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Trunk postures and upper-body muscle activations during physically demanding wildfire suppression tasks a

Daniel Neesham-Smith , Brad Aisbett

ab

& Kevin Netto

c

a

Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria, Australia b

Bushfire Co-Operative Research Centre, East Melbourne, Victoria, Australia

c

School of Physiotherapy and Exercise Science, Curtin University, Bentley, Western Australia, Australia Published online: 24 Dec 2013.

To cite this article: Daniel Neesham-Smith, Brad Aisbett & Kevin Netto (2014) Trunk postures and upperbody muscle activations during physically demanding wildfire suppression tasks, Ergonomics, 57:1, 86-92, DOI: 10.1080/00140139.2013.862308 To link to this article: http://dx.doi.org/10.1080/00140139.2013.862308

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Ergonomics, 2014 Vol. 57, No. 1, 86–92, http://dx.doi.org/10.1080/00140139.2013.862308

Trunk postures and upper-body muscle activations during physically demanding wildfire suppression tasks Daniel Neesham-Smitha†, Brad Aisbetta,b and Kevin Nettoc* a

Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria, Australia; bBushfire Co-Operative Research Centre, East Melbourne, Victoria, Australia; cSchool of Physiotherapy and Exercise Science, Curtin University, Bentley, Western Australia, Australia

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(Received 9 July 2013; accepted 30 October 2013) This study examined the trunk postures and upper-body muscle activations during four physically demanding wildfire suppression tasks. Bilateral, wireless surface electromyography was recorded from the trapezius and erector spinae muscles of nine experienced, wildfire fighters. Synchronised video captured two retroreflective markers to allow for quantification of two-dimensional sagittal trunk flexion. In all tasks, significantly longer time was spent in the mild and severe trunk flexion ( p # 0.002) compared to the time spent in a neutral posture. Mean and peak muscle activation in all tasks exceeded previously established safe limits. These activation levels also significantly increased through the performance of each task ( p , 0.001). The results suggest that the wildfire suppression tasks analysed impose significant musculoskeletal demand on firefighters. Fire agencies should consider developing interventions to reduce the exposure of their personnel to these potentially injurious musculoskeletal demands. Practitioner Summary: Wildfire fighters adopt high-risk trunk postures and utilise high levels of upper-body muscle activity to perform wildfire suppression tasks. This combination places these workers at elevated risk of musculoskeletal injury. Interventions should be developed to manage the injury exposure risk of this vital workforce. Keywords: wildfire; electromyography; posture

1.

Introduction

Wildfire poses a significant risk to the lives, communities and industries of America, Europe, Africa and Australasia (Liu, Stanturf, and Goodrick 2010). In Australia, the combination of a fire-sensitive ecosystem, an arid climate and erratic rainfall coalesce to make it the most wildfire-prone continent in the world (McLennan and Birch 2005; Aisbett et al. 2007). Rural firefighters, the vast majority being volunteers, play a vital role in protecting the Australian population from the threat of wildfire (McLennan and Birch 2005). The lives of firefighters, as well as the safety and assets of the greater community, could be at considerable risk if the health and safety needs of this workforce are not met. It is well established that wildfire fighting is a demanding occupation (Aisbett et al. 2012). Several studies have demonstrated that many common tasks and duties performed by firefighters place near maximal strain on their cardiovascular system (Brotherhood et al. 1997; Budd et al. 1997a; Phillips et al. 2011; Rodrı´guez-Marroyo et al. 2012). In addition, firefighters perform these duties in highly volatile working environments, often having to tolerate extreme radiant temperatures, thick smoke and intense noise (Aisbett et al. 2012). Whilst several studies have examined the physiological demands (Cuddy et al. 2007; Rodrı´guez-Marroyo et al. 2012; Raines et al. 2013) and environmental (Budd 2001; Cuddy et al. 2007) stressors of wildfire fighting, no study has investigated the musculoskeletal demands of the occupation. In many physically demanding occupations, a clear dose–response association exists between high musculoskeletal demand and musculoskeletal injury (Kumar and Kumar 2008; Nelson and Hughes 2009). Considering musculoskeletal injury is the most prevalent injury suffered on the Australian fireground, accounting for 33% of all injuries (Aisbett et al. 2007), it is reasonable to assume that the musculoskeletal demands imposed on wildfire fighters are significant. As such, in order to completely understand the physical demands of wildfire suppression, it is essential the musculoskeletal demands of the occupation be quantified. Currently, no universal strategy exists to quantify the musculoskeletal demands in occupation (Bos, Kuijer, and FringsDresen 2002). However, in ergonomics, a conceptual framework is generally relied upon to systematically guide investigators with their approach (Westgaard and Winkel 1996; Radwin, Marras, and Lavender 2001). The models of Westgaard and Winkel (1996) demonstrate that a certain work situation is accomplished by a particular working method: a

*Corresponding author. Email: [email protected] † Present address for Daniel Neesham-Smith: Leighton Contractors Pty Limited, Infrastructure Division - Southern, Melbourne, Victoria, Australia q 2013 Taylor & Francis

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method which is usually imposed by the constraints of the work setting. The adopted technique leads to specific postural changes or movements of the human body and the exertion of forces (Westgaard and Winkel 1996). Indeed, specific postures (e.g. lumber flexion . 458; Punnett et al. 1991) and high levels of muscle exertion (e.g. muscle activations . 30% of maximum voluntary contraction, MVC; Winkel and Westgaard 1992) are significant risk factors, depending on an individual’s work capacity, for sustaining work-related musculoskeletal injury (Westgaard and Winkel 1996). Existing wildfire fighting research has documented the physically demanding tasks (Phillips et al. 2012), and firefighters’ cardiorespiratory (Rodrı´guez-Marroyo et al. 2011, 2012), thermoregulatory (Budd 2001; Rodrı´guez-Marroyo et al. 2012; Raines et al. 2013) and metabolic (Cuddy et al. 2007; Cuddy and Ruby 2011) responses to their work. No information regarding the musculoskeletal stress of wildfire fighting exists. Thus, the aim of this study was to quantify trunk postures and upper-body muscle activations during physically demanding wildfire suppression tasks.

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2.

Methods

Nine male incumbent volunteer firefighters participated in this study (mean ^ SD age: 31 ^ 8 yr; height: 1.8 ^ 0.05 m; weight: 87.4 ^ 18.0 kg; service: 6 ^ 3 yr). Standard fire-retardant personal protective clothing (pants, gloves, boots, goggles and hard hat), designed to shield the firefighter from environmental hazards and injury, was worn throughout the testing. Participants substituted firefighting jackets with an upper-body compression garment (Skins, Australia) to allow accurate quantification of trunk posture. Ethical approval was obtained from the Deakin University Human Ethics Advisory Group and participant gave informed consent prior to testing. Participants performed four simulated wildfire suppression tasks. These tasks were chosen as they have been previously shown to elicit the highest mean or peak heart rates, take the longest periods and/or occur most frequently during wildfire suppression (Phillips et al. 2011). Charged advance (CA). The participant and an additional operator collectively advanced a charged hose 50 m over flat terrain. The hose rig consisted of three lengths (90 m) of 38-mm canvas fire hose and a branch nozzle (Pro 332 Branch, Protek, Australia). A distance of 10 m was allocated between the rear of the fire tanker and the start position to arrange the three lengths of hose in an operational zigzag formation. All hose rig preparations were performed by additional operators. The participant was allocated to the second hose position, which was located 1.5 m from the hose branch (Figure 1a). The second position was chosen since this role has elicited higher oxygen uptake and heart rate response than the first, third and fourth positions (Phillips et al. 2008). Making up on the bight (MOB). Participants worked independently to make up (coil) a bowled (rolled out) 30-m length of uncharged, 38-mm rubber fire hose (Figure 1b). Fire line construction (FLC). To replicate FLC, participants were required to clear a 10 £ 1 m area filled with 400 l of mulch debris using a rakehoe (Fire Trader, Australia), a dual-sided metal rake with a six-prong face and flat sharpened edge. A researcher ensured the area was satisfactorily cleared before completion for all participants. A fire line width of 1 m was implemented to replicate standard operational practice (Figure 1c). Blacking out (BO). Participants entered a clearly defined 3 m £ 3 m area, where three logs of different lengths and widths lay to replicate the varied debris experienced on the fireground. Additionally, 160 l of mulched debris was spread around the logs perimeter. To simulate the inspection of live embers, participants commenced the task by striking the logs with a rakehoe six times; this was then repeated along the logs opposite side. Thereafter, participants cleared the area of mulched debris. For all participants, the same researcher confirmed the area was satisfactorily cleared before the task was considered completed (Figure 1d). Two trials of each task were performed with experimental recordings being made during the second attempt, with the first serving as a familiarisation. Tasks were performed in a randomised order. A 10-min passive rest period was enforced between both task repetitions and subsequent tasks. Participants were instructed to perform each task at normal operational pace. To ensure all tasks were completed to a satisfactory operational standard, each task was adjudicated by the same experienced firefighting official. To preserve environmental validity, each task was performed on terrain and vegetation characteristic of that experienced on the firegrounds of south-eastern Australia. Surface electromyography (EMG) signals were recorded bilaterally from m. trapezius descendens at a position 50% of the line from the acromion to the spinous process of vertebra C7 and m. lumbar erector spinae, 2 cm lateral from the spinous process of vertebrae L1 (Freriks et al. 1999). Electrode sites were shaved, scoured and cleaned in customary fashion. Pre-gelled, dual 40-mm £ 22-mm circular Ag – AgCl disposable surface electrodes (Noraxon, USA) were adhered with a 20-mm centre-to-centre distance along the muscle fibre orientation. The EMG signals were sampled at 1500 Hz via a wireless EMG system (Telemyo 2400T DTS, Noraxon, Arizona, USA), which transmitted signals to a receiver connected to a laptop personal computer (Lenovo, USA), where the data were recorded through the manufacturer supplied software (MyoResearch XP Master Edition, Noraxon, Arizona, USA). Prior to the commencement of task

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Figure 1. Participant completing a charged advance (CA, Figure 1a), making up on the bight (MOB, Figure 1b), fire line construction (FLC, Figure 1c) and blacking out (BO, Figure 1d).

simulations, participants performed three, five-second maximum voluntary isometric contractions (MVICs) for the purpose of EMG normalisation. Throughout each task, a wheeled-tripod mounted digital video camera (GZ-MG330HAA, JVC, Japan) was used to capture the movement of two 25-mm spherical retroreflective markers (Medical Motion, USA). Markers were located over the iliac crest and lowest palpable edge of the rib cage to create a two-point model of the trunk. The video camera sampled at 25 Hz and was adjusted to the height of the participant’s waist and travelled orthogonally to their sagittal plane of motion, at a constant distance of three meters. All EMG signals were full-wave rectified and root-mean-square smoothed over a 200-ms window using manufacturer supplied software (MyoResearch XP Master Edition, Noraxon, Arizona, USA) (Merletti et al. 1999). Processed signals were normalised to the maximum muscle activation determined from the MVICs (expressed as % MVIC). The highest level of muscle activity obtained for each muscle recorded from the participant during the MVIC test series was selected as the reference level. Processed EMG signals were sectioned into concise epochs based on either temporal factors or clearly identifiable discrete movement patterns. These epochs represented the tasks’ start, middle and end phases. For CA and MOB, time to completion was divided into quintiles, with the first, third and fifth quintiles selected for analysis. For FLC, three epochs, each consisting of 10 complete rakehoe strokes, were selected. The first epoch commenced from the start of the 2nd stroke to the completion of the 11th. The 2nd was identified by calculating the number of all strokes, and analysing the middle 10, with the final epoch consisting of the 10 strokes preceding the last of the task. BO was represented by only two epochs (start and end) as only the strike component was analysed. Each epoch comprised six complete rakehoe log strikes with the first six representing the task’s start and the final six as the end of the task. Strokes (FLC) and strikes (BO) were defined as starting and ending with the rakehoe furthest away from the body. Video files were digitally captured to allow investigation in movement analysis software (eHUMAN 6.0, HMATechnology, Canada). Due to the pre-synchronisation of EMG with the video data, identical epochs to EMG analysis were analysed. Processing required the manual digitisation of the two retroreflective markers to obtain angular positional data of the trunk. In cases where markers were visually occluded, marker position was interpolated using a quintic spline

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(prediction) function through previous and proceeding video frames. Sagittal trunk flexion and extension angles were taken from the markers connecting the vertical line extending off the apex of the iliac crest, to the line connecting the rib and ilium. From the digitised video files, the time spent in neutral ( 258 to 158), mild (168 to 458) and severe (. 458) postural zones (Punnett et al. 1991) was quantified as a percentage of total epoch duration. Extension (.2 58) was not identified in any task simulations and, therefore, was not included in further analysis. From the digitised video files, the time spent in neutral, mild and severe postural zones was quantified as a percentage of total epoch duration. Prior to analyses, the normality of the data was confirmed using Shapiro –Wilk tests. Thereafter, a three-way analysis of variance (ANOVA) with task, muscle and phase as the within-participant factors was used to identify differences in mean and peak muscle activation, and postural zone between tasks, muscles and task phases. When ANOVA revealed a significant interaction, simple effects analyses were used to identify where differences lay. The level of statistical significance was set at p , 0.05. All statistical analyses were performed using Statistical Package for the Social Sciences software (IBM SPSS V17.0, USA)

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3.

Results

Initial postural analysis showed no three-way interaction for the percentage time for postural zone, phase and task ( p ¼ 0.395). Furthermore, no interactions were evident in percentage time for postural zone and phase, or phase and task ( p ¼ 0.325). A significant interaction was, however, identified in percentage time in postural zones and task ( p , 0.001). For CA, 58 ^ 28.2% and 50 ^ 28.2% more time was spent in the mild zone compared to both the neutral ( p , 0.001) and severe ( p , 0.001) zones, respectively. Similarly, a greater percentage of time was spent in mild comparative to neutral ( p , 0.001) and severe ( p , 0.001) zones during BO. For MOB, 44 ^ 30.3% and 34 ^ 30.3% more time was spent in the neutral ( p , 0.001) and severe zones ( p ¼ 0.029), respectively, when compared to mild. For FLC, the percentage of time spent in the severe zone was 79 ^ 22.3% greater compared to time in the neutral zone ( p , 0.001) and 66 ^ 22.3% greater than time spent in the mild zone ( p , 0.001). When comparisons between tasks were made, 50 ^ 24.4%, 45 ^ 24.9% and 33 ^ 25.8% more time was spent in the neutral zone during MOB compared with FLC ( p , 0.001), CA ( p , 0.001) and BO ( p ¼ 0.001), respectively. During CA, 60 ^ 23.8% and 52 ^ 23.8% more time was spent in the mild zone, compared with MOB ( p , 0.001) and FLC ( p , 0.001). Time spent in the mild zone during BO was 54 ^ 24.7% and 47 ^ 24.7% higher, respectively, than for MOB ( p , 0.001) and FLC ( p , 0.001). Throughout FLC, 64 ^ 27.1%, 58 ^ 26.2% and 43 ^ 25.7% more time was spent in the severe zone when compared with BO ( p , 0.001), CA ( p , 0.001) and MOB ( p , 0.001), respectively. A main effect was observed for postural zones, with 15 ^ 18.9% greater time spent in mild than neutral ( p ¼ 0.002) across all tasks and phases. Further, 19 ^ 18.9% more time was spent in the severe zone than neutral ( p , 0.001) across all tasks and phases. Initial analysis revealed no significant interaction in mean muscle activations for phase, task and muscle ( p ¼ 0.978). Additionally, no interactions were evident for phase and task, phase and muscle or muscle and task ( p ¼ 0.562). Main effects for collective mean activation levels were detected for task and phase. A 12 ^ 11.5% and 10 ^ 11.4% greater activation across all muscle and phases was evident during the CA when compared to MOB ( p , 0.001) and FLC ( p , 0.001), respectively. Similarly, higher levels of activation across all muscle and phases were elicited for BO compared to MOB ( p , 0.001) and FLC ( p , 0.001), with differences of 8 ^ 11.9% and 6 ^ 11.8%, respectively. For the main effect of phase, a 6 ^ 10.9% increase in activation was evident during the end phase when compared to the start phase across all tasks and muscles ( p ¼ 0.001). Initial analysis of peak muscle activation revealed no three-way interaction for comparisons of phase, task and muscle ( p ¼ 0.992). Further, no interactions were evident between phase and muscle ( p ¼ 0.876), phase and task ( p ¼ 0.992), or muscle and task ( p ¼ 0.279). Main effects were observed for task, muscle and phase. Comparisons between tasks revealed peak muscle activation was 18.2 ^ 16.4% greater in BO compared to both FLC ( p , 0.001) and MOB ( p , 0.001) across all muscles and phases. Comparisons between muscles across all tasks and phases showed peak muscle activation in the right trapezius was 14 ^ 16.0%, 15 ^ 16.0% and 18 ^ 16.0% lower than peak activation in the left trapezius ( p , 0.001), right erector spinae ( p , 0.001) and left erector spinae ( p , 0.001), respectively. Comparisons between phases showed an 8 ^ 15.2% higher ( p ¼ 0.016) peak muscle activations were experienced during the end phase compared to the start, across all muscles and tasks. 4.

Discussion

The aim of this study was to examine the trunk postures and upper-body muscle activations of four physically demanding tanker-based wildfire suppression tasks. The findings of this investigation demonstrated FLC was the most posturally demanding of the four tasks, with 86% of the task spent in severe sagittal trunk flexion. However, both mean and peak muscle activations during FLC were not significantly greater than three other tasks investigated. Both CA and BO elicited

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the highest mean activation levels of all tasks. Furthermore, BO elicited the highest peak muscle activation when compared to MOB and FLC. 4.1 Posture The severe flexion predominance noted during FLC is consistent with a number of tasks where the foci are at or near ground level. Gregory, Milosavljevic, and Callaghan (2006) identified that sheep shearers spend 97% of time in severe flexion when clipping sheep. Further, Punnett et al (1991) demonstrated industrial workers spend 74% of time in severe flexion when manufacturing car chassis. Similar postural findings have also been demonstrated during harvesting, shovelling and cleaning (Kumar and Cheng 1990; Nag and Pradhan 1992; Kumar and Kumar 2008; Hwang, Kong, and Jung 2010). It has been reported that workers who spend extended periods of work cycles in severe flexion are up to nine times more likely to sustain a work-related back injury (Punnett et al. 1991; Kumar, Ferrari, and Narayan 2005). Biomechanically, the heightened level of injury risk from assuming such postures can be attributed to the viscoelastic creep response within the spine (McGill 1992). When the trunk is placed in severe flexion, the weight of the upper body is primarily supported by a passively generated extension moment provided from spinal ligaments, intervertebral discs, spinal facets and the passive component of the extensor muscle tendon units (Shin, Lee, and Kim 2007). If sustained for extended periods, even as short as one minute, significant deformation (i.e. creep) of these passive support structures occurs (McGill 1992; Shin, Lee, and Kim 2007). The development of creep introduces significant laxity into the spinal system (McGill 1992), potentially leading to acute intervertebral subluxation (McGill 1997), ligament rupture (Solomonow 2004) and facet fracture or vertebral compression (Adams and Dolan 2005). As such, the postures evident during FLC can be considered highly injurious to firefighters. Following a period of severe flexion, residual laxity in passive support structures remains for a period of time, placing the spine in state of hyper-flexibility (McGill 1992). In this state, the stability of the spine is compromised, making it more susceptible to compression and shear force injuries (McGill 1992). It is suggested that full recovery from viscoelastic creep requires between six to seven times the duration of exposure (Hoops et al. 2007; Le et al. 2007). Thus, to reduce firefighters risk of injury during and subsequent to FLC, interventions should be aimed at work-to-rest ratios. In situ, the mean duration of FLC has ranged from 39 s (Budd et al. 1997b) to 8 min (Phillips et al. 2011), whilst volunteer Australian firefighters reported that FLC work could last as long as 30 min during a subjective task analyses (Phillips et al. 2012). Given the upper range, adopting rest periods six to seven times the length of the FLC task will not be practical for fire agencies who often have to balance the health and safety risks of deploying fatigued workers against the community risks of not deploying any firefighters (Aisbett et al. 2012). The need to investigate and (if required) implement work-to-rest interventions such as task rotation should, however, vary across agencies and jurisdictions, to account for the variability in task demands caused by the terrain, vegetation, weather, fire behaviour and fire suppression tactics. For example, for Australian volunteer rural firefighters, repetitive FLC work is scarcely performed (Phillips et al. 2012), so there may be no need to mandate task rotations that permit rest from stressful postures. Alternatively, salaried crews in North American and Australia are more likely to perform prolonged FLC. However, many of these crews use the ‘step up’ method where each firefighter rakes their specific area of fire line and then pauses until their adjacent colleague ‘steps up’ to the next un-raked patch (Budd et al. 1997b). Budd et al. (1997b) reported that the step up method afforded firefighters 10-s break for every 40 s of FLC, and across an approximately four-hour period, they engaged in FLC for only 113 ^ 55 min (or 47 ^ 23% of total time). Given the intermittent nature wildfire suppression by these crews (Cuddy et al. 2007), it is possible that the firefighters themselves have developed work pacing strategies to balance their productivity and safety. The prospect that workers in high-risk occupations may develop their own informal risk-management strategies has been recently argued by Dawson, Chapman, and Thomas (2012). Future research into the work pacing strategies adopted by experienced firefighters and the implications these practices have on spinal fatigue could produce valuable outcomes for agencies striving to promote and preserve the health and safety of their workers. 4.2 Muscle activation The mean and peak muscle activations elicited during this investigation suggest all the wildfire suppression tasks analysed have the potential to cause musculoskeletal injury. Global ergonomic recommendations (Winkel and Westgaard 1992; Westgaard and Winkel 1996) advise that exposure to mean activations in the range of 8 –30% MVC and peak activations of 30 –50% MVC should be limited as they are a high risk factor to work-related musculoskeletal injury. It is suggested that muscle activations generated at sustained sub-maximal levels engage only a fraction of the motor units available (Visser and van Diee¨n 2006). The continuous activity of these motor units during occupational tasks is hypothesised to cause degenerative damage that can lead to muscle myalgia (Visser and van Diee¨n 2006). Additionally, high activation of muscles may cause their corresponding tendons to stretch, thereby compressing their vascular epitenon, peritenon and endotenon microstructures (Visser and van Diee¨n 2006). If maintained, this may cause ischaemia, fibrillar tearing and inflammation

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(Kumar 2001). Furthermore, sustained high mean muscle activation reduces the failure tolerance of the engaged muscle and its associated tendons (Kumar 2001). Although the levels of postural exposure and muscle activation evident across the four tasks are indicative of high load and potential musculoskeletal injury, exposure to such loads may not be injurious if the exposure time is sufficiently short (Laursen and Schibye 2002). As was described previously (for FLC), fireground tasks can be quite brief, with Phillips et al. (2011) reporting that many of the tasks simulated in this study last less than 90 s in situ. However, an important work-related factor that must be taken into consideration is cumulative loading. It is understood that injury results from the accumulated effect of transient loads that, in isolation, are insufficient to exceed tissue tolerances (Kumar 2001). It is when this loading accumulates by repeated exposures that the internal tolerances of tissues are eventually exceeded (Kumar 2001). Considering fireground shifts can last up to 16 hours with successive work days, the cumulative effect of these loads is an area that requires further assessment.

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5.

Conclusion

The findings of the present study suggest that wildfire fighters may be at elevated risk of musculoskeletal injury due to the non-neutral postures assumed, as well as the high mean and peak muscle activations elicited whilst performing four common wildfire fighting tasks. This workforce would benefit from task and shift-based interventions aimed at managing and/or reducing exposure to such injurious work demands. Fire services can use the information gained in this study as a foundation on which further research into the musculoskeletal demands of wildfire suppression can be constructed and effective interventions can be developed.

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