Comparison Between Musculoskeletal Pain and Gender-Specific, Non-gendered Job-Exposure Matrix and Self-reported Exposures in CONSTANCES.

PURPOSE: Musculoskeletal disorders (MSDs) are common worldwide and gender differences exist in terms of prevalence and disability. MSDs are a leading cause of sick leave and physical work exposures. To assess the association between physical exposures assessed by the gender-specific CONSTANCES Job-Exposure Matrix (JEM) and musculoskeletal pain in six areas: neck pain, shoulder pain, elbow/arm pain, hand/wrist pain, low back pain, knee/leg pain; and to compare the results with those obtained using the non-gendered CONSTANCES JEM and with individual self-report exposures. METHODS: We included 48,736 male and 63,326 female workers from the CONSTANCES cohort (France). The association between 27 physical exposures and musculoskeletal self-reported pain in six body areas was assessed using logistic regression. We conducted the analysis with three types of exposures: (1) individual self-reported exposures; (2) gender-specific CONSTANCES JEM; (3) non-gendered CONSTANCES JEM, and adjusted for age and Body Mass Index (BMI). Analyses were stratified by gender. RESULTS: The associations to the gender-specific and non-gendered JEM were similar. The odds ratios using individual self-reported exposures were comparable to the JEM-based associations, with the exceptions of the exposures 'change tasks', 'rest eyes' and 'reach behind'. In some comparisons, there were differences in the direction and/or significance of effects between genders (regardless of whether the JEM used was gender-specific or not). CONCLUSION: The gender-specific and non-gendered JEMs gave similar results, hence, developing physical work exposures JEMs that are gender-specific may not be essential. However, when predicting musculoskeletal pain, it seems relevant to stratify the analysis by gender.

Supporting the Resilience and Mental Health of Missouri Healthcare Workers Through COVID-19 and Beyond: the Gateway2Wellness Program.

The COVID-19 pandemic is over, but US healthcare workers (HCWs) continue to report high levels of work-related exhaustion and burnout but are unlikely to seek help. Digital tools offer a scalable solution. Between February and June 2022, we surveyed Missouri hospital administrators to assess HCW mental health and identify related evidence-based or evidence-informed resources. Simultaneously, we conducted a digital survey and focus groups with HCWs and leaders at Washington University School of Medicine (WUSOM) in St. Louis to evaluate HCW mental health needs, and preferences for digital support. Here, we describe the results and subsequent development of the Gateway to Wellness (G2W) program, a digital precision engagement platform that links HCWs to the most effective tailored resources for their mental health needs.

Effects of Persistent Exposure to COVID-19 on Mental Health Outcomes Among Trainees: a Longitudinal Survey Study.

BACKGROUND: The rapid spread of the coronavirus disease 2019 (COVID-19) has created considerable strain on the physical and mental health of healthcare workers around the world. The effects have been acute for physician trainees-a unique group functioning simultaneously as learners and care providers with limited autonomy. OBJECTIVE: To investigate the longitudinal effects of physician trainee exposure to patients being tested for COVID-19 on stress, anxiety, depression, and burnout using three surveys conducted during the early phase of the pandemic. DESIGN: Longitudinal survey study. PARTICIPANTS: All physician trainees (N = 1375) at an academic medical center. MAIN MEASURE: Assess the relationship between repeated exposure to patients being tested for COVID-19 and stress, anxiety, depression, and burnout. KEY RESULTS: Three hundred eighty-nine trainees completed the baseline survey (28.3%). Of these, 191 and 136 completed the ensuing surveys. Mean stress, anxiety, and burnout decreased by 21% (95% confidence interval (CI): - 28 to - 12%; P < 0.001), 25% (95% CI: - 36 to - 11%; P < 0.001), and 13% (95% CI: - 18 to - 7%; P < 0.001), respectively, per survey. However, for each survey time point, there was mean increase in stress, anxiety, and burnout per additional exposure: stress [24% (95% CI: + 12 to + 38%; P < 0.001)], anxiety [22% (95% CI: + 2 to + 46%; P = 0.026)], and burnout [18% (95% CI: + 10 to + 28%; P < 0.001)]. For depression, the association between exposure was strongest for the third survey, where mean depression scores increased by 33% per additional exposure (95% CI: + 18 to + 50%; P < 0.001). CONCLUSIONS: Training programs should adapt to address the detrimental effects of the "pileup" of distress associated with persistent exposure through adaptive programs that allow flexibility for time off and recovery.

Temporal Associations Between EHR-Derived Workload, Burnout, and Errors: a Prospective Cohort Study.

BACKGROUND: The temporal progression and workload-related causal contributors to physician burnout are not well-understood. OBJECTIVE: To characterize burnout's time course and evaluate the effect of time-varying workload on burnout and medical errors. DESIGN: Six-month longitudinal cohort study with measurements of burnout, workload, and wrong-patient orders every 4 weeks. PARTICIPANTS: Seventy-five intern physicians in internal medicine, pediatrics, and anesthesiology at a large academic medical center. MAIN MEASURES: Burnout was measured using the Professional Fulfillment Index survey. Workload was collected from electronic health record (EHR) audit logs and summarized as follows: total time spent on the EHR, after-hours EHR time, patient load, inbox time, chart review time, note-writing time, and number of orders. Wrong-patient orders were assessed using retract-and-reorder events. KEY RESULTS: Seventy-five of 104 interns enrolled (72.1%) in the study. A total of 337 surveys and 8,863,318 EHR-based actions were analyzed. Median burnout score across the cohort across all time points was 1.2 (IQR 0.7-1.7). Individual-level burnout was variable (median monthly change 0.3, IQR 0.1-0.6). In multivariable analysis, increased total EHR time (ß=0.121 for an increase from 54.5 h per month (25th percentile) to 123.0 h per month (75th percentile), 95%CI=0.016-0.226), increased patient load (ß=0.130 for an increase from 4.9 (25th percentile) to 7.1 (75th percentile) patients per day, 95%CI=0.053-0.207), and increased chart review time (ß=0.096 for an increase from 0.39 (25th percentile) to 0.59 (75th percentile) hours per patient per day, 95%CI=0.015-0.177) were associated with an increased burnout score. After adjusting for the total number of ordering sessions, burnout was not statistically associated with an increased rate of wrong-patient orders (rate ratio=1.20, 95%CI=0.76-1.89). CONCLUSIONS: Burnout and recovery were associated with recent clinical workload for a cohort of physician trainees, highlighting the elastic nature of burnout. Wellness interventions should focus on strategies to mitigate sustained elevations of work responsibilities.

Occupational characteristics associated with SARS-CoV-2 infection in the UK Biobank during August-November 2020: a cohort study.

BACKGROUND: Occupational exposures may play a key role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection risk. We used a job-exposure matrix linked to the UK Biobank to measure occupational characteristics and estimate associations with a positive SARS-CoV-2 test. METHODS: People reporting job titles at their baseline interview in England who were < 65 years of age in 2020 were included. Healthcare workers were excluded because of differential access to testing. Jobs were linked to the US Occupational Information Network (O*NET) job exposure matrix. O*NET-based scores were examined for occupational physical proximity, exposure to diseases/infection, working outdoors exposed to weather, and working outdoors under cover (score range = 1-5). Jobs were classified as remote work using two algorithms. SARS-CoV-2 test results were evaluated between August 5th-November 10th, 2020, when the UK was released from lockdown. Cox regression was used to calculate adjusted hazard ratios (aHRs), accounting for age, sex, race, education, neighborhood deprivation, assessment center, household size, and income. RESULTS: We included 115,451 people with job titles, of whom 1746 tested positive for SARS-CoV-2. A one-point increase in physical proximity score was associated with 1.14 times higher risk of SARS-CoV-2 (95%CI = 1.05-1.24). A one-point increase in the exposure to diseases/infections score was associated with 1.09 times higher risk of SARS-CoV-2 (95%CI = 1.02-1.16). People reporting jobs that could not be done remotely had higher risk of SARS-CoV-2 regardless of the classification algorithm used (aHRs = 1.17 and 1.20). Outdoors work showed an association with SARS-CoV-2 (exposed to weather aHR = 1.06, 95%CI = 1.01-1.11; under cover aHR = 1.08, 95%CI = 1.00-1.17), but these associations were not significant after accounting for whether work could be done remotely. CONCLUSION: People in occupations that were not amenable to remote work, required closer physical proximity, and required more general exposure to diseases/infection had higher risk of a positive SARS-CoV-2 test. These findings provide additional evidence that coronavirus disease 2019 (COVID-19) is an occupational disease, even outside of the healthcare setting, and indicate that strategies for mitigating transmission in in-person work settings will remain important.

Reliability of O*NET physical exposures between Italian and US databases.

BACKGROUND: Comparison between cross-national job-exposure matrices (JEMs) may provide indications of their reliability, particularly if created using the same items. This study evaluated concordance between two JEMs created from United States (US) and Italian O*NET data, using job codes linked through international job codes. METHODS: Twenty-one physical exposures were obtained from the US and Italian O*NET databases. Italian O*NET items were direct translations of US O*NET items. Six hundred and eighty-four US and 586 Italian job codes were linked via crosswalks to 281 ISCO-08 job codes. A sensitivity study also assessed concordance on 258 jobs matched one-to-one across the two national job classifications. Concordance of US and Italian O*NET exposures was estimated by intraclass correlation coefficients (ICC) in multilevel models adjusted and not adjusted for country. RESULTS: ICCs showed moderate to poor agreement for all physical exposures in jobs linked through ISCO-08 codes. There was good to moderate agreement for 14 out of 21 exposures in models with one-to-one matched jobs between countries; greater agreement was found in all models adjusted for country. Exposure to whole-body vibration, time standing, and working outdoor exposed to weather showed the highest agreement. CONCLUSIONS: These results showed moderate to good agreement for most physical exposures across the two JEMs when US and Italian jobs were matched one-to-one and the analysis was adjusted for country. Job code assignments through crosswalks and differences in exposure levels between countries might greatly influence the observed cross-country agreement. Future multinational epidemiological studies should consider the quality of the cross-national job matching, and potential cross-national differences in exposure levels.

Text-message-based behavioral weight loss for endometrial cancer survivors with obesity: A randomized controlled trial.

OBJECTIVE: To evaluate the ability of a personalized text-message-based intervention to increase weight loss among endometrial cancer survivors with obesity. METHODS: In this randomized, controlled trial, endometrial cancer survivors with obesity (BMI ≥30 kg/m2) were randomized to a personalized SMS text-message-based weight loss intervention or enhanced usual care. Primary outcome was weight loss at 6 months; secondary outcomes were weight loss at 12 months and changes in psychosocial measures. We also compared clinical characteristics and weight change between trial participants and non-participants. RESULTS: Between May 18 and December 31, 2017, 80 endometrial cancer survivors with obesity consented to participate in the randomized trial. There were no differences in clinical characteristics between the two arms. Weight changes were similar in the two arms (P = 0.08). At 6 months, no differences in quality of life, physical activity, or body image were noted. Of 358 eligible patients, 80 became trial participants and 278, non-participants. Trial participants were younger (59.3 vs. 63.4 years, P < 0.001), more likely non-white (P = 0.02), on fewer medications (4 vs. 7, P < 0.001), and had a higher median BMI (38.7 vs. 37.6 kg/m2, P = 0.01) than non-participants. Weight change was similar between participants and non-participants (P = 0.85). At 6 months, similar percentages of participants and non-participants (47.7% vs. 44.4%) had gained weight, and similar percentages (9.2% vs. 11.2%) had lost at least 5% of their body weight. CONCLUSIONS: This text-message-based intervention did not increase weight loss among endometrial cancer survivors with obesity, nor did participation in the trial. Other weight management interventions should be promoted to increase weight loss. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, www.clinicaltrials.gov, NCT03169023.

Predictors of long-term opioid use and opioid use disorder among construction workers: Analysis of claims data.

BACKGROUND: Construction workers have high rates of work-related musculoskeletal disorders, which lead to frequent opioid use and opioid use disorder (OUD). This paper quantified the incidence of opioid use and OUD among construction workers with and without musculoskeletal disorders. METHODS: We conducted a retrospective study using union health claims from January 2015 to June 2018 from 19,909 construction workers. Claims for diagnoses of chronic musculoskeletal disorders, acute musculoskeletal injuries, musculoskeletal surgery, and other conditions were linked to new opioid prescriptions. We examined the effects of high doses (≥50 morphine mg equivalents per day), large supply (more than 7 days per fill), long-term opioid use (60 or more days supplied within a calendar quarter), and musculoskeletal disorders, on the odds of a future OUD. RESULTS: There were high rates (42.8% per year) of chronic musculoskeletal disorders among workers, of whom 24.1% received new opioid prescriptions and 6.3% received long-term opioid prescriptions per year. Workers receiving opioids for chronic musculoskeletal disorders had the highest odds of future OUD: 4.71 (95% confidence interval 3.09-7.37); workers prescribed long-term opioids in any calendar quarter had a nearly 10-fold odds of developing an OUD. CONCLUSIONS: Among construction workers, opioids initiated for musculoskeletal pain were strongly associated with incident long-term opioid use and OUD. Musculoskeletal pain from physically demanding work is likely one driver of the opioid epidemic in occupations like construction. Prevention of work injuries and alternative pain management are needed for workers at risk for musculoskeletal injuries.

Determining occupation for National Violent Death Reporting System records: An evaluation of autocoding programs.

BACKGROUND: Suicide is a leading cause of death for working-age adults. Suicide risk varies across occupations. The National Violent Death Reporting System (NVDRS) collects information about violent deaths occurring in the United States. Occupation can be determined using autocoding programs with NVDRS data. The objective of this analysis is to determine the accuracy of autocoding programs for assigning occupations in the NVDRS. METHODS: Deaths from suicide were identified in NVDRS for individuals age 16 and older from 2010 to 2017. Occupations were assigned after processing job description free text with autocoding programs. Job assigned by autocoding program were compared with the occupation code recorded on the death certificate. RESULTS: Assignment of major occupation group had substantial agreement (Cohen's kappa > 0.7) for the two autocoding programs evaluated. Agreement of assigned code varied across race/ethnicity and occupation type. CONCLUSIONS: Autocoding programs provide an efficient method for identifying the occupation for decedents in NVDRS data. By identifying occupation, circumstances of suicide and rates of suicide can be studied across occupations.

Correction: Work-Related and Personal Factors Associated With Mental Well-Being During the COVID-19 Response: Survey of Health Care and Other Workers.

[This corrects the article DOI: 10.2196/21366.].

Risk factors associated with physician trainee concern over missed educational opportunities during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in patient volume, impacting physician trainee education due to lost clinical and didactic opportunities. We measured the prevalence of trainee concern over missed educational opportunities and investigated the risk factors leading to such concerns. METHODS: All residents and fellows at a large academic medical center were invited to participate in a web-based survey in May of 2020. Participants responded to questions regarding demographic characteristics, specialty, primary assigned responsibility during the previous 2 weeks (clinical, education, or research), perceived concern over missed educational opportunities, and burnout. Multivariable logistic regression was used to assess the relationship between missed educational opportunities and the measured variables. RESULTS: 22% (301 of 1375) of the trainees completed the survey. 47% of the participants were concerned about missed educational opportunities. Trainees assigned to education at home had 2.85 [95%CI 1.33-6.45] greater odds of being concerned over missed educational opportunities as compared with trainees performing clinical work. Trainees performing research were not similarly affected [aOR = 0.96, 95%CI (0.47-1.93)]. Trainees in pathology or radiology had 2.51 [95%CI 1.16-5.68] greater odds of concern for missed educational opportunities as compared with medicine. Trainees with greater concern over missed opportunities were more likely to be experiencing burnout (p = 0.038). CONCLUSIONS: Trainees in radiology or pathology and those assigned to education at home were more likely to be concerned about their missed educational opportunities. Residency programs should consider providing trainees with research or at home clinical opportunities as an alternative to self-study should future need for reduced clinical hours arise.

Musculoskeletal symptoms associated with workplace physical exposures estimated by a job exposure matrix and by self-report.

BACKGROUND: A job-exposure matrix (JEM) is an efficient method to assign physical workplace exposures based on job titles. JEMs offer the possibility of linking work exposures to outcome data from national health registers that contain job titles. The French CONSTANCES JEM was constructed from self-reported physical work exposures of asymptomatic workers participating in a large general population study. We validated this general population JEM by testing its ability to demonstrate exposure-outcome associations for musculoskeletal disorders (MSD) symptoms. METHODS: The CONSTANCES JEM was evaluated by assigning exposure estimates to a validation sample of new participants in the CONSTANCES study (final n = 38 730). We used weighted Kappas to compare the level of agreement between JEM-assigned and self-reported exposures across job codes for each of the 27 physical exposure variables. We computed prevalence ratios and 95% confidence intervals using Poisson regression models adjusted for age and sex for pain at six body locations associated with work exposures estimated via individual self-report and by the JEM. RESULTS: Agreement between individual self-reported and JEM-assigned exposures ranged from κ = 0.16 to 0.71; generally, the level of agreement was fair to good. We observed consistent and significant associations between pain and both self-reported and JEM-assigned exposures at all body locations. CONCLUSIONS: The CONSTANCES JEM replicated known associations between physical risk factors and prevalent MSD symptoms. Physical exposure JEMs can reduce some types of information bias, and open new avenues of research in the prevention of MSDs and other health conditions related to workplace physical activities.

Work-Related and Personal Factors Associated With Mental Well-Being During the COVID-19 Response: Survey of Health Care and Other Workers.

BACKGROUND: The response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has created an unprecedented disruption in work conditions. This study describes the mental health and well-being of workers both with and without clinical exposure to patients with coronavirus disease (COVID-19). OBJECTIVE: The aim of this study is to measure the prevalence of stress, anxiety, depression, work exhaustion, burnout, and decreased well-being among faculty and staff at a university and academic medical center during the SARS-CoV-2 pandemic and describe work-related and personal factors associated with their mental health and well-being. METHODS: All faculty, staff, and postdoctoral fellows of a university, including its medical school, were invited in April 2020 to complete an online questionnaire measuring stress, anxiety, depression, work exhaustion, burnout, and decreased well-being. We examined associations between these outcomes and factors including work in high-risk clinical settings and family/home stressors. RESULTS: There were 5550 respondents (overall response rate of 34.3%). Overall, 34% of faculty and 14% of staff (n=915) were providing clinical care, while 61% of faculty and 77% of staff were working from home. Among all workers, anxiety (prevalence ratio 1.37, 95% CI 1.09-1.73), depression (prevalence ratio 1.28, 95% CI 1.03-1.59), and high work exhaustion (prevalence ratio 1.24, 95% CI 1.13-1.36) were independently associated with community or clinical exposure to COVID-19. Poor family-supportive behaviors by supervisors were also associated with these outcomes (prevalence ratio 1.40, 95% CI 1.21-1.62; prevalence ratio 1.69, 95% CI 1.48-1.92; and prevalence ratio 1.54, 95% CI 1.44-1.64, respectively). Age <40 years and a greater number of family/home stressors were also associated with these poorer outcomes. Among the subset of clinicians, caring for patients with COVID-19 and working in high-risk clinical settings were additional risk factors. CONCLUSIONS: Our findings suggest that the pandemic has had negative effects on the mental health and well-being of both clinical and nonclinical employees. Mitigating exposure to COVID-19 and increasing supervisor support are modifiable risk factors that may protect mental health and well-being for all workers.

Association Between Reported Long Working Hours and History of Stroke in the CONSTANCES Cohort.

Background and Purpose- Long working hours (LWHs) are a potential risk factor for stroke. The aim of this study was to investigate this association in a large general population cohort. Methods- We used the French population-based cohort, CONSTANCES (Cohorte des Consultants des Centres d'Examens de Santé), to retrieve information on age, sex, smoking, and working hours from the baseline, self-administered questionnaire. Other cardiovascular risk factors and previous occurrence of stroke were taken from a parallel medical interview. We defined LWH as working time >10 hours daily for at least 50 days per year. Participants with primarily part-time jobs were excluded as were those with stroke before LWH exposure. We used logistic models to estimate the association between LWH and stroke, stratified by age, sex, and occupation. In additional modeling, we excluded subjects whose stroke occurred within 5 years of the first reported work exposure. Results- Among the 143 592 participants in the analyses, there were 1224 (0.9%) strokes, 42 542 (29.6%) reported LWH, and 14 481 (10.1%) reported LWH for 10 years or more. LWH was associated with an increased risk of stroke: adjusted odds ratio of 1.29 (95% CI, 1.11-1.49). Being exposed to LWH for 10 years or more was more strongly associated with stroke, adjusted odds ratio of 1.45 (95% CI, 1.21-1.74). The association showed no differences between men and women but was stronger in white-collar workers under 50 years of age. Conclusions- This large analysis reveals a significant association between stroke and exposure to LWH for 10 years or more. The findings are relevant for individual and global prevention.

The CONSTANCES job exposure matrix based on self-reported exposure to physical risk factors: development and evaluation.

OBJECTIVES: Job exposure matrices (JEMs) can be constructed from expert-rated assessments, direct measurement and self-reports. This paper describes the construction of a general population JEM based on self-reported physical exposures, its ability to create homogeneous exposure groups (HEG) and the use of different exposure metrics to express job-level estimates. METHODS: The JEM was constructed from physical exposure data obtained from the Cohorte des consultants des Centres d'examens de santé (CONSTANCES). Using data from 35 526 eligible participants, the JEM consisted of 27 physical risk factors from 407 job codes. We determined whether the JEM created HEG by performing non-parametric multivariate analysis of variance (NPMANOVA). We compared three exposure metrics (mean, bias-corrected mean, median) by calculating within-job and between-job variances, and by residual plots between each metric and individual reported exposure. RESULTS: NPMANOVA showed significantly higher between-job than within-job variance among the 27 risk factors (F(253,21964)=61.33, p<0.0001, r2=41.1%). The bias-corrected mean produced more favourable HEG as we observed higher between-job variance and more explained variance than either means or medians. When compared with individual reported exposures, the bias-corrected mean led to near-zero mean differences and lower variance than other exposure metrics. CONCLUSIONS: CONSTANCES JEM using self-reported data yielded HEGs, and can thus classify individual participants based on job title. The bias-corrected mean metric may better reflect the shape of the underlying exposure distribution. This JEM opens new possibilities for using unbiased exposure estimates to study the effects of workplace physical exposures on a variety of health conditions within a large general population study.

Efficiency of autocoding programs for converting job descriptors into standard occupational classification (SOC) codes.

BACKGROUND: Existing datasets often lack job exposure data. Standard Occupational Classification (SOC) codes can link work exposure data to health outcomes via a Job Exposure Matrix, but manually assigning SOC codes is laborious. We explored the utility of two SOC autocoding programs. METHODS: We entered industry and occupation descriptions from two existing cohorts into two publicly available SOC autocoding programs. SOC codes were also assigned manually by experienced coders. These SOC codes were then linked to exposures from the Occupational Information Network (O*NET). RESULTS: Agreement between the SOC codes produced by autocoding programs and those produced manually was modest at the 6-digit level, and strong at the 2-digit level. Importantly, O*NET exposure values based on SOC code assignment showed strong agreement between manual and autocoded methods. CONCLUSION: Both available autocoding programs can be useful tools for assigning SOC codes, allowing linkage of occupational exposures to data containing free-text occupation descriptors.

Modeling the Effect of the 2018 Revised ACGIH® Hand Activity Threshold Limit Value® (TLV) at Reducing Risk for Carpal Tunnel Syndrome.

Recent studies have shown the 2001 American Conference of Governmental Industrial Hygienists (ACGIH®) Threshold Limit Value (TLV®) for Hand Activity was not sufficiently protective for workers at risk of carpal tunnel syndrome (CTS). These studies led to a revision of the TLV and Action Limit. This study compares the effect of applying the 2018 TLV vs. the 2001 TLV to predict incident CTS within a large occupational pooled cohort study (n = 4,321 workers). Time from study enrollment to first occurrence of CTS was modeled using Cox proportional hazard regression. Adjusted and unadjusted hazard ratios for incident CTS were calculated using three exposure categories: below the Action Limit, between the Action Limit and TLV, and above the TLV. Workers exposed above the 2001 Action Limit demonstrated significant excess risk of carpal tunnel syndrome, while the 2018 TLV demonstrated significant excess risk only above the TLV. Of 186 total cases of CTS, 52 cases occurred among workers exposed above the 2001 TLV vs. 100 among those exposed above the 2018 value. Eliminating exposures above the 2001 TLV might have prevented 11.2% of all cases of CTS seen in our pooled cohort, vs. 25.1% of cases potentially prevented by keeping exposures below the 2018 value. The 2018 revision of the TLV better protects workers from CTS, a recognized occupational health indicator important to public health. A significant number of workers are currently exposed to forceful repetitive hand activity above these guidelines. Public health professionals should promulgate these new guidelines and encourage employers to reduce hand intensive exposures to prevent CTS and other musculoskeletal disorders.

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.

Development of a scalable weight loss intervention for low-income workers through adaptation of interactive obesity treatment approach (iOTA).

BACKGROUND: Describing how and why an evidence-based intervention is adapted for a new population and setting using a formal evaluation and an adaptation framework can inform others seeking to modify evidence-based weight management interventions for different populations or settings. The Working for You intervention was adapted, to fit a workplace environment, from Be Fit Be Well, an evidence-based intervention that targets weight-control and hypertension in patients at an outpatient clinic. Workplace-based efforts that promote diet and activity behavior change among low-income employees have potential to address the obesity epidemic. This paper aims to explicitly describe how Be Fit Be Well was adapted for this new setting and population. METHODS: To describe and understand the worksite culture, environment, and policies that support or constrain healthy eating and activity in the target population, we used qualitative and quantitative methods including key informant interviews, focus groups, and a worker survey; these data informed intervention adaptation. We organized the adaptations made to Be Fit Be Well using an adaptation framework from implementation science. RESULTS: The adapted intervention, Working for You, maintains the theoretical premise and evidence-base underpinning Be Fit Be Well. However, it was modified in terms of the means of delivery (i.e., rather than using interactive voice response, Working for You employs automated SMS text messaging), defined as a modification to context by the adaptation framework. The adaptation framework also includes modifications to content; in this case the behavioral goals were modified for the target population based on updated science related to weight loss and to target a workplace population (e.g., a goal to avoiding free food at work). CONCLUSIONS: If effective, this scalable and relatively inexpensive intervention can be translated to other work settings to reduce obesity and diabetes risk among low-SES workers, a group with a higher prevalence of these conditions. Using a formal evaluation and framework to guide and organize how and why an evidence-based intervention is adapted for a new population and setting can push the field of intervention research forward. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02934113 ; Received: October 12, 2016; Updated: November 7, 2017.

[Development of "MADE", a French Job exposure matrix for evaluation of biomechanical exposure]. / Développement d?une matrice emplois-expositions française (« MADE ¼) pour l'évaluation des contraintes biomécaniques.

OBJECTIVE: This paper presents the stages of development of an occupational biomechanical exposure matrix and preliminary reliability and validity indicators. METHODS: The expertise-based job exposure matrix, called "MADE" (for "difficult physical conditions and job matrix"), was developed from the French and international classification of jobs for 17 biomechanical exposures. Three pairs of investigators independently rate the frequency and intensity of exposure of each job from 0 to 5; discordant scores within pairs (mean difference >20% for each biomechanical exposure considered) were discussed collectively. Reliability was assessed by the difference between the initial ratings, the number of revised jobs, and the correlation between the two classifications (with transcoding). Validity was studied by correlating variables similar to those from existing United States and Danish matrices. RESULTS: The difference between the mean scores of the pairs was considered to be "fair" (less than one point). Of the 51 paired results studied (17 exposures - 3 pairs of investigators), four coefficients were found to be less than 0.6, and 14 were between 0.6 and 0.7. Forty-nine of the 1,169 job categories were reviewed. Correlation coefficients between the initial classification and transcoding were greater than 0.7. Correlation coefficients between the French, United States and Danish MEE variables were fair to good. CONCLUSION: An expertise-based job exposure matrix with fairly reliable indicators has been developed, opening up the prospects to improve certain some fields of public health, at both national and international levels.