Edinburgh Napier University

About: Edinburgh Napier University is a education organization based out in Edinburgh, United Kingdom. It is known for research contribution in the topics: Population & Health care. The organization has 2665 authors who have published 6859 publications receiving 175272 citations.

Risk factors and comorbidity of ICD‐11 PTSD and complex PTSD: Findings from a trauma‐exposed population based sample of adults in the United Kingdom

Abstract: BACKGROUND: Following the recently published 11th version of the WHO International Classification of Diseases (ICD-11), we sought to examine the risk factors and comorbidities associated with posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD). METHOD: Cross-sectional and retrospective design. The sample consisted of 1,051 trauma-exposed participants from a nationally representative panel of the UK adult population. RESULTS: A total of 5.3% (95% confidence interval [CI] = 4.0-6.7%) met the diagnostic criteria for PTSD and 12.9% (95% CI = 10.9-15.0%) for CPTSD. Diagnosis of PTSD was independently associated with being female, being in a relationship, and the recency of traumatic exposure. CPTSD was independently associated with younger age, interpersonal trauma in childhood, and interpersonal trauma in adulthood. Growing up in an urban environment was associated with the diagnosis of PTSD and CPTSD. High rates of physical and mental health comorbidity were observed for PTSD and CPTSD. Those with CPTSD were more likely to endorse symptoms reflecting major depressive disorder (odds ratio [OR] = 21.85, 95 CI = 12.51-38.04) and generalized anxiety disorder (OR = 24.63, 95 CI = 14.77-41.07). Presence of PTSD (OR = 3.13, 95 CI = 1.81-5.41) and CPTSD (OR = 3.43, 95 CI = 2.37-4.70) increased the likelihood of suicidality by more than three times. Nearly half the participants with PTSD and CPTSD reported the presence of a chronic illness. CONCLUSIONS: CPTSD is a more common, comorbid, debilitating condition compared to PTSD. Further research is now required to identify effective interventions for its treatment.

Spatial mixture relative risk models applied to disease mapping.

Abstract: An important issue within health services research is the correct allocation of resources within health authority regions and the capability of public health professionals to make such allocation appropriately. This allocation is often based on a mapping of relevant disease incidence and the assessment of the geographical distribution of relative risk of disease in small areas within the health authority administrative domain. Existing methods for the statistical analysis of small area risk are mostly based on smoothing methods. However, these methods often smooth over large discontinuities in the risk surface which might be important to maintain for the purposes of resource allocation. In this paper we propose a method that involves the use of spatial mixtures of components that can provide a balance between smoothness and the maintenance of discontinuity. The method is applied to a sudden infant death incidence data set.