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

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.

Wearable inertial sensors for human movement analysis: a five-year update

INTRODUCTION

The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings.

AREAS COVERED

Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings.

EXPERT OPINION

IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

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.

Trunk and upper arm postures in paper mill work

The aim of this study was to assess postures and movements of the trunk and upper arm during paper mill work, and to determine the extent to which they differ depending on method of assessment. For each of 28 paper mill workers, postures and movements were assessed during three full shifts using inclinometer registration and observation from video. Summary metrics for each shift, e.g., 10^th, 50^th, and 90^th posture percentile, were averaged across shifts and across workers. In addition, the standard deviation between workers, and the standard deviation between shifts within worker were computed. The results showed that trunk and arm postures during paper mill work were similar to other occupations involving manual materials handling, but the velocities of arm movements were lower. While postures determined by inclinometry and observation were similar on a group level, substantial differences were found between results obtained by the two methods for individual workers, particularly for extreme postures. Thus, measurements by either method on individuals or small groups should be interpreted with caution.

Uncertainty in monetary cost estimates for assessing working postures using inclinometry, observation or self-report

OBJECTIVE

To assess uncertainty in cost estimates for collecting posture data by inclinometry, observations and self-report.

METHOD

In a study addressing physical workloads at a paper mill, costs were calculated for measuring postures of twenty-eight workers during three shifts. Uncertainty in costs was assessed for all three methods as the range between an assumed best case (lowest cost) and worst case (highest cost) using scenario analysis.

RESULTS

The cost for observation was larger, but also more uncertain (€16506 and €89552 in the best and worst case, respectively) than that of inclinometry (€7613 - €45896). Self-report costs were both lower and less uncertain (€3743 - €23368).

CONCLUSIONS

The extent of uncertainty in cost estimates implies that observation could be less expensive than inclinometry, e.g., in a scenario where experienced observers could use existing software, while inclinometers would have to be purchased. We propose adding uncertainty assessments to cost estimates when selecting a method for measuring working postures, and offer guidance in how to proceed in a specific setting.

A practical guidance for assessments of sedentary behavior at work: A PEROSH initiative

Sedentary behavior is defined as sitting or lying with low energy expenditure. Humans in industrialized societies spend an increasing amount of time in sedentary behaviors every day. This has been associated with detrimental health outcomes. Despite a growing interest in the health effects of sedentary behavior at work, associations remain unclear, plausibly due to poor and diverse methods for assessing sedentary behavior. Thus, good practice guidance for researchers and practitioners on how to assess occupational sedentary behavior are needed. The aim of this paper is to provide a practical guidance for practitioners and researchers on how to assess occupational sedentary behavior. Ambulatory systems for use in field applications (wearables) are a promising approach for sedentary behavior assessment. Many different small-size consumer wearables, with long battery life and high data storage capacity are commercially available today. However, no stand-alone commercial system is able to assess sedentary behavior in accordance with its definition. The present paper offers decision support for practitioners and researchers in selecting wearables and data collection strategies for their purpose of study on sedentary behavior. Valid and reliable assessment of occupational sedentary behavior is currently not easy. Several aspects need to be considered in the decision process on how to assess sedentary behavior. There is a need for development of a cheap and easily useable wearable for assessment of occupational sedentary behavior by researchers and practitioners.

Predicting Whole-Body Vibration Exposure in Canadian Prairie Farmers

Direct workplace whole-body vibration exposure assessment provides ecological validity for evaluating health risk in epidemiological studies, yet it is complex and expensive in practical applications. Exposure prediction modeling could be a cost-efficient alternative to directly assessing occupational vibration exposures. The objective of this study was to model directly measured whole-body vibration exposures with predictors from machinery, farm, and self-reported characteristics among Canadian prairies farmers. As per ISO 2631-1, whole-body vibration data were measured on the seat surface at three axes (x, y, z), then summarized into vector sums of the root-mean-squared (RMS) acceleration and the vibration dose value (VDV). All candidate predictors were obtained via questionnaires and onsite observations. A total of 87 whole-body vibration measurements were collected from 40 male farm workers located at 21 central Saskatchewan farms. Using log-transformed RMS and time-standardized VDV outcomes, modeling started from the bivariate analysis where predictors with P-values < 0.2 were considered eligible for multivariate analysis. With random effects of 'farm' and 'farmer', a series of mixed-effects models were constructed through the manual backward elimination method. Final models were internally validated by 1000 bootstrapped samples. The RMS model explained 47.7% of the variance in the directly measured RMS vector sum, with 42.7% obtained from five predictors of 'horsepower', 'transmission', 'vehicle year', 'jerk/jolt frequency', and 'seat bottom-out frequency', while the VDV model explained 19.5% of the variance in the directly measured VDV vector sum, with 11.6% described by the same five predictors as the RMS model. Predictive ability of the RMS model among 1000 bootstrapped samples can be anticipated to range from 14.3 to 69.1%, which may be considered adequate as exposure assessment tool for uses of epidemiological studies. The percentage of variance explained ranged from 0 to 40.5% for the VDV model, which is not robust and therefore likely not appropriate for use in survey-based exposure prediction. Whole-body vibration exposure modeling remains valuable, but is challenging in farming; the described model variance may increase with a more comprehensive list of candidate variables collected and quantified at machinery, farm, and farmer level. Predictors identified in the current and future models may provide a better understanding of how whole-body vibration exposure is modified, guide farmer's future decision on updating equipment, and allow for the development and initiation of interventions.