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Original article
The CONSTANCES job exposure matrix based on self-reported exposure to physical risk factors: development and evaluation
  1. Bradley A Evanoff1,
  2. Marcus Yung1,
  3. Skye Buckner-Petty1,
  4. Johan Hviid Andersen2,
  5. Yves Roquelaure3,
  6. Alexis Descatha3,4,5,
  7. Ann Marie Dale1
  1. 1 Division of General Medical Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
  2. 2 Department of Occupational Medicine, Danish Ramazzini Centre, Regional Hospital West Jutland, University Research Clinic, Herning, Denmark
  3. 3 INSERM, U1085, IRSET (Institute de recherché en santé, environnement et travail), ESTER Team, University of Angers, Angers, France
  4. 4 AP-HP, EMS (Samu92), Occupational Health Unit, Raymond Poincaré University Hospital, Garches, France
  5. 5 INSERM, UMR 1168 UMS011, University of Versailles Saint-Quentin-en-Yvelines, Villejuif, France
  1. Correspondence to Dr Bradley A Evanoff, Division of General Medical Sciences, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA; bevanoff{at}


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.

  • ergonomics
  • exposure assessment
  • occupational biomechanical exposure
  • musculoskeletal disorders

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  • AD and AMD contributed equally.

  • Contributors BAE, AD, YR and AMD designed the study, obtained funding, and reviewed and edited the paper. MY and BAE made significant contributions to the data visualisation, writing and formatting of this manuscript. SP-B was the primary data analyst and made significant contributions to the visualisations. JHA made significant contributions to the conceptualisation, and reviewed and edited the paper.

  • Funding This study was supported by research funding from the American National Institute for Occupational Safety and Health (NIOSH R01OH011076). The French CONSTANCES cohort is supported by the French National Research Agency (ANR-11-INBS-0002), Caisse Nationale d’Assurance Maladie des travailleurs salariés-CNAMTS, and is funded by the Institut de Recherche en Santé Publique/Institut Thématique Santé Publique, and the following sponsors: Ministère de la santé et des sports, Ministère délégué à la recherche, Institut national de la santé et de la recherche médicale, Institut national du cancer et Caisse nationale de solidarité pour l’autonomie, as well as Institute for research in public health (IReSP, CapaciT project).

  • Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute for Occupational Safety and Health (NIOSH), nor the sponsors of the CONSTANCES project.

  • Competing interests None declared.

  • Ethics approval Washington University in St Louis, USA.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Patient consent for publication Not required.

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