Increasingly, the risks associated with excessive and unmitigated fatigue is being realised in both the public and industrial spaces. The mining sector, in particular, has faced increasing pressure to manage fatigue risk.
In view of this, the Mines Inspectorate of the Department of Natural Resources and Mines recently released an updated guidance note to the management of fatigue, titled ‘QGN 16 Guidance Note for Fatigue Risk Management’ (2013). This guidance note (herein referred to as QGN16) replaced the existing fatigue management guidance note from 2001. Compared to the 2001 guidance note, which gave little assistance in identifying factors such as high risk roster design, fatigue risk factors, and suggested fatigue risk thresholds, QGN16 provides greater guidance (using a risk-based approach) to the fatigue-related issues relevant to mining.
Contributors to Fatigue
Fatigue is a complex and multi-factorial phenomenon. A range of different factors may contribute to the genesis of fatigue. Some of these contributors are shown in Figure 1.
Some of the key fatigue risks will now be expanded briefly upon by outlining key risk thresholds from the QGN16, supported by data from scientific studies in order to communicate risk.
Fatigue Risk Factors
QGN16 outlines the risk profile of working during then night. Night shifts are always more fatiguing, due to the circadian rhythm and higher sleepiness during night hours (QGN16), and due to reduced sleep length and quality of sleep during the day hours. A recent mining-based study found that reaction time responses were significantly slower at the end of night shifts compared to any other testing time (e.g. start and end of day and night shifts; Ferguson, Paech, Dorrian, Roach & Jay, 2011). Figure 2 panel A visually demonstrates the higher risk associated with working night shifts (30.4%) and afternoon shifts (18.3%), compared to the morning/day shifts.
QGN16 expands on the risk associated with successive night shifts. Less than four successive night shifts (SNS) represents lower risk; four SNS represent moderate risk; and five to seven and more SNS represent high to extremely high fatigue risk. We can see from Figure 2 panel B below that risk of accidents increases over each SNS. By the second SNS, average risk has increased by 6% (relative to day one). A 17% average increase of risk is seen during the third night shift and an increase by 36% for the fourth night shift, both compared to the first night shift.
Figure 2. Relative risk of accident of working either afternoon or night shifts compared to the morning shift (panel A); and relative risk of working four successive night shifts, compared to baseline risk on day one (panel B). Higher relative risk (Y-axes) indicates greater accident risk. Retrieved from Folkard and Tucker (2003, pg. 97).
Hours Worked in Shift
Another risk highlighted in QGN16 is the number of hours worked in a shift. Lower risk is associated with 8 hours worked in a single shift. Moderate risk is associated with over 8 hours worked in a single shift, but equal to or less than 12 hours. High to extremely high risk of fatigue is associated with working 12 hours and more in a single shift. In Figure 3 panel A we see how the average risk of an accident increases over the course of hours on duty. This is with the exception of a small decrease in risk after five hours duty, which is said to be due to the positive influence of a rest break. The risk at 12 hours on duty is double that at 8 hours duty.
It should be noted that no negative effects on safety incident frequency or absenteeism rates were discovered when switching from an 8-hour/7-day roster schedule to both either a 12-hour/7-day or 12-hour/5-day roster schedule (respectively) in an Australian coal mine (Baker, Heiler & Ferguson, 2003). An increase in absenteeism was observed in the maintenance sector of the mine when unregulated and excessive overtime was introduced on the 12-hour/5-day roster, however (Baker et al., 2003).
Furthermore, in another study based in the Australian coal mining industry, no association between hours of work on the number or severity of safety incidents or injuries were found (Cliff & Horberry, 2008).
Figure 3 panel B shows how rest breaks during a shift can influence accidents. Risk increases fairly linearly between each rest break during the shift, and roughly doubles by the last 30 minute period of work before the next break occurs. QGN16 gives guidance on the use of rest breaks within shifts, suggesting that:
- Less than 3 hours between breaks at night or less than 5 hours during the day, and over a 30 minute main break for an 8+ hour shift represents lower risk;
- 3 hours between breaks at night or 5 hours between breaks during the day, and a 30 minute main break for an 8+ hour shift represents moderate risk; and
- Over 3 hours between breaks at night or over 5 hours between breaks during the day, and less than a 30 minute main break for an 8+ hour shift represents high to extremely high risk.
The clear influence that within-shift rest breaks can play on safety is evident.
Figure 3. How the mean relative risk of an accident changes over hours on duty (panel A); and how minutes since last within-shift rest break influences risk (panel B). Higher mean relative risk (Y-axes) indicates greater accident risk. Retrieved from Folkard and Tucker (2003, pg. 98).
Hours Worked Per Week
QGN16 identifies the hours worked per week as a risk factor. Forty hours per week and less worked indicates lower risk of fatigue. Over 40 but equal to and less than 60 hours worked per week indicate moderate risk. Over 60 hours worked per week indicates high to extremely high risk of fatigue. In a study looking at the risk of a safety incident among US construction workers (Dong, 2005), it was found that working over 40 hours per week increased injury risk slightly. However, the risk of injury was found to nearly double when average weekly work hours went above 50 hours per week (odds ratio of an accident of 1.98).
In another US study across multiple industries and professions (Dembe, Erickson, Delbos & Banks, 2005) it was found that working over 60 hours per week raised injury risk by 23%. The trend of increased injury risk as a function of weekly work hours are shown in Figure 4.
Figure 4. Trend in the rate of safety incidents as a function of hours worked per week. Safety incidents are denoted with the diamond symbols and unbroken line, with a regression line (perforated line) indicating the direction of change. Adapted from Dembe et al. (2005, pg. 593).
Sleep Risk Factors
When addressing the topic of fatigue, it is crucial to understand that although it may appear that the roster schedule and hours of work may be the primary links in the causation of fatigue, this may not actually be the case. The true link may be that as hours of work increase, the time left for sleep decreases (Dawson, McCulloch & Baker, 2001); resulting in commensurate increases in fatigue and reduced alertness (Dawson et al., 2001).
This link has been observed in mining. In 35 mining operators working a range of roster schedules it was found that sleep history (and their prior time awake) was a significant predictor of reaction time response (Ferguson et al., 2011). Reaction time responses depended on the amount of prior sleep obtained such that less than 6 hours of sleep (in the prior 24 hours) produced the slowest reaction times; conversely, sleep of more than 7 hours produced less impairments in reaction performance. These effects occurred independently of the rostering schedule.
Regarding risk factor thresholds, sleep during the night, and 8 hours or more sleep per night represent lower risk; whereas, sleep during the day (e.g. after a night shift), or 6 hours or less total sleep represents higher risk (NSW Mining Industry Health Working Party, 2009). Self-reported sleeping disturbances have been shown to nearly double the risk of having a fatal work accident (Akerstedt, Fredlund, Gillberg & Jansson, 2002). Furthermore up to 13% of all workplace injuries may be attributable to sleeping problems (Uehli et al., 2013).
Using blood alcohol concentration (BAC) as a comparison, it has been shown that only two hours of sleep loss in a single night can produce performance impairments similar to a BAC of 0.05% (Roehrs et al., 2003). Other researchers found that simple reaction time reduced to a BAC of 0.4-0.6% after restricting the sleep of volunteers to five hours per night over four successive nights (Elmenhorst et al., 2009). Based at a fly-in/fly-out mining operation in Australia it was discovered that performance levels (indicative of fatigue) reduced to a BAC equivalent of 0.05% after approximately eight successive days of day shifts (Muller, Carter & Williamson, 2007); greater impairments set in much earlier during successive night shifts. The latter two studies indicate the effects of chronic sleep loss and the attainment of a ‘sleep debt’. Figure 5 shows the performance data from the aforementioned mining study. Extended times awake also have negative consequences, with performance after 16-17 hours of continued wakefulness declining to levels comparable to BAC 0.05% (Dawson & Reid, 1997).
Findings that reduced sleep lead to dose-dependent decreases in performance are applicable to mining. Total average sleep times in mining environments may be as low as 6.1 hours per night (for day shifts), and 5.7 hours per day (for night shifts, sleeping during the day), compared to 7.4 hours on days off (Ferguson et al., 2010).
Figure 5. Performance data indicating the percentage change over 10 successive day shifts. Adapted from Muller et al. (2007, pg. 70).
Additional Sleep Risk Factors
The difficulty with fatigue is that it its causation is multi-factorial and may have many contributors. For instance, the hours of work may increase fatigue by reducing the total time available for sleep. Early morning shift starts (common in fly-in/fly-out mining environments) can also significantly reduce total sleep length, of which people rarely compensate for by going to bed earlier the night before (Paech et al., 2010). Moreover, the recovery afforded during 2-3 days of rest and leave (and indeed, on weekends during ‘regular’ work weeks) may be inadequate to return fatigue-related performance impairment back to baseline (Belenky et al., 2003; Paech et al., 2010). Additionally, people have been shown to generally have poor ability to predict their level of performance impairment due to chronic sleep loss (Van Dongen, Maislin, Mullington & Dinges, 2003). The latter findings indicate two pernicious effects of chronic sleep loss, and a potential limitation of relying solely on people self-reporting their performance or fatigue level.
Sleep (and fatigue) may also be affected by underlying health, medical and sleep disorders, social life, drugs, alcohol, obesity and more (QGN16). Hydration can also be a contributing factor to fatigue (Muller et al., 2007), although this may be more related to physical fatigue.
Sleep disorders are common in Australia (around 8.9% of the population have one of three major sleep disorders; Access Economics, 2011); yet, under-recognised and given little attention. Obstructive sleep apnoea (OSA), a common sleep disorder, has been shown to double the risk of vehicle crash compared to drivers who do not have OSA (Tregear, Reston, Schoelles & Phillips, 2009). Thus, for work tasks that are safety-critical (e.g. driving, plant and machinery operation etc.), underlying sleep disorders could potentially predispose people to serious harm.
QGN16 suggests that sleeping disorders (and key predictive risk factors such as obesity, snoring, sleeping difficulties, fitness etc.) should be considered within fatigue risk assessments.
Taken together, the key point is that a systematic manner is required when addressing fatigue risk. Risk assessments must be cognisant of the different contributory mechanisms leading to fatigue. Whilst restrictions on the hours of work can be a sound risk control, it is limited in its ability to control for other mechanisms of fatigue, particularly as a result of sleep and circadian (i.e. time of day) factors. Thankfully, the QGN16 guideline provides a thorough and robust approach to addressing fatigue risk in mining environments.
Considering this point, then, and based on the current understanding of fatigue risk based on the QGN16 document, is your company managing fatigue so far as is reasonably practical?
A fatigue risk checklist can be downloaded here order to kick-start a fatigue intervention.