The Effects of Race/Ethnicity, Age, and Area Deprivation Index (ADI) on COVID-19 Disease Early Dynamics: Washington, D.C. Case Study

The current state of academic neurosurgery: A national survey assessing academic neurosurgical capacity and perceived needs

BACKGROUND

While inequities in the provision of neurosurgical care exist worldwide, the specific challenges in academic neurosurgical capacity remain inadequately understood. We sought to evaluate current neurosurgical capacity in United States academic tertiary care centers with neurosurgical residency programs and assess perceived needs in their respective practice settings.

METHODS

An online survey regarding human resources, medications, equipment, and infrastructure was distributed to all 117 residency programs in the US. Institutions were categorized using the Area Deprivation Index (ADI), a tool quantifying socioeconomic disadvantage, into low (0-50) or high (51-100) groups.

RESULTS

Responses from 37 institutions were recorded (59 % low ADI, 41 % high ADI). Common limitations included shortages of floor beds (84 %), nurses (81 %), and Neurocritical Care Unit (NCCU) beds (77 %). The least available equipment were intraoperative MRI (49 % total, Low ADI: 59 %, High ADI: 33 %, p = 0.18) and exoscopes (51 % total, Low ADI: 59 %, High ADI:40 %, p = 0.32). The most desired change in human resources was more operating room (OR) nurses (86 %, Low ADI: 77 %, High ADI: 100 %, p = 0.07) and the most common desired infrastructural changes were for more ORs (81 % total, Low ADI: 73 %, High ADI: 93 %, p = 0.2), floor beds (70 % total, Low ADI:59 %, High ADI:87 %, p = 0.14) and NCCU beds (70 % total, Low ADI: 68 %, High ADI:73 %, p = 1.0).

CONCLUSIONS

Academic centers across the US may face challenges related to advanced equipment, infrastructure, and personnel. More deprived programs may experience greater limitations. Interventions to address these limitations may be necessary, but further research is needed to comprehensively and objectively assess neurosurgical capacity.

Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing

PURPOSE

This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processing (NLP) and machine learning (ML) techniques on race-related spatiotemporal social media text data. Specifically, this study establishes the extent to which Latent Dirichlet Allocation (LDA) and Gibbs Sampling Dirichlet Multinomial Mixture (GSDMM)-based topic modeling determines social determinants of health (SDOH) categories, and how adequately custom named-entity recognition (NER) detects key SDOH factors from a race/ethnicity-related Reddit data corpus.

METHODS

In this study, we collected race/ethnicity-specific data from 5 location subreddits including New York City, NY; Los Angeles, CA; Chicago, IL; Philadelphia, PA; and Houston, TX from March to December 2019 (before COVID-19 pandemic) and from March to December 2020 (during COVID-19 pandemic). Next, we applied methods from natural language processing and machine learning to analyze SDOH issues from extracted Reddit comments and conversation threads using feature engineering, topic modeling, and custom named-entity recognition (NER).

RESULTS

Topic modeling identified 35 SDOH-related topics. The SDOH-based custom NER analyses revealed that the COVID-19 pandemic significantly impacted SDOH issues of marginalized Black and Asian communities. On average, the Social and Community Context (SCC) category of SDOH had the highest percent increase (366%) from the pre-pandemic period to the pandemic period across all locations and population groups. Some of the detected SCC issues were racism, protests, arrests, immigration, police brutality, hate crime, white supremacy, and discrimination.

CONCLUSION

Reddit social media platform can be an alternative source to assess the SDOH issues of marginalized Black and Asian communities during the COVID-19 pandemic. By employing NLP/ML techniques such as LDA/GSDMM-based topic modeling and custom NER on a race/ethnicity-specific Reddit corpus, we uncovered various SDOH issues affecting marginalized Black and Asian communities that were significantly worsened during the COVID-19 pandemic. As a result of conducting this research, we recommend that researchers, healthcare providers, and governments utilize social media and collaboratively formulate responses and policies that will address SDOH issues during public health crises.

Disparities in Infection Risk Among Home Health Care Patients: A Study Using Area Deprivation Index

OBJECTIVE

To examine the association between neighborhood deprivation and infection-related hospitalizations among home health care (HHC) patients across different rurality levels.

DESIGN

Retrospective observation analysis of 2019 national data sets, including Medicare data linked to 2019 Area Deprivation Index (ADI) data and Rural-Urban Continuum Codes (RUCCs).

SETTING AND PARTICIPANTS

The sample includes 3,656,810 HHC patients from 8135 HHC agencies nationwide. Patients were predominantly White (77.6%), with an average age of 80 years, and mostly female (61.7%). The sample included 24% dual-eligible patients and those living in large metropolitan (53.8%), small metro (30.2%), rural adjacent (11.4%), and remote rural areas (4.6%).

METHODS

Hospital admissions due to infection were identified through International Classification of Diseases, Tenth Revision (ICD-10), codes. Neighborhood deprivation was measured by the 2019 ADI. Patients were stratified by RUCC (large metro, small metro, rural adjacent, or remote rural). Within each rurality stratum, ADI quartiles were constructed, with higher quartiles indicating greater neighborhood deprivation. Multivariable logistic regression was conducted, adjusting for multiple-level variables.

RESULTS

As neighborhood deprivation increased, there was a rise in the proportion of dual-eligible, female, Black, and Hispanic patients, whereas the proportion of White patients decreased, especially in rural areas. Rural areas with higher ADI rankings showed lower quality metrics and reduced health care resources. Higher ADI quartiles were significantly associated with increased infection risks after adjusting for covariates, but this was only observed in remote rural areas, not in urban areas.

CONCLUSIONS AND IMPLICATIONS

The findings highlight significant policy and clinical implications for remote rural areas. Policymakers should increase investments in rural health infrastructure, enhance telehealth, improve transportation services, and offer incentives for health care providers to practice in these areas. The nonsignificant association between neighborhood deprivation and infection outcomes in metropolitan areas may stem from the ADI's limited sensitivity to urban contexts, highlighting the need for more nuanced indices that better capture urban socioeconomic challenges.

Analyzing the Association of the Area Deprivation Index on Patient-Reported Outcomes in Patients Undergoing Hip Arthroscopy

BACKGROUND

Hip arthroscopy is a valuable tool through which intra- and extra-articular hip pathologies may be addressed, with the goal of improving pain and function while preventing osteoarthritis progression. Little data are available regarding the effect of social determinants of health on hip arthroscopy outcomes.

PURPOSE

To determine if a patient's lived environment is associated with better or worse postoperative outcomes using the area deprivation index (ADI).

STUDY DESIGN

Cohort study; Level of evidence, 3.

METHODS

Patients undergoing hip arthroscopy between January 1, 2015, and June 30, 2022, at a single institution were identified using Current Procedural Terminology codes. Patients' zip codes were utilized to identify ADI measures. Patients were divided into quartiles of ADI, and the most deprived (ADIHigh) and least deprived (ADILow) quartiles were compared. Pre- and postoperative Patient-Reported Outcomes Measurement Information System (PROMIS) scores for the Pain Interference (PI), Physical Function (PF), and Depression domains were obtained. For the PF and PI domains, the minimal clinically important difference (MCID) was defined using an anchor-based approach using previously established cutoffs. For the Depression domain, the MCID was defined using a distribution-based approach and calculated as one-half of the standard deviation of the preoperative PROMIS score. Multivariable logistic regression models were estimated to characterize the association of the ADI with MCID attainment along PROMIS domains.

RESULTS

A total of 170 patients were included in the analysis of the ADIHigh (n = 85) and ADILow (n = 85) cohorts. Age, body mass index, smoking status, and race did not significantly vary between groups. No significant differences in MCID attainment were observed at any time point in the PF, PI, or Depression domains. However, the ADIHigh cohort had higher mean PI (worse) scores compared with the ADILow cohort at the preoperative, 1-year, and final follow-up (mean, 2.52 years) time points. In multivariable logistic regression analyses, ADI was not associated with the odds of MCID attainment.

CONCLUSION

For patients undergoing hip arthroscopy, increased social disadvantage measured by the ADI was not associated with the odds of MCID attainment in any PROMIS domain. This information provides guidance for care providers, researchers, and policymakers to seek and identify other mechanisms that may affect outcomes after hip arthroscopy.

Comparing the prevalence of substance use disorders between persons with and without autism spectrum disorders

Recent research has suggested that people with autism spectrum disorder may be disproportionately at risk of substance use disorders. This study analyzed national-level Medicaid Claims data to compare substance use disorder prevalence among Medicaid enrollees with autism spectrum disorder (N = 388,426) and a random sample of enrollees without autism spectrum disorder (n = 745,699) and to examine whether this association differs across sex and age groups and changes after adjusting for co-occurring mental health conditions. We also examined how the association between autism spectrum disorder and substance use disorder is moderated by co-occurring non-autism spectrum disorder mental health conditions and by community-level social determinants of health by merging Medicaid Claims data with zip code-level US Census data on socioeconomic deprivation. By 2016, 7% of Medicaid beneficiaries with autism spectrum disorder and no intellectual disability had at least one substance use disorder diagnosis, up from 1.75% USD prevalence among enrollees with autism spectrum disorder (no intellectual disability) in 2012 Medicaid data. Individuals with autism spectrum disorder aged 30-64 years were at an elevated risk of cannabis and hallucinogen disorders; this risk is likely compounded by co-occurring mental health conditions, which affect a half of all individuals with autism spectrum disorder and only 23% of individuals without autism spectrum disorder. Research and policy implications are discussed in turn.Lay abstractRecent research has suggested that people with autism spectrum disorder may be disproportionately at risk of substance use disorders. The present study analyzed national-level Medicaid Claims data to compare substance use disorder prevalence among Medicaid beneficiaries with autism spectrum disorder and without autism spectrum disorder and to examine whether this association differs across sex and age groups and depends on mental health conditions besides autism. We also examined how the association between autism spectrum disorder and substance use disorder is moderated by co-occurring non-autism spectrum disorder mental health conditions and by community-level social determinants of health. For the latter purpose, Medicaid Claims data were merged with zip code-level US Census data on socioeconomic deprivation. Our analyses demonstrated that, by 2016, 7% of Medicaid enrollees with autism spectrum disorder and no intellectual disability had at least one substance use disorder diagnosis, up from 1.75% USD prevalence among enrollees with autism spectrum disorder (no intellectual disability) in 2012 Medicaid data. Individuals with autism spectrum disorder aged 30-64 years are at an elevated risk of cannabis and hallucinogen use disorders, while this risk is likely compounded by co-occurring mental health conditions, which affect a half of all individuals with autism spectrum disorder and only 23% of individuals without autism spectrum disorder. Research and policy implications are discussed in turn.

Socioeconomic Disparities and the Prevalence of Antimicrobial Resistance

BACKGROUND

The increased prevalence of antimicrobial-resistant (AMR) infections is a significant global health threat, resulting in increased disease, deaths, and costs. The drivers of AMR are complex and potentially impacted by socioeconomic factors. We investigated the relationships between geographic and socioeconomic factors and AMR.

METHODS

We collected select patient bacterial culture results from 2015 to 2020 from electronic health records of 2 expansive healthcare systems within the Dallas-Fort Worth, Texas, metropolitan area. Among individuals with electronic health records who resided in the 4 most populous counties in Dallas-Fort Worth, culture data were aggregated. Case counts for each organism studied were standardized per 1000 persons per area population. Using residential addresses, the cultures were geocoded and linked to socioeconomic index values. Spatial autocorrelation tests identified geographic clusters of high and low AMR organism prevalence and correlations with established socioeconomic indices.

RESULTS

We found significant clusters of AMR organisms in areas with high levels of deprivation, as measured by the area deprivation index (ADI). We found a significant spatial autocorrelation between ADI and the prevalence of AMR organisms, particularly for AmpC β-lactamase and methicillin-resistant Staphylococcus aureus, with 14% and 13%, respectively, of the variability in prevalence rates being attributable to their relationship with the ADI values of the neighboring locations.

CONCLUSIONS

We found that areas with a high ADI are more likely to have higher rates of AMR organisms. Interventions that improve socioeconomic factors such as poverty, unemployment, decreased access to healthcare, crowding, and sanitation in these areas of high prevalence may reduce the spread of AMR.

Association of Area Deprivation Index With Mortality in Critically Ill Adults With COVID-19

BACKGROUND

Various social determinants of health have been established as significant risk factors for COVID-19 transmission, prevalence, incidence, and mortality. Area deprivation index (ADI, a composite score made up of educational, housing, and poverty markers) is an accepted multidimensional social determinants of health measure. Little is known about how structural social determinants of health before hospitalization, including ADI, may affect mortality related to COVID-19 in critically ill patients.

OBJECTIVES

To examine the association of ADI with intensive care unit (ICU) mortality in patients with COVID-19 and compare its predictive power with that of clinical factors.

METHODS

This was a retrospective cohort study of critically ill adults with COVID-19 in 3 hospitals within a single health system. Multivariable logistic regression models (adjusted for demographic and clinical variables) were used to examine the association of ADI with ICU mortality.

RESULTS

Data from 1784 patients hospitalized from 2020 to 2022 were analyzed. In multivariable models, no association was found between national ADI and ICU mortality. Notable factors associated with ICU mortality included treatment year, age, van Walraven weighted score, invasive mechanical ventilation, and body mass index.

CONCLUSION

In this study, clinical factors were more predictive of mortality than ADI and other social determinants of health. The influence of ADI may be most relevant before hospital admission. These findings could serve as a foundation for shaping targeted public health strategies and hospital interventions, enhancing care delivery, and potentially contributing to better outcomes in future pandemics.

Striving for Equity: Examining Health Disparities in Urologic Oncology

Health disparities in urologic oncology, particularly in prostate, bladder, kidney, and testicular cancers, significantly impact patient outcomes across different demographic groups. This narrative review aims to investigate the extent and drivers of these disparities, focusing on the influence of race, socioeconomic status, and geographic location on diagnosis, treatment, and survival outcomes. We conducted a comprehensive review of the existing literature and analyzed data from national cancer databases to identify patterns of inequity. Our findings reveal that minority populations, individuals with lower socioeconomic status, and those residing in underserved areas are less likely to receive timely and guideline-based care, leading to worse outcomes. This review underscores the urgent need for targeted interventions, including policy reforms, health system restructuring, enhanced community outreach, and increased funding for disparity-focused research, to ensure equitable access to high-quality oncologic care. Addressing these disparities is crucial for improving cancer outcomes and achieving health equity in urologic oncology.

Association Between Neighborhood Deprivation and Number of Ophthalmology Providers

PURPOSE

The Area Deprivation Index (ADI) is a quantitative measurement of neighborhood socioeconomic disadvantage used to identify high-risk communities. The distribution of physicians with respect to ADI can indicate decreased healthcare access in deprived neighborhoods. This study applies ADI to the distribution of ophthalmologists and demonstrates how practice patterns in the national Medicare Part D program may vary with ADI.

METHODS

The Centers for Medicare and Medicaid Services Data "Medicare Part D Prescribers by Provider" data for 2021 was analyzed. Geocodio identified ADIs corresponding to the practice addresses listed in the dataset. The national rank ADIs were compared against the number of ophthalmologists. Spearman's correlation test and one-way ANOVA determined statistically significant differences in Medicare data extracted between quintiles of ADI ranks.

RESULTS

We identified 14,668 ophthalmologists who provided care to Medicare beneficiaries. Each time ADI increased by 10, there was an average 9.4% decrease in ophthalmologists (p < 0.001). The distribution of ophthalmologists practicing throughout the United States by increasing ADI quintile are: 32%, 23%, 19%, 16%, and 9%. Providers practicing in neighborhoods in the first-ADI quintile were more likely to see Medicare beneficiaries compared to providers in the fifth-ADI quintile (p < 0.001).

CONCLUSION

The lack of ophthalmologists in high-ADI areas results in reduced eye care access in deprived neighborhoods. Many factors contribute to these disparities including limited access to metropolitan areas/academic institutions and fewer residency programs. Future programs and policies should focus efforts on creating an even distribution of ophthalmologists across the United States and improving access to eye care.

Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data

BACKGROUND

Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients endured worse outcomes disproportionately compared with non-Hispanic White patients, but the epidemiological basis for these observations was complex and multifaceted.

OBJECTIVE

This study aimed to elucidate the potential reasons behind the worse outcomes of COVID-19 experienced by non-Hispanic Black patients compared with non-Hispanic White patients and how these variables interact using an explainable machine learning approach.

METHODS

In this retrospective cohort study, we examined 28,943 laboratory-confirmed COVID-19 cases from the OneFlorida Research Consortium's data trust of health care recipients in Florida through April 28, 2021. We assessed the prevalence of pre-existing comorbid conditions, geo-socioeconomic factors, and health outcomes in the structured electronic health records of COVID-19 cases. The primary outcome was a composite of hospitalization, intensive care unit admission, and mortality at index admission. We developed and validated a machine learning model using Extreme Gradient Boosting to evaluate predictors of worse outcomes of COVID-19 and rank them by importance.

RESULTS

Compared to non-Hispanic White patients, non-Hispanic Blacks patients were younger, more likely to be uninsured, had a higher prevalence of emergency department and inpatient visits, and were in regions with higher area deprivation index rankings and pollutant concentrations. Non-Hispanic Black patients had the highest burden of comorbidities and rates of the primary outcome. Age was a key predictor in all models, ranking highest in non-Hispanic White patients. However, for non-Hispanic Black patients, congestive heart failure was a primary predictor. Other variables, such as food environment measures and air pollution indicators, also ranked high. By consolidating comorbidities into the Elixhauser Comorbidity Index, this became the top predictor, providing a comprehensive risk measure.

CONCLUSIONS

The study reveals that individual and geo-socioeconomic factors significantly influence the outcomes of COVID-19. It also highlights varying risk profiles among different racial groups. While these findings suggest potential disparities, further causal inference and statistical testing are needed to fully substantiate these observations. Recognizing these relationships is vital for creating effective, tailored interventions that reduce disparities and enhance health outcomes across all racial and socioeconomic groups.

Disparities in the Presentation and Management of Pediatric Retropharyngeal Abscess

OBJECTIVES

Differences in management and outcomes of otolaryngologic diseases may reflect inequities driven by social determinants of health. This study aimed to investigate disparities in presentation and outcomes of retropharyngeal abscess (RPA) among 231 pediatric patients.

METHODS

Medical records were searched for pediatric patients with RPA from 2010 to 2021. Charts were reviewed for demographics, clinical features, and treatment decisions. Area deprivation index (ADI) scores for patient zip codes were determined. Chi-square analysis independent samples t-test, and regression analyses were used to investigate associations between variables.

RESULTS

Among patients presenting for RPA, Black patients were less likely to undergo surgical management than non-Black patients (53.2% vs. 71.6%, p = 0.009). Black patients had a lower rate of treatment with antibiotics prior to hospital admission (19.4% vs. 54.4%, p < 0.001). Among patients who received surgery, Black patients had higher cross-sectional abscess area on CT (6.4 ± 8.4 cm2  > vs. 3.8 ± 3.3 cm2 , p = 0.014), longer length of stay (5.4 ± 3.3 days vs. 3.2 ± 1.5, p < 0.001), and longer time between admission and surgery (2.3 ± 2.1 vs. 0.83 ± 1.1, p < 0.001). Increased ADI was correlated with increased rate of trismus.

CONCLUSIONS

Lower rates of pre-admission antibiotics and larger abscess area on CT imaging among Black patients may suggest disparities in access to primary care, resulting in presentation to tertiary care at later stages of disease and higher rates of medical management trial prior to surgical intervention.

LEVEL OF EVIDENCE

3 (retrospective cohort study) Laryngoscope, 134:1907-1912, 2024.

Increased Neighborhood Deprivation Is Associated with Prolonged Hospital Stays After Surgical Fixation of Traumatic Pelvic Ring Injuries

BACKGROUND

The purpose of this study was to understand the role of social determinants of health assessed by the Area Deprivation Index (ADI) on hospital length of stay and discharge destination following surgical fixation of pelvic ring fractures.

METHODS

A retrospective chart analysis was performed for all patients who presented to our level-I trauma center with pelvic ring injuries that were treated with surgical fixation. Social determinants of health were determined via use of the ADI, a comprehensive metric of socioeconomic status, education, income, employment, and housing quality. ADI values range from 0 to 100 and are normalized to a U.S. mean of 50, with higher scores representing greater social deprivation. We stratified our cohort into 4 ADI quartiles. Statistical analysis was performed on the bottom (25th percentile and below, least deprived) and top (75th percentile and above, most deprived) ADI quartiles. Significance was set at p < 0.05.

RESULTS

There were 134 patients who met the inclusion criteria. Patients in the most deprived group were significantly more likely to have a history of smoking, to self-identify as Black, and to have a lower mean household income (p = 0.001). The most deprived ADI quartile had a significantly longer mean length of stay (and standard deviation) (19.2 ± 19 days) compared with the least deprived ADI quartile (14.7 ± 11 days) (p = 0.04). The least deprived quartile had a significantly higher percentage of patients who were discharged to a resource-intensive skilled nursing facility or inpatient rehabilitation facility compared with those in the most deprived quartile (p = 0.04). Race, insurance, and income were not significant predictors of discharge destination or hospital length of stay.

CONCLUSIONS

Patients facing greater social determinants of health had longer hospital stays and were less likely to be discharged to resource-intensive facilities when compared with patients of lesser social deprivation. This may be due to socioeconomic barriers that limit access to such facilities.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Disparities in COVID-19 related outcomes in the United States by race and ethnicity pre-vaccination era: an umbrella review of meta-analyses

Background

Meta-analyses have investigated associations between race and ethnicity and COVID-19 outcomes. However, there is uncertainty about these associations' existence, magnitude, and level of evidence. We, therefore, aimed to synthesize, quantify, and grade the strength of evidence of race and ethnicity and COVID-19 outcomes in the US.

Methods

In this umbrella review, we searched four databases (Pubmed, Embase, the Cochrane Database of Systematic Reviews, and Epistemonikos) from database inception to April 2022. The methodological quality of each meta-analysis was assessed using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR-2). The strength of evidence of the associations between race and ethnicity with outcomes was ranked according to established criteria as convincing, highly suggestive, suggestive, weak, or non-significant. The study protocol was registered with PROSPERO, CRD42022336805.

Results

Of 880 records screened, we selected seven meta-analyses for evidence synthesis, with 42 associations examined. Overall, 10 of 42 associations were statistically significant (p ≤ 0.05). Two associations were highly suggestive, two were suggestive, and two were weak, whereas the remaining 32 associations were non-significant. The risk of COVID-19 infection was higher in Black individuals compared to White individuals (risk ratio, 2.08, 95% Confidence Interval (CI), 1.60-2.71), which was supported by highly suggestive evidence; with the conservative estimates from the sensitivity analyses, this association remained suggestive. Among those infected with COVID-19, Hispanic individuals had a higher risk of COVID-19 hospitalization than non-Hispanic White individuals (odds ratio, 2.08, 95% CI, 1.60-2.70) with highly suggestive evidence which remained after sensitivity analyses.

Conclusion

Individuals of Black and Hispanic groups had a higher risk of COVID-19 infection and hospitalization compared to their White counterparts. These associations of race and ethnicity and COVID-19 outcomes existed more obviously in the pre-hospitalization stage. More consideration should be given in this stage for addressing health inequity.

Medication and Road Test Performance Among Cognitively Healthy Older Adults

Importance

Older adults are increasingly prescribed medications that have adverse effects. Prior studies have found a higher risk of motor vehicle crashes to be associated with certain medication use.

Objective

To determine whether specific medication classes were associated with performance decline as assessed by a standardized road test in a community sample of cognitively healthy older adults, to evaluate additional associations of poor road test performance with comorbid medical conditions and demographic characteristics, and to test the hypothesis that specific medication classes (ie, antidepressants, benzodiazepines, sedatives or hypnotics, anticholinergics, antihistamines, and nonsteroidal anti-inflammatory drugs or acetaminophen) would be associated with an increase in risk of impaired driving performance over time.

Design, Setting, and Participants

This was a prospective cohort study of 198 cognitively healthy adults 65 years and older with a valid driver's license who were followed up annually, with rolling enrollment. Data were collected from participants in St Louis, Missouri, and neighboring Illinois who were enrolled in the Knight Alzheimer's Disease Research Center. Data were collected from August 28, 2012, to March 14, 2023, and analyzed from April 1 to 25, 2023. Participants with healthy cognition, defined as a Clinical Dementia Rating score of 0 at baseline and subsequent visits, who had available clinical, neuropsychological, road tests, and self-reported medication data were included.

Exposure

Potentially driver-impairing medication use.

Main Outcomes and Measures

The primary outcome measure was performance on the Washington University Road Test (pass or marginal/fail). Multivariable Cox proportional hazards models were used to evaluate associations between potentially driver-impairing medication use and road test performance.

Results

Of the 198 included adults (mean [SD] baseline age, 72.6 [4.6] years; 87 female [43.9%]), 70 (35%) received a marginal/fail rating on the road test over a mean (SD) follow-up of 5.70 (2.45) years. Any use of antidepressants (adjusted hazard ratio [aHR], 2.68; 95% CI, 1.69-4.71), serotonin and norepinephrine reuptake inhibitors (aHR, 2.68; 95% CI, 1.54-4.64), sedatives or hypnotics (aHR, 2.70; 95% CI, 1.40-5.19), or nonsteroidal anti-inflammatory drugs (aHR, 2.72; 95% CI, 1.31-5.63) was associated with an increase in risk of receiving a marginal/fail rating on the road test compared with control individuals. Conversely, participants taking lipid-lowering agents had a lower risk of receiving a marginal/fail rating compared to control individuals. There were no statistically significant associations found between anticholinergic or antihistamines and poor performance.

Conclusions and Relevance

In this prospective cohort study, specific medication classes were associated with an increase in risk of poor road test performance over time. Clinicians should consider this information and counsel patients accordingly when prescribing these medications.

New York State, New York City, New Jersey, Puerto Rico, and the US Virgin Islands' Health Department Experiences Promoting Health Equity During the Initial COVID-19 Omicron Variant Period, 2021-2022

In this case study, we aim to understand how health departments in 5 US jurisdictions addressed health inequities and implemented strategies to reach populations disproportionately affected by COVID-19 during the initial Omicron variant period. We used qualitative methods to examine health department experiences during the initial Omicron surge, from November 2021 to April 2022, assessing successful interventions, barriers, and lessons learned from efforts to promote health equity. Our findings indicate that government leadership supported prioritizing health equity from the beginning of the pandemic, seeing it as a need and vital part of the response framework. All jurisdictions acknowledged the historical trauma and distrust of the government. Health departments found that collaborating and communicating with trusted community leaders helped mitigate public distrust. Having partnerships, resources, and infrastructure in place before the pandemic facilitated the establishment of equity-focused COVID-19 response activities. Finally, misinformation about COVID-19 was a challenge for all jurisdictions. Addressing the needs of diverse populations involves community-informed decisionmaking, diversity of thought, and delivery measures that are tailored to the community. It is imperative to expand efforts to reduce and eliminate health inequities to ensure that individuals and communities recover equitably from the effects of COVID-19.

Regional differences in health screening participation between before and during COVID-19 pandemic

BACKGROUND

Health screening is a preventive and cost-effective public health strategy for early detection of diseases. However, the COVID-19 pandemic has decreased health screening participation. The aim of this study was to examine regional differences in health screening participation between before and during COVID-19 pandemic and vulnerabilities of health screening participation in the regional context.

METHODS

Administrative data from 229 districts consisting of 16 provinces in South Korea and health screening participation rate of each district collected in 2019 and 2020 were included in the study. Data were then analyzed via descriptive statistics and geographically weighted regression (GWR).

RESULTS

This study revealed that health screening participation rates decreased in all districts during COVID-19. Regional vulnerabilities contributing to a further reduction in health screening participation rate included COVID-19 concerns, the population of those aged 65+ years and the disabled, lower education level, lower access to healthcare, and the prevalence of chronic disease. GWR analysis showed that different vulnerable factors had different degrees of influence on differences in health screening participation rate.

CONCLUSIONS

These findings could enhance our understanding of decreased health screening participation due to COVID-19 and suggest that regional vulnerabilities should be considered stringent public health strategies after COVID-19.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

Association of Plasma and Cerebrospinal Fluid Alzheimer Disease Biomarkers With Race and the Role of Genetic Ancestry, Vascular Comorbidities, and Neighborhood Factors

IMPORTANCE

Differences in cerebrospinal fluid (CSF) tau Alzheimer dementia (AD) biomarkers by self-identified race have been observed in prior studies. More recently, plasma biomarkers have been gaining recognition, but whether they exhibit similar differences is unclear. Furthermore, the underlying explanation for these differences in AD biomarkers is still unexplored.

OBJECTIVES

To investigate differences in plasma biomarkers by race and genetic ancestry and explore potential underlying explanations for these differences.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used participant data from the Brain, Stress, Hypertension, and Aging Research Program (B-SHARP), an observational study conducted in the greater Atlanta metropolitan area. Participants were enrolled from March 1, 2016, to January 1, 2020.

MAIN OUTCOMES AND MEASURES

Main outcomes were plasma and CSF amyloid-β (Aβ) 42, Aβ40, phosphorylated tau181 (p-tau181), and neurofilament light. General linear models were used for key comparisons.

EXPOSURES

Main independent variables were self-identified race and genetic ancestry. Additional variables were cardiovascular factors, APOE4, educational attainment, Area Deprivation Index, and C-reactive protein (reflecting systemic inflammation state).

RESULTS

This analysis included 617 participants (mean [SD] age, 66 [7.9] years; 300 [49%] African American and 317 [51%] White; 429 [70%] with mild cognitive impairment). On the basis of self-reported race, plasma levels of Aβ42 (adjusted mean difference, -1.20 pg/mL; 95% CI, -2.33 to -0.07 pg/mL), Aβ40 (adjusted mean difference, -37.78 pg/mL; 95% CI, -60.16 to -15.39 pg/mL), p-tau181 (adjusted mean difference, -4.66 pg/mL; 95% CI, -7.05 to -1.90 pg/mL), and neurofilament light (adjusted mean difference, -1.58; 95% CI, -2.83 to -0.19 pg/mL) were consistently lower in African American individuals after adjusting for demographic characteristics, educational attainment, cognition, APOE4, and cardiovascular factors. A similar pattern was observed in the CSF biomarkers except for Aβ42 and Aβ40. Although unadjusted analyses revealed an association between these biomarkers and African ancestry, these associations were not significant after adjusting for the same covariates. Differences by self-reported race were not explained by varied cardiovascular risk factors, C-reactive protein, educational attainment, or Area Deprivation Index.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study of plasma biomarkers by race and genetic ancestry, the results indicated that plasma p-tau181, Aβ40, and NFL were lower in African American individuals based on self-reported race but not genetic ancestry. These differences were not explained by cardiovascular risks or clinical stage differences. These racial differences should be considered in clinical interpretations and clinical trial screenings to avoid an additional increase in underrepresentation of African American individuals in AD trials.

Impact of Socioeconomic Deprivation on the Local Spread of COVID-19 Cases Mediated by the Effect of Seasons and Restrictive Public Health Measures: A Retrospective Observational Study in Apulia Region, Italy

The aim of this study was to investigate the spatiotemporal association between socioeconomic deprivation and the incidence of COVID-19 and how this association changes through the seasons due to the existence of restrictive public health measures. A retrospective observational study was conducted among COVID-19 cases that occurred in the Apulia region from 29 February 2020 to 31 December 2021, dividing the period into four phases with different levels of restrictions. A generalized estimating equation (GEE) model was applied to test the independent effect of deprivation on the incidence of COVID-19, taking into account age, sex, and regional incidence as possible confounding effects and covariates, such as season and levels of restrictions, as possible modifying effects. The highest incidence was in areas with a very high deprivation index (DI) in winter. During total lockdown, no rate ratio between areas with different levels of DI was significant, while during soft lockdown, areas with very high DI were more at risk than all other areas. The effects of social inequalities on the incidence of COVID-19 changed in association with the seasons and restrictions on public health. Disadvantaged areas showed a higher incidence of COVID-19 in the cold seasons and in the phases of soft lockdown.