General Psychiatry最新文献

Background: There is limited evidence suggesting that osteoporosis might exacerbate depressive symptoms, while more studies demonstrate that depression negatively affects bone density and increases fracture risk.

Aims: To explore the relationship between major depressive disorder (MDD) and fracture risk.

Methods: We conducted a nested case-control analysis (32 670 patients with fracture and 397 017 individuals without fracture) and a matched cohort analysis (16 496 patients with MDD and 435 492 individuals without MDD) in the same prospective UK Biobank data set. Further, we investigated the shared genetic architecture between MDD and fracture with linkage disequilibrium score regression and the MiXeR statistical tools. We used the conditional/conjunctional false discovery rate approach to identify the specific shared loci. We calculated the weighted genetic risk score for individuals in the UK Biobank and logistic regression was used to confirm the association observed in the prospective study.

Results: We found that MDD was associated with a 14% increase in fracture risk (hazard ratio (HR) 1.14, 95% CI 1.14 to 1.15, p<0.001) in the nested case-control analysis, while fracture was associated with a 72% increase in MDD risk (HR 1.72, 95% CI 1.64 to 1.79, p<0.001) in the matched cohort analysis, suggesting a longitudinal and bidirectional relationship. Further, genetic summary data suggested a genetic overlap between MDD and fracture. Specifically, we identified four shared genomic loci, with the top signal (rs7554101) near SGIP1. The protein encoded by SGIP1 is involved in cannabinoid receptor type 1 signalling. We found that genetically predicted MDD was associated with a higher risk of fracture and vice versa. In addition, we found that the higher expression level of SGIP1 in the spinal cord and muscle was associated with an increased risk of fracture and MDD.

Conclusions: The genetic pleiotropy between MDD and fracture highlights the bidirectional association observed in the epidemiological analysis. The shared genetic components (such as SGIP1) between the diseases suggest that modulating the endocannabinoid system could be a potential therapeutic strategy for both MDD and bone loss.

Background: Growing evidence attests to the efficacy of mindfulness-based interventions (MBIs), but their effectiveness for healthcare workers remains uncertain.

Aims: To evaluate the evidence for MBIs in improving healthcare workers' psychological well-being.

Methods: A systematic literature search was conducted on Medline, Embase, Cumulative Index for Nursing and Allied Health Literature, PsycINFO and Cochrane Central Register of Controlled Trials up to 31 August 2022 using the keywords 'healthcare worker', 'doctor', 'nurse', 'allied health', 'mindfulness', 'wellness', 'workshop' and 'program'. Randomised controlled trials with a defined MBI focusing on healthcare workers and quantitative outcome measures related to subjective or psychological well-being were eligible for inclusion. R V.4.0.3 was used for data analysis, with the standardised mean difference as the primary outcome, employing DerSimonian and Laird's random effects model. Grading of Recommendations, Assessment, Development and Evaluation framework was used to evaluate the quality of evidence. Cochrane's Risk of Bias 2 tool was used to assess the risk of bias in the included studies.

Results: A total of 27 studies with 2506 participants were included, mostly from the USA, involving various healthcare professions. MBIs such as stress reduction programmes, apps, meditation and training showed small to large effects on anxiety, burnout, stress, depression, psychological distress and job strain outcomes of the participants. Positive effects were also seen in self-compassion, empathy, mindfulness and well-being. However, long-term outcomes (1 month or longer postintervention) varied, and the effects were not consistently sustained.

Conclusions: MBIs offer short-term benefits in reducing stress-related symptoms in healthcare workers. The review also highlights limitations such as intervention heterogeneity, reduced power in specific subgroup analyses and variable study quality.

Prospero registration number: CRD42022353340.