A Pilot Study of Healthy Living Options at 16 Truck Stops Across the United States.

PURPOSE: There is a growing body of evidence that the built environment influences diet and exercise and, as a consequence, community health status. Since long-haul truck drivers spend long periods of time at truck stops, it is important to know if this built environment includes resources that contribute to the emotional and physical well-being of drivers. SETTING: The truck stop environment was defined as the truck stop itself, grocery stores, and medical clinics near the truck stop that could be accessed by a large truck or safely on foot. DESIGN: Researchers at the National Institute for Occupational Safety and Health (NIOSH) developed and utilized a checklist to record the availability of resources for personal hygiene and comfort, communication and mental stimulation, health care, safety, physical activity, and nutrition at truck stops. SUBJECTS: The NIOSH checklist was used to collect data at a convenience sample of 16 truck stops throughout the United States along both high-flow and low-flow truck traffic routes. MEASURES: The checklist was completed by observation within and around the truck stops. RESULTS: No truck stops offered exercise facilities, 94% lacked access to health care, 81% lacked a walking path, 50% lacked fresh fruit, and 37% lacked fresh vegetables in their restaurant or convenience store. CONCLUSION: The NIOSH found that most truck stops did not provide an overall healthy living environment.

NIOSH national survey of long-haul truck drivers: Injury and safety.

Approximately 1,701,500 people were employed as heavy and tractor-trailer truck drivers in the United States in 2012. The majority of them were long-haul truck drivers (LHTDs). There are limited data on occupational injury and safety in LHTDs, which prompted a targeted national survey. The National Institute of Occupational Safety and Health conducted a nationally representative survey of 1265 LHTDs at 32 truck stops across the contiguous United States in 2010. Data were collected on truck crashes, near misses, moving violations, work-related injuries, work environment, safety climate, driver training, job satisfaction, and driving behaviors. Results suggested that an estimated 2.6% of LHTDs reported a truck crash in 2010, 35% reported at least one crash while working as an LHTD, 24% reported at least one near miss in the previous 7 days, 17% reported at least one moving violation ticket and 4.7% reported a non-crash injury involving days away from work in the previous 12 months. The majority (68%) of non-crash injuries among company drivers were not reported to employers. An estimate of 73% of LHTDs (16% often and 58% sometimes) perceived their delivery schedules unrealistically tight; 24% often continued driving despite fatigue, bad weather, or heavy traffic because they needed to deliver or pick up a load at a given time; 4.5% often drove 10miles per hours or more over the speed limit; 6.0% never wore a seatbelt; 36% were often frustrated by other drivers on the road; 35% often had to wait for access to a loading dock; 37% reported being noncompliant with hours-of-service rules (10% often and 27% sometimes); 38% of LHTDs perceived their entry-level training inadequate; and 15% did not feel that safety of workers was a high priority with their management. This survey brings to light a number of important safety issues for further research and interventions, e.g., high prevalence of truck crashes, injury underreporting, unrealistically tight delivery schedules, noncompliance with hours-of-service rules, and inadequate entry-level training.

Vital signs: seat belt use among long-haul truck drivers--United States, 2010.

BACKGROUND: Motor vehicle crashes were the leading cause of occupational fatalities in the United States in 2012, accounting for 25% of deaths. Truck drivers accounted for 46% of these deaths. This study estimates the prevalence of seat belt use and identifies factors associated with nonuse of seat belts among long-haul truck drivers (LHTDs), a group of workers at high risk for fatalities resulting from truck crashes. METHODS: CDC analyzed data from its 2010 national survey of LHTD health and injury. A total of 1,265 drivers completed the survey interview. Logistic regression was used to examine the association between seat belt nonuse and risk factors. RESULTS: An estimated 86.1% of LHTDs reported often using a seat belt, 7.8% used it sometimes, and 6.0% never. Reporting never using a belt was associated with often driving ≥10 mph (16 kph) over the speed limit (adjusted odds ratio [AOR] = 2.9), working for a company with no written safety program (AOR = 2.8), receiving two or more tickets for moving violations in the preceding 12 months (AOR = 2.2), living in a state without a primary belt law (AOR = 2.1); and being female (AOR = 2.3). CONCLUSIONS: Approximately 14% of LHTDs are at increased risk for injury and death because they do not use a seat belt on every trip. Safety programs and other management interventions, engineering changes, and design changes might increase seat belt use among LHTDs. IMPLICATIONS FOR PUBLIC HEALTH: Primary state belt laws can help increase belt use among LHTDs. Manufacturers can use recently collected anthropometric data to design better-fitting and more comfortable seat belt systems.

National Survey of US Long-Haul Truck Driver Health and Injury: health behaviors.

OBJECTIVE: To compare selected health behaviors and body mass index (modifiable risk factors) of US long-haul truck drivers to the US working population by sex. METHODS: The National Survey of US Long-Haul Truck Driver Health and Injury interviewed a nationally representative sample of long-haul truck drivers (n = 1265) at truck stops. Age-adjusted results were compared with national health surveys. RESULTS: Compared with US workers, drivers had significantly higher body mass index, current cigarette use, and pack-years of smoking; lower prevalence of annual influenza vaccination; and generally lower alcohol consumption. Physical activity level was low for most drivers, and 25% had never had their cholesterol levels tested. CONCLUSIONS: Working conditions common to long-haul trucking may create significant barriers to certain healthy behaviors; thus, transportation and health professionals should address the unique work environment when developing interventions for long-haul drivers.

Obesity and other risk factors: the national survey of U.S. long-haul truck driver health and injury.

BACKGROUND: Drivers of heavy and tractor-trailer trucks accounted for 56% of all production and nonsupervisory employees in the truck transportation industry in 2011. There are limited data for illness and injury in long-haul truck drivers, which prompted a targeted national survey. METHODS: Interviewers collected data during 2010 from 1,670 long-haul truck drivers at 32 truck stops across the 48 contiguous United States that were used to compute prevalence estimates for self-reported health conditions and risk factors. RESULTS: Obesity (69% vs. 31%, P < 0.01) and current smoking (51% vs. 19%, P < 0.01) were twice as prevalent in long-haul truck drivers as in the 2010 U.S. adult working population. Sixty-one percent reported having two or more of the risk factors: hypertension, obesity, smoking, high cholesterol, no physical activity, 6 or fewer hours of sleep per 24-hr period. CONCLUSION: Survey findings suggest a need for targeted interventions and continued surveillance for long-haul truck drivers.

Active and passive fatigue in simulated driving: discriminating styles of workload regulation and their safety impacts.

Despite the known dangers of driver fatigue, it is a difficult construct to study empirically. Different forms of task-induced fatigue may differ in their effects on driver performance and safety. Desmond and Hancock (2001) defined active and passive fatigue states that reflect different styles of workload regulation. In 2 driving simulator studies we investigated the multidimensional subjective states and safety outcomes associated with active and passive fatigue. Wind gusts were used to induce active fatigue, and full vehicle automation to induce passive fatigue. Drive duration was independently manipulated to track the development of fatigue states over time. Participants were undergraduate students. Study 1 (N = 108) focused on subjective response and associated cognitive stress processes, while Study 2 (N = 168) tested fatigue effects on vehicle control and alertness. In both studies the 2 fatigue manipulations produced different patterns of subjective response reflecting different styles of workload regulation, appraisal, and coping. Active fatigue was associated with distress, overload, and heightened coping efforts, whereas passive fatigue corresponded to large-magnitude declines in task engagement, cognitive underload, and reduced challenge appraisal. Study 2 showed that only passive fatigue reduced alertness, operationalized as speed of braking and steering responses to an emergency event. Passive fatigue also increased crash probability, but did not affect a measure of vehicle control. Findings support theories that see fatigue as an outcome of strategies for managing workload. The distinction between active and passive fatigue is important for assessment of fatigue and for evaluating automated driving systems which may induce dangerous levels of passive fatigue.

Strategies for nurses to prevent sleep-related injuries and errors.

Rehabilitation nurses work shift schedules or long hours to provide essential patient services around the clock. These demanding hours can lead to sleep difficulties, declines in performance, and increased worker errors. This article gives an overview of selected declines in cognitive performance that are associated with inadequate sleep and several factors that increase riskforfatigue-related errors. Selected strategies for nurses and managers to reduce these risks are discussed, such as better sleep practices, improved work schedule design, naps, caffeine, exposure to light, and rest breaks. Both nurses and managers share responsibility for implementing strategies to reduce risks from inadequate sleep.

Visual contrast sensitivity testing: a comparison of two F.A.C.T. test types.

Measures of visual contrast sensitivity (VCS), rather than traditional measures of visual acuity using high-contrast stimuli, have been presented as better appraisals of visual dysfunction resulting from chemical exposures. The present study sought to determine if differences exist between two available measures of contrast sensitivity that use similar stimuli, specifically, a hand-held chart and an Optec 1000 vision tester. Monocular contrast sensitivity measures using both tests were obtained from 45 individuals as part of a NIOSH neurobehavioral test-battery appraisal. Test-retest reliability was found to be high for both the hand-held system and the Optec 1000 test (r=.750 and.773, respectively). In comparison to the automated test, the hand-held version produced statistically significant higher contrast sensitivity scores for lower spatial frequencies (1.5 and 3.0 cycles per degree) and lower scores for a relatively higher spatial frequency (18.0 cycles per degree [cpd]). Consequently, this study documents a difference in spatial frequency scores obtained with the hand-held form and Optec 1000 form of contrast sensitivity test, and attributes these differences to design characteristics affecting viewing. It is concluded that caution should be taken when making absolute comparisons of contrast sensitivity test scores between neurobehavioral studies that have used different forms of VCS testing.