes the atherometabolic syndrome, which includes the deadly triad of dysglycemia, atherogenic dyslipoproteinemia, and hypertension, and is associated with other health problems such as the development of type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), atherosclerotic cardiovascular disease, increased risk of certain cancers, degenerative joint disease, sleep apnea, and asthma. Favorable changes in lifestyle remain difficult to achieve, and so clinicians now rely heavily on weight-loss medications and bariatric surgery for the treatment of obesity and its associated health problems. Because of the zeal with which many people use smartphone applications (“apps”), several research groups have attempted to use applications as tools for lifestyle interventions. The applications are used primarily as instruments to decrease caloric consumption and increase physical activity. We conducted a meta-analysis of published studies to determine the strength of current evidence for an effect of smartphone applications on body weight in overweight and obese subjects. Methods We performed searches in databases including PubMed, Embase, Web of Science, SCOPUS, and psycINFO. Randomized controlled clinical trials in adolescents or adults that included weight as a primary or secondary outcome and used smartphone applications in lifestyle interventions were selected for analysis. Only randomized clinical trials (RCTs) that specifically compared subjects randomized to use, or to not use, a smartphone app. Results Of 302 published studies on smartphone applications and weight loss, only 12 met our inclusion and exclusion criteria for our meta-analysis. The longest duration to measure weight outcome was 24 months. Taken individually, only 10 of the 12 studies reported statistically significantly more weight loss with versus without a smartphone app, and 2 studies reported significantly less weight loss with versus without a smartphone application. Moreover, there was considerable heterogeneity amongst the 12 studies in the smartphone applications they used and how they tested them. Nevertheless, in our meta-analysis combining the 12 studies, we found a statistically significant Hedges’ g effect size of -2.260 (95% CI: -3.251 to -1.269, p<0.001, I2 = 98.591%) from the use of smartphone applications as part of a weight loss intervention. Conclusion Despite the low number of qualifying studies and their heterogeneity, our meta-analysis suggests that smartphone applications may be useful tools for lifestyle interventions for weight loss. Areas of need include longer-term studies and studies that examine hard clinical endpoints, such as effects on progression to T2DM or atherosclerotic cardiovascular events. / Clinical Research and Translational Medicine

The use of mobile communication devices (MCDs) by drivers is a significant public health problem. Research suggests that MCD use plays a role in almost 400,000 traffic crashes each year, resulting in over 3,000 deaths (NHTSA, 2013). Drivers using an MCD are as much as four times more likely to crash as other motorists (Redelmeier & Tibshirani, 1997). Since 2001 forty-eight states have adopted one or more laws aimed at reducing the use of MCDs by drivers, many of which have been strengthened through subsequent amendments. Evaluations have yielded a mixed picture of their effectiveness (Braitman & McCartt, 2010; Highway Loss Data Institute, 2010; McCartt & Geary, 2004; McCartt, Hellinga, Strouse, & Farmer, 2010). Existing studies, however, have been limited by various design features. This study employs time-series methods to explore whether laws prohibiting use of MCDs by young drivers effectively reduce crash fatalities. The quasi-experimental design relies on an identification strategy that is common in empirical legal studies but has not yet been applied to laws regulating driver MCD use. The implementation of the identification strategy leverages the developing concept of legal epidemiology. Four state laws are ultimately evaluated. The primary analytic approach is difference-in-difference. In two of the four instances, there is some evidence suggesting a protective effect could be attributed to the law. However, this evidence was limited and differed in relation to specification choices. These findings cast doubt on some fifty state panel analyses that have suggested that laws are effectively decreasing MCD use and associated harms. / Public Health

BACKGROUND: The local public health workforce in the United States is severely depleted, requiring a coordinated approach to re-build and repair the public health infrastructure to respond to community needs appropriately and efficiently. One important strategy is the recruitment of public health graduates by pipeline programs that recruit students to roles in local public health through applied practice experiences and enrichment activities. However, few published studies exist on pipeline programs that target local public health and of those that do, few describe components of their program, outcomes, and lessons learned to inform future adaptations, expansion, and replication. Rigorous evaluation is a necessity to inform training and career preparedness programs, barriers and facilitators to implementation of those programs, and outcomes and competencies that are most effectively achieved through the programs. These results inform future design and use of these programs to be most effective in training the next generation of public health professionals. This dissertation fills this evidence gap and aims to identify factors that support effective implementation and achievement of outcomes in the context of a specific pipeline program through a thorough scoping review and subsequent mixed methods evaluation. METHODS: A two-pronged approach was used to address the aims. First, to understand the national landscape, a scoping review of peer-reviewed literature was conducted regarding public health work-education programs in the United States. The scoping review resulted in 34 programs and formed the basis for a typology of work-education programs. The typology classified differences across three program types and was differentiated by ten characteristics. Second, a mixed methods process and outcome evaluation was conducted on the Academic Public Health Corps (APHC) program in Massachusetts, a 160-hour, public health student workforce pipeline program established in 2021, to provide insights on a novel work-education program. The CDC Framework for Evaluation provided the foundation for the evaluation design and the Practical, Robust Implementation and Sustainability Model (PRISM) guided data collection and analysis. Study participants included stakeholders (e.g., APHC leaders and staff) and students, or “Corps members”. Quantitative data included stakeholder surveys (n=12), Corps member surveys (n=63) and qualitative data included key informant interviews (n=17), focus groups (n=4) and an assessment of APHC program artifacts. Thematic analysis and a matched pre-post survey design were used to identify the barriers and facilitators of the APHC program. Additionally, Corps member achievement of knowledge and skills were assessed across five domains as well as intention to pursue a career in local public health. RESULTS: First, the scoping review and typology illustrated the spectrum of work-education programs and the significant variability that exists with each work-education program including the knowledge and skill objectives, applied practice experiences, mentorship, networking, and reflection. Second, the mixed methods evaluation revealed the APHC program increased local health department capacity through student-based project assignments and provided a positive learning experience for students. Pre- and post-survey resulted in mean increases in select competencies within each of the five public health domains. Students indicated the APHC program enrichment activities exposed them to different career pathways in local public health, including the breadth and depth of roles available for new graduates. Post-survey results indicated that students are interested in pursuing a role in state or local public health. Qualitative findings provided further context with students’ need to continue to explore their career options and may require more time. Stakeholders and students noted barriers limiting the APHC as a pipeline program and qualitative findings suggest that there are critical gaps in program design and operating practices that would benefit from enhancement. CONCLUSIONS: Rebuilding the local public health workforce requires strategies to recruit new talent to promote and preserve the health of communities. Collaboration between academic partners, State and Local Health Departments, and other community partners are needed to build pipeline programs that inspire students to pursue a career in local public health. This study explored an evaluation of a novel workforce pipeline program and identified best practices and lessons learned to support student public health recruitment. As state agencies, public health practitioners, associations, and/or local health departments contemplate a new program or enhance an existing program, the scoping review and mixed-methods evaluation identified five areas of consideration for successful program design: (1) defining the strategic vision of program, (2) using evidence-based approaches, (3) developing and defining collaborative partnerships, (4) establishing performance measurement standards, and (5) developing a sustainability and maintenance framework. / 2026-05-10T00:00:00Z

Eating and drinking are human behaviors that most people take for granted. They are a prerequisite for proper nutrition, but they also define people personally and culturally. Unfortunately, every year 1 in 25 people experience trouble swallowing (dysphagia). Dysphagia is associated with reduction in quality of life, and increased risk of weight loss, dehydration, malnutrition, pneumonia, and death. The nature and severity of dysphagia is commonly assessed with Flexible Endoscopic Evaluation of Swallowing (FEES). A FEES exam allows direct observation of food/liquid passing through the throat, and allows a clinician to assess swallow safety and efficiency. Swallow efficiency, a critical aspect of the swallow evaluation, is assessed by measuring the severity of residue, defined by food/liquid left in the throat after a swallow. In the absence of well-designed measurement tools, residue is often assessed as “none/mild/moderate/severe” without operational definitions which hinders meaningful measurement or communication of swallow dysfunction. In addition to FEES, a variety of clinical procedures and patient reported outcome questionnaires can be used to evaluate the nature and severity of a patient’s dysphagia. However, there are no universally recognized evidence-based guidelines that inform treating clinicians as to which clinical procedures and which questionnaires should be employed to optimize dysphagia assessment and treatment outcomes. It is unknown whether this lack of guidance leads to inadvertent and/or inequitable variation in dysphagia assessment practices. To address these dysphagia assessment challenges, three projects were conducted. Project 1 entailed comprehensive reliability and validity testing of a novel visuoperceptual residue rating scale called BRACS. Project 2 entailed establishing preliminary BRACS interpretability using modified Delphi and bookmarking methodologies to identify clinically meaningful BRACS score categories. Projects 1&2 demonstrated that BRACS is a psychometrically sound residue rating instrument that can be confidently incorporated into clinical practice and as a clinical trial outcome. Project 3, which was distinct from projects 1&2, explored whether clinician and patient factors were associated with variable dysphagia assessment practices, namely provision of patient reported outcome questionnaires. Five drivers of variation were identified, paving the way for replication studies and remediation strategies aimed at minimizing assessment variation, and maximizing clinical care equity. / 2026-05-10T00:00:00Z

BACKGROUND: Improving adherence to antiretroviral therapy (ART) is crucial for achieving HIV epidemic control in South Africa. The SUSTAIN trial aims to identify the most cost-effective package of evidence-based strategies for adherence monitoring (pharmacy refill monitoring (PRM), electronic adherence monitoring (EAM), viral load (VL) monitoring) and support (check-in texts (SMS), enhanced adherence counselling (EC)) for patients newly initiating ART. Participants were randomized to receive one of sixteen combinations of interventions using a multi-phase optimization strategy design. METHODS: First, a cost analysis of implementing SUSTAIN interventions for the first cohort (n=260) of participants was conducted from a health system perspective, using a micro-costing approach that employed three data collection methods: self-reported time and cost worksheets, independent staff observation, and discussions with staff during site visits. Second, a cost-effectiveness analysis was conducted using costing and adherence data from SUSTAIN participants to explore costs for achieving >80%, >90%, and >95% adherence for each intervention component. Third, a forward-looking costing model estimated costs for scaling up the interventions in a real-world setting (City of Cape Town) over a 10-year time horizon. All cost analyses were adjusted for inflation and discounted using an annual rate of 3%. RESULTS: The costs for one person-year of participation in SUSTAIN were $12 for PRM, $25 for VL monitoring, $162 for EAM, $16 for EC and $42 for SMS. Cost-effectiveness analyses showed PRM was cost-saving versus EAM and VL monitoring for achieving all categories of adherence. For support interventions, EC was cost-saving compared to SMS for achieving all categories of adherence. Estimated per annum future costs per patient ranged from $11–$25 for general program costs, $12–$20 for VL monitoring, $69–$122 for EAM, $3–$5 for PRM, $12–$14 for SMS, and $16–$31 for EC. A cost-effectiveness analysis of future costs found SMS would be more cost-saving than EC; the monitoring interventions remained the same. CONCLUSION: EAM was costliest due to high technology costs; however, these will decrease with mass production if scaled up. Pending final cost-effectiveness results from the main SUSTAIN trial, a differentiated approach based on cost and sensitivity of monitoring interventions could be considered for those restarting versus initiating ART. Support options require further investigation.