Work hours, workload, sleep and fatigue in Australian Rail Industry employees

Research suggests that less than 5 h sleep in the 24 h prior to work and/or more than 16 h of wakefulness can significantly increase the likelihood of fatigue-related impairment and error at work. Studies have also shown exponential safety declines with time on shift, with roughly double the likelihood of accident or injury after 10 h relative to the first 8 h. While it is acknowledged that reduced sleep, increased wakefulness and longer work hours produce work-related fatigue, few studies have examined the impact of workload on this relationship. Studies in the rail industry have focused on drivers. This study investigated fatigue in a large sample of Australian Rail Industry Employees. Participants were from four companies (n = 90: 85m, 5f; mean age 40.2 ± 8.6 y). Data was analysed for a total of 713 shifts. Subjects wore wrist actigraphs and completed sleep and work diaries for 14-days. They also completed the Samn–Perelli Fatigue Scale at the beginning and end of shifts, and the NASA-TLX workload scale at least twice during each shift. Average (±SD) sleep length (7.2 ± 2.6 h), prior wake at shift end (12.0 ± 4.7 h), shift duration (8.0 ± 1.3) and fatigue (4.1 ± 1.3, “a little tired, less than fresh”) were within limits generally considered acceptable from a fatigue perspective. However, participants received 5 h or less sleep in the prior 24 h on 13%, were awake for at least 16 h at the end of 16% and worked at least 10 h on 7% of shifts. Subjects reported that they felt “extremely tired, very difficult to concentrate,” or “completely exhausted, unable to function effectively” on 13% of shifts. Sleep length (OR = 0.88, p < 0.01), shift duration (OR = 1.18, p < 0.05), night shift (REF = morning shift, OR = 2.12, p < 0.05) and workload ratings (OR = 1.2, p < 0.05) were significant predictors of ratings of extreme tiredness/exhaustion (yes/no). While on average, sleep loss, extended wakefulness, longer work hours and work-related fatigue do not appear problematic in this sample, there is still a notable percentage of shifts that are likely to be associated with high levels of work-related fatigue. Given the size of the Australian Rail Industry, with thousands of shifts occurring each day, this is potentially of operational concern. Further, results indicate that, in addition to sleep length, wakefulness and work hours, workload significantly influences fatigue. This has possible implications for bio-mathematical predictions of fatigue and for fatigue management more generally.