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Factors associated with sickness absence in a large NHS Trust

Research output: Contribution to journalArticlepeer-review

P. Grime, D. M. McElvenny, I. Madan

Original languageEnglish
Pages (from-to)467-472
Number of pages6
JournalOccupational medicine (Oxford, England)
Issue number9
Published24 Dec 2021

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Publisher Copyright: © The Author(s) 2021. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email:

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BACKGROUND: Sickness absence rates vary widely across a large acute NHS Trust, with the highest rates in some of the largest directorates. AIMS: This study was aimed to identify factors associated with sickness absence in teams and to inform interventions to improve staff health and well-being. METHODS: Using 2018 data from the electronic staff record and NHS Staff Survey, we examined variables associated with cost centre sickness absence rates, perceived abuse and staff engagement scores using multivariable linear regression. RESULTS: Data were available for 9362/15 423 (61%) of staff. Cost centre sickness absence was significantly positively associated with predominance of nursing and midwifery staff (β = 0.28 [0.012-0.55]) and significantly inversely associated with predominance of medical and dental staff (β = -0.94 [-1.2 to -0.65]) and proportion white (β = -1.11 [-1.9 to -0.37]). Cost centre sickness absence was not significantly associated with staff engagement, reported abuse, age or higher headcount. Cost centre staff engagement was significantly positively associated with proportion white (β = 0.98 [0.42-1.6]). Reported abuse by managers (β = -13 [-22 to -4.2]) and by colleagues (β = -24 [-35 to -12]) was significantly inversely associated with proportion white. Reported abuse by colleagues was significantly associated with predominance of medical and dental (β = 7.6 [2.3-13]) and nursing and midwifery staff (β = 9.1 [4.4-14]). CONCLUSIONS: These observed associations of sickness absence, staff engagement and perceived abuse with job mix and ethnicity should be further explored. Individual or team-level data, rather than cost centre-level data, might more meaningfully elucidate why sickness absence rates vary between groups of staff.

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