Comparing the results of five lifting analysis tools
Introduction
The prevalence and severity of work-related back injuries is a significant problem; in the State of Washington, self-insured worker's compensation claims data for the period of 1992–2000 shows that 51.5% of compensable closed claims were for back disorders (Safety and Health Assessment and Research for Prevention (SHARP), 2002). Heavy lifting has been identified as a major risk factor for the development of back injuries (Marras et al., 1993; Hildebrandt, 1987). Ergonomists have long sought ways to objectively quantify the exposures associated with heavy lifting in order to more accurately anticipate high risk activities and prescribe appropriate interventions (Dempsey, 1998). Consequently, numerous lifting analysis tools have emerged with each one having different inputs, outputs, and subsequent interpretive capacities. These tools, while advancing the ability to characterize, quantify and predict the exposures, nevertheless retain a degree of uncertainty, incompleteness, and differing attributes that practitioners need to be aware of when using and interpreting results (Fallentin et al., 2001; Janowitz et al., 2005).
Five lifting analysis methods were chosen for comparison: the revised 1991 National Institute of Occupational Safety and Health lifting equation (NIOSH) (Waters et al., 1993), the American Conference of Governmental Industrial Hygienists lifting threshold limit values (ACGIH TLV) (ACGIH, 2005), the Liberty Mutual “Snook” Lifting Tables (Snook)(Snook and Ciriello, 1991), the University of Michigan 3D static strength prediction program (3DSSPP) (University of Michigan, 2001) and the Washington State ergonomics rule lifting calculator (WA L&I) (WAC 296-62-051, 2000a, WAC 296-62-051, 2000b).
Each of the instruments has unique attributes that make it desirable for this study. The NIOSH instrument was selected because it is universally recognized and widely used throughout the world. The ACGIH TLV tool is largely based on the NIOSH instrument, but is designed to be more expedient than NIOSH. It is the most recently developed tool and used mostly within the US. The Snook, a psychophysical-based tool, is used by US practitioners to obtain design guidelines. The 3DSSPP was chosen because of its unique low back compression force predictive capabilities. Finally, the WA L&I, which is based on the NIOSH methodology, was designed for use as a regulatory instrument in Washington state and was designed to identify the highest risk jobs.
The specificity and resolution of inputs (i.e., angles, distances) varies across these tools (Table 1). All methods derive an outcome that attempts to predict the relative safety and/or risk of a lift for given populations, but use different terminology and parameters to do so. All instruments are limited in their capacity to incorporate the degree of acceleration/deceleration, shear forces, ambient temperature extremes, one-handed lifts, the lifting of unstable and odd-shaped objects, or the continuous three-dimensional (3D) forces and moments about the spine into their calculations (Fathallah, 1997).
While the literature is replete with descriptions of individual instruments, quantitative comparisons between the respective methods is less complete (Marklin and Wilzbacher, 1999; Marras et al., 1999; Waters et al., 1998). The aim of our study was to compare the results of the five lifting analyses of a common lifting task in order to clarify the similarities and differences between instruments and provide guidance to ergonomics practitioners.
Section snippets
Work parameters
A regional grocery store chain requested assistance to assess the potential impact of switching from 23 l cases to 15 l containers in their stocking operations. This opportunity was used to compare five instruments used for assessing musculoskeletal exposures. Baseline data for the analyses were collected by interviewing, observing and videotaping an experienced 95th percentile (for height) male worker while he stocked the dairy cooler with milk shipped in 23 l cases. Anatomical landmarks required
Analysis
For the purpose of normalizing the tool outcomes so as to compare inter-case level and inter-tool results, the output of each lifting instrument was converted to an exposure index (EI) similar to the NIOSH LI. The outputs (recommended weight guidelines) for all possible lifting combinations at each level were averaged. The milk case weights of 17 kg (15 l) and 26 kg (23 l) were then divided by the averaged outputs to calculate composite EIs for each level. An EI of 1.0 indicates that the
Results
The NIOSH EIs all exceeded 1.0 (Fig. 2). The average EI for 23 l cases (1.9) was 53% higher than the average EI for the 15 l cases (1.25). As shown in Fig. 2, the EI progressively increased by case level. Exposure indexes ranged from 1.14 to 1.52 for the 15 l cases and from 1.74 to 2.32 for the 23 l cases.
The ACGIH TLV EI exceeded 1.0 for all levels with levels 6 and 7 having substantially greater exposures (Fig. 3). When averaged over all levels, the EI was 53% greater for the 23 l cases (range
Discussion
The primary aim of this study was to compare outcomes of five lifting assessment instruments when applied to a uniform task (milk case lifting). As expected, all instruments predicted a higher exposure when lifting the heavier 23 l cases versus the 15 l cases, although the extent of the disparity varied between instruments. In four of the five instruments (all but 3DSSPP), lifting cases from the lowest level resulted in exposure indexes that were virtually the same or less than the mid-range
Conclusion
This study found that NIOSH, ACGIH TLV and Snook instruments provided similar results when assessing musculoskeletal exposures associated with a lifting task. The WA L&I instrument predicted only low to moderate exposures for lifts that were deemed hazardous by the above three methods. The 3DSSPP low back compression force analysis differed from these four tools in that it showed a reverse pattern of exposure prediction relative to lifting height and like the WA L&I indicated that the exposure
Acknowledgments
Funding was supplied in part by the Washington State Medical Aid and Accident Fund and the University of Washington Department of Environmental and Occupational Health Sciences.
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