Comparison Between a Job-Exposure Matrix (JEM) Score and Self-Reported Exposures for Carrying Heavy Loads Over the Working Lifetime in the CONSTANCES Cohort

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.

Flexibility of a large blindly synthetized avatar database for occupational research: Example from the CONSTANCES cohort for stroke and knee pain

OBJECTIVES

Though the rise of big data in the field of occupational health offers new opportunities especially for cross-cutting research, they raise the issue of privacy and security of data, especially when linking sensitive data from the field of insurance, occupational health or compensation claims. We aimed to validate a large, blinded synthesized database developed from the CONSTANCES cohort by comparing associations between three independently selected outcomes, and various exposures.

METHODS

From the CONSTANCES cohort, a large synthetic dataset was constructed using the avatar method (Octopize) that is agnostic to the data primary or secondary data uses. Three main analyses of interest were chosen to compare associations between the raw and avatar dataset: risk of stroke (any stroke, and subtypes of stroke), risk of knee pain and limitations associated with knee pain. Logistic models were computed, and a qualitative comparison of paired odds ratio (OR) was made.

RESULTS

Both raw and avatar datasets included 162,434 observations and 19 relevant variables. On the 172 paired raw/avatar OR that were computed, including stratified analyses on sex, more than 77% of the comparisons had a OR difference ≤0.5 and less than 7% had a discrepancy in the statistical significance of the associations, with a Cohen's Kappa coefficient of 0.80.

CONCLUSIONS

This study shows the flexibility and the multiple usage of a synthetic database created with the avatar method in the particular field of occupational health, which can be shared in open access without risking re-identification and privacy issues and help bring new insights for complex phenomenon like return to work.

How to Use Biomechanical Job Exposure Matrices with Job History to Access Work Exposure for Musculoskeletal Disorders? Application of Mathematical Modeling in Severe Knee Pain in the Constances Cohort

INTRODUCTION

Musculoskeletal disorders related to work might be caused by the cumulative effect of occupational exposures during working life. We aimed to develop a new model which allows to compare the accuracy of duration of work and intensity/frequency associations in application to severe knee pain.

METHODS

From the CONSTANCES cohort, 62,620 subjects who were working at inclusion and coded were included in the study. The biomechanical job exposure matrix "JEM Constances" was used to assess the intensity/frequency of heavy lifting and kneeling/squatting at work together with work history to characterize the association between occupational exposure and severe knee pain. An innovative model G was developed and evaluated, allowing to compare the accuracy of duration of work and intensity/frequency associations.

RESULTS

The mean age was 49 years at inception with 46 percent of women. The G model developed was slightly better than regular models. Among the men subgroup, odds ratios of the highest quartile for the duration and low intensity were not significant for both exposures, whereas intensity/duration were for every duration. Results in women were less interpretable.

CONCLUSIONS

Though higher duration increased strength of association with severe knee pain, intensity/frequency were important predictors among men. Exposure estimation along working history should have emphasis on such parameters, though other outcomes should be studied and have a focus on women.

Influence of low back pain characteristics on the healthcare procedures prescribed by general practitioners for adult patients: ancillary analysis of the French ECOGEN study

BACKGROUND

Non-specific low back pain is a frequent reason for consultation, yet little is known about how general practitioners manage it in France.

OBJECTIVES

To describe the healthcare procedures general practitioners prescribe for low back pain in France.

MATERIALS AND METHODS

This is an ancillary analysis of an observational, cross-sectional study (ECOGEN) conducted between November 2011 and April 2012 among 128 general practitioners. Adults younger than 65 years consulting for low back pain were included. Patient and general practitioner characteristics, consultation results (diagnosis) and healthcare procedures were collected and coded using the International Classification in Primary Care. Analyses focused on the initial or follow-up consultation, adjusting on age, gender, and socio-occupational category.

RESULTS AND DISCUSSION

Out of 11510 consultations, 845 (7.3%) were for low back pain. Of these, 776 (79.5%) resulted in a clinical examination, 634 (73.4%) in medication prescription, and 203 (23.9%) were prescribed sick leave, but imaging and specialist referral were rare. Imaging was more frequent with radiating pain (adjusted odds ratio (aOR) = 1.61; 95% CI [1.07, 2.42]), as were specialist referrals (OR = 2.92; 95% CI [1.40, 6.09]) and sick leave prescription (aOR = 1.52; 95% CI [1.10, 2.09]), but physiotherapist referral was less frequent (aOR = 0.55; 95% CI [0.38, 0.82]). Clinical examinations (aOR = 2.75; 95% CI [1.98, 3.80]), imaging (aOR = 1.61; 95% CI [1.02, 2.31]) and medication prescriptions (aOR = 2.34; 95% CI [1.65, 3.30]) were more common in initial consultations, but specialist referral (aOR = 0.16; 95% CI [0.05, 0.47]) or sick leave prescription (aOR = 0.68; 95% CI [0.48, 0.97]) were rarer.

CONCLUSION

Low back pain characteristics could influence healthcare procedures more markedly than patient or general practitioner characteristics.

Observed vs. self-reported agricultural activities: Evaluating 24-hr recall in a pilot study

Few studies have evaluated the validity of self-report of work activities because of challenges in obtaining objective measures. In this study, farmers' recall of the previous day's agricultural activities was compared to activities observed by field staff during air monitoring. Recall was assessed in 32 farmers from the Biomarkers of Exposure and Effect in Agriculture Study, a subset of a prospective cohort study. The farmers participated in 56 visits that comprised air monitoring the day before an interview. The answers for 14 agricultural activities were compared to activities observed by field staff during air monitoring (median duration 380 min, range 129-486). For each task, evaluated as yes/no, overall agreement, sensitivity, specificity, and kappa were calculated. Median prevalence of the 14 activities was 8% from observation and 13% from participants (range: 2-54%). Agreement was generally good to perfect, with a median overall agreement of 95% (range: 89-100%), median sensitivity of 84% (50-100%), median specificity of 95% (88-100%), and median kappa of 0.65 (0.31-1.0). Reasons for disagreement included activities occurring when the field staff was not present (i.e., milking cows), unclear timing notes that made it difficult to determine whether the activity occurred the day of and/or day before the interview, definition issues (i.e., participant included hauling in the definition of harvesting), and difficulty in observing details of an activity (i.e., whether hay was moldy). This study provides support for accurate participant recall the day after activities.