463. Factors of Social Determinants of Health Associated with Length of Stay in COVID-19 Patients with Multimorbidity in Southwest Georgia, United States

Abstract Background Previous studies have observed that multimorbidity, defined as two or more comorbidities, is associated with longer lengths of stay (LOS) and higher mortality in patients with COVID-19. In addition, inequality in social determinants of health (SDOH), dictated by economic stability, education access and quality, healthcare access and quality, neighborhoods and built environment, and social and community context have only added to disparities in morbidity and mortality associated with COVID-19. However, the relationship between SDOH and LOS in COVID-19 patients with multimorbidity is poorly characterized. Analyzing the effect SDOH have on LOS can help identify patients at high risk for prolonged hospitalization and allow prioritization of treatment and supportive measures to promote safe and expeditious discharge. Methods This study was a multicenter, retrospective analysis of adult patients with multimorbidity who were hospitalized with COVID-19. The primary outcome was to determine the LOS in these patients. The secondary outcome was to evaluate the role that SDOH play in LOS. Poisson regression analyses were performed to examine associations between individual SDOH and LOS. Results A total of 370 patients were included with a median age of 65 years (IQR 55-74), of which 57% were female and 77% were African American. Median Charlson Comorbidity Index was 4 (IQR 2-6) with hypertension (77%) and diabetes (51%) being the most common, while in-hospital mortality was 23%. Overall, median length of stay was 7 days (IQR 4-13). White race (-0.16, 95% CI -0.27 to -0.05, p=0.003) and residence in a single-family home (-0.28, 95% CI -0.38 to -0.17, p< 0.001) or nursing home/long term care facility (-0.36, 95% CI -0.51 to -0.21, p< 0.001) were associated with decreased LOS, while Medicare (0.24, 95% CI 0.10 to 0.38, p=0.001) and part-time (0.35, 95% CI 0.13 to 0.57, p=0.002) or full-time (0.25, 95% CI 0.12 to 0.38, p< 0.001) employment were associated with increased LOS. Conclusion Based on our results, differences in SDOH, including economic stability, neighborhood and built environment, social and community context, as well as healthcare access and quality, have observable effects on COVID-19 patient LOS in the hospital. Disclosures All Authors: No reported disclosures

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Racial Disparities in Incidence of Legionnaires’ Disease and Social Determinants of Health: A Narrative Review

Public Health Reports ◽

10.1177/00333549211026781 ◽

2021 ◽

pp. 003335492110267

Author(s):

Candis M. Hunter ◽

Simone W. Salandy ◽

Jessica C. Smith ◽

Chris Edens ◽

Brian Hubbard

Keyword(s):

Health Care ◽

Built Environment ◽

Social Determinants Of Health ◽

Social Determinants ◽

Health Care Access ◽

Narrative Review ◽

Economic Stability ◽

Care Access ◽

Legionnaires Disease ◽

Access And Quality

Objectives Racial and socioeconomic disparities in the incidence of Legionnaires’ disease have been documented for the past 2 decades; however, the social determinants of health (SDH) that contribute to these disparities are not well studied. The objective of this narrative review was to characterize SDH to inform efforts to reduce disparities in the incidence of Legionnaires’ disease. Methods We conducted a narrative review of articles published from January 1979 through October 2019 that focused on disparities in the incidence of Legionnaires’ disease and pneumonia (inclusive of bacterial pneumonia and/or community-acquired pneumonia) among adults and children (excluding articles that were limited to people aged <18 years). We identified 220 articles, of which 19 met our criteria: original research, published in English, and examined Legionnaires’ disease or pneumonia, health disparities, and SDH. We organized findings using the Healthy People 2030 SDH domains: economic stability, education access and quality, social and community context, health care access and quality, and neighborhood and built environment. Results Of the 19 articles reviewed, multiple articles examined disparities in incidence of Legionnaires’ disease and pneumonia related to economic stability/income (n = 13) and comorbidities (n = 10), and fewer articles incorporated SDH variables related to education (n = 3), social support (none), health care access (n = 1), and neighborhood and built environment (n = 6) in their analyses. Conclusions Neighborhood and built-environment factors such as housing, drinking water infrastructure, and pollutant exposures represent critical partnership and research opportunities. More research that incorporates SDH and multilevel, cross-sector interventions is needed to address disparities in Legionnaires’ disease incidence.

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Defining Disparities in Cochlear Implantation through the Social Determinants of Health

Seminars in Hearing ◽

10.1055/s-0041-1739282 ◽

2021 ◽

Vol 42 (04) ◽

pp. 321-330

Author(s):

Marissa Schuh ◽

Matthew L. Bush

Keyword(s):

Hearing Loss ◽

Social Determinants Of Health ◽

Social Determinants ◽

Cochlear Implantation ◽

Healthcare Access ◽

Public Health Problem ◽

Community Context ◽

Determinants Of Health ◽

Global Public Health ◽

Socioeconomic Resources

AbstractHearing loss is a global public health problem with high prevalence and profound impacts on health. Cochlear implantation (CI) is a well-established evidence-based treatment for hearing loss; however, there are significant disparities in utilization, access, and clinical outcomes among different populations. While variations in CI outcomes are influenced by innate biological differences, a wide array of social, environmental, and economic factors significantly impact optimal outcomes. These differences in hearing health are rooted in inequities of health-related socioeconomic resources. To define disparities and advance equity in CI, there is a pressing need to understand and target these social factors that influence equitable outcomes, access, and utilization. These factors can be categorized according to the widely accepted framework of social determinants of health, which include the following domains: healthcare access/quality, education access/quality, social and community context, economic stability, and neighborhood and physical environment. This article defines these domains in the context of CI and examines the published research and the gaps in research of each of these domains. Further consideration is given to how these factors can influence equity in CI and how to incorporate this information in the evaluation and management of patients receiving cochlear implants.

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Impact of Social Determinants of Health on Chronic Kidney Disease: A Review of Disparities in Renal Transplantation

Translation: The University of Toledo Journal of Medical Sciences ◽

10.46570/utjms.vol9-2021-515 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Conner Lombardi ◽

Logan Glosser ◽

Hanna Knauss ◽

Teanya Norwood ◽

Julia Berry ◽

...

Keyword(s):

Chronic Kidney Disease ◽

Kidney Transplantation ◽

Kidney Disease ◽

Social Determinants Of Health ◽

Social Determinants ◽

Health Impact ◽

Community Context ◽

Determinants Of Health ◽

Economic Stability ◽

The Social

Background: Striking disparity exists in the incidence and treatment of chronic kidney disease (CKD) secondary to individual social determinants of health. Additionally, the uninsured, minority racial-ethnic groups, and Medicaid enrollees receive less nephrology care prior to being diagnosed with end-stage renal disease (ESRD). The most effective treatment for the management of kidney failure is kidney transplantation. This review addresses how social determinants of health impact the workup for patients with ESRD, with emphasis on the kidney transplant process. Methods: A search was conducted via multiple online databases (MedLine, PubMed, etc.) for articles that addressed the interplay between CKD, ESRD and kidney transplantation with the social determinants of health. Findings: The impact of the social determinants of health on CKD, ESRD, and the kidney transplantation process can be qualitatively and quantitatively measured using the five categories of education, health care and access, economic stability, neighborhood and built environment, and social and community context. Conclusion: Social determinants of health impact outcomes in CKD, ESRD, and kidney transplantation. Public and private initiatives aimed at reducing social disparities among patients with kidney disease must include emphasis on education, health care and access, economic stability, neighborhood and built environment, and social and community context. This initiative is necessary to prevent progression to ESRD and to ensure quality care in the kidney transplantation process.

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Impact of social determinants of health on a late diagnosis and survival of patients with pancreatic cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e18530 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e18530-e18530

Author(s):

Jesus C. Fabregas ◽

Miranda Lam

Keyword(s):

Pancreatic Cancer ◽

Social Determinants Of Health ◽

Social Determinants ◽

Univariate Analysis ◽

Stage Iv ◽

Late Diagnosis ◽

Determinants Of Health ◽

Secondary Outcome ◽

Black Race ◽

Cox Analysis

e18530 Background: While disparities in pancreatic cancer (PC) are documented, it is unclear whether these inequities occur at the time of diagnosis or throughout treatment. We hypothesize social determinants of health (SDH) such as income, education, race and insurance status are a) associated with a late diagnosis of PC (Stage IV vs Stages 0-III) and b) associated with overall survival (OS) in Stage IV patients. Methods: The National Cancer Database 2017 version was accessed. Primary outcome: diagnosis of Stage IV PC. Secondary outcome: OS. Primary predictors: race, income, education, insurance. Confounders: Charlson comorbidity score, age, sex. Univariate and multivariate regression models evaluated the association between SDH and a late diagnosis of PC. Univariate and multivariate Cox proportional hazards model examined OS. 95% Confidence Intervals were used. Results: 230,877 patients were included. Median 68 yrs, mean 67.3 SD(12.1). In univariate analysis, education (>93% high school completion (HSC) vs <82.4%, OR 0.93 [0.91 – 0.95]), income (>$63,333 vs<$40,277, OR 0.94 [0.92– 0.96]), and insurance (Private vs No, OR 0.70 [0.66 – 0.73]), decreased the odds of Stage IV PC. Black race was associated with higher odds of Stage IV PC (vs White, OR 1.11 [1.08 – 1.14]). In multivariate analysis, education and having insurance decreased the risk of a late diagnosis, whereas black race increased it (table). In univariate Cox analysis, higher income (>$63,333 (vs<$40,277), HR 0.82 [0.81– 0.83]), insurance (Private vs No, HR 0.77 [0.73 – 0.76]) and education (>93% HSC vs <82.4%, HR 0.87 [0.86 – 0.88]) improved OS. Black race was associated with poorer OS (vs White, HR 1.03 [1.02 – 1.05]). In multivariate Cox analysis, only higher income (>$63,333 (vs<$40,277), HR 0.87 [0.85 – 0.89]) and having insurance (Private vs No, HR 0.77 [0.74 – 0.79]) were associated with improved OS. Conclusions: SDH impacted the continuum of pancreatic neoplasia care, from diagnosis to treatment. Expanding insurance coverage could be an effective public health intervention to improve early diagnosis and survival rates.[Table: see text]

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Evaluating Concussion Nondisclosure in College Athletes using a Health Disparities Framework and Appreciation for Social Determinants of Health

Journal of Athletic Training ◽

10.4085/1062-6050-0054.21 ◽

2021 ◽

Author(s):

Jessica Wallace ◽

Erica Beidler ◽

Johna K. Register-Mihalik ◽

Tamaria Hibbler ◽

Abigail Bretzin ◽

...

Keyword(s):

High School ◽

Social Determinants Of Health ◽

Social Determinants ◽

College Athletes ◽

Healthcare Access ◽

Determinants Of Health ◽

Athletic Trainer ◽

Black Athletes ◽

Cross Sectional ◽

History Of

Abstract Context: There is limited research concerning the relationship between social determinants of health, including race, healthcare access, socioeconomic status (SES), and physical environment; and, concussion nondisclosure in college-athletes. However, in high school athletes, disparities have been noted, with Black athletes attending under-resourced schools and lacking access to an athletic trainer (AT) disclosing fewer concussions. Objective: To investigate whether concussion nondisclosure disparities exist by 1) race, 2) SES, and 3) AT healthcare access prior to college; and to understand the differential reasons for concussion nondisclosure between Black and White college-athletes. Design: Cross-sectional Setting: College athletics Participants: 735 college-athletes (84.6% White, 15.4% Black) Main Outcome Measures: Participants completed a questionnaire that directly assessed concussion nondisclosure, including reasons for not reporting a suspected concussion. With the premise of investigating social determinants of health, race was the primary exposure of interest. The outcome of interest, nondisclosure, was assessed with a binary (yes/no) question, “Have you ever sustained a concussion that you did not report to your coach, athletic trainer, parent, teammate, or anyone else?” Results: Overall, among White and Black athletes 15.6% and 17.7% respectively reported a history of concussion nondisclosure. No significant differences were found by race for distributions of history of concussion nondisclosure (p=0.57). Race was not associated with concussion nondisclosure when evaluated as an effect modification measure or confounder; and, no significant associations were noted by SES or high school AT access. Differences by race for reported reasons for nondisclosure were found for: “At the time I did not think it was a concussion” (p=0.045) and “I thought my teammates would think I am weak” (p=0.03) with Black athletes reporting these more frequently than White athletes. Conclusions: These data help to contextualize race and its intersection with other social determinants of health that could influence concussion nondisclosure outcomes in college-athletes.

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INTEREST GROUP SESSION—MENTAL HEALTH PRACTICE AND AGING: INTEGRATION OF SOCIAL DETERMINANTS OF HEALTH IN DEFINING HEALTH BEHAVIORS AND OUTCOMES AMONG DIVERSE OLDER ADULTS

Innovation in Aging ◽

10.1093/geroni/igz038.1449 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S393-S393

Author(s):

Jacquelyn Minahan ◽

Tamara A Baker

Keyword(s):

Older Adults ◽

Health Behaviors ◽

Life Course ◽

Life Span ◽

Social Determinants Of Health ◽

Social Determinants ◽

Chronic Illnesses ◽

Community Context ◽

Determinants Of Health ◽

The Life Course

Abstract Social determinants of health (SDoH) are conditions in which individuals live, learn, work, and play. Specifically, they are influenced by the distribution of resources, money, and power, and have significant implications on health behaviors and outcomes across the life span. Existent data show the influence these indictors may have in the onset and progression of chronic illnesses. However, much of these data focus on the effect of race and health, as social determinants, but fail to adequately address the myriad other factors (e.g., health care, social and community context) that influence the social patterning across the life course. This symposium presents findings from several studies highlighting the nuanced role of SDoH across diverse populations of older adults. Scholars will present findings on the influence that identified determinants, such as social networks, lifestyle behaviors, and gender, have in defining health outcomes across the life course. Minahan presents the relationship between chronic illnesses and depression and compares depressive symptomatology according to disease cluster in a nationally-representative sample of older adults. Atakere discusses determinants of well-being among African American males with chronic illnesses and the challenges associated with this marginalized population. Booker examines spirituality as a mechanism for pain management among older African Americans and presents this as a crucial determinant of health. This symposium will expand on the existing body of literature by emphasizing social and cultural determinants, aside from race, that influence health behaviors and outcomes across the life span.

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The influence of social determinants of health on single-level anterior cervical discectomy and fusion outcomes

Journal of Neurosurgery Spine ◽

10.3171/2021.9.spine211059 ◽

2021 ◽

pp. 1-6

Keyword(s):

Length Of Stay ◽

Postoperative Complication ◽

Social Determinants Of Health ◽

Social Determinants ◽

Revision Surgery ◽

Determinants Of Health ◽

Anterior Cervical Discectomy ◽

Complication Rates ◽

Cervical Discectomy ◽

Single Level

OBJECTIVE Methods of reducing complications in individuals electing to undergo anterior cervical discectomy and fusion (ACDF) rely upon understanding at-risk patient populations, among other factors. This study aims to investigate the interplay between social determinants of health (SDOH) and postoperative complication rates, length of stay, revision surgery, and rates of postoperative readmission at 30 and 90 days in individuals electing to have single-level ACDF. METHODS Using MARINER30, a database that contains claims information from all payers, patients were identified who underwent single-level ACDF between 2010 and 2019. Identification of patients experiencing disparities in 1 of 6 categories of SDOH was completed using ICD-9 and ICD-10 (International Classifications of Diseases, Ninth and Tenth Revisions) codes. The population was propensity matched into 2 cohorts based on comorbidity status: those with SDOH versus those without. RESULTS A total of 10,030 patients were analyzed; there were 5015 (50.0%) in each cohort. The rates of any postoperative complication (12.0% vs 4.6%, p < 0.001); pseudarthrosis (3.4% vs 2.6%, p = 0.017); instrumentation removal (1.8% vs 1.2%, p = 0.033); length of stay (2.54 ± 5.9 days vs 2.08 ± 5.07 days, p < 0.001 [mean ± SD]); and revision surgery (9.7% vs 4.2%, p < 0.001) were higher in the SDOH group compared to patients without SDOH, respectively. Patients with any SDOH had higher odds of perioperative complications (OR 2.8, 95% CI 2.43–3.33), pseudarthrosis (OR 1.3, 95% CI 1.06–1.68), revision surgery (OR 2.4, 95% CI 2.04–2.85), and instrumentation removal (OR 1.4, 95% CI 1.04–2.00). CONCLUSIONS In patients who underwent single-level ACDF, there is an association between SDOH and higher complication rates, longer stay, increased need for instrumentation removal, and likelihood of revision surgery.

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The Social Determinants of Health in a Community Context: Lessons for Sociological Practice

Journal of Applied Social Science ◽

10.1177/1936724418785413 ◽

2018 ◽

Vol 12 (2) ◽

pp. 67-81

Author(s):

Tim Knapp ◽

Lisa Hall

Keyword(s):

Public Health ◽

Social Determinants Of Health ◽

Social Determinants ◽

Access To Health Care ◽

Well Being ◽

Community Context ◽

Determinants Of Health ◽

Physical And Mental Health ◽

Sociological Practice ◽

The Social

Much of the research on the social determinants of health has been done at national or international comparative levels. Findings from these studies highlight the importance of macro social factors that affect health outcomes, such as limited and unequal access to health care and the effects of racial discrimination, economic inequality, and patriarchy. However, such macro-level research provides limited information about how applied and clinical sociologists can address local social determinants of health and improve the well-being of individuals and community residents. Results from a county-level public health survey shed more specific light on how interpersonal networks, social activities, and neighborhood characteristics affect people’s physical and mental health. The results can be utilized by clinical and applied sociologists who counsel individuals and work to invigorate neighborhoods, and by public health officials who develop and reform community-level health policies and programs.

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516: SOCIAL DETERMINANTS OF HEALTH IMPACT HOSPITAL LENGTH OF STAY FOR CHILDREN WITH SEVERE SEPSIS

Critical Care Medicine ◽

10.1097/01.ccm.0000808388.04541.2b ◽

2021 ◽

Vol 50 (1) ◽

pp. 249-249

Author(s):

Alina West ◽

Hunter Hamilton ◽

Nariman Ammar ◽

Fatma Gunturkun ◽

Tamekia Jones ◽

...

Keyword(s):

Severe Sepsis ◽

Length Of Stay ◽

Social Determinants Of Health ◽

Social Determinants ◽

Health Impact ◽

Hospital Length ◽

Determinants Of Health ◽

Hospital Length Of Stay

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Identifying Communities at Risk for COVID-19–Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators (Preprint)

10.2196/preprints.26604 ◽

2020 ◽

Author(s):

Andrew Deonarine ◽

Genevieve Lyons ◽

Chirag Lakhani ◽

Walter De Brouwer

Keyword(s):

New York ◽

New York City ◽

Built Environment ◽

Social Determinants Of Health ◽

Satellite Imagery ◽

Risk Score ◽

Social Determinants ◽

York City ◽

Complex Disease ◽

Determinants Of Health

BACKGROUND Although it is well-known that older individuals with certain comorbidities are at the highest risk for complications related to COVID-19 including hospitalization and death, we lack tools to identify communities at the highest risk with fine-grained spatial resolution. Information collected at a county level obscures local risk and complex interactions between clinical comorbidities, the built environment, population factors, and other social determinants of health. OBJECTIVE This study aims to develop a COVID-19 community risk score that summarizes complex disease prevalence together with age and sex, and compares the score to different social determinants of health indicators and built environment measures derived from satellite images using deep learning. METHODS We developed a robust COVID-19 community risk score (COVID-19 risk score) that summarizes the complex disease co-occurrences (using data for 2019) for individual census tracts with unsupervised learning, selected on the basis of their association with risk for COVID-19 complications such as death. We mapped the COVID-19 risk score to corresponding zip codes in New York City and associated the score with COVID-19–related death. We further modeled the variance of the COVID-19 risk score using satellite imagery and social determinants of health. RESULTS Using 2019 chronic disease data, the COVID-19 risk score described 85% of the variation in the co-occurrence of 15 diseases and health behaviors that are risk factors for COVID-19 complications among ~28,000 census tract neighborhoods (median population size of tracts 4091). The COVID-19 risk score was associated with a 40% greater risk for COVID-19–related death across New York City (April and September 2020) for a 1 SD change in the score (risk ratio for 1 SD change in COVID-19 risk score 1.4; P<.001) at the zip code level. Satellite imagery coupled with social determinants of health explain nearly 90% of the variance in the COVID-19 risk score in the United States in census tracts (r2=0.87). CONCLUSIONS The COVID-19 risk score localizes risk at the census tract level and was able to predict COVID-19–related mortality in New York City. The built environment explained significant variations in the score, suggesting risk models could be enhanced with satellite imagery.

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