The Impact of Community Distress and Social Vulnerability on Outcomes and Length of Stay Following Fibular Fracture Fixation

1. INTRODUCTION

Fibular fractures are a common lower extremity injury, most frequently occurring distally at the level of the lateral malleolus, with particularly high incidence among elderly patients.¹ Postoperative complications, including infection and hardware failure, as well as outcomes such as visual analog scale (VAS) pain scores and length of stay (LOS), are key determinants of recovery and healthcare utilization. Traditional risk stratification models in fracture care have focused primarily on injury severity, surgical factors, and patient comorbidities. However, the contribution of community-level socioeconomic distress to postoperative outcomes remains undercharacterized.

Social determinants of health (SDOH) and socioeconomic status (SES) are increasingly recognized as contributors to variability in surgical outcomes. The distressed communities index (DCI) is a composite measure derived from American Community Survey and U.S. Census data that quantifies economic distress across U.S. communities using seven domains: education, housing vacancy, unemployment, poverty, median income ratio, employment change, and business establishment change.² The social vulnerability index (SVI), also derived from U.S. Census data, was originally developed to identify communities requiring support during disasters and includes four domains: SES, household composition and disability, minority status and language, and housing type & transportation.³ Together, these indices provide standardized, community-level measures of social vulnerability, including income, education, housing stability, employment, and access to transportation.

Prior studies suggest that higher DCI and SVI scores are associated with worse surgical outcomes, although these relationships remain understudied in orthopedic trauma and fibular fractures specifically.⁴ Existing literature has demonstrated associations between social factors and outcomes such as fracture healing, readmission rates, and patient-reported outcomes, but the relationship between these indices and outcomes following fibular fracture repair remains unclear.⁵ Given the high incidence of fibular fractures and the impact of LOS on healthcare resource utilization, further investigation is warranted.

The purpose of this retrospective study was to evaluate the association of SVI and DCI with postoperative infection, VAS pain scores, LOS, and hardware failure following open reduction and internal fixation of fibular fractures. It was hypothesized that higher SVI and DCI scores would be associated with worse postoperative outcomes following fibular fracture repair.

2. MATERIAL AND METHODS

2.3 Data collection

Demographic and clinical information, including age, sex, race, ethnicity, BMI, comorbidities, and substance use history were extracted from the electronic health record using a standardized data extraction protocol. Patient SVI and DCI scores were collected from publicly available centers for disease control (CDC) and economic innovation group databases using patients’ residential zip codes. Overall SVI scores and scores for each SVI subdomain were recorded, including SES, household characteristics, racial and ethnic minority status, and housing type & transportation vulnerability.

Frequency distributions of SVI and DCI scores were generated, and patients were stratified into risk groups based on the distribution characteristics of each index. SVI scores were categorized using national quartiles, with low risk being defined as the first three quartiles, and high risk being defined as the top quartile [Figure 1]. DCI scores were stratified by tertiles within the cohort, with high-risk DCI defined as the top tertile, and low risk DCI defined as the lower two tertiles [Figure 2]. The use of differing cutoff methods reflects both the underlying score distributions and established conventions in the literature. Specifically, the ≥0.75 (top-quartile) threshold for high SVI aligns with CDC/ ATSDR recommendations and prior surgical studies.^3,7,8 In contrast, national DCI categories were not applied because relatively few patients in this single-institution cohort resided in communities classified as “Distressed.” Instead, cohort-specific tertiles were used to ensure adequate group sizes while capturing relative differences in community socioeconomic distress within the study population. This approach is consistent with prior surgical and orthopedic literature utilizing DCI as a zip code–level measure of community socioeconomic distress in outcomes research.^9,10

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Figure 1: Frequency distribution of social vulnerability index (SVI) for patients included in the study, categorized into low and high-risk SVI categories.

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Figure 2: Frequency distribution of distressed communities index (DCI) for patients included in the study, categorized into low risk and high-risk DCI categories.

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2.5 Statistical analysis

Univariate analyses were performed using Chi-squared or Fisher’s exact for categorical outcomes and independent t-tests for continuous outcomes. Multivariate logistic regression was utilized for adjusted analyses of binary outcomes, controlling for age, sex, body mass index (BMI), coronary artery disease (CAD), alcohol use, drug use, and procedure length. VAS pain scores were analyzed using a multivariable linear regression model, adjusting for the same covariates. All hospital encounters, including those with an LOS < 1 day, were retained for the unadjusted analyses to preserve the full clinical spectrum of ED and short-stay admissions. However, because of this inclusion, the LOS distribution was highly right-skewed. Therefore, to improve multivariable regression model stability, adjusted analysis for LOS was restricted to encounters with LOS ≥ 1 day, using a gamma regression with a log link. This approach allowed for a more stable and interpretable model while still maintaining a complete representation of the cohort in unadjusted results. Adjusted regression results are presented in forest plot form [Figure 3], with full model outputs provided in Supplemental digital content [Tables 1–4].

Supplementary Table 1

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Supplementary Table 2

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Supplementary Table 3

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Supplementary Table 4

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Figure 3: Multivariate regression forest plots demonstrating adjusted associations between clinical and demographic predictors and (a) postoperative complications, (b) hardware failure, (c) length of hospital admission, and (d) visual analog scale (VAS) pain scores. Adjusted odds ratios, adjusted mean ratios, and adjusted β coefficients are displayed with corresponding 95% confidence intervals depending on regression model type. For postoperative complications and hardware failure, multivariable logistic regression was used. DCI: Distressed communities index, SVI: Social vulnerability index, SD: Standard deviation, BMI: Body mass index.

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3. RESULTS

4. DISCUSSION

The influence of social determinants of health on patient outcomes has gained increasing attention, with growing evidence suggesting that socioeconomic vulnerability affects outcomes across a broad range of medical disciplines.^7-9 Although existing orthopedic literature links social deprivation to poor surgical outcomes such as postoperative infection, slow fracture healing, and high rates of readmission, the relationship between community-level SES, social vulnerability, and postoperative outcomes after fibular fracture fixation remains poorly characterized in literature.^5,11

This study demonstrated a significant association between high-risk DCI and prolonged LOS. In a Level I trauma setting, fibular fractures frequently occur in the context of polytrauma. Therefore, prolonged LOS in high-risk populations may partly reflect greater overall injury burden, suggesting that socioeconomic disadvantage may be associated with more complex injury patterns. Although overall SVI risk was not associated with the measured postoperative outcomes, higher vulnerability within the SVI housing characteristics and housing type & transportation subdomains was also associated with increased LOS. Additionally, procedure length independently predicted postoperative infection/complication, prolonged LOS, and hardware failure. While DCI was not independently associated with these adverse outcomes after adjustment, patients in the high-risk DCI cohort underwent significantly longer procedures than those in the low-risk cohort.

These findings align with prior studies demonstrating the impact of community-level SES on postoperative LOS across multiple orthopedic populations. A retrospective cohort study evaluating the relationship between DCI and elective posterior cervical decompression and fusion identified residence in a distressed community as an independent predictor of prolonged hospitalization.¹⁰ Another study found that higher DCI was associated with increased LOS following total joint arthroplasty after risk adjustment, although it was not associated with other measured postoperative complications.¹² Similarly, high SVI has been associated with prolonged LOS following both total knee arthroplasty and elective lumbar fusion.^13,14

Notably, the present study, as well as studies by Chandrashekar et al^.12 and Rahman et al.¹³ demonstrated a significant relationship between increased social deprivation and prolonged LOS in the absence of associations with other postoperative complications.^12,13 These findings suggest that patients who are otherwise medically ready for discharge may face nonmedical barriers to safe discharge planning that prolong hospitalization. The observed association between increased LOS and the SVI subdomains of housing characteristics and housing type & transportation further supports this interpretation, as housing instability and limited transportation access may contribute to delayed discharge. Collectively, these findings highlight the importance of targeted care coordination and discharge planning interventions for patients residing in socioeconomically deprived communities.

The findings of this study are corroborated by prior literature demonstrating that prolonged operative duration is associated with increased postoperative complications across multiple surgical specialties. Meta-analyses have shown a near doubling in complication risk for procedures exceeding 2 hours of operative time.^15,16 Daley et al.¹⁷ found that increased operative time was associated with nearly all common postoperative complications following major surgery, with the greatest marginal increase in risk observed for sepsis. Similarly, Cheng et al.¹⁵ identified operative duration greater than 2 hours as an independent risk factor for surgical site infection and overall complications. Additional analyses of nearly 300,000 general surgical procedures demonstrated independent associations between longer operative time, postoperative infection, and prolonged hospitalization.^15,16,18

Orthopedic-specific literature has similarly demonstrated associations between prolonged operative time and adverse outcomes following total joint arthroplasty, hip fracture fixation, and joint arthroscopy, including increased rates of reoperation, infection, transfusion requirement, and extended hospitalization.^19-23 Although increased LOS was the only outcome directly associated with DCI in the present study, patients in the high-risk DCI cohort also underwent significantly longer procedures. This may reflect differences in injury complexity, baseline health status, access to care, or other unmeasured social and clinical factors associated with community socioeconomic deprivation. Given that operative duration independently predicted postoperative infection/ complication, prolonged LOS, and hardware failure, these findings suggest that the relationship between community socioeconomic distress and adverse postoperative outcomes may be partially mediated by procedural complexity and related confounders. Collectively, the results of this study and previous literature support consideration of operative duration in postoperative risk stratification and patient counseling, particularly among patients from socioeconomically distressed communities, and suggest that operative efficiency may represent a modifiable risk factor.

5. LIMITATIONS

This study should be interpreted within the context of several limitations. First, this was a retrospective study conducted at a single Level I trauma center, which may limit generalizability to institutions with different patient populations, referral patterns, and operative practices. Additionally, adverse events were limited to those documented within the institutional electronic medical record, and complications treated at outside institutions may not have been captured.

Second, although the ICD coding criteria were selective for fibular diaphyseal and distal fibular/lateral malleolus fractures, fracture-specific characteristics such as fracture severity, open versus closed injury status, degree of comminution, and soft tissue injury were not evaluated. Patients with isolated fibular fractures and those with polytrauma were analyzed together without stratification by overall injury burden, and the observed lengths of stay likely reflect the elevated acuity associated with polytraumatic presentations.

The retrospective design limits the ability to establish causality between community-level socioeconomic indices and postoperative outcomes. Although multivariable regression was used to adjust for potential confounders, residual confounding may remain. Furthermore, the zip code–level measures used in this study may not accurately reflect individual SES, introducing the potential for ecological fallacy and misclassification bias. While the study was designed to evaluate community-level socioeconomic distress rather than individual SES, important patient-level socioeconomic variables, including insurance status, income, education, employment, housing instability, transportation access, and social support, were unavailable and may influence postoperative recovery. Additionally, specific barriers to discharge or differences in discharge disposition were not evaluated, potentially contributing to variation in LOS.

Despite these limitations, this study provides novel insight into the relationship between community-level socioeconomic distress and postoperative outcomes following fibular fracture fixation. These findings highlight the potential importance of targeted discharge planning and perioperative support strategies for socially vulnerable patient populations. Future studies should incorporate fracture complexity measures, individual-level socioeconomic variables, and multicenter validation to further characterize these relationships.

6. CONCLUSION

In this retrospective cohort of patients undergoing fibular fracture fixation, residence in areas with high-risk DCI was independently associated with prolonged hospital LOS in unadjusted analysis, but did not remain statistically significant after adjustment. The overall SVI was not associated with postoperative complications. However, increased vulnerability within the SVI housing characteristics and housing type & transportation subdomains was associated with longer hospitalization, suggesting that specific social factors may influence discharge readiness. Procedure length was an independent predictor of infection, hardware failure, and prolonged LOS, and was greater among patients from high-risk DCI communities. Although community-level distress was not directly associated with increased complication rates, its association with operative duration may reflect indirect or downstream effects of socioeconomic disadvantage. Overall, community-level deprivation appears to primarily impact LOS and healthcare utilization rather than short-term surgical complications. These findings support the role of targeted discharge planning and perioperative optimization strategies to reduce prolonged hospitalization in socially vulnerable populations.