Background & Aims
Nearly half of UK adults report pain lasting longer than three months (chronic pain).[1,2] While most people manage well, around 11% of the population have pain that has far-reaching, negative impacts on their lives, leading to disability, distress, social isolation, and high healthcare needs.[3] There is a gap in evidence regarding potential causes affecting long-term transitions in high impact CP. This interdisciplinary programme of research aims to inform prevention, selfcare and treatment options for high impact CP. Specific objectives are to
1.Use clustering methods to identify and describe high impact CP presentations
2.Use causal inference methods to investigate the role of (a) cognitive and affective factors, and (b) social factors and traumatic experiences in explaining transitions
3.Identify potential targets for prevention and treatment, and estimate expected benefit from individual or population level intervention.
This abstract will focus on the 2nd objective.
Methods
The project uses data from UK Biobank (UKB) which includes health information from nearly 500,000 people aged 40-69 years at baseline (2006-2010).[4] The analysis will focus on the most common presentations of CP, including back pain, joint pain, and widespread pain. The presence of CP was assessed at inclusion. A detailed CP survey (completed by 167,184 participants in 2019, to be repeated in 2024) is used to assess CP impact (BPI and EQ-5D-5L).
Public involvement is integral at every stage. People with lived experience of CP are represented on the study team, and a larger panel has contributed to defining research questions. They shared their life stories, and suggested factors that may explain changes in high impact CP over time. Hypothesised causal pathways are visualised in Directed Acyclic Graphs (DAGs, [5]) to inform causal inference models.[6] We expect CP pathways to be moderated by sociodemographic factors (age, gender, deprivation), general health, and treatment of CP.
Results
Based on previous evidence, workshops conducted with our patient panel, and research expert opinion, the following factors have been prioritised for analysis, because of their likely influence on the onset, persistence, or changes in the impact of CP: cognitive function (including executive functioning); traumatic experiences during childhood or as adults; onset of menopause; and social isolation. Potential mediating factors were identified, including pain severity, physical activity, affective factors (e.g. symptoms of anxiety or depression), sleep, fatigue, BMI, multimorbidity). DAGs have been constructed and data on potential causes, mediating and moderating factors extracted from UKB baseline assessment, from additional tests and surveys conducted at later time-points, and from linked health care records over a period of 15 years. Initial results of causal inference models will be available at the time of the conference.
Conclusions
Potential causes assumed to influence long-term changes in high impact chronic pain were identified together with public contributors. Analysis is underway to determine the effect of traumatic experiences, social isolation, cognitive function, and menopause on impact of chronic pain. The role of candidate mediating factors, which could be potential targets for self-management or healthcare interventions, will be explored as part of causal inference analyses.
Alongside this work, systematic reviews are being conducted to summarize evidence of interventions that may effectively target modifiable causes or mediators of high impact CP, such as increasing physical activity, weight management, improving sleep quality, cognitive behavioural approaches, or appropriate medical treatments (e.g. hormone replacement therapy in women with menopausal symptoms). Future analyses will estimate the expected benefits of such interventions if they would successfully address identified mediating facto
References
[1]Fayaz A, Croft P, Langford RM, et al. BMJ Open 2016;6(6):e010364.
[2]Macfarlane GJ, Beasley M, Smith BH, et al. Br J Pain 2015;9(4): 203-12.
[3]Von Korff M, DeBar LL, Krebs EE, et al. Pain 2020;161(3):651-661.
[4]UK Biobank https://www.ukbiobank.ac.uk/
[5]Pearl J, Glymour M, Jewell NP. Wiley, 2016. ISBN-13-978-1119186847
[6]VanderWeele TJ. Epidemiology 2014;25(5):749–61.
Presenting Author
Danielle van der Windt
Poster Authors
Danielle Van der Windt
PhD
Keele University
Lead Author
Charlotte Woolley
PhD
Centre for Epidemiology Versus Arthritis, University of Manchester
Lead Author
Payam Amani
PhD
Primary Care Centre Versus Arthritis, School of Medicine, Keele University
Lead Author
Anna Gibby
University of Bath
Lead Author
Laura Lisboa
PhD
Institute for Mathematical Innovation, University of Bath
Lead Author
Matthew Nunes
PhD
School of Mathematical Sciences, University of Bath
Lead Author
Marcus Beasley
BSc (Hons)
Institute of Applied Health Sciences, School of Medicine, University of Aberdeen
Lead Author
Annick De Paepe
Ghent University
Lead Author
Taylor Robert
Research User Group, Primary Care Centre Versus Arthritis, Keele University
Lead Author
Emma Fisher
PhD
University of Bath
Lead Author
Emma Parry
MRCGP
Primary Care Centre Versus Arthritis, School of Medicine, Keele University
Lead Author
Milica Blagojevic-Bucknall
PhD
Primary Care Centre Versus Arthritis, School of Medicine, Keele University
Lead Author
Beate Ehrhardt
PhD
Institute for Mathematical Innovation, University of Bath
Lead Author
Barbara Nicholl
BSc (Hons)
University of Glasgow
Lead Author
Elaine Wainwright
PhD
University of Aberdeen
Lead Author
Gary Macfarlane
MBChB
University of Aberdeen
Lead Author
John McBeth
MA (Hons)
Centre for Epidemiology Versus Arthritis, University of Manchester
Lead Author
Edmund Keogh
PhD
University of Bath
Lead Author
Geert Crombez
Ghent University
Lead Author
Chris Eccleston
PhD
University of Bath
Lead Author
Topics
- Mechanisms: Psychosocial and Biopsychosocial