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dc.contributor.author | Whyte, Carmen J.![]() |
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dc.contributor.author | Basu, Debashis![]() |
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dc.contributor.author | Kocks, Daniel![]() |
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dc.contributor.author | Martins, Johanna E.![]() |
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dc.date.accessioned | 2022-12-08T09:53:24Z | |
dc.date.available | 2022-12-08T09:53:24Z | |
dc.date.issued | 2021-09 | |
dc.description.abstract | BACKGROUND : The health workforce is key to service delivery and forms part of the World Health Organization’s six building blocks for health systems. It is therefore important to prioritise the health and wellbeing of healthcare workers (HCWs) to maintain their productivity. OBJECTIVE : We assessed the association of risk factors for cardiometabolic diseases, such as hypertension, diabetes, and obesity on sickness absence in HCWs, using routine medical surveillance records. METHODOLOGY : Six hundred HCWs’ health records were randomly selected from the occupational health clinic at two hospitals in Gauteng province, from 1 April to 30 June 2019. Backward stepwise logistic regression was used to assess the relationships between risk factors for cardiometabolic diseases, including body mass index (BMI), blood pressure, smoking, alcohol intake, regular exercise, and sickness absence. RESULTS : Four hundred and fifty records (75.0%) were for female HCWs. The overall median age was 37 years (IQR 30–47 years). Most HCWs were nurses (n = 290, 48.3%), followed by service workers (n = 124, 20.7%). Males had lower odds of sickness absence than females (AOR = 0.61; 95% CI 0.40, 0.94; p = 0.024). Compared to HCWs aged 30 years or younger, those aged 31 to 50 years and older than 50 years had significantly higher odds of sickness absence (AOR = 1.87; 95% CI 1.23–2.86; p = 0.004, and AOR = 2.25; 95% CI 1.30–3.89; p = 0.004). For each increasing unit of BMI, the odds of sickness absence increased by 3% (AOR = 1.03; 95% CI 1.00–1.06; p = 0.023). CONCLUSION : The presence of risk factors for cardiometabolic diseases and their association with productivity (measured as sick leave) highlight the importance of assessing lifestyle risk factors during medical surveillance for healthcare workers. | en_US |
dc.description.department | Occupational Therapy | en_US |
dc.description.librarian | am2022 | en_US |
dc.description.uri | http://www.occhealth.co.za | en_US |
dc.identifier.citation | Whyte, C.J., Basu, D., Kocks, D. & Martins, J.E. 2021, 'Factors associated with sickness absence in healthcare workers in two public sector hospitals in Gauteng province, South Africa', Occupational Health Southern Africa, vol. 27, no. 5, pp. 172-176. | en_US |
dc.identifier.issn | 1024-6274 (print) | |
dc.identifier.issn | 2226-6097 (online) | |
dc.identifier.uri | https://repository.up.ac.za/handle/2263/88712 | |
dc.language.iso | en | en_US |
dc.publisher | South African Society of Occupational Medicine | en_US |
dc.rights | South African Society of Occupational Medicine (SASOM) | en_US |
dc.subject | Blood pressure | en_US |
dc.subject | Glucose | en_US |
dc.subject | Exercise | en_US |
dc.subject | Sick leave | en_US |
dc.subject | Body mass index (BMI) | en_US |
dc.subject | Healthcare workers (HCW) | en_US |
dc.title | Factors associated with sickness absence in healthcare workers in two public sector hospitals in Gauteng province, South Africa | en_US |
dc.type | Article | en_US |