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. Author manuscript; available in PMC: 2025 Dec 1.
Published in final edited form as: Dis Colon Rectum. 2024 Sep 10;67(12):1515–1526. doi: 10.1097/DCR.0000000000003425

Social Determinants of Health in Diverticulitis: A Systematic Review

Thomas E Ueland 1, Praveen Vimalathas 1, Raeshell S Sweeting 2, Megan M Shroder 3, Samuel A Younan 3, Alexander T Hawkins 3
PMCID: PMC11891087  NIHMSID: NIHMS2020280  PMID: 39254206

Abstract

BACKGROUND:

There is growing interest in social determinants of health for surgical populations. Within diverticulitis, no systematic collation of available evidence has been performed.

OBJECTIVE:

To assess frequency, variety, and association directions for social determinants of health in colonic diverticular disease.

DATA SOURCES:

Four electronic databases were queried: PubMed, Embase, Cochrane, and Web of Science.

STUDY SELECTION:

Included studies reported symptomatic left-sided colonic diverticular disease with respect to a social determinant of health according to the Healthy People 2030 initiative or applicable proxy variable. Studies with non-English full text, cohort size fewer than 50, pediatric cohorts, and exclusively non-left sided disease were excluded.

MAIN OUTCOME MEASURES:

Quality assessment through modified Newcastle-Ottawa scale, frequency of variables reported, and effect size trends for common comparisons.

RESULTS:

Among 50 included studies, 40 were good and 10 were fair in quality. Social determinants of health in diverticulitis were identified across Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context domains. The two most common variables were self-reported race and ethnicity (n = 33) and insurance (n = 22). Among 18 unique studies reporting comparisons of white versus any other self-reported race and ethnicity, twelve identified a disparity disadvantaging non-white groups with effect sizes (95% confidence interval ranging from 1.23 [1.10 −1.37] to 5.35 [1.32 – 21.61]). Among 15 unique studies reporting a non-private versus private insurance comparison, nine identified non-private insurance as a risk factor with effect sizes (95% confidence intervals ranging from 1.15 [1.02 – 1.29] to 3.83 [3.01 – 4.87]).

LIMITATIONS:

Retrospective studies, heterogeneity across cohort and variable definitions.

CONCLUSIONS:

Social determinants of health domains are associated with a variety of diverticulitis outcomes. Additional studies are needed to address infrequently reported domains and identify optimal strategies for intervening in clinical settings.

PROSPERO ID:

CRD42023422606

Keywords: Social determinants of health, health equity, diverticular disease, diverticulitis

INTRODUCTION

Diverticulitis is a common gastrointestinal disorder accounting for 250,000 admissions and $3 billion in health care costs annually.1 Among patients with acute diverticulitis, 5% to 25% have complicated disease through macro-perforation, abscess, fistula, or stricture. The burden of recurrent symptoms or disease progression requiring operative intervention accounts for substantial detriment to patient quality of life. Numerous clinical predictors for diverticulitis outcomes have been established,2 with growing interest around associations between social variables and diverticulitis outcomes.

Social determinants of health are defined by the United States Department of Health and Human Services as “environments where people are born, live, learn, work, play, worship, and age.”3 The Healthy People 2030 Initiative categorizes social determinants of health into five domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context.3 Given difficulty in capturing individual-level social determinants, proxy variables are frequently relied upon. For example, race has previously been used as a poor yet available proxy for the social determinant of systemic or internalized racism.4 In a surgical setting, social factors exert influence at multiple points of a patient’s care trajectory including access to surgical specialists, severity of initial presentation, treatment selection, and postoperative outcomes. While explored in other colorectal pathologies, to our knowledge no systematic collation of social determinants of health or racial disparities has been performed in diverticular disease.5,6

This review sought to summarize existing primary studies of adult patients with left-sided colonic symptomatic diverticular disease reporting a social determinant of health. Our primary aims were a) to assess the frequency of these variables in the diverticulitis literature and b) to qualitatively examine trends for commonly reported comparisons.

METHODS

The systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines,7 including registration with the International Prospective Register of Systematic Reviews (PROSPERO ID CRD42023422606).

Literature Search

Search Strategy

The search strategy was informed by a clinical subject matter expert (A.T.H) with review from a trained medical librarian (R.L.W). It included terms to identify diverticular disease and social determinants from the Healthy People 2030 domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context (Supplementary File 1 at https://links.lww.com/DCR/CXX). As the domains are unable to be directly measured in studies, we selected representative proxy variables including health insurance, distance from care provider, income, employment, housing instability, language, literacy, social support, neighborhood deprivation indices, geographic variation, population density or rurality, and self-reported race and ethnicity. The search strategy was applied to PubMed (National Library of Medicine), Embase (Elsevier), Cochrane Library (Wiley), and Web of Science (Clarivate) electronic databases on August 8, 2023.

Study Selection

Articles were included if reporting a social determinant of health on a cohort of adult patients with symptomatic left-sided colonic diverticular disease pertaining to initial diagnosis, disease severity, treatment selection, post-treatment care, or prognosis. Due to lack of availability of studies reporting racism as a social determinant of health, self-reported race and ethnicity was used as a proxy variable for this construct. Studies were excluded if they only reported diverticulosis, only reported non-left sided disease, lacked availability of a non-English language full text, or included a cohort size less than 50. Reference lists of included studies were reviewed for additional relevant publications.

Study selection was performed through the Covidence platform.8 Studies were deduplicated followed by independent review from two authors (T.E.U., P.V.) for inclusion (inter-rater Pearson correlation coefficient 0.73). Inclusion discrepancies were resolved through iterative discussion with a third author (A.T.H).

Data Extraction, Quality Assessment, and Synthesis

Data extraction forms were built using REDCap.9 Extraction was performed by a single author (T.E.U or P.V.) with entries independently verified by another author (T.E.U or P.V.). To minimize data availability bias, a study’s corresponding author was contacted if information about a reported variable was not available in the published manuscript or supplementary materials.

Critical appraisal of cohort selection, comparability, and outcome was performed using a modified Newcastle-Ottawa Scale.10 Risk of bias for each domain was categorized as low, some, or high concern on the basis of achieving all stars (low), half or more available stars (some), or less than half of available stars (high) in that domain. A composite quality score was also assigned using a previously published algorithm.11

Two variables from the initial search strategy were excluded a posteriori during the full text review stage: sex/gender and seasonal variation. Given the breadth of included variables in this review, it was determined that the final study count after inclusion of sex/gender would hinder critical examination and meaningful collation of remaining studies. Seasonal variation was excluded after reassessment of relevance to the Healthy People 2030 domains.

To investigate the frequency of social variable reporting from each of the Healthy People 2030 domains, we calculated counts of unique studies examining that variable. Next, we identified the two most common types of comparisons, which were non-white versus white self-reported race and ethnicity and non-private versus private insurance. For studies reporting one of these comparisons in an adjusted analysis, we transformed effect sizes so that higher numbers corresponded to greater risk of a bad outcome for the traditionally disadvantaged group. The effect sizes were then grouped by association direction (positive, negative, or null), consistent with existing recommendations for analyses of health equity.12 To avoid placing greater weight on studies that included multiple variations of a single comparison (i.e. reporting Medicare vs. private insurance in addition to self-pay vs. private insurance), a study could contribute a maximum of one comparison for each association direction. To complement this approach from the perspective of social determinants of health comparisons, we performed the same steps for all studies reporting an outcome of mortality. A meta-analysis was not attempted given heterogeneity with diverticulitis cohort definitions, operationalization of social determinants, and outcome assessment. Degree of certainty in the body of evidence was approximated through the Diseases of the Colon & Rectum (DCR) quality rating scheme for individual studies.13 R 4.2.2 statistical software was used for analysis calculations.

RESULTS

The initial search returned 2,652 unique studies. After removal of 2,508 studies from title and abstract review followed by 80 studies from full text review, 50 studies met final inclusion criteria (Fig. 1). One study adopted a prospective cohort design14 (DCR quality rating 3), while the remainder were retrospective cohort (n = 44, DCR quality rating 2) or cross-sectional (n = 5, DCR quality rating 1). Studies reported cohorts with diverticulitis (n = 39) or combined diverticulitis with diverticulosis (n = 11). Data sources included US-based national registries (n = 24), US-based state registries (n = 13), single- or multicenter hospitals (n = 8), and international registries (n = 5). The range of data collection years was 1985 – 2019, with most studies capturing information after 2010 and a trend of increasing publications over time (Fig. 2). Methods for operationalizing diverticulitis were through International Classification of Diseases (ICD) coding only (n = 18), through multiple criteria (n = 30), or unclear (n = 2). Forty-six studies included other variables in an adjusted analysis with respect to the diverticulitis outcome.

Figure 1:

Figure 1:

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Study inclusion flow chart.

Figure 2:

Figure 2:

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Trends in social determinants of health reporting over time among diverticulitis studies. A) Counts of studies reported over time when grouped according to publication year. Line represents locally weighted scatterplot smoothing (LOESS) estimation of conditional means. Shading represents 95% confidence intervals for LOESS estimates. B) Data collection spans of included studies. JSR: Journal of Surgical Research. JGS: Journal of Gastrointestinal Surgery

Quality Assessment

Concerns of bias were highest in selection and outcome domains (Supplementary Figure 1 at https://links.lww.com/DCR/CXX). By the composite scoring algorithm for the modified Newcastle Ottawa scale, studies were either good (n = 40) or fair quality (n = 10). Reasons for selection bias included an inability to randomize for social determinants, an inpatient setting preference, and missing data for covariates. Unmeasured confounders due to retrospective study designs also likely influenced findings. The large-scale claims databases and hospitals represented in this review frequently lack standardized methodologies for capturing social determinants of health. While the comparability of exposed and non-exposed groups within a single study is preserved, this variation in curation limits between-study comparability.

Social Determinants of Health Domains

All Healthy People 2030 domains were represented in studies of diverticulitis (Table 1 and Fig. 3). Adjusted odds ratios among studies reporting an outcome of mortality are shown in Supplementary Figure 2 at https://links.lww.com/DCR/CXX.

Table 1:

Overview of Social Determinant of Health Comparisons in Diverticulitis

SDOH Variable Unique Study Count Data Sourcesa Cohort Descriptionsa Outcomes Considereda
Economic Stability
Income 11 HCUP State Inpatient Databases (3), HCUP Nationwide Inpatient Sample (3), HCUP Nationwide Readmissions Database (2), HCUP Nationwide Emergency Department Sample (1), International Registry (1), Single or Multi-center Hospitals (1) Diverticulitis (10), Both Diverticulitis and Diverticulosis (1) Readmission (2), Mortality (2), Ostomy removal (1), Hospital admission (1), Laparoscopic approach (1), Emergent surgery (1), Severity (1), Quality of life (1), Ostomy creation (1), Length of Stay (1), Total Hospital Cost (1)
Non-income economic variable 2 CMS Medicare Databases (1), International Registry (1) Both Diverticulitis and Diverticulosis (2) Colectomy (1), Hospital admission (1)
Education Access and Quality
Education 3 Single or Multi-center Hospitals (2), International Registry (1) Both Diverticulitis and Diverticulosis (2), Diverticulitis (1) Severity (2), Quality of life (1)
Literacy or language 2 Single or Multi-center Hospitals (1), HCUP State Inpatient Databases (1) Diverticulitis (2) Severity (1), Emergent surgery (1), ICU Admission (1), Any surgery (1), Length of Stay (1)
Healthcare Access and Quality
Insurance 22 HCUP Nationwide Inpatient Sample (6), HCUP State Inpatient Databases (4), US State registry (4), HCUP Nationwide Readmissions Database (3), HCUP Nationwide Emergency Department Sample (2), MarketScan (1), Single or Multi-center Hospitals (1), International Registry (1) Diverticulitis (21), Both Diverticulitis and Diverticulosis (1) Mortality (6), Any surgery (5), Hospital admission (4), Severity (4), Emergent surgery (3), Readmission (3), Ostomy creation (3), Laparoscopic approach (2), Ostomy removal (1), Quality of life (1), Treatment failure (1), Postoperative complication (1), Length of Stay (1), Total Hospital Cost (1)
Hospital characteristics 7 HCUP Nationwide Inpatient Sample (3), HCUP Nationwide Readmissions Database (2), HCUP State Inpatient Databases (1), US State registry (1) Diverticulitis (6), Both Diverticulitis and Diverticulosis (1) Mortality (4), Readmission (2), Any surgery (1), Emergent surgery (1), Postoperative complication (1), Ostomy creation (1), Length of Stay (1), Laparoscopic approach (1)
Distance from hospital 1 US State registry (1) Diverticulitis (1) Severity (1)
Neighborhood and Built Environment
Population density 9 HCUP Nationwide Inpatient Sample (3), International Registry (2), US State registry (1), HCUP Nationwide Readmissions Database (1), Single or Multi-center Hospitals (1), HCUP State Inpatient Databases (1) Diverticulitis (5), Both Diverticulitis and Diverticulosis (4) Mortality (2), Laparoscopic approach (2), Hospital admission (2), Readmission (2), Severity (2), Emergent surgery (1), Ostomy creation (1), Postoperative complication (1), Any surgery (1)
Geographic difference 9 HCUP Nationwide Inpatient Sample (3), US State registry (2), International Registry (2), MarketScan (1), CMS Medicare Databases (1) Diverticulitis (5), Both Diverticulitis and Diverticulosis (4) Mortality (3), Emergent surgery (2), Severity (1), Colectomy (1), Any surgery (1), Postoperative complication (1), Length of Stay (1), Total Hospital Cost (1), Laparoscopic approach (1), Hospital admission (1
Deprivation index 4 CMS Medicare Databases (2), Single or Multi-center Hospitals (1), HCUP State Inpatient Databases (1) Diverticulitis (4) Emergent surgery (1), Severity (1), Ostomy removal (1), Ostomy creation (1), ICU Admission (1), Mortality (1), Any surgery (1), Length of Stay (1)
Social and Community Context
Self-reported race and ethnicityb 33 HCUP Nationwide Inpatient Sample (8), Single or Multi-center Hospitals (7), US State registry (6), ACS NSQIP (4), HCUP State Inpatient Databases (3), CMS Medicare Databases (3), International Registry (2) Diverticulitis (27), Both Diverticulitis and Diverticulosis (6) Mortality (12), Severity (8), Any surgery (7), Hospital admission (6), Ostomy creation (5), Emergent surgery (3), Laparoscopic approach (3), Length of Stay (3), Readmission (3), Postoperative complication (2), Recurrence (2), Morbidity (2), Total Hospital Cost (2), Ostomy removal (1), Open surgical approach (1), Quality of life (1), Emergent admission (1), Elective interval operation (1), Transfer status (1), Treatment failure (1), ICU Admission (1)
Other
Multiple variable combination 2 HCUP State Inpatient Databases (2) Both Diverticulitis and Diverticulosis (1), Diverticulitis (1) Emergent admission (1), Ostomy removal (1), Colectomy (1)
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a

Numbers in parentheses represent counts of unique studies reporting that characteristic for a variable.

b

Self-reported race and ethnicity was used as a proxy variable for internalized systemic racism

Figure 3:

Figure 3:

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Social determinants of health reported by diverticulitis studies. Bars correspond to a Social Determinant of Health domain. Counts represent variables reported by at least two unique studies. Hospital Char = Hospital characteristics. Pop Density = Population Density. Geo = Geographic Comparison. Dep Index = Neighborhood deprivation indices. Non-income econ = Non-income economic variable. Lit or Lang = Literacy or Language. Multiple vars = Multiple variables included in comparison

Economic Stability

Thirteen studies reported variables related to income or non-income economic themes.14–26 Of these, seven found significant differences in an adjusted analysis.16–19,22,24,26 Lower income was found to be associated with lower odds of minimally invasive approach to colectomy16 as well as higher odds of emergency surgical admissions,17 readmission,18 and mortality.22 In contrast, Nikberg et al’s (2017)19 study of the Swedish Hospital Discharge Register from 1997–2012 noted lower income as a protective factor against complicated diverticular disease presentation, despite finding that fewer years of education increased the risk for complicated disease. The authors hypothesized that low correlation between income and education in the Swedish population may have contributed to this difference.

Education Access and Quality

Mixed findings were found for the effect of education.14,19,27 Khor et al (2021)14 conducted a prospective cohort study of disease-specific quality of life in 177 diverticulitis patients. Among those with a graduate degree, nearly twice as many patients reported a satisfactory disease state relative to a disease state that limits quality of life (37.7% vs 19.6%), but this trend was reversed among those with occupational degrees (21.7% vs 40.2%). However, Lukosiene et al (2021)27 reported that for 1,333 patients from German and Lithuanian referral centers with diverticular disease confirmed on colonoscopy, higher educational attainment was associated with more than twice increased risk for diverticulitis (OR 2.45 [95% CI, 1.31 – 4.59]). They hypothesized that education may have been a proxy for other factors such as a sedentary lifestyle or Western diet known to influence diverticulitis risk.

Two studies reported effects of literacy28 or language.17 Maurer et al (2021)17 identified non-English primary language as a risk factor for an emergency setting of diverticulitis surgery. This association persisted in a sensitivity analysis when stratifying by another significant social determinant variable in their adjusted analysis, noncommercial insurance. In a single-center cohort, Hamdan et al (2022)28 found no difference in the severity of diverticulitis presentation when examining health literacy.

Healthcare Access and Quality

Twenty-two studies reported the influence of insurance status,14–18,21,23,25,29–42 including 14 comparing non-private versus private insurance (Fig. 4).

Figure 4:

Figure 4:

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Effect size plots for social determinants of health comparisons. A) Non-white self-reported race and ethnicity. B) Non-private versus private insurance comparisons. The X-axis represents odds ratio or relative risk with 95% confidence interval, transformed so that higher numbers correspond to higher risk of a bad outcome for the traditionally disadvantaged group. The Y-axis represents unique studies reporting a positive association (top panel), negative association (middle panel) or no association (bottom panel) for the comparison. JSR = Journal of Surgical Research. *Transformed effect size estimate

In a retrospective query of the 2013–2014 United States National Readmission Database, Mehta et al (2021)18 identified non-private insurance as a risk factor for readmission in non-hemorrhagic diverticulitis. Similarly, Lassiter et al (2017)16 reported lower odds of laparoscopic approach among those with non-private insurance, and Maurer et al (2021)17 found that diverticulitis patients undergoing partial colon resection with self-pay insurance were almost four times as likely to have an emergent admission type relative to commercially insured patients. Other studies detected varying association directions depending on the type of non-private insurance and the outcome. For example, Mills et al (2013)38 demonstrated higher risk of mortality in Medicare, Medicaid, or uninsured patients but lower odds of procedural intervention among Medicare patients. In addition, Choi et al (2016)42 reported a shorter length of stay in Medicare patients, but that Medicare or Medicaid insurance status was associated with higher risk of mortality. To assess the influence of Medicaid expansion under the Affordable Care Act in the United States, Eguia et al (2021)41 compared states that expanded Medicaid access to those that did not with respect to rates of surgical procedures for diverticular disease. They identified a positive association between expanded Medicaid access and rates of surgical procedures.

Additional variables were distance from the hospital,43 level 1 trauma center status,44 hospital size or teaching status,30,35 and hospital market competition.26

Neighborhood and Built Environment

Included studies reported geographic differences,24,26,29,31,32,35,42,43,45 neighborhood-level deprivation indices,23,28,46,47 and population density16,18,19,23,24,31,35,48,49

At the national level, Simianu et al (2016)29 queried the MarketScan (TruvenHealth Analytics) database and found regional location to be an independent predictor of early elective colectomy for diverticulitis. Using the Nationwide Inpatient Sample, Maguire et al (2015)48 discovered greater rates of diverticulitis admissions among areas with low ultraviolet light exposure. Within-state differences have also been reported, as Lemini et al (2020)35 examined seven regions in the state of Florida and found that location was associated with an urgent or emergent surgical setting among surgical diverticulitis patients.

Multiple neighborhood-level socioeconomic measures were considered, including the social vulnerability index, the area deprivation index, and the social deprivation index. Diaz et al (2021)47 found that among diverticulitis patients undergoing a colon resection, those living in areas with higher social vulnerability were at greater risk of non-elective colon resection, postoperative complications, and higher hospital costs. Similarly, for Zarate Rodriquez et al (2023)23 social vulnerability was a predictor of stoma creation among patients undergoing non-elective surgery for uncomplicated diverticulitis. Reid et al (2021)46 reported that higher Social Deprivation index scores were associated with lower rates of stoma reversal and greater rates of mortality. They also noted the disproportionate impact of this trend across self-reported race and ethnicity.

Rurality or population-based metrics were also examined. While most studies did not find significant effects of rurality,16,19,23,31,35,49 this variable was identified as a positive predictor of hospital admission in Hjern et al (2006)24 and Maguire et al (2015)48 as well as a negative predictor of short-term readmission in Mehta et al (2021).18

Social and Community Context

Self-reported race and ethnicity was the most common variable,14,16,20,22–25,28,31–37,42–44,47–61 with 33 studies mentioning any comparison and 18 studies reporting a non-white versus white comparison (Fig. 4).

In looking at the American College of Surgeons National Surgical Quality Improvement Program for diverticulitis patients undergoing surgery, Alavi et al (2012)51 found that African Americans had greater rates of comorbidities in addition to higher rates of urgent surgery, morbidity, and mortality. Other outcome associations for self-reported black race and ethnicity were open approach to surgery in Akram et al (2022),50 future nonoperative readmissions for diverticulitis in Tong et al (2023),60 operative intervention after a previous medical admission for diverticulitis in Bose et al (2013),52 30-day morbidity in Braschi et al (2023),61 and mortality in Schneider et al (2011).58 In contrast, Mathews et al (2017)37 found all non-white groups to be at lower risk of more than 1 hospital admission for diverticulitis.

DISCUSSION

The primary contributions of this review are 1) summarizing social determinants of health for a common surgical gastrointestinal disease organized by nationally recognized domains, and 2) a qualitative summary of effect sizes for comparisons that have been frequently reported. Many studies have addressed self-reported race and ethnicity and insurance status, with non-white and non-private insurance often associated with poorer outcomes including mortality, disease severity, ostomy status, admissions, and postoperative complications. Notable reporting gaps exist for health literacy, food insecurity, and housing instability.

Unmet social needs have repeatedly been shown to impact health outcomes when controlling for relevant clinical factors.62 Just as unique medical and surgical histories influence decisions for surgical patients, the growing body of work with social determinants of health increasingly supports inclusion in clinical practice. Given that social pressures may vary with the demands of different diseases, a disease-specific approach is often adopted to identify areas for targeted intervention.63,64 Examples of actionable initiatives originating from investigations of social variables can be found at both the policy and clinician level. After identifying disparities in colorectal cancer screening, the Delaware Cancer Consortium was established to oversee implementation of screening colonoscopy coverage expansion for uninsured patients, subsidies for cancer care costs in the uninsured, and patient navigators to facilitate downstream care. They found increased rates of overall colorectal screening (from 57% to 74%) as well as reductions in the percentage of regional or advanced stages at initial diagnosis of colorectal cancer in the African American subgroup (from 79% to 40%).65 At the surgeon-level, the Department of Surgery at Boston Medical Center implemented initiatives to increase social resource availability to operative patients, including a dedicated team of mental health professionals for victims of violence in the trauma setting, hospital-specific food pantry referrals, and personnel to help patients address social concerns in the legal sphere.66 These efforts have been described under an umbrella model of Socially Responsible Surgery and since adapted at multiple other institutions.67 Broadly, our results support the value of connecting patients with local social resources to achieve optimal outcomes. Future studies are needed to definitively establish ideal scenarios and candidate variables for screening in surgical populations. For diverticulitis specifically, the mixed findings for educational attainment and rurality in this study suggest that attention may be best devoted to other social variables.

By identifying social variable reporting trends, this review provides direction for future studies. Self-reported race and ethnicity and insurance status were most often addressed in diverticulitis studies, which agrees with prior similar investigations of surgical diseases. In Fonseca et al’s (2022)68 systematic review of disparities for pancreatic cancer care, 41 / 47 eligible studies reported race and ethnicity and 37 of these identified race-based disparities in care. From 18 of their studies reporting any insurance variable, 17 identified significant differences. Specific areas for future investigators include health literacy (n = 1), primary language (n = 1), food instability (n = 0), or housing instability (n = 0). This may be due in part to a lack of data availability. For example, self-reported race and ethnicity and insurance are commonly documented throughout the course of routine clinical care, whereas other variables like health literacy require additional administration of a validated survey. There may also be barriers related to publication bias, where nonsignificance of findings discourages reporting even though the investigation has been performed. However, a search of pre-print servers performed by the current authors did not yield additional eligible studies in these areas. The high prevalence of limited health literacy in surgical populations (34%)69 and a growing non-English speaking population in the United States highlights the importance of future work to evaluate impact with respect to diverticulitis outcomes. Given the breadth of potential social influences that can be examined, we recommend categorization according to the US Department of Health and Human Services Healthy People 2030 framework in future studies. Two resources linking social determinants of health with clinical records include the Social Determinants of Health Database from the Agency for Healthcare Research and Quality70 and the All of Us Research Program.71

Identifying specific times in the care process where social variables act has implications for the design of targeted initiatives. For example, if socially disadvantaged groups have more complicated initial presentations or emergent care needs, then attention may be directed to policy efforts addressing upstream contributors. On the other hand, disparities in surgical approach or readmission rates lends support to interventions for hospital workflows or patient screening. With both our self-reported race and ethnicity and insurance comparisons, significant associations were identified not only upon initial presentation but also throughout post-treatment care with readmissions and mortality. In addition, most studies reported an association where the traditionally disadvantaged group (non-white or non-private insurance) was associated with poorer outcomes. Thus, the findings of this review suggest that future interventions should be guided by community-specific needs and feasibility rather than a specific point in the care trajectory.

An area in need of continued study is the exploration of additive effects and interactions between social variables.72,73 One example comes from Turner et al (2019)73 who found that self-reported black race when combined with no insurance was strongly associated with colostomy reversal rates at 2 years (OR 0.27, 95% CI [0.14 – 0.51]). It is plausible that social determinants of health may act through clinical comorbidities such as obesity; obesity rates have been associated with rural residence, lower access to exercise-based activities, lower income, and availability of fast-food restaurants.74 However, other independent pathways may also be involved. Further work beyond investigations of associations is needed to understand intermediary stages between social variables and poorer health outcomes.

There are a number of limitations to this study. First, no meta-analysis was attempted among included studies due to heterogeneity in cohorts and variable definitions. At the cohort level, there was variation in ICD codes applied, in requirement of additional evidence such as imaging confirmation, and in inclusion qualifiers such as history of prior episodes or presence of concomitant surgical interventions. At the variable operationalization level, differences existed with data collection (i.e. for education, years of education vs degree achievements) as well as data presentation (i.e for income, currency values vs quartiles). While meta-analysis would provide an interpretable pooled effect size estimate, the authors believe that the risk of bias from pooled estimates of heterogeneous non-randomized studies outweigh the benefits with the current body of evidence.75 Second, nearly all studies were retrospective with only one achieving a DCR quality rating of 3, which limits confidence in certainty of evidence. Third, exclusion of non-English language full texts may have resulted in missing studies that otherwise would have been eligible. We did not include qualitative studies or mixed-methods studies, and thus may be missing important themes that lack quantitative assessments in the literature. Fourth, few studies directly measured social determinants of health domains. None examined racism, and thus race was utilized as a proxy variable. This serves as both a limitation of the current study and a call to action for future investigators. Fifth, this work is subject to the potential for selective outcome reporting and publication bias present in all systematic reviews, though studies were selected based on inclusion of a variable rather than result significance.

CONCLUSIONS

Social determinants of health domains are associated with a variety of diverticulitis outcomes. Additional studies are needed to address infrequently reported domains and identify optimal strategies for intervening in clinical settings.

Supplementary Material

Supp Fig 1

Supplementary Figure 1: Risk of bias among included studies using the modified Newcastle-Ottawa Scale

Supp Fig 2

Supplementary Figure 2: Associations between social determinants of health and mortality in diverticulitis. The X-axis represents odds ratio or relative risk with 95% confidence interval, transformed so that higher numbers correspond to higher risk of a bad outcome for the traditionally disadvantaged group. The Y-axis represents unique studies reporting a positive association (top panel), negative association (middle panel) or no association (bottom panel) for the comparison. *Transformed effect size estimate

ACKNOWLEDGMENTS

The authors would like to acknowledge Rachel Lane Walden, MLIS from the Eskind Biomedical Library for her assistance with developing and refining the search strategy of this study.

Funding/Support:

Dr. Hawkins work on this manuscript was supported by the National Institute of Diabetes and Digestive and Kidney Disease of the National Institutes of Health under award number K23DK118192. Mr. Ueland’s work was supported by National Institutes of Health award number T32DK007673. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Financial Disclosures:

None reported.

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Associated Data

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

Supplementary Materials

Supp Fig 1

Supplementary Figure 1: Risk of bias among included studies using the modified Newcastle-Ottawa Scale

NIHMS2020280-supplement-Supp_Fig_1.pdf (4.4KB, pdf)
Supp Fig 2

Supplementary Figure 2: Associations between social determinants of health and mortality in diverticulitis. The X-axis represents odds ratio or relative risk with 95% confidence interval, transformed so that higher numbers correspond to higher risk of a bad outcome for the traditionally disadvantaged group. The Y-axis represents unique studies reporting a positive association (top panel), negative association (middle panel) or no association (bottom panel) for the comparison. *Transformed effect size estimate

NIHMS2020280-supplement-Supp_Fig_2.pdf (217KB, pdf)

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