A blueprint for a new commercial driving epidemiology: An emerging paradigm grounded in integrative exposome and network epistemologies.

Excess health and safety risks of commercial drivers are largely determined by, embedded in, or operate as complex, dynamic, and randomly determined systems with interacting parts. Yet, prevailing epidemiology is entrenched in narrow, deterministic, and static exposure-response frameworks along with ensuing inadequate data and limiting methods, thereby perpetuating an incomplete understanding of commercial drivers' health and safety risks. This paper is grounded in our ongoing research that conceptualizes health and safety challenges of working people as multilayered "wholes" of interacting work and nonwork factors, exemplified by complex-systems epistemologies. Building upon and expanding these assumptions, herein we: (a) discuss how insights from integrative exposome and network-science-based frameworks can enhance our understanding of commercial drivers' chronic disease and injury burden; (b) introduce the "working life exposome of commercial driving" (WLE-CD)-an array of multifactorial and interdependent work and nonwork exposures and associated biological responses that concurrently or sequentially impact commercial drivers' health and safety during and beyond their work tenure; (c) conceptualize commercial drivers' health and safety risks as multilayered networks centered on the WLE-CD and network relational patterns and topological properties-that is, arrangement, connections, and relationships among network components-that largely govern risk dynamics; and (d) elucidate how integrative exposome and network-science-based innovations can contribute to a more comprehensive understanding of commercial drivers' chronic disease and injury risk dynamics. Development, validation, and proliferation of this emerging discourse can move commercial driving epidemiology to the frontier of science with implications for policy, action, other working populations, and population health at large.

The indispensable whole of work and population health: How the working life exposome can advance empirical research, policy, and action.

OBJECTIVES: The thesis of this paper is that health and safety challenges of working people can only be fully understood by examining them as wholes with interacting parts. This paper unravels this indispensable whole by introducing the working life exposome and elucidating how associated epistemologies and methodologies can enhance empirical research. METHODS: Network and population health scientists have initiated an ongoing discourse on the state of empirical work-health-safety-well-being research. RESULTS: Empirical research has not fully captured the totality and complexity of multiple and interacting work and nonwork factors defining the health of working people over their life course. We challenge the prevailing paradigm by proposing to expand it from narrow work-related exposures and associated monocausal frameworks to the holistic study of work and population health grounded in complexity and exposome sciences. Health challenges of working people are determined by, embedded in, and/or operate as complex systems comprised of multilayered and interdependent components. One can identify many potentially causal factors as sufficient and component causes where removal of one or more of these can impact disease progression. We, therefore, cannot effectively study them by an a priori determination of a set of components and/or properties to be examined separately and then recombine partial approaches, attempting to form a picture of the whole. Instead, we must examine these challenges as wholes from the start, with an emphasis on interactions among their multifactorial components and their emergent properties. Despite various challenges, working-life-exposome-grounded frameworks and associated innovations have the potential to accomplish that. CONCLUSIONS: This emerging paradigm shift can move empirical work-health-safety-well-being research to cutting-edge science and enable more impactful policies and actions.

Work Challenges and Health of Immigrant Hotel Housekeepers: Part 2.

BACKGROUND: Hotel housekeepers' major responsibility is to perform cleaning tasks. In the course of performing their duties, hotel housekeepers are disproportionately exposed to multiple workplace hazards (i.e., physical, chemical, biological, and psychosocial hazards) that put them at risk of adverse health consequences. This study aims to discover the occupational and health challenges encountered by immigrant hotel housekeepers in Orlando, Florida, and help hotel management to develop strategies to improve their occupational health. METHODS: This study adopted an interviewer-administered survey method for data collection. Data were collected from members of the United Here Union, Local 7373 in Orlando, Florida. Trained Spanish-English bilingual associates of the Union administered the surveys through interviews with participants. Descriptive statistics and stepwise multiple regression were employed to analyze data (n = 140) using SPSS 22. FINDINGS: This study shows that Florida hotel housekeepers participating in this study worked under great time pressures, endured excessive workloads, did not have enough time to rest and recover, and often skipped or shortened lunch breaks. Participants believed that their employers valued work productivity more than their safety and health. More than half of the respondents experienced racial discrimination at their workplaces. CONCLUSION/APPLICATION TO PRACTICE: The article brings an important contribution to the awareness of housekeepers' feelings toward their work and the need for effective safety and health policies and programs.

Occupational Health and Safety of Immigrant Hotel Housekeepers.

BACKGROUND: The accommodations sector is one of the largest employers of immigrant and minority workers in the United States. Hotel housekeepers represent the industry's largest workforce while facing difficult work conditions, health hazards, and psychological stress. This is one of the few empirical studies that address the working conditions of housekeepers in the United States and their perspective of health challenges they face. METHODS: A cross-sectional survey study was conducted with hotel housekeepers (N = 140) in Florida and in collaboration with the local labor union as a rapid assessment of occupational health and safety risk exposures, work-related injuries, coping mechanisms, and perceived management responses. Experienced union workers recruited study participants and administered interviewer-administered surveys. The analysis included descriptive statistics and multivariate regression. FINDINGS: Sampled hotel housekeepers were found to work under significant time pressures to complete excessive workloads and to experience chemical and biological exposures and physical and psychosocial strains. Poor work equipment/insufficient supplies had a negative impact on hotel housekeepers' health, these include heavy wet towels vacuum cleaners having a significant effect on (p < .001) sprains and strains. Poor cleaning supplies had a significant effect (p < .001) on chemical burns. Other significant findings are provided in the article. CONCLUSION/APPLICATION TO PRACTICE: While housekeeping work conditions include many challenges, relatively simple changes by hotels' management can provide potential relief and improve workers' health and safety outcomes, such as functional equipment, sufficient inventory, management support, and proper rest breaks-subsequently increasing workers' health and reducing accidents, and thus potentially improving productivity at a relatively low cost.

Work, physical activity, and metabolic health: Understanding insulin sensitivity of long-haul truck drivers.

BACKGROUND: Long-haul truck drivers are disproportionately exposed to metabolic risk; however, little is known about their metabolic health and the role of physical activity and other risk factors in metabolic outcomes. OBJECTIVE: This study compares truck drivers' insulin sensitivity, and associations between metabolic risk factors and insulin sensitivity, with those of the general population. METHODS: Survey, anthropometric, and biometric data were collected from 115 long-haul truckers, which were then compared to the general population data using the National Health and Nutrition Examination Survey (NHANES) dataset. The quantitative insulin sensitivity check index (QUICKI) was used to estimate insulin sensitivity. RESULTS: Truck drivers had lower QUICKI scores than the general population cohort. Sagittal abdominal diameter and exercise were predictive for QUICKI among combined cohorts. Waist circumference and perceived health were more predictive for QUICKI among truck drivers, and sagittal abdominal diameter and income were more predictive for QUICKI among the general population. CONCLUSIONS: Long-haul truckers appear to represent a subset of the general population regarding the impact of physical activity and other metabolic risk factors on QUICKI. Accordingly, comprehensive efforts which target these factors are needed to improve truckers' physical activity levels and other metabolic risks.

Exploring the Role of Social Network Structure in Disease Risk among U.S. Long-haul Truck Drivers in Urban Areas.

Objective: Using mixed methods, we explored properties of long-haul truckers' social networks potentially influencing STI/BBI acquisition and transmission. Methods: We recruited inner-city drug and sex network members (N = 88) for interviews. Blood and urine samples and vaginal swabs were collected to test for STIs/BBIs. Data were collected on participants' role in the network (trucker, sex worker, or intermediary), sexual and substance-use behaviors, and dyadic relationships with drug and/or sex contacts. We analyzed network data using UCINET. Results: Data revealed 2 major network clusters (58 male truckers, 6 male intermediaries, and 24 female sex workers; 27.3% STI/BBI positive). Overall, 18.8% of network members had more than one type of risky relationship with the same person (multiplexity), 11.4% of dyads were between 2 STI/ BBI positive people (assortative mixing), 36.4% were between one STI/BBI positive person and one negative person (disassortative mixing), 44.3% of people were connected to more than one person who was STI/BBI positive (concurrency), and 62.5% of nodes were just one path removed from an STI/BBI positive individual (bridging). Conclusion: Despite only 27.3% of the network being STI/BBI positive, our results revealed network characteristics (and potential intervention points) that amplify risk of disease spread within trucker-centered networks.

The Hospitality Industry in the Face of the COVID-19 Pandemic: Current Topics and Research Methods.

This study reports on a systematic review of the published literature used to reveal the current research investigating the hospitality industry in the face of the COVID-19 pandemic. The presented review identified relevant papers using Google Scholar, Web of Science, and Science Direct databases. Of the 175 articles found, 50 papers met the predefined inclusion criteria. The included papers were classified concerning the following dimensions: the source of publication, hospitality industry domain, and methodology. The reviewed articles focused on different aspects of the hospitality industry, including hospitality workers' issues, loss of jobs, revenue impact, the COVID-19 spreading patterns in the industry, market demand, prospects for recovery of the hospitality industry, safety and health, travel behavior, and preference of customers. The results revealed a variety of research approaches that have been used to investigate the hospitality industry at the time of the pandemic. The reported approaches include simulation and scenario modeling for discovering the COVID-19 spreading patterns, field surveys, secondary data analysis, discussing the resumption of activities during and after the pandemic, comparing the COVID-19 pandemic with previous public health crises, and measuring the impact of the pandemic in terms of economics.

Understanding the effects of COVID-19 on the health and safety of immigrant hospitality workers in the United States.

The U.S. tourism and hospitality workforce is disproportionately represented by immigrants and minorities, particularly in low-wage jobs with adverse work conditions. Immigrant hotel and foodservice workers face excess chronic stress and related syndemic risks, exacerbated by social, political, and economic inequities. COVID-19 has suddenly intensified the stressful and already difficult circumstances of immigrant service sector workers. The travel and tourism sector is one of the hardest hit due to widespread travel restrictions and shelter-in-place orders designed to curb infection spread. Restrictions and lockdowns have devastated tourism-dependent destinations and displaced millions of vulnerable workers, causing them to lose their livelihoods. Compared to the general workforce, a sizeable increase in occupational stress has already been observed in the hospitality/tourism sector over the past 15-20 years. COVID-19 and related fears add further strains on immigrant hotel and foodservice workers, potentially exerting a significant toll on mental and physical health and safety.

Syndemic frameworks to understand the effects of COVID-19 on commercial driver stress, health, and safety.

INTRODUCTION: U.S. commercial drivers are entrenched in a stressogenic profession, and exposures to endemic chronic stressors shape drivers' behavioral and psychosocial responses and induce profound health and safety disparities. To gain a complete understanding of how the COVID-19 pandemic will affect commercial driver stress, health, and safety over time, and to mitigate these impacts, research and prevention efforts must be grounded in theoretical perspectives that contextualize these impacts within the chronic stressors already endemic to profession, the historical and ongoing forces that have induced them, and the potentially reinforcing nature of the resulting afflictions. METHODS: Extant literature reveals how an array of macro-level changes has shaped downstream trucking industry policies, resulting in stressogenic work organization and workplace characteristics. Emerging evidence suggests that the COVID-19 pandemic exacerbates existing stressors and introduces novel stressors, with potentially exacerbatory impacts on health and safety disparities. RESULTS: As COVID-19 exerts an array of multi-level stressors on commercial drivers, syndemic frameworks can provide the appropriate theoretical lens to guide research and prevention. Syndemic frameworks can provide the grounding to allow foregoing commercial driver COVID-19 research to transcend the limitations of prevailing research frameworks by contextualizing COVID-19 stressors holistically within the complex system of endemic chronic stressors and interrelated health and safety afflictions. Syndemic-informed prevention efforts can then be implemented that simultaneously tackle multiple afflictions and the macro-level forces that result in the emergence of commercial drivers' health and safety disparities over time. CONCLUSIONS: The impacts of the COVID-19 pandemic on commercial drivers cannot be adequately understood or acted upon in isolation from the endemic chronic stressors and interrelated health and safety disparities that characterize the profession. Instead, commercial driver COVID-19 research and prevention needs syndemic frameworks to holistically understand the impacts of COVID-19 on commercial driver stress, health, and safety, and to identify high-leverage preventive actions.

A novel COVID-19 based truck driver syndemic? Implications for public health, safety, and vital supply chains.

U.S. long-haul truck drivers traverse great distances and interact with numerous individuals, rendering them vulnerable to acquiring and transmitting coronavirus disease 2019 (COVID-19). Together, the unique co-occurrence of pronounced health disparities and known COVID-19 infection, morbidity, and mortality risks suggest the possibility of a novel COVID-19 based truck driver syndemic due to advanced driver age and endemic health issues. In turn, COVID-19 sequelae may perpetuate existing health disparities. The co-occurrence of afflictions may also result in compromised safety performance. To curb the likelihood of a COVID-19 based truck driver syndemic, several action stepsare needed. First, key COVID-19 metrics need to be established for this population. Second, relationships between long-haul trucker network attributes and COVID-19 spread need to bedelineated. Third, mutually reinforcing interactions between endemic health disparities and COVID-19 vulnerability need to be elucidated. Finally, grounded in the aforementioned steps, policies and interventions need to be identified and implemented.

Integrating complex systems science into road safety research and practice, part 1: review of formative concepts.

Many of our most persistent public health problems are complex problems. They arise from a web of factors that interact and change over time and may exhibit resistance to intervention efforts. The domain of systems science provides several tools to help injury prevention researchers and practitioners examine deep, complex and persistent problems and identify opportunities to intervene. Using the increase in pedestrian death rates as an example, we provide (1) an accessible overview of how complex systems science approaches can augment established injury prevention frameworks and (2) a straightforward example of how specific systems science tools can deepen understanding, with a goal of ultimately informing action.

Work-Life Conflict among U.S. Long-Haul Truck Drivers: Influences of Work Organization, Perceived Job Stress, Sleep, and Organizational Support.

Work-life balance and job stress are critical to health and well-being. Long-haul truck driving (LHTD) is among the unhealthiest and most unsafe occupations in the U.S. Despite these disparities, there are no extant published studies examining the influence of work, stress and sleep outcomes on drivers' work-life balance. The current study investigated whether adverse work organization, stress, and poor sleep health among LHTDs are significantly associated with work-life conflict. Logistic regression was used to examine how work organization characteristics, job stress, and sleep influenced perceived stress and a composite measure of work-life conflict among a sample of 260 U.S. LHTDs. The pattern of regression results dictated subsequent analyses using structural equation modeling (SEM). Perceived job stress was the only statistically significant predictor for work-life balance. Fast pace of work, sleep duration and sleep quality were predictors of perceived job stress. SEM further elucidated that stress mediates the influences of fast work pace, supervisor/coworker support, and low sleep duration on each of the individual work-life balance indicators. There is an urgent need to address work conditions of LHTDs to better support their health, well-being, and work-life balance. Specifically, the findings from this study illustrate that scheduling practices and sleep outcomes could alleviate job stress and need to be addressed to more effectively support work-life balance. Future research and interventions should focus on policy and systems-level change.

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.

Occupational health disparities among U.S. long-haul truck drivers: the influence of work organization and sleep on cardiovascular and metabolic disease risk.

OBJECTIVE: The organization of work has undergone vast transformations over the past four decades in the United States and has had profound impacts on worker health and wellbeing. The profession of commercial truck driving is one of the best examples. Particularly for long-haul truck drivers, changes in work organization have led to disproportionately poor physiological, psychological, and sleep health outcomes. METHODS: The present study examined disparities in cardiometabolic disease risk among long-haul truck drivers and the general population, and the influence of work organization and sleep in generating these outcomes. Researchers collected survey data from 260 drivers, and blood assay samples from 115 of those drivers, at a large highway truck stop in North Carolina. Comparisons were made for cardiovascular and metabolic risk against the 2011-2012 National Health and Nutrition Examination Survey (NHANES). In addition, logistic regression was used to explore predictive relationships between work organization and sleep and risk for cardiovascular and metabolic disease. RESULTS: There were statistically significant mean differences between the long-haul truck driver sample and the NHANES sample for both cardiovascular (3.71 vs. 3.10; p <0.001) and metabolic (4.31 vs. 3.09; p <0.001) disease risk. The truck driver sample was less physically active and had lower HDL cholesterol along with greater levels of smoking, BMI, and metabolic syndrome diagnosis. More years of driving experience and poor sleep quality were statistically significant predictors for both cardiovascular and metabolic disease risk. CONCLUSIONS: Study findings implicate elements of the occupational milieu experienced by long-haul truck drivers that induce disproportionate cardiometabolic disease risk. Sleep quality, largely compromised by poor work conditions and workplace environments, plays a significant role in increased risks for cardiometabolic disease. There is an urgent need for longitudinal studies of this critical occupational sector as well as intervention research centered on policy and systems level change.

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

Chronic discrimination and associated socioeconomic inequalities have shaped the health and well-being of Black Americans. As a consequence of the intersection of these factors with rural deprivation, rural Black Americans live and work in particularly pathogenic environments that generate disproportionate and interacting chronic comorbidities (syndemics) compared to their White and/or urban counterparts. Traditional prevention research has been unable to fully capture the underlying complexity of rural minority health and has generated mostly low-leverage interventions that have failed to reverse adverse metabolic outcomes among rural Black Americans. In contrast, novel research approaches-such as system dynamics modeling-that seek to understand holistic system structure and determine complex health outcomes over time provide a robust framework to develop a more accurate understanding of the key factors contributing to type 2 diabetes. This framework can then be used to establish more efficacious interventions to address disparities among minorities in rural areas. This paper advocates for a unified complex systems epistemology and methodology in advancing rural minority health disparities research. Toward this goal, we (1) provide an overview of rural Black American metabolic health research, (2) introduce a complex systems framework in rural minority health disparities research, and (3) demonstrate how community-based system dynamics modeling and simulation can help us plow new ground in rural minority health disparities research and action. We anticipate that this paper can serve as a catalyst for a long-overdue discourse on the relevance of complex systems approaches in minority health research, with practical benefits for numerous disproportionately burdened communities.

Can subjective sleep problems detect latent sleep disorders among commercial drivers?

INTRODUCTION: Long-haul truck drivers experience poor sleep health and heightened accident rates, and undiagnosed sleep disorders contribute to these negative outcomes. Subjective sleep disorder screening tools may aid in detecting drivers' sleep disorders. This study sought to evaluate the value of subjective screening methods for detecting latent sleep disorders and identifying truck drivers at-risk for poor sleep health and safety-relevant performance. MATERIALS AND METHODS: Using cross-sectional data from 260 long-haul truck drivers, we: 1) used factor analysis to identify possible latent sleep disorders; 2) explored the construct validity of extracted sleep disorder factors by determining their associations with established sleep disorder risk factors and symptoms; and 3) explored the predictive validity of resulting sleep disorder factors by determining their associations with sleep health and safety-relevant performance. RESULTS: Five latent sleep disorder factors were extracted: 1) circadian rhythm sleep disorders; 2) sleep-related breathing disorders; 3) parasomnias; 4) insomnias; 5) and sleep-related movement disorders. Patterns of associations between these factors generally corresponded with known risk factors and symptoms. One or more of the extracted latent sleep disorder factors were significantly associated with all the sleep health and safety outcomes. DISCUSSION: Using subjective sleep problems to detect latent sleep disorders among long-haul truck drivers may be a timely and effective way to screen this highly mobile occupational segment. This approach should constitute one component of comprehensive efforts to diagnose and treat sleep disorders among commercial transport operators.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

BACKGROUND AND AIMS: Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. METHODS: System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. RESULTS: The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. CONCLUSIONS: Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention.

Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.

BACKGROUND AND AIMS: The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. METHODS: A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. RESULTS: The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. CONCLUSIONS: A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions.