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BackgroundSix research groups independently conducted prospective studies of carpal tunnel syndrome (CTS) incidence in 54 US workplaces in 10 US States. Physical exposure variables were collected by all research groups at the individual worker level. Data from these research groups were pooled to increase the exposure spectrum and statistical power.ObjectiveThis paper provides a detailed description of the characteristics of the pooled physical exposure variables and the source data information from the individual research studies.MethodsPhysical exposure data were inspected and prepared by each of the individual research studies according to detailed instructions provided by an exposure subcommittee of the research consortium. Descriptive analyses were performed on the pooled physical exposure data set. Correlation analyses were performed among exposure variables estimating similar exposure aspects.ResultsAt baseline, there were a total of 3010 participants in the pooled physical exposure data set. Overall, the pooled data meaningfully increased the spectra of most exposure variables. The increased spectra were due to the wider range in exposure data of different jobs provided by the research studies. The correlations between variables estimating similar exposure aspects showed different patterns among data provided by the research studies.ConclusionsThe increased spectra of the physical exposure variables among the data pooled likely improved the possibility of detecting potential associations between these physical exposure variables and CTS incidence. It is also recognised that methods need to be developed for general use by all researchers for standardisation of physical exposure variable definition, data collection, processing and reduction.

ObjectivesThis paper aimed to quantify exposure-response relationships between the American Conference of Governmental Industrial Hygienists' (ACGIH) threshold limit value (TLV) for hand-activity level (HAL) and incidence of carpal tunnel syndrome (CTS).MethodsManufacturing and service workers previously studied by six research institutions had their data combined and re-analyzed. CTS cases were defined by symptoms and abnormal nerve conduction. Hazard ratios (HR) were calculated using proportional hazards regression after adjusting for age, gender, body mass index, and CTS predisposing conditions.ResultsThe longitudinal study comprised 2751 incident-eligible workers, followed prospectively for up to 6.4 years and contributing 6243 person-years of data. Associations were found between CTS and TLV for HAL both as a continuous variable [HR 1.32 per unit, 95% confidence interval (95% CI) 1.11-1.57] and when categorized using the ACGIH action limit (AL) and TLV. Those between the AL and TLV and above the TLV had HR of 1.7 (95% CI 1.2-2.5) and 1.5 (95% CI 1.0-2.1), respectively. As independent variables (in the same adjusted model) the HR for peak force (PF) and HAL were 1.14 per unit (95% CI 1.05-1.25), and 1.04 per unit (95% CI 0.93-1.15), respectively.ConclusionThose with exposures above the AL were at increased risk of CTS, but there was no further increase in risk for workers above the TLV. This suggests that the current AL may not be sufficiently protective of workers. Combinations of PF and HAL are useful for predicting risk of CTS.

Objective: To examine differences in demographic, psychosocial, and job physical exposure risk factors between multiple low back pain (LBP) outcomes in a prospective cohort of industrial workers. Background: LBP remains a leading cause of lost industrial productivity. Different case definitions involving pain (general LBP), medication use (M-LBP), seeking healthcare (H-LBP), and lost time (L-LBP) are often used to study LBP outcomes. However, the relationship between these outcomes remains unclear. Method: Demographic, health status, psychosocial, and job physical exposure risk factors were quantified for 635 incident-eligible industrial workers. Incident cases of LBP outcomes and pain symptoms were quantified and compared across the four outcomes. Results: Differences in age, gender, medical history, and LBP history were found between the four outcomes. Most incident-eligible workers (67%) suffered an LBP outcome during follow-up. Cases decreased from 420 for LBP (25.4 cases/100 person-years) to 303 for M-LBP (22.0 cases/100 person-years), to 151 for H-LBP (15.6 cases/100 person-years), and finally to 56 for L-LBP (8.7 cases/100 person-years). Conversely, pain intensity and duration increased from LBP to H-LBP. However, pain duration was relatively lower for L-LBP than for H-LBP. Conclusion: Patterns of cases, pain intensity, and pain duration suggest the influence of the four outcomes. However, few differences in apparent risk factors were observed between the outcomes. Further research is needed to establish consistent case definitions. Application: Knowledge of patterns between different LBP outcomes can improve interpretation of research and guide future research and intervention studies in industry. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to investigate the prevalence of carpal tunnel syndrome (CTS) in workers with trigger digit. There are few cross-sectional studies that assess this relationship. Methods: A baseline examination of 1216 workers from 17 diverse manufacturing facilities was conducted. Worker demographics, medical history, and symptoms of trigger digit were assessed. Age, sex, and body mass index were obtained. Biomechanical factors were individually measured using the Strain Index (SI). Prevalence was assessed with univariate and multivariate logistic regression. Results: Unadjusted prevalence of trigger digit was 12.0%, and among those workers, there was an unadjusted CTS prevalence of 26.7%. The adjusted multivariate model found an odds ratio (OR) of CTS of 1.56 (95% confidence interval [CI], 1.03-2.36) among the workers with trigger digit. The ORs of CTS for SI (OR = 1.53 [95% CI, 1.04-2.23]), age (OR = 1.03 [95% CI, 1.01-1.04]), and current smoking (OR = 1.76 [95% CI, 1.12-2.75]) were also significant. Sex and diabetes were not statistically significant covariates. Conclusion: The prevalence of CTS is higher among workers with trigger digit. [ABSTRACT FROM AUTHOR]

Prolonged sitting is a risk factor for several diseases and the prevalence of worksite-based interventions such as sit-to-stand workstations is increasing. Although their impact on sedentary behaviour has been regularly investigated, the effect of working in alternating body postures on cognitive performance is unclear. To address this uncertainty, 45 students participated in a two-arm, randomised controlled cross-over trial under laboratory conditions. Subjects executed validated cognitive tests (working speed, reaction time, concentration performance) either in sitting or alternating working postures on two separate days (ClinicalTrials.gov Identifier: NCT02863731). MANOVA results showed no significant difference in cognitive performance between trials executed in alternating, standing or sitting postures. Perceived workload did not differ between sitting and alternating days. Repeated measures ANOVA revealed significant learning effects regarding concentration performance and working speed for both days. These results suggest that working posture did not affect cognitive performance in the short term. Practitioner Summary: Prior reports indicated health-related benefits based on alternated (sit/stand) body postures. Nevertheless, their effect on cognitive performance is unknown. This randomised controlled trial showed that working in alternating body postures did not influence reaction time, concentration performance, working speed or workload perception in the short term. [ABSTRACT FROM AUTHOR]

The Strain Index (SI) and the American Conference of Governmental Industrial Hygienists (ACGIH) threshold limit value for hand activity level (TLV for HAL) have been shown to be associated with prevalence of distal upper-limb musculoskeletal disorders such as carpal tunnel syndrome (CTS). The SI and TLV for HAL disagree on more than half of task exposure classifications. Similarly, time-weighted average (TWA), peak, and typical exposure techniques used to quantity physical exposure from multi-task jobs have shown between-technique agreement ranging from 61% to 93%, depending upon whether the SI or TLV for HAL model was used. This study compared exposure-response relationships between each model-technique combination and prevalence of CTS. Physical exposure data from 1,834 workers (710 with multi-task jobs) were analyzed using the SI and TLV for HAL and the TWA, typical, and peak multi-task job exposure techniques. Additionally, exposure classifications from the SI and TLV for HAL were combined into a single measure and evaluated. Prevalent CTS cases were identified using symptoms and nerve-conduction studies. Mixed effects logistic regression was used to quantify exposure-response relationships between categorized (i.e., low, medium, and high) physical exposure and CTS prevalence for all model-technique combinations, and for multi-task workers, mono-task workers, and all workers combined. Except for TWA TLV for HAL, all model-technique combinations showed monotonic increases in risk of CTS with increased physical exposure. The combined-models approach showed stronger association than the SI or TLV for HAL for multi-task workers. Despite differences in exposure classifications, nearly all model-technique combinations showed exposure-response relationships with prevalence of CTS for the combined sample of mono-task and multi-task workers. Both the TLV for HAL and the SI, with the TWA or typical techniques, appear useful for epidemiological studies and surveillance. However, the utility of TWA, typical, and peak techniques for job design and intervention is dubious. [ABSTRACT FROM PUBLISHER]

The Composite Strain Index (COSI) quantifies biomechanical stressors for complex tasks consisting of exertions at different force levels and/or with different exertion times. The Cumulative Strain Index (CUSI) further integrates biomechanical stressors from different tasks to quantify exposure for the entire work shift. The paper provides methodologies to compute COSI and CUSI along with examples. Complex task simulation produced 169,214 distinct tasks. Use of average, time-weighted average (TWA) and peak force and COSI classified 66.9, 28.2, 100 and 38.9% of tasks as hazardous, respectively. For job rotation the simulation produced 10,920 distinct jobs. TWA COSI, peak task COSI and CUSI classified 36.5, 78.1 and 66.6% jobs as hazardous, respectively. The results suggest that the TWA approach systematically underestimates the biomechanical stressors and peak approach overestimates biomechanical stressors, both at the task and job level. It is believed that the COSI and CUSI partially address these underestimations and overestimations of biomechanical stressors. Practitioner Summary:COSI quantifies exposure when applied hand force and/or duration of that force changes during a task cycle. CUSI integrates physical exposures from job rotation. These should be valuable tools for designing and analysing tasks and job rotation to determine risk of musculoskeletal injuries. [ABSTRACT FROM PUBLISHER]

The Revised Strain Index (RSI) is a distal upper extremity (DUE) physical exposure assessment model based on: intensity of exertion, frequency of exertion, duration per exertion, hand/wrist posture and duration of task per day. The RSI improves upon the 1995 Strain Index (SI) by using continuous rather than categorical multipliers, and replacing duty cycle with duration per exertion. In a simulation of 13,944 tasks, the RSI and 1995 SI showed good agreement in risk predictions for 1995 SI scores ≤3 (safe) and >13.5 (hazardous). For tasks with 1995 SI scores of >3 and ≤13.5, the two models showed marked disagreement, with the RSI providing much greater discriminations between ‘safe’ and ‘hazardous’ tasks for various combinations of force, repetition and duty cycle. We believe the RSI is a substantially improved model that will be useful for DUE task analysis, intervention and design. Practitioner Summary:RSI is a substantial improvement over the 1995 SI. It should be a valuable tool for designing and analysing tasks to determine risk of musculoskeletal injuries. RSI is applicable to a wide variety of tasks including very low force and very high repetition tasks such as keyboard use. [ABSTRACT FROM PUBLISHER]

The relationships between work organisational, biomechanical and psychosocial factors were studied using cross-sectional data from a pooled dataset of 1834 participants. The work organisational factors included: job rotation, overtime work, having second jobs and work pace. Task and job level biomechanical variables were obtained through sub-task data collected in the field or analysed in the laboratory. Psychosocial variables were collected based on responses to 10 questions. The results showed that job rotations had significant effects on all biomechanical and most psychosocial measures. Those with job rotations generally had higher job biomechanical stressors, and lower job satisfaction. Overtime work was associated with higher job biomechanical stressors, and possibly self-reported physical exhaustion. Those having second jobs reported getting along with co-workers well. Work pace had significant influences on all biomechanical stressors, but its impact on job biomechanical stressors and psychosocial effects are complicated. Practitioner Summary: The findings are based on a large number of subjects collected by three research teams in diverse US workplaces. Job rotation practices used in many workplaces may not be effective in reducing job biomechanical stressors for work-related musculoskeletal disorders. Overtime work is also associated with higher biomechanical stressors. [ABSTRACT FROM AUTHOR]