Embracing Causal Complexity in Health Disparities: Metabolic Syndemics and Structural Prevention in Rural Minority Communities

System dynamics modeling for cancer prevention and control: A systematic review

Cancer prevention and control requires consideration of complex interactions between multilevel factors. System dynamics modeling, which consists of diagramming and simulation approaches for understanding and managing such complexity, is being increasingly applied to cancer prevention and control, but the breadth, characteristics, and quality of these studies is not known. We searched PubMed, Scopus, APA PsycInfo, and eight peer-reviewed journals to identify cancer-related studies that used system dynamics modeling. A dual review process was used to determine eligibility. Included studies were assessed using quality criteria adapted from prior literature and mapped onto the cancer control continuum. Characteristics of studies and models were abstracted and qualitatively synthesized. 32 studies met our inclusion criteria. A mix of simulation and diagramming approaches were used to address diverse topics, including chemotherapy treatments (16%), interventions to reduce tobacco or e-cigarettes use (16%), and cancer risk from environmental contamination (13%). Models spanned all focus areas of the cancer control continuum, with treatment (44%), prevention (34%), and detection (31%) being the most common. The quality assessment of studies was low, particularly for simulation approaches. Diagramming-only studies more often used participatory approaches. Involvement of participants, description of model development processes, and proper calibration and validation of models showed the greatest room for improvement. System dynamics modeling can illustrate complex interactions and help identify potential interventions across the cancer control continuum. Prior efforts have been hampered by a lack of rigor and transparency regarding model development and testing. Supportive infrastructure for increasing awareness, accessibility, and further development of best practices of system dynamics for multidisciplinary cancer research is needed.

Double Disparity of Sexual Minority Status and Rurality in Cardiometabolic Hospitalization Risk: A Secondary Analysis Using Linked Population-Based Data

Studies have shown separately that sexual minority populations generally experience poorer chronic health outcomes compared with those who identify as heterosexual, as do rural populations compared with urban dwellers. This Canadian national observational study explored healthcare patterns at the little-understood intersections of lesbian, gay, or bisexual (LGB) identity with residence in rural and remote communities, beyond chronic disease status. The secondary analysis applied logistic regressions on multiple linked datasets from representative health surveys, administrative hospital records, and a geocoded index of community remoteness to examine differences in the risk of potentially avoidable cardiometabolic-related hospitalization among adults of working age. Among those with an underlying cardiometabolic condition and residing in more rural and remote communities, a significantly higher hospitalization risk was found for LGB-identified persons compared with their heterosexual peers (odds ratio: 4.2; 95% confidence interval: 1.5-11.7), adjusting for sociodemographic characteristics, behavioral risk factors, and primary healthcare access. In models stratified by sex, the association remained significant among gay and bisexual men (5.6; CI: 1.3-24.4) but not among lesbian and bisexual women (3.5; CI: 0.9-13.6). More research is needed leveraging linkable datasets to better understand the complex and multiplicative influences of sexual minority status and rurality on cardiometabolic health to inform equity-enhancing preventive healthcare interventions.

Promoting the health of vulnerable populations: Three steps towards a systems-based re-orientation of public health intervention research

This paper proposes a novel framework for the development of interventions in vulnerable populations. The framework combines a complex systems lens with syndemic theory. Whereas funding bodies, research organizations and reporting guidelines tend to encourage intervention research that (i) focuses on singular and predefined health outcomes, (ii) searches for generalizable cause-effect relationships, and (iii) aims to identify universally effective interventions, the paper suggests that a different direction is needed for addressing health inequities: We need to (i) start with exploratory analysis of population-level data, and (ii) invest in contextualized in-depth knowledge of the complex dynamics that produce health inequities in specific populations and settings, while we (iii) work with stakeholders at multiple levels to create change within systems.

Multiple Case Study of Changes in Participation of Adults with Myotonic Dystrophy Type 1: Importance of Redesigning Accomplishment and Resilience

Background: Myotonic dystrophy type 1 (DM1) is the most prevalent adult form of neuromuscular disorders, for which a decrease of participation with age is known. However, little is known about facilitators and barriers to participation, especially from the perspective of both patients and caregivers. Objective: This study explored and explained changes in participation post-diagnosis with myotonic dystrophy type 1 from the perspective of six adults, their relatives and nurse case managers. Methods: A multiple case study was carried out with these triads (n =  6) using semi-structured individual interviews, medical charts, and a participation patient-reported outcome measure. The six cases were built around three women and three men (age: 40–56 years; disease duration: 19–39 years). Their “relatives” were mainly family members. Nurse case managers had done annual follow-ups with all the adults for approximately ten years. Changes in participation were characterized generally by: 1) heterogeneity, 2) insidious increase in restrictions, and more specifically by: 3) redesigning accomplishment, 4) progressive social isolation, 5) restrictions in life-space mobility, and 6) increasingly sedentary activities. Results: Important facilitators of participation were the adult’s resilience, highly meaningful activities, social support, living arrangement, and willingness to use technical aids. Barriers were mostly related to symptoms and a precarious social network, and were affected by misfit and potential syndemic interactions between personal (e.g., comorbidities) and environmental (e.g., stigma) factors. Conclusion: This study identified key facilitators and barriers and their underlying processes, which should be integrated into the evaluation and intervention framework to optimize participation over time.

Long drives and red tape: mapping rural veteran access to primary care using causal-loop diagramming

Background

Rural veterans experience more challenges than their urban peers in accessing primary care services, which can negatively impact their health and wellbeing. The factors driving this disparity are complex and involve patient, clinic, health system, community and policy influences. Federal policies over the last decade have relaxed requirements for some veterans to receive primary care services from community providers through their VA benefits, known as community care.

Methods

We used a participatory systems mapping approach involving causal-loop diagramming to identify interrelationships between variables underlying challenges to veteran access to primary care and potential opportunities for change—known as leverage points in systems science. Our methods involved a secondary analysis of semi-structured qualitative interviews with rural veterans, VA staff, non-VA clinic staff and providers who serve rural veterans, and veteran service officers (VSOs) in the Northwest region of the US, followed by a two-part participatory modeling session with a study advisory board. We then applied Meadows’s leverage point framework to identify and categorize potential interventions to improve rural veteran access to primary care.

Results

The final model illustrated challenges at the veteran, clinic, and system levels as experienced by stakeholders. Main components of the diagram pertained to the choice of VA or non-VA primary care, veteran satisfaction with the VA, enrollment in VA benefits and other insurance, community care authorization, reimbursement of non-VA care, referrals to specialty care, record sharing and communication between VA and non-VA providers, institutional stability of the VA, and staffing challenges. Fourteen interventions, including administrative and communications changes, were identified by analyzing the model using the leverage points framework.

Conclusions

Our findings illustrate how challenges rural veterans face accessing health care are interconnected and persist despite recent changes to federal law pertaining to the VA health care system in recent years. Systems mapping and modeling approaches such as causal-loop diagramming have potential for engaging stakeholders and supporting intervention and implementation planning.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08318-2.

Applications of System Dynamics Models in Chronic Disease Prevention: A Systematic Review

Introduction

Chronic disease is a serious health problem worldwide. Given that health care resources are limited, a comprehensive, effective, and affordable way is needed to provide insights to prevent chronic diseases. System dynamics models provide a comprehensive and systematic method that can predict results over time. These models can simulate and predict appropriate prevention measures for chronic diseases to determine the best practice.

Methods

Two researchers (Y.W., B.H.) independently searched databases (PubMed, Web of Science, Scopus, and Embase) for full-text articles published from January 2000 through February 2021. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020–compliant search was carried out to review system dynamics models of chronic disease prevention. A total of 34 articles were included in our study.

Results

We divided the prevention measures of system dynamics models into 2 main categories: upstream prevention and downstream prevention. Upstream prevention measures include lifestyle (eg, tobacco control, balanced diet, mental health, moderate exercise), obesity prevention, and social factors. Downstream prevention measures include clinical treatment of chronic diseases. Results showed that effective upstream prevention measures could reduce the prevalence of chronic diseases, and downstream prevention measures could reduce the incidence of complications, improve quality of life, prolong life, save medical costs, and reduce mortality.

Conclusion

To our knowledge, our systematic review is the first to evaluate the application of system dynamics models in preventing chronic diseases. Such models can provide effective simulations. Hence, we can use system dynamics models to design and implement effective prevention measures for people with chronic diseases.

Community Susceptibility and Resiliency to COVID-19 Across the Rural-Urban Continuum in the United States

Purpose

This study creates a COVID‐19 susceptibility scale at the county level, describes its components, and then assesses the health and socioeconomic resiliency of susceptible places across the rural‐urban continuum.

Methods

Factor analysis grouped 11 indicators into 7 distinct susceptibility factors for 3,079 counties in the conterminous United States. Unconditional mean differences are assessed using a multivariate general linear model. Data from 2018 are primarily taken from the US Census Bureau and CDC.

Results

About 33% of rural counties are highly susceptible to COVID‐19, driven by older and health‐compromised populations, and care facilities for the elderly. Major vulnerabilities in rural counties include fewer physicians, lack of mental health services, higher disability, and more uninsured. Poor Internet access limits telemedicine. Lack of social capital and social services may hinder local pandemic recovery. Meat processing facilities drive risk in micropolitan counties. Although metropolitan counties are less susceptible due to healthier and younger populations, about 6% are at risk due to community spread from dense populations. Metropolitan vulnerabilities include minorities at higher health and diabetes risk, language barriers, being a transportation hub that helps spread infection, and acute housing distress.

Conclusions

There is an immediate need to know specific types of susceptibilities and vulnerabilities ahead of time to allow local and state health officials to plan and allocate resources accordingly. In rural areas it is essential to shelter‐in‐place vulnerable populations, whereas in large metropolitan areas general closure orders are needed to stop community spread. Pandemic response plans should address vulnerabilities.

The Impact of Work Organization, Job Stress, and Sleep on the Health Behaviors and Outcomes of U.S. Long-Haul Truck Drivers

Background. Compared with other occupations, long-haul truck drivers (LHTD) engage in excessively unhealthy behaviors and experience disproportionately poor health outcomes. Health promotion efforts targeting LHTDs focus on improving individual-level behaviors; however, this occupation is replete with adverse work organization characteristics, high job stress, and compromised sleep health, which are hypothesized to cause poor health behaviors and outcomes among LHTDs. Therefore, the purpose of this study was to explore the connections between work characteristics, job stress, and sleep outcomes, and health behaviors and physical and mental health outcomes among LHTDs. Method. This was a cross-sectional study, using interviewer-administered surveys with LHTDs (n = 260). Bivariate correlation analysis was used to explore the associations among work organization, job stress, sleep health, and health behaviors and outcomes. Logistic regression analyses were used to determine whether these work organization, job stress, and sleep factors predicted health behaviors and outcomes. Results. Long work hours of more than 11 hours daily (odds ratio [OR] = 2.34) resulted in increased odds of high caffeine consumption. High job stress (OR = 0.48) and poor sleep quality (OR = 0.42) led to decreased odds for spending at least 1 hour daily for cooking/eating. Low sleep duration, less than 7 hours daily (OR = 2.55), led to increased odds of a physical health diagnosis. Both high job stress (OR = 3.58) and poor sleep quality (OR = 2.22) resulted in increased odds of a mental health diagnosis. Conclusion. Health promotion efforts targeting LHTDs need to be coupled with upstream policy, environmental, and systems-level change, especially at the governmental and trucking industry levels.