What Medical Conditions Limit or Medically Disqualify Truck Drivers: A Large Cross Sectional Study

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.

A preliminary study on the barriers and facilitators to improving the health, safety, and well-being of aging heavy vehicle drivers

INTRODUCTION

Managers from road freight transportation organizations were interviewed on barriers and facilitators to implementation of occupational health, safety, and well-being interventions for aging heavy vehicle drivers. As aging drivers are more likely to be seriously injured or die in a work-related incident than younger drivers, it is important to recognize strengths and weaknesses throughout the system to identify intervention that addresses their specific needs.

METHOD

A Systems Theoretic Accident Model and Processes (STAMP) control structure was constructed to chart the controllers, controls, and feedback channels in the system to identify gaps in health, safety, and well-being intervention in the system. The STAMP control structure also charted the barriers and facilitators within levels across the system. Eleven managers were recruited into the study representing a range of road freight transportation organizations throughout Australia.

RESULTS

Interview data revealed that barriers and facilitators existed at most levels of the system. Facilitators included advice from external agencies, support from upper management, modern technology, and regular social communication with drivers. Barriers were a lack of guidance on aging issues, operational conflicts with health and safety objectives, and the drivers' fear of disclosing health information associated with their driving role. In regards to formalized intervention in place to support aging heavy vehicle drivers, the system is reliant on fitness to drive medical assessments based on age and jurisdiction.

CONCLUSIONS

As there was generally a lack of senior direction cited from the upper levels of the system on aging issues, there was much variation across the study on how aging risks are managed in the workplace for heavy vehicle drivers.

PRACTICAL APPLICATIONS

This study recommends that managers across the road freight transportation industry receive formalized aging-awareness health and safety training in how to manage work-related driving hazards for aging heavy vehicle drivers.

Metabolic syndrome among commercial truck drivers: The relationship between condition prevalence and crashes

BACKGROUND

Metabolic syndrome (MetS) is especially prevalent among US truck drivers. However, there has been limited research exploring associations between MetS conditions with roadway crashes among truck drivers. The objective of this paper is to assess relationships between specific combinations of individual MetS components and crashes and near-misses.

METHODS

Survey, biometric, and anthropometric data were collected from 817 truck drivers across 6 diverse US states. Survey data focused on demographics and roadway safety outcomes, and anthropometric/biometric data corresponded to five MetS conditions (waist circumference blood pressure, hemoglobin A1c, triglycerides, and high-density lipoprotein [HDL] cholesterol). Logistic regression was used to calculate odds ratios of lifetime crashes and near-miss 1-month period prevalence associated with: 1) specific MetS conditions regardless of presence or absence of other MetS conditions, and 2) specific MetS conditions and counts of other accompanying MetS conditions.

RESULTS

Hypertension was the MetS characteristic most strongly associated with lifetime crash and 1-month near-miss outcomes, while high triglycerides, low HDL cholesterol, and large waist circumference were most commonly present among groups of conditions associated with crashes and near-misses. Overall, an increasing number of specific co-occurring MetS conditions were associated with higher reporting of roadway crashes.

CONCLUSIONS

Specific combinations and higher prevalence of MetS conditions were associated with increased frequency of reported crashes. Moreover, when the co-occurrence of MetS conditions is aggregated, a dose-response relationship with crashes appears. These results suggest that policy changes and interventions addressing MetS may increase driver health and reduce crash risk.

Challenges in Conducting Empirical Epidemiological Research with Truck and Bus Drivers in Diverse Settings in North America

Over 6.5 million commercial vehicle drivers were operating a large truck or bus in the United States in 2020. This career often has high stress and long working hours, with few opportunities for physical activity. Previous research has linked these factors to adverse health conditions. Adverse health conditions affect not only the professional drivers' wellbeing but potentially also commercial motor vehicle (CMV) operators' safe driving ability and public safety for others sharing the roadway. The prevalence of health conditions with high impact on roadway safety in North American CMV drivers necessitates empirical epidemiological research to better understand and improve driver health. The paper presents four challenges in conducting epidemiological research with truck and bus drivers in North America and potential resolutions identified in past and current research. These challenges include (1) the correlation between driving performance, driving experience, and driver demographic factors; (2) the impact of medical treatment status on the relationship between health conditions and driver risk; (3) capturing accurate data in self-report data collection methods; and (4) reaching the CMV population for research. These challenges are common and influential in epidemiological research of this population, as drivers face severe health issues, health-related federal regulations, and the impact of vehicle operation on the safety of themselves and others using the roadways.

Factors Associated with Colorectal Cancer Prevalence Among Long-Haul Truck Drivers in the United States

PURPOSE

To determine the age-adjusted association between colorectal cancer (CRC) risk factors and CRC prevalence among long-haul truck drivers (aged 21-85), after adjustment for age.

DESIGN

Pooled cross-sectional analysis using Commercial Driver Medical Exam (CDME) data. Setting. National survey data from January 1, 2005, to October 31, 2012.

PARTICIPANTS

47,786 commercial motor vehicle drivers in 48 states.

MEASURES

CRC prevalence was the primary outcome; independent variables included demographics, body mass index (BMI), and concomitant medical conditions.

ANALYSIS

Kruskal-Wallis tests to analyze continuous variables; Fischer's exact tests to analyze categorical variables; univariate and multivariable logistic regression for rare events (Firth method) to quantify the association between the independent variables of interest and CRC prevalence. Odds ratios (ORs) and 95% confidence intervals (CIs) were adjusted for age, gender, years with current employer, year of exam, and BMI in a multivariate logistic regression.

RESULTS

Many factors were statistically significant. Obesity (OR = 3.14; 95% CI = 1.03-9.61) and increasing age (OR = 1.10 per year; 95% CI = 1.07-1.13) were significantly associated with CRC prevalence. Truckers with 4 or more concomitant medical conditions were significantly more likely to have CRC (OR = 7.03; 95% CI = 1.83-27.03).

CONCLUSIONS

Our findings highlight mutable risk factors and represent an opportunity for intervention that may decrease CRC morbidity and mortality among truck drivers, a unique population in the United States estimated to live up to 16 years less than the general population.

Incidence of Workers' Compensation Claims in Opioid-Using Truck Drivers

OBJECTIVE

This study examines the relationship between opioid use prevalence and subsequent filing of workers' compensation claims.

METHODS

A retrospective cohort study design was utilized to examine data from drivers' initial commercial driver medical exam, employment data, and workers' compensation claims data.

RESULTS

Data from 57,733 over 7 years were analyzed. Drivers who reported opioid use at their initial medical exam visit filed subsequent workers' compensation claims 1.81 times sooner (P = 0.0001; 95% CI 1.34, 2.44) than drivers who did not report opioid use at their CDME when controlling for age, gender, BMI, and diastolic blood pressure.

CONCLUSIONS

These findings provide information that may aid in improving regulations to control for incidents, training programs to inform professional drivers of factors that increase accident risk and educating prescribers about increased risks of injury among opioid-using drivers.