Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States

Census tract geospatial analysis comparing social determinants of health with tooth loss in California seniors: An ecologic study

OBJECTIVES

Individual-level social determinant of health (SDOH) measures alone may insufficiently explain disparities in edentulism among seniors. Therefore, the authors examined the correlation of census tract-level SDOH and residential racial segregation measures with edentulism in Californian adults aged ≥65 years old.

METHODS

Explanatory variables were obtained from Healthy Places Index (HPI), the National Cancer Institute and diversitydatakids.org. The edentulism outcome variable was obtained from CDC's PLACES small area estimates from the 2018 Behavioral Risk Factor Surveillance System data. Pearson and Spearman rank correlations were estimated. Multiple linear regression and multi-collinearity evaluations were performed. The Global Moran's I statistic assessed partial autocorrelation within census tracts.

RESULTS

Pearson and Spearman correlations were similar, supporting robustness. HPI, an area measure of advantage, strongly negatively correlated with edentulism prevalence [correlation coefficient: -0.87; 95% confidence interval (CI): -0.87, -0.86]. A change of 1.0 in HPI corresponded to an estimated decrease in edentulism prevalence of 5.9% (linear model adjusted R2 = 0.78). Racially segregated census tracts with Hispanics or Blacks alone were positively correlated with edentulism prevalence [0.60, 95% CI: 0.58, 0.62; and 0.33, 95% CI: 0.31, 0.35, respectively]. The converse was seen in census tracts with non-Hispanic Whites alone [-0.57, 95% CI: -0.58, -0.55]. Global Moran's I statistic for edentulism (0.13) and HPI scores (0.19) were significant (both p < .001) indicating geospatial autocorrelation.

CONCLUSIONS

Higher disadvantage and minority racial segregation within census tracts were positively correlated with edentulism prevalence. Future research and policy should consider possible interventions improving SDOH to reduce oral health inequities.

Assessing the Relationship Between Neighborhood Socioeconomic Disadvantage and Telemedicine Use Among Patients With Breast Cancer and Examining Differential Provisions of Oncology Services Between Telehealth and In-Person Visits: Quantitative Study

BACKGROUND

Since the COVID-19 pandemic began, we have seen rapid growth in telemedicine use. However, telehealth care and services are not equally distributed, and not all patients with breast cancer have equal access across US regions. There are notable gaps in existing literature regarding the influence of neighborhood-level socioeconomic status on telemedicine use in patients with breast cancer and oncology services offered through telehealth versus in-person visits.

OBJECTIVE

We assessed the relationship between neighborhood socioeconomic disadvantage and telemedicine use among patients with breast cancer and examined differential provisions of oncology services between telehealth and in-person visits.

METHODS

Neighborhood socioeconomic disadvantage was measured using the Area Deprivation Index (ADI), with higher scores indicating greater disadvantages. Telemedicine and in-person visits were defined as having had a telehealth and in-person visit with a provider, respectively, in the past 12 months. Multivariable logistic regression was performed to examine the association between ADI and telemedicine use. The McNemar test was used to assess match-paired data on types of oncology services comparing telehealth and in-person visits.

RESULTS

The mean age of the patients with breast cancer (n=1163) was 61.8 (SD 12.0) years; 4.58% (52/1161) identified as Asian, 19.72% (229/1161) as Black, 3.01% (35/1161) as Hispanic, and 72.78% (845/1161) as White. Overall, 35.96% (416/1157) had a telemedicine visit in the past 12 months. Of these patients, 65% (266/409) had a videoconference visit only, 22.7% (93/409) had a telephone visit only, and 12.2% (50/409) had visits by both videoconference and telephone. Higher ADI scores were associated with a lower likelihood of telemedicine use (adjusted odds ratio [AOR] 0.89, 95% CI 0.82-0.97). Black (AOR 2.38, 95% CI 1.41-4.00) and Hispanic (AOR 2.65, 95% CI 1.07-6.58) patients had greater odds of telemedicine use than White patients. Compared to patients with high school or less education, those with an associate's degree (AOR 2.67, 95% CI 1.33-5.35), a bachelor's degree (AOR 2.75, 95% CI 1.38-5.48), or a graduate or professional degree (AOR 2.57, 95% CI 1.31-5.04) had higher odds of telemedicine use in the past 12 months. There were no significant differences in providing treatment consultation (45/405, 11.1% vs 55/405, 13.6%; P=.32) or cancer genetic counseling (11/405, 2.7% vs 19/405, 4.7%; P=.14) between telehealth and in-person visits. Of the telemedicine users, 95.8% (390/407) reported being somewhat to extremely satisfied, and 61.8% (254/411) were likely or very likely to continue using telemedicine.

CONCLUSIONS

In this study of a multiethnic cohort of patients with breast cancer, our findings suggest that neighborhood-level socioeconomic disparities exist in telemedicine use and that telehealth visits could be used to provide treatment consultation and cancer genetic counseling. Oncology programs should address these disparities and needs to improve care delivery and achieve telehealth equity for their patient populations.

A Systematic Review of Artificial Intelligence Used to Predict Loneliness, Social Isolation, and Drug Use During the COVID-19 Pandemic

This systematic literature review evaluates the role of machine learning, artificial intelligence (AI), and social determinants of health (SDOH) in identifying loneliness during the COVID-19 pandemic. By examining various studies and articles through a comprehensive search of databases EBSCOhost, Medline Complete, Academic Search Complete, Directory of Open Access Journals, and Complementary Index, the research team sought to discern consistent themes and patterns. We identified four constructs central to understanding the impact of the pandemic on societal well-being: (1) the prediction of compliance with COVID-19 measures, (2) the prediction of loneliness and its effects, (3) the prediction of well-being and social inclusion, and (4) the prediction of drug use. Within these constructs, prevalent themes related to opioid overdose, stress levels, mental health, well-being, and cognitive decline emerged. The adherence to the PRISMA 2020 checklist has resulted in a PRISMA flow diagram that categorizes the selected literature. The findings of this review, including the proportion of studies predicting various attributes related to loneliness, demonstrate the critical intersections between machine learning, AI, SDOH, and the psychosocial phenomenon of loneliness amidst a global health crisis. The review results provide a summary of the occurrences and predictive percentages of each construct as determined by the literature, contributing to a nuanced understanding of the pandemic's multifaceted impact on loneliness, social isolation, and drug use. Using AI to predict these constructs has remarkable capabilities in identifying individuals at risk and facilitating timely interventions to mitigate adverse outcomes and promote mental health resilience in the face of challenges such as the COVID-19 pandemic. Moving forward, future research is warranted to refine AI algorithms, validate predictive models and utilize AI-based interventions in healthcare and mental health services while ensuring data security, and individuals' privacy.

Food insecurity in pediatric HIV: understanding a critical challenge in the United States

Advancing the well-being of individuals living with HIV necessitates attention to social determinants of health, including food insecurity. Through a clinical and community-based needs assessment, we aimed to gain insight into experiences of food insecurity among patients receiving care at a large pediatric HIV outpatient clinic in the Southeastern United States. We adopted a multimodal assessment approach involving a literature review, community profiling, key informant interviews, focus group discussions with staff, patients and parents and a community stakeholder advisory meeting. Our needs assessment demonstrates that food insecurity is an important aspect of the lived experience of children, adolescents and young adults living with HIV. Clinical staff agreed that food insecurity screening should be incorporated into the patient care workflow but ideally only in concert with providing resources that meet their needs. We formulated a recommendation matrix for addressing food insecurity based on priority importance and feasibility. Collaborative relationships between healthcare practitioners and leaders, community-based organizations and local and federal funding sources are vital for enhancing patients' access to sustainable, reliable solutions to this fundamental determinant of health. Our approach provides a tested model for other clinics seeking to identify and alleviate food insecurity among patients.

Social Vulnerability and Biological Aging in New York City: An Electronic Health Records-Based Study

Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging. Social Vulnerability Index (SVI) is a composite index accounting for different facets of the social, economic, and demographic environment grouped into four themes: socioeconomic status, household composition and disability, minority status and language, and housing and transportation. We aim to assess the concurrent and combined associations of the four SVI themes on PhenoAgeAccel and the differential effects on disadvantaged groups. We use electronic health records data from 31,913 patients from the Mount Sinai Health System (116,952 person-years) and calculate PhenoAge for years with available laboratory results (2011-2022). PhenoAge is calculated as a weighted linear combination of lab results and PhenoAgeAccel is the differential between PhenoAge and chronological age. A decile increase in the mixture of SVI dimensions was associated with an increase of 0.23 years (95% CI: 0.21, 0.25) in PhenoAgeAccel. The socioeconomic status dimension was the main driver of the association, accounting for 61% of the weight. Interaction models revealed a more substantial detrimental association for women and racial and ethnic minorities with differences in leading SVI themes. These findings suggest that neighborhood-level social vulnerability increases the biological age of its residents, increasing morbidity and mortality risks. Socioeconomic status has the larger detrimental role amongst the different facets of social environment.

The health implications of neighborhood networks based on daily mobility in US cities

A large body of research has been dedicated to understanding the neighborhood conditions that impact health, which outcomes are affected, and how these associations vary by demographic and socioeconomic neighborhood and individual characteristics. This literature has focused mostly on the neighborhoods in which individuals reside, thus failing to recognize that residents across race/ethnicity and class spend a non-trivial amount of their time in neighborhoods far from their residential settings. To address this gap, we use mobile phone data from the company SafeGraph to compare racial inequality in neighborhood socioeconomic advantage exposure across three scales: the neighborhoods that residents live in, their adjacent neighborhoods, and the neighborhoods that they regularly visit. We found that the socioeconomic advantage levels in neighborhood networks differ from the levels at the residential and adjacent scales across all ethnoracial neighborhoods. Furthermore, socioeconomic advantage at the network level is associated with diabetes and hypertension prevalence above and beyond its impact at the residential and adjacent levels. We also find ethnoracial differences in these associations, with greater beneficial consequences of network socioeconomic advantage exposure on hypertension and diabetes for white neighborhoods. Future social determinants of health research needs to reconceptualize exposure to include the larger neighborhood network that a community is embedded in based on where their residents travel to and from.

Where you live matters: Area deprivation predicts poor survival and liver transplant waitlisting

Social determinants of health (SDOH) are important predictors of poor clinical outcomes in chronic diseases, but their associations among the general cirrhosis population and liver transplantation (LT) are limited. We conducted a retrospective, multiinstitutional analysis of adult (≥18-years-old) patients with cirrhosis in metropolitan Chicago to determine the associations of poor neighborhood-level SDOH on decompensation complications, mortality, and LT waitlisting. Area deprivation index and covariates extracted from the American Census Survey were aspects of SDOH that were investigated. Among 15 101 patients with cirrhosis, the mean age was 57.2 years; 6414 (42.5%) were women, 6589 (43.6%) were non-Hispanic White, 3652 (24.2%) were non-Hispanic Black, and 2662 (17.6%) were Hispanic. Each quintile increase in area deprivation was associated with poor outcomes in decompensation (sHR [subdistribution hazard ratio] 1.07; 95% CI 1.05-1.10; P < .001), waitlisting (sHR 0.72; 95% CI 0.67-0.76; P < .001), and all-cause mortality (sHR 1.09; 95% CI 1.06-1.12; P < .001). Domains of SDOH associated with a lower likelihood of waitlisting and survival included low income, low education, poor household conditions, and social support (P < .001). Overall, patients with cirrhosis residing in poor neighborhood-level SDOH had higher decompensation, and mortality, and were less likely to be waitlisted for LT. Further exploration of structural barriers toward LT or optimizing health outcomes is warranted.

Neighborhood Predictors of Poor Prenatal Care and Well-Child Visit Attendance

PURPOSE

Women and children continue to miss preventive visits. Which neighborhood factors predict inadequate prenatal care (PNC) and well-child visit (WCV) attendance remain unclear.

DESCRIPTION

In a retrospective case-control study at Virginia Commonwealth University Health System, mothers with less than 50% adherence or initiation after 5 months gestation were eligible as cases and those with ≥ 80% adherence and initiation before 5 months were eligible as controls. Children in the lowest quintile of adherence were eligible as cases and those with ≥ 80% of adherence were eligible as controls. Cases and controls were randomly selected at a 1:2 ratio and matched on birth month. Covariates were derived from the 2018 American Community Survey. A hotspot was defined as a zip code tabulation area (ZCTA) with a proportion of controls less than 0.66. ZCTAs with fewer than 5 individuals were excluded. Weighted quantile regression was used to determine which covariates were most associated with inadequate attendance.

ASSESSMENT

We identified 38 and 35 ZCTAs for the PNC and WCV analyses, respectively. Five of 11 hotspots for WCV were also hotspots for PNC. Education and income predicted 51% and 34% of the variation in missed PNCs, respectively; language, education and transportation difficulties explained 33%, 29%, and 17% of the variation in missed WCVs, respectively. Higher proportions of Black residents lived in hotspots of inadequate PCV and WCV attendance.

CONCLUSION

Neighborhood-level factors performed well in predicting inadequate PCV and WCV attendance. The disproportionate impact impact of inadequate PCV and WCV in neighborhoods where higher proportions of Black people lived highlights the potential influence of systemic racism and segregation on healthcare utilization.

Childhood opportunity and appropriate use of child safety restraints in motor vehicle collisions

Objectives

Safety restraints reduce injuries from motor vehicle collisions (MVCs) but are often improperly applied or not used. The Childhood Opportunity Index (COI) reflects social determinants of health and its study in pediatric trauma is limited. We hypothesized that MVC patients from low-opportunity neighborhoods are less likely to be appropriately restrained.

Methods

A retrospective cross-sectional study was performed on children/adolescents ≤18 years old in MVCs between January 1, 2011 and December 31, 2021. Patients were identified from the Children's Hospital Los Angeles trauma registry. The outcome was safety restraint use (appropriately restrained, not appropriately restrained). COI levels by home zip codes were stratified as very low, low, moderate, high, and very high. Multivariable regression controlling for age identified factors associated with safety restraint use.

Results

Of 337 patients, 73.9% were appropriately restrained and 26.1% were not appropriately restrained. Compared with appropriately restrained patients, more not appropriately restrained patients were from low-COI (26.1% vs 20.9%), high-COI (14.8% vs 10.8%) and very high-COI (10.2% vs 3.6%) neighborhoods. Multivariable analysis demonstrated no significant associations in appropriate restraint use and COI. There was a non-significant trend that children/adolescents from moderate-COI neighborhoods were more likely than those from very low-COI neighborhoods to be appropriately restrained (OR=1.82, 95% CI 0.78, 4.28).

Conclusion

Injury prevention initiatives focused on safety restraints should target families of children from all neighborhood types.

Level of evidence

III.

Sociodemographic Factors are Associated with Care Delivery and Outcomes in Pediatric Severe Sepsis

IMPORTANCE

Sepsis is a leading cause of morbidity and mortality in the United States and disparate outcomes exist between racial/ethnic groups despite improvements in sepsis management. These observed differences are often related to social determinants of health (SDoH). Little is known about the role of SDoH on outcomes in pediatric sepsis.

OBJECTIVE

This study examined the differences in care delivery and outcomes in children with severe sepsis based on race/ethnicity and neighborhood context (as measured by the social vulnerability index).

DESIGN SETTING AND PARTICIPANTS

This retrospective, cross-sectional study was completed in a quaternary care children's hospital. Patients 18 years old or younger who were admitted between May 1, 2018, and February 28, 2022, met the improving pediatric sepsis outcomes (IPSO) collaborative definition for severe sepsis. Composite measures of social vulnerability, care delivery, and clinical outcomes were stratified by race/ethnicity.

MAIN OUTCOMES AND MEASURES

The primary outcome of interest was admission to the PICU. Secondary outcomes were sepsis recognition and early goal-directed therapy (EGDT).

RESULTS

A total of 967 children met the criteria for IPSO-defined severe sepsis, of whom 53.4% were White/non-Hispanic. Nearly half of the cohort (48.7%) required PICU admission. There was no difference in illness severity at PICU admission by race (1.01 vs. 1.1, p = 0.18). Non-White race/Hispanic ethnicity was independently associated with PICU admission (odds ratio [OR] 1.35 [1.01-1.8], p = 0.04). Although social vulnerability was not independently associated with PICU admission (OR 0.95 [0.59-1.53], p = 0.83), non-White children were significantly more likely to reside in vulnerable neighborhoods (0.66 vs. 0.38, p < 0.001). Non-White race was associated with lower sepsis recognition (87.8% vs. 93.6%, p = 0.002) and less EGDT compliance (35.7% vs. 42.8%, p = 0.024).

CONCLUSIONS AND RELEVANCE

Non-White race/ethnicity was independently associated with PICU admission. Differences in care delivery were also identified. Prospective studies are needed to further investigate these findings.

Validity evidence and psychometric evaluation of a socially accountable health index for health professions schools

There is an expectation that health professions schools respond to priority societal health needs. This expectation is largely based on the underlying assumption that schools are aware of the priority needs in their communities. This paper demonstrates how open-access, pan-national health data can be used to create a reliable health index to assist schools in identifying societal needs and advance social accountability in health professions education. Using open-access data, a psychometric evaluation was conducted to examine the reliability and validity of the Canadian Health Indicators Framework (CHIF) conceptual model. A non-linear confirmatory factor analysis (CFA) on 67 health indicators, at the health-region level (n = 97) was used to assess the model fit of the hypothesized 10-factor model. Reliability analysis using McDonald's Omega were conducted, followed by Pearson's correlation coefficients. Findings from the non-linear CFA rejected the original conceptual model structure of the CHIF. Exploratory post hoc analyses were conducted using modification indices and parameter constraints to improve model fit. A final 5-factor multidimensional model demonstrated superior fit, reducing the number of indicators from 67 to 32. The 5-factors included: Health Conditions (8-indicators); Health Functions (6-indicators); Deaths (5-indicators); Non-Medical Health Determinants (7-indicators); and Community & Health System Characteristics (6-indicators). All factor loadings were statistically significant (p < 0.001) and demonstrated excellent internal consistency ( ω >0.95). Many schools struggle to identify and measure socially accountable outcomes. The process highlighted in this paper and the indices developed serve as starting points to allow schools to leverage open-access data as an initial step in identifying societal needs.

Association of social determinants of health International Classification of Disease, Tenth Edition clinical modification codes with outcomes for emergency general surgery and trauma admissions

BACKGROUND

Patients with Acute Care Surgery needs (ie, emergency general surgery diagnosis or trauma admission) are at particularly high risk for nonmedical patient-related factors that can be important drivers of healthcare outcomes. These social determinants of health are typically ascertained at the geographic area level (ie, county or neighborhood) rather than at the individual patient level. Recently, the International Classification of Diseases Tenth Revision, Tenth Edition created codes to capture health hazards related to patient socioeconomic and psychosocial circumstances. We sought to characterize the impact of these social determinants of health-related codes on perioperative outcomes among patients with acute care surgery needs.

METHODS

Patients diagnosed between 2017 and 2020 with acute care surgery needs (ie, emergency general surgery diagnosis or a trauma admission) were identified in the California Department of Healthcare Access and information Patient Discharge database. Data on concomitant social determinants of health-related codes (International Classification of Diseases Tenth Revision, Tenth Edition Z55-Z65), which designated health hazards related to socioeconomic and psychosocial (socioeconomic and psychosocial, respectively) circumstances, were obtained. After controlling for patient factors, including age, sex, race, payer type, and admitting hospital, the association of socioeconomic and psychosocial codes with perioperative outcomes and hospital disposition was analyzed.

RESULTS

Among 483,280 with an acute care surgery admission (emergency general surgery: n = 289,530, 59.9%; trauma: n = 193,705, 40.1%) mean age was 56.5 years (standard deviation: 21.5) and 271,911 (56.3%) individuals were male. Overall, 16,263 (3.4%) patients had a concomitant socioeconomic and psychosocial diagnosis code. The percentage of patients with a concurrent social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis increased throughout the study period from 2.6% in 2017 to 4.4% in 2020. Patients that were male (odds ratio 1.89; 95% confidence interval 1.82, 1.96), insured by Medicaid (odds ratio 5.43; 95% confidence interval 5.15, 5.72) or self-pay (odds ratio 3.04; 95% confidence interval 2.75, 3.36) all had higher odds of having an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis. Black race did not have a significant association with an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis (odds ratio 0.99; 95% confidence interval 0.94, 1.04); however, Hispanic (odds ratio 0.44; 95% confidence interval 0.43, 0.46) and Asian (odds ratio 0.40; 95% confidence interval 0.36, 0.44) race/ethnicity was associated with a lower odds of having an social determinants of health International Classification of Diseases Tenth Revision, Tenth Edition diagnosis. After controlling for competing risk factors on multivariable analyses, the risk-adjusted probability of hospital postoperative death was 3.1% (95% confidence interval 2.8, 3.4) among patients with a social determinants of health diagnosis versus 5.9% (95% confidence interval 5.9, 6.0) (odds ratio 0.48; 95% confidence interval 0.44, 0.54) among patients without a social determinants of health diagnosis. Risk-adjusted complications were 26.7% (95% confidence interval 26.1, 37.3) among patients with a social determinants of health diagnosis compared with 31.9% (95% confidence interval 31.7, 32.0) (odds ratio 0.74; 95% confidence interval 0.71, 0.77) among patients without a social determinants of health diagnosis.

CONCLUSION

International Classification of Diseases Tenth Revision, Tenth Edition social determinants of health code use was low, with only 3.4% of patients having documentation of a socioeconomic and psychosocial circumstance. The presence of an International Classification of Diseases Tenth Revision, Tenth Edition social determinants of health code was not associated with greater odds of complications or death; however, it was associated with longer length of stay and higher odds of being discharged to a skilled nursing facility.

Chronic Disease Prevalence in the US: Sociodemographic and Geographic Variations by Zip Code Tabulation Area

Introduction

We examined the geographic distribution and sociodemographic and economic characteristics of chronic disease prevalence in the US. Understanding disease prevalence and its impact on communities is crucial for effective public health interventions.

Methods

Data came from the American Community Survey, the American Hospital Association Survey, and the Centers for Disease Control and Prevention's PLACES. We used quartile thresholds for 10 chronic diseases to assess chronic disease prevalence by Zip Code Tabulation Areas (ZCTAs). ZCTAs were scored from 0 to 20 based on their chronic disease prevalence quartile. Three prevalence categories were established: least prevalent (score ≤6), moderately prevalent (score 7-13), and highest prevalence (score ≥14). Community characteristics were compared across categories and spatial analyses to identify clusters of ZCTAs with high disease prevalence.

Results

Our study showed a high prevalence of chronic disease in the southeastern region of the US. Populations in ZCTAs with the highest prevalence showed significantly greater socioeconomic disadvantages (ie, lower household income, lower home value, lower educational attainment, and higher uninsured rates) and barriers to health care access (lower percentage of car ownership and longer travel distances to hospital-based intensive care units, emergency departments, federally qualified health centers, and pharmacies) compared with ZCTAs with the lowest prevalence.

Conclusion

Socioeconomic disparities and health care access should be addressed in communities with high chronic disease prevalence. Carefully directed resource allocation and interventions are necessary to reduce the effects of chronic disease on these communities. Policy makers and clinicians should prioritize efforts to reduce chronic disease prevalence and improve the overall health and well-being of affected communities throughout the US.

Association of ICD-10 Clinical Modification Codes for Social Determinants of Health with Surgical Outcomes and Hospital Charges Among Cancer Patients

INTRODUCTION

We sought to characterize the impact of social determinants of health (SDOH)-related codes on outcomes among patients with a cancer diagnosis.

METHODS

Patients diagnosed with lung, pancreas, colon, or rectal cancer between 2017 and 2020 were identified in the California Department of Healthcare Access and Information Patient Discharge Database. Data on concomitant SDOH-related codes (International Classification of Diseases, Tenth Revision [ICD-10] Z55-Z65) designating health hazards related to socioeconomic and psychosocial circumstances were obtained. The association of these SDOH codes with postoperative outcomes was evaluated.

RESULTS

Among 10,421 patients who underwent an operation from 2017 to 2020, median age was 66 years (interquartile range [IQR] 56-75) and nearly half of the cohort was male (n = 551,252.9%). In total, 102 (1%) patients had a concurrent ICD-10 SDOH diagnosis. After controlling for competing risk factors, the risk-adjusted probability of in-hospital death was 4.1% (95% confidence interval [CI] 1.0-7.2) among patients with an SDOH diagnosis compared with 2.9% (95% CI 2.5-3.2) among patients without an SDOH diagnosis (odds ratio [OR] 1.52, 95% CI 0.63-3.66; p = 0.258); postoperative complications were 27.0% (95% CI 20.0-34.1) compared with 24.9% (95% CI 24.1-25.6) among patients without an SDOH diagnosis (OR 1.15, 95% CI 0.73-1.82; p = 0.141), and length of stay was 10.6 days (95% CI 10.0-11.2) compared with 9.4 days (95% CI 9.3-9.5) among patients without an SDOH diagnosis. Patients with an SDOH diagnosis had a 5.19 (95% CI 3.23-8.34; p < 0.005) higher odds of being discharged to a skilled nursing facility versus patients without an SDOH diagnosis.

CONCLUSION

Uptake and utilization of ICD-10 SDOH was 1% among California patients with lung, pancreas, colon, or rectal cancer. Patients with a concomitant ICD-10 SDOH code had longer length of stay and had higher odds of being discharged to a skilled nursing facility.

Finance, race, ethnicity, and spoken language impact clinical outcomes for children with acute liver failure

BACKGROUND

Pediatric acute liver failure (PALF) is an emergency, necessitating prompt referral and management at an experienced liver transplant center. Social determinants of health (SDOH) drive healthcare disparities and can affect many aspects of disease presentation, access to care, and ultimately clinical outcomes. Potential associations between SDOH and PALF outcomes, including spontaneous recovery (SR), liver transplant (LT) or death, are unknown. This study aims to investigate how SDOH may affect PALF and therefore identify areas for intervention to mitigate unrecognized disparities.

METHODS

A retrospective, single-center cohort was analyzed and then compared and validated with data from the multicenter National Institutes of Health PALF Study Group. The single-center review included 145 patients admitted with PALF using diagnostic codes. Medical records were reviewed to extract patient demographics, family structure, inpatient social worker assessments, and clinical outcomes. Data were stratified by outcome.

RESULTS

This analysis determined that level of family support (p = .02), caretaker employment (p = .02), patient age, race, and language (p = .01) may impact clinical outcomes. Specifically, the cohort of children that died had the largest proportion of non-English speaking patients with limited support systems and parents who worked full-time. Conversely, patients who underwent LT more often belonged to English-speaking families with a homemaker and extensive support systems.

CONCLUSION

This study suggests that SDOH impact PALF outcomes and highlights patient populations facing additional challenges during an already complex healthcare emergency. These associations may indicate unconscious biases held by transplant teams when evaluating waitlist candidacy, as well as barriers to healthcare access. Strategies to better understand the broader applicability of our findings and, if confirmed, efforts to mitigate social disparities, may improve clinical outcomes in PALF.

Associations Between Social Vulnerability Indicators and Pediatric Tonsillectomy Outcomes

OBJECTIVE

To investigate the impact of neighborhood-level social vulnerability on pediatric tonsillectomy outcomes.

METHODS

This single-center retrospective cohort study included tonsillectomies performed on children aged 1 to 18 between August 2019 and August 2020. Geographic information systems were used to geocode addresses, and spatial overlays were used to assign census-tract level social vulnerability index (SVI) scores to each patient. For categorical variables, two-sided Pearson chi-square tests were used, whereas for continuous variables, paired t-tests, means, and standard deviations were calculated. SVI and its four subthemes were investigated using binomial logistic regressions to determine their impact on post-T&A complications and readmissions.

RESULTS

The study included 397 patients, with 52 having complications (13.1%) and 33 (8.3%) requiring readmissions due to their complications. Controlling for age, gender, race, insurance status, surgical indication, comorbidities, obesity, and obstructive sleep apnea, postoperative complications were associated with high overall SVI (odds ratio [OR] 5.086, 95% confidence interval [CI] 1.128-22.938), high socioeconomic vulnerability (SVI theme 1, OR 6.003, 95% CI 1.270-28.385), and high house composition vulnerability (SVI theme 2, OR 6.340, 95% CI 1.275-31.525). Readmissions were also associated with high overall SVI (10.149, 95% CI 1.293-79.647) and high housing/transportation vulnerability (SVI theme 4, OR 5.657, 95% CI 1.089-29.396).

CONCLUSION

Social vulnerability at the neighborhood level is linked to poorer surgical outcomes in otherwise healthy children, suggesting a target for community-based interventions. Because of the increased risk, it may have implications for preoperative decision-making, treatment plans, and clinic follow-ups.

LEVEL OF EVIDENCE: 3

Laryngoscope, 134:954-962, 2024.

Analyzing Multiple Social Determinants of Health Using Different Clustering Methods

Social determinants of health (SDoH) have become an increasingly important area to acknowledge and address in healthcare; however, dealing with these measures in outcomes research can be challenging due to the inherent collinearity of these factors. Here we discuss our experience utilizing three statistical methods-exploratory factor analysis (FA), hierarchical clustering, and latent class analysis (LCA)-to analyze data collected using an electronic medical record social risk screener called Protocol for Responding to and Assessing Patient Assets, Risks, and Experience (PRAPARE). The PRAPARE tool is a standardized instrument designed to collect patient-reported data on SDoH factors, such as income, education, housing, and access to care. A total of 2380 patients had complete PRAPARE and neighborhood-level data for analysis. We identified a total of three composite SDoH clusters using FA, along with four clusters identified through hierarchical clustering, and four latent classes of patients using LCA. Our results highlight how different approaches can be used to handle SDoH, as well as how to select a method based on the intended outcome of the researcher. Additionally, our study shows the usefulness of employing multiple statistical methods to analyze complex SDoH gathered using social risk screeners such as the PRAPARE tool.

Perinatal Outcomes among Women Identified by a Community Health Needs Assessment

OBJECTIVE

The aim of the study is to compare perinatal outcomes for women with greater social needs, as identified by the Community Health Needs Assessment, to those of women living in other areas of the county.

STUDY DESIGN

This was a retrospective cohort study of pregnant women delivering at a large inner-city county hospital. Perinatal outcomes were analyzed for women living within a target area with substantial health disparities and social needs, and compared with those women living outside the target area. Statistical analysis included student's t-test, Chi square, and logistic regression.

RESULTS

Between January 2015 and July 2020, 66,936 women delivered at Parkland hospital. Of these, 7,585 (11%) resided within the target area. These women were younger (26.8 ± 6.5 vs. 27.9 ± 6.4 years, p < 0.001), more likely to be black (37 vs. 13%, p < 0.001), and had a higher body mass index or BMI (33.3 ± 7.0 vs. 32.6 ± 6.4 kg/m2, p < 0.001). All women were likely to access prenatal care, with 7,320 (96.5%) in the target area and 57,677 (97.2%) outside the area attending at least one visit. Adverse perinatal outcomes were increased for women living within the target area, which persisted after adjustment for age, race, and BMI. This included an increased risk of preeclampsia (adjusted risk ratio [aRR] 1.1, 95% confidence interval or CI [1.03, 1.2]) and abruption (aRR 1.3, 95% CI [1.1, 1.7]), as well as preterm birth before both 34 weeks (aRR 1.3, 95% CI [1.2, 1.5]) and 28 weeks (aRR 1.3, 95% CI [1.02,1.7]). It follows that neonatal ICU admission (aRR 2.1, 95% CI [1.3, 3.4]) and neonatal death (aRR 1.2, 95% CI [1.1, 1.3]) were increased within the target area. Interestingly, rate of postpartum visit attendance was higher in the target area (57 vs. 48%), p < 0.001.

CONCLUSION

Even among vulnerable populations, women in areas with worse health disparities and social needs are at greater risk of adverse perinatal outcomes. Efforts to achieve health equity will need to address social disparities.

KEY POINTS

· At a county hospital, 97% of women accessed prenatal care.. · Greater social needs were associated with adverse perinatal outcomes.. · Differences persisted with adjustment for age, race, and BMI..

Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States

BACKGROUND

Exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment.

METHODS

Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3.

RESULTS

In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type.

CONCLUSIONS

Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health

Importance

Social determinants of health (SDOH) influence child health. However, most previous studies have used individual, small-set, or cherry-picked SDOH variables without examining unbiased computed SDOH patterns from high-dimensional SDOH factors to investigate associations with child mental health, cognition, and physical health.

Objective

To identify SDOH patterns and estimate their associations with children's mental, cognitive, and physical developmental outcomes.

Design, Setting, and Participants

This population-based cohort study included children aged 9 to 10 years at baseline and their caregivers enrolled in the Adolescent Brain Cognitive Development (ABCD) Study between 2016 and 2021. The ABCD Study includes 21 sites across 17 states.

Exposures

Eighty-four neighborhood-level, geocoded variables spanning 7 domains of SDOH, including bias, education, physical and health infrastructure, natural environment, socioeconomic status, social context, and crime and drugs, were studied. Hierarchical agglomerative clustering was used to identify SDOH patterns.

Main Outcomes and Measures

Associations of SDOH and child mental health (internalizing and externalizing behaviors) and suicidal behaviors, cognitive function (performance, reading skills), and physical health (body mass index, exercise, sleep disorder) were estimated using mixed-effects linear and logistic regression models.

Results

Among 10 504 children (baseline median [SD] age, 9.9 [0.6] years; 5510 boys [52.5%] and 4994 girls [47.5%]; 229 Asian [2.2%], 1468 Black [14.0%], 2128 Hispanic [20.3%], 5565 White [53.0%], and 1108 multiracial [10.5%]), 4 SDOH patterns were identified: pattern 1, affluence (4078 children [38.8%]); pattern 2, high-stigma environment (2661 children [25.3%]); pattern 3, high socioeconomic deprivation (2653 children [25.3%]); and pattern 4, high crime and drug sales, low education, and high population density (1112 children [10.6%]). The SDOH patterns were distinctly associated with child health outcomes. Children exposed to socioeconomic deprivation (SDOH pattern 3) showed the worst health profiles, manifesting more internalizing (β = 0.75; 95% CI, 0.14-1.37) and externalizing (β = 1.43; 95% CI, 0.83-2.02) mental health problems, lower cognitive performance, and adverse physical health.

Conclusions

This study shows that an unbiased quantitative analysis of multidimensional SDOH can permit the determination of how SDOH patterns are associated with child developmental outcomes. Children exposed to socioeconomic deprivation showed the worst outcomes relative to other SDOH categories. These findings suggest the need to determine whether improvement in socioeconomic conditions can enhance child developmental outcomes.

Sociome Data Commons: A scalable and sustainable platform for investigating the full social context and determinants of health

Background/Objective

Non-clinical aspects of life, such as social, environmental, behavioral, psychological, and economic factors, what we call the sociome, play significant roles in shaping patient health and health outcomes. This paper introduces the Sociome Data Commons (SDC), a new research platform that enables large-scale data analysis for investigating such factors.

Methods

This platform focuses on "hyper-local" data, i.e., at the neighborhood or point level, a geospatial scale of data not adequately considered in existing tools and projects. We enumerate key insights gained regarding data quality standards, data governance, and organizational structure for long-term project sustainability. A pilot use case investigating sociome factors associated with asthma exacerbations in children residing on the South Side of Chicago used machine learning and six SDC datasets.

Results

The pilot use case reveals one dominant spatial cluster for asthma exacerbations and important roles of housing conditions and cost, proximity to Superfund pollution sites, urban flooding, violent crime, lack of insurance, and a poverty index.

Conclusion

The SDC has been purposefully designed to support and encourage extension of the platform into new data sets as well as the continued development, refinement, and adoption of standards for dataset quality, dataset inclusion, metadata annotation, and data access/governance. The asthma pilot has served as the first driver use case and demonstrates promise for future investigation into the sociome and clinical outcomes. Additional projects will be selected, in part for their ability to exercise and grow the capacity of the SDC to meet its ambitious goals.

Treatment patterns and outcomes of Medicare enrolees who developed venous leg ulcers

OBJECTIVE

To retrospectively evaluate the comorbidities, treatment patterns and outcomes of Medicare enrolees who developed venous leg ulcers (VLUs).

METHOD

Medicare Limited Data Standard Analytic Hospital Inpatient and Outpatient Department Files were used to follow patients who received medical care for a VLU between 1 October 2015 and 2 October 2019. Patients diagnosed with chronic venous insufficiency (CVI) and a VLU were propensity matched into four groups based on their treatment regimen. Episode claims were used to document demographics, comorbidities and treatments of Medicare enrolees who developed VLUs, as well as important outcomes, such as time to ulcer closure, rates of complications and hospital utilisation rates. Outcomes were compared across key propensity-matched groups.

RESULTS

In total, 42% of Medicare enrolees with CVI (n=1,225,278), developed at least one VLU during the study, and 79% had their episode claim completed within one year. However, 59% of patients developed another VLU during the study period. This analysis shows that only 38.4% of VLU episodes received documented VLU conservative care treatment. Propensity-matched episodes that received an advanced treatment or high-cost skin substitutes for a wound which had not progressed by 30 days demonstrated the best outcomes when their cellular, acellular, matrix-like product (CAMP) treatment was applied weekly or biweekly (following parameters for use). Complications such as rates of infection (33%) and emergency department visits (>50%) decreased among patients who received an advanced treatment (following parameters for use).

CONCLUSION

Medicare enrolees with CVI have diverse comorbidities and many do not receive sufficient management, which contributes to high rates of VLUs and subsequent complications. Medicare patients at risk of a VLU who receive early identification and advanced CAMP treatment demonstrated improved quality of life and significantly reduced healthcare resource utilisation.

Social determinants of access to timely elective surgery in Ontario, Canada: a cross-sectional population level study

BACKGROUND

Equitable access to surgical care has clinical and policy implications. We assess the association between social disadvantage and wait times for elective surgical procedures in Ontario.

METHODS

We conducted a cross-sectional analysis using administrative data sets of adults receiving nonurgent inguinal hernia repair, cholecystectomy, hip arthroplasty, knee arthroplasty, arthroscopy, benign uterine surgery and cataract surgery from April 2013 to December 2019. We assessed the relation between exceeding target wait times and the highest versus lowest quintile of marginalization dimensions by use of generalized estimating equations logistic regression.

RESULTS

Of the 1 385 673 procedures included, 174 633 (12.6%) exceeded the target wait time. Adjusted analysis for cataract surgery found significantly increased odds of exceeding wait times for residential instability (adjusted odd ratio [OR] 1.16, 95% confidence interval [CI] 1.11-1.21) and recent immigration (adjusted OR 1.12, 95% CI 1.07-1.18). The highest deprivation quintile was associated with 18% (adjusted OR 1.18, 95% CI 1.12-1.24) and 20% (adjusted OR 1.20, 95% CI 1.12-1.28) increased odds of exceeding wait times for knee and hip arthroplasty, respectively. Residence in areas where higher proportions of residents self-identify as being part of a visible minority group was independently associated with reduced odds of exceeding target wait times for hip arthroplasty (adjusted OR 0.82, 95% CI 0.75-0.91), cholecystectomy (adjusted OR 0.68, 95% CI 0.59-0.79) and hernia repair (adjusted OR 0.65, 95% CI 0.56-0.77) with an opposite effect in benign uterine surgery (adjusted OR 1.28, 95% CI 1.17-1.40).

INTERPRETATION

Social disadvantage had a small and inconsistent impact on receiving care within wait time targets. Future research should consider these differences as they relate to resource distribution and the organization of clinical service delivery.

The Association between Mediated Deprivation and Ovarian Cancer Survival among African American Women

BACKGROUND

Deprivation indices are often used to adjust for socio-economic disparities in health studies. Their role has been partially evaluated for certain population-level cancer outcomes, but examination of their role in ovarian cancer is limited. In this study, we evaluated a range of well-recognized deprivation indices in relation to cancer survival in a cohort of self-identified Black women diagnosed with ovarian cancer. This study aimed to determine if clinical or diagnostic characteristics lie on a mediating pathway between socioeconomic status (SES) and deprivation and ovarian cancer survival in a minority population that experiences worse survival from ovarian cancer.

METHODS

We used mediation analysis to look at the direct and indirect causal effects of deprivation indices with main mediators of the SEER stage at diagnosis and residual disease. The analysis employed Bayesian structural equation models with variable selection. We applied a joint Bayesian structural model for the mediator, including a Weibull mixed model for the vital outcome with deprivation as exposure. We selected modifiers via a Monte Carlo model selection procedure.

RESULTS

The results suggest that high SES-related indices, such as Yost, Kolak urbanicity (URB), mobility (MOB) and SES dimensions, and concentrated disadvantage index (CDI), all have a significant impact on improved survival. In contrast, area deprivation index (ADI)/Singh, and area level poverty (POV) did not have a major impact. In some cases, the indirect effects have very wide credible intervals, so the total effect is not well estimated despite the estimation of the direct effect.

CONCLUSIONS

First, it is clear that commonly used indices such as Yost, or CDI both significantly impact the survival experience of Black women diagnosed with epithelial ovarian cancer. In addition, the Kolak dimension indices (URB, MOB, mixed immigrant: MICA and SES) also demonstrate a significant association, depending on the mediator. Mediation effects differ according to the mediator chosen.

Deprivation and segregation in ovarian cancer survival among African American women: a mediation analysis

PURPOSE

Deprivation and segregation indices are often examined as possible explanations for observed health disparities in population-based studies. In this study, we assessed the role of recognized deprivation and segregation indices specifically as they affect survival in a cohort of self-identified Black women diagnosed with ovarian cancer who enrolled in the African American Cancer Epidemiology Study.

METHODS

Mediation analysis was used to examine the direct and indirect effects between deprivation or segregation and overall survival via a Bayesian structural equation model with Gibbs variable selection.

RESULTS

The results suggest that high socioeconomic status-related indices have an association with increased survival, ranging from 25% to 56%. In contrast, index of concentration at the extremes-race does not have a significant impact on overall survival. In many cases, the indirect effects have very wide credible intervals; consequently, the total effect is not well estimated despite the estimation of the direct effect.

CONCLUSIONS

Our results show that Black women living in higher socioeconomic status neighborhoods are associated with increased survival with ovarian cancer using area-level economic indices such as Yost or index of concentration at the extremes-income. In addition, the Kolak urbanization index has a similar impact and highlights the importance of area-level deprivation and segregation as potentially modifiable social factors in ovarian cancer survival.

A Novel Approach to Developing Disease and Outcome-Specific Social Risk Indices

INTRODUCTION

A variety of industry composite indices are employed within health research in risk-adjusted outcome measures and to assess health-related social needs. During the COVID-19 pandemic, the relationships among risk adjustment, clinical outcomes, and composite indices of social risk have become relevant topics for research and healthcare operations. Despite the widespread use of these indices, composite indices are often comprised of correlated variables and therefore may be affected by information duplicity of their underlying risk factors.

METHODS

A novel approach is proposed to assign outcome- and disease group-driven weights to social risk variables to form disease and outcome-specific social risk indices and apply the approach to the county-level Centers for Disease Control and Prevention social vulnerability factors for demonstration. The method uses a subset of principal components reweighed through Poisson rate regressions while controlling for county-level patient mix. The analyses use 6,135,302 unique patient encounters from 2021 across seven disease strata.

RESULTS

The reweighed index shows reduced root mean squared error in explaining county-level mortality in five of the seven disease strata and equivalent performance in the remaining strata compared with the reduced root mean squared error using the current Centers for Disease Control and Prevention Social Vulnerability Index as a benchmark.

CONCLUSIONS

A robust method is provided, designed to overcome challenges with current social risk indices, by accounting for redundancy and assigning more meaningful disease and outcome-specific variable weights.

Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study

BACKGROUND

Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors.

OBJECTIVE

This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US.

METHODS

Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together.

RESULTS

Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas.

CONCLUSIONS

The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

Association between the Environmental Quality Index and Textbook Outcomes Among Medicare Beneficiaries Undergoing Surgery for Early-Stage Pancreatic Adenocarcinoma

BACKGROUND

Access to high-quality cancer care is affected by environmental exposures and structural inequities. This study sought to investigate the association between the environmental quality index (EQI) and achievement of textbook outcomes (TO) among Medicare beneficiaries over the age of 65 who underwent surgical resection for early-stage pancreatic adenocarcinoma (PDAC).

METHODS

Patients diagnosed with early-stage PDAC from 2004 to 2015 were identified using the SEER-Medicare database and combined with the US Environmental Protection Agency's EQI data. High EQI category indicated poor environmental quality, whereas low EQI indicated better environmental conditions.

RESULTS

A total of 5,310 patients were included, of which 45.0% (n = 2,387) patients achieved TO. Median age was 73 years and more than half were female (n = 2,807, 52.9%), married (n = 3,280, 61.8%), and resided in the Western region of the US (n = 2,712, 51.1%). On multivariable analysis, patients residing in moderate and high EQI counties were less likely to achieve a TO (referent: low EQI; moderate EQI: OR 0.66, 95% CI 0.46-0.95; high EQI: OR 0.65, 95% CI 0.45-0.94; p < 0.05). Increasing age (OR 0.98, 95%CI 0.97-0.99), racial minorities (OR 0.73, 95% CI 0.63-0.85), having a Charlson co-morbidity index > 2 (OR 0.54, 95%CI 0.47-0.61) and stage II disease (OR 0.82, 95%CI 0.71-0.96) were also associated with not achieving a TO (all p < 0.001).

CONCLUSION

Older Medicare patients residing in moderate or high EQI counties were less likely to achieve an "optimal" TO after surgery. These results demonstrate that environmental factors may drive post-operative outcomes among patients with PDAC.

Persistence of Poverty and its Impact on Surgical Care and Postoperative Outcomes

OBJECTIVE

We sought to characterize the association between prolonged county-level poverty with postoperative outcomes.

BACKGROUND

The impact of long-standing poverty on surgical outcomes remains ill-defined.

METHODS

Patients who underwent lung resection, colectomy, coronary artery bypass graft, or lower extremity joint replacement were identified from Medicare Standard Analytical Files Database (2015-2017) and merged with data from the American Community Survey and the United States Department of Agriculture. Patients were categorized according to the duration of high poverty status from 1980 to 2015 [ie, never high poverty (NHP), persistent poverty (PP)]. Logistic regression was used to characterize the association between the duration of poverty and postoperative outcomes. Principal component and generalized structural equation modeling were used to assess the effect of mediators in the achievement of Textbook Outcomes (TO).

RESULTS

Overall, 335,595 patients underwent lung resection (10.1%), colectomy (29.4%), coronary artery bypass graft (36.4%), or lower extremity joint replacement (24.2%). While 80.3% of patients lived in NHP, 4.4% resided in PP counties. Compared with NHP, patients residing in PP were at increased risk of serious postoperative complications [odds ratio (OR)=1.10, 95% CI: 1.05-1.15], 30-day readmission (OR=1.09, 95% CI: 1.01-1.16), 30-day mortality (OR=1.08, 95% CI: 1.00-1.17), and higher expenditures (mean difference, $1010.0, 95% CI: 643.7-1376.4) (all P <0.05). Notably, PP was associated with lower odds of achieving TO (OR=0.93, 95% CI: 0.90-0.97, P <0.001); 65% of this effect was mediated by other social determinant factors. Minority patients were less likely to achieve TO (OR=0.81, 95% CI: 0.79-0.84, P <0.001), and the disparity persisted across all poverty categories.

CONCLUSIONS

County-level poverty duration was associated with adverse postoperative outcomes and higher expenditures. These effects were mediated by various socioeconomic factors and were most pronounced among minority patients.

Advancing health equity through implementation science: Identifying and examining measures of the outer setting

BACKGROUND

Implementation science (IS) could accelerate progress toward achieving health equity goals. However, the lack of attention to the outer setting where interventions are implemented limits applicability and generalizability of findings to different populations, settings, and time periods. We developed a data resource to assess outer setting across seven centers funded by the National Cancer Institute's IS Centers in Cancer Control (ISC3) Network Program.

OBJECTIVE

To describe the development of the Outer Setting Data Resource and characterize the county-level outer context across Centers.

METHODS

Our Data Resource captures seven key environments, including: (1) food; (2) physical; (3) economic; (4) social; (5) health care; (6) cancer behavioral and screening; and (7) cancer-related policy. Data were obtained from public sources including the US Census and American Community Survey. We present medians and interquartile ranges based on the distribution of all counties in the US, all ISC3 centers, and within each Center for twelve selected measures. Distributions of each factor are compared with the national estimate using single sample sign tests.

RESULTS

ISC3 centers' catchment areas include 458 counties and over 126 million people across 28 states. The median percentage of population living within ½ mile of a park is higher in ISC3 counties (38.0%, interquartile range (IQR): 16.0%-59.0%) compared to nationally (18.0%, IQR: 7.0%-38.0%; p < 0.0001). The median percentage of households with no broadband access is significantly lower in ISC3 counties (28.4%, IQR: 21.4%-35.6%) compared the nation overall (32.8%, IQR: 25.8%-41.2%; p < 0.0001). The median unemployment rate was significantly higher in ISC3 counties (5.2%, IQR: 4.1%-6.4%) compared to nationally (4.9%, 3.6%-6.3%, p = 0.0006).

CONCLUSIONS

Our results indicate that the outer setting varies across Centers and often differs from the national level. These findings demonstrate the importance of assessing the contextual environment in which interventions are implemented and suggest potential implications for intervention generalizability and scalability.

Enriching Real-world Data with Social Determinants of Health for Health Outcomes and Health Equity: Successes, Challenges, and Opportunities

OBJECTIVE

To summarize the recent methods and applications that leverage real-world data such as electronic health records (EHRs) with social determinants of health (SDoH) for public and population health and health equity and identify successes, challenges, and possible solutions.

METHODS

In this opinion review, grounded on a social-ecological-model-based conceptual framework, we surveyed data sources and recent informatics approaches that enable leveraging SDoH along with real-world data to support public health and clinical health applications including helping design public health intervention, enhancing risk stratification, and enabling the prediction of unmet social needs.

RESULTS

Besides summarizing data sources, we identified gaps in capturing SDoH data in existing EHR systems and opportunities to leverage informatics approaches to collect SDoH information either from structured and unstructured EHR data or through linking with public surveys and environmental data. We also surveyed recently developed ontologies for standardizing SDoH information and approaches that incorporate SDoH for disease risk stratification, public health crisis prediction, and development of tailored interventions.

CONCLUSIONS

To enable effective public health and clinical applications using real-world data with SDoH, it is necessary to develop both non-technical solutions involving incentives, policies, and training as well as technical solutions such as novel social risk management tools that are integrated into clinical workflow. Ultimately, SDoH-powered social risk management, disease risk prediction, and development of SDoH tailored interventions for disease prevention and management have the potential to improve population health, reduce disparities, and improve health equity.

Incidence of Subsequent Mental Health Disorders and Social Adversity Following Pediatric Concussion: A Longitudinal, Population-Based Study

OBJECTIVE

To determine the long-term risk of new adverse psychosocial outcomes among adolescents diagnosed with a concussion compared with those not diagnosed.

STUDY DESIGN

A retrospective, population-based cohort study was conducted. Adolescents (10-18 years) with a physician-diagnosed concussion between 2000 and 2005 were matched on neighborhood and age with 5 controls without concussion from the general population. New-onset mental health disorders, medication use, social, and justice outcomes were extracted using datasets linked to the population data repository. Adolescents were followed for 11-16 years. Adjusted hazard ratios (95% CIs) were estimated.

RESULTS

In total, 2082 adolescents with a concussion were matched to 10 510 without. Adolescents with a concussion had an increased risk of any mental health disorder (HR 1.34; 95% CI 1.25-1.45), mood disorder (HR 1.30; 95% 1.18-1.43), psychosis (HR 1.43; 95% CI 1.18-1.74), substance abuse disorder (HR 1.67; 95% 1.31-2.14), and receiving a psychotropic prescription (HR 1.31; 95% CI 1.20-1.42). Female adolescents had an increased risk of ADHD following concussion (HR 1.89; 95% CI 1.17-3.05). Adolescents with a concussion had an increased risk of being accused (HR 1.22; 95% CI 1.11-1.34), victim (HR 1.29; 95% CI 1.11-1.48), or witness (HR 1.16; 95% CI 1.01-1.32) of a crime, or contact with Child and Family Services (HR 1.33; 95% CI 1.10-1.62). There was no association between concussion and attempting or completing suicide, receiving housing support, or collecting income support.

CONCLUSIONS

Concussion was associated with an increased risk for multiple adverse psychosocial outcomes. Future work should focus on early identification of those at risk of these outcomes to help optimize longitudinal medical care and support.

Intersections of oppression: Examining the interactive effect of racial discrimination and neighborhood poverty on PTSD symptoms in Black women

Black Americans living in urban environments are disproportionately impacted by posttraumatic stress disorder (PTSD). Both racial discrimination and neighborhood poverty are factors that contribute to this health disparity. However, studies focused on the intersection of these two oppressive systems on PTSD symptoms are lacking. To address this gap in the literature, we assessed the interactive effects of racial discrimination and neighborhood poverty on PTSD symptoms in an urban sample of trauma-exposed Black women (N = 300). Simple moderation analysis was used to assess the main and interactive effects of racial discrimination and neighborhood poverty on PTSD symptoms. The overall model significantly predicted PTSD symptoms, with a main effect of racial discrimination (B = 1.87, p = .009) and neighborhood poverty rate (B = 0.29, p = .008), independent of prior trauma exposure and percentage of Black residents in the zip code. More frequent experiences of racial discrimination and higher rates of neighborhood poverty both predicted higher PTSD symptoms. There was also a trending interaction of racial discrimination and neighborhood poverty (B = -0.05, p = .054), where the effect of neighborhood poverty on PTSD symptoms was only present for those who reported fewer experiences of racial discrimination. Our results suggest that people who have experienced more instances of racial discrimination show high levels of PTSD symptoms regardless of neighborhood poverty rates and highlight the importance of considering multiple levels of oppression that Black individuals face while diagnosing and treating stress-related psychopathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neighborhood-level COVID vaccination and booster disparities: A population-level analysis across California

Objectives

To describe vaccine and booster uptake by neighborhood-level factors in California.

Methods

We examined trends in COVID-19 vaccination up to September 21, 2021, and boosters up to March 29, 2022 using data from the California Department of Public Health. Quasi-Poisson regression was used to model the association between neighborhood-level factors and fully vaccinated and boosted among ZIP codes. Sub-analyses on booster rates were compared among the 10 census regions.

Results

In a minimally adjusted model, a higher proportion of Black residents was associated with lower vaccination (HR = 0.97; 95%CI: 0.96-0.98). However, in a fully adjusted model, proportion of Black, Hispanic/Latinx, and Asian residents were associated with higher vaccination rates (HR = 1.02; 95%CI: 1.01-1.03 for all). The strongest predictor of low vaccine coverage was disability (HR = 0.89; 95%CI: 0.86-0.91). Similar trends persisted for booster doses. Factors associated with booster coverage varied by region.

Conclusions

Examining neighborhood-level factors associated with COVID-19 vaccination and booster rates uncovered significant variation within the large and geographically and demographically diverse state of California. Equity-based approaches to vaccination must ensure a robust consideration of multiple social determinants of health.

Neighborhood factors and triple negative breast cancer: The role of cumulative exposure to area-level risk factors

BACKGROUND

Despite similar incidence rates among Black and White women, breast cancer mortality rates are 40% higher among Black women. More than half of the racial difference in breast cancer mortality can be attributed to triple negative breast cancer (TNBC), an aggressive subtype of invasive breast cancer that disproportionately affects Black women. Recent research has implicated neighborhood conditions in the etiology of TNBC. This study investigated the relationship between cumulative neighborhood-level exposures and TNBC risk.

METHODS

This single-institution retrospective study was conducted on a cohort of 3316 breast cancer cases from New Castle County, Delaware (from 2012 to 2020), an area of the country with elevated TNBC rates. Cases were stratified into TNBC and "Non-TNBC" diagnosis and geocoded by residential address. Neighborhood exposures included census tract-level measures of unhealthy alcohol use, metabolic dysfunction, breastfeeding, and environmental hazards. An overall cumulative risk score was calculated based on tract-level exposures.

RESULTS

Univariate analyses showed each tract-level exposure was associated with greater TNBC odds. In multivariate analyses that controlled for patient-level race and age, tract-level exposures were not associated with TNBC odds. However, in a second multivariate model that included patient-level variables and considered tract-level risk factors as a cumulative exposure risk score, each one unit increase in cumulative exposure was significantly associated with a 10% increase in TNBC odds. Higher cumulative exposure risk scores were found in census tracts with relatively high proportions of Black residents.

CONCLUSIONS

Cumulative exposure to neighborhood-level risk factors that disproportionately affect Black communities was associated with greater TNBC risk.

Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American cancer epidemiology study (AACES)

PURPOSE

The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC.

METHODS

AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010-2015) are presented.

RESULTS

Thus far, ~ 650 patients with EOC have been enrolled in the AACES. The five-year OS of AACES participants approximates those of Black women in the Surveillance Epidemiology and End Results (SEER) registry who survive at least 10-month past diagnosis and is worse compared to white women in SEER, 49 vs. 60%, respectively. A high proportion of women in AACES have low levels of household income (45% < $25,000 annually), education (51% ≤ high school education), and insurance coverage (32% uninsured or Medicaid). Those followed annually differ from those without follow-up with higher levels of localized disease (28 vs 24%) and higher levels of optimal debulking status (73 vs 67%).

CONCLUSION

AACES is well positioned to evaluate the contribution of social determinants of health to the poor survival of Black women with EOC and advance understanding of the multi-factorial causes of the ovarian cancer survival disparity in Black women.

Association of Social Determinants of Health and Clinical Factors with Postpartum Hospital Readmissions among Nulliparous Individuals

OBJECTIVE

Prior data suggest that there are racial and ethnic disparities in postpartum readmission among individuals, especially among those with hypertensive disorders of pregnancy. Existing reports commonly lack granular information on social determinants of health. The objective of this study was to investigate factors associated with postpartum readmission for individuals and address whether such risk factors differed by whether an individual had an antecedent diagnosis of a hypertensive disorder of pregnancy (HDP).

STUDY DESIGN

This is a secondary analysis of a large, multicenter prospective cohort study of 10,038 nulliparous participants. The primary outcome of this analysis was postpartum readmission. A priori, participants were analyzed separately based on whether they had HDP. Participant characteristics previously associated with a greater risk of perinatal morbidity or readmission (including social determinants of health, preexisting and chronic comorbidities, and intrapartum characteristics) were compared with bivariable analyses and retained in multivariable models if p < 0.05. Social determinants of health evaluated in this analysis included insurance status, self-identified race and ethnicity (as a proxy for structural racism), income, marital status, primary language, and educational attainment.

RESULTS

Of 9,457 participants eligible for inclusion, 1.7% (n = 165) were readmitted following initial hospital discharge. A higher proportion of individuals with HDP were readmitted compared with individuals without HDP (3.4 vs 1.3%, p < 0.001). Among participants without HDP, the only factors associated with postpartum readmission were chorioamnionitis and cesarean delivery. Among participants with HDP, gestational diabetes and postpartum hemorrhage requiring transfusion were associated with postpartum readmission. While the number of postpartum readmissions included in our analysis was relatively small, social determinants of health that we examined were not associated with postpartum readmission for either group.

CONCLUSION

In this diverse cohort of nulliparous pregnant individuals, there was a higher frequency of postpartum readmission among participants with HDP. Preexisting comorbidity and intrapartum complications were associated with postpartum readmission among this population engaged in a longitudinal study.

KEY POINTS

· Non-HDP patients had higher odds of PPR with chorioamnionitis or cesarean.. · HDP patients had higher odds of PPR if they had GDM or PPH.. · Characterizing PPR may identify and highlight modifiable factors..

Are Neighborhood Conditions Associated With Surgical Delays and Meniscus Tears in Children and Adolescents Undergoing ACL Reconstruction?

BACKGROUND

Markers of a patient's social determinants of health, including healthcare insurance and median household income based on ZIP Code, have been associated with the interval between injury and ACL reconstruction (ACLR) as well as the presence of concomitant meniscus tears in children and adolescents. However, the aforementioned surrogate indicators of a patient's social determinants of health may not reflect all socioeconomic and healthcare resources affecting the care of ACL injuries in children and adolescents. The use of multivariate indices such as the Child Opportunity Index (COI) may help to better identify patients at risk for increased risk for delay between ACL injury and surgery, as well as the incidence of meniscus tears at the time of surgery. The COI is a summative measure of 29 indicators that reflect neighborhood opportunities across three domains: education, health and environment, and social and economic factors. COI scores range from 0 to 100 (100 being the highest possible score), as well as five categorical scores (very low, low, moderate, high, and very high) based on quintile rankings.

QUESTIONS/PURPOSES

To investigate the relationship between neighborhood conditions and the treatment of ACL injuries in children and adolescents via the COI, we asked: (1) Is a lower COI score associated with a longer delay between ACL injury and surgery? (2) Does a higher proportion of patients with lower COI scores have meniscus tears at the time of ACLR?

METHODS

In this retrospective, comparative study, we considered data from 565 patients, 18 years or younger, who underwent primary ACLR at an urban, tertiary children's hospital between 2011 and 2021. Of these patients, 5% (31 of 565) did not have a clearly documented date of injury, 2% (11 of 565) underwent revision reconstructions, and 1% (5 of 565) underwent intentionally delayed or staged procedures. Because we specifically sought to compare patients who had low or very low COI scores (lowest two quintiles) with those who had high or very high scores (highest two quintiles), we excluded 18% (103 of 565) of patients with moderate scores. Ultimately, 73% (415 of 565) of patients with COI scores in either the top or bottom two quintiles were included. Patient addresses at the time of surgery were used to determine the COI score. There were no differences between the groups in terms of gender. However, patients with high or very high COI scores had a lower median (IQR) age (15 years [2.6] versus 17 years [1.8]; p < 0.001) and BMI (23 kg/m 2 [6.1] versus 25 kg/m 2 [8.8]; p < 0.001), were more commonly privately insured (62% [117 of 188] versus 22% [51 of 227]; p < 0.001), and had a higher proportion of patients identifying as White (67% [126 of 188] versus 6.2% [14 of 227]; p < 0.001) compared with patients with low or very low COI scores. Medical records were reviewed for demographic, preoperative, and intraoperative data. Univariate analyses focused on the relationship of the COI and interval between injury and surgery, frequency of concomitant meniscus tears, and frequency of irreparable meniscus tears treated with partial meniscectomy. Multivariable regression analyses were used to determine factors that were independently associated with delayed surgery (longer than 60 and 90 days after injury), presence of concomitant meniscal injuries, and performance of meniscectomy. Multivariable models included insurance and race or ethnicity to determine whether COI was independently associative after accounting for these variables.

RESULTS

Patients with a high or very high COI score had surgery earlier than those with a low or very low COI score (median [IQR] 53 days [53] versus 97 days [104]; p < 0.001). After adjusting for insurance and race/ethnicity, we found that patients with a low or very low COI score were more likely than patients with a high or very high COI score to have surgery more than 60 days after injury (OR 2.1 [95% CI 1.1 to 4.0]; p = 0.02) or more than 90 days after injury (OR 1.8 [95% CI 1.1 to 3.4]; p = 0.04). Furthermore, patients with low or very low COI scores were more likely to have concomitant meniscus tears (OR 1.6 [95% CI 1.1 to 2.5]; p = 0.04) compared with patients with high or very high COI scores. After controlling for insurance, race/ethnicity, time to surgery, and other variables, there was no association between COI and meniscectomy (OR 1.6 [95% CI 0.9 to 2.8]; p = 0.12) or presence of a chondral injury (OR 1.7 [95% CI 0.7 to 3.9]; p = 0.20).

CONCLUSION

As the COI score is independently associated with a delay between ACL injury and surgery as well as the incidence of meniscus tears at the time of surgery, this score can be useful in identifying patients and communities at risk for disparate care after ACL injury. The COI score or similar metrics can be incorporated into medical records to identify at-risk patients and dedicate appropriate resources for efficient care. Additionally, neighborhoods with a low COI score may benefit from improvements in the availability of additional and/or improved resources. Future studies should focus on the relationship between the COI score and long-term patient-reported functional outcomes after ACL injury, identification of the specific timepoints in care that lead to delayed surgery for those with lower COI scores, and the impact of community-based interventions in improving health equity in children with ACL injury.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Neighborhood Socioeconomic Status and Women's Mental Health: A Longitudinal Study of Hurricane Katrina Survivors, 2005-2015

There is limited knowledge on the relationship between neighborhood factors and mental health among displaced disaster survivors, particularly among women. Hurricane Katrina (Katrina) was the largest internal displacement in the United States (U.S.), which presented itself as a natural experiment. We examined the association between neighborhood socioeconomic status (SES) and mental health among women up to 10 years following Katrina (N = 394). We also investigated whether this association was modified by move status, comparing women who were permanently displaced to those who had returned to their pre-Katrina residence. We used hierarchical linear models to measure this association, using data from the American Community Survey and the Gulf Coast Child and Family Health study. Neighborhood SES was created as an index which represented social and economic characteristics of participants' neighborhoods. Mental health was measured using mental component summary (MCS) scores. Increased neighborhood SES was positively associated with mental health after controlling for age, race/ethnicity, economic positioning, time, and move status (19.6, 95% Confidence Interval: 5.8, 33.7). Neighborhood SES and mental health was also modified by move status. These findings underscore the need to better understand the impacts of socioeconomic conditions and health outcomes among women affected by natural disasters.

Area Deprivation Index is Associated with Variation in Quality of Life and Psychosocial Well-being Following Breast Cancer Surgery

BACKGROUND

Neighborhood-level factors have been shown to influence surgical outcomes through material deprivation, psychosocial mechanisms, health behaviors, and access to resources. To date, no study has examined the relationship between area-level deprivation (ADI) and post-mastectomy outcomes.

METHODS

A cross-sectional survey of adult female breast cancer patients who underwent lumpectomy or mastectomy between January 2018 to June 2019 was carried out. Patient-specific characteristics and ADI information were abstracted and correlated with postoperative global- (SF-12) and condition-specific (BREAST-Q) quality-of-life performance via multivariable regression. Patients were classified into three ADI terciles: 0-39 (low deprivation), 40-59 (moderate deprivation), and 60-100 (high deprivation).

RESULTS

A total of 564 consecutive patients were identified, being mostly white (75%) with mean age of 60.2 ± 12.4 years, median body mass index of 27.8 [interquartile range (IQR) 24.3-32.2) kg/m², median Charlson Comorbidity Index of 3 (IQR 2-5), and mean ADI of 42.3 ± 25.7. African American and Hispanic patients and those with high BMI were more likely to reside in highly deprived neighborhoods (p = 0.003 and p < 0.001). In adjusted models, patients in highly deprived neighborhoods had significantly lower mean SF-12 physical (44.9 [95% CI, 43.8-46.0] versus 44.9 [95% CI, 43.7-46.1] versus 46.3 [95% CI, 45.3-47.3], p = 0.03) and BREAST-Q psychosocial well-being scores (63.5 [95% CI, 59.32-67.8] versus 69.3 [95% CI, 65.1-73.6] versus 69.7 [95% CI, 66.4-73.1], p = 0.01) relative to moderate- and low-deprivation groups.

CONCLUSIONS

Patients residing in the most deprived neighborhoods were identified to have worse psychological well-being and quality-of-life. The ADI should be incorporated into the shared decision-making process and perioperative counseling to engender value-based and personalized care, especially for vulnerable populations.

Examining neighbourhood-level disparities in Black, Latina/o, Asian, and White physical health, mental health, chronic conditions, and social disadvantage in California

Racial/ethnic minority individuals in the U.S. experience numerous health disparities versus Whites, often due to differences in social determinants. Yet, limited large-scale research has examined these differences at the neighbourhood level. We merged 2021 PLACES Project and 2020 American Community Survey data across 3,211 census tracts (neighbourhoods) defined as majority (>50%) Black, Latina/o, Asian or White. T-tests and hierarchical linear regressions were used to examine differences and associations between neighbourhoods on key health (general health, mental health, obesity, diabetes, cancer, coronary heart disease, chronic obstructive pulmonary disease, stroke), and social outcomes (income, unemployment, age, population density). Results indicated that minority neighbourhoods in California exhibited stark health and social disparities versus White neighbourhoods, displaying worse outcomes on nearly every social and health variable/condition examined; particularly for Black and Latina/o neighbourhoods. Moreover, regression findings revealed that, after considering income, unemployment, and population density, (1) fair/poor mental health and higher percentages of Black, Latina/o and Asian residents in neighbourhoods independently associated with greater neighbourhood fair/poor physical health, and (2) fair/poor mental health significantly associated with greater prevalence of obesity and COPD. This study thus underscores the need to address the profound health and social disparities experienced by minority neighbourhoods for more equitable neighbourhoods.

Aging in Rural Communities

Purpose of Review

Population aging is occurring worldwide, particularly in developed countries such as the United States (US). However, in the US, the population is aging more rapidly in rural areas than in urban areas. Healthy aging in rural areas presents unique challenges. Understanding and addressing those challenges is essential to ensure healthy aging and promote health equity across the lifespan and all geographies. This review aims to present findings and evaluate recent literature (2019-2022) on rural aging and highlight future directions and opportunities to improve population health in rural communities.

Recent Findings

The review first addresses several methodological considerations in measuring rurality, including the choice of measure used, the composition of each measure, and the limitations and drawbacks of each measure. Next, the review considers important concepts and context when describing what it means to be rural, including social, cultural, economic, and environmental conditions. The review assesses several key epidemiologic studies addressing rural-urban differences in population health among older adults. Health and social services in rural areas are then discussed in the context of healthy aging in rural areas. Racial and ethnic minorities, indigenous peoples, and informal caregivers are considered as special populations in the discussion of rural older adults and healthy aging. Lastly, the review provides evidence to support critical longitudinal, place-based research to promote healthy aging across the rural-urban divide is highlighted.

Summary

Policies, programs, and interventions to reduce rural-urban differences in population health and to promote health equity and healthy aging necessitate a context-specific approach. Considering the cultural context and root causes of rural-urban differences in population health and healthy aging is essential to support the real-world effectiveness of such programs, policies, and interventions.

Multilevel factors associated with inequities in multidisciplinary cancer consultation

OBJECTIVE

To assess changes in the prevalence of multidisciplinary cancer consultations (MDCc) over the last decade and examine patient, surgeon, hospital, and neighborhood factors associated with receipt of MDCc among individuals diagnosed with cancer.

DATA SOURCE

Surveillance, Epidemiology and End Results (SEER)-Medicare data from 2006 to 2016.

STUDY DESIGN

We used time-series analysis to assess change in MDCc prevalence from 2007 to 2015. We also conducted multilevel logistic regression with random surgeon- and hospital-level effects to assess associations between patient, surgeon, neighborhood, and health care organization-level factors and receipt of MDCc during the cancer treatment planning phase, defined as the 2 months following cancer diagnosis.

DATA COLLECTION/EXTRACTION METHODS

We identified Medicare beneficiaries >65 years of age with surgically resected breast, colorectal (CRC), or non-small cell lung cancer (NSCLC) stages I-III (n = 103,250).

PRINCIPAL FINDINGS

From 2007 to 2015, the prevalence of MDCc increased from 35.0% to 61.2%. Overall, MDCc was most common among patients with breast cancer compared to CRC and NSCLC. Cancer patients who were Black, had comorbidities, had dual Medicare-Medicaid coverage, were residing in rural areas or in areas with higher Black and Hispanic neighborhood composition were significantly less likely to have received MDCc. Patients receiving surgery at disproportionate payment-sharing or rural-designated hospitals had 2% (95% CI: -3.55, 0.58) and 17.6% (95% CI: -21.45, 13.70), respectively, less probability of receiving MDCc. Surgeon- and hospital-level effects accounted for 15% of the variance in receipt of MDCc.

CONCLUSIONS

The practice of MDCc has increased over the last decade, but significant geographical and health care organizational barriers continue to impede equitable access to and delivery of quality care across cancer patient populations. Multilevel and multicomponent interventions that target care coordination, health system, and policy changes may enhance equitable access to and receipt of MDCc.

Toward informatics-enabled preparedness for natural hazards to minimize health impacts of climate change

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them.

Substance use disorders and social determinants of health from electronic medical records obtained during Kentucky's "triple wave"

Social determinants of health (SDOH) play a critical role in the risk of harmful drug use. Examining SDOH as a means of differentiating populations with multiple co-occurring substance use disorders (SUDs) is particularly salient in the era of prevalent opioid and stimulant use known as the "Third Wave". This study uses electronic medical records (EMRs) from a safety net hospital system from 14,032 patients in Kentucky from 2017 to 2019 in order to 1) define three types of SUD cohorts with shared/unique risk factors, 2) identify patients with unstable housing using novel methods for EMRs and 3) link patients to their residential neighborhood to obtain quantitative perspective on social vulnerability. We identified patients in three cohorts with statistically significant unique risk factors that included race, biological sex, insurance type, smoking status, and urban/rural residential location. Adjusting for these variables, we found a statistically significant, increasing risk gradient for patients experiencing unstable housing by cohort type: opioid-only (n = 7385, reference), stimulant-only (n = 4794, odds ratio (aOR) 1.86 95 % confidence interval (CI): 1.66-2.09), and co-diagnosed (n = 1853, aOR = 2.75, 95 % CI: 2.39 to 3.16). At the neighborhood-level, we used 8 different measures of social vulnerability and found that, for the most part, increasing proportions of patients with stimulant use living in a census tract was associated with more social vulnerability. Our study identifies potentially modifiable factors that can be tailored by substance type and demonstrates robust use of EMRs to meet national goals of enhancing research on social determinants of health.

Improving patient well-being in the United States through care coordination interventions informed by social determinants of health

Health and well-being are promoted when primary care teams partner with patients and provide care coordination to mitigate risks and promote optimal health. Identification of patients for care coordination is typically based on claim-driven risk assessments. Evidence shows that social determinants of health (SDOH) drive risk for adverse health outcomes but are omitted from existing risk tools. Missed opportunities for care coordination contribute to increased healthcare costs, poorer health outcomes and reduced patient well-being. To address the gap of risk-informed care coordination that includes SDOH, the aim of this project was to implement process improvement of a system's care coordination program through refined patient selection and customised engagement in intensive care coordination. A non-randomised care coordination quality improvement project was conducted at a community health centre in 2020. Inclusion criteria (i.e. presence of risk attribution score, SDOH questionnaire completed) resulted in 540 patients being offered care coordination services; Patients having at least one month of care coordination were included in the analysis (N = 216). Analysis included the 216 patients that chose participation and the 324 patients that maintained usual care. Descriptive statistics were generated to distinguish patient demographics, frequency of care coordination contact, and specific SDOH insecurities for both the study and comparison groups. Paired t-tests were incorporated to evaluate statistical significance of the intervention group. Impact on well-being, SDOH barriers, appointment adherence and health outcomes were assessed in both conditions. Intervention condition patients reported improvement in well-being [feeling anxious (t = 4.051; p < 0.000)] and reduced SDOH barriers [food access (t = 4.662; p < 0.000); housing (t = 2.203; p = 0.008)] that were significantly different from the usual care condition in the expected directions. Care coordination based on factors including SDOH risks shows promise in improving patient well-being. Future research should refine this approach for comprehensive risk assessment to intervene and support patient health and well-being.

Relationship Between Neighborhood Socioeconomic Disadvantage and Severe Maternal Morbidity and Maternal Mortality

Background

Rates of severe maternal morbidity and maternal mortality (SMM/MM) in the United States are rising. Disparities in SMM/MM persist by race, ethnicity and geography, and could partially be attributed to social determinants of health.

Purpose

Utilizing data from the largest, statewide referral hospital in Alabama, we investigated the relationship between residence in disadvantaged neighborhoods and SMM/MM.

Methods

Data on all pregnancies between 2010 and 2020 were included; SMM/MM cases were identified using CDC definitions. Area deprivation index (ADI) available at the census-block group was geographically linked to individual records and categorized using quintile cutoffs; higher ADI score indicated higher socioeconomic disadvantage. Generalized estimating equation models were used to adjust for spatial autocorrelation and ORs were computed to evaluate the relationship between ADI and SMM/MM, adjusted for covariates including age, race, insurance, residence in medically underserved areas/population (MUAP), and urban/rural residence.

Results

Overall, 32,909 live-birth deliveries were identified, with a prevalence of 9.8% deliveries with SMM/MM with blood transfusion and 5.3% without blood transfusion, respectively. Increased levels of ADI were associated with increased odds of SMM/MM. Compared to women in the lowest quintile, the adjusted OR for SMM/MM among women in highest quintile was 1.78 (95%CI, 1.22-2.59, P=.0027); increasing age, non-Hispanic Black, government insurance and residence in MUAP were also significantly associated with increased odds of SMM/MM.

Conclusion

Our results suggest that residence within disadvantaged neighborhoods may contribute to SMM/MM even after adjusting for patient-level factors. Measures such as ADI can help identify the most vulnerable populations and provide points to intervene.

From Genes to Geography, from Cells to Community, from Biomolecules to Behaviors: The Importance of Social Determinants of Health

Much scientific work over the past few decades has linked health outcomes and disease risk to genomics, to derive a better understanding of disease mechanisms at the genetic and molecular level. However, genomics alone does not quite capture the full picture of one’s overall health. Modern computational biomedical research is moving in the direction of including social/environmental factors that ultimately affect quality of life and health outcomes at both the population and individual level. The future of studying disease now lies at the hands of the social determinants of health (SDOH) to answer pressing clinical questions and address healthcare disparities across population groups through its integration into electronic health records (EHRs). In this perspective article, we argue that the SDOH are the future of disease risk and health outcomes studies due to their vast coverage of a patient’s overall health. SDOH data availability in EHRs has improved tremendously over the years with EHR toolkits, diagnosis codes, wearable devices, and census tract information to study disease risk. We discuss the availability of SDOH data, challenges in SDOH implementation, its future in real-world evidence studies, and the next steps to report study outcomes in an equitable and actionable way.