With the rapid growth and diversity of HIV-related data sources, there is increasing consensus that data integration is a valuable tool that can help advance knowledge in HIV prevention and treatment. We conducted a scoping review to analyze the data integration methods used to combine HIV-related data from heterogeneous, multi-level sources and to summarize the emerging themes and concepts. Through a structured search of PubMed, EMBASE, and Web of Science for articles published between 1994 and 2025, we identified 47 articles that employed one or more of four main data integration methods: record linkage, multiple-frame methods, imputation-based methods, and modeling. Five main themes emerged from the research goals of the included studies: etiology and prognosis; database development and operationalization; HIV-related risk factors; population size estimation; and HIV or HIV-related factor prevalence estimation. Multiple-frame methods were the most prevalent data integration technique (51
Antimicrobial resistance genes (ARGs) are often transmitted among microbes via mobile genetic elements (MGEs), but few antimicrobial resistance (AMR) surveillance programs incorporate MGEs. This review presents our current understanding of the role of MGEs in AMR dynamics with examples and recommendations for their inclusion in AMR surveillance. MGEs have been incorporated successfully in retrospective AMR outbreak investigation, but are not yet considered in prospective surveillance programs. We recommend the development of standardized approaches for inclusion of MGEs in AMR surveillance systems.
Mobile cancer screening services in the US aim to expand access to underserved and frequently underscreened populations. As screening approaches evolve in complexity (e.g., risk stratification, supplemental modalities), there is a need for updated reviews to understand how mobile screening programs are implemented, identify gaps in incorporating new screening complexities, and identify research and implementation priorities to best optimize the impact of mobile cancer screening on underscreened populations. This scoping review synthesizes information from 36 articles published from 2010 to 2025 on the development, implementation, and evaluation of mobile breast and lung cancer screening services in the U.S. The review further summarizes reported barriers and facilitators to mobile screening services, reported performance outcomes, and how community engagement strategies are incorporated in mobile cancer screening planning, delivery, and evaluation. Most articles describe using community outreach or consultation, with few reaching community collaboration or shared leadership. We identify research directions to inform effective mobile cancer screening programs, including comparative studies to identify optimal development or implementation strategies and greater community collaboration.
The pediatric metabolic syndrome (MetS) construct lacks an accepted definition, with frameworks yielding prevalence estimates that vary by an order of magnitude within the same populations. In 2023, the American Heart Association introduced cardiovascular-kidney-metabolic (CKM) syndrome, a staged model linking adiposity, metabolic risk, chronic kidney disease, and cardiovascular disease across the life course. This scoping review maps pediatric MetS definitions and prevalence, the longitudinal links between childhood metabolic risk and adult outcomes, how the CKM framework applies to youth, and the gaps in adapting CKM staging to children and adolescents. Across 53 included sources, five major pediatric definitions yielded prevalence estimates of 0.3
Hypertension, a leading modifiable risk factor for cardiovascular diseases, is projected to contribute substantially to the global burden of cardiovascular health by 2050. Sleep has emerged as a potential factor in the prevention and management of hypertension. This review synthesizes recent evidence on the relationship between sleep health dimensions and hypertension, highlighting clinical significance, identifying gaps, and outlining future research directions. Prolonged sleep latency, greater wake after sleep onset, both short and long sleep duration, poor overall sleep quality, and reduced sleep efficiency are associated with a higher risk of hypertension. However, most studies are cross-sectional and rely primarily on subjective measures, often limited to sleep duration. A multidimensional approach to sleep health may reduce hypertension risk and improve blood pressure control. More longitudinal and intervention studies in varied populations are needed to develop tailored sleep health recommendations and guide clinical guidelines.
Spatial data and spatially enabled tools are now embedded in routine epidemiologic practice, yet their widespread availability has outpaced explicit attention to the conceptual reasoning that should guide their use. This review asks how epidemiologists can more deliberately bring spatial thinking — reasoning about place, scale, and spatial relationships — to bear before choosing analytic methods, and what conceptual frameworks best support that process. The geographic and spatial statistical literatures offer three foundational components of spatial thinking: concepts of space and place, representations of space and place, and processes of spatial reasoning. Epidemiologic conceptualizations of place have evolved across four frameworks — place as container, cause, modifier, and dynamic system — each of which foregrounds different questions and methods. Methodological work highlights persistent challenges including the modifiable areal unit problem, scale-data misalignment, and the ways that analytic choices can quietly redefine the estimand. Spatial thinking should precede and structure spatial analysis rather than follow it. Organizing that thinking around three recurring epidemiologic questions — whether meaningful spatial heterogeneity exists, whether spatial dependence is substantively informative, and how places are relationally connected — clarifies the inferential target and improves analytic coherence. Spatial approaches yield their greatest epidemiologic value when grounded in explicit conceptual framing and when maps and models are understood as representations of ongoing population processes rather than causal endpoints.
Candidozyma auris is an emerging fungal pathogen characterized by multi-drug resistance, high mortality, and a unique ability to persist in healthcare environments. U.S. cases increased significantly since 2019, and screening methodology remains logistically challenging. This review evaluates the efficacy and operation impact of three possible screening methods: Active Surveillance (AS), Point Prevalence Survey (PPS), and Epidemiological Linkage (Epi-link). A review of published reports indicates that test positivity varies widely, ranging from 0
Target trial emulation is a methodological framework designed to emulate hypothetical randomized controlled trials using observational data, particularly when conducting actual trials is unethical or infeasible. Non-pharmaceutical interventions, such as dietary patterns, physical activity, and environmental exposures, require unique methodological considerations for target trial emulation compared to pharmaceutical interventions. In this review, we aim to familiarize researchers with the key methodological challenges involved in emulating target trials of non-pharmaceutical interventions and to offer evidence-based recommendations for addressing these challenges. We outline the fundamental assumptions necessary for valid causal inference when emulating a target trial: consistency, exchangeability, and positivity. We examine why these assumptions are particularly challenging to uphold for non-pharmaceutical interventions compared to pharmaceutical exposures. Next, we review recent work on non-pharmaceutical interventions studied using target trial emulation and highlight five methodological challenges that threaten the validity of causal assumptions: ill-defined interventions, intervention heterogeneity, uncommon or infeasible strategies, unclear time zero, and periodic measurement with sustained adherence assumptions. We map each challenge to specific components of the target trial protocol. To demonstrate how these challenges manifest in practice, we present a case study of maternal dairy intake and risk of child allergies and conclude with practical recommendations for mitigating each challenge. The framework and strategies outlined in this review will enable researchers to rigorously apply target trial emulation to non-pharmaceutical interventions, shifting the focus from documenting associations to estimating causal effects and strengthening the role of observational research in guiding evidence-based population health research.
This review aims to synthesize the current literature on how Community Health Workers (CHWs) are leveraging Artificial Intelligence (AI). By examining how CHWs are interacting with AI in healthcare settings, it seeks to propose novel research opportunities and identify critical challenges that, when addressed, can effectively enhance cardiovascular health outcomes for adults with limited health literacy. Most of the studies were conducted outside the United States. Very few presented empirical findings, addressed literacy, or discussed implications for cardiovascular disease. We identified several opportunities for researchers and policymakers around CHW+AI efforts in cardiovascular health and health literacy. These opportunities range from testing their ability to bridge communication gaps in written and spoken language to improving CHWs skills related to AI literacy (e.g., ability to understand and effectively use AI tools), health literacy (e.g., the ability to find, understand, and use information and services to make informed health-related decisions), and understanding of strategies to promote cardiovascular health. However, more work needs to be done in the United States, and integrating AI introduces critical challenges that still have not been addressed.
Ambient air pollution drives cardiovascular disease (CVD), yet single-pollutant models overlook how risk emerges within broader environmental and structural contexts. This review applies the Public Health Exposome (PHE) framework, which integrates natural, built, social, and policy environments, to show how multilevel systems shape CVD vulnerability. Extreme heat, humidity, and climate variability modify pollutant toxicity, while structural inequities, discriminatory policies, and inadequate planning intensify exposures in marginalized communities. Cumulative psychosocial stress further amplifies inflammatory responses, activating the endo-exposome. Multi-omics studies reveal that pollution alters epigenomic, transcriptomic, and metabolomic pathways linked to inflammation, oxidative stress, and endothelial dysfunction. Emerging tools like machine learning, high-resolution exposure modeling, graph-based analytics, and wearable sensing, enable integration of environmental data and support systems-level approaches. The PHE framework illustrates how layered environmental and structural stressors accumulate to elevate CVD risk. Reducing this burden requires coupling PHE science with equitable public policy.
This scoping review focused on the use of large language models (LLMs) to extract clinically-relevant heart failure (HF) information from electronic health records (EHRs). We identified 10 studies that focused on the ability of LLMs to extract HF data from EHRs and to clinically use the data. While early demonstrations of extraction accuracy and clinical prediction endpoints were encouraging, some studies offered limited descriptions of baseline characteristics and most studies had clinical endpoints that lacked specificity relevant to heart failure phenotype, goal-directed medical therapy, medication titration, and other important evidence-based domains known to impact clinical outcomes in heart failure. Even with the application of a comprehensive search strategy, relatively few studies were identified meeting the pre-specified criteria for inclusion in this review. All included studies that met criteria were retrospective with some case control designed studies. Additional LLM studies are needed to better define how heart failure diagnosis, prevention, management, and treatment can benefit from the use of large language models associated with electronic medical records. This is particularly true for areas of interest where LLM analytics may be applied (e.g., early diagnosis, HF phenotype and treatment variation, medication adherence, medication titration) to further advance the evidence-base for diagnosis and phenotype-specific treatment, deepen understanding barriers to treatment and management, and close adoption gaps widened by variations in clinician behavior.
Sedentary behavior is increasingly recognized as an independent risk factor for cardiovascular disease (CVD), yet prevention efforts continue to emphasize aerobic exercise while underutilizing resistance training (RT). This review synthesizes recent evidence (2018–2025) examining how sedentary behavior, physical activity, and RT jointly influence cardiovascular risk, with particular attention to translational and population health implications. Large-scale epidemiologic studies consistently link prolonged sedentary time to increased cardiovascular morbidity and mortality, even among physically active adults. Emerging mechanistic and intervention evidence demonstrates that RT favorably modifies vascular function, metabolic health, autonomic regulation, and functional capacity. Community- and clinic-based RT interventions show promise in reducing sedentary risk, particularly among older adults and high-risk populations. Reframing cardiovascular prevention to explicitly include RT offers a scalable, equitable, and physiologically targeted strategy to counteract sedentary behavior–related cardiovascular risk. Greater integration of RT into research, practice, and policy is warranted globally.
Autistic individuals—representing one in 31 individuals in the U.S.—experience disproportionate poor cardiovascular health. This review synthesizes the current evidence on cardiovascular health in autism, with attention to epidemiology, modifying factors, mechanistic pathways, and implications for future research and practice. Evidence from population-based cohorts and systematic reviews demonstrates elevated cardiovascular risk factors among autistic individuals, driven by interacting behavioral, biological, psychosocial, and environmental pathways and modified by individual and family characteristics. Studies are limited by methodological challenges and future research should: (1) focus on comprehensive assessments of cardiovascular health, (2) align with developmental science, (3) integrate multiple levels of analysis, (4) evaluate associations between mental and physical health, and (5) shift from autism biomarkers to health biomarkers. Cardiovascular health is an urgent priority for autistic individuals and there is a need for improved research to inform effective health interventions for this population.
Homelessness is a rapidly escalating crisis. People experiencing homelessness (PEH) face intersecting social and health vulnerabilities that increase their risk of burn injury and complicate recovery. This scoping review synthesizes evidence on burn injuries among PEH and contrasts their epidemiology with domiciled people (DP) to inform prevention and health system strengthening. We conducted a scoping review guided by Arksey and O’Malley’s methodological framework and reported according to the PRISMA Extension for Scoping Reviews. Systematic searches were performed in seven bibliographic databases to identify literature published between 1990 and 2025. A narrative synthesis was completed to characterize the risks and incidence of burn injuries among PEH, describe their injury patterns, recovery and rehabilitation, and compare with DP. The search and analysis were completed in 2025.Thirty-seven reports were analyzed. Within the U.S., PEH were more often male, of White or Black race, had histories of substance use and mental illness, and were more likely to sustain injuries from fire, assault and selfimmolation compared to DP. West Coast data suggested larger burn sizes among PEH compared to DP, whereas national and other regional data reported no differences. Compared to DP, PEH experienced longer hospitalizations, incurred higher charges, were more likely to leave against medical advice, and were less likely to receive follow-up care. No consistent differences were found in rates of inhalation injury, amputations, inpatient complications, or mortality. Developing effective burn prevention strategies and strengthening burn care for PEH requires recognizing their unique injury patterns, care needs, and recovery challenges. Our findings emphasize the importance of targeted prevention and integrated trauma-informed care pathways that address both burn management and social and behavioral health needs.
Early life constitutes a critical developmental window during which environmental exposures can permanently alter physiological trajectories, thereby influencing long-term susceptibility to allergic diseases. Polycystic ovary syndrome (PCOS), the most prevalent endocrine disorder in reproductive-aged women, is characterized by a constellation of metabolic and endocrine abnormalities—including obesity, insulin resistance, immune dysregulation, vitamin D deficiency, and steroid hormone dysregulation. This review aims to synthesize and evaluate the evidence for an association between these multifaceted maternal features and an increased risk of allergic diseases, particularly asthma, in offspring. Despite growing interest, the specific role of PCOS in offspring asthma remains incompletely understood. This review synthesizes current observational evidence linking maternal PCOS to offspring allergic diseases, with a focus on asthma. By integrating findings from human cohorts, animal models, and mechanistic studies, the available evidence illustrates how PCOS-associated maternal metabolic/endocrine derangements may interfere with fetal immune development and prime offspring for allergic sensitization. Recent investigations have also begun to elucidate emerging epigenetic mechanisms (e.g., DNA methylation) that may mediate these transgenerational effects, offering a framework for identifying novel biomarkers and preventive targets. This work broadens the etiological understanding of asthma’s developmental origins by linking a common maternal endocrine disorder to offspring allergic susceptibility. Ultimately, it aims to provide actionable insights for early-life intervention strategies, emphasizing the potential to mitigate asthma risk through targeted management of PCOS-related maternal metabolic and endocrine health.
Herpes zoster (HZ), or shingles, is caused by reactivation of varicella-zoster virus (VZV), the virus responsible for chickenpox. We aim to characterize the global landscape of national vaccination recommendations for the use of recombinant zoster vaccine (RZV; Shingrix®, GSK). A recent systematic review found a cumulative incidence of HZ among adults aged ≥ 50 years of 2.9–19.5 cases per 1,000 individuals. In 2017, the US and Canada authorized Shingrix for this age group. Shingrix has now been approved for use in dozens of countries. We identified information about Shingrix national vaccination recommendations in 30 of 52 countries (58
The 66 million Americans who live in rural areas experience notable cancer disparities. It is imperative to examine the spatial elements of these disparities to know how to best target policies and interventions. Our review summarizes spatial methods in rural cancer control research. Spatial methods relevant for rural cancer control research range from identifying patterns to spatial accessibility to regression approaches. Recent applications have adapted to the new rural health landscape by considering the role of telehealth in spatial accessibility measures and the impact of rural hospital closures in multilevel regression modeling with spatial considerations. Further, research continues to innovate on small area estimation techniques to provide useful risk factor and burden estimates to inform interventions. As rural cancer disparities persist, it is critical that researchers continue to develop and adapt spatial methods that will best inform policies and interventions to reduce these disparities.
In the US, people with HIV (PWH) are more likely to be diagnosed with cancer at advanced stages, contributing to higher cancer-specific mortality rates. As such, the leading cause of non-AIDS death among PWH is cancer, including cancers with guideline recommended screening as a part of preventative care. Nonmedical drivers of health contribute to poor access to timely cancer screening among PWH. Thus, the purpose of this systematic review is to summarize the available evidence on the relationship between social determinants of health (SDoH) and cancer screening behaviors among PWH in the US. Following PRISMA guidelines, we conducted a systematic search for peer-reviewed US-specific studies published between 2010–2024 using PubMed, Embase, CINAHL, and Web of Science. Our search strategy included key terms that fell under four key concepts: 1. SDoH, 2. HIV, 3. Cancers of interest, and 4. Outcomes of interest. Of the 2334 articles identified, 1146 underwent title/abstract screening and 86 full-length articles were reviewed for eligibility. Overall, 40 articles met eligibility criteria for inclusion in our data synthesis. Over two-thirds (68
