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Factors associated with suicidal ideation in people with parkinsonism: findings from the PRIME-UK cross-sectional
Savannah Haworth1, Anahita Nodehi1, Yoav Ben-Shlomo2
1Ageing and Movement Research Group, Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol, BS8 2PS, United Kingdom.
Objective:
To assess the frequency, and factors associated with suicidal ideation (SI) in people with parkinsonism (PwP).
Background:
Both the neuropsychiatric and motor features, coupled with the incurable progression of parkinsonism, make this population at increased risk of suicide. Whilst a meta-analysis found a pooled prevalence of SI of 22%, frequency of SI and the associated factors vary significantly between studies.
Methods:
This single-centre cross-sectional questionnaire study included participants with a diagnosis of idiopathic Parkinson's Disease (PD), and other types of parkinsonism (excluding drug-induced). Participants were considered to have SI if they reported passive or active suicidal thoughts on question 9 of the Beck Depression Inventory. We present descriptive statistics and logistic regression models to estimate associations between PD symptoms, health and demographic measures, and SI.
Results:
442 participants were included (66% male, median age 75.9 years (IQR 70.7-81.4). SI was reported by 19% of participants (n = 82; 95%CI 15-22%) Factors associated with SI after adjustment for possible confounders included female sex (OR 1.89; 95%CI 1.16-3.08; p = 0.01), non-iPD parkinsonism (OR 2.70; 95%CI 1.38-5.30; p = 0.004), living in rented accommodation (OR 4.48; 95%CI 2.24-8.94; p < 0.001), higher non-motor symptom (NMS) burden (OR per 1 unit change 1.15; 95%CI 1.09-1.21; p < 0.001) and poorer quality of life (OR per 1 unit change 1.04; 95%CI 1.02-1.05; p < 0.001).
Conclusions:
We demonstrated that SI is common in this population. Female gender, non-iPD parkinsonism, higher NMS and rented accommodation were associated with increased odds of SI. Awareness of these associated factors assists clinicians in identifying individuals at higher risk.
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