Task-based estimation of mechanical job exposure in occupational groups

Cost and statistical efficiency of posture assessment by inclinometry and observation, exemplified by paper mill work

Postures at work are paramount in ergonomics. They can be determined using observation and inclinometry in a variety of measurement scenarios that may differ both in costs associated with collecting and processing data, and in efficiency, i.e. the precision of the eventual outcome. The trade-off between cost and efficiency has rarely been addressed in research despite the obvious interest of obtaining precise data at low costs. Median trunk and upper arm inclination were determined for full shifts in 28 paper mill workers using both observation and inclinometry. Costs were estimated using comprehensive cost equations; and efficiency, i.e. the inverted standard deviation of the group mean, was assessed on basis of exposure variance components. Cost and efficiency were estimated in simulations of six sampling scenarios: two for inclinometry (sampling from one or three shifts) and four for observation (one or three observers rating one or three shifts). Each of the six scenarios was evaluated for 1 through 50 workers. Cost-efficiency relationships between the scenarios were intricate. As an example, inclinometry was always more cost-efficient than observation for trunk inclination, except for observation strategies involving only few workers; while for arm inclination, observation by three observers of one shift per worker outperformed inclinometry on three shifts up to a budget of €20000, after which inclinometry prevailed. At a budget of €10000, the best sampling scenario for arm inclination was 2.5 times more efficient than the worst. Arm inclination could be determined with better cost-efficiency than trunk inclination. Our study illustrates that the cost-efficiency of different posture measurement strategies can be assessed and compared using easily accessible diagrams. While the numeric examples in our study are specific to the investigated occupation, exposure variables, and sampling logistics, we believe that inclinometry will, in general, outperform observation. In any specific case, we recommend a thorough analysis, using the comparison procedure proposed in the present study, of feasible strategies for obtaining data, in order to arrive at an informed decision support.

Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)

Data on the use of time in different exposures, behaviors, and work tasks are common in occupational research. Such data are most often expressed in hours, minutes, or percentage of work time. Thus, they are constrained or ‘compositional’, in that they add up to a finite sum (e.g. 8 h of work or 100% work time). Due to their properties, compositional data need to be processed and analyzed using specifically adapted methods. Compositional data analysis (CoDA) has become a particularly established framework to handle such data in various scientific fields such as nutritional epidemiology, geology, and chemistry, but has only recently gained attention in public and occupational health sciences. In this paper, we introduce the reader to CoDA by explaining why CoDA should be used when dealing with compositional time-use data, showing how to perform CoDA, including a worked example, and pointing at some remaining challenges in CoDA. The paper concludes by emphasizing that CoDA in occupational research is still in its infancy, and stresses the need for further development and experience in the use of CoDA for time-based occupational exposures. We hope that the paper will encourage researchers to adopt and apply CoDA in studies of work exposures and health.

Equal health at work? Protocol for an observational study of work organisation, workload and musculoskeletal complaints among women and men in grocery retail

INTRODUCTION

Women generally report more work-related musculoskeletal complaints than men and have higher rates of sickness absence, even within occupations. One likely reason is that work tasks within the occupation are gendered, that is, women and men have different tasks, even when sharing the same job title. Retail is an appealing sector for studying working conditions and work environment in a gender context. The prevalence of work-related complaints is high, physical loads may differ considerably between tasks and the distribution of tasks is likely gendered. The overall aim of this study in retail is to examine factors at the organisational and individual level that may, in a gender perspective, explain working conditions, work tasks, workloads and musculoskeletal health.

METHODS AND ANALYSES

Data will be collected in two grocery stores, each with 50-70 workers, at two occasions interspersed by about 1 year. In each of these four waves, data collection will include a web-based questionnaire to all workers addressing, for example, work tasks, psychosocial factors, fatigue and pain; semistructured interviews with managers and approximately 10 workers addressing, for example, competences and decision levels; and technical measurements of postures, movements and heart rate in about 30 workers. The study is novel in combining an organisational gender perspective addressed through qualitative methods with a quantitative analysis of tasks, workload and health. The design allows an examination of both how genders may differ, and why they may differ, as well as analyses of the extent to which gendered working conditions change over time in the two participating stores.

ETHICS AND DISSEMINATION

Approval of the study by the Swedish Ethical Review Authority (reference number 2017/404) has been obtained. This work will be disseminated by publication of peer-reviewed papers in scientific journals, presentations at scientific conferences and in meetings with representatives from Swedish retail, including unions and employers' organisations.

Radio frequency identification to measure the duration of machine-paced assembly tasks: Agreement with self-reported task duration and application in variance components analyses of upper arm postures and movements recorded over multiple days

Technical advances in inertial measurement units (IMUs) with data logging functionality have enabled multi-day collection of fullshift upper arm postures and movements. Such data are useful for characterizing job-level exposures and, when coupled with task-level information, can inform interventions to mitigate high-exposure tasks. Previously reported methods for capturing task-level information, however, were limited primarily to self-report diaries or direct observation. In this study of machine-paced manufacturing workers (n=6), a low-cost radio frequency identification (RFID) system was used to collect information about when, and for how long, specific assembly tasks were performed during up to 14 consecutive work shifts (76 total work shifts across the six participants). The RFID data were compared to information collected with a self-report diary using Bland-Altman analyses. In addition, the RFID data were paired with IMU data to identify task-level exposures from within full-shift recordings of upper arm postures and movements. These data were then used to estimate the relative contributions of between- and within-worker sources of variance to overall variance in posture and movement summary measures using hierarchical random-effects analysis of variance (ANOVA) techniques. Average estimates of daily task duration based on RFID data were comparable to estimates obtained by self-report (mean bias < ±1 minute) but with substantial variability (limits of agreement > ±100 minutes). In addition, the ANOVA models containing task-level information suggested a substantial amount of the overall exposure variance was attributed to repeated observations of the same task within a work day. These findings (i) suggest that while the RFID system used in this study performed adequately, further refinement, validation, and/or alternative strategies may be needed and (ii) underscore the importance of repeated full-shift and task-based measurement approaches in characterizing physical exposures, even in machine-paced environments.

Comparison of muscle activity from upper trapezius and wrist extensors between dominant and non-dominant upper limbs during computer-based tasks

BACKGROUND

Sustained low-level muscle activity occurring during computer-based tasks is associated with the development of WMSDs (work-related musculoskeletal disorders) and this biomechanical exposure may be different between limbs.

OBJECTIVE

To compare muscle activity from dominant and non-dominant upper trapezius (UT) and wrist extensors (WE) during computer-based tasks in real work settings.

METHODS

Forty-five workers were monitored during two hours while performing their usual administrative tasks. Surface electromyography (sEMG) was recorded from UT and WE muscles in both sides. Rest and general exposure variables were calculated.

RESULTS

The 50th percentile demonstrated little muscle activity demand, for both dominant and non-dominant UT and no difference between sides was observed. The dominant WE muscles had lower measures of rest and higher muscle activity when compared with the non-dominant side.

CONCLUSIONS

Differences in sEMG between upper limbs were only found in WE muscles, probably due to the use of the mouse. The overall low-level muscle activity suggests a constant activation of the same motor units for the entire data-collection period, which can be considered harmful for musculoskeletal health.

Correctness of Self-Reported Task Durations: A Systematic Review

Objectives

Duration of tasks in a job is an essential interest in occupational epidemiology. Such duration is frequently measured using self-reports, which may, however, be associated with both bias and random errors. The present systematic literature review examines the correctness of self-reported durations of tasks, i.e. the extent to which they differ from more valid reference data due to either systematic or random errors, and factors influencing this correctness, with particular emphasis on the assessment of exposures of relevance to musculoskeletal disorders.

Methods

The search for relevant studies included the databases ISI Web of Science, MEDLINE, EBSCO HOST, Proquest, and Psycnet.

Results

Thirty-two articles were identified; of which, 23 examined occupational tasks and 9 examined non-occupational tasks. Agreement between self-reports and a more correct reference was reported for, in total, 182 tasks. Average proportional errors were, for most tasks, between -50% (i.e. underestimations) and +100%, with a dominance of overestimations; 22% of all results considered overestimations of 100% or more. For 15% of the 182 reported tasks, the mean difference between the self-reported and the reference duration value was <5%, and 20% of the 182 mean differences were between 5 and 20%. In general, respondents were able to correctly distinguish tasks of a longer duration from shorter tasks, even though the actual durations were not correct. A number of factors associated with the task per se appeared to influence agreement between self-reports and reference data, including type of task, true task duration, task pattern across time (continuous versus discontinuous), and whether the addressed task is composed of subtasks. The musculoskeletal health status of the respondent did not have a clear effect on the ability to correctly report task durations. Studies differed in key design characteristics and detail of information reported, which hampers a formal aggregation of results.

Conclusions

The correctness of self-reported task durations is, at the best, moderate at the individual level, and this may present a significant problem when using self-reports in task-based assessment of individual job exposures. However, average self-reports at the group level appear reasonably correct and may thus be a viable method in studies addressing, for instance, the relative occurrence of tasks in a production system. Due to the disparity of studies, definite conclusions on the quantitative effect on agreement of different modifiers are not justified, and we encourage future studies specifically devoted to understanding and controlling sources of bias in self-reported task durations. We also encourage studies developing decision support for when to apply or avoid self-reports to measure task durations, depending on study purpose and occupational setting.

Predicting Forearm Physical Exposures During Computer Work Using Self-Reports, Software-Recorded Computer Usage Patterns, and Anthropometric and Workstation Measurements

Objectives

Alternative techniques to assess physical exposures, such as prediction models, could facilitate more efficient epidemiological assessments in future large cohort studies examining physical exposures in relation to work-related musculoskeletal symptoms. The aim of this study was to evaluate two types of models that predict arm-wrist-hand physical exposures (i.e. muscle activity, wrist postures and kinematics, and keyboard and mouse forces) during computer use, which only differed with respect to the candidate predicting variables; (i) a full set of predicting variables, including self-reported factors, software-recorded computer usage patterns, and worksite measurements of anthropometrics and workstation set-up (full models); and (ii) a practical set of predicting variables, only including the self-reported factors and software-recorded computer usage patterns, that are relatively easy to assess (practical models).

Methods

Prediction models were build using data from a field study among 117 office workers who were symptom-free at the time of measurement. Arm-wrist-hand physical exposures were measured for approximately two hours while workers performed their own computer work. Each worker's anthropometry and workstation set-up were measured by an experimenter, computer usage patterns were recorded using software and self-reported factors (including individual factors, job characteristics, computer work behaviours, psychosocial factors, workstation set-up characteristics, and leisure-time activities) were collected by an online questionnaire. We determined the predictive quality of the models in terms of R2 and root mean squared (RMS) values and exposure classification agreement to low-, medium-, and high-exposure categories (in the practical model only).

Results

The full models had R2 values that ranged from 0.16 to 0.80, whereas for the practical models values ranged from 0.05 to 0.43. Interquartile ranges were not that different for the two models, indicating that only for some physical exposures the full models performed better. Relative RMS errors ranged between 5% and 19% for the full models, and between 10% and 19% for the practical model. When the predicted physical exposures were classified into low, medium, and high, classification agreement ranged from 26% to 71%.

Conclusion

The full prediction models, based on self-reported factors, software-recorded computer usage patterns, and additional measurements of anthropometrics and workstation set-up, show a better predictive quality as compared to the practical models based on self-reported factors and recorded computer usage patterns only. However, predictive quality varied largely across different arm-wrist-hand exposure parameters. Future exploration of the relation between predicted physical exposure and symptoms is therefore only recommended for physical exposures that can be reasonably well predicted.

Inter- and Intrasubject Similarity of Muscle Synergies During Bench Press With Slow and Fast Velocity

We investigated the effect of low and high bar velocity on inter- and intrasubject similarity of muscle synergies during bench press. A total of 13 trained male subjects underwent two exercise conditions: a slow- and a fast-velocity bench press. Surface electromyography was recorded from 13 muscles, and muscle synergies were extracted using a nonnegative matrix factorization algorithm. The intrasubject similarity across conditions and intersubject similarity within conditions were computed for muscle synergy vectors and activation coefficients. Two muscle synergies were sufficient to describe the dataset variability. For the second synergy activation coefficient, the intersubject similarity within the fast-velocity condition was greater than the intrasubject similarity of the activation coefficient across the conditions. An opposite pattern was observed for the first muscle synergy vector. We concluded that the activation coefficients are robust within conditions, indicating a robust temporal pattern of muscular activity across individuals, but the muscle synergy vector seemed to be individually assigned.

Predicting Directly Measured Trunk and Upper Arm Postures in Paper Mill Work From Administrative Data, Workers' Ratings and Posture Observations

Objectives

A cost-efficient approach for assessing working postures could be to build statistical models for predicting results of direct measurements from cheaper data, and apply these models to samples in which only the latter data are available. The present study aimed to build and assess the performance of statistical models predicting inclinometer-assessed trunk and arm posture among paper mill workers. Separate models were built using administrative data, workers' ratings of their exposure, and observations of the work from video recordings as predictors.

Methods

Trunk and upper arm postures were measured using inclinometry on 28 paper mill workers during three work shifts each. Simultaneously, the workers were video filmed, and their postures were assessed by observation of the videos afterwards. Workers' ratings of exposure, and administrative data on staff and production during the shifts were also collected. Linear mixed models were fitted for predicting inclinometer-assessed exposure variables (median trunk and upper arm angle, proportion of time with neutral trunk and upper arm posture, and frequency of periods in neutral trunk and upper arm inclination) from administrative data, workers' ratings, and observations, respectively. Performance was evaluated in terms of Akaike information criterion, proportion of variance explained (R2), and standard error (SE) of the model estimate. For models performing well, validity was assessed by bootstrap resampling.

Results

Models based on administrative data performed poorly (R2 ≤ 15%) and would not be useful for assessing posture in this population. Models using workers' ratings of exposure performed slightly better (8% ≤ R2 ≤ 27% for trunk posture; 14% ≤ R2 ≤ 36% for arm posture). The best model was obtained when using observational data for predicting frequency of periods with neutral arm inclination. It explained 56% of the variance in the postural exposure, and its SE was 5.6. Bootstrap validation of this model showed similar expected performance in other samples (5th-95th percentile: R2 = 45-63%; SE = 5.1-6.2).

Conclusions

Observational data had a better ability to predict inclinometer-assessed upper arm exposures than workers' ratings or administrative data. However, observational measurements are typically more expensive to obtain. The results encourage analyses of the cost-efficiency of modeling based on administrative data, workers' ratings, and observation, compared to the performance and cost of measuring exposure directly.

Gender differences in fatigability and muscle activity responses to a short-cycle repetitive task

PURPOSE

Epidemiological research has identified women to be more susceptible to developing neck-shoulder musculoskeletal disorders when performing low-force, repetitive work tasks. Whether this is attributable to gender differences in fatigability and motor control is currently unclear. This study investigated the extent to which women differ from men in fatigability and motor control while performing a short-cycle repetitive task.

METHODS

113 healthy young adults (58 women, 55 men) performed a standardized repetitive pointing task. The task was terminated when the subject's perceived exertion reached 8 on the Borg scale. The time to task termination, and changes in means and cycle-to-cycle variabilities of surface electromyography signals from start to end of the task, were compared between women and men, for the upper trapezius, anterior deltoid, biceps and triceps muscles.

RESULTS

Women and men terminated the task after 6.5 (SD 3.75) and 7 (SD 4) min on average (p > 0.05). All four muscles showed an increase of 25-35 % in average muscle activity with fatigue (no significant sex differences). However, men exhibited a higher increase than women in trapezius muscle variability with fatigue (31 vs. 7 %; p < 0.05), and a decrease in biceps muscle variability where women had an increase (-23 vs. 12 %; p < 0.05).

CONCLUSIONS

Our results suggest that women and men may not differ in the ability to perform repetitive tasks at low-to-moderate force levels. However, differences in motor control strategies employed in task performance may explain gender differences in susceptibility to developing musculoskeletal disorders when performing repetitive work for prolonged periods in occupational life.

Accuracy and repeatability of an inertial measurement unit system for field-based occupational studies

The accuracy and repeatability of an inertial measurement unit (IMU) system for directly measuring trunk angular displacement and upper arm elevation were evaluated over eight hours (i) in comparison to a gold standard, optical motion capture (OMC) system in a laboratory setting, and (ii) during a field-based assessment of dairy parlour work. Sample-to-sample root mean square differences between the IMU and OMC system ranged from 4.1° to 6.6° for the trunk and 7.2°-12.1° for the upper arm depending on the processing method. Estimates of mean angular displacement and angular displacement variation (difference between the 90th and 10th percentiles of angular displacement) were observed to change <4.5° on average in the laboratory and <1.5° on average in the field per eight hours of data collection. Results suggest the IMU system may serve as an acceptable instrument for directly measuring trunk and upper arm postures in field-based occupational exposure assessment studies with long sampling durations. Practitioner Summary: Few studies have evaluated inertial measurement unit (IMU) systems in the field or over long sampling durations. Results of this study indicate that the IMU system evaluated has reasonably good accuracy and repeatability for use in a field setting over a long sampling duration.

Detailed assessment of low-back loads may not be worth the effort: A comparison of two methods for exposure-outcome assessment of low-back pain

The trade-off between feasibility and accuracy of measurements of physical exposure at the workplace has often been discussed, but is unsufficiently understood. We therefore explored the effect of two low-back loading measurement tools with different accuracies on exposure estimates and their associations with low-back pain (LBP). Low-back moments of 93 workers were obtained using two methods: a moderately accurate observation-based method and a relatively more accurate video-analysis method. Group-based exposure metrics were assigned to a total of 1131 workers who reported on their LBP status during three follow-up years. The two methods were compared regarding individual and group-based moments and their predictive value for LBP. Differences between the two methods for peak moments were high at the individual level and remained substantial at group level. For cumulative moments, differences between the two methods were attenuated as random inaccuracies cancelled out. Peak moments were not predictive for LBP in any method while cumulative moments were, suggesting comparable predictive values of the two methods. While assessment of low-back load improves from investing in collecting relatively more accurate individual-based data, this does not necessarily lead to better predictive values on a group level, especially not for cumulative loads.

A Comparison of Two Strategies for Building an Exposure Prediction Model

Cost-efficient assessments of job exposures in large populations may be obtained from models in which 'true' exposures assessed by expensive measurement methods are estimated from easily accessible and cheap predictors. Typically, the models are built on the basis of a validation study comprising 'true' exposure data as well as an extensive collection of candidate predictors from questionnaires or company data, which cannot all be included in the models due to restrictions in the degrees of freedom available for modeling. In these situations, predictors need to be selected using procedures that can identify the best possible subset of predictors among the candidates. The present study compares two strategies for selecting a set of predictor variables. One strategy relies on stepwise hypothesis testing of associations between predictors and exposure, while the other uses cluster analysis to reduce the number of predictors without relying on empirical information about the measured exposure. Both strategies were applied to the same dataset on biomechanical exposure and candidate predictors among computer users, and they were compared in terms of identified predictors of exposure as well as the resulting model fit using bootstrapped resamples of the original data. The identified predictors were, to a large part, different between the two strategies, and the initial model fit was better for the stepwise testing strategy than for the clustering approach. Internal validation of the models using bootstrap resampling with fixed predictors revealed an equally reduced model fit in resampled datasets for both strategies. However, when predictor selection was incorporated in the validation procedure for the stepwise testing strategy, the model fit was reduced to the extent that both strategies showed similar model fit. Thus, the two strategies would both be expected to perform poorly with respect to predicting biomechanical exposure in other samples of computer users.

Shoulder kinematics and spatial pattern of trapezius electromyographic activity in real and virtual environments

The design of an industrial workstation tends to include ergonomic assessment steps based on a digital mock-up and a virtual reality setup. Lack of interaction and system fidelity is often reported as a main issue in such virtual reality applications. This limitation is a crucial issue as thorough ergonomic analysis is required for an investigation of the biomechanics. In the current study, we investigated the biomechanical responses of the shoulder joint in a simulated assembly task for comparison with the biomechanical responses in virtual environments. Sixteen male healthy novice subjects performed the task on three different platforms: real (RE), virtual (VE), and virtual environment with force feedback (VEF) with low and high precision demands. The subjects repeated the task 12 times (i.e., 12 cycles). High density electromyography from the upper trapezius and rotation angles of the shoulder joint were recorded and split into the cycles. The angular trajectories and velocity profiles of the shoulder joint angles over a cycle were computed in 3D. The inter-subject similarity in terms of normalized mutual information on kinematics and electromyography was investigated. Compared with RE the task in VE and VEF was characterized by lower kinematic maxima. The inter-subject similarity in RE compared with intra-subject similarity across the platforms was lower in terms of movement trajectories and greater in terms of trapezius muscle activation. The precision demand resulted in lower inter- and intra-subject similarity across platforms. The proposed approach identifies biomechanical differences in the shoulder joint in both VE and VEF compared with the RE platform, but these differences are less marked in VE mostly due to technical limitations of co-localizing the force feedback system in the VEF platform.

Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome--effects of study size and exposure measurement efforts

OBJECTIVES

Exposure-outcome studies, for instance on work-related low-back pain (LBP), often classify workers into groups for which exposures are estimated from measurements on a sample of workers within or outside the specific study. The present study investigated the influence on bias and power in exposure-outcome associations of the sizes of the total study population and the sample used to estimate exposures.

METHODS

At baseline, lifting, trunk flexion, and trunk rotation were observed for 371 of 1131 workers allocated to 19 a-priori defined occupational groups. LBP (dichotomous) was reported by all workers during 3 years of follow-up. All three exposures were associated with LBP in this parent study (P < 0.01). All 21 combinations of n = 10, 20, 30 workers per group with an outcome, and k = 1, 2, 3, 5, 10, 15, 20 workers actually being observed were investigated using bootstrapping, repeating each combination 10000 times. Odds ratios (OR) with P values were determined for each of these virtual studies. Average OR and statistical power (P < 0.05 and P < 0.01) was determined from the bootstrap distributions at each (n, k) combination.

RESULTS

For lifting and flexed trunk, studies including n ≥ 20 workers, with k ≥ 5 observed, led to an almost unbiased OR and a power >0.80 (P level = 0.05). A similar performance required n ≥ 30 workers for rotated trunk. Small numbers of observed workers (k) resulted in biased OR, while power was, in general, more sensitive to the total number of workers (n).

CONCLUSIONS

In epidemiologic studies using a group-based exposure assessment strategy, statistical performance may be sufficient if outcome is obtained from a reasonably large number of workers, even if exposure is estimated from only few workers per group.

The ability of non-computer tasks to increase biomechanical exposure variability in computer-intensive office work

Postures and muscle activity in the upper body were recorded from 50 academics office workers during 2 hours of normal work, categorised by observation into computer work (CW) and three non-computer (NC) tasks (NC seated work, NC standing/walking work and breaks). NC tasks differed significantly in exposures from CW, with standing/walking NC tasks representing the largest contrasts for most of the exposure variables. For the majority of workers, exposure variability was larger in their present job than in CW alone, as measured by the job variance ratio (JVR), i.e. the ratio between min-min variabilities in the job and in CW. Calculations of JVRs for simulated jobs containing different proportions of CW showed that variability could, indeed, be increased by redistributing available tasks, but that substantial increases could only be achieved by introducing more vigorous tasks in the job, in casu illustrated by cleaning.

Prediction of trapezius muscle activity and shoulder, head, neck, and torso postures during computer use: results of a field study

BACKGROUND

Due to difficulties in performing direct measurements as an exposure assessment technique, evidence supporting an association between physical exposures such as neck and shoulder muscle activities and postures and musculoskeletal disorders during computer use is limited. Alternative exposure assessment techniques are needed.

METHODS

We predicted the median and range of amplitude (90th-10th percentiles) of trapezius muscle activity and the median and range of motion (90th-10th percentiles) of shoulder, head, neck, and torso postures based on two sets of parameters: the distribution of keyboard/mouse/idle activities only ("task-based" predictions), and a comprehensive set of task, questionnaire, workstation, and anthropometric parameters ("expanded model" predictions). We compared the task-based and expanded model predictions based on R2 values, root mean squared (RMS) errors, and relative RMS errors calculated compared to direct measurements.

RESULTS

The expanded model predictions of the median and range of amplitude of trapezius muscle activity had consistently better R2 values (range 0.40-0.55 compared to 0.00-0.06), RMS errors (range 2-3%MVC compared to 3-4%MVC), and relative RMS errors (range 10-14%MVC compared to 16-19%MVC) than the task-based predictions. The expanded model predictions of the median and range of amplitude of postures also had consistently better R2 values (range 0.22-0.58 compared to 0.00-0.35), RMS errors (range 2-14 degrees compared to 3-22 degrees), and relative RMS errors (range 9-21 degrees compared to 13-42 degrees) than the task-based predictions.

CONCLUSIONS

The variation in physical exposures across users performing the same task is large, especially in comparison to the variation across tasks. Thus, expanded model predictions of physical exposures during computer use should be used rather than task-based predictions to improve exposure assessment for future epidemiological studies. Clinically, this finding also indicates that computer users will have differences in their physical exposures even when performing the same tasks.

Occupational kneeling and squatting: development and validation of an assessment method combining measurements and diaries

Objectives

As knee-straining postures such as kneeling and squatting are known to be risk factors for knee disorders, there is a need for effective exposure assessment at the workplace. Therefore, the aim of this study was to develop a method to capture knee-straining postures for entire work shifts by combining measurement techniques with the information obtained from diaries, and thus avoiding measuring entire work shifts. This approach was applied to various occupational tasks to obtain an overview of typical exposure values in current specific occupations.

Methods

The analyses were carried out in the field using an ambulatory measuring system (CUELA) to assess posture combined with one-day self-reported occupational diaries describing the durations of various work tasks. In total, 242 work shifts were measured, representing 81 typical tasks from 16 professions. Knee-straining postures were analysed as daily time intervals for five different postures. The accuracy of the method was examined by comparing the results to measurements of entire work shifts.

Results

Unsupported kneeling was the most widely used knee posture in our sample (median 11.4 % per work shift), followed by supported kneeling (3.0 %), sitting on heels (1.1 %), squatting (0.7 %), and crawling (0.0 %). The daily time spent in knee-straining postures varied considerably, both between the individual occupations, within an occupation (e.g. parquet layers: 0.0–88.9 %), and to some extent even within a single task (e.g. preparation work of floor layers (22.0 ± 23.0 %). The applied measuring method for obtaining daily exposure to the knee has been proven valid and efficient randomly compared with whole-shift measurements (p = 0.27).

Conclusions

The daily degree of postural exposure to the knee showed a huge variation within the analysed job categories and seemed to be dependent on the particular tasks performed. The results of this study may help to develop an exposure matrix with respect to occupational knee-straining postures. The tested combination of task-based measurement and diary information may be a promising option for providing a cost-effective assessment tool.

Statistical performance of observational work sampling for assessment of categorical exposure variables: a simulation approach illustrated using PATH data

Objectives:

Observational work sampling is often used in occupational studies to assess categorical biomechanical exposures and occurrence of specific work tasks. The statistical performance of data obtained by work sampling is, however, not well understood, impeding informed measurement strategy design. The purpose of this study was to develop a procedure for assessing the statistical properties of work sampling strategies evaluating categorical exposure variables and to illustrate the usefulness of this procedure to examine bias and precision of exposure estimates from samples of different sizes.

Methods:

From a parent data set of observations on 10 construction workers performing a single operation, the probabilities were determined for each worker of performing four component tasks and working in four mutually exclusive trunk posture categories (neutral, mild flexion, severe flexion, twisted). Using these probabilities, 5000 simulated data sets were created via probability-based resampling for each of six sampling strategies, ranging from 300 to 4500 observations. For each strategy, mean exposure and exposure variability metrics were calculated at both the operation level and task level and for each metric, bias and precision were assessed across the 5000 simulations.

Results:

Estimates of exposure variability were substantially more uncertain at all sample sizes than estimates of mean exposures and task proportions. Estimates at small sample sizes were also biased. With only 600 samples, proportions of the different tasks and of working with a neutral trunk posture (the most common) were within 10% of the true target value in at least 80% of all the simulated data sets; rarer exposures required at least 1500 samples. For most task-level mean exposure variables and for all operation-level and task-level estimates of exposure variability, performance was low, even with 4500 samples. In general, the precision of mean exposure estimates did not depend on the exposure variability between workers.

Conclusions:

The suggested probability-based simulation approach proved to be versatile and generally suitable for assessing bias and precision of data collection strategies using work sampling to estimate categorical data. The approach can be used in both real and hypothetical scenarios, in ergonomics, as well as in other areas of occupational epidemiology and intervention research. The reported statistical properties associated with sample size are likely widely relevant to studies using work sampling to assess categorical variables.

Variance in direct exposure measures of typing force and wrist kinematics across hours and days among office computer workers

To determine the number of direct measurements needed to obtain a representative estimate of typing force and wrist kinematics, continuous measures of keyboard reaction force and wrist joint angle were collected at the workstation of 22 office workers while they completed their own work over three days, six hours per day. Typing force and wrist kinematics during keyboard, mouse and idle activities were calculated for each hour of measurement along with variance in measurements between subjects and between day and hour within subjects. Variance in measurements between subjects was significantly greater than variance in measurements between days and hours within subjects. Therefore, we concluded a single, one-hour period of continuous measures is sufficient to identify differences in typing force and wrist kinematics between subjects. Within subjects, day and hour of measurement had a significant effect on some measures and thus should be accounted for when comparing measures within a subject.

PRACTITIONER SUMMARY

The dose response relationship between exposure to computer related biomechanical risk factors and musculoskeletal disorders is poorly understood due to the difficulty and cost of direct measures. This study demonstrates a single hour of direct continuous measures is sufficient to identify differences in wrist kinematics and typing force between individuals.

Variability in muscle activity and wrist motion measurements among workers performing non-cyclic work

Appropriate sampling strategies for estimation of exposure to physical risk factors require knowledge of exposure variability over time. Limited information is available about the variability of exposure to physical risk factors for upper extremity musculoskeletal disorders, especially during non-cyclic work activities. We investigated the magnitude and relative contributions of several sources of variance to the total exposure variance among office, custodial, or maintenance workers (N = 5 per group). In addition, we examined the homogeneity of exposure within each group of workers and exposure contrast between groups of workers. Activation of the flexor carpi radialis and upper trapezius muscle groups was assessed with surface electromyography (EMG) and wrist motion was assessed with electrogoniometry. Exposure information was collected continuously over a complete work shift on two occasions. We observed a substantial contribution of the within-day-within-subject variance component to the total exposure variance for all EMG and electrogoniometer summary measures. We also observed limited exposure contrast between the occupational groups in summary measures of upper trapezius EMG and most electrogoniometry summary measures. The large within-day-within-subject variance suggests the need for prolonged measurement durations (e.g., more than 1 hr) in future epidemiologic investigations of associations between exposure to physical risk factors and upper extremity musculoskeletal disorders.

Developing a framework for predicting upper extremity muscle activities, postures, velocities, and accelerations during computer use: the effect of keyboard use, mouse use, and individual factors on physical exposures

Prediction models were developed based on keyboard and mouse use in combination with individual factors that could be used to predict median upper extremity muscle activities, postures, velocities, and accelerations experienced during computer use. In the laboratory, 25 participants performed five simulated computer trials with different amounts of keyboard and mouse use ranging from a highly keyboard-intensive trial to a highly mouse-intensive trial. During each trial, muscle activity and postures of the shoulder and wrist and velocities and accelerations of the wrists, along with percentage keyboard and mouse use, were measured. Four individual factors (hand length, shoulder width, age, and gender) were also measured on the day of data collection. Percentage keyboard and mouse use explained a large amount of the variability in wrist velocities and accelerations. Although hand length, shoulder width, and age were each significant predictors of at least one median muscle activity, posture, velocity, or acceleration exposure, these individual factors explained very little variability in addition to percentage keyboard and mouse use in any of the physical exposures investigated. The amounts of variability explained for models predicting median wrist velocities and accelerations ranged from 75 to 84% but were much lower for median muscle activities and postures (0-50%). RMS errors ranged between 8 to 13% of the range observed. While the predictions for wrist velocities and accelerations may be able to be used to improve exposure assessment for future epidemiologic studies, more research is needed to identify other factors that may improve the predictions for muscle activities and postures.

Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered

Background

Reliable exposure data is a vital concern in medical epidemiology and intervention studies. The present study addresses the needs of the medical researcher to spend monetary resources devoted to exposure assessment with an optimal cost-efficiency, i.e. obtain the best possible statistical performance at a specified budget. A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios.

Methods

Statistical performance, i.e. efficiency, was assessed in terms of the precision of an exposure mean value, as determined in a hierarchical, nested measurement model with three stages. Total costs were assessed using a corresponding three-stage cost model, allowing costs at each stage to vary non-linearly with the number of measurements according to a power function. Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components.

Results

Explicit mathematical rules for identifying optimal allocation could be developed when cost functions were linear, while non-linear cost functions implied that parts of or the entire optimization procedure had to be carried out using numerical methods.

For many of the 225 scenarios, the optimal strategy consisted in measuring on only one occasion from each of as many subjects as allowed by the budget. Significant deviations from this principle occurred if costs for recruiting subjects were large compared to costs for setting up measurement occasions, and, at the same time, the between-subjects to within-subject variance ratio was small. In these cases, non-linearities had a profound influence on the optimal allocation and on the eventual size of the exposure data set.

Conclusions

The analysis procedures developed in the present study can be used for informed design of exposure assessment strategies, provided that data are available on exposure variability and the costs of collecting and processing data. The present shortage of empirical evidence on costs and appropriate cost functions however impedes general conclusions on optimal exposure measurement strategies in different epidemiologic scenarios.

Evaluation and comparison of three exposure assessment techniques

This study was conducted to verify the performance of a recently developed subjective rating (SR) exposure assessment technique and to compare estimates made using this and two other techniques (trade mean, or TM, and task-based, or TB, approaches) to measured exposures. Subjects (n = 68) each completed three full-shift noise measurements over 4 months. Individual measured mean exposures were created by averaging each subject's repeated measurements, and TM, TB, and SR estimates were created using noise levels from worksites external to the current study. The bias, precision, accuracy, and absolute agreement of estimates created using the three techniques were evaluated by comparing estimated exposures with measured exposures. Trade mean estimates showed little bias, while neither the TM nor the SR techniques produced unbiased estimates, and the SR estimates showed the greatest bias of the three techniques. Accuracy was essentially equivalent among the three techniques. All three techniques showed poor agreement with measured exposures and were not highly correlated with each other. Estimates from the SR technique generally performed similarly to the TM and TB techniques. Methods to incorporate information from each technique into exposure estimates should be explored.

Cost-efficient design of occupational exposure assessment strategies--a review

When designing a strategy for collecting occupational exposure data, both economic and statistical performance criteria should be considered. However, very few studies have addressed the trade-off between the cost of obtaining data and the precision/accuracy of the exposure estimate as a research issue. To highlight the need of providing cost-efficient designs for assessing exposure variables in occupational research, the present review explains and critically evaluates the concepts and analytical tools used in available cost efficiency studies. Nine studies were identified through a systematic search using two algorithms in the databases PubMed and ScienceDirect. Two main approaches could be identified in these studies: 'comparisons' of the cost efficiency associated with different measurement designs and 'optimizations' of resource allocation on the basis of functions describing cost and statistical efficiency. In either case, the reviewed studies use simplified analytical tools and insufficient economic analyses. More research is needed to understand whether these drawbacks jeopardize the guidance on cost-efficient exposure assessment provided by the studies, as well as to support theoretical results by empirical data from occupational life.

Using observation and self-report to predict mean, 90th percentile, and cumulative low back muscle activity in heavy industry workers

Occupational injury research depends on the ability to accurately assess workplace exposures for large numbers of workers. This study used mixed modeling to identify observed and self-reported predictors of mean, 90th percentile, and cumulative low back muscle activity to help researchers efficiently assess physical exposures in epidemiological studies. Full-shift low back electromyography (EMG) was measured for 133 worker-days in heavy industry. Additionally, full-shift, 1-min interval work-sampling observations and post-shift interviews assessed exposure to work tasks, trunk postures, and manual materials handling. Data were also collected on demographic and job variables. Regression models using observed variables predicted 31-47% of the variability in the EMG activity measures, while self-reported variables predicted 21-36%. Observation-based models performed better than self-report-based models and may provide an alternative to direct measurement of back injury risk factors.

The ability of limited exposure sampling to detect effects of interventions that reduce the occurrence of pronounced trunk inclination

Ergonomics interventions often focus on reducing exposure in those parts of the job having the highest exposure levels, while leaving other parts unattended. A successful intervention will thus change the form of the job exposure distribution. This disqualifies standard methods for assessing the ability of various exposure measurement strategies to correctly detect an intervention's effect on the overall job exposure of an individual worker, in particular for the safety or ergonomics practitioner who with limited resources can only collect a few measurements. This study used a non-parametric simulation procedure to evaluate the relationship between the number of measurements collected during a self-paced manufacturing job undergoing ergonomics interventions of varying effectiveness, and the probability of correctly determining whether and to which extent the interventions reduced the overall occurrence of pronounced trunk inclination, defined as an inclination of at least 20 degrees . Sixteen video-recordings taken at random times on multiple days for each of three workers were used to estimate the time distribution of each worker's exposure to pronounced trunk inclination. Nine hypothetical ergonomics intervention scenarios were simulated, in which the occurrence of pronounced trunk inclination in the upper 1/8, 1/4, and 1/2 of the job exposure distribution was reduced by 10%, 30% and 50%. Ten exposure measurement strategies were explored, collecting from one to ten pre- and post-intervention exposure samples from an individual worker. For each worker, intervention scenario and sampling strategy, data were bootstrapped from the measured (pre-intervention) and simulated (post-intervention) exposure distributions to generate empirical distributions of the estimated intervention effect. Results showed that for the one to three intervention scenarios that had the greatest effect on the overall occurrence of trunk inclination in the job, one to four pre- and post-intervention measurements, depending on worker, were sufficient to reach an 80% probability of detecting that the intervention did, indeed, have an effect. However, even for the intervention scenario that had the greatest effect on job exposure, seven or more samples were needed for two of the three workers to obtain a probability larger than 50% of estimating the magnitude of the intervention effect to within +/-50% of its true size. For almost all interventions affecting 1/8 or 1/4 of the job, limited exposure sampling led to low probabilities of detecting any intervention effect, let alone its correct size.

Differences in muscle load between computer and non-computer work among office workers

Introduction of more non-computer tasks has been suggested to increase exposure variation and thus reduce musculoskeletal complaints (MSC) in computer-intensive office work. This study investigated whether muscle activity did, indeed, differ between computer and non-computer activities. Whole-day logs of input device use in 30 office workers were used to identify computer and non-computer work, using a range of classification thresholds (non-computer thresholds (NCTs)). Exposure during these activities was assessed by bilateral electromyography recordings from the upper trapezius and lower arm. Contrasts in muscle activity between computer and non-computer work were distinct but small, even at the individualised, optimal NCT. Using an average group-based NCT resulted in less contrast, even in smaller subgroups defined by job function or MSC. Thus, computer activity logs should be used cautiously as proxies of biomechanical exposure. Conventional non-computer tasks may have a limited potential to increase variation in muscle activity during computer-intensive office work.

Task exposures in an office environment: a comparison of methods

Task-related factors such as frequency and duration are associated with musculoskeletal disorders in office settings. The primary objective was to compare various task recording methods as measures of exposure in an office workplace. A total of 41 workers from different jobs were recruited from a large urban newspaper (71% female, mean age 41 years SD 9.6). Questionnaire, task diaries, direct observation and video methods were used to record tasks. A common set of task codes was used across methods. Different estimates of task duration, number of tasks and task transitions arose from the different methods. Self-report methods did not consistently result in longer task duration estimates. Methodological issues could explain some of the differences in estimates seen between methods observed. It was concluded that different task recording methods result in different estimates of exposure likely due to different exposure constructs. This work addresses issues of exposure measurement in office environments. It is of relevance to ergonomists/researchers interested in how to best assess the risk of injury among office workers. The paper discusses the trade-offs between precision, accuracy and burden in the collection of computer task-based exposure measures and different underlying constructs captures in each method.

Work pattern causes bias in self-reported activity duration: a randomised study of mechanisms and implications for exposure assessment and epidemiology

BACKGROUND

Self-reported activity duration is used to estimate cumulative exposures in epidemiological research.

OBJECTIVE

The effects of work pattern, self-reported task dullness (a measure of cognitive task demand), and heart rate ratio and perceived physical exertion (measures of physical task demands) on error in task duration estimation were investigated.

METHODS

24 participants (23-54 years old, 12 males) were randomly assigned to execute three tasks in either a continuous (three periods of 40 continuous minutes, one for each task) or a discontinuous work pattern (40 min tasks each divided into four periods of 4, 8, 12 and 16 min). Heart rate was measured during tasks. After completing the 2 h work session, subjects reported the perceived duration, dullness and physical exertion for each of the three tasks. Multivariate models were fitted to analyse errors and their absolute value to assess the accuracy in task duration estimation and the mediating role of task demands on the observed results.

RESULTS

Participants overestimated the time spent shelving boxes (up to 38%) and filing journals (up to 9%), and underestimated the time typing articles (up to -22%). Over- and underestimates and absolute errors were greater in the discontinuous work pattern group. Only the self-reported task dullness mediated the differences in task duration estimation accuracy between work patterns.

CONCLUSIONS

Task-related factors can affect self-reported activity duration. Exposure assessment strategies requiring workers to allocate work time to different tasks could result in biased measures of association depending on the demands of the tasks during which the exposure of interest occurs.

Electromyographic assessment of apple bucket intervention designed to reduce back strain

The authors previously developed an apple bucket that was modified by use of a hip belt to reduce muscle fatigue. The intervention of belt use was accepted by workers and shown not to interfere with productivity. However, use of this intervention did not appear to reduce muscle fatigue when measured by tests of voluntary muscle strength. The purpose of the present study was to evaluate the intervention's effect on muscle fatigue employing surface electromyographic (EMG) amplitude. Amplitude measurements on 15 muscles were taken from 10 laboratory volunteers who were carrying a full bucket of apples, once while wearing the intervention belt and once without the intervention. These measurements were taken for seven different postures (four angles of trunk flexion (0 degrees , 20 degrees , 45 degrees , 90 degrees ) and three raised-arm positions (both up, dominant up, non-dominant up)) common to apple harvest work. Participants were measured in these conditions both with the bucket carried in front and with the bucket carried to the side. Significant reductions in amplitude favouring the intervention were seen for 11 of the 15 muscles in models considering the four body flexion angles. Ten of these were of the middle and lower back. These control/intervention differences were seen with both bucket-carrying positions (front vs. side) and tended to increase with increasing flexion angle. In contrast, no significant intervention effects were observed in models considering treatment by arm-raised position. One significant main effect (upper trapezius, side bucket) showed an amplitude reduction in the treatment condition. Another main effect showing increased amplitude in the intervention condition use was observed in the dominant levator scapulae (side bucket). Thus, the use of the intervention belt reduces EMG amplitude among a number of mid- and lower-back muscles. This is suggestive of a protective effect against back strain.

Time--a key issue for musculoskeletal health and manufacturing

Time is a key issue for both ergonomists and engineers when they engage in production system interventions. While not their primary purpose, the actions of engineers have major effects on biomechanical exposure; possibly of much greater magnitude than many ergonomics interventions. This paper summarises the aims, actions and tools of engineers and ergonomists, emphasising time-related outcomes. Activities of the two groups when attempting to manipulate time aspects of work may be contradictory; engineers wishing to improve production and ergonomists aiming at better health as well as contributing to production. Consequently, tools developed by ergonomists for assessing time aspects of work describe rest patterns, movement velocities or daily duration of exposures, while engineering tools emphasise time-efficient production. The paper identifies measures that could be used to communicate time-relevant information between engineers and ergonomists. Further cooperation between these two stakeholders as well as research on the topic are needed to enable ergonomists to have a larger impact on the design of production systems.

Diversity and variation in biomechanical exposure: what is it, and why would we like to know?

Trends in global working life suggest that the occurrence of jobs characterized by long-lasting low-level loads or repetitive operations is increasing. More physical "variation" is commonly believed to be a remedy against musculoskeletal disorders in such jobs. One aim of the present paper was to shortly review the validity of this conviction. An examination of the available epidemiologic literature pointed out that the effectiveness of initiatives like job rotation or more breaks is weakly supported by empirical evidence, and only for short-term psychophysical outcomes. Only a limited number of studies have been devoted to physical variation, and concepts and metrics for variation in biomechanical exposure are not well developed. Thus, as a second objective, the paper proposes a framework for investigating and evaluating aspects of exposure variation, based on explicit definitions of variation as "the change in exposure across time" and diversity as "the extent that exposure entities differ". Operational methods for assessing these concepts are also discussed.

On the evolution of task-based analysis of manual materials handling, and its applicability in contemporary ergonomics

The industrial revolution significantly changed the way work was organized and analyzed by the introduction and widespread implementation of the division of labor philosophy. This philosophy has continued to dominate work design, and has evolved beyond the factory to include many facets of service industries, and even professional occupations. The analysis of manual work, particularly materials handling tasks, remains an active domain of ergonomics research and practice. Many of the task-analytic tools used for workplace analysis are rooted in the philosophy of dividing work into elements, analyzing the individual elements, and synthesizing the results into conclusions about the entire job, including the risk of contracting musculoskeletal disorders (MSDs). The authors discuss the notion that the nature of modern work, which is characterized by multiple tasks in a complex time pattern, and the complex nature of MSDs, which are influenced by biomechanical as well as psychological, political, and economic factors, may limit the effectiveness of classical task analytic techniques in preventing MSDs.