Research on sickness absence has typically focussed on single diagnoses, despite increasing recognition that long-term health conditions are highly multimorbid and clusters comprising coexisting mental and physical conditions are associated with poorer clinical and functional outcomes. The digitisation of sickness certification in the UK offers an opportunity to address sickness absence in a large primary care population.

Lambeth Datanet is a primary care database which collects individual-level data on general practitioner consultations, prescriptions, Quality and Outcomes Framework diagnostic data, sickness certification (fit note receipt) and demographic information (including age, gender, self-identified ethnicity, and truncated postcode). We analysed 326 415 people's records covering a 40-month period from January 2014 to April 2017.

We found significant variation in multimorbidity by demographic variables, most notably by self-defined ethnicity. Multimorbid health conditions were associated with increased fit note receipt. Comorbid depression had the largest impact on first fit note receipt, more than any other comorbid diagnoses. Highest rates of first fit note receipt after adjustment for demographics were for comorbid epilepsy and rheumatoid arthritis (HR 4.69; 95% CI 1.73–12.68), followed by epilepsy and depression (HR 4.19; 95% CI 3.60–4.87), chronic pain and depression (HR 4.14; 95% CI 3.69–4.65), cardiac condition and depression (HR 4.08; 95% CI 3.36–4.95).

Our results show striking variation in multimorbid conditions by gender, deprivation and ethnicity, and highlight the importance of multimorbidity, in particular comorbid depression, as a leading cause of disability among working-age adults.

Many people confront potentially morally injurious experiences (PMIEs) in the course of their work which can violate deeply held moral values or beliefs, putting them at risk for psychological difficulties (e.g. post-traumatic stress disorder (PTSD), depression, etc.).

We aimed to assess the effect of moral injury on mental health outcomes.

We conducted a systematic review and meta-analysis to assess the association between work-related PMIEs and mental health disorders. Studies were independently assessed for methodological quality and potential moderator variables, including participant age, gender and PMIE factors, were also examined.

Thirteen studies were included, representing 6373 participants. PMIEs accounted for 9.4% of the variance in PTSD, 5.2% of the variance in depression and 2.0% of the variance in suicidality. PMIEs were associated with more symptoms of anxiety and behavioural problems (e.g. hostility), although this relationship was not consistently significant. Moderator analyses indicated that methodological factors (e.g. PMIE measurement tool), demographic characteristics and PMIE variables (e.g. military v. non-military context) did not affect the association between a PMIE and mental health outcomes.

Most studies examined occupational PMIEs in military samples and additional studies investigating the effect of PMIEs on civilians are needed. Given the limited number of high-quality studies available, only tentative conclusions about the association between exposure to PMIEs and mental health disorders can be made.

None.