The Neighborhood Atlas Area Deprivation Index For Measuring Socioeconomic Status: An Overemphasis On Home Value

Impact of Social Determinants of Health on Predictive Models for Outcomes After Congenital Heart Surgery

BACKGROUND

Despite documented associations between social determinants of health and outcomes post-congenital heart surgery, clinical risk models typically exclude these factors.

OBJECTIVES

The study sought to characterize associations between social determinants and operative and longitudinal mortality as well as assess impacts on risk model performance.

METHODS

Demographic and clinical data were obtained for all congenital heart surgeries (2006-2021) from locally held Congenital Heart Surgery Collaborative for Longitudinal Outcomes and Utilization of Resources Society of Thoracic Surgeons Congenital Heart Surgery Database data. Neighborhood-level American Community Survey and composite sociodemographic measures were linked by zip code. Model prediction, discrimination, and impact on quality assessment were assessed before and after inclusion of social determinants in models based on the 2020 Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model.

RESULTS

Of 14,173 total index operations across New York State, 12,321 cases, representing 10,271 patients at 8 centers, had zip codes for linkage. A total of 327 (2.7%) patients died in the hospital or before 30 days, and 314 children died by December 31, 2021 (total n = 641; 6.2%). Multiple measures of social determinants of health explained as much or more variability in operative and longitudinal mortality than clinical comorbidities or prior cardiac surgery. Inclusion of social determinants minimally improved models' predictive performance (operative: 0.834-0.844; longitudinal 0.808-0.811), but significantly improved model discrimination; 10.0% more survivors and 4.8% more mortalities were appropriately risk classified with inclusion. Wide variation in reclassification was observed by site, resulting in changes in the center performance classification category for 2 of 8 centers.

CONCLUSIONS

Although indiscriminate inclusion of social determinants in clinical risk modeling can conceal inequities, thoughtful consideration can help centers understand their performance across populations and guide efforts to improve health equity.

Neighborhood Deprivation and Treatment Challenges in Pediatric Musculoskeletal Infections: A Socioeconomic Analysis

Introduction Musculoskeletal (MSK) infections are prevalent in the pediatric population, with previous research highlighting the significant impact of socioeconomic status (SES) on treatment outcomes. However, the specific link in pediatric cohorts remains poorly understood. The Area Deprivation Index (ADI), a measure of neighborhood-level disadvantage, serves as a crucial marker for SES. This study aims to investigate how ADI influences disease characteristics, treatment delays, and outcomes in pediatric patients with MSK infections. Methods A single-center retrospective cohort analysis was conducted using patient charts from a large urban pediatric hospital over six years from 2017 to 2022. Patients aged 0-18 years with diagnoses of osteomyelitis, septic arthritis, cellulitis, or pyomyositis were identified using the International Classification of Diseases - 10th Revision (ICD-10) codes. Data collection included demographics, disease characteristics, treatment delay intervals, and complications. Patient zip codes were obtained and entered into the Neighborhood Atlas® mapping website to determine their ADI. Patients were then stratified into four groups based on ADI scores: 1-10, 11-20, 21-40, and 41-100. Statistical analysis included the use of the Mann-Whitney U test for continuous data and the Chi-square/Fisher's exact test for binary and categorical data comparisons among the ADI groups. Results A total of 121 patients were included. Categorization based on ADI revealed 25 (20.7%) patients in the 1-10 ADI percentile group, 36 (29.8%) in the 11-20 group, 38 (31.4%) in the 21-40 group, and 22 (18.2%) in the 41-100 group. There were no significant differences between ADI and patient demographics, disease characteristics, presentation delay interval, treatment received, and complications. Conclusion The study demonstrates that there was no significant difference between ADI groups regarding demographics, disease characteristics, presentation delay interval, treatment received, and complications in pediatric populations. Despite the lack of evidence for differences in MSK infections attributable to ADI, this does not negate the potential existence of such a relationship.

Financial hardship and neighborhood socioeconomic disadvantage in long-term childhood cancer survivors

BACKGROUND

Long-term survivors of childhood cancer face elevated risk for financial hardship. We evaluate whether childhood cancer survivors live in areas of greater deprivation and the association with self-reported financial hardships.

METHODS

We performed a cross-sectional analysis of data from the Childhood Cancer Survivor Study between 1970 and 1999 and self-reported financial information from 2017 to 2019. We measured neighborhood deprivation with the Area Deprivation Index (ADI) based on current zip code. Financial hardship was measured with validated surveys that captured behavioral, material and financial sacrifice, and psychological hardship. Bivariate analyses described neighborhood differences between survivors and siblings. Generalized linear models estimated effect sizes between ADI and financial hardship adjusting for clinical factors and personal socioeconomic status.

RESULTS

Analysis was restricted to 3475 long-term childhood cancer survivors and 923 sibling controls. Median ages at time of evaluation was 39 years (interquartile range [IQR] = 33-46 years and 47 years (IQR = 39-59 years), respectively. Survivors resided in areas with greater deprivation (ADI ≥ 50: 38.7% survivors vs 31.8% siblings; P < .001). One quintile increases in deprivation were associated with small increases in behavioral (second quintile, P = .017) and psychological financial hardship (second quintile, P = .009; third quintile, P = .014). Lower psychological financial hardship was associated with individual factors including greater household income (≥$60 000 income, P < .001) and being single (P = .048).

CONCLUSIONS

Childhood cancer survivors were more likely to live in areas with socioeconomic deprivation. Neighborhood-level disadvantage and personal socioeconomic circumstances should be evaluated when trying to assist childhood cancer survivors with financial hardships.

Neighborhood disadvantage is associated with working memory and hippocampal volumes among older adults

It is not well understood how neighborhood disadvantage is associated with specific domains of cognitive function and underlying brain health within older adults. Thus, the objective was to examine associations between neighborhood disadvantage, brain health, and cognitive performance, and examine whether associations were more pronounced among women. The study included 136 older adults who underwent cognitive testing and MRI. Neighborhood disadvantage was characterized using the Area Deprivation Index (ADI). Descriptive statistics, bivariate correlations, and multiple regressions were run. Multiple regressions, adjusted for age, sex, education, and depression, showed that higher ADI state rankings (greater disadvantage) were associated with poorer working memory performance (p < .01) and lower hippocampal volumes (p < .01), but not total, frontal, and white matter lesion volumes, nor visual and verbal memory performance. There were no significant sex interactions. Findings suggest that greater neighborhood disadvantage may play a role in working memory and underlying brain structure.

Living in high-poverty areas is associated with reduced survival in patients with thoracoabdominal aortic aneurysms

OBJECTIVES

Studies have demonstrated that socioeconomic status, insurance, race, and distance impact clinical outcomes in patients with abdominal aortic aneurysms. The purpose of this study was to assess if these factors also impact clinical outcomes in patients with thoracoabdominal aortic aneurysms (TAAAs).

METHODS

We conducted a retrospective review of patients with TAAAs confirmed by computed tomography imaging between 2009 and 2019 at a single institution. Patients' zip codes were mapped to American Community Survey Data to obtain geographic poverty rates. We used the standard U.S. Census definition of high-poverty concentration as >20% of the population living at 100% of the poverty rate. Our primary outcome was overall survival, stratified by whether the patient underwent repair.

RESULTS

Of 578 patients, 575 had zip code data and were analyzed. In both the nonoperative (N = 268) and operative (N = 307) groups, there were no significant differences in age, race, comorbidities, clinical urgency, surgery utilization, or surgery modality between patients living in high-poverty areas (N = 95, 16.4%) vs not. In the nonoperative group, patients from high-poverty areas were more likely to have aneurysm due to dissection (37.5% vs 17.6%, P = .03). In multivariate analyses, patients from high-poverty zip codes had significantly worse nonoperative survival (hazard ratio [HR]: 1.9, 95% confidence interval [CI]: 1.1-3.3, P = .03). In the repair group, high poverty was also a significant predictor of reduced postoperative survival (HR: 1.65, 95% CI: 1-2.63, P = .04). Adding the Gagne Index, these differences persisted in both groups (nonoperative: HR: 1.93, 95% CI: 1.01-3.70, P = .05; operative: HR: 1.62, 95% CI: 1.03-2.56, P = .04). In Kaplan-Meier analysis, the difference in postoperative survival began approximately 1.5 years after repair. Private insurance was predictive of improved postoperative survival (HR: 0.42, 95% CI: 0.18-0.95, P = .04) but reduced nonoperative survival (HR: 2.05, 95% 1.01-4.14, P = .04). Data were insufficient to determine if race impacted survival discretely from poverty status. These results were found after adjusting for age, race, sex, maximum aortic diameter, coronary artery disease, distance from the hospital, insurance, and active smoking. Interestingly, in multivariate regression, traveling greater than 100 miles was correlated with increased surgery utilization (odds ratio: 1.58, 95% CI: 1.08-2.33, P = .02) and long-term survival (HR: 0.61, 95% CI: 0.41-0.92, P = .02).

CONCLUSIONS

Patients with TAAAs living in high-poverty areas had significantly more dissections and suffered a nearly doubled risk of mortality compared with patients living outside such areas. These data suggest that these disparities are attributed to the overall impacts of poverty and highlight the pressing need for research into TAAA disparities.

Area-Level Socioeconomic Disadvantage and Health Care Spending: A Systematic Review

Importance

Publicly available, US Census-based composite measures of socioeconomic disadvantage are increasingly being used in a wide range of clinical outcomes and health services research. Area Deprivation Index (ADI) and Social Vulnerability Index (SVI) are 2 of the most commonly used measures. There is also early interest in incorporating area-level measures to create more equitable alternative payment models.

Objective

To review the evidence on the association of ADI and SVI with health care spending, including claims-based spending and patient-reported barriers to care due to cost.

Evidence Review

A systematic search for English-language articles and abstracts was performed in the PubMed, Web of Science, Embase, and Cochrane databases (from inception to March 1, 2023). Peer-reviewed articles and abstracts using a cross-sectional, case-control, or cohort study design and based in the US were identified. Data analysis was performed in March 2023.

Findings

This review included 24 articles and abstracts that used a cross-sectional, case-control, or cohort study design. In 20 of 24 studies (83%), ADI and SVI were associated with increased health care spending. No association was observed in the 4 remaining studies, mostly with smaller sample sizes from single centers. In adjusted models, the increase in spending associated with higher ADI or SVI residence was $574 to $1811 for index surgical hospitalizations, $3003 to $24 075 for 30- and 90-day episodes of care, and $3519 for total annual spending for Medicare beneficiaries. In the studies that explored mechanisms, postoperative complications, readmission risk, and poor primary care access emerged as health care system-related drivers of increased spending.

Conclusions and Relevance

The findings of this systematic review suggest that both ADI and SVI can play important roles in efforts to understand drivers of health care spending and in the design of payment and care delivery programs that capture aspects of social risk. At the health care system level, higher health care spending and poor care access associated with ADI or SVI may represent opportunities to codesign interventions with patients from high ADI or SVI areas to improve access to high-value health care and health promotion more broadly.

Evaluating potential disparities in geospatial access to American College of Surgeons/American Association for the Surgery of Trauma-verified emergency general surgery centers

BACKGROUND

The American Association for the Surgery of Trauma and the American College of Surgeons have recently introduced emergency general surgery (EGS) center verification, which could enhance patient outcomes. Distance and resource availability may affect access to these centers, which has been linked to higher mortality. Although many patients can receive adequate care at community centers, those with critical conditions may require specialized treatment at EGS-verified centers. We aimed to evaluate geospatial access to potential EGS-verified centers and identify disparities across different scenarios of EGS verification program uptake in the United States.

METHODS

We used hospital capabilities and verified pilot centers to estimate potential patterns of which centers would become EGS verified under four scenarios (EGS centers, high-volume EGS centers, high-volume EGS plus level 1 trauma centers, and quaternary referral centers). We calculated the spatial accessibility index using an enhanced two-step floating catchment technique to determine geospatial access for each scenario. We also evaluated social determinants of health across geospatial access using the Area Deprivation Index (ADI).

RESULTS

A total of 1,932 hospitals were categorized as EGS centers, 307 as high-volume EGS centers, 401 as high-volume EGS plus level 1trauma centers, and 146 as quaternary centers. Spatial accessibility index decreased as the stringency of EGS verification increased in each scenario (226.6 [111.7-330.7], 51.8 [0-126.1], 71.52 [3.34-164.56], 6.2 [0-62.2]; p < 0.001). Within each scenario, spatial accessibility index also declined as the ADI quartile increased ( p < 0.001). The high-volume EGS plus level 1trauma center scenario had the most significant disparity in access between the first and fourth ADI quartiles (-54.68).

CONCLUSION

Access to EGS-verified centers may vary considerably based on the program's implementation. Disadvantaged communities may be disproportionately affected by limited access. Further work to study regional needs can allow a strategic implementation of the EGS verification program to optimize outcomes while minimizing disparities.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.

A retrospective cohort study of socioeconomic deprivation and post-liver transplant survival in adults

The Area Deprivation Index is a granular measure of neighborhood socioeconomic deprivation. The relationship between neighborhood socioeconomic deprivation and recipient survival following liver transplantation (LT) is unclear. To investigate this, the authors performed a retrospective cohort study of adults who underwent LT at the University of Washington Medical Center from January 1, 2004, to December 31, 2020. The primary exposure was a degree of neighborhood socioeconomic deprivation as determined by the Area Deprivation Index score. The primary outcome was posttransplant recipient mortality. In a multivariable Cox proportional analysis, LT recipients from high-deprivation areas had a higher risk of mortality than those from low-deprivation areas (HR: 1.81; 95% CI: 1.03-3.18, p =0.04). Notably, the difference in mortality between area deprivation groups did not become statistically significant until 6 years after transplantation. In summary, LT recipients experiencing high socioeconomic deprivation tended to have worse posttransplant survival. Further research is needed to elucidate the extent to which neighborhood socioeconomic deprivation contributes to mortality risk and identify effective measures to improve survival in more socioeconomically disadvantaged LT recipients.

Addressing Veteran Health-Related Social Needs: How Joint Commission Standards Accelerated Integration and Expansion of Tools and Services in the Veterans Health Administration

BACKGROUND

The Joint Commission recently named reduction of health care disparities and improvement of health care equity as quality and safety priorities (Leadership [LD] Standard LD.04.03.08 and National Patient Safety Goal [NPSG] Standard NPSG.16.01.01). As the largest integrated health system, the Veterans Health Administration (VHA) sought to leverage these new accreditation standards to further integrate and expand existing tools and initiatives to reduce health care disparities and address health-related social needs (HRSNs).

INITIATIVES AND TOOLS

A combination of existing data tools (for example, Primary Care Equity Dashboard), resource tools (for example, Assessing Circumstances and Offering Resources for Needs tool), and a care delivery approach (for example, Whole Health) are discussed as quality improvement opportunities to further integrate and expand how VHA addresses health care disparities and HRSNs. The authors detail the development timeline, building, limitations, and future plans for these tools and initiatives.

COORDINATION OF INITIATIVES

Responding to new health care equity Joint Commission standards led to new implementation strategies and deeper partnerships across VHA that facilitated expanded dissemination, technical assistance activities, and additional resources for VHA facilities to meet new standards and improve health care equity for veterans. Health care systems may learn from VHA's experiences, which include building actionable data platforms, employing user-centered design for initiative development and iteration, designing wide-reaching dissemination strategies for tools, and recognizing the importance of providing technical assistance for stakeholders.

FUTURE DIRECTIONS

VHA continues to expand implementation of a diverse set of tools and resources to reduce health care disparities and identify and address unmet individual veteran HRSNs more widely and effectively.

A research agenda for understanding how social inequality is linked to brain structure and function

Consistent evidence documents powerful effects of social inequality on health, well-being and academic achievement. Yet research on whether social inequality may also be linked to brain structure and function has, until recently, been rare. Here we describe three methodological approaches that can be used to study this question-single site, single study; multi-site, single study; and spatial meta-analysis. We review empirical work that, using these approaches, has observed associations between neural outcomes and structural measures of social inequality-including structural stigma, community-level prejudice, gender inequality, neighbourhood disadvantage and the generosity of the social safety net for low-income families. We evaluate the relative strengths and limitations of these approaches, discuss ethical considerations and outline directions for future research. In doing so, we advocate for a paradigm shift in cognitive neuroscience that explicitly incorporates upstream structural and contextual factors, which we argue holds promise for uncovering the neural correlates of social inequality.

Deciphering the Neighborhood Atlas Area Deprivation Index: the consequences of not standardizing

The Area Deprivation Index (ADI) is a widely used measure recently selected for several federal payment models that adjusts payments based on where beneficiaries live. A recent debate in Health Affairs focuses on seemingly implausible ADI rankings in major cities and across New York. At the root of the issue is the importance of standardization of measures prior to calculating index scores. Neighborhood Atlas researchers are implicitly arguing that their choice to not standardize is of little consequence. Using the same data and methods as the Neighborhood Atlas, this paper focuses on this choice by calculating and comparing standardized and unstandardized ADI scores. The calculated unstandardized ADI nearly perfectly matches the Neighborhood Atlas ADI (r > 0.9999), whereas the correlation with a standardized version is much lower (r = 0.7245). The main finding is that, without standardization, the ADI is reducible to a weighted average of just 2 measures-income and home values-certainly not the advertised multidimensional measure. Federal programs that have incorporated the ADI risk poorly allocating scarce resources meant to reduce health inequities.

Comparison of two area-level socioeconomic deprivation indices: Implications for public health research, practice, and policy

OBJECTIVES

To compare 2 frequently used area-level socioeconomic deprivation indices: the Area Deprivation Index (ADI) and the Social Vulnerability Index (SVI).

METHODS

Index agreement was assessed via pairwise correlations, decile score distribution and mean comparisons, and mapping. The 2019 ADI and 2018 SVI indices at the U.S. census tract-level were analyzed.

RESULTS

Index correlation was modest (R = 0.51). Less than half (44.4%) of all tracts had good index agreement (0-1 decile difference). Among the 6.3% of tracts with poor index agreement (≥6 decile difference), nearly 1 in 5 were classified by high SVI and low ADI scores. Index items driving poor agreement, such as high rents, mortgages, and home values in urban areas with characteristics indicative of socioeconomic deprivation, were also identified.

CONCLUSIONS

Differences in index dimensions and agreement indicated that ADI and SVI are not interchangeable measures of socioeconomic deprivation at the tract level. Careful consideration is necessary when selecting an area-level socioeconomic deprivation measure that appropriately defines deprivation relative to the context in which it will be used. How deprivation is operationalized affects interpretation by researchers as well as public health practitioners and policymakers making decisions about resource allocation and working to address health equity.

Measuring The Enduring Imprint Of Structural Racism On American Neighborhoods

A long history of discriminatory policies in the United States has created disparities in neighborhood resources that shape ethnoracial health inequities today. To quantify these differences, we organized publicly available data on forty-two variables at the census tract level within nine domains affected by structural racism: built environment, criminal justice, education, employment, housing, income and poverty, social cohesion, transportation, and wealth. Using data from multiple sources at several levels of geography, we developed scores in each domain, as well as a summary score that we call the Structural Racism Effect Index. We examined correlations with life expectancy and other measures of health for this index and other commonly used area-based indices. The Structural Racism Effect Index was more strongly associated with each health outcome than were the other indices. Its domain and summary scores can be used to describe differences in social risk factors, and they provide powerful new tools to guide policies and investments to advance health equity.

Neighborhood Characteristics and Elevated Blood Pressure in Older Adults

Importance

The local environment remains an understudied contributor to elevated blood pressure among older adults. Untargeted approaches can identify neighborhood conditions interrelated with racial segregation that drive hypertension disparities.

Objective

To evaluate independent associations of sociodemographic, economic, and housing neighborhood factors with elevated blood pressure.

Design, Setting, and Participants

In this cohort study, the sample included Health and Retirement Study participants who had between 1 and 3 sets of biennial sphygmomanometer readings from 2006 to 2014 or 2008 to 2016. Statistical analyses were conducted from February 5 to November 30, 2021.

Exposures

Fifty-one standardized American Community Survey census tract variables (2005-2009).

Main Outcomes and Measures

Elevated sphygmomanometer readings over the study period (6-year period prevalence): a value of at least 140 mm Hg for systolic blood pressure and/or at least 90 mm Hg for diastolic blood pressure. Participants were divided 50:50 into training and test data sets. Generalized estimating equations were used to summarize multivariable associations between each neighborhood variable and the period prevalence of elevated blood pressure, adjusting for individual-level covariates. Any neighborhood factor associated (Simes-adjusted for multiple comparisons P ≤ .05) with elevated blood pressure in the training data set was rerun in the test data set to gauge model performance. Lastly, in the full cohort, race- and ethnicity-stratified associations were evaluated for each identified neighborhood factor on the likelihood of elevated blood pressure.

Results

Of 12 946 participants, 4565 (35%) had elevated sphygmomanometer readings (median [IQR] age, 68 [63-73] years; 2283 [50%] male; 228 [5%] Hispanic or Latino, 502 [11%] non-Hispanic Black, and 3761 [82%] non-Hispanic White). Between 2006 and 2016, a lower likelihood of elevated blood pressure was observed (relative risk for highest vs lowest tertile, 0.91; 95% CI, 0.86-0.96) among participants residing in a neighborhood with recent (post-1999) in-migration of homeowners. This association was precise among participants with non-Hispanic White and other race and ethnicity (relative risk, 0.91; 95% CI, 0.85-0.97) but not non-Hispanic Black participants (relative risk, 0.97; 95% CI, 0.85-1.11; P = .48 for interaction) or Hispanic or Latino participants (relative risk, 0.84; 95% CI, 0.65-1.09; P = .78 for interaction).

Conclusions and Relevance

In this cohort study of older adults, recent relocation of homeowners to a neighborhood was robustly associated with reduced likelihood of elevated blood pressure among White participants but not their racially and ethnically marginalized counterparts. Our findings indicate that gentrification may influence later-life blood pressure control.

Representativeness of Patients Enrolled in the Lung Cancer Master Protocol (Lung-MAP)

PURPOSE

Lung Cancer Master Protocol (Lung-MAP), a public-private partnership, established infrastructure for conducting a biomarker-driven master protocol in molecularly targeted therapies. We compared characteristics of patients enrolled in Lung-MAP with those of patients in advanced non-small-cell lung cancer (NSCLC) trials to examine if master protocols improve trial access.

METHODS

We examined patients enrolled in Lung-MAP (2014-2020) according to sociodemographic characteristics. Proportions for characteristics were compared with those for a set of advanced NSCLC trials (2001-2020) and the US advanced NSCLC population using SEER registry data (2014-2018). Characteristics of patients enrolled in Lung-MAP treatment substudies were examined in subgroup analysis. Two-sided tests of proportions at an alpha of .01 were used for all comparisons.

RESULTS

A total of 3,556 patients enrolled in Lung-MAP were compared with 2,215 patients enrolled in other NSCLC studies. Patients enrolled in Lung-MAP were more likely to be 65 years and older (57.2% v 46.3%; P < .0001), from rural areas (17.3% v 14.4%; P = .004), and from socioeconomically deprived neighborhoods (42.2% v 36.7%, P < .0001), but less likely to be female (38.6% v 47.2%; P < .0001), Asian (2.8% v 5.1%; P < .0001), or Hispanic (2.4% v 3.8%; P = .003). Among patients younger than 65 years, Lung-MAP enrolled more patients using Medicaid/no insurance (27.6% v 17.8%; P < .0001). Compared with the US advanced NSCLC population, Lung-MAP under represented patients 65 years and older (57.2% v 69.8%; P < .0001), females (38.6% v 46.0%; P < .0001), and racial or ethnic minorities (14.8% v 21.5%; P < .0001).

CONCLUSION

Master protocols may improve access to trials using novel therapeutics for older patients and socioeconomically vulnerable patients compared with conventional trials, but specific patient exclusion criteria influenced demographic composition. Further research examining participation barriers for under represented racial or ethnic minorities in precision medicine clinical trials is warranted.