Data warehouse for detection of occupational diseases in OHS data

Godderis, Lode; Mylle, Godewina; Coene, Matthias; Verbeek, Chris; Viaene, B; Bulterys, Simon; Schouteden, Martijn

doi:10.1093/occmed/kqv074

Cited by 15 publications

(12 citation statements)

References 28 publications

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“…A Spanish study using data from the Surveillance System for Nontransmissible Diseases Risk Factors (SIV-FRENT) for the Madrid region found that drivers accumulated more than two cardiovascular risk factors more often than other occupations (Zimmermann Verdejo et al 2010). An analysis of data from our data warehouse on health complaints, medication, and sickness absence by economic sector between 2010 and 2014 revealed that transport and storage were the top two for cardiovascular health problems and cardiovascular medication (Godderis et al 2015). One reason for these findings could be the sedentary aspect of driving that may attract an older and less active population.…”

Section: Discussionmentioning

confidence: 99%

“…In 2018, 222 occupational health nurses and 179 occupational physicians from IDEWE performed medical examinations and recorded data in the workers' electronic medical files. The data stored in the electronic medical files were loaded into a data warehouse described by Godderis et al, according to Belgian and international privacy and ethical legislation, allowing post hoc analysis of anonymised data (Godderis et al 2015).…”

Section: Methodsmentioning

confidence: 99%

“…The statistical Classification of Economic Activities in the European Community or Nomenclature statistique des Activités économiques dans la Communauté Européenne (NACE) was used to characterise the economic sector in which the worker was employed. For the analysis, the NACE codes were regrouped in main categories as described by Godderis et al (2015).…”

Section: Methodsmentioning

confidence: 99%

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Prevalence of high cardiovascular risk by economic sector

Vandersmissen

Schouteden

Verbeek

et al. 2019

Int Arch Occup Environ Health

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Purpose The aim of this study was to assess the prevalence of high cardiovascular risk and the trend of cardiovascular risk factors in a large sample of Belgian workers. Methods A cross-sectional study was performed on the data of workers under medical surveillance by the non-profit occupational health service IDEWE in 2018. The prevalence of poor health for smoking, physical activity, body mass index (BMI), and blood pressure according to the American Heart Association (AHA) definition was investigated. The presence of three or more poor cardiovascular health metrics was considered high cardiovascular risk. A log-binomial regression model was used to compare the prevalence of high cardiovascular risk between economic sectors taking into account age and gender and to calculate predicted probabilities of high cardiovascular risk. Results Data about 212,792 workers were available. In 2018, overall, 7% of workers had high cardiovascular risk. Transport and construction had the highest prevalence of high cardiovascular risk, 14% and 12%, respectively. The lowest prevalence, 3%, was observed in education. Differences between sectors remained statistically significant after adjustment for age and gender. In men, workers in transport and storage and in construction had the highest predicted probability of high cardiovascular risk that increased with age. In women, highest predicted probability was observed in transport and storage. Conclusions When implementing health promotion initiatives, priority should be given to sectors and professions where risk factors are most prevalent or are increasing rapidly. Measures should be tailored to the special needs of the occupational groups at high risk.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Prevalence of high cardiovascular risk by economic sector

Vandersmissen

Schouteden

Verbeek

et al. 2019

Int Arch Occup Environ Health

Self Cite

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“…In the European Union, 46% of people within the labour market reported to have work limitations due to health problems (Eurostat 2015 ). Within the health care sector, a particular large proportion of over 60% of the employees was found to have health problems (Godderis et al 2015 ). Musculoskeletal diseases (MSD), cardiovascular diseases (CVD), mental disorders (MD), and respiratory diseases (RD) have been identified as important causes of sick leave (Ferrie et al 2009 ; Vahtera et al 2010 ).…”

Section: Introductionmentioning

confidence: 99%

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

Berg¹,

Burdorf²,

Robroek³

2017

Int Arch Occup Environ Health

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PurposeThis study investigates whether common diseases, i.e., musculoskeletal diseases (MSD), cardiovascular diseases (CVD), mental disorders (MD), and respiratory diseases (RD), influence work ability and sick leave and whether lifestyle-related factors, and psychosocial and physical work-related factors are associated with low work ability and sick leave.MethodsIn a cross-sectional study among 8364 Dutch health care employees, self-reported information was acquired concerning common diseases, lifestyle-related factors, psychosocial and physical work-related factors, work ability, and sick leave. Logistic regression analyses were performed to describe the associations between common diseases with low work ability and sick leave, and to evaluate differences in associations between lifestyle-related and work-related factors with low work ability and sick leave among healthy employees and employees with common diseases.ResultsEmployees with MD (OR 6.35), CVD (OR 2.63), MSD (OR 2.62), and RD (OR 2.11) had a higher risk of low work ability compared to healthy employees. Workers with common diseases also reported more often sick leave (ORs > 1.60), in particular long-term sick leave (>25 days). Multimorbidity increased both the occurrence of low work ability and sick leave. Unfavourable psychosocial work-related factors were associated with low work ability and sick leave regardless of health status. Physical work-related factors and lifestyle factors were less consistently associated with low work ability and sick leave.ConclusionsCommon diseases, and foremost mental disorders, were related to both low work ability and sick leave. To maintain or improve work ability and prevent sick leave, interventions that promote a healthy psychosocial work environment are needed.

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“…OHS are indeed complex to evaluate and present many scientific challenges for researchers: benefits are often preventative and therefore more difficult to observe (or only in the long run), have a multidimensional and interacting nature (eg, better workers’ health has a range of economic knock-on effects, for instance reduced staff turnover), involve several ‘intangible’ benefits (eg, an improved reputation), and large datasets are usually required 12. Moreover, strong study designs that minimise confounding are often difficult to implement in practice.…”

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confidence: 99%