Constructing and validating an Occupational Mechanical Job Exposure Index based on five Norwegian nationwide Surveys of Living Conditions on work environment

Abstract

Background The overall aim of this study was to examine essential aspects of reliability and validity of a constructed Occupational Mechanical Job Exposure Index for use in analyses of Norwegian register data. Methods We utilized data from the Norwegian nationwide Survey of Living Conditions on work environment in 2006, 2009, 2013, 2016 and 2019. Occupations were classified on a 4-digit level based on the Norwegian version of the International Standard Classification of Occupations (ISCO-88). We constructed a 4-digit correspondence table between the occupational codes used in the 2006 and 2009 surveys (STYRK-98) and the codes used in 2013, 2016 and 2019 (STYRK-08). The mechanical exposures were collected by Statistics Norway using telephone interviews. As for reliability, we examined the agreement between the individual- and the occupational-based mechanical exposures using Cohen’s kappa, sensitivity and specificity measures. Construct, concurrent and predictive validity pertaining to the Occupational Mechanical Job Exposure Index were analysed using both survey data and nationwide register data. Results The analysis shows a fair-to-moderate overlap between occupational-based mechanical exposures and the individually reported exposures. Construct validity of the Occupational Mechanical Job Exposure Index, as estimated by a confirmatory factor analysis using the occupational-based mechanical exposures, showed that the 8 exposures formed one underlying factor. When assessing the concurrent value of the Occupational Mechanical Job Exposure Index to the index based on the individual reported exposures, the occupational mechanical index showed lower and reproducible associations with lower back pain for both men and women. For long-term sick leave, the occupational mechanical index showed higher and reproducible associations for both genders. As for predictive validity, the register data analysis shows that the occupational mechanical index was associated with disability and a higher number of long-term sickness benefits periods for both men and women. For men the index also predicted higher mortality. Conclusion Our tests of reliability and validity of the Occupational Mechanical Job Exposure Index indicate that the index overall has acceptable statistical properties and will be useful in analyses of Norwegian register data where individual information on these types of exposures is missing.

Return to work after cancer–the impact of working conditions: A Norwegian Register-based Study.

“…Working conditions were measured by using the Occupational Mechanical Job Exposure Index and Occupational Job Strain Index, which were constructed and validated for use in register-based research [17,18]. The two job exposure indices were based on ve Norwegian nationwide surveys of living conditions concerning work environment in 2006, 2009, 2013, 2016, and 2019.…”

“…The strain index also theoretically ranges from 0 to 100 percent, where higher values on the index represent higher degrees of demand and lower degrees of control. For a more detailed description of the mechanical index, see Hermansen and Dahl (2022) [17]. See Le Hermansen, and Dahl (2023) [18] for a description of the job strain index.…”

“…Third, the study applied job exposure matrices, which allow us to investigate the role of working conditions on RTW after cancer based on register data. The two matrices have been validated and found to be reproducible and e cient tools for use in evaluating the mechanical and psychosocial work environment in Norwegian data [17,18]. Nonetheless, it is important to note that JEMs cannot be seen as a gold standard measure for job exposure [66, 67], as the method entails the risk of errors in JEM assignments [68] and the risk of differential misclassi cation [66].…”

“…To do so, we analyze longitudinal register data on the entire Norwegian population. The novel contribution of this study is the use of two job exposure matrices (JEMs) that re ect occupation-based mechanical (or physical) and psychosocial job exposure, respectively [17,18]. As indicated above, this approach allows us to explore whether hazardous working conditions play a role in RTW after cancer diagnosis while also taking into account sociodemographic and socioeconomic factors.…”

Sickness absence among mothers caring for a child with disability: Examining the impact of mechanical and psychosocial occupational exposures

“…In this paper, we will focus on mechanical and psychosocial exposures. Mechanical job exposures include heavy lifting and physical labour associated with musculoskeletal disorder ( Hermansen & Dahl, 2022 ), while psychosocial job exposures may be best exemplified by the aspects of Karasek’s (1979) model: psychological demands, decision latitude, and social support. Female-dominated occupations, such as shop salespersons and other sales personnel, nurses, nursing and care assistant, cleaners, and waitresses, are examples of professions that fall under both high mechanical and psychosocial exposures.…”