Socioecological determinants of health (SEDOHs) are “the conditions in which people are born, grow, live, work and age”¹. The Healthy People 2030 document categorize these factors into five domains including economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social/community context². Barriers to these social circumstances create societal stratification and contribute to disparities at the individual, interpersonal, organizational, and community-level. These barriers disproportionately affect older, rural, and Black patients^3,4. As a result, these vulnerable populations suffer worse overall health^5,6 and outcomes when undergoing surgical procedures^7,8. In Alabama, where 16.2% of the population is impoverished, 26.8% is Black, and 43.6% resides in rural areas⁹, SEDOHs are likely a major contributor to health disparities. However, a knowledge gap exists regarding which SEDOHs are pertinent in rural communities and the linkage between SEDOHs and surgical outcomes.

Surgical outcomes are influenced by multiple factors including healthcare access, health literacy¹⁰, insurance coverage⁴, and social capital¹¹; however, prior studies investigating disparities among surgical populations are limited either by the low number of SEDOHs assessed or by focusing only on individual level factors³. As a result, they may not comprehensively assess the complexity of the problem, especially in rural settings, as geospatial disparities are known to be more complex than rurality alone¹². One reason that many of these studies may not have included comprehensive SEDOH assessments may be due to the challenges of measuring SEDOHs, particularly in resource-constrained settings such as rural hospitals¹³. First, at the patient-level, marginalized populations may lack awareness of which factors may be impacting their overall health and suffer low health literacy, thereby biasing self-reporting SEDOH assessment results¹⁴. Second, at the provider-level, thorough assessment of SEDOHs may be challenging due to staff shortages^15,16. Third, at the system-level, integrating the use of large-scale SEDOH measuring tools^17–19 into the increasingly time-pressured patient-provider consultation may be burdensome. Despite these challenges, it has become increasingly urgent to assess and address SEDOHs within rural communities as health systems transition to value-based care with a more holistic understanding of individual and population health¹⁵.

In an effort to address these challenges, our team recently developed and validated a comprehensive 88-item survey (SEDOH-88)²⁰ that captures individual, interpersonal, organizational, and community domains of SEDOHs. In this paper we primarily aimed to assess SEDOHs across three rural surgical populations in Alabama using the SEDOH-88 survey. Second, we wished to measure the acceptability and feasibility of using the instrument in rural communities. We hypothesized that significant variation in SEDOH measurements would exist across sites but measuring them would be acceptable and feasible.

Of the 178 patients contacted via phone or approached in person from July 2021 to August 2023, 107 (60%) agreed to participate. Sixty-four completed the SEDOH-88 via phone, while an additional 43 were completed in person. Participants comprised 48 (44.9%) from Demopolis, 27 (25.2%) from Alexander City, and 32 (29.9%) from Greenville. The overall median age was 64 (54.5–71.0) years and 65.4% were female. The majority of patients underwent an endoscopic procedure (80.0%), followed by open (14.2%) and minimally invasive surgery (5.9%) (Table 2).

This retrospective study measured and characterized SEDOHs across three rural health facilities in Alabama using the SEDOH-88 survey. High acceptability and feasibility of the survey was found among elderly minority participants across gender, race/ethnicity, and location as 81.5% found it easy to complete and 96.3% agreed that it captured important health-related aspects. Our study demonstrates that the population at Demopolis had significantly worse SEDOHs at every socioecological level compared to Alexander City and Greenville. Specifically, at the individual level, Demopolis had the largest Black population, in addition to the lowest rates of employment, tertiary-level education, and health literacy. At the organizational level, those at Demopolis had the lowest rate of private health insurance and finally, at the community level, those at Demopolis were least likely to have access to transit stops and sidewalks, in addition to lacking recreational facilities, fresh produce and internet access in their community. Together, these findings indicate that while health disparities are ubiquitous in resource-limited areas, significant variability exist among rural surgical populations.

Rural residents have significantly lower health status compared their urban counterparts^30,31 and this is related to increasing age, poor healthcare access, and higher rates of high-risk behavior such as physical inactivity, poor diet, and smoking³². While there are “clear regional patterns of rural disadvantage”³³, our study aligns with Stone et al. who highlights a paradigm shift away from a monolithic approach to rural health research in recognizing the heterogeneity of rural communities³⁴. In terms of individual factors, Demopolis had the oldest population with the lowest rates of employment, tertiary-level education, and health literacy compared to Alexander City and Greenville. It is known that lower education levels and unemployment are associated with poor health, the inability to access high quality nutritious food, and social isolation³⁵. We demonstrated that more than 25% of the overall cohort felt that the fresh produce in their community was not of a high quality, in addition to 50% of the population at Demopolis not having recreational facilities in their neighborhood. While physical activity and healthy eating habits are influenced by self-efficacy³⁶ and behavioral knowledge³⁷, these findings align with previous studies noting that physical inactivity and poor nutrition are influenced by social and economic factors and are more common among individuals with lower socioeconomic status³⁸.

Our study additionally found that the population at Demopolis comprised of disproportionately more Black residents (p<0.001) and had significantly more patients insured with Medicaid (p=0.033) compared to Alexander City and Greenville, respectively. Factors influencing health insurance coverage are complex and affect health seeking behavior³⁹. Both national and state-based analyses of claims data show that individuals insured with Medicaid have lower rates of preventative care such as cancer screening compared to privately insured individuals⁴⁰. These findings have been thought to be influenced by multiple factors including Medicaid enrollees possibly placing a lower value on preventative care than commercially insured individuals⁴¹ and area-level deprivation impacting employment-based coverage, as low-income workers are least likely to be eligible for insurance, rural job categories lacking unionization, and minimal employer contributions towards coverage⁴². Furthermore, Pan et al. investigated differences in cancer-specific mortality (CSM) within insurance subgroups and found that patients insured with Medicaid had a higher risk of death compared to non-Medicaid patients (HR = 1.42; 95% CI, 1.40–1.44; p<0.0001), and after adjusting for multiple covariates including age, sex, area-level, disease site, and insurance status, demonstrated that Black patients had a higher CSM compared to White patients (HR = 1.10; 95% CI, 1.08 – 1.12, p<0.001)⁴. Despite these disparities, the population at Demopolis found it the easiest scheduling medical appointments compared to those at Alexander City and Greenville (p=0.004), a finding that may have been mediated by efforts of the Patient Protection and Affordable Care Act (ACA)⁴³ which included increasing Medicaid payment rates to providers and eliminating out-of-pocket costs for over 40 United States Preventative Services Task Force (USPSTF) recommended services⁴⁰.

While policy reform such as the ACA⁴³ and programs incorporating telemedicine⁴⁴ have helped address disparities in rural communities including specialists’ geographic misdistribution⁴⁵ and low health literacy, inequalities still exist due to a lack of internet access. We noted that while 80% of patients across all three facilities had access to the internet, the population at Demopolis were least likely to have internet access compared to Alexander City and Greenville (p<0.001). As online healthcare information is increasingly being utilized⁴⁶, these underserviced communities cannot leverage the benefits of internet-based health provision and promotion initiatives³⁴. Compounding these tele-communicative barriers are the findings that patients at Demopolis were more likely to always require help reading hospital materials (p=0.007) and felt least confident at completing medical forms independently (p=0.043), highlighting the variability of health literacy across sites, with particular concerns for Demopolis as low health literacy has been associated with a higher incidence of surgical complications¹⁰, longer lengths-of-stay⁸, and increased healthcare costs⁴⁷.

Healthcare access is a major issue in rural communities⁴⁸ and is modulated by structural and logistical factors including distance, travel time, transportation, and affordability^49,50. With respect to transportation, 41.4% of the cohort strongly disagreed to having a bus or train stop within a 10–15-minute walk from their home. Furthermore, significantly more patients at Demopolis strongly disagreed to having sidewalks (p=0.026) and bicycle lanes (p=0.022) in their community compared to Alexander City and Greenville, respectively. These findings support previous publications noting that rural patients face a lack of public transportation, and may travel 59% more miles to receive health care than their urban counterparts^44,51. However, while further travelling distances have been associated with increased cost^52,53, the majority of patients in our study did not delay seeking medical care due to a lack of transportation or travel cost, which may have been mediated by the facilitating effect of a supportive social environment⁵⁰ as patients at Demopolis were more likely to be active church members (p=0.009) and agree to having a close-knit community (p=0.002) compared to Alexander City and Greenville, respectively.

An integral step towards ameliorating health inequality among vulnerable populations is being able to measure the degree of disparities experienced. However, prior studies have reported multiple barriers with respect to survey administration among minority, “hard-to-survey” populations⁵⁴ including rarity of the population⁵⁵, reluctance to participate due to researcher mistrust, in addition to interview difficulty secondary to language barriers or low health literacy. In contrast to these barriers which portend an unfavorable survey climate⁵⁴, we have demonstrated high acceptability and feasibility of the SEDOH-88 among older, rural, and Black patients as 81.5% found it easy to complete and 96.3% agreed that it captured important health-related aspects. These findings underscore the novelty of the SEDOH-88 for measuring SEDOHs in underserved, resource-constrained settings, among populations known to suffer significant disparities^3,4.

Our study findings supports extant literature related to disparities that demonstrates that geographic location matters^56,57 and inequalities vary between different regions within a specific area⁵⁸. We noted significant variation in SEDOHs across sites located within a region of Alabama imbued with economic hardship and disparities. In addition, while previous studies have investigated the “neighborhood effect” on medical conditions in urban areas^59,60, our study addresses the paucity of data on surgical populations in rural areas. While this study primarily aimed to measure and characterize SEDOHs across rural Alabama, future work is planned to assess the associations of these SEDOHs to surgical outcomes.

Our study has several limitations. First, our sample comprised entirely of patients with an average age > 60-years. Consequently, the generalizability of the results to younger or middle-aged rural adults may be limited. Second, while a strength of the study includes that the SEDOH-88 was developed from previously validated sources, the somewhat less extensive, more efficient construction may not have gathered all potentially important SEDOHs. Third, as we intentionally administered the secondary survey assessing acceptability and feasibility to a smaller subset of the overall cohort, specifically racial minority, and elderly participants, we recognize that the results may be biased due to the low number of participants from Greenville (n=6) and Alexander City (n=2), respectively. However, a reassuring observation includes the overall 90.9% positive score for all domains of acceptability/feasibility among those traditionally at highest risk of surgical disparities.

We demonstrated that significant variations in SEDOHs exist across rural communities with respect to individual (education, race, and health literacy), structural (insurance coverage and community involvement), and environmental-level factors (availability of nutritious food, healthcare, and internet access). In addition, the SEDOH-88 was shown to be highly acceptable and feasible for rural populations to measure SEDOHs. These findings show the potential utility of the SEDOH-88 in identifying targets for future disparity-reducing interventions.