Literature DB >> 26503980

Data warehouse for detection of occupational diseases in OHS data.

L Godderis1, G Mylle2, M Coene2, C Verbeek2, B Viaene2, S Bulterys2, M Schouteden2.   

Abstract

BACKGROUND: Occupational health and safety (OHS) services collect a wide range of data during health surveillance. AIMS: To build a 'data warehouse' to make OHS data available for research and to investigate sector-specific health problems.
METHODS: Medical data were extracted, transformed and loaded into the data warehouse. After validation, data on lifestyle, categorized medication use, ICD-9-CM encoded sickness absences and health complaints, collected between 2010 and 2014, were analysed with logistic regression to compare proportions between employment sectors, taking into account age, gender, body mass index (BMI) and year of examination.
RESULTS: The data set comprised 585000 employees. Average age and employment seniority were 39 ± 12 and 8 ± 9 years, respectively. BMI was 26 ± 5 kg/m(2). Health complaints, medication use and sickness absence significantly increased with BMI and age. The proportion of employees with health problems was highest in health care (64%), government (61%) and manufacturing (60%) and lowest in the service sector. In all sectors, 10% of workers reported locomotor health problems, apart from the service sector (8%) with similar results for medication consumption. Neuropsychological drugs were more frequently used by health care workers (8%). The transport sector contained the highest proportion of cardiological medication users (12%). Finally, 30-59% of employees reported at least one sickness absence episode. Sickness absence due to locomotor issues was highest in manufacturing (11%) and health care (10%), followed by government (9%) and construction (9%).
CONCLUSIONS: Significant differences in indices of workers' health were observed between sectors. This information is now being used in the implementation of a sector-oriented health surveillance programme.
© The Author 2015. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Data collection; information storage and retrieval; occupational diseases; occupational health services; population surveillance; public health.

Mesh:

Year:  2015        PMID: 26503980     DOI: 10.1093/occmed/kqv074

Source DB:  PubMed          Journal:  Occup Med (Lond)        ISSN: 0962-7480            Impact factor:   1.611


  5 in total

1.  The long-term effect of job mobility on workers' mental health: a propensity score analysis.

Authors:  Lode Godderis; Domenica Matranga; Laura Maniscalco; Martijn Schouteden; Jan Boon; Sofie Vandenbroeck; Ingrid Sivesind Mehlum
Journal:  BMC Public Health       Date:  2022-06-08       Impact factor: 4.135

2.  Associations between common diseases and work ability and sick leave among health care workers.

Authors:  Sophie van den Berg; Alex Burdorf; Suzan J W Robroek
Journal:  Int Arch Occup Environ Health       Date:  2017-05-26       Impact factor: 3.015

3.  Incidence of ill-health related job loss and related social and occupational factors. The "unfit for the job" study: a one-year follow-up study of 51,132 workers.

Authors:  Francois-Xavier Lesage; Frederic Dutheil; Lode Godderis; Aymeric Divies; Guillaume Choron
Journal:  PeerJ       Date:  2018-06-19       Impact factor: 2.984

4.  Prevalence of high cardiovascular risk by economic sector.

Authors:  Godelieve J M Vandersmissen; M Schouteden; C Verbeek; S Bulterys; L Godderis
Journal:  Int Arch Occup Environ Health       Date:  2019-07-15       Impact factor: 3.015

5.  The Impact of a Change in Employment on Three Work-Related Diseases: A Retrospective Longitudinal Study of 10,530 Belgian Employees.

Authors:  Laura Maniscalco; Martijn Schouteden; Jan Boon; Domenica Matranga; Lode Godderis
Journal:  Int J Environ Res Public Health       Date:  2020-10-14       Impact factor: 3.390

  5 in total

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