Michael K. Lemke

Health and Wellness Programs for Commercial Motor-Vehicle Drivers Organizational Assessment and New Research Directions

The workplace is an invaluable venue for health protection and promotion interventions, particularly for truck drivers due to their overreliance on their work environments, a plethora of work-related stressors, and their morbidity rates. Extant efforts of trucking companies to address driver health through worksite health and wellness programs have been inadequate, producing unsustainable results. The Driver Health and Wellness Program Survey was designed for and disseminated to 46 trucking companies to assess the current state of health and wellness programs in the trucking industry, including program participation rates and longevity, program evaluation procedures, and program activities and resources. Findings indicate that programmatic efforts in trucking companies continue to fall short, and health and wellness programs are insufficient to improve health outcomes in a sustainably positive direction. A new integrated, systems-based paradigm is proposed as a conceptual and methodological framework with the potential to meaningfully advance interventions in blue-collar work settings.

Obesity indices are predictive of elevated C-reactive protein in long-haul truck drivers.

BACKGROUND Obesity rates in long-haul truck drivers have been shown to be significantly higher than the general population. We hypothesized that commercial drivers with the highest levels of general obesity and abdominal adiposity would have higher concentrations of high sensitivity C-reactive protein (CRP), a marker of inflammation. METHODS Survey and anthropometric data were collected from 262 commercial drivers. Weight, circumference measures, and blood analysis for CRP (N = 115) were conducted and compared to National Health and Nutrition Examination Survey (NHANES) data. CRP values were non-normally distributed and logarithmically transformed for statistical analyses. RESULTS BMI, waist circumference, sagittal abdominal diameter, and CRP were significantly higher than in the general population. Anthropometric indices that included height (BMI, waist-to-height ratio, and sagittal diameter-to-height ratio), were most predictive of CRP values. CONCLUSIONS Abdominal obesity is prevalent in commercial vehicle drivers and is an important indicator of the presence of inflammation in this population. Am. J. Ind. Med. 59:665-675, 2016.

Work and Chronic Disease: Comparison of Cardiometabolic Risk Markers Between Truck Drivers and the General Us Population

Objective: US long-haul truck drivers experience a wide array of excess cardiometabolic disease (CMD) risks unique to their occupation. How these risks translate to, and potentially induce, elevations in the clinical CMD risk profile of this population is unknown. Methods: A non-experimental, descriptive, cross-sectional design was employed to collect anthropometric and biometric data from 115 long-haul truckers to generate for the first time a comprehensive CMD risk marker profile, which was then compared with the general US population. The relationships between CMD risk markers and CMD outcomes were examined for both populations. Results: The long-haul trucker sample presented elevated CMD risk markers, generally scoring significantly worse than the general population. Associations between CMD risk markers and disease states varied between both populations. Conclusions: US long-haul truck drivers’ distinctive CMD risk profile indicates occupationally-linked CMD pathogenesis.

Work Strain, Social Isolation and Mental Health of Long-Haul Truckers

ABSTRACT Commercial driving is associated with myriad work strains. An ethnographic approach is used to examine how chronic, excess work strains impact the overall mental health of U.S. long-haul truckers. Social isolation and inherent difficulties of establishing and maintaining meaningful social ties during long stretches on the road are found to take a toll on drivers’ mental health. Truckers struggle with loneliness and are overstressed from work pressures and weak support systems. Therefore, commercial driving urgently needs policies designed to curb trucking’s harmful effects on driver mental health and public safety and occupational therapy programs designed to improve mental health.

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.

Overcoming Barriers in Unhealthy Settings A Phenomenological Study of Healthy Truck Drivers

We investigated the phenomenon of sustained health-supportive behaviors among long-haul commercial truck drivers, who belong to an occupational segment with extreme health disparities. With a focus on setting-level factors, this study sought to discover ways in which individuals exhibit resiliency while immersed in endemically obesogenic environments, as well as understand setting-level barriers to engaging in health-supportive behaviors. Using a transcendental phenomenological research design, 12 long-haul truck drivers who met screening criteria were selected using purposeful maximum sampling. Seven broad themes were identified: access to health resources, barriers to health behaviors, recommended alternative settings, constituents of health behavior, motivation for health behaviors, attitude toward health behaviors, and trucking culture. We suggest applying ecological theories of health behavior and settings approaches to improve driver health. We also propose the Integrative and Dynamic Healthy Commercial Driving (IDHCD) paradigm, grounded in complexity science, as a new theoretical framework for improving driver health outcomes.

Mapping U.S. long-haul truck drivers’ multiplex networks and risk topography in inner-city neighborhoods

This article illustrates how urban inner-city trucking milieux may influence STI/BBI/HIV acquisition and transmission risks for U.S. long-haul truckers, as well as their social and risk relationships. Using mixed methods, we collected ethnoepidemiological and biological data from long-haul truck drivers and their risk contacts in inner-city trucking milieux in Atlanta, Georgia, United States. Key findings indicate that within the risk-endemic environment of distressed inner-city areas, diverse trucking risk milieux can amplify STI/BBI/HIV risk for multiplex networks of truckers. Inner-city neighborhood location, short geographic distance among risk contacts, and trucker concurrency can potentially exacerbate transmission via bridging higher-risk individuals with lower-risk populations at disparate geographic and epidemiological locations.

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.

Work organization, sleep and metabolic syndrome among long-haul truck drivers

Background The work organization of long-haul truck drivers in the USA contains factors that have been shown to degrade sleep. In combination, these factors generate elevated cardiometabolic risk by inducing components of the metabolic syndrome (MetS). However, the prevalence and severity of MetS and the degree to which such factors differentially influence MetS among these drivers are unknown. Aims To determine the prevalence and severity of MetS among US long-haul truck drivers and to determine the predictive value of demographic, work organization and sleep variables in MetS diagnosis and severity. Methods A non-experimental, descriptive, cross-sectional study, designed to collect survey, anthropometric and biometric data from US long-haul truck drivers. Descriptive analyses were performed for demographic, work organization, sleep and MetS measures. Logistic and linear regression analyses examined potential predictive relationships between demographic, work organization and sleep variables and MetS diagnosis and severity. Results The study population was 262. Nearly 60% of drivers met MetS diagnosis criteria. Over 80% had a waist circumference >102 cm, 50% had triglyceride levels of ≥150 mg/dl, 66% had an high-density lipoprotein of <40 mg/dl, 28% had a blood pressure of ≥135/80 mm Hg and 17% had a fasting glucose of ≥110 mg/dl. Driving experience and work day sleep quality were associated with MetS prevalence and severity. Conclusions The prevalence and severity of MetS among this sample of US long-haul truck drivers were high. Preventive efforts should focus on experienced drivers and work day sleep quality.

Work, sleep, and cholesterol levels of U.S. long-haul truck drivers

Long-haul truck drivers in the United States experience elevated cardiovascular health risks, possibly due to hypercholesterolemia. The current study has two objectives: 1) to generate a cholesterol profile for U.S. long-haul truck drivers; and 2) to determine the influence of work organization characteristics and sleep quality and duration on cholesterol levels of long-haul truck drivers. Survey and biometric data were collected from 262 long-haul truck drivers. Descriptive analyses were performed for demographic, work organization, sleep, and cholesterol measures. Linear regression and ordinal logistic regression analyses were conducted to examine for possible predictive relationships between demographic, work organization, and sleep variables, and cholesterol outcomes. The majority (66.4%) of drivers had a low HDL (<40 mg/dL), and nearly 42% of drivers had a high-risk total cholesterol to HDL cholesterol ratio. Sleep quality was associated with HDL, LDL, and total cholesterol, and daily work hours were associated with LDL cholesterol. Workday sleep duration was associated with non-HDL cholesterol, and driving experience and sleep quality were associated with cholesterol ratio. Long-haul truck drivers have a high risk cholesterol profile, and sleep quality and work organization factors may induce these cholesterol outcomes. Targeted worksite health promotion programs are needed to curb these atherosclerotic risks.