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  • 1.
    Bergsten, Eva L.
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Kwak, Lydia
    Unit of Intervention and Implementation Research for worker health, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Vingård, Eva
    Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Daily shoulder pain among flight baggage handlers and its association with work tasks and upper arm postures on the same day2017In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 61, no 9, p. 1145-1153Article in journal (Refereed)
    Abstract [en]

    Objectives: This study of flight baggage handlers aimed at examining the extent to which shoulder pain developed during single work shifts, and whether a possible development was associated with biomechanical exposures and psychosocial factors during the same shift.

    Methods: Data were collected during, in total, 82 work shifts in 44 workers. Right and left shoulder pain intensity was rated just before and just after the shift (VAS scale 0-100 mm). Objective data on time in extreme and time in neutral upper arm postures were obtained for the full shift using accelerometers, and the baggage handlers registered the number of aircrafts handled in a diary. During half of the shift, workers were recorded on video for subsequent task analysis of baggage handling. Influence at work and support from colleagues were measured by use of Copenhagen Psychosocial Questionnaire (COPSOQ). Associations between exposures and the increase in pain intensity during the shift (daily pain) were analysed for the right and left shoulder separately using Generalized Estimating Equations (GEE).

    Results: Daily pain was observed in approximately one third of all shifts.  It was significantly associated with the number of aircrafts handled for both the right and left shoulder. In multivariate models including both biomechanical exposures and the psychosocial factors influence at work and support from colleagues, aircrafts handled was still significantly associated with daily pain in both shoulders, and so was influence and support, however in opposite directions.

    Conclusions: Daily pain was, in general, associated with biomechanical exposures during the same shift and with general influence and support in the job. In an effort to reduce pain among flight baggage handlers, it may therefore be justified to consider a reduction of biomechanical exposures during handling of aircrafts, combined with due attention to psychosocial factors at work.

  • 2.
    Coenen, Pieter
    et al.
    Curtin University, Perth, Australia; VU University Amsterdam, the Netherlands; Body@Work, Research Center on Physical Activity, Work and Health, the Netherlands.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Kingma, Idsart
    VU University Amsterdam, the Netherlands; Body@Work, Research Center on Physical Activity, Work and Health, the Netherlands.
    Boot, Cécile
    Body@Work, Research Center on Physical Activity, Work and Health, the Netherlands; EMGO Institute, VU University Medical Center, Amsterdam, the Netherlands.
    Bongers, Paulien
    Body@Work, Research Center on Physical Activity, Work and Health, the Netherlands; TNO Healthy Living, Hoofddorp, the Netherlands.
    van Dieën, Jaap
    VU University Amsterdam, the Netherlands; King Abdulaziz University,Jeddah, Saudi Arabia.
    Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: effects of study size and exposure measurement efforts2015In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 59, no 4, p. 439-454Article in journal (Refereed)
    Abstract [en]

    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 three 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 10,000 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.

  • 3.
    Heiden, Marina
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Garza, Jennifer
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Division of Occupational and Environmental Medicine, UConn Health, Farmington, CT, United States .
    Liv, Per
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Centre for Research and Development, Uppsala University/County Council of Gävleborg.
    Wahlström, Jens
    Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine, Umeå University, Umeå, Sweden.
    A comparison of two strategies for building an exposure prediction model2016In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 60, no 1, p. 74-89Article in journal (Refereed)
    Abstract [en]

    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.

  • 4.
    Liv, Per
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Svendsen, Susanne Wulff
    Danish Ramazzini Center, Department of Occupational Medicine, Herning Hospital, Denmark.
    Theoretical and empirical efficiency of sampling strategies for estimating upper arm elevation2011In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 55, p. 436-449Article in journal (Refereed)
    Abstract [en]

    Objectives

    To investigate the statistical efficiency of strategies for sampling upper arm elevation data, which differed with respect to sample sizes and sample allocations within and across measurement days. The study was also designed to compare standard theoretical predictions of sampling efficiency, which rely on several assumptions about the data structure, with “true” efficiency as determined by bootstrap simulations.

    Methods

    Sixty-five sampling strategies were investigated using a data set containing minute-by-minute values of average right upper arm elevation, percentage of time with the arm elevated less than 15°, and percentage of time with an arm elevated more than 90° in a population of 23 house painters, 23 car mechanics and 26 machinists, all followed for four full working days. Total sample times per subject between 30 and 240 minutes were subdivided into continuous time blocks between 1 and 240 minutes long, allocated to one or four days per subject. Within day(s), blocks were distributed using either a random or fixed-interval principle. Sampling efficiency was expressed in terms of the variance of estimated mean exposure values of 20 subjects, and assessed using standard theoretical models assuming independence between variables and homoscedasticity. Theoretical performance was compared to empirical efficiencies obtained by a nonparametric bootstrapping procedure.

    Results

    We found the assumptions of independence and homoscedasticity in the theoretical model to be violated, most notably expressed through an autocorrelation between measurement units within working days. The empirical variance of the mean exposure estimates decreased, i.e. sampling efficiency increased, for sampling strategies where measurements were distributed widely across time. Thus, the most efficient allocation strategy was to organize a sample into one-minute blocks collected at fixed time intervals across four days. Theoretical estimates of efficiency generally agreed with empirical variances if the sample was allocated into small blocks, while for larger block sizes the empirical, “true” variance was considerably larger than predicted by theory. Theory overestimated efficiency in particular for strategies with short total sample times per subject.

    Conclusions This study demonstrates that when exposure data are autocorrelated within days – which we argue is the major reason why theory overestimates sampling performance – sampling efficiency can be improved by distributing the sample widely across the day or across days, preferably using a fixed-interval strategy. While this guidance is particularly valid when small proportions of working days are assessed, we generally recommend collecting more data than suggested by theory if a certain precision of the resulting exposure estimate is needed. More data per se give a better precision, and sampling larger proportion(s) of the working day(s) also alleviate the negative effects of possible autocorrelation in data

  • 5.
    Luger, Tessy
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. TNO Leiden, Leiden, The Netherlands; Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, VU University Amsterdam, MOVE Research Institute Amsterdam, Amsterdam, The Netherlands; Institute of Occupational and Social Medicine and Health Services Research, Faculty of Medicine, University Hospital, Eberhard Karls University Tübingen, Tübingen, Germany.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Srinivasan, Divya
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, USA.
    Bosch, Tim
    TNO Leiden, Leiden, The Netherlands; Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, VU University Amsterdam, MOVE Research Institute Amsterdam, Amsterdam, The Netherlands.
    Influence of work pace on upper extremity kinematics and muscle activity in a short-cycle repetitive pick-and-place task2017In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 61, no 3, p. 356-368Article in journal (Refereed)
    Abstract [en]

    Aim: This study investigated the extent to which controlled changes in work pace in a cyclic pick-and-place task influence upper extremity kinematics and muscle activity, and whether an effect depends on working height. Methods: Thirteen participants performed the task four minutes at each of five work paces ranging from 8 to 12 cycles·min-1 in each of two experimental conditions where the hand was moved horizontally with an average upper arm elevation of 30° and 50°, respectively. For each work cycle, we calculated the average and standard deviation of the upper arm elevation angle and the activity of the trapezius and deltoid muscles, as well as the angular peak velocity. We summarized these seven variables by calculating averages across cycles and cycle-to-cycle variabilities. Results: At 30° arm elevation, pace significantly influenced within-cycle angle variation, cycle-to-cycle variability of the average angle, angular peak velocity, and cycle-to-cycle variability of peak velocity. However, only angular peak velocity increased monotonically across all paces from 8 to 12 cycles·min-1). Average activity in the trapezius and the deltoid were the only muscle activity variables to increase consistently with pace. These effects of work pace did not change with working height. Conclusion: The present study did not find any consistent work pace effect on upper extremity kinematics and muscle activity, in spite of a comprehensive empirical basis compared to previous literature. While our results suggest that work pace may not be of critical concern in an occupational health context, we encourage further studies verifying or disproving this notion.

  • 6.
    Mathiassen, Svend Erik
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Jackson, Jennie
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Punnett, Laura
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Department of Work Environment, University of Massachusetts Lowell, USA.
    Statistical performance of observational work sampling for assessment of categorical exposure variables: A simulation approach illustrated using PATH data2014In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 58, no 3, p. 294-316Article in journal (Refereed)
    Abstract [en]

    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 re-sampling 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- and task-levels and, for each of these, 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- 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.

  • 7.
    Pulido, Jean Alexander
    et al.
    Centro de Estudios de Ergonomía, Department of Industrial Engineering, School of Engineering, Pontificia Universidad Javeriana, Bogotá.
    Barrero, Lope Hugo
    Centro de Estudios de Ergonomía, Department of Industrial Engineering, School of Engineering, Pontificia Universidad Javeriana, Bogotá.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Dennerlein, Jack
    Department of Physical Therapy, Movement, and Rehabilitation Sciences, Bouvé College of Health Sciences, Northeastern University, Boston.
    Correctness of self-reported task durations: a systematic review: a systematic review2018In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 62, no 1, p. 1-16Article in journal (Refereed)
    Abstract [en]

    Background: Durations of tasks in a job is an essential interest in occupational epidemiology. Such durations are 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 error, and factors influencing this correctness, with particular emphasis on assessment of exposures of relevance to musculoskeletal disorders.

    Method: The search for relevant studies included the databases ISI web of Science, Medline, EBSCO HOST, Proquest and Psycnet.

    Results: Thirty-two articles were identified, 23 of which examined occupational tasks and nine 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 less than 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 vs. 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.

    Discussion: 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.

  • 8.
    Rezagholi, Mahmoud
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Cost-Efficient Design of Occupational Exposure Assessment Strategies: A Review2010In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 54, no 8, p. 858-868Article in journal (Refereed)
    Abstract [en]

    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.

  • 9.
    Trask, Catherine
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research. University of British Columbia School of Environmental Health, Vancouver, BC, Canada.
    Teschke, Kay
    University of British Columbia School of Population and Public Health, Vancouver, Canada .
    Morrison, Jim
    Simon Fraser University School of Kinesiology, Burnaby, Canada.
    Village, Judy
    University of British Columbia School of Environmental Health, Vancouver, Canada.
    Johnson, Peter
    Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, USA.
    Koehoorn, Mieke
    University of British Columbia School of Population and Public Health, Canada .
    Using observation and self-report to predict mean, 90th percentile, and cumulative low back muscle activity in heavy industry workers2010In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 54, no 5, p. 595-606Article in journal (Refereed)
    Abstract [en]

    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.

  • 10.
    Wahlström, Jens
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine, Umeå University, Umeå, Sweden.
    Bergsten, Eva
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Trask, Catherine
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Centre for Health and Safety in Agriculture, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Jackson, Jennie
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.
    Forsman, Mikael
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. IMM Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Full-shift trunk and upper arm postures and movements among aircraft baggage handlers2016In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 60, no 8, p. 977-990Article in journal (Refereed)
    Abstract [en]

    Objectives: The present study assessed full shift trunk and upper arm postural exposure amplitudes, frequencies, and durations among Swedish airport baggage handlers, and aimed to determine whether exposures differ between workers at the ramp (loading and unloading aircraft) and baggage sorting areas.

    Methods: Trunk and upper arm postures were measured using inclinometers during three full work shifts on each of 27, male baggage handlers working at a large Swedish airport. Sixteen of the baggage handlers worked on the ramp and 11 in the sorting area. Variables summarizing postures and movements were calculated, and mean values and variance components between subjects and within subject (between days) were estimated using restricted maximum likelihood algorithms in a one-way random effect model.

    Results: In total, data from 79 full shifts (651 hours) were collected with a mean recording time of 495 minutes per shift (range 319-632). On average, baggage handlers worked with the right and left arm elevated >60° for 6.4% and 6.3% of the total workday, respectively. The 90th percentile trunk forward projection (FP) was 34.1° and the 50th percentile trunk movement velocity was 8°s-1. For most trunk (FP) and upper arm exposure variables, between-subject variability was considerable, suggesting that the flight baggage handlers were not a homogeneously exposed group. A notable between-days variability pointed to the contents of the job differing on different days. Peak exposures (>90°) were higher for ramp workers than for sorting area workers (trunk 0.6% ramp vs 0.3% sorting; right arm 1.3% ramp vs 0.7% sorting).

    Conclusions: Trunk and upper arm postures and movements among flight baggage handlers measured by inclinometry were similar to those found in other jobs comprising manual material handling, known to be associated with increased risks for musculoskeletal disorders. The results showed that full-shift trunk (FP), and to some extent peak arm exposures, were higher for ramp workers compared to sorting workers.

  • 11.
    Wahlström, Jens
    et al.
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Mathiassen, Svend Erik
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Liv, Per
    University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, CBF. University of Gävle, Centre for Musculoskeletal Research.
    Hedlund, Pernilla
    Department of Occupational and Environmental Medicine, Umea University Hospital, SE-901 85 Umeå, Sweden.
    Ahlgren, Christina
    Department of Community Medicine and Rehabilitation, Umea University, SE-901 87 Umeå, Sweden.
    Forsman, Mikael
    Department of Public Health Sciences, Karolinska Institutet, SE-171 77 Stockholm, Sweden.
    Upper arm postures and movements in female hairdressers across four full working days2010In: Annals of Occupational Hygiene, ISSN 0003-4878, E-ISSN 1475-3162, Vol. 54, no 5, p. 584-594Article in journal (Refereed)
    Abstract [en]

    OBJECTIVES: To describe upper arm postures and movements among female hairdressers, including the variability between hairdressers, between days within hairdresser, and between tasks, as a basis for understanding the characteristics of exposures in the job, considering possible sources of variation and recovery, and discussing appropriate exposure assessment strategies. METHODS: Data on upper arm postures were collected using inclinometers during four working days the same week from 28 female hairdressers working in 13 salons. Twenty of the hairdressers noted customer on and off times in a diary, to allow separate analyses of customer tasks (CT) and auxiliary non-customer tasks (AT), including breaks. For a number of posture and movement variables, mean values and variance components between subjects (BS) and within subjects between days (BD) were estimated using restricted maximum likelihood algorithms in one-way random effect models. RESULTS: For the 20 hairdressers with diaries, CT accounted for 279 min (58%) (SD(BS) = 39 min and SD(BD) = 85 min) of the working day and AT and breaks for 207 min (42%) (SD(BS) = 46 min and SD(BD) = 88 min). The hairdressers worked with the right arm elevated >60 degrees for 6.8% of the whole job (SD(BS) = 2.8% and SD(BD) = 2.0%). On average, the hairdressers worked with the right arm elevated >60 degrees for 9.0% of the time during CT, compared to 3.7% during AT, resulting in a contrast between tasks of 0.35. CONCLUSIONS: Hairdressers may be at risk for developing musculoskeletal disorders in the neck and shoulders due to a considerable occurrence of highly elevated arms, especially during CT. On the other hand, we do not find reasons to classify hairdressing as a job with too little variation. Posture variability between days within hairdressers was in the same order of magnitude as that between hairdressers, suggesting that 'typical' workdays do not exist. The exposure contrast between CT and AT for variables describing elevated arm postures indicates that for these variables a simple task-based approach for estimating job exposure could be successful.

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