Evaluating Different Measures of Low Back Pain Among U.S. Manual Materials Handling Workers: Comparisons of Demographic, Psychosocial, and Job Physical Exposure.

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.

Validation of the Revised Strain Index for Predicting Risk of Incident Carpal Tunnel Syndrome in a Prospective Cohort.

The Revised Strain Index (RSI), a model that quantifies physical exposure from individual hand/wrist exertions, tasks, and multi-task jobs, was used to quantify exposure for 1372 incident-eligible manufacturing, service and healthcare workers. Workers were followed for an average of 2.5 years (maximum 6 years) and had an average carpal tunnel syndrome (CTS) incidence rate of 4.6 per 100 person-years. Exceeding the a-priori RSI limit of 10.0 showed increased risk of CTS (Hazard Ratio (HR) = 1.45, 95% CI: 1.11-1.91, p = 0.01). There also was a dose-response relationship using proposed low (RSI ≤ 8.5, HR = 1.00), medium (HR = 1.42 (95% CI: 0.96-2.09, p = 0.08)), and high limits (RSI > 15, HR = 1.79 (95% CI: 1.19-2.69, p = 0.01), respectively. RSI as a continuous variable showed CTS risk increased steadily by between 1.9% and 3.3% per unit increase in RSI (p ≤ 0.03). These results suggest that the RSI is a useful tool for surveillance as well as for job intervention/design and continuous improvement processes.Practitioner Summary The Revised Strain Index (RSI) quantifies physical exposure from individual hand/wrist exertions, tasks, and multi-task jobs. Increased cumulative RSI scores (i.e. daily exposure score) are associated with increased risk of carpal tunnel syndrome (CTS). The RSI is potentially useful as a risk surveillance and intervention design tool.

The Coexistence of Carpal Tunnel Syndrome in Workers With Trigger Digit.

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.

Prevalence of low back pain, seeking medical care, and lost time due to low back pain among manual material handling workers in the United States.

BACKGROUND: Low back pain (LBP) is a common and costly problem throughout the United States. To achieve a greater understanding of the occupational risk factors, the National Institute for Occupational Safety and Health (NIOSH) funded a low back health effects consortium, which performed several surveillance studies throughout the United States. This study combines data from the consortium research groups resulting in a data set with nearly 2000 workers in various regions of the country. The purpose of this paper is to examine prevalence and personal risk factors of low back health effects among these workers. METHODS: There were three common questions regarding history of low back health effects in the past 12 months including 1) have you had LBP lasting 7 days, 2) have you sought medical care for LBP, and 3) have you taken time off work due to LBP. The questionnaire included demographic questions. There were five data collections institutions or sites including NIOSH, Ohio State University, University of Wisconsin-Milwaukee, Texas A&M University, and University of Utah. RESULTS: The 12-month period prevalence of low back pain lasting 7 days, seeking medical care, and lost time due to LBP were 25, 14 and 10%, respectively. There were no statistically significant differences in gender, age or weight between cases and non-cases for any prevalence measure. The height of workers was significantly greater in the cases compared to non-cases for all three prevalence definitions. There were significant differences among the sites on the prevalence of seeking medical care for LBP and lost time due to LBP. The Ohio State University had significantly higher prevalence rates for seeking medical care and lost time due to LBP than University of Wisconsin, University of Utah, or Texas A&M University. CONCLUSION: LBP, the least severe low back health effect studied, had the highest prevalence (25%) and lost time due to LBP, the most severe low back health effect studied, had the lowest prevalence (10%) among nearly 2000 US manual material handling workers. There was a significant site or regional influence in prevalence rates for seeking medical care and lost time due to LBP.

Medium-term effects of a two-desk sit/stand workstation on cognitive performance and workload for healthy people performing sedentary work: a secondary analysis of a randomised controlled trial.

Implementing sit/stand workstations in sedentary work environments is a common way to reduce sedentary time, but their medium-term effect on cognitive performance is unclear. To address this circumstance, eighteen office workers participated in a two-arm, randomised controlled cross-over trial (ClinicalTrials.gov Identifier: NCT02825303), either working at a traditional (sit) or an interventional (sit/stand) workplace for 23 weeks. Cognitive performance (working speed, reaction time, concentration performance, accuracy), workload and relevant covariates (salivary cortisol level, heart rate, physical activity, sitting time) were measured pre- and post-intervention under laboratory conditions. MANOVA and RMANOVA results did not show differences in performance parameters and workload, respectively, between sit/stand and traditional workplace users. Differences in text editing accuracy and cortisol levels for sit/stand workstation users indicate potential connectivity to cognitive parameters which should be further examined with large-scale studies. Practitioner summary: Medium-term effects of working at sit/stand workstations on cognitive performance and workload are unexplored. This randomised controlled trial suggests that cognitive performance and workload are unaffected for sit/stand workstation users after 23 weeks of use. However, accuracy appeared to improve and physiological stress appeared to be altered. Abbreviations: BMI: body mass index; IPAQ: International physical activity questionnaire; MET: metabolic equivalent of task; MANOVA: multivariate ANOVA; NASA TLX: NASA task load index; RMANOVA: repeated measures ANOVA.

Biomechanical Evaluations of Bed-to-Wheelchair Transfer: Gait Belt Versus Walking Belt.

Nursing personnel, particularly caregivers who frequently perform manual patient transfer tasks, are at risk for work-related musculoskeletal disorders (WMSDs). The purpose of this study was to perform biomechanical evaluations of bed-to-wheelchair transfer using two low-cost assistive devices: walking belt and gait belt. Twenty-eight college students, serving as caregivers, transferred 14 students, serving as patients. "Caregiver" spinal loading and strength requirements at major joints were measured using a 3D Static Strength Prediction Model. "Caregiver"-perceived stresses were assessed using the Borg CR-10 Scale. "Patient" safety and comfort ratings were determined using Likert-type scales. The findings indicated that transferring "patients" using walking belts with a pulling technique produced significantly lower biomechanical stress than using gait belts. "Patients" also felt more comfortable and safer during walking belt transfers. It is recommended that health care facilities should consider use of walking belts in place of gait belts to transfer partially weight-bearing patients.

Effect of alternating postures on cognitive performance for healthy people performing sedentary work.

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.

Risk assessments using the Strain Index and the TLV for HAL, Part II: Multi-task jobs and prevalence of CTS.

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.

Risk assessments using the Strain Index and the TLV for HAL, Part I: Task and multi-task job exposure classifications.

BACKGROUND: The Strain Index (SI) and the American Conference of Governmental Industrial Hygienists (ACGIH) Threshold Limit Value for Hand Activity Level (TLV for HAL) use different constituent variables to quantify task physical exposures. Similarly, time-weighted-average (TWA), Peak, and Typical exposure techniques to quantify physical exposure from multi-task jobs make different assumptions about each task's contribution to the whole job exposure. Thus, task and job physical exposure classifications differ depending upon which model and technique are used for quantification. This study examines exposure classification agreement, disagreement, correlation, and magnitude of classification differences between these models and techniques. METHODS: Data from 710 multi-task job workers performing 3,647 tasks were analyzed using the SI and TLV for HAL models, as well as with the TWA, Typical and Peak job exposure techniques. Physical exposures were classified as low, medium, and high using each model's recommended, or a priori limits. Exposure classification agreement and disagreement between models (SI, TLV for HAL) and between job exposure techniques (TWA, Typical, Peak) were described and analyzed. RESULTS: Regardless of technique, the SI classified more tasks as high exposure than the TLV for HAL, and the TLV for HAL classified more tasks as low exposure. The models agreed on 48.5% of task classifications (kappa = 0.28) with 15.5% of disagreement between low and high exposure categories. Between-technique (i.e., TWA, Typical, Peak) agreement ranged from 61-93% (kappa: 0.16-0.92) depending on whether the SI or TLV for HAL was used. CONCLUSIONS: There was disagreement between the SI and TLV for HAL and between the TWA, Typical and Peak techniques. Disagreement creates uncertainty for job design, job analysis, risk assessments, and developing interventions. Task exposure classifications from the SI and TLV for HAL might complement each other. However, TWA, Typical, and Peak job exposure techniques all have limitations. Part II of this article examines whether the observed differences between these models and techniques produce different exposure-response relationships for predicting prevalence of carpal tunnel syndrome.

Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines.

Truncated power basis expansions and penalized spline methods are demonstrated for estimating nonlinear exposure-response relationships in the Cox proportional hazards model. R code is provided for fitting models to get point and interval estimates. The method is illustrated using a simulated data set under a known exposure-response relationship and in a data application examining risk of carpal tunnel syndrome in an occupational cohort.

The Composite Strain Index (COSI) and Cumulative Strain Index (CUSI): methodologies for quantifying biomechanical stressors for complex tasks and job rotation using the Revised Strain Index.

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.

The Revised Strain Index: an improved upper extremity exposure assessment model.

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.

Impact of Work Organizational Factors on Carpal Tunnel Syndrome and Epicondylitis.

OBJECTIVE: The aim of this study was to identify relationships between work organizational variables (job rotation, overtime work, having a second job, and work pacing) (These work organizational variables and their relationships with biomechanical and psychosocial exposures were studied previously and published in a separate paper.) and health outcome measures [carpal tunnel syndrome (CTS), lateral and medial epicondylitis (LEPI/MEPI)]. METHODS: Using a pooled baseline cohort of 1834 subjects, the relationships were studied using logistic regression models. RESULTS: Varied degrees of associations between the work organizational and outcomes variables were found. Job rotation was significantly associated with being a CTS case [odds ratio (OR) = 1.23, 95% confidence interval (95% CI): 1.00 to 1.50]. Overtime work was significantly associated with lower LEPI prevalence (OR = 0.48, 95% CI: 0.28 to 0.84). No statistically significant associations were found between having a second job and different work pacing and any of the three health outcome measures. CONCLUSIONS: Work organizational variables were only partially associated with the studied health outcomes.

Effect of a novel two-desk sit-to-stand workplace (ACTIVE OFFICE) on sitting time, performance and physiological parameters: protocol for a randomized control trial.

BACKGROUND: Prolonged sitting is ubiquitous in modern society and linked to several diseases. Height-adjustable desks are being used to decrease worksite based sitting time (ST). Single-desk sit-to-stand workplaces exhibit small ST reduction potential and short-term loss in performance. The aim of this paper is to report the study design and methodology of an ACTIVE OFFICE trial. DESIGN: The study was a 1-year three-arm, randomized controlled trial in 18 healthy Austrian office workers. Allocation was done via a regional health insurance, with data collection during Jan 2014 - March 2015. Participants were allocated to either an intervention or control group. Intervention group subjects were provided with traditional or two-desk sit-to-stand workstations in either the first or the second half of the study, while control subjects did not experience any changes during the whole study duration. Sitting time and physical activity (IPAQ-long), cognitive performance (text editing task, Stroop-test, d2R test of attention), workload perception (NASA-TLX) and physiological parameters (salivary cortisol, heartrate variability and body weight) were measured pre- and post-intervention (23 weeks after baseline) for intervention and control periods. Postural changes and sitting/standing time (software logger) were recorded at the workplace for the whole intervention period. DISCUSSION: This study evaluates the effects of a novel two-desk sit-to-stand workplace on sitting time, physical parameters and work performance of healthy office based workers. If the intervention proves effective, it has a great potential to be implemented in regular workplaces to reduce diseases related to prolonged sitting. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02825303 , July 2016 (retrospectively registered).

The Cumulative Lifting Index (CULI) for the Revised NIOSH Lifting Equation: Quantifying Risk for Workers With Job Rotation.

OBJECTIVE: The objectives were to: (a) develop a continuous frequency multiplier (FM) for the Revised NIOSH Lifting Equation (RNLE) as a function of lifting frequency and duration of a lifting task, and (b) describe the Cumulative Lifting Index (CULI), a methodology for estimating physical exposure to workers with job rotation. BACKGROUND: The existing FM for the RNLE (FME) does not differentiate between task duration >2 hr and <8 hr, which makes quantifying physical exposure to workers with job rotation difficult and presents challenges to job designers. METHOD: Using the existing FMs for 1, 2, and 8 hr of task durations, we developed a continuous FM (FMP) that extends to 12 hr per day. We simulated 157,500 jobs consisting of two tasks each and, using different combinations of Frequency Independent Lifting Index, lifting frequency and duration of lifting. Biomechanical stresses were estimated using the CULI, time-weighted average (TWA), and peak exposure. RESULTS: The median difference between FME and FMP was ±1% (range: 0%-15%). Compared to CULI, TWA underestimated risk of low-back pain (LBP) for 18% to 30% of jobs, and peak exposure for an assumed 8-hr work shift overestimated risk of LBP for 20% to 25% of jobs. Peak task exposure showed 90% agreement with CULI but ignored one of two tasks. CONCLUSION: The CULI partially addressed the underestimation of physical exposure using the TWA approach and overestimation of exposure using the peak-exposure approach. APPLICATION: The proposed FM and CULI may provide more accurate physical exposure estimates, and therefore estimated risk of LBP, for workers with job rotation.

Relationships between job organisational factors, biomechanical and psychosocial exposures.

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.

Developing a pooled job physical exposure data set from multiple independent studies: an example of a consortium study of carpal tunnel syndrome.

BACKGROUND: Six 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. OBJECTIVE: This paper provides a detailed description of the characteristics of the pooled physical exposure variables and the source data information from the individual research studies. METHODS: Physical 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. RESULTS: At 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. CONCLUSIONS: The 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.

Exposure-response relationships for the ACGIH threshold limit value for hand-activity level: results from a pooled data study of carpal tunnel syndrome.

OBJECTIVES: This 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). METHODS: Manufacturing 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. RESULTS: The 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. CONCLUSION: Those 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.

Association between lifting and use of medication for low back pain: results from the Backworks Prospective Cohort Study.

OBJECTIVE: To evaluate relationships between lifting and lowering of loads and risk of low back pain resulting in medication use (M-LBP). METHODS: At baseline, worker demographics, psychosocial factors, hobbies, LBP history, and lifting and lowering (quantified using the Revised NIOSH Lifting Equation) were assessed. A cohort of 258 incident-eligible workers was followed up for 4.5 years to determine new M-LBP cases and changes in lifting/lowering requirements. Proportional hazards regression with time-varying covariates was used to model associations. RESULTS: Factors predicting M-LBP included peak lifting index (PLI) and composite lifting index (PCLI), LBP history, anxiety, and housework. In adjusted models, PLI and PCLI showed exposure-response relationships with peak hazard ratios of 3.8 and 4.3, respectively (P ≤ 0.02). CONCLUSIONS: Lifting of loads is associated with increased risk of M-LBP. The PLI and PCLI are useful metrics for estimating the risk of M-LBP from lifting.

The NIOSH lifting equation and low-back pain, Part 1: Association with low-back pain in the backworks prospective cohort study.

OBJECTIVE: The aim of this study was to evaluate relationships between the revised NIOSH lifting equation (RNLE) and risk of low-back pain (LBP). BACKGROUND: The RNLE is commonly used to quantify job physical stressors to the low back from lifting and/or lowering of loads. There is no prospective study on the relationship between RNLE and LBP that includes accounting for relevant covariates. METHOD: A cohort of 258 incident-eligible workers from 30 diverse facilities was followed for up to 4.5 years. Job physical exposures were individually measured. Worker demographics, medical history, psychosocial factors, hobbies, and current LBP were obtained at baseline. The cohort was followed monthly to ascertain development of LBP and quarterly to determine changes in job physical exposure. The relationship between LBP and peak lifting index (PLI) and peak composite lifting index (PCLI) were tested in multivariate models using proportional hazards regression. RESULTS: Point and lifetime prevalences of LBP at baseline were 7.1% and 75.1%, respectively. During follow-up, there were 123 incident LBP cases. Factors predicting development of LBP included job physical exposure (PLI and PCLI), history of LBP, psychosocial factors, and housework. In adjusted models, risk (hazard ratio [HR]) increased per-unit increase in PLI and PCLI (p = .05 and .02; maximum HR = 4.3 and 4.2, respectively). PLI suggested a continuous increase in risk with an increase in PLI, whereas the PCLI showed elevated, but somewhat reduced, risk at higher exposures. CONCLUSION: Job physical stressors are associated with increased risk of LBP. Data suggest that the PLI and PCLI are useful metrics for estimating exposure to job physical stressors.