British journal of anaesthesia
October 16, 2026 · via Europe PMC
Socioeconomic position and preoperative characteristics in Perioperative Quality Improvement Programme participants: a UK national observational study.
Durrand J, Hou B, Hunt A, +6 more, PQIP collaborative.
AI summary — for doctors, generated from the abstract only
Patients from more deprived areas presented for major elective surgery in poorer overall health and were under-represented in this national programme.
What was studied
A UK observational analysis of 55,938 adults in the Perioperative Quality Improvement Programme, comparing preoperative characteristics by Index of Multiple Deprivation (IMD) quintile.
Key findings
- The most deprived quintile was the smallest subgroup (14.2%), and median age was 62 years in IMD 1 versus 67 in IMD 5.
- Smoking, inactivity and obesity increased from IMD 5 to 1, as did diabetes, heart failure, stroke and ASA 3-4.
- The proportions of patients with frailty and disability increased with deprivation.
Clinical relevance
Supports tailoring preoperative optimisation and support to socioeconomic context to avoid widening perioperative inequalities.
Who should care
Limitations
Area-level deprivation is a proxy for individual circumstances; recruitment varied by region and site, so deprived patients may be under-represented; the study is descriptive and does not examine outcomes.
Deprivation tracks with worse preoperative health, so targeted interventions are warranted.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Background
Patients from more deprived backgrounds experience poorer postoperative outcomes. We analysed preoperative characteristics in UK Perioperative Quality Improvement Programme participants according to socioeconomic position to explore opportunities for targeted interventions.
Methods
Participants were adults aged ≥18 yr undergoing major elective surgery at UK Perioperative Quality Improvement Programme sites. Socioeconomic position was determined using postcode data and the Index of Multiple Deprivation (IMD) standardised aggregate scale of area-level deprivation. Associations between IMD position and patient characteristics, health behaviours, and comorbidities were analysed using descriptive statistics with appropriate parametric and nonparametric testing.
Results
Of 55 938 participants included, quintile 1 (most deprived) represented the smallest subgroup (14.2%), with recruitment varying by region and site. Median age was 66 yr with IMD 1 participants 5 yr younger (62 yr) than IMD 5 (67 yr). Deprivation gradients (IMD 5 to 1) were seen for home ownership, occupation, and educational attainment. Prevalences of smoking, inactivity, and obesity increased from IMD 5 to 1. Higher prevalences of major long-term conditions including diabetes mellitus, heart failure, stroke, and ASA physical status 3-4 were observed in more deprived quintiles. Prevalence rates of dementia and renal impairment were similar across quintiles despite the age gradient. Notably, the proportions of patients living with frailty and disability increased with deprivation.
Conclusions
Patients presenting for major surgery from more deprived backgrounds do so in poorer overall health. They can encounter barriers to both research participation and available preoperative support. Addressing this unmet need to prevent widening perioperative health inequalities requires interventions tailored to the patient's socioeconomic context.
DOI
10.1016/j.bja.2026.09.002
PMID
42888145
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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