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. 2026 Jan 8;7(1):28–36. doi: 10.1302/2633-1462.71.BJO-2025-0152.R1

BMI and its association with patient-reported outcome measures following revision hip surgery

Rachel Baumber 1,2, Ahmed Mehmood 1,✉, Robert McCulloch 3, Snehal M Pinto Pereira 4, Eleanor Warwick 5, Alister Hart 1,4, S Ramani Moonesinghe 6,7,8; PQIP delivery team; PQIP collaborative; On behalf of the PQIP delivery team and collaborative
PMCID: PMC12780918  PMID: 41502394

Abstract

Aims

Obesity is associated with increased surgical complexity and poorer postoperative outcomes after primary total hip arthroplasty (THA), yet its impact on revision THA remains unclear. This study evaluates the relationship between BMI and outcomes following revision THA.

Methods

We analyzed prospectively collected data from patients who consented to participation in the Perioperative Quality Improvement Programme (PQIP) research study. All patients undergoing revision THA from May 2018 to December 2022 were included. Patients were stratified into BMI categories, and outcomes were assessed using the EuroQol five-dimension five-level questionnaire (EQ-5D-5L) at baseline, six, and 12 months postoperatively. Statistical comparisons were performed to evaluate differences in health-related quality of life (HRQoL) between BMI groups.

Results

Higher BMI was associated with lower preoperative EQ-5D scores. However, all BMI groups demonstrated significant postoperative improvement, with the greatest gains observed in patients with a BMI > 40 kg/m2. At six and 12 months, HRQoL improvements were comparable across BMI groups, with no significant difference in long-term outcomes between those living with and without obesity.

Conclusion

Despite potentially increased intraoperative risks, high BMI patients experience meaningful functional improvement following revision THA. These findings challenge the rationale for BMI-based surgical restrictions, suggesting that high BMI alone should not be a contraindication for revision THA.

Cite this article: Bone Jt Open 2026;7(1):28–36.

Keywords: Revision hip arthroplasty, Surgical risk stratification, Obesity, Perioperative outcomes, Healthcare policy, BMI, revision hip surgery, patient-reported outcome measures, EQ-5D scores, higher BMIs, primary total hip arthroplasty, EQ-5D-5L, contraindication, revision surgeries

Introduction

Obesity is a growing global public health concern, posing significant challenges to healthcare institutions and patient outcomes. In 2022, the World Health Organization calculated that 16% of the world’s adult population met the criteria for obesity (BMI > 30 kg/m2).1 In the UK, approximately 25% of adults are living with obesity, and forecasts by the Organisation for Economic Co-operation and Development are predicting that by 2030, obesity rates in the UK could increase to 35%.2,3 In the USA, the Centers for Disease Control and Prevention (CDC) estimates that 42% of all adults aged over 20 years in the USA are obese. This is predicted to rise to 50% by the year 2030, with an additional 25% considered morbidly obese (BMI > 35 kg/m2).4

Obesity is strongly associated with osteoarthritis (OA). Males with obesity are four times as likely to develop knee OA, while individuals with BMIs over 40 kg/m2 are 8.5 times more likely to develop hip OA.5 The excess mechanical load on weightbearing joints accelerates the degenerative process, leading to pain, stiffness, and functional decline.6,7

Patients with high BMI undergoing total hip arthroplasty (THA) are at increased risk of surgical complications and requiring revision surgeries.8 Factors contributing to this, including impaired wound healing, increased inflammatory response, and difficulties in surgical exposure and prosthetic fixation, all contribute to the heightened risks in this population. Comorbidities such as diabetes and cardiovascular disease further exacerbate these risks.8,9 Given the strong association between high BMI and the progression of OA, and the increasing prevalence of obesity, it is foreseeable that the demand for both primary and revision THAs will continue to rise. Although most future projections focus on primary procedures, the growing volume of primary THAs and longer patient survival strongly imply a corresponding increase in revision procedures in the coming decades. In fact, it is estimated that by the year 2060, rates of primary THAs will increase by 37.7% compared with 2018 levels.10 Revision procedures are often required for aseptic loosening, instability, implant failure, periprosthetic infection, and failure.11 Obesity can aggravate these issues, accelerating wear, loosening, and instability.12 Surgical challenges, including component malposition, wound complications, perioperative infections, and surgical exposure, are more common in patients with high BMI.8-11,13-18

Current literature regarding high BMI and primary THA indicates that although it is associated with an increased risk of operative complication, their overall functional outcomes show improvement.15-17,19 McLaughlin et al18 highlighted that BMI should not be an exclusion to THA, but inequalities still exist. However, while outcomes of primary THA in high BMI patients have been increasingly studied, there remains a lack of data on outcomes following revision hip arthroplasty in this group.15-19 This gap in the literature serves as the aim for the present study.

The aim of this study is to evaluate patient-reported outcome (PRO) following revision hip arthroplasty in relation to BMI. Understanding the relationship between BMI and postoperative outcomes will provide insight into optimizing care for this high-risk patient population.

Methods

Data were collected through the Perioperative Quality Improvement Programme (PQIP), which is a national research study of patients undergoing major elective surgery; study design and rationale has been described previously.19 Ethical approval for PQIP was given by the UK Health Research Authority (South East Coast – Surrey Research Ethics Committee; REC reference 16/LO/1827). All patients gave informed consent and data analysis was undertaken on a fully anonymized dataset.

We included data on all patients undergoing revision hip arthroplasty procedures between May 2018 and December 2022. Patients for whom BMI or baseline EuroQol five-dimension questionnaire (EQ-5D)20 data were missing were excluded from analysis, as were two patients who died while in hospital. The dataset was stratified into distinct BMI groups to discern potential correlations between BMI and post-surgical outcomes as per National Institute for Clinical Excellence (NICE) guidance.21

Patient characteristics

In total, 1,130 patients underwent revision hip arthroplasty; two were excluded because of missing BMI data. Two patients who died in hospital were excluded from analysis, as well as those who did not have admission EQ-5D values, leaving a final sample of 991 patients with recorded BMI and EQ-5D data on admission available for analysis. Patient follow-up is visualized in Figure 1.

Fig. 1.

Flowchart of patient follow-up: 1,130 total patients, two excluded for missing BMI. 11,28 remain; 991 have admission EQ-5D data. At six months, 459 followed (532 lost); at 12 months, 339 followed (120 lost). Flowchart showing patient follow-up data: It starts with total patients (n = 1,130). Two patients with no listed body mass index are excluded, leaving 1,128. Of these, 991 have admission EuroQol five-dimension questionnaire data. At six-month follow-up, there were 459 patients (532 lost to follow-up). At 12-month follow-up, there were 339 patients (120 lost to follow-up).

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Diagram tracking patient retention, showing the number of patients with admission EuroQol five-dimension (EQ-5D) questionnaire data and those available for follow-up (F/U) at six and 12 months.

Patient demographic details classified according to BMI groups is summarized in Table I. The mean BMI calculated across the entire patient cohort was 29.5 kg/m2 (SD 6.1), with 21 patients (1.9%) in the < 20 kg/m2 category, 223 (19.8%) a healthy weight, 382 (33.9%) in the overweight category, with 261 patients (23.1%), 180 (16.0%), and 61 (5.4%) in the Class 1, 2, and 3 obesity categories, respectively. This indicates a population with a slightly higher average BMI compared with the recorded average for primary hip arthroplasties, which was reported as 28.7 kg/m2 by the National Joint Registry (NJR).22 The mean age was 68.9 years (SD 11.5), with males comprising 51.1% of the overall cohort. Overall, 95.5% of surgeries were performed electively, 4.5% were marked as expedited.

Table I.

Demographic details of the cohort.

Variable BMI < 20 kg/m2 (n = 21) BMI 20 to 25 kg/m2 (n = 223) BMI 25 to 30 kg/m2 (n = 382) BMI 30 to 35 kg/m2 (n = 261) BMI 35 to 40 kg/m2 (n = 180) BMI > 40 kg/m2 (n = 61) p-value
Mean age, yrs (SD) 60.1 (17.3) 70.2 (12.7) 70.2 (10.9) 69.3 (9.9) 65.1 (11.1) 61.0 (11.4) < 0.001
Male, n (%) 6 (28.6) 74 (33.2) 203 (53.1) 146 (55.9) 84 (46.7) 27 (44.3) < 0.001
ASA grade, n (%)
1 2 (9.5) 30 (13.5) 48 (12.6) 18 (6.9) 9 (5.0) 1 (1.7)
2 14 (66.7) 120 (53.8) 219 (57.3) 146 (55.9) 77 (42.8) 23 (37.8)
3 4 (19.0) 71 (31.8) 108 (28.3) 96 (36.8) 86 (47.8) 33 (54.1)
4 1 (4.8) 1 (0.4) 4 (1.0) 0 4 (2.2) 3 (4.9)
Missing 0 (0) 2 (0.9) 3 (0.8) 1 (0.4) 4 (2.2) 1 (1.7) < 0.001
EBL, n (%)
< 101 ml 4 (19.0) 13 (5.8) 29 (8.0) 15 (5.7) 11 (6.1) 2 (3.3)
101 to 500 ml 9 (42.9) 81 (36.3) 132 (34.6) 86 (33.0) 36 (20.0) 10 (16.4)
501 to 1,000 ml 1 (4.8) 59 (26.5) 81 (21.2) 62 (23.8) 39 (21.7) 12 (19.7)
> 1,000 ml 2 (9.5) 24 (10.8) 50 (13.1) 37 (14.2) 38 (21.1) 14 (23.0)
Missing 5 (23.8) 46 (20.6) 90 (23.6) 61 (23.4) 56 (31.1) 23 (37.8) 0.006
Cardiac disease, n (%) 2 (9.5) 40 (17.9) 85 (22.3) 69 (26.4) 51 (28.3) 17 (27.9) 0.053
Liver disease, n (%) 0 (0) 2 (0.9) 3 (0.8) 1 (0.4) 0 (0) 0 (0) 0.906
Respiratory disease, n (%) 1 (4.8) 24 (10.8) 35 (9.2) 33 (12.6) 17 (9.4) 4 (6.6) 0.125
History of cancer, n (%) 2 (9.5) 13 (5.8) 24 (6.3) 20 (7.7) 9 (5.0) 6 (9.8) 0.387
Diabetes, n (%) 1 (4.8) 11 (4.9) 38 (9.9) 45 (17.2) 30 (16.7) 9 (14.8) 0.003
Current smoker, n (%) 5 (23.8) 23 (10.3) 28 (7.3) 14 (5.4) 16 (8.9) 8 (13.1) 0.134
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ASA, American Society of Anesthesiologists; EBL, estimated blood loss.

Patient-reported health outcomes were assessed using the EQ-5D five-level questionnaire (EQ-5D-5L). This validated tool captured self-reported health status, provided analyzable data of patients' physical, emotional, and social wellbeing, and is a measure of generic health-related quality of life (HRQoL). It is short and easy to use, shows good responsiveness and is capable of capturing clinically important changes. It is recommended for use in measuring HRQoL in perioperative core outcomes.23 The EQ-5D questionnaire, comprising five dimensions of mobility, self-care, usual activities, pain and discomfort, and anxiety and depression, allows for quantifiable data in evaluating health status longitudinally. These scores give a health state, which is converted into an index value using composite time trade-off values and are calculated using population specific values. The maximum index value is 1, a score of 0 equates to death, but a score of less than zero is possible and indicates a quality of life which is considered worse than death. Assessment of EQ-5D-5L values were performed as per the recommendations in the EQ-5D user guide, published by the EuroQol group.24

Six and 12-month follow-up EQ-5D data were missing in 53.7% and 65.8% of patients, respectively. These data were considered to be missing not at random, because patients with a lower quality of life have been found in previous studies to be less likely to respond at follow-up.21 Therefore, for the EQ-5D index, multiple imputation with chained equations using predictive mean matching was performed to account for this missing data, as it gave a similar overall distribution to the original data. Variables used for imputation were age, sex, BMI, estimated blood loss, duration of surgery, American Society of Anesthesiologists (ASA) grade,25 frailty, and admission EQ-5D index.

Statistical analysis

Overall EQ-5D index values were analyzed for skew, with an anticipated leftward skew of data requiring non parametric tests to be used for analysis. Demographic data were therefore compared using Kruskal Wallis for continuous and Mann Whitney U tests for categorical variables. EQ-5D indices at admission, six, and 12 months were analyzed and compared between BMI categories, as defined by the World Health Organization, using Wilcoxon paired test. EQ-5D dimension scores are presented as number and proportion, and changes were assessed using the Paretian Classification of Health Change.26,27 This gives a result of worsening, improvement, no change, or a mixed change in the overall dimension score between time points. A mixed change would be seen if there was improvement in some dimensions but worsening in others, improvement would be seen if improvement in some dimensions but others stayed the same. Individual dimension data were only available for 495 patients at six months and 369 patients at 12 months and a complete data analysis was used as it was felt there were too many missing variables such as reason for revision, which may impact on the individual dimension scores.

Analysis was undertaken using R Statistical Software v. 4.3.3 (R Foundation for Statistical Computing, Austria). Statistical significance was set at p < 0.05.

Results

An unexpected finding was that diabetes was most prevalent in the BMI 30 to 35 kg/m2 group rather than in the > 40 kg/m2 group. This may reflect variability in underlying comorbidity burden, or unmeasured cofounders such as socioeconomic status or ethnicity. While this does not impact the overall findings, it highlights the need for further investigation into the distribution of comorbidities across BMI in revision arthroplasty populations

Analysis of EQ-5D data, seen in Table II and visualized in Figure 2, revealed improvements in EQ-5D index at both six and 12 months post-revision hip surgery in all BMI categories, except those who were underweight. These improvements were significant (p < 0.001) at both six and 12 months when compared with baseline values in all those whose BMI was over 20 kg/m2. Further improvements between six and 12 months indices were only significant in patients with a BMI between 20 kg/m2 and 25 kg/m2.

Table II.

Analysis of EuroQol five-dimension (EQ-5D) index at six and 12 months.

BMI, kg/m2 Admission EQ-5D index Six-month index p-value* 12-month index p-value*
< 20 (n = 21) 0.625 0.733 0.056 0.627 0.360
20 to 25 (n = 223) 0.538 0.667 < 0.001 0.696 0.014
25 to 30 (n = 382) 0.541 0.708 < 0.001 0.746 0.602
30 to 35 (n = 261) 0.518 0.721 < 0.001 0.693 0.113
35 to 40 (n = 180) 0.447 0.652 < 0.001 0.694 0.167
> 40 (n = 61) 0.325 0.638 < 0.001 0.667 0.598
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*

Wilcoxon paired test.

Fig. 2.

Line graph showing mean EuroQol five-dimension index over zero, six, and 12 months by BMI category in kg/m2 (< 20, 20 to 25, 25 to 30, 30 to 35, 35 to 40, > 40). All categories increase at six months. Line graph, titled BMI category, showing mean EuroQol five-dimension index over time (zero, six, and 12 months) for six BMI groups: < 20 kg/m2, 20 to 25 kg/m2, 25 to 30 kg/m2, 30 to 35 kg/m2, 35 to 40 kg/m2, and > 40 kg/m2. All groups start between 0.3 and 0.65 at baseline, rise by six months, then mostly stabilize by 12 months. The < 20 kg/m2 group peaks highest at six months then declines, while other categories remain steady or slightly increase.

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Visualization of mean EuroQol five-dimension (EQ-5D) index values of BMI subgroups in kg/m2, from zero to 12 months.

Increasing BMI was associated with lower preoperative EQ-5D scores. Those with BMIs below 20 kg/m2 and above 40 kg/m2 experienced the highest and lowest mean index scores, respectively (0.625 (SD 28) and 0.324 (SD 24)). Significant improvements in EQ-5D index scores were observed across all BMI groups by six months, with the exception of patients with a BMI below 20 kg/m2. There was continued improvement observed between six and 12 months in most BMI groups, but this was not clinically significant except in those with a BMI between 20 kg/m2 and 25 kg/m2. At both the six and 12-month mark, the greatest increase in mean index scores was seen in the over 40 kg/m2 BMI subgroup; an increase of 0.313 at six months and 0.342 at 12 months.

As shown in Table III, analysis of EQ-5D visual analogue scale (VAS) scores found no significant differences across different BMI categories at both six and 12 months post-surgery. This suggests that patients' subjective evaluations of their overall health status remained consistent across varying BMI levels. The p-values for the over 40 kg/m2 BMI subgroup were unable to be calculated due to small numbers and missing data at six and 12 months.

Table III.

Visual analogue scale (VAS) scores at six and 12 months, showing no significant difference across subgroups.

BMI, kg/m2 Mean admission VAS (SD) Mean six-month VAS (SD) p-value* Mean 12-month VAS (SD) p-value*
< 20 (n = 21) 63.4 (26.8) 70.7 (20.2) 0.209 65.3 (7.3) 0.146
20 to 25 (n = 223) 64.3 (23.0) 70.7 (22.1) 0.738 70.9 (22.9) 0.128
25 to 30 (n = 382) 65.2 (21.6) 67.1 (22.9) 0.118 70.0 (23.4) 0.053
30 to 35 (n = 261) 62.2 (21.4) 66.8 (21.8) 0.063 69.4 (22.0) 0.128
35 to 40 (n = 180) 58.1 (24.9) 63.1 (20.4) 0.224 61.2 (26.2) 0.363
> 40 (n = 61) 51.6 (25.6) 62.5 (24.3) 0.358 68.1 (26.1) 0.121
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*

Wilcoxon paired test.

BMI-specific analysis

At the six-month follow-up (n = 459), as assessed by the Pareto Classification of Health Change,27 over half of patients (51.4%, n = 236) exhibited improvement in their health status following revision hip surgery; 15.0% (n = 69) experienced deterioration and 0.4% (n = 2) showed no change. Additionally, 152 patients (33.1%) demonstrated mixed changes in their health status, with improvements observed in some dimensions while others declined. Similar trends in patient outcomes were observed at 12-month follow-up (n = 339), with a slightly higher percentage (54.3%, n = 184) of patients showing improvement in their health status. However, 13.3% (n = 45) experienced deterioration, and 32.4% (n = 110) experienced mixed changes, with improvements in some aspects of the EQ-5D and decline in others.

Table IV and Table V show changes in individual dimensions stratified by BMI category at six and 12 months, respectively. These results are then visualized in Figures 3 to 7. Patients with a BMI of over 40 kg/m2 had the highest proportion who improved in the mobility (78.6%), usual activities (75.0%), and pain and discomfort (71.4%) six months postoperatively. Up until this BMI group, percentage of patients experiencing improvements in mobility at six months decreased with increasing BMI. However, pain and discomfort percentage improvements increased with higher BMI category, as did anxiety and depression. Patients with a BMI of less than 20 kg/m2 had the lowest proportion of improvement in self-care (20.0%), usual activities (30.0%), and pain and discomfort scores (50.0%) at six months postoperatively.

Table IV.

Individual dimensions stratified by BMI category at six months.

Dimension BMI < 20 kg/m2 BMI 20 to 30 kg/m2 BMI 30 to 40 kg/m2 BMI > 40 kg/m2
Mobility
Improve 66.7 59.3 56.5 78.6
Worsen 0 16.5 15.3 7.1
No change 33.3 24.2 28.2 14.3
Self care
Improve 33.3 49.2 51.2 52.6
Worsen 50.0 33.0 26.4 31.6
No change 17.7 17.8 22.4 15.8
Usual activities
Improve 33.3 57.1 54.5 75.0
Worsen 22.2 23.1 27.9 17.9
No change 50.0 19.8 17.6 7.1
Pain and discomfort
Improve 55.6 60.0 61.8 71.4
Worsen 33.3 15.8 19.4 10.7
No change 11.1 24.2 18.8 17.9
Anxiety and depression
Improve 71.4 53.5 61.2 58.3
Worsen 0 27.3 22.5 25.0
No change 28.6 19.2 16.3 16.7
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Table V.

Individual dimensions stratified by BMI category at 12 months.

Dimension BMI < 20 kg/m2 BMI 20 to 30 kg/m2 BMI 30 to 40 kg/m2 BMI > 40 kg/m2
Mobility
Improve 83.3 65.4 55.8 76.2
Worsen 16.7 16.8 20.8 0.0
No change 0.0 17.8 23.4 23.8
Self care
Improve 40.0 61.7 49.4 66.7
Worsen 40.0 31.2 30.3 20.0
No change 20.0 7.1 20.3 13.3
Usual activities
Improve 40.0 61.0 54.3 85.7
Worsen 20.0 31.2 27.6 14.3
No change 40.0 7.8 18.1 0.0
Pain and discomfort
Improve 50.0 65.8 57.9 71.4
Worsen 50.0 18.5 20.7 9.5
No change 0.0 15.7 21.4 15.1
Anxiety and depression
Improve 75.0 64.1 62.1 61.1
Worsen 25.0 26.2 23.2 11.1
No change 0.0 9.7 14.7 27.8
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Fig. 3.

Bar chart titled ‘mobility’, showing improvement and worsening across BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, > 40. Respective improve rates are 83%, 65%, 56%, 76%, while worsen are 17%, 17%, 21%, 24%. Y-axis ranges 0 to 90%. Bar chart, titled ‘mobility’, showing percentage of improvement and worsening across BMI categories. Four BMI categories are displayed on the x-axis: < 20 kg/m2, 20 to 30 kg/m2, 30 to 40 kg/m2, and > 40 kg/m2. The y-axis represents percentage from 0 to 90. For each category, two bars are shown: one for ‘Improve’ and another for ‘worsen.’ Values for ‘improve’ are approximately 83% (< 20 kg/m2), 65% (20 to 30 kg/m2), 56% (30 to 40 kg/m2), and 76% (> 40 kg/m2). Values for ‘worsen’ are about 17% (< 20 kg/m2), 17% (20 to 30 kg/m2), 21% (30 to 40 kg/m2), and 24% (> 40 kg/m2).

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Change in patient-reported health outcomes over 12 months, stratified by BMI category in kg/m². The chart illustrates the percentage of patients within BMI group whose condition improved or worsened within the mobility quality of life dimension.

Fig. 7.

Bar chart titled ‘anxiety and depression’, showing improvement and worsening across BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, > 40. Respective improve rates arey 75%, 64%, 62%, 61%, while worsen are 25%, 26%, 23%, 11%. The y-axis is 0 to 70%. Bar chart, titled ‘anxiety and depression’, comparing improvement and worsening percentages across BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, and > 40. The y-axis ranges from 0 to 80 percent. Each category has two barsfor ‘improve’ and ‘worsen.’ For BMI < 20 kg/m2, improve is about 75% and worsen about 25%. For BMI 20 to 30 kg/m2, improve is around 64% and worsen about 26%. For BMI 30 to 40 kg/m2, improve is near 62% and worsen about 23%. For BMI > 40 kg/m2, improve is about 61% while worsen drops to 11%. The chart shows that improvement remains relatively high across all BMI categories, while worsening decreases significantly at higher BMI levels.

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Change in patient-reported health outcomes over 12 months, stratified by BMI category in kg/m². The chart illustrates the percentage of patients within each BMI group whose condition improved or worsened within the anxiety and depression quality of life dimension.

Fig. 4.

Bar chart, titled ‘self care’, showing percentage of improvement and worsening across BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, > 40. Respective improve rates are 40%, 62%, 49%, 67%, while worsen are 40%, 31%, 30%, 20%. The y-axis is 0 to 70%. Bar chart, titled ‘self care’, comparing improvement and worsening percentages across four BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, and > 40. The y-axis ranges from 0 to 70 percent. Each category has two bars demonstrating ‘improve’ and ‘worsen.’ For BMI < 20, both improve and worsen are about 40%. For BMI 20 to 30, improve is around 62% and worsen about 31%. For BMI 30 to 40, improve is near 49% and worsen about 30%. For BMI > 40, improve reaches about 67% while worsen drops to 20%. The chart shows that improvement generally increases with BMI, except for the 30 to 40 range, while worsening decreases at higher BMI levels.

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Change in patient-reported health outcomes over 12 months, stratified by BMI category in kg/m². The chart illustrates the percentage of patients within each BMI group whose condition improved or worsened within the self-care quality of life dimension.

Fig. 5.

Bar chart titled ‘usual activities’, showing improvement and worsening across BMI categories in in kg/m2: < 20, 20 to 30, 30 to 40, > 40. Respective improve rates are 40%, 61%, 55%, 86%, while worsen are 20%, 31%, 27%, 14%. The y-axis is 0 to 90%. Bar chart titled ‘usual activities’ showing percentages of improvement and worsening across BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, and > 40. The y-axis ranges from 0 to 90 percent. For BMI < 20 kg/m2, improve is about 40% and worsen about 20%. For BMI 20 to 30 kg/m2, improve is around 61% and worsen about 31%. For BMI 30 to 40 kg/m2, improve is near 55% and worsen about 27%. For BMI > 40 kg/m2, improve reaches about 86% while worsen drops to 14%. The chart indicates that improvement increases significantly at higher BMI levels, while worsening decreases.

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Change in patient-reported health outcomes over 12 months, stratified by BMI category in kg/m². The chart illustrates the percentage of patients within each BMI group whose condition improved or worsened within the usual activities quality of life dimension.

Fig. 6.

Bar chart titled ‘pain and discomfort’, showing improvement and worsening across BMI categories in kg/m2: < 20, 20 to 30, 30 to 40, > 40. Respective improve rates are 50%, 66%, 58%, 71%, while worsen are 50%, 18%, 21%, 9%. The y-axis ranges 0 to 70%. Bar chart titled ‘pain and discomfort’ comparing improvement and worsening percentages across BMI categories: < 20 kg/m2, 20 to 30 kg/m2, 30 to 40 kg/m2, and > 40 kg/m2. The y-axis ranges from 0 to 70 percent. Each category has two bars for ‘improve’ and ‘worsen.’ For BMI < 20 kg/m2, both improve and worsen are about 50%. For BMI 20 to 30 kg/m2, improve rises to around 66% while worsen drops to about 18%. For BMI 30 to 40 kg/m2, improve is near 58% and worsen about 21%. For BMI > 40 kg/m2, improve reaches about 71% while worsen falls to 9%. The chart shows that improvement increases with BMI, while worsening decreases significantly at higher BMI levels.

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Change in patient-reported health outcomes over 12 months, stratified by BMI category in kg/m². The chart illustrates the percentage of patients within each BMI group whose condition improved or worsened within the pain and discomfort quality of life dimension.

Discussion

While the guidance and evidence supporting the avoidance of blanket restrictions to primary hip arthroplasty based on BMI is clear, there is a gap in the literature regarding patient-centred outcomes of revision procedures for patients with higher BMI. Our study demonstrates that higher BMI patients undergoing revision total hip arthroplasties also experience significant improvements in self-reported outcomes. These findings align with the principles outlined above to primary hip arthroplasties, suggesting that BMI should similarly not be a sole criterion for excluding patients from revision surgeries. By adopting a more inclusive approach, healthcare providers can ensure equitable access to necessary surgical interventions for all patients, regardless of BMI.

Guidance from NICE states that obesity should not be a disqualifying factor for patients seeking a primary hip arthroplasty. While the guidance acknowledges that high BMI can increase the risk of complications fourfold, it also emphasizes that the overall outcomes for primary hip arthroplasties are comparable across different BMI groups.28 However, despite this guidance, many institutions impose a BMI threshold as a prerequisite for access to arthroplasty surgery.29 This policy is often implemented with the aim of mitigating the increased risks associated with higher BMI, such as infection, wound complications, and prolonged recovery times. Healthcare providers argue that these thresholds aim to enhance patient safety; however, an alternative perspective is that it may delay necessary surgical interventions for patients living with obesity who are otherwise suitable candidates for hip arthroplasty. BMI thresholds can lead to inequities in healthcare access with those without the means to access care in the independent sector left attempting to lose weight18 with limited mobility and pain making this a potentially insurmountable task. There also exists an obesity paradox, which describes a lower rate of complications and mortality following other types of surgery;26,30 this has yet to be described in revision hip surgery but may explain some of the findings above.

Management of high BMI in the context of arthroplasty can include preoperative interventions such as bariatric surgery. While these interventions can effectively reduce a patient’s BMI, the current evidence suggests that they do not significantly alter the perioperative risk profile associated with high BMI.31,32 In recent years the use of glucagon-like peptide 1 receptor agnoists (GLP1) in weight loss prior to arthroplasty has also been investigated. GLP1 agonists used preoperatively have been shown to reduce rates of periprosthetic joint infections, readmission within 90 days of operation.33,34 Despite this benefit, GLP1 agonists have also been associated with an increased risk of myocardial infarction, acute kidney injury, pneumonia, and hypoglycaemic events.34 While further research on the risks and benefits of these interventions to reduce high BMI and its consequences in perioperative pathways would be welcome, there does not currently appear to be a strong case for using them to improve outcomes from joint arthroplasty, including revision surgery.

A limitation of this study is the lack of data regarding the indication for revision procedures. The NJR’s most recent annual report identified that among 43,682 first revisions, the most common indications were aseptic loosening (n = 10,828), dislocation/subluxation (n = 7,602), periprosthetic fracture (n = 7,176), infection (n = 6,779), and pain (n = 5,100).5 It is probable that outcomes (including patient-reported outcomes) will vary according to reason for revision, and also other factors which we did not record, such as duration of time on the waiting list and disease-specific quality of life outcomes such as Oxford Hip Score. Generic health-related quality of life outcomes as reported in this study focus on the overall health status of a patient and allow better overall comparisons between different diseases, interventions, and population. This study therefore demonstrates a significant overall health benefit from revision hip arthroplasty rather than concentrating on the disease process or joint. We have also not undertaken multivariable analysis to report independent risk factors for worse outcomes. This is because the purpose of this analysis was to evaluate if there would be a rationale for decision-making on suitability for revision surgery based on BMI alone, as our clinical experience, and previous data, tells us still occurs in clinical practice in the NHS. Our conclusion is that there is no rationale for decision-making based on BMI alone.

Another limitation to consider is the potential floor effect of the EQ-5D scores at baseline; patients with higher BMI in this cohort tended to report lower preoperative health-related quality of life scores, leading greater scope for measurable improvement postoperatively. This may partly explain the larger gains observed in this group, as the EQ-5D instrument is less sensitive at the lower end of the scale. However, the consistent pattern of improvement across BMI categories and the magnitude of change seen, suggest that the observed gains are unlikely to be entirely artifactual. While this effect should be considered when interpreting the results, it does not negate the meaningful health improvements experienced by patients following revision hip arthroplasty. Interestingly, although EQ-5D index scores improved significantly across most BMI categories, the EQ-5D VAS scores did not show significant differences between groups at either six or 12 months. This discrepancy may reflect the nature of the VAS as a single-item measure of self-rated global health, which can be influenced by broader psychosocial factors such as mood, coping strategies, or individual expectations. In contrast, the EQ-5D index score is derived from multiple specific dimensions (e.g. mobility, pain/discomfort), and may therefore be more sensitive to functional recovery following surgery. These differences highlight the importance of using both domain-specific and global PROMs to capture the full impact of revision arthroplasty on patient wellbeing.

A further limitation is the drop out rate at six and 12 months. The average dropout rate for a clinical trial is 30%, but this increases to 50% to 70% for observational studies.35 Therefore, the loss to follow-up rates in this population are comparable with other studies. Imputation for the EQ-5D index was used to minimize the impact of this. Many studies aim to describe EQ-5D improvements by the minimal clinically important difference (MCID)36,37 . There is a lack of literature describing the MCID for EQ-5D in revision total hip arthroplasty and it was not the purpose of this study to define it. Further analysis may be able to generate a MCID in this population which could be used in future studies of revision THA. In addition, the use of the MCID as a tool to assess change in EQ-5D is not recommended by the EuroQoL group user guide.

In conclusion, our data suggests that patients of all BMI categories experience an improvement in health-related quality of life, with those in the highest BMI categories having the largest improvement in EQ-5D index. Patients living with higher BMIs have lower baseline health-related quality of life, and this improves after surgery to become commensurate with outcomes for patients of lower BMI. Despite the potential complexities associated with providing care to this patient demographic group, this study would advocate against the denial or delay of revision hip arthroplasty solely based on BMI status. Instead, and in keeping with national guidance, we support shared decision-making between patients and the multidisciplinary team, taking into consideration a holistic review of patient and surgical factors, incorporating BMI into a personalized risk assessment framework alongside comorbidities, functional status, and patient preferences. This can help provide tailored preoperative counselling and optimize decision-making, ensuring that treatment plans are both equitable and patient centred.

Take home message

- Despite lower preoperative scores, patients with higher BMI show substantial improvement in health-related quality of life after revision total hip arthroplasty (THA).

- At six and 12 months, functional gains were similar between patients living with and without obesity.

- Higher BMI does not justify exclusion from revision THA, as patients experience meaningful postoperative recovery.

- Perioperative risks exist but do not negate benefits. While high BMI increases surgical complexity, it does not prevent positive long-term outcomes.

- Policy reconsideration is needed. Blanket BMI-based restrictions on revision THA may deny effective treatment to patients who stand to benefit.

Author contributions

R. Baumber: Conceptualization, Data curation, Formal analysis, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing

A. Mehmood: Conceptualization, Visualization, Writing – original draft, Writing – review & editing

R. McCulloch: Conceptualization, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

S. M. P. Pereira: Conceptualization, Data curation, Supervision, Writing – original draft, Writing – review & editing

E. Warwick: Writing – review & editing

A. Hart: Supervision, Writing – review & editing, Conceptualization, Data curation, Resources

S. R. Moonesinghe: Conceptualization, Supervision, Writing – review & editing, Resources

Funding statement

The author(s) disclose receipt of the following financial or material support for the research, authorship, and/or publication of this article: Perioperative Quality Improvement Programme from the Royal College of Anaesthetists, the Health Foundation and the National Institute for Health Research's Central London Patient Safety Research Collaboration

ICMJE COI statement

The Perioperative Quality Improvement Programme has received funding from the Health Foundation (personal fellowship for S.R. Moonesinghe), from the Royal College of Anaesthetists and from the National Institute for Health Research (NIHR) Central London Patient Safety Research Collaboration (reference: NIHR204297). S.R. Moonesinghe also receives funding from the University College London Hospitals (UCLH) NIHR Biomedical Research Centre (reference: NIHR203328). S. M. Pinto Pereira is supported by a UK Medical Research Council senior non-clinical fellowship (reference: MR/Y009398/1). All other authors have no conflicts of interest to disclose.

Data sharing

The data that support the findings for this study are available to other researchers from the corresponding author upon reasonable request.

Acknowledgements

PQIP delivery team:

S. Ramani Moonesinghe, Duncan Wagstaff, James Bedford, Arun Sahni, Dermot McGuckin, David Gilhooly, Cristel Santos, Jonathan Wilson, Peter Martin, Georgina Singleton, Kylie Edwards, Rachel Baumber, Cecilia Vindrola-Padros, Samantha Warnakulasuriya, Jenny Dorey, Irene Leeman, Martha Belete, Eleanor Warwick, Michael Argent, Rachael Brooks, Adam Firth Hunt, Eimear Lusby, Dominic Olive, Bo Hou, Aiman Al-Eryani, James Durrand, and Scott Weerasuriya.

PQIP collaborative:

Anna Batchelor, Chris Snowden, Dave Murray, Elspeth Evans, Emma Vaux, John Abercrombie, Jonathan McGhie, Jugdeep Dhesi, Tom Clark, Anna Crossley, John McGrath, Marie Digner, Mark Hamilton, Robert Hill, Samantha Shinde, and Stephen Brett.

Open access funding

The open access fee was funded by the Royal National Orthopaedic Hospital Research Department, Stanmore, UK.

© 2026 Baumber et al. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc-nd/4.0/

Contributor Information

Ahmed Mehmood, Email: Ahmed.mehmood@doctors.org.uk.

Collaborators: PQIP Delivery Team, S Ramani Moonesinghe, Duncan Wagstaff, James Bedford, Arun Sahni, Dermot McGuckin, David Gilhooly, Cristel Santos, Jonathan Wilson, Peter Martin, Georgina Singleton, Kylie Edwards, Cecilia Vindrola-Padros, Samantha Warnakulasuriya, Jenny Dorey, Irene Leemans, Dorian Martinez, Jose Lourtie, Rachel Baumber, Jenny Dorey, Andrew Swift, Alexander Jackson, Martha Belete, Eleanor Warwick, Michael Argent, Rachael Brooks, Naomi Fulop, Alexandra Brent, Karen Williams, Mike Grocott, Monty Mythen, Dominic Olive, Christine Taylor, Sharon Drake, Mike Swart, Anne-Marie Bougeard, Matthew Bedford, Abigail Vallance, Pritam Singh, Ravi Vohra, Aleksandra Ignacka, Olga Tucker, Giuseppe Aresu, Martin Cripps, Helen Ellicott, Katie Samuel, Maria Chazapis, Adam Firth Hunt, Eimhear Lusby, James Durrand, Scott Weerasuriya, PQIP Collaborative, Anna Batchelor, Chris Snowden, Dave Murray, Elspeth Evans, Emma Vaux, John Abercrombie, Jonathan McGhie, Jugdeep Dhesi, Tom Clark, Anna Crossley, John McGrath, Marie Digner, Mark Hamilton, Robert Hill, Samantha Shinde, and Stephen Brett

Data Availability

The data that support the findings for this study are available to other researchers from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings for this study are available to other researchers from the corresponding author upon reasonable request.

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