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Occupation as a Proxy for Job Exposures? Routine Data Analysis Using the Example of Rehabilitation
Martin Brünger1, Sebastian Bernert1, Karla Spyra1
1Institute of Medical Sociology and Rehabilitation Science, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany.
Aim Of The Study:
Job exposures are associated with health-related outcomes including sick leave and reduction in earning capacity. Rehabilitation of persons in working age aims primarily to secure or restore work capacity. Information concerning job exposures is, however, not directly available in routine data of healthcare payers. Since exposures relate to specific occupations and the current occupation is part of routine data, job exposures may be determined indirectly via job-exposure matrices (JEM). The aim of the study is to describe the possibilities and challenges of the representation of job exposures by the occupation according to routine data using the example of rehabilitation.
Methods:
The Scientific Use File 'SUFRSDLV15B' of the German Pension Insurance was analysed. We used data from n=1 242 171 persons in work with at least one completed medical rehabilitation between 2008 and 2015 (dataset 1). The occupation is coded according to KldB 88 or KldB 2010 (German Classification of Occupations). In addition, data from a nationwide survey with 2530 rehabilitation patients was available (dataset 2). Job exposures are operationalized by the Job Exposure Index via JEM. The relationship to the return-to-work prognosis at the end of rehabilitation (dataset 1) and to patient reported outcome measures (dataset 2) is described.
Results:
Information concerning the occupation is available for about 91% of rehabilitation measures of employed patients for the year prior to rehabilitation. At high levels of job exposures, the proportion of persons with a predicted working capacity in the last job of fewer than 3 h per day increased by a factor of 4 compared to low-level job exposures (23.5 vs. 6.1%). On the other hand, there is a low association only to reduced working capacity in the general labour market (2.9 vs. 2.4%). High-level job exposures are associated with self-reported, work-related impairments.
Conclusion:
The Job Exposure Index may offer a valid approach to depict occupation-related exposures. The index can be used in the analysis of routine data of the pension insurance and other social security funds, as well as in the linkage of individual assessment data with routine data containing the occupation, without any additional data collection effort. Due to its construction based on job classifications, it will not replace the assessment of individual burdens.
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