Abstract
Background:
Achilles tendon rupture (ATR) is a common injury with an estimated incidence of about 7 to 40 per 100,000 person-years. Identifying risk factors for ATR is an important step toward injury prevention. Modifiable factors, such as body mass index (BMI), are of particular interest because of the potential for intervention, and recent studies have shown mixed results for BMI as a risk factor for ATR. This case-control study aims to compare the BMI of patients diagnosed with a primary ATR to age and sex-matched controls diagnosed with an ankle sprain.
Methods:
A retrospective chart review of 168 patients was performed, which included 56 patients with ATR age- and sex-matched with 112 ankle sprain controls. Demographics and BMI data were collected and compared across the 2 groups. Mann-Whitney U tests and Fisher exact tests were used to determine differences between groups. Multivariate logistic regression models were used to further analyze significant variables.
Results:
The mean BMI for ATR was 33.4 and ankle sprain was 31.9, which was not statistically significant (P = .162). When BMI was divided into subclasses, there were significantly fewer patients who sustained ATR compared to ankle sprain controls in the class 1 (BMI 18-25; P = .020). Participating in sports (P < .001) and African American race (P < .001) were the only other statistically significant risk factors. Multivariate logistic regression showed increased likelihood of ATR for patients who were African American (P = .006), participated in athletics (P < .001), and had a BMI higher than 25 (P = .018).
Conclusion:
This study found that a BMI between 18 and 25 was associated with lower rates of ATR when compared to BMI classes greater than 25. Our data suggests that BMI may be an independent factor associated with ATR, even in patients engaging in sporting activity.
Level of Evidence:
Level III, case-control study.
This is a visual representation of the abstract.
Keywords
Introduction
Achilles tendon rupture (ATR) is a common tendon rupture with an estimated incidence of about 7 to 40 per 100,000 person-years, 9 which has significantly increased in recent decades.6,8 This injury is typically sustained during sporting activity when there is a sudden push-off, jumping, or acceleration movement accompanied by a sudden onset of pain with an audible “pop” or “snap” at the injury site. Men in their third to fifth decade of life have a significantly higher incidence of ATR compared with women. 7 It is important to identify risk factors that predispose patients to ATR to guide prevention and treatment for those at higher risk.
There have been numerous studies examining the risk factors for ATR, which include age, race, fluoroquinolone use, local and oral corticosteroid use, history of prior Achilles tendinopathy, blood type, medical comorbidities (ie, diabetes, hyperuricemia), and participation in sports.3,4,15,20 Prior evidence has correlated increased body mass index (BMI) as a risk factor for Achilles tendinopathy, 5 but the literature has mixed results with BMI as a risk factor for ATR.1,10,11,13,14 Macchi et al 10 performed a systematic review of clinical studies that found patients with obesity (BMI > 30) had a greater risk of Achilles tendinopathy, attributed to the increased pro-inflammatory cytokines and high mechanical demand in obese patients. This degenerative process is thought to increase the mechanical breakdown of the tendon, which may increase the risk of rupture when a sufficient eccentric force is applied. 16 Despite this, Macchi et al concluded there was no increased risk of ATR in patients with obesity. To further assess the relationship between BMI and ATR, Noback et al 11 conducted a study that compared the BMI of patients with ATR to a control group of patients who sustained ankle sprains. They found no clinically significant difference between BMI across the 2 groups. They concluded that activity level was a better predictor of ATR than BMI because there must be a large enough force generated to rupture the tendon. In contrast, a recent population-based study of >16 million people in South Korea found that higher BMI had an increased risk of ATR. 1 Overall, only a few relevant studies have examined the relationship between BMI and ATR, and the inconsistent conclusion across these studies calls for a better understanding of BMI as a risk factor for ATR.
This study will replicate the matched case-control study design of Noback et al 11 to determine if a similar relationship is true in a different patient population. This case-control study aims to compare the BMI of patients diagnosed with a primary ATR to age- and sex-matched controls diagnosed with an ankle sprain to assess BMI as a risk factor for ATR. We hypothesize that there will be no significant difference in the mean BMI of those sustaining ATR and ankle sprain controls.
Methods
Population
Institutional review board approval was obtained before retrospective chart review was performed on patients with the International Classification of Diseases, Tenth Revision (ICD-10) codes for ATR or ankle sprain during a 10-year period from January 1, 2015, to January 31, 2024. The diagnosis of ATR was confirmed by chart review and based on the clinical examination findings of altered resting tension relative to the uninjured side, a positive Thompson test, and imaging when available. The diagnosis of ankle sprain was confirmed by the mechanism of injury, negative radiographs, and tenderness to palpation over the ligaments of the ankle. All patient data were collected from a single tertiary academic medical center treated by the same foot and ankle orthopaedic surgeon.
All patients between the ages of 18 and 89 years with confirmation of ATR or ankle sprain were included in the study. Patients were excluded if there were insufficient data to calculate BMI, the presence of bilateral ruptures, or presentation more than 12 weeks after injury, which precluded the calculation of an accurate BMI at the time of injury. Patients were also excluded if there was a high-energy mechanism of injury (ie, motor vehicle collision, trauma), the injury was chronic, there was a traumatic laceration, or a re-rupture of the tendon. Both cases and controls were excluded if radiographs and/or clinical evaluation suggested an alternative diagnosis (ie, ankle fracture).
Study Design
This is a 2-to-1 matched case-control study where each ATR was age- and sex-matched with 2 ankle sprain controls. The ankle sprain control group was included in the study to provide a set of comparable patients routinely seen in an orthopaedic foot and ankle clinic. Ankle sprains are a common injury that occurs in a broad demographic range, making these patients a reasonable proxy for the general population in our geographical area.
Information about each patient’s treatment course and demographics were recorded, including factors previously associated with risk of ATR; age, gender, race, occupation, tobacco use, participation in athletic activities (termed “athlete status”), mechanism of injury, medical comorbidities, history of Achilles tendinopathy, history of fluoroquinolone use, and history of exposure to corticosteroids. “Athlete status” was determined based on patient reported participation in a sporting activity at the time of injury, which was collected from emergency room or clinic documentation. BMI was calculated from the patient’s height and weight on initial evaluation of the injury, with subjects having a BMI of 30 or higher as obese. We further divided the BMI of patients into subgroups based on the current guidelines in use by the National Institute of Health (NIH) and WHO. 18 Our final classification system included 4 total groups as follows: class 1, BMI 18-25; class 2, BMI 25-30; class 3, BMI 30-35; and class 4, BMI ≥35. Patients in both the ATR and ankle sprain groups were compared for differences in each BMI class.
Statistical Analysis
Patients in the ATR group were 1:2 matched to patients in the ankle sprain group by age and sex. The threshold for significance was set at P <.05, and the Shapiro-Wilk test and Bartlett test were used to check for normality and variances, respectively, of continuous data. Fisher exact test was used when comparing nominal variables such as demographics and risk factor exposure status. Two-sample t tests or Mann-Whitney U test were used to compare continuous data between the 2 cohorts. Descriptive statistics, such as means, frequencies, and SDs, were used when appropriate to display data. Statistical analysis was performed using R Statistical Software (R version 4.2.2, http://www.r-project.org) and Excel (Microsoft).
A multivariate logistic regression model was used to assess risk factors that were found to be statistically different between groups during preliminary analysis. Interaction effects between potentially correlated values were also assessed in a separate multivariate logistic analysis to control for possible confounding variables. Odds ratios (ORs) with 95% CIs were calculated for each covariate.
Results
We found 56 ATR patients that met inclusion and exclusion criteria over the 10-year study period. These 56 patients were 1:2 age and sex matched with 112 ankle sprain patients over the same study period to give a total sample size of 168 patients. Age and BMI were found to be nonnormally distributed in both the ATR group (P = .004, P < .0001, respectively) and ankle sprain group (P < .0001, P < .0001, respectively), whereas BMI among athletes was found to be nonnormally distributed in the ATR group (P < .0001). Variances were unequal in age (P = .037) between the ATR and ankle sprain group but were equal in BMI among athletes (P = .410, P = .939, respectively).
There were significantly more African American patients in the ATR group (ATR: n = 17 [30%] vs Ankle Sprain: n = 7 [6%], P < .001); conversely, there were more White patients in the ankle sprain group (ATR: n = 35 [63%] vs Ankle Sprain: n = 92 [82%], P = .007; Table 1). The mean BMI in the ATR group and ankle sprain group was 33.40 (±7.6) and 31.90 (±8.4), respectively, which was not a statistically significant difference (P = .162). When examining patients divided into BMI subclasses, Class 1, containing patients with BMI of 18-25, demonstrated a statistically significant difference between the groups (ATR: n = 3 [5%], Ankle Sprain: n = 21 [19%], P = .020). When examining the incidence of known risk factors for ATR, there was a significant association found in athlete status (P <.001, Table 1). There was no detected difference in the incidence of obesity (BMI >30) between the groups (ATR: n = 31 [55%], Ankle Sprain: n = 58 [52%], P = .744). Thirty ATR patients (53%) and 21 ankle sprain patients (19%) were classified as athletes at the time of injury. Among patients who were athletes at the time of injury, there was a statistical difference in mean BMI (ATR: 29.46 ± 4.51, Ankle Sprain: 26.20 ± 4.59, P = .014, Table 2).
Demographic Overview.
Abbreviation: BMI, body mass index.
Welch’s 2-sample t test.
Mann-Whitney U test; Fisher exact test was performed for all categorical variables.
P values <.05 were considered statistically significant.
Athlete Subgroup Analysis.
Abbreviation: BMI, body mass index.
Mann-Whitney U test.
P values <.05 were considered statistically significant.
Given the statistically significant difference calculated in the preliminary analysis; race, BMI classes, and athlete status were included in a multivariate regression analysis (Table 3). With Caucasian/White patients as the baseline, the model found a statistically significant higher adjusted OR in ATR for African American/Black patients (OR = 4.26, 95% CI: 1.53-11.8, P = .006). Our model was unable to calculate an adjusted OR for the Asian race category, because of insufficient sample size. Within the model, with BMI class 1 (BMI 18-25) as baseline, there was a statistically significant adjusted OR classified for class 2 (OR = 6.77, 95% CI: 1.40-32.9, P = .018), class 3 (OR = 6.89, 95% CI: 1.32-36.0, P = .022), and class 4 (OR = 10.7, 95% CI: 1.99-57.7, P = .006). The model found positive athlete status to be statistically significant (P < .001) with an adjusted OR of 6.00 (95% CI: 2.50-14.4). When assessing between interaction of BMI class and athlete status, there was no statistically significant interaction determined (Table 4); however, there was high collinearity in this model, including unexplained differences in graphing of data, so many CIs could not be calculated.
Multivariate Logistic Regression Model: BMI, Race, and Athlete Status.
Abbreviations: BMI, body mass index; OR, odds ratio.
Because of zero Asian patients being in the ankle sprain group, the model was unable to calculate an odds ratio.
P < 0.05; **P < 0.01; ***P < 0.001.
Multivariate Logistic Regression Model: Interaction of BMI and Athlete Status.
Abbreviations: BMI, body mass index; OR, odds ratio.
P < .05; **P < .01; ***P < .001.
Discussion
We based our study methodology on the study performed by Noback et al, 11 which consisted of 93 ATR and 186 ankle sprain controls in their sample. The mean BMI of their rupture group and ankle sprain group was 27.77 and 26.66, respectively. They concluded that this 1.11 BMI unit difference did not translate into a clinically meaningful result. Additionally, they found there was no correlation between a higher BMI and a sedentary lifestyle in their ATR group, which they attributed to BMI being a suboptimal measure of adiposity in a relatively young, healthy male population. This contradicted prior research that showed patients who sustained ATR often had higher BMIs than the general population. 4 Noback et al concluded that BMI is not a significant risk factor for ATR.
This study assessed possible risk factors for ATR and looked for significant differences between the ATR and ankle sprain groups. A statistically significant difference was detected for class 1 BMI, African American/Black race, and athlete status. It was interesting that our patient population only had a difference in normal weight BMI whereas there was no difference between the higher BMI classes. Race is a poorly understood risk factor, and this study was not designed to examine racial differences in ATR. The logistic regression allowed for control of this variable to further examine other significant factors. Athlete status is a very well-known risk factor for ATR, so it was expected to have this as a significant factor. The multivariate logistic regression model further investigated the relationship among these 3 variables, and they all remained significantly associated with increased ATR.
The results of this study support our hypothesis that there was no statistically significant difference detected between the mean BMI across the 2 groups (P = .162), in line with the Noback et al result. However, when athlete status was isolated, we saw an overall decrease in mean BMI, and a significantly higher BMI in the ATR group (P = .014). It is logical to observe lower mean BMIs in a more athletic population, but the increased BMI for the ATR groups suggests that BMI might have an independent effect on ATR. Although our model on an interaction effect did not demonstrate significance, the high collinearity and small sample necessitate future studies. When looking at the BMI subclasses, we found that normal-weight patients in class 1 (BMI 18-25) had a significantly lower rate of ATRs compared with ankle sprain controls (P = .020), which was further supported by our logistic regression model. This suggests that increased BMI was associated with ATR in our patient population.
A population-based study performed by Ahn et al 1 investigated the association between BMI and ATR in a South Korean population. With access to 31,424 patients who sustained ATR, this robust sample found higher BMIs to be significantly associated with increased risk of ATR. Ahn et al separated patients into the following 4 BMI ranges: less than 18.5, 18.5 to 23, 23 to 25, and 25 plus. It is worth mentioning that the NIH classification acknowledges a BMI of 23 to 24.9 is overweight and BMI >25 is obese for Asian and South Asian populations. 18 This makes the groups in the Ahn study comparable to the groups in our study, which was done in an American population. For ATR patients in the 18.5 to 23 BMI group, there was a hazard ratio of 1.83 compared to a hazard ratio of 3.49 for ATR in obese patients. This means that patients with a BMI greater than 25 had a nearly 2-fold increase in risk for ATR compared to patients in the 18.5 to 23 BMI group. We found similar results in our study, with BMI classes 2, 3, and 4 being associated with increased ATR, but we also had an underrepresentation of ATR patients in the BMI class 1 (18-25) compared with ankle sprains. The Ahn et al study along with our results provide further evidence that there may be a more complex relationship between BMI and ATR.
One explanation for the relationship between increased BMI and risk for ATR may be explained by mechanical forces placed on the Achilles tendon. Acute ATR occurs when the Achilles tendon cannot resist the forces from a sudden calf muscle contraction, which leads to catastrophic rupture of the tendon. Wearing et al 17 found that the mean cross-sectional area of the Achilles tendon was 12% thicker in subjects with a BMI >27.5 compared to subjects with BMI <23. They concluded that the structural changes in the tendon might impair intratendinous fluid movement in response to load due to higher BMI. In obese individuals, the amount of force transferred through the tendon is increased significantly, so the increased forces coupled with the impaired ability to resist these forces puts the tendon at increased risk for rupture. Our study is among the first to show a decreased patient representation for ATR in lower BMI, but further study is needed to determine if this effect is correlated with structural changes in the tendon.
This exploratory study provides pilot data from our select population of ATR patients. Our preliminary results imply there is a unique relationship between ATR and BMI. Given our results, the authors theorize there may be a protective effect in low-BMI patients that is contributing to this underrepresentation in the ATR group. This information could help educate patients at higher BMIs about their risk for ATR while implementing proper prevention strategies such as stretching, allowing time for warm-up and cool-down, wearing supportive shoes, and stopping activity if there is any pain around the Achilles tendon area.12,19 Nevertheless, there is a need for further research to confirm whether there is a protective element associated with a lower BMI in patients who sustain ATR.
Strengths and Limitations
To our knowledge, this is the second case-control study used to examine the association between BMI and ATR. Although this methodology was established by Noback et al, 11 our study revealed potentially novel information regarding ATR and BMI. First, the study population differed from the previous study because of a higher average BMI, which may be explained by the demographic differences in a rural West Texas population. Second, we organized our patients into specific subclasses of BMI values to contextualize our patient population in a more clinically significant way. Third, the use of a logistic regression model helped characterize the independent associations of statistically significant risk factors and ATR.
With respect to limitations, our patient population was from a single tertiary care center treated by a single orthopaedic surgeon, impairing generalizability. Coming from a safety net hospital, our patient population has potentially more severe injuries, more comorbidities, or a lower socioeconomic status than the general population. 2 The decision to use ankle sprains as a control group for ATR also makes it difficult to control for differences in activity level and variability in presentation. Additionally, athletic participation was a patient-reported variable that does not include the frequency and experience each patient has with the sport. All patient data was retrospectively collected, which can result in variations of reporting height and weight for BMI calculation. Lastly, there is inherent limitations related to epidemiologic studies to draw definitive conclusions because of retrospective data collection and potentially limited statistical power. Post hoc power analysis was conducted with an effect size of 0.2 from an estimated Cohen d calculation. To have power at 0.8, this study would need 196 patients, which revealed it to be underpowered. Although this study lacked the statistical power and methodology to show a true relationship between ATR and BMI, we intend our results to act as pilot data for future studies to confirm our results.
Conclusion
The results of this study found that a BMI between 18 and 25 was associated with lower rates of ATR when compared to BMI classes greater than 25. Given the morbidity and significant recovery process associated with ATR, it is important to educate patients on factors that increase their risk of sustaining such an injury. Our data suggests that BMI may be an independent factor associated with ATR, even in patients engaging in sporting activity.
Supplemental Material
sj-pdf-1-fao-10.1177_24730114251327212 – Supplemental material for The Association of Body Mass Index and Achilles Tendon Rupture: A Retrospective Case-Control Study
Supplemental material, sj-pdf-1-fao-10.1177_24730114251327212 for The Association of Body Mass Index and Achilles Tendon Rupture: A Retrospective Case-Control Study by W. Chad Elliott, Alvin Ouseph, Alexander Abraham, Jarrod Martinez and Jerry S. Grimes in Foot & Ankle Orthopaedics
Footnotes
Ethical Approval
Institutional Review Board approval was obtained before retrospective chart review was performed on patients who met inclusion criteria.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Disclosure forms for all authors are available online.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Consent to Participate
Institutional Review Board waived consent requirement because of retrospective design of study.
Data Availability
Data cannot be shared due to inclusion of patient specific information in the data set that could be identifiable to individuals.
References
Supplementary Material
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