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Introduction: Community-acquired pneumonia (CAP) is a major health concern in the United States (US), with its incidence, severity, and outcomes influenced by social determinants of health, including socioeconomic status. The impact of neighborhood socioeconomic status, as measured by the Distressed Communities Index (DCI), on CAP-related admissions remains understudied in the literature. Objective: To determine the independent association between DCI and CAP-related admissions in Maryland. Methods: We conducted a retrospective study using the Maryland State Inpatient Database (SID) to collate data on CAP-related admissions from January 2018 to December 2020. The study included adults aged 18-85 years. We explored the independent association between community-level economic deprivation based on DCI quintiles and CAP-related admissions, adjusting for significant covariates. Results: In the study period, 61,467 cases of CAP-related admissions were identified. The patients were predominantly White (49.7%) and female (52.4%), with 48.6% being over 65 years old. A substantive association was found between the DCI and CAP-related admissions. Compared to prosperous neighborhoods, patients living in economically deprived communities had 43% increased odds of CAP-related admissions. Conclusion: Residents of the poorest neighborhoods in Maryland have the highest risk of CAP-related admissions, emphasizing the need to develop effective public health strategies beneficial to the at-risk patient population.

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Background: Asthma represents a substantial public health challenge in the United States, affecting over 25 million adults. This study investigates the impact of neighborhood economic deprivation on asthma-associated Emergency Department (ED) visits in Maryland, using the Distressed Communities Index (DCI) for analysis. Methods: A retrospective analysis of Maryland's Emergency Department Databases from January 2018 to December 2020 was conducted, focusing on asthma-associated ED visits. Results: The study involved 185,317 ED visits, majority of which were females (56.3%) and non-Hispanic whites (65.2%). A significant association was found between increased neighborhood socioeconomic deprivation and asthma-related ED visits. The poorest neighborhoods showed the highest rates of such visits. Compared to prosperous areas, neighborhoods classified from Comfortable to Distressed had progressively higher odds for asthma-related ED visits (Comfortable: OR = 1.14, Distressed OR = 1.65). Other significant asthma predictors included obesity, female gender, tobacco smoking, and older age. Conclusion: There is a substantive association between higher asthma-related ED visits and high neighborhood economic deprivation, underscoring the impact of socioeconomic factors on health outcomes. Public health implications: Addressing healthcare disparities and improving access to care in economically distressed neighborhoods is crucial. Targeted interventions, such as community health clinics and asthma education programs, can help mitigate the impact of neighborhood disadvantage.

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BACKGROUND: Ideally, health services and interventions to improve dental health should be tailored to local target populations. But this is not the standard. Little is known about risk clusters in dental health care and their evaluation based on small-scale, spatial data, particularly among under-represented groups in health surveys. Our study aims to investigate the incidence rates of major oral diseases among privately insured and self-paying individuals in Germany, explore the spatial clustering of these diseases, and evaluate the influence of social determinants on oral disease risk clusters using advanced data analysis techniques, i.e. machine learning. METHODS: A retrospective cohort study was performed to calculate the age- and sex-standardized incidence rate of oral diseases in a study population of privately insured and self-pay patients in Germany who received dental treatment between 2016 and 2021. This was based on anonymized claims data from BFS health finance, Bertelsmann, Dortmund, Germany. The disease history of individuals was recorded and aggregated at the ZIP code 5 level (n = 8871). RESULTS: Statistically significant, spatially compact clusters and relative risks (RR) of incidence rates were identified. By linking disease and socioeconomic databases on the ZIP-5 level, local risk models for each disease were estimated based on spatial-neighborhood variables using different machine learning models. We found that dental diseases were spatially clustered among privately insured and self-payer patients in Germany. Incidence rates within clusters were significantly elevated compared to incidence rates outside clusters. The relative risks (RR) for a new dental disease in primary risk clusters were min = 1.3 (irreversible pulpitis; 95%-CI = 1.3-1.3) and max = 2.7 (periodontitis; 95%-CI = 2.6-2.8), depending on the disease. Despite some similarity in the importance of variables from machine learning models across different clusters, each cluster is unique and must be treated as such when addressing oral public health threats. CONCLUSIONS: Our study analyzed the incidence of major oral diseases in Germany and employed spatial methods to identify and characterize high-risk clusters for targeted interventions. We found that private claims data, combined with a network-based, data-driven approach, can effectively pinpoint areas and factors relevant to oral healthcare, including socioeconomic determinants like income and occupational status. The methodology presented here enables the identification of disease clusters of greatest demand, which would allow implementing more targeted approaches and improve access to quality care where they can have the most impact.

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BACKGROUND: Streptococcus pneumoniae (Spn) infection remains common worldwide despite recent vaccine efforts. Invasive pneumococcal disease (IPD) is the most severe form of Spn infection. Known individual risk factors for IPD include male gender and African American race. However, area-level socioeconomic factors have not been assessed. We examined the association of neighborhood-level disadvantages and risk of IPD in a tertiary medical center located in a socioeconomic diverse urban area in the Southeastern United States. METHODS: Patients hospitalized with culture-confirmed Streptococcus pneumoniae (Spn) infection from 01/01/2010 - 12/31/2019 were identified from electronic health record (EHR). The cohort's demographic and clinical information were obtained from EHR. Patients' residential address was geocoded and matched to 2015 area deprivation index (ADI). The association of ADI and IPD was evaluated using logistic regression after controlling for the demographic information (age, sex, race) and clinical factors (BMI, smoking status, alcoholism, immunosuppressive status, vaccination status, comorbidities). RESULTS: A total of 268 patients were hospitalized with culture-positive Streptococcus pneumoniae infection and 92 (34.3%) of them had IPD. The analysis showed that higher neighborhood deprivation (ADI in 79-100) was associated with increased risk of developing IPD in younger patients with age less than 65 (p = 0.007) after controlling for the individual demographic information and clinical factors. CONCLUSIONS: ADI is a risk factor for IPD in younger adults. Community-level socioeconomic risk factors should be considered when developing prevention strategies such as increasing vaccine uptake in high risk population to reduce the disease burden of IPD.

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BACKGROUND: Studies have suggested possible multiple sclerosis (MS) prodrome with non-routine healthcare utilization as an indicator. The objective of this project was to compare utilization in the four years (years -1, -2, -3, -4) before clinically definite diagnosis and examine demographic associations. METHODS: i2B2 database search at the Medical College of Wisconsin Comprehensive MS center yielded 613 patients between 07/01/2018 and 07/01/2022. Patients with established MS diagnosis, MS mimicker diagnoses, and pediatric-onset MS were excluded; 108 met the criteria for adult patients ≥ 18 years of age newly diagnosed with clinically definite MS after manual chart review. Utilization score for each of the four years before diagnosis was calculated; demographic variables were also collected. Adjusted repeated measures mixed model and Pearson correlation analysis were performed; P value was set at <0.05 for statistical significance. RESULTS: Utilization was greatest for year -1 compared to years -2, -3, and -4 after demographics adjustment (p < 0.001). Utilization was greater (p < 0.05) for older age and unmarried, patients. CONCLUSIONS: Utilization increased a year before formal MS diagnosis, suggestive of prodromal presentation.

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PURPOSE: To assess the rate of visual impairment (VI) from uncorrected refractive error (URE) and associations with demographic and socioeconomic factors among low-income patients presenting to the Michigan Screening and Intervention for Glaucoma and Eye Health through Telemedicine (MI-SIGHT) program. DESIGN: Cross-sectional study. PARTICIPANTS: Adults ≥ 18 years without acute ocular symptoms. METHODS: MI-SIGHT program participants received a telemedicine-based eye disease screening and ordered glasses through an online optical store. Participants were categorized based on refractive error (RE) status: VI from URE (presenting visual acuity [PVA], ≤ 20/50; best-corrected visual acuity [BCVA], ≥ 20/40), URE without VI (PVA, ≥ 20/40; ≥ 2-line improvement to BCVA), and no or adequately corrected RE (PVA, ≥ 20/40; < 2-line improvement to BCVA). Patient demographics, self-reported visual function, and satisfaction with glasses obtained through the program were compared among groups using analysis of variance, Kruskal-Wallis, chi-square, and Fisher exact testing. MAIN OUTCOME MEASURES: PVA, BCVA, and presence of VI (defined as PVA ≤ 20/50). RESULTS: Of 1171 participants enrolled in the MI-SIGHT program during the first year, average age was 55.1 years (SD = 14.5), 37.7% were male, 54.1% identified as Black, and 1166 (99.6%) had both PVA and BCVA measured. VI was observed in 120 participants (10.3%); 96 had VI from URE (8.2%), 168 participants (14.4%) had URE without VI, and 878 (75.3%) had no or adequately corrected RE. A smaller percentage of participants with VI resulting from URE reported having a college degree, and a larger percentage reported income < $10 000 compared with participants with no or adequately corrected RE (3.2% vs. 14.2% [P = 0.02]; 45.5% vs. 21.6% [P < 0.0001], respectively). Visual function was lowest among participants with VI from URE, followed by those with URE without VI, and then those with no or adequately corrected RE (9-item National Eye Institute Visual Function Questionnaire composite score, 67.3 ± 19.6 vs. 77.0 ± 14.4 vs. 82.2 ± 13.3, respectively; P < 0.0001). In total, 71.2% (n = 830) ordered glasses for an average cost of $36.80 ± $32.60; 97.7% were satisfied with their glasses. CONCLUSIONS: URE was the main cause of VI at 2 clinics serving low-income communities and was associated with reduced vision-related quality of life. An online optical store with lower prices made eyeglasses accessible to low-income patients. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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BACKGROUND: Long COVID symptoms - which include brain fog, depression, and fatigue - are mild at best and debilitating at worst. Some U.S. health surveys have found that women, lower income individuals, and those with less education are overrepresented among adults with long COVID, but these studies do not address intersectionality. To fill this gap, we conduct an intersectional analysis of the prevalence and outcomes of long COVID in the U.S. We posit that disparities in long COVID have less to do with the virus itself and more to do with social determinants of health, especially those associated with occupational segregation and the gendered division of household work. METHODS: We use 10 rounds of Household Pulse Survey (HPS) data collected between June 2022 and March 2023 to perform an intersectional analysis using a battery of descriptive statistics that evaluate (1) the prevalence of long COVID and (2) the interference of long COVID symptoms with day-to-day activities. We also use the HPS data to estimate a set of multivariate logistic regressions that relate the odds of having long COVID and activity limitations due to long COVID to a set of individual characteristics as well as intersections by sex, race/ethnicity, education, and sexual orientation and gender identity. RESULTS: Findings indicate that women, some people of color, sexual and gender minorities, and people without college degrees are more likely to have long COVID and to have activity limitations from long COVID. Women have considerably higher odds of developing long COVID compared to men, a disparity exacerbated by having less education. Intersectional analysis by gender, race, ethnicity, and education reveals a striking step-like pattern: college-educated men have the lowest prevalence of long COVID while women without college educations have the highest prevalence. Daily activity limitations are more evenly distributed across demographics, but a different step-like pattern is present: fewer women with degrees have activity limitations while limitations are more widespread among men without degrees. Regression results confirm the negative association of long COVID with being a woman, less educated, Hispanic, and a sexual and gender minority, while results for the intersectional effects are more nuanced. CONCLUSIONS: Results point to systematic disparities in health, highlighting the urgent need for policies that increase access to quality healthcare, strengthen the social safety net, and reduce economic precarity.

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Measuring health inequalities is essential to inform policy making and for monitoring implementation to reduce avoidable and unfair differences in health status. We conducted a geospatial analysis of child mortality in Iran using death records from the Ministry of Health and Medical Education from 2016 to 2018 stratified by sex, age, province, and district, and household expenditure and income survey data from the Statistical Center of Iran collected in 2017. We applied multilevel mixed-effect models and detected significant inequality in child mortality and the impact of socioeconomic factors, especially household income. We advocate for using mortality rate for young children (< 5 years old) as an indicator for assessing the impact of interventions to reduce inequalities among various socioeconomic groups. We also recommend to design and implement comprehensive and longitudinal data collection systems for accurate, regular, and specific monitoring of health inequalities.

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The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical use. Drawing on the traditional principles of medical and research ethics, and highlighting the need to ensure health justice, the AI task force of the Society of Nuclear Medicine and Molecular Imaging has identified 4 major ethical risks: privacy of data subjects, data quality and model efficacy, fairness toward marginalized populations, and transparency of clinical performance. We provide preliminary recommendations to developers of AI-driven medical devices for mitigating the impact of these risks on patients and populations.

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INTRODUCTION: Enhanced recovery after surgery (ERAS) colorectal programs have been shown to improve the length of stay (LOS) without increasing hospital resource utilization at academic centers worldwide. A multidisciplinary ERAS protocol that includes preoperative, intraoperative, and postoperative management guidelines was recently implemented at our urban, racially diverse, and academically affiliated community hospital. A delivery option was provided to reduce barriers to care. Given our unique patient population, the objective of our study was to determine if improvements in outcomes were reproducible in our hospital. METHODS: This is a retrospective study of patients undergoing elective colectomy at New York-Presbyterian Queens Hospital between January 1, 2015, and December 31, 2020. Patient outcomes were compared between surgeries performed under standard practice (all colectomies prior to April 2017) and those performed after the implementation of the ERAS protocol. Demographic and perioperative data were abstracted from a prospectively derived database used to submit data to the National Surgical Quality Improvement Program. Additional data were obtained from chart review. RESULTS: Six hundred five elective colectomies were performed by 12 surgeons (range 1-228 cases) during the study period. Of these, 22 were performed open (41% followed ERAS), 467 were performed laparoscopically (57% followed ERAS), and 116 were performed robotically (74% followed ERAS). The average patient age was 64 y. Of which, 55% were male; 34% were Asian, 27% were non-Hispanic Caucasian, 27% were Hispanic, and 11% were Black or African American (all P-values > 0.05 for ERAS versus non-ERAS). Average duration of procedure was longer in the ERAS group (262 min versus 243 min, P = 0.04), although when stratified by procedure type, this relationship held true only for laparoscopic procedures. Hospital LOS was significantly shorter in the ERAS group (4.3 versus 5.4 d, P < 0.001) and this relationship held true for procedures performed both laparoscopically (4.2 versus 5.3 d, P = 0.01) and robotically (4.1 versus 5.1 d, P = 0.04). Of the ERAS group, patients who opted for delivery of ERAS components (n = 205) had the shortest LOS when compared to patients who picked up components (n = 91) or opted out of ERAS (n = 309) (4.1 versus 4.4 versus 5.2 d, P = 0.003). No significant differences were found for 30-d mortality, 30-d readmission, wound infection, or other postoperative complications (all P-values > 0.05). CONCLUSIONS: Implementation of an ERAS protocol in an urban, diverse, academically affiliated community hospital is associated with reductions in LOS for colectomies performed both laparoscopically and robotically. Facilitating ERAS compliance with a delivery option was also associated with improvements in hospital LOS. Preoperative nutrition supplementation was not associated with outcomes. No differences in mortality, readmission rates, or rates of postoperative complications were found.

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The COVID-19 pandemic has created a severe upheaval in the U.S., with a particular burden on the state of Mississippi, which already has an exhausted healthcare burden. The main objectives of this study are: (1) to analyze the county-level COVID-19 cases, deaths, and vaccine distribution and (2) to determine the correlation between various social determinants of health (SDOH) and COVID-19 vaccination coverage. We analyzed COVID-19-associated data and county-level SDOH factors in 82 counties of Mississippi. The cumulative COVID-19 and socio-demographic data variables were grouped into feature and target variables. The statistical and exploratory data analysis (EDA) was conducted using Python 3.8.5. The correlation between the target and feature variables was performed by Pearson Correlation analysis. The heat Map Correlation Matrix was visually presented to illustrate the correlation between each pair of features and each target variable. Results indicated that people of Asian descent had the highest vaccination coverage of 77% fully vaccinated compared to 52%, 46%, 42% and 25% for African Americans, Whites, Hispanics, and American Indians/Alaska Natives, respectively. The county-level vaccination rate was significantly higher among the minority populations than the White population. It was observed that COVID-19 cases and deaths were positively correlated with per capita income and negatively correlated with the percentage of persons without a high school diploma (age 25+). This study strongly demonstrates that different SDOH factors influence the outcome of the COVID-19 vaccination rate, which also affects the total number of COVID-19 cases and deaths. Vaccine promotion should be given to all populations regardless of race and ethnicity to achieve uniform acceptance. Therefore, statewide policy recommendations focusing on specific community needs should help achieve health equity in COVID-19 vaccination management.

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OBJECTIVE: Pediatric postoperative neurosurgical care is an essential component of a child's treatment pathway. It is important to better understand how neurosurgeons in lower middle-income countries (LMICs) have been able to address socioeconomic and systemic factors to improve their patients' access to quality pediatric postoperative neurosurgical care. We aim to characterize the pediatric neurosurgical postoperative system in place in Zambia and to discuss how these efforts have been implemented to improve outcomes and address socioeconomic barriers to accessing health care. METHODS: We acquired a patient list of 90 tenants of House of Hope (HOH)-an out-of-hospital center caring for children awaiting surgery, as well as those recovering from surgery. Of the patient list, 44 patients qualified for our study. Survey responses and occurrence of demographic and clinical characteristics were calculated. Non-normally distributed variables (age) were reported by median and interquartile range (IQR). Dichotomous variables were presented as percentages. Fisher's Exact test was applied to compare categorical data and hospital re-admission. A P-value of <0.05 was considered significant. RESULTS: Our study demonstrates two key findings: (1) low 30-day hospital re-admission rate of 9% and (2) favorable postoperative experience by patient families. Of the 44 patients, a majority were 1-year-old children (n = 31, 70%) and female (n = 24, 55%) (IQR 1-2 years). Presenting conditions included: hydrocephalus only (n = 35, 80%), hydrocephalus and myelomeningocele (n = 5, 11%), myelomeningocele only (n = 2, 5%), cerebral palsy (n = 1, 2%), and encephalocele (n = 1, 2%). Half (n = 22, 50%) of the patients lived in east Zambia, 8 (18%) lived in central, 8 (18%) in north, 5 (11%) in south, and 1 (2%) in west Zambia. CONCLUSIONS: We report the first qualitative and quantitative analysis of postoperative care for LMIC pediatric neurosurgical patients in the academic literature. Quality, patient-centered postoperative pediatric neurosurgical care that is rooted in addressing socioeconomic determinants of health produces good outcomes in LMICs.

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INTRODUCTION: Thoracic endovascular aortic repair (TEVAR) became the standard of care for treating Type B aortic dissections and descending thoracic aortic aneurysms. We aimed to describe the racial/ethnic differences in TEVAR utilization and outcomes. METHODS: The National Inpatient Sample was reviewed for all TEVARs performed between 2010 and 2017 for Type B aortic dissection and descending thoracic aortic aneurysm (DTAA). We compared groups stratifying by their racial/ethnicity background in White, Black, Hispanic, and others. Mixed-effects logistic regression was performed to assess the relationship between race/ethnicity and the primary outcome, in-hospital mortality. RESULTS: A total of 25,260 admissions for TEVAR during 2010-2017 were identified. Of those, 52.74% (n = 13,322) were performed for aneurysm and 47.2% (n = 11,938) were performed for Type B dissection. 68.1% were White, 19.6% were Black, 5.7% Hispanic, and 6.5% were classified as others. White patients were the oldest (median age 71 years; p < .001), with TEVAR being performed electively more often for aortic aneurysm (58.8% vs. 34% vs. 48.3% vs. 48.2%; p < .001). In contrast, TEVAR was more likely urgent or emergent for Type B dissection in Black patients (65.6% vs. 41.1% vs. 51.6% vs. 51.7%; p < .001). Finally, the Black population showed a relative increase in the incidence rate of TEVAR over time. The adjusted multivariable model showed that race/ethnicity was not associated with in-hospital mortality. CONCLUSION: Although there is a differential distribution of thoracic indication and comorbidities between race/ethnicity in TEVAR, racial disparities do not appear to be associated with in-hospital mortality after adjusting for covariates.

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INTRODUCTION: Uninsured pediatric trauma patients are at increased risk of poor outcomes. The impact of the Patient Protection and Affordable Care Act (ACA) on pediatric trauma patients has not been studied. We hypothesized that the expansion of Medicaid coverage under the ACA was associated with increased insurance coverage and improved outcomes. METHODS: Retrospective review of patients <18 y old presenting to a level 1 pediatric trauma center 2009-2019. An interrupted time series analysis was performed to assess the impact of Medicaid expansion under the ACA in January 2014. The primary outcome was rate of insurance coverage. Secondary outcomes included in-hospital mortality, disposition, 30-day readmission, length of stay (LOS), and intensive care unit (ICU) LOS. RESULTS: A total of 5645 patients were evaluated, (pre-ACA n = 2,243, post-ACA n = 3402). Expansion of Medicaid was associated with minimal changes on insurance coverage. There a decrease in mortality (RR = 0.96, P = 0.0355) and a slight increase in disposition to a rehabilitation facility (RR = 1.02, P = 0.0341). There was no association with 30-day readmission (RR = 1.02, P = 0.3498). Similarly, expansion of Medicaid was not associated with change in LOS (estimate = -0.00, P = 0.8893). There was a slight decrease in ICU LOS (estimate = -0.03, P < 0.0001). CONCLUSIONS: Medicaid expansion was associated with marginal changes in insurance coverage among pediatric trauma patients. We did not identify significant impacts on patient outcomes.

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Individuals with substance use disorders (SUDs) are at increased risk for COVID-19 infection and for adverse outcomes of the infection. Though vaccines are highly effective against COVID-19, their effectiveness in individuals with SUDs might be curtailed by compromised immune status and a greater likelihood of exposures, added to the waning vaccine immunity and the new SARS-CoV-2 variants. In a population-based cohort study, we assessed the risk, time trends, outcomes and disparities of COVID-19 breakthrough infection in fully vaccinated SUD patients starting 14 days after completion of vaccination. The study included 579,372 individuals (30,183 with a diagnosis of SUD and 549,189 without such a diagnosis) who were fully vaccinated between December 2020 and August 2021, and had not contracted COVID-19 infection prior to vaccination. We used the TriNetX Analytics network platform to access de-identified electronic health records from 63 health care organizations in the US. Among SUD patients, the risk for breakthrough infection ranged from 6.8% for tobacco use disorder to 7.8% for cannabis use disorder, all significantly higher than the 3.6% in non-SUD population (p<0.001). Breakthrough infection risk remained significantly higher after controlling for demographics (age, gender, ethnicity) and vaccine types for all SUD subtypes, except for tobacco use disorder, and was highest for cocaine and cannabis use disorders (hazard ratio, HR=2.06, 95% CI: 1.30-3.25 for cocaine; HR=1.92, 95% CI: 1.39-2.66 for cannabis). When we matched SUD and non-SUD individuals for lifetime comorbidities and adverse socioeconomic determinants of health, the risk for breakthrough infection no longer differed between these populations, except for patients with cannabis use disorder, who remained at increased risk (HR=1.55, 95% CI: 1.22-1.99). The risk for breakthrough infection was higher in SUD patients who received the Pfizer than the Moderna vaccine (HR=1.49, 95% CI: 1.31-1.69). In the vaccinated SUD population, the risk for hospitalization was 22.5% for the breakthrough cohort and 1.6% for the non-breakthrough cohort (risk ratio, RR=14.4, 95% CI: 10.19-20.42), while the risk for death was 1.7% and 0.5% respectively (RR=3.5, 95% CI: 1.74-7.05). No significant age, gender and ethnic disparities for breakthrough infection were observed in vaccinated SUD patients. These data suggest that fully vaccinated SUD individuals are at higher risk for breakthrough COVID-19 infection, and this is largely due to their higher prevalence of comorbidities and adverse socioeconomic determinants of health compared with non-SUD individuals. The high frequency of comorbidities in SUD patients is also likely to contribute to their high rates of hospitalization and death following breakthrough infection.

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Purpose: This work evaluates demographic and socioeconomic predictors of delayed care for rhegmatogenous retinal detachments (RRDs) during the spring 2020 COVID-19 shutdown in a US hot spot. Methods: This multicenter, retrospective, case-control study took place in 3 academic vitreoretinal practices in metropolitan Boston. Consecutive patients treated for RRD during the COVID-19 state of emergency were compared with patients treated during the same period in 2018 and 2019. The primary outcome was macula status for RRD. Secondary outcomes included visual acuity, symptom duration, proportion with proliferative vitreoretinopathy, time to procedure, method of repair, and patient demographics. Results: The total number of acute RRD decreased by 13.7% from 2018 to 2020 and 17.2% from 2019 to 2020. Symptom duration was significantly longer in 2020 than 2018 and 2019 (median, 7 vs 4 days) with a higher proportion of macula-off detachments (80 of 125 [64%] in 2020 vs 75 of 145 [51.7%] in 2018 and 78 of 151 [51.6%] in 2019). The 2020 cohort included significantly fewer patients in the racial and/or ethnic minority group than in 2019 (P = .02), and use of low-income, government-sponsored health insurance was a predictor of macula-off status during the pandemic (P = .04). Conclusions: RRDs during the spring 2020 COVID-19 lockdown were more likely to be macula-off at presentation. Because sociodemographic factors including race, ethnicity, and income level were associated with deferral of care, ophthalmologists should consider measures targeting vulnerable populations to avoid preventable vision loss as the pandemic continues or in future health care emergencies.

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BACKGROUND: Socioeconomic status (SES) is an important determinant of health, and SES data is an important confounder to control for in epidemiology and health services research. Individual level SES measures are cumbersome to collect and susceptible to biases, while area level SES measures may have insufficient granularity. The 'Singapore Housing Index' (SHI) is a validated, building level SES measure that bridges individual and area level measures. However, determination of the SHI has previously required periodic data purchase and manual parsing. In this study, we describe a means of SHI determination for public housing buildings with open government data, and validate this against the previous SHI determination method. METHODS: Government open data sources (e.g. DATA: gov.sg, Singapore Land Authority OneMAP API, Urban Redevelopment Authority API) were queried using custom Python scripts. Data on residential public housing block address and composition from the HDB Property Information dataset (data.gov.sg) was matched to postal code and geographical coordinates via OneMAP API calls. The SHI was calculated from open data, and compared to the original SHI dataset that was curated from non-open data sources in 2018. RESULTS: Ten thousand seventy-seven unique residential buildings were identified from open data. OneMAP API calls generated valid geographical coordinates for all (100%) buildings, and valid postal code for 10,012 (99.36%) buildings. There was an overlap of 10,011 buildings between the open dataset and the original SHI dataset. Intraclass correlation coefficient was 0.999 for the two sources of SHI, indicating almost perfect agreement. A Bland-Altman plot analysis identified a small number of outliers, and this revealed 5 properties that had an incorrect SHI assigned by the original dataset. Information on recently transacted property prices was also obtained for 8599 (85.3%) of buildings. CONCLUSION: SHI, a useful tool for health services research, can be accurately reconstructed using open datasets at no cost. This method is a convenient means for future researchers to obtain updated building-level markers of socioeconomic status for policy and research.

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INTRODUCTION: We aimed to assess the impact of socio-economic determinants of health (SEDH) on survival disparities within and between the ethnic groups of young-onset (<50 years age) colorectal adenocarcinoma patients. PATIENTS AND METHODS: Surveillance, epidemiology, and end results (SEER) registry was used to identify colorectal adenocarcinoma patients aged between 25-49 years from 2012 and 2016. Survival analysis was performed using the Kaplan-Meir method. Cox proportional hazards model was used to determine the hazard effect of SEDH. American community survey (ACS) data 2012-2016 were used to analyze the impact of high school education, immigration status, poverty, household income, employment, marital status, and insurance type. RESULTS: A total of 17,145 young-onset colorectal adenocarcinoma patients were studied. Hispanic (H) = 2874, Non-Hispanic American Indian/Alaskan Native (NHAIAN) = 164, Non-Hispanic Asian Pacific Islander (NHAPI) = 1676, Non-Hispanic black (NHB) = 2305, Non-Hispanic white (NHW) = 10,126. Overall cancer-specific survival was, at 5 years, 69 m. NHB (65.58 m) and NHAIAN (65.67 m) experienced worse survival compared with NHW (70.11 m), NHAPI (68.7), and H (68.31). High school education conferred improved cancer-specific survival significantly with NHAPI, NHB, and NHW but not with H and NHAIAN. Poverty lowered and high school education improved cancer-specific survival (CSS) in NHB, NHW, and NHAPI. Unemployment was associated with lowered CSS in H and NAPI. Lower income below the median negatively impacted survival among H, NHAPI NHB, and NHW. Recent immigration within the last 12 months lowered CSS survival in NHW. Commercial health insurance compared with government insurance conferred improved CSS in all groups. CONCLUSIONS: Survival disparities were found among all races with young-onset colorectal adenocarcinoma. The pattern of SEDH influencing survival was unique to each race. Overall higher income levels, high school education, private insurance, and marital status appeared to be independent factors conferring favorable survival found on multivariate analysis.

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OBJECTIVES: The global COVID-19 pandemic has affected various populations differently. We investigated the relationship between socioeconomic determinants of health obtained from the Robert Wood Johnson Foundation County Health Rankings and COVID-19 incidence and mortality at the county level in Georgia. METHODS: We analyzed data on COVID-19 incidence and case-fatality rates (CFRs) from the Georgia Department of Public Health from March 1 through August 31, 2020. We used repeated measures generalized linear mixed models to determine differences over time in Georgia counties among quartile health rankings of health outcomes, health behaviors, clinical care, social and economic factors, and physical environment. RESULTS: COVID-19 incidence per 100 000 population increased across all quartile county groups for all health rankings (range, 23.1-51.6 in May to 688.4-1062.0 in August). COVID-19 CFRs per 100 000 population peaked in April and May (range, 3312-6835) for all health rankings, declined in June and July (range, 827-5202), and increased again in August (range, 1877-3310). Peak CFRs occurred later in counties with low health rankings for health behavior and clinical care and in counties with high health rankings for social and economic factors and physical environment. All interactions between the health ranking quartile variables and month were significant (P < .001). County-level Gini indices were associated with significantly higher rates of COVID-19 incidence (P < .001) but not CFRs. CONCLUSIONS: From March through August 2020, COVID-19 incidence rose in Georgia's counties independent of health rankings categorization. Differences in time to peak CFRs differed at the county level based upon key health rankings. Public health interventions should incorporate unique strategies to improve COVID-19-related patient outcomes in these environments.

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Community health centers have withstood adversity for several decades. As health-care systems seek to reverse health inequities experienced by Black, Indigenous, and People of Color (BIPOC), learnings from community health centers demonstrate tangible ways to improve access and health for all. During the COVID-19 pandemic many community health centers have engaged in innovations in services to build on trust and to reach community members with testing and other needed services. Lessons around leading these efforts could support systemic change in the health-care system.

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