Geographic Disparities and Determinants of COVID-19 Incidence Risk in the Greater St. Louis Area, Missouri

Background: Evidence suggests that the risk of Coronavirus Disease 2019 (COVID-19) varies geographically due to differences in population characteristics. Therefore, the objectives of this study were to identify: (a) geographic disparities of COVID-19 risk in the Greater St. Louis area of Missouri, USA; (b) predictors of the identified disparities. Methods: Data on COVID-19 incidence and chronic disease hospitalizations were obtained from the Departments of Health and Missouri Hospital Association, respectively. Socioeconomic and demographic data were obtained from the 2018 American Community Survey while population mobility data were obtained from the SafeGraph website. Choropleth maps were used to identify geographic disparities of COVID-19 risk and its predictors at the ZIP Code Tabulation Area (ZCTA) spatial scale. Global negative binomial and local geographically weighted negative binomial models were used to identify predictors of ZCTA-level geographic disparities of COVID-19 risk. Results: There were geographic disparities in COVID-19 risk. Risks tended to be higher in ZCTAs with high percentages of the population with a bachelors degree (p<0.0001) and obesity hospitalizations (p<0.0001). Conversely, risks tended to be lower in ZCTAs with high percentages of the population working in agriculture (p<0.0001). However, the association between agricultural occupation and COVID-19 risk was modified by per capita between ZCTA visits. Areas that had both high per capita between ZCTA visits and high percentages of the population employed in agriculture had high COVID-19 risks. The strength of association between agricultural occupation and COVID-19 risk varied by geographic location. Conclusions: Geographic Information Systems, global and local models are useful for identifying geographic disparities and predictors of COVID-19 risk. Geographic disparities of COVID-19 risk exist in the St. Louis area and are explained by differences in sociodemographic factors, population movements, and obesity hospitalization risks. The latter is particularly concerning due to the growing prevalence of obesity and the known immunological impairments among obese individuals. Therefore, future studies need to focus on improving our understanding of the relationships between COVID-19 vaccination efficacy, obesity and waning of immunity among obese individuals so as to better guide vaccination regimens, reduce disparities and improve population health for all.

Increasing access to allotransplants in the United States: the impact of race, geography, and socioeconomics

Allogeneic hematopoietic cell transplantation (HCT) is particularly susceptible to racial, socioeconomic, and geographic disparities in access and outcomes given its specialized nature and its availability in select centers in the United States. Nearly all patients who need HCT have a potential donor in the current era, but racial minority populations are less likely to have an optimal donor and often rely on alternative donor sources. Furthermore, prevalent health care disparity factors are further accentuated and can be barriers to access and referral to a transplant center. Research has primarily focused on defining and quantifying a variety of social determinants of health and their association with access to allogeneic HCT, with a focus on race/ethnicity and socioeconomic status. However, research on interventions is lacking and is an urgent unmet need. We discuss the role of racial, socioeconomic, and geographic disparities in access to allogeneic HCT, along with policy changes to address and mitigate them and opportunities for future research.

Geographic Disparities of Alzheimer’s Disease Mortality in Females With Breast Cancer

Our estimates showed significant gaps in mortality rates between the West and East parts of the U.S. when these rates are based on death certificate data. These geographic disparities were persistent over time and could not be fully explained by differences in demographic and socioeconomic characteristics, comorbidities, and/or differences in AD coding between these regions. However, incidence and incidence-based mortality rates based on Medicare data do not reproduce these geographic disparities. Death certificate-based patterns hold for the subset of the population with breast cancer, e.g., for subpopulation for which breast cancer was listed as a secondary cause of death. Therefore, SEER-Medicare data, which contains both death-certificate records and Medicare administrative claims for the same individuals can be used to resolve this inconsistency in findings. Analysis of breast cancer patients from two SEER registries in NJ and WA states in SEER-Medicare data (2000-2013) showed that the fraction of deceased individuals with an underlying cause AD among those who had a Medicare diagnosis of AD is 2.5-3.5 times (depending on the Medicare ascertainment algorithm) higher in WA comparing to NJ (p&lt;0.0001). The odds ratio of not-having AD as an underlying cause is 1.3 for WA vs. NJ and increases with age, for non-white races, and unmarried individuals. Our findings do not support the hypothesis of higher rates of AD in WA state but show that AD is likely underrepresented in death certificate in NJ and possibly other East coast states.

Geographic Disparities in Cardiovascular Death Among Patients with Myelodysplastic Syndromes

Introduction: Acquired somatic mutations in hematopoietic stem cells lead to myelodysplastic syndromes (MDS) and are also associated with accelerated atherosclerosis. In subjects without MDS, these mutations constitute a potent cardiovascular risk factor: clonal hematopoiesis (CH). In a previous analysis, we demonstrated that an MDS diagnosis was an independent risk factor for cardiovascular disease (CVD) compared to propensity matched non-cancer controls. CVD is the most common non-cancer cause of death in MDS, and rural residence has been independently associated with many CVD risk factors. However, there are no studies examining the association of geographic disparities and cardiovascular death in patients with MDS. Methods: We identified adult patients diagnosed with MDS between 2001 and 2016 using the Surveillance, Epidemiology, and End Results (SEER) database. MDS risk was classified as low, intermediate or high, using International Classification of Diseases for Oncology 3 rd Edition (ICDO-3) codes. Rural and urban populations were categorized using the US Department of Agriculture's Rural-Urban Continuum Codes (RUCC). Primary cause of death reported to State Registries (SEER COD recode) was used to estimate cause-specific survival, calculated from date of MDS diagnosis to date of CVD-related death. Cases with missing data on any key variable were excluded from analysis. SEER*Stat version 8.3.9 was used to calculate incidence rates. Chi-square and t-test were used to compare categorical and continuous variables, respectively. Survival analyses employed the Kaplan-Meier method and log-rank tests. Multivariable Cox-proportional hazards repression estimated the association of rural residence with CVD death adjusting for age, sex, race, ethnicity, MDS risk, and geographic location. SAS version 9.4 was used for statistical analysis. Results: We included 52,750 patients with MDS, 56.8% were male and 84.8% were white. Low, intermediate and high histologic risk were seen in 18.7%, 64.4% and 16.9% respectively. Most patients were from urban areas (88%), however the estimated incidence rate for MDS was 6.7 per 100,000 per population at risk in both urban and rural populations. The rural MDS population was younger (median age 75 vs 77 years, p&lt;0.004) and had a higher proportion of whites (90.5% vs 84%, p&lt;0.001), but no difference in MDS risk distribution was noted by rurality (Table 1). Unadjusted analyses revealed a trend towards lower overall survival in the rural MDS population (24 vs 25 months, p=0.051). After adjusting for age, sex, race, ethnicity, MDS risk and area of residence, rural subjects with MDS had a 12% increased hazard (HR 1.12, 95%CI 1.03 - 1.22) for CVD-related death compared to urban subjects (Figure 1). Further, the adjusted HR for CVD-related death was 1.23 (CI95% 1.01 - 1.50) for those who lived in the most rural areas (RUCC codes 8 and 9, less than 2,500 urban population). Among young MDS patients (age&lt;65), those residing in rural areas had a higher proportion of CVD-related death (6% vs 4.7%, p=0.031) and significantly shorter CVD-specific survival compared to urban patients (Figure 2). MDS histologic risk was also a significant factor in the multivariable model (Table 2). Compared to low risk MDS, patients with intermediate and high risk had adjusted HR for CVD-related death of 1.17 (95%CI 1.11 - 1.24) and 1.2 (95%CI 1.09 - 1.32), respectively. Other factors significantly associated with increased hazard for CVD-related death in the adjusted model were advancing age and male sex. Discussion: In a large population-based study, we found that rural area of residence is significantly associated with a higher burden of CVD-related death in subjects with MDS, after adjusting for demographic risk factors and MDS risk classification. Although aging is an important issue in rural areas, the geographical disparities in CVD-related death among MDS patients are not explained by age alone and the difference was notable in young MDS patients. These findings should prompt hematologists caring for patients with MDS from rural areas to rigorously evaluate and address CVD risk factors. As novel treatments improve cancer-specific survival in MDS, marginalized populations with different CVD risk profiles may be disproportionally affected by the cardiovascular risk from CH, which should be considered when developing MDS surveillance programs. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Acute Ischemic Stroke Interventions in the United States and Racial, Socioeconomic, and Geographic Disparities

Background and ObjectivesIn ischemic stroke (IS) patients, intravenous alteplase (tPA) and endovascular thrombectomy (EVT) reduce long-term disability, but their utilization has not been fully optimized. Prior research has also demonstrated disparities in the use of tPA and EVT specific to sex, race/ethnicity, socioeconomic status, and geographic location. We sought to determine the utilization of tPA and EVT in the United States from 2016-18 and if disparities in utilization persist.MethodsThis is a retrospective, longitudinal analysis of the 2016-18 National Inpatient Sample.We included adult patients who had a primary discharge diagnosis of IS. The primary study outcomes were the proportions who received tPA or EVT. We fit a multivariate logistic regression model to our outcomes in the full cohort and also in the subset of patients who had an available baseline NIH Stroke Scale (NIHSS).ResultsThe full cohort after weighting included 1,439,295 IS patients. The proportion who received tPA increased from 8.8% in 2016 to 10.2% in 2018 (p<0.001); and who had EVT from 2.8% in 2016 to 4.9% in 2018 (p<0.001). Comparing Black to White patients, the odds ratio of receiving tPA was 0.82 (95% CI 0.79-0.86) and for having EVT was 0.75 (95% CI 0.70-0.81). Comparing patients with a median income in their ZIP code of ≤$37,999 to >$64,000, the odds ratio of receiving tPA was 0.81 (95% CI 0.78-0.85) and for having EVT was 0.84 (95% CI 0.77-0.91). Comparing patients living in a rural area to a large metro area, the odds ratio of receiving tPA was 0.48 (95% CI 0.44-0.52) and for having EVT was 0.92 (95% CI 0.81-1.05). These associations were largely maintained after adjustment for NIHSS, although the effect size changed for many of them. Contrary to prior reports with older datasets, sex was not consistently associated with tPA or EVT.ConclusionUtilization of tPA and EVT for IS in the United States increased from 2016 to 2018. Still, there are racial, socioeconomic, and geographic disparities in the accessibility of tPA and EVT for IS patients with important public health implications that require further study.