Alysha R. Meyers

Cohort mortality study of garment industry workers exposed to formaldehyde: Update and internal comparisons

BACKGROUND To further evaluate the association between formaldehyde and leukemia, we extended follow-up through 2008 for a cohort mortality study of 11,043 US formaldehyde-exposed garment workers. METHODS We computed standardized mortality ratios and standardized rate ratios stratified by year of first exposure, exposure duration, and time since first exposure. Associations between exposure duration and rates of leukemia and myeloid leukemia were further examined using Poisson regression models. RESULTS Compared to the US population, myeloid leukemia mortality was elevated but overall leukemia mortality was not. In internal analyses, overall leukemia mortality increased with increasing exposure duration and this trend was statistically significant. CONCLUSIONS We continue to see limited evidence of an association between formaldehyde and leukemia. However, the extended follow-up did not strengthen previously observed associations. In addition to continued epidemiologic research, we recommend further research to evaluate the biological plausibility of a causal relation between formaldehyde and leukemia.

Assessment of ALS mortality in a cohort of formaldehyde-exposed garment workers

The etiology of ALS is unknown. Although some investigators have evaluated the role of occupational exposures (1), their role is poorly understood. Among subjects with known exposure duration in the American Cancer Society’s Cancer Prevention Study II cohort (~1 million subjects), the ALS mortality rate was more than two times higher for subjects with self-reported formaldehyde exposure, compared to unexposed subjects (rate ratio 2.47, 95% confidence interval (CI) 1.58-3.86, 1120 unexposed and 22 exposed cases), and strongly associated with exposure duration (2). Compared to unexposed subjects, the rate ratios were 1.5, 2.1, and 4.1 for subjects with 10 years of self-reported formaldehyde exposure, respectively. In contrast, formaldehyde exposure (inferred from occupation) was not associated with ALS in a small case-control study (109 cases, 253 controls) by Fang and colleagues (1). In this study, no association was observed with weighted exposure duration although an imprecise 3-fold increase of ALS, based on four cases, was observed among a sub-group of the highest exposure tertile. We evaluated ALS mortality among a cohort of formaldehyde-exposed garment workers (3–5).

Mortality among styrene-exposed workers in the reinforced plastic boatbuilding industry

Background We updated mortality through 2011 for 5203 boat-building workers potentially exposed to styrene, and analysed mortality among 1678 employed a year or more between 1959 and 1978. The a priori hypotheses: excess leukaemia and lymphoma would be found. Methods Standardised mortality ratios (SMRs) and 95% CIs and standardised rate ratios (SRRs) used Washington State rates and a person-years analysis programme, LTAS.NET. The SRR analysis compared outcomes among tertiles of estimated cumulative potential styrene exposure. Results Overall, 598 deaths (SMR=0.96, CI 0.89 to 1.04) included excess lung (SMR=1.23, CI 0.95 to 1.56) and ovarian cancer (SMR 3.08, CI 1.00 to 7.19), and chronic obstructive pulmonary disease (COPD) (SMR=1.15, CI 0.81 to 1.58). Among 580 workers with potential high-styrene exposure, COPD mortality increased 2-fold (SMR=2.02, CI 1.08 to 3.46). Conclusions COPD was more pronounced among those with potential high-styrene exposure. However, no outcome was related to estimated cumulative styrene exposure, and there was no change when latency was taken into account. We found no excess leukaemia or lymphoma mortality. As in most occupational cohort studies, lack of information on lifestyle factors or other employment was a substantial limitation although we excluded from the analyses those (n=3525) who worked <1 year. Unanticipated excess ovarian cancer mortality could be a chance finding. Comparing subcohorts with potential high-styrene and low-styrene exposure, COPD mortality SRR was elevated while lung cancer SRR was not, suggesting that smoking was not the only cause for excess COPD mortality.

Evaluation of alternate category structures for the Strain Index: an empirical analysis.

Objective: The purpose of this study was to develop alternative Strain Index risk classification categories. Background: Strain Index scores are usually categorized into four Strain Index “risk categories.” The “original” risk categories were developed in the meat-packing industry and may not be fully applicable to other industries. Method: Daily Strain Index scores were estimated among 276 manufacturing workers participating in a cohort study of occupational risk factors for hand–arm musculoskeletal symptoms. Each score was categorized using the original method and a new method based on quartiles of Strain Index score values among symptomatic participants. Models examining associations between original Strain Index risk categories and incident hand–arm symptoms were compared to models examining associations between the alternative Strain Index risk categories and incident hand–arm symptoms. Results: Compared to the respective referent categories, a twofold or greater increase in the risk of incident hand–arm symptoms was observed for the highest original Strain Index risk category (HR = 2.06, 95% CI = [1.08–3.92]) and for the second highest alternate Strain Index risk exposure category (HR = 2.21, 95% CI = [1.26–3.85]). Although significant associations between Strain Index risk category and incident hand–arm symptoms were observed for both Strain Index categorization methods, model fit statistics favored the alternate approach. Conclusion: Results from this study suggests that the Strain Index risk category structure may need to be tailored to specific populations. Application: If verified, results from this study provide a better way to identify hazardous manufacturing jobs and target them for exposure reduction.

How Do Computer Vision Upper Extremity Exposure Measures Compare Against Manual Measures

Background Various quantification methods have been used to measure exposure to risk factors for musculoskeletal injuries, including observation, video-based frame-by-frame analysis, and direct measurements. Each technique has advantages and disadvantages. The American Conference of Government Industrial Hygienists (2017) Threshold Limit Value® (TLV®) uses the hand activity level (HAL) rating scale, a 10-point visual analog scale based on hand speed and rest pauses. HAL may be determined subjectively by an observer or from a lookup table, or an equation by measuring exertion frequency (F) and percent duty cycle (D). This study compares task level physical exposure variables measured manually and using video computer vision for jobs selected from a selected subset of the Upper Limb MSD Consortium prospective study. We compared F and D, calculated both using manual single-frame MVTA analysis and automatic computer vision (Akkas et al., 2015, Akkas et al., 2016, Akkas et al., 2017, Greene et al., 2017). Methods This study utilized exposure data from prospective studies conducted by the National Institute for Occupational Safety and Health (NIOSH), the Safety & Health Assessment & Research for Prevention (SHARP) in the State of Washington, and the University of California -San Francisco (UCSF). Some data from these prospective cohort studies had been previously pooled and analyzed as part of the Upper Limb MSD Consortium, a group of seven prospective cohort studies (Bao et al., 2015; Harris-Adamson et. al., 2013a, 2013b; Harris-Adamson et. al., 2014; Kapellusch et al., 2013, 2014; Fan et al., 2015). Because the videos were created for a different purpose, not all were suitable for computer vision analysis. We selected 1001 videos where we applied hand tracking and data checking to date. Thus, not all study sites are equally represented. The occurrence of each exertion was first identified in all the videos by human analysts for manually calculating the frequency (exertions/ second) and duty cycle (percent exertion time/ cycle time). The hands were tracked using marker-less video tracking and a feature vector training (FVT) algorithm (Akkas et al., 2016 Akkas et al., 2017) was trained using the first cycle exertions identified by an analyst, for automatically estimating subsequent exertions in the videos. We then applied the FVT algorithm to the 1001 videos clips and automatically identified video frames representing exertions of the dominant hand. As a result, we counted total frames of exertions as well as the total number of exertions to calculate F and D. Results The calculated D (%) and F (Hz) errors were the average difference between the manual frame-by-frame and the computer vision estimates. We found an average error of 12.7% (SD=36.8%) for D and 0.06 Hz (SD=0.38 Hz) for F. The average HAL error was 1.3 (SD=2.2), which is considered negligible. Conclusions The results indicate that computer vision can reliably estimate important exposure variables for many tasks. Since the videos used in this study were taken for a different purpose, we anticipate the algorithms will perform better when videos are recorded specifically for computer vision analysis.

Incident CTS in a large pooled cohort study: associations obtained by a Job Exposure Matrix versus associations obtained from observed exposures

Background There is growing use of a job exposure matrix (JEM) to provide exposure estimates in studies of work-related musculoskeletal disorders; few studies have examined the validity of such estimates, nor did compare associations obtained with a JEM with those obtained using other exposures. Objective This study estimated upper extremity exposures using a JEM derived from a publicly available data set (Occupational Network, O*NET), and compared exposure-disease associations for incident carpal tunnel syndrome (CTS) with those obtained using observed physical exposure measures in a large prospective study. Methods 2393 workers from several industries were followed for up to 2.8 years (5.5 person-years). Standard Occupational Classification (SOC) codes were assigned to the job at enrolment. SOC codes linked to physical exposures for forceful hand exertion and repetitive activities were extracted from O*NET. We used multivariable Cox proportional hazards regression models to describe exposure-disease associations for incident CTS for individually observed physical exposures and JEM exposures from O*NET. Results Both exposure methods found associations between incident CTS and exposures of force and repetition, with evidence of dose–response. Observed associations were similar across the two methods, with somewhat wider CIs for HRs calculated using the JEM method. Conclusion Exposures estimated using a JEM provided similar exposure-disease associations for CTS when compared with associations obtained using the ‘gold standard’ method of individual observation. While JEMs have a number of limitations, in some studies they can provide useful exposure estimates in the absence of individual-level observed exposures.

The Speed Calculated Hand Activity Level (HAL) Matches Observer Estimates Better Than the Frequency Calculated HAL

Hand Activity Level (HAL) can be estimated from observations (HALO), calculated from exertion frequency, F and duty cycle D (HALF) or from speed, S and D (HALS). Data collected by prospective cohort studies were used to compare these methods. There was 75% agreement between HALO and HALS (HALS = 1.02 × HALO −0.2, R2 = 0.78, F(1,1003) = 43665, p < .001), but only 30% agreement between HALO and HALF (HALF = 0.21 × HALO + 2.2, R2 = 0.04, F(1,1003) = 71.71, p < .001). HALS was more consistent with HALO since both are dependent on speed, and because HALS can be automated, it is more objective than HALF or HALO in this sample.

0110 Cancer Mortality among Styrene and Fibreglass Exposed Workers in the Reinforced Plastic Boatbuilding Industry

Objectives Mortality was updaated through 2008 for 5203 workers exposed to styrene, fibreglass, and wood dust between 1959 and 1978 at two boatbuilding plants. The a priori hypothesis: leukaemia and lymphoma excesses would be found Method Standardised mortality ratios (SMR), standardised rate ratios (SRR), and 95% confidence intervals (CI) were calculated using Washington State rates and a person-years analysis program, LTAS. NET, controlling for age, calendar period, race, and gender. The SRR analysis compared tertiles of estimated cumulative styrene exposure. Results Overall, 484 cancer deaths occurred (SMR 1.20, CI 1.10–1.31), with excess mortality for respiratory cancers (n = 171, SMR 1.33, CI 1.14–1.55) and prostate cancer (n = 41, SMR 1.44, CI 1.03–1.96). Among 2063 workers highly exposed to styrene and fibreglass there were excesses of mesothelioma (n = 3, SMR 5.28, CI 1.09–15.4) and ovarian cancer (n = 6, SMR 2.94, CI 1.08–6.41). The SRR analysis did not find strong associations between tertiles of styrene exposure and cancer mortality. Conclusions We found no excess leukaemia or lymphoma mortality. Unanticipated excess mesothelioma and ovarian cancer mortality are difficult to interpret and could be due to fibreglass exposure or employment elsewhere, or could be chance findings.