Invited Review

Social Determinants of Health and Spine Surgery Outcomes: A Literature Overview

Vahe Yacoubian, MD, MPH

Loma Linda University Medical Center Loma Linda, CA

Adelin Tulcan

Loma Linda University School of Medicine Loma Linda, CA

Olumide Danisa, MD

Duke University Medical Center Durham, NC

Key Takeaways

  • Social determinants of health (SDoH) substantially influence access, presentation severity, perioperative outcomes, and recovery after spine surgery.
  • Spine literature demonstrates consistent associations between socioeconomic disadvantage and worse baseline disability, increased complications, prolonged length of stay, and reduced patient-reported outcome completion.
  • Area-level indices such as the Social Vulnerability Index (SVI), Area Deprivation Index (ADI), Distressed Communities Index (DCI), and Social Deprivation Index (SDI) provide scalable methods to operationalize SDoH in spine research and clinical workflows.
  • Recent spine-specific studies show that social vulnerability affects outcomes and utilization patterns but should not be interpreted as a determinant of surgical futility.
  • Integrating SDoH awareness into preoperative planning offers an opportunity to improve equity through targeted support rather than altered surgical indications.

Introduction

Outcomes following spine surgery are traditionally evaluated through anatomical and procedural variables, such as diagnosis, comorbid disease burden, surgical approach, and perioperative complications. However, recovery after spine surgery occurs within a broader social context that shapes access to care, health behaviors, and the ability to engage in postoperative rehabilitation. Increasing evidence indicates that social determinants of health (SDoH) exert independent, clinically meaningful influence on outcomes following spine surgery. SDoH include factors such as socioeconomic status, education, housing stability, neighborhood environment, transportation access, and social support systems.1 These determinants influence when patients present for care, the severity of disease at presentation, adherence to postoperative restrictions, and long-term functional recovery.2 In spine surgery—where outcomes often depend on sustained engagement with physical therapy, pain management, and follow-up care—these social factors may be particularly impactful.3

Historically, SDoH have been difficult to integrate into surgical decision-making due to challenges in measurement and standardization. As a result, spine outcomes research has relied heavily on administrative comorbidity indices and physiologic risk stratification tools that do not fully capture social risk.4 To address this gap, investigators have increasingly adopted area-level socioeconomic indices as pragmatic proxies for social vulnerability. These tools enable linkage of patient residence to publicly available census and economic data, facilitating population-level assessment of social risk in spine cohorts.5

Understanding the social determinants of health in spine surgery is not merely an academic exercise—it is a practical pathway to improving outcomes by examining patient backgrounds in a holistic context. Social risk shapes modifiable barriers that often determine whether an operation translates into recovery: the ability to attend follow-up visits, secure transportation, obtain medications, adhere to restrictions, and participate consistently in rehabilitation. When social vulnerability is measured and studied systematically, it can inform more accurate preoperative counseling and risk stratification, as well as trigger targeted supports. In this way, SDoH data can move beyond describing disparities to guiding interventions, aligning resources with need, and ultimately helping patients achieve safer recoveries and more durable functional gains after spine surgery.

This invited review synthesizes the expanding literature on SDoH in spine surgery, beginning with foundational evidence linking socioeconomic disadvantage to spine outcomes and progressing to contemporary applications of composite indices such as the Social Vulnerability Index (SVI), Area Deprivation Index (ADI), Distressed Communities Index (DCI), and Social Deprivation Index (SDI).

Discussion

Social Determinants and Spine Surgery Outcomes: Access to Spine Care and Timing of Presentation

Multiple studies demonstrate that socioeconomic disadvantage is associated with delayed access to specialty spine care and increased disease severity at presentation. Patients from lower-income or underinsured backgrounds are less likely to receive timely imaging, specialist referral, or elective intervention for degenerative spine conditions.6 These delays may contribute to worse neurologic compromise, higher baseline pain, and reduced functional reserve at the time of surgery.7 Geographic and transportation barriers further exacerbate disparities in spine care access, particularly for patients living in medically underserved or rural communities. Longer travel distances and limited access to subspecialty surgeons have been associated with delayed operative intervention and increased reliance on emergency care for spine-related conditions.

Socioeconomic Status and Baseline Disability

Socioeconomic disadvantage has been consistently linked to worse baseline patient-reported outcomes in spine populations. Lower income, reduced educational attainment, and unemployment correlate with higher pain intensity, greater disability, and worse health-related quality of life prior to surgery.8 These disparities persist even after adjustment for radiographic severity and comorbid disease.9 Health literacy also plays a critical role, as patients with spinal conditions who have limited health literacy demonstrate poorer understanding of surgical expectations, reduced adherence to postoperative instructions, and lower completion rates of patient-reported outcome measures.10 These factors may influence both perceived and objective outcomes after surgery.11

Postoperative Outcomes and Utilization

Beyond baseline differences, the utilization patterns reported in the spine literature suggest that SDoH shape postoperative trajectories through structural barriers that extend beyond intraoperative factors. Holbert et al found that socioeconomically disadvantaged patients undergoing lumbar spine surgery experienced longer hospital stays, were more frequently discharged to skilled nursing facilities, and had higher rates of readmission or emergency department utilization.12 Using a large Medicare claims analysis, Engler et al similarly demonstrated that community-level disadvantage is associated with postoperative safety and utilization disparities across spine procedures, including both cervical and lumbar operations such as decompression and fusion.4 Notably, the persistence of these associations after adjustment for age, comorbidities, and surgical complexity supports the interpretation that “social risk” contributes independently to recovery and resource needs rather than merely reflecting greater medical frailty.12,13 This aligns with broader evidence on surgical outcomes from Diaz et al, who showed that county level social vulnerability is associated with worse postoperative outcomes—particularly among minority patients—reinforcing the importance of measuring social context when interpreting spine surgery outcomes and designing postacute support pathways.13

Area-Level Indices as Proxies for Social Determinants of Health: Rationale for Area-Level Measures

Area-level indices leverage census and economic data to approximate the social environment in which patients live. While they do not capture individual circumstances, they provide scalable, standardized metrics that can be applied across large datasets and health systems.14 These tools are particularly attractive for spine research using administrative databases and electronic health records.15 Among the most commonly used indices in spine surgery literature are the SVI, ADI, DCI, and SDI.

Across the literature, these indices have been validated as meaningful area-level proxies for risk stratification and disparities research across surgical and nonsurgical domains. To provide a few examples, ADI has been linked to postoperative outcomes and resource utilization after major joint procedures (eg, higher complication risk after total hip arthroplasty) and has also shown construct validity by correlating with self-reported socioeconomic measures and baseline functional status in orthopedic outpatient surgical populations.16,17 In general surgery and broader perioperative research, SVI has been used as a standardized proxy for social risk and is associated with worse postoperative outcomes across large surgical cohorts, supporting its use in comparative outcomes research when individual-level SDoH are unavailable.18 In orthopaedic surgery, SVI-based analyses in arthroplasty and fracture populations similarly show higher vulnerability tracking with worse outcomes, reinforcing its external validity within musculoskeletal care.19,20 DCI has been validated in cardiac and other surgical fields as a community-level distress metric associated with operative outcomes and postoperative resource use, including coronary artery bypass grafting (CABG) outcomes and bariatric surgery utilization, supporting its role as a complementary socioeconomic signal distinct from purely medical risk.21

Social Vulnerability Index (SVI)

The SVI, developed by the Centers for Disease Control and Prevention, incorporates 16 census variables grouped into four domains: socioeconomic status, household composition, minority status and language, and housing and transportation. An overall SVI score is calculated as the aggregate percentile of its four subdomain components. Each of the four SVI domains has been validated as a predictor of population vulnerability to adverse events.22,23 The socioeconomic status domain incorporates five variables: percentage of individuals living below 150% of the federal poverty level, unemployment, housing cost burden, lack of a high school diploma, and absence of health insurance. The household characteristics domain includes age ≥65 years, age ≤17 years, civilian disability status, single-parent households, and limited English proficiency. Racial and ethnic minority status is determined by the proportion of residents who identify as Hispanic or Latino (of any race), Black or African American, Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, individuals reporting two or more races, or other races. The housing type and transportation domain consists of five measures: multiunit housing, mobile homes, household crowding, lack of vehicle access, and residence in group quarters. Higher scores indicate greater relative vulnerability compared with other US census tracts.24 Figure 1 displays the metrics and subdomains used to calculate SVI.24

Recent spine-specific studies have demonstrated significant associations between higher SVI and adverse perioperative outcomes. Patients undergoing elective lumbar fusion from high-SVI communities experienced longer lengths of stay and higher rates of pulmonary and cardiac complications compared with lower-SVI counterparts.25 Other investigations have linked higher SVI to worse postoperative physical function, higher pain interference, and reduced likelihood of achieving minimum clinically important difference following lumbar fusion.8 Additionally, higher SVI has been associated with lower completion rates of patient-reported outcome measures in spine clinics, limiting longitudinal assessment and potentially masking disparities.26 Compared with other indices, SVI offers the advantage of capturing multiple dimensions of vulnerability, including household structure and transportation access, which may be particularly relevant to postoperative recovery.27

Figure 1. 2024 CDC ATSDR Social Vulnerability Index Variables and Themes

SVI factor/domain
Variables used in the SVI
What the variables represent
Socioeconomic Status
1. Below 150% poverty
2. Unemployed
3. Housing cost burden 4. No high school diploma 5. No health insurance
Poverty, employment, housing affordability, educational attainment, and insurance-related access to resources
Household Characteristics
6. Aged 65 years and older
7. Aged 17 years and younger 8. Civilian with a disability 9. Single-parent households 10. English language proficiency
Age dependency, disability, household composition, caregiving burden, and language-related barriers
Racial and Ethnic Minority Status
11. Racial and ethnic minority status, including:
  • Hispanic or Latino of any race
  • Black or African American, not Hispanic or Latino
  • Asian, not Hispanic or Latino
  • American Indian or Alaska Native, not Hispanic or Latino
  • Native Hawaiian or Pacific Islander, not Hispanic or Latino
  • Two or More Races, not Hispanic or Latino
  • Other Races, not Hispanic or Latino
Population groups more likely to experience structural inequities, barriers to care, and unequal access to resources
Housing Type and Transportation
12. Multiunit structures 13. Mobile homes 14. Crowding 15. No vehicle 16. Group quarters
Housing density, housing type, household crowding, transportation access, and institutional or group living conditions

Area Deprivation Index

ADI is a neighborhood-level measure of socioeconomic disadvantage that was originally developed to quantify the cumulative effects of material deprivation on health outcomes. It is derived from 17 US Census variables obtained from the American Community Survey and is calculated at the census block group level, which provides a finer geographic resolution than census tracts. These variables are grouped into four conceptual domains: income, education, employment, and housing quality. Each variable reflects a dimension of material deprivation that has been independently associated with adverse health outcomes.28 Unlike broader vulnerability indices that incorporate demographic or household-structure variables, the ADI focuses specifically on socioeconomic and housing-related disadvantage, making it particularly well-suited to studying structural inequities related to income, education, employment, and living conditions. Figure 2 visualizes the components of the ADI as it combines neighborhood-level socioeconomic indicators related to education, income, employment, housing, and household resources into a composite measure of area deprivation.

It has been widely applied in health services research and orthopedic surgery.27 In spine populations, higher ADI has been associated with increased readmissions, prolonged hospitalization, and worse postoperative pain outcomes following cervical and lumbar surgery.29 Several studies demonstrate that patients in the most deprived ADI quartiles are less likely to achieve meaningful improvements in pain and function after lumbar fusion.30 However, comparative studies suggest that ADI may be less sensitive than SVI in identifying specific vulnerability domains that influence spine outcomes.9 This limitation has prompted interest in using ADI alongside other indices rather than as a stand-alone measure.

Figure 2. Area Deprivation Index Factors, Variables, and Description

ADI factor/domain
Variables used in the ADI
What the variables represent
Education

1. Percent of population age 25 or older with less than 9 years of education

2. Percent of population age 25 or older with at least a high school diploma

Educational attainment and long-term socioeconomic opportunity
Income/employment

3. Median family income

4. Income disparity

5. Percent of families below the federal poverty level

6. Percent of population below 150 percent of the federal poverty level

7. Percent of civilian labor force age 16 or older unemployed

8. Percent of employed population age 16 or older in white-collar occupations

Income, poverty, occupational status, and labor-market participation
Housing
9. Median home value
10. Median gross rent
11. Median monthly mortgage
12. Percent of owner-occupied housing units
13. Percent of occupied housing units without complete plumbing
14. Percent of households with more than one person per room
Housing wealth, housing cost, tenure, housing quality, and crowding
Household characteristics and material resources

15. Percent of single-parent households with children under age 18

16. Percent of households without a motor vehicle

17. Percent of households without telephone service in historical ADI versions; newer Neighborhood Atlas ADI releases use percent of households without internet access

Family structure and access to household resources, communication, and transportation

Distressed Communities Index

DCI is a composite, area-level economic metric developed by the Economic Innovation Group to characterize the relative economic well-being of US communities based on structural measures of growth, employment, and financial stability. Unlike indices such as the SVI or ADI, which emphasize household characteristics and social vulnerability, the DCI focuses more narrowly on macroeconomic conditions and economic opportunity within a given geographic area, typically at the zip code or county level. The index incorporates seven economic indicators, including the percentage of adults without a high school diploma, housing vacancy rate, unemployment rate, poverty rate, median household income relative to state averages, change in employment, and change in the number of business establishments over time, allowing it to capture both static deprivation and longitudinal economic decline. DCI scores are ranked nationally and used to classify communities into five categories—prosperous, comfortable, midtier, at risk, and distressed—with higher distress reflecting sustained economic disadvantage and stagnation.31 Figure 3 displays the components of the DCI as it combines seven equally weighted indicators into a single community distress score from 0 to 100. The score is based on average percentile rank across the indicators. Lower scores indicate higher economic well-being; higher scores indicate deeper distress.

Lambrechts and colleagues examined the DCI, SVI, and ADI in cohorts undergoing cervical and lumbar spine surgery to assess the relationship between community-level economic distress and surgical outcomes. They found that patients residing in more economically distressed communities demonstrated significantly worse baseline pain scores, higher disability indices, and poorer preoperative functional status, suggesting that economic distress is strongly associated with disease severity at presentation.32 These findings are consistent with prior spine literature demonstrating that patients from economically disadvantaged communities often present later in the disease course, with higher baseline disability and reduced functional reserve, likely reflecting barriers to timely access to specialty spine care.6,33 Similarly, Tarazi and colleagues evaluated socioeconomic and community-level factors associated with unexpected hospital admission following lumbar spine laminectomy and found that while markers of social and economic disadvantage were associated with differences in care utilization patterns, they were not independent predictors of adverse postoperative outcomes after adjustment for clinical variables.34 This reinforces the concept that economic distress influences how and when patients access care, but does not necessarily translate into inferior short-term surgical results.

Figure 3. Distressed Communities Index Factors, Variables, and Description

DCI factor/domain
Variables used in the DCI
What the variables represent
Education

1. No high school diploma: share of adults age 25+ without a high school diploma or equivalent

Educational attainment and constrained economic opportunity
Housing market/ neighborhood stability

2. Housing vacancy rate: share of habitable housing that is unoccupied, excluding seasonal or recreational use

Neighborhood demand, property-market strength, and infrastructure stability
Employment/
labor-force attachment
3. Adults not working: share of prime-age adults age 25-54 who are not currently employed
Unemployment plus labor-force detachment among working-age adults
Poverty

4. Poverty rate: share of the population living below the federal poverty line

Direct material deprivation and low household resources
Income/ relative prosperity
5. Median income ratio: local median household income as a percentage of the area median, using the metro area or state as the comparison area
Relative income position while accounting for regional differences
Labor-market dynamism
6. Employment change: percent change in the number of jobs over the past five years
Growth or decline in local job opportunities
Business dynamism
7. Business establishment change: percent change in the number of business establishments over the past five years
Growth or decline of the local business ecosystem

Social Deprivation Index

SDI is utilized to measure area-level deprivation based on seven demographic characteristics derived from the American Community Survey, analogous to DCI. Unlike DCI's strictly economic approach, SDI focuses on the impact of socioeconomic variations on health outcomes. The index aggregates at four geographic levels—county, census tract, aggregated ZIP Code Tabulation Area, and Primary Care Service Area—to quantify SDoH across both localized neighborhoods and service-based regions. SDI incorporates the proportions of individuals living in poverty, adults with less than a high school education, single-parent households, households renting or overcrowded, households without access to a vehicle, and nonemployed adults under 65 years of age.35 The score is calculated on a scale from 0 to 100, with 0 indicating low distress and 100 indicating high distress. Figure 4 visualizes the seven components of the SDI. The SDI combines these components into an area-level deprivation score using factor analysis and weighted factor loadings. Higher SDI scores indicate higher levels of social deprivation.

Primarily used in specialties such as primary care and epidemiology, SDI has received limited research attention in orthopaedic surgery. Hejazi-Garcia and colleagues studied the association between SDI and lumbar spine surgery outcomes, indicating that high SDI values were associated with longer length of stay.36 In a comprehensive study assessing the variance among nine composite indices of social determinants of health, SDI and SVI were found to be positively correlated, with similar patterns in life expectancy.37 Additionally, Brodeur and colleagues examine social disparities in conjunction with surgeon volume and find that low-volume surgeons were more likely to treat patients from areas with higher SDI scores. Low-volume surgeons in the study were treating a patient population with an increased overall SDI due to negative social determinants of health.38

Figure 4. Social Deprivation Index Factors, Variables, and Description

SDI factor/domain
Variables used in the SDI
What the variables represent
Poverty

1. Percent population living below 100 percent of the federal poverty level

Material deprivation and limited household economic resources
Education

2. Percent population age 25 or older with less than 12 years of education

Educational attainment and barriers to opportunity
Employment/ labor-force attachment
3. Percent nonemployed population ages 16-64, including people unemployed or not in the labor force
Labor-market disadvantage and reduced employment access
Housing tenure

4. Percent households living in renter-occupied housing units

Housing tenure, residential security, and housing-market disadvantage
Housing crowding
5. Percent households living in crowded housing units: crowded means occupants per room are greater than or equal to 1.01
Housing adequacy, household crowding, and constrained living conditions
Family structure
6. Percent single-parent families with dependents younger than 18 years
Family structure and potential caregiving or economic strain
Transportation access
7. Percent households with no vehicle
Transportation access and ability to reach work, care, and community resources

Interpreting Social Risk in Spine Surgery

Collectively, the literature suggests that SDoH and area-level indices influence presentation severity, perioperative risk, and health care utilization, but they do not reliably predict the degree of symptomatic improvement after surgery.3 This distinction is critical. Social vulnerability should not be interpreted as a marker of poor surgical candidacy. Rather, it identifies patients who may require additional perioperative support. In practice, linking patient addresses to SVI or ADI data within the electronic health record can flag patients at increased social risk. These patients may benefit from early care coordination, social work involvement, discharge planning, and tailored education. Such interventions aim to mitigate risk without altering surgical indications.39

Area-level indices are subject to ecological fallacy and may misclassify individual risk.40 Significant heterogeneity exists within census tracts, and individual circumstances may diverge from community averages.7 Additionally, different indices capture overlapping but distinct constructs, complicating direct comparison. Therefore, selecting an index that captures the most relevant underlying factors is essential to ensure that the dimensions of deprivation most pertinent to orthopaedic analysis are accurately assessed. These tools should therefore complement—not replace—clinical judgment and individualized assessment.

Conclusion

Social determinants of health exert a measurable influence on outcomes, access, and utilization in spine surgery. Foundational spine literature demonstrates that socioeconomic disadvantage is associated with worse baseline disability, increased complications, and prolonged recovery. Area-level indices such as SVI, ADI, DCI, and SDI provide pragmatic tools to operationalize social risk, with SVI offering the broadest multidimensional framework. Integrating these measures into spine care pathways offers an opportunity to improve equity by providing targeted support rather than restricting access to surgical care.

Building on these findings, future spine outcomes work should treat social risk not as a confounder but as a clinical signal that helps explain why patients present with different severity, follow different recovery trajectories, and use postoperative services differently—even when diagnosis, comorbidity burden, approach, and complications are comparable. A consistent message across the reviewed literature is that SDoH shape access to care, timing and severity at presentation, adherence to postoperative restrictions, and engagement in rehabilitation and follow-up, all of which are central determinants of functional recovery in spine surgery. Accordingly, incorporating an SDoH metric, such as SVI/ADI/DCI or SDI, into research and care pathways can support more realistic counseling and planning while enabling targeted supports that improve equity without compromising surgical candidacy. Important underdeveloped domains for future study include: (1) procedure- and episode-specific risk prediction that combines social indices with disease severity, surgical complexity, and patient-reported outcomes; (2) subspecialty and setting heterogeneity, such as deformity, tumor, infection, trauma, and outpatient/ambulatory spine surgery; and (3) system-level and policy interfaces—bundled payments, post-acute network design, and quality metrics—to ensure value-based spine care does not inadvertently penalize hospitals and surgeons caring for vulnerable communities.

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Author Disclosures

V Yacoubian: Nothing to disclose

A Tulcan: Nothing to disclose

O Danisa: Speaking and/or Teaching Arrangements: MTF (H); Trips/Travel: American Board Of Orthopaedic Surgeons (Travel Expense Reimbursement).

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