Search

Background: Social and ecological differences in early SARS-CoV-2 pandemic screening and outcomes have been documented, but the means by which these differences have arisen are not well understood., Objective: To characterize socioeconomic and chronic disease-related mechanisms underlying these differences., Design: Observational cohort study., Setting: Outpatient and emergency care., Patients: 12900 Cleveland Clinic Health System patients referred for SARS-CoV-2 testing between March 17 and April 15, 2020., Interventions: Nasopharyngeal PCR test for SARS-CoV-2 infection., Measurements: Test location (emergency department, ED, vs. outpatient care), COVID-19 symptoms, test positivity and hospitalization among positive cases., Results: We identified six classes of symptoms, ranging in test positivity from 3.4% to 23%. Non-Hispanic Black race/ethnicity was disproportionately represented in the group with highest positivity rates. Non-Hispanic Black patients ranged from 1.81 [95% confidence interval: 0.91-3.59] times (at age 20) to 2.37 [1.54-3.65] times (at age 80) more likely to test positive for the SARS-CoV-2 virus than non-Hispanic White patients, while test positivity was not significantly different across the neighborhood income spectrum. Testing in the emergency department (OR: 5.4 [3.9, 7.5]) and cardiovascular disease (OR: 2.5 [1.7, 3.8]) were related to increased risk of hospitalization among the 1247 patients who tested positive., Limitations: Constraints on availability of test kits forced providers to selectively test for SARS-Cov-2., Conclusion: Non-Hispanic Black patients and patients from low-income neighborhoods tended toward more severe and prolonged symptom profiles and increased comorbidity burden. These factors were associated with higher rates of testing in the ED. Non-Hispanic Black patients also had higher test positivity rates., Competing Interests: The authors have declared that no competing interests exist.

Background: Inequality in health outcomes in relation to Americans' socioeconomic position is rising., Objective: First, to evaluate the spatial relationship between neighborhood disadvantage and major atherosclerotic cardiovascular disease (ASCVD)-related events; second, to evaluate the relative extent to which neighborhood disadvantage and physiologic risk account for neighborhood-level variation in ASCVD event rates., Design: Observational cohort analysis of geocoded longitudinal electronic health records., Setting: A single academic health center and surrounding neighborhoods in northeastern Ohio., Patients: 109 793 patients from the Cleveland Clinic Health System (CCHS) who had an outpatient lipid panel drawn between 2007 and 2010. The date of the first qualifying lipid panel served as the study baseline., Measurements: Time from baseline to the first occurrence of a major ASCVD event (myocardial infarction, stroke, or cardiovascular death) within 5 years, modeled as a function of a locally derived neighborhood disadvantage index (NDI) and the predicted 5-year ASCVD event rate from the Pooled Cohort Equations Risk Model (PCERM) of the American College of Cardiology and American Heart Association. Outcome data were censored if no CCHS encounters occurred for 2 consecutive years or when state death data were no longer available (that is, from 2014 onward)., Results: The PCERM systematically underpredicted ASCVD event risk among patients from disadvantaged communities. Model discrimination was poorer among these patients (concordance index [C], 0.70 [95% CI, 0.67 to 0.74]) than those from the most affluent communities (C, 0.80 [CI, 0.78 to 0.81]). The NDI alone accounted for 32.0% of census tract-level variation in ASCVD event rates, compared with 10.0% accounted for by the PCERM., Limitations: Patients from affluent communities were overrepresented. Outcomes of patients who received treatment for cardiovascular disease at Cleveland Clinic were assumed to be independent of whether the patients came from a disadvantaged or an affluent neighborhood., Conclusion: Neighborhood disadvantage may be a powerful regulator of ASCVD event risk. In addition to supplemental risk models and clinical screening criteria, population-based solutions are needed to ameliorate the deleterious effects of neighborhood disadvantage on health outcomes., Primary Funding Source: The Clinical and Translational Science Collaborative of Cleveland and National Institutes of Health.

Background: Evidence on the effects of neighborhood socioeconomic disadvantage on dementia risk in racially and ethically diverse populations is limited. Our objective was to evaluate the relative extent to which neighborhood disadvantage accounts for racial/ethnic variation in dementia incidence rates. Secondarily, we evaluated the spatial relationship between neighborhood disadvantage and dementia risk. Methods: In this retrospective study using electronic health records (EHR) at two regional health systems in Northeast Ohio, participants included 253,421 patients aged >60 years who had an outpatient primary care visit between January 1, 2005 and December 31, 2015. The date of the first qualifying visit served as the study baseline. Cumulative incidence of composite dementia outcome, defined as EHR‐documented dementia diagnosis or dementia‐related death, stratified by neighborhood socioeconomic deprivation (as measured by Area Deprivation Index) was determined by competing‐risk regression analysis, with non‐dementia‐related death as the competing risk. Fine‐Gray sub‐distribution hazard ratios were determined for neighborhood socioeconomic deprivation, race/ethnicity, and clinical risk factors. The degree to which neighborhood socioeconomic position accounted for racial/ethnic disparities in the incidence of composite dementia outcome was evaluated via mediation analysis with Poisson rate models. Results: Increasing neighborhood disadvantage was associated with increased risk of EHR‐documented dementia diagnosis or dementia‐related death (most vs. least disadvantaged ADI quintile HR = 1.76, 95% confidence interval = 1.69–1.84) after adjusting for age and sex. The effect of neighborhood disadvantage on this composite dementia outcome remained after accounting for known medical risk factors of dementia. Mediation analysis indicated that neighborhood disadvantage accounted for 34% and 29% of the elevated risk for composite dementia outcome in Hispanic and Black patients compared to White patients, respectively. Conclusion: Neighborhood disadvantage is related to the risk of EHR‐documented dementia diagnosis or dementia‐related death and accounts for a portion of racial/ethnic differences in dementia burden, even after adjustment for clinically important confounders. [ABSTRACT FROM AUTHOR]

Since its development, Singh's 2003 Area Deprivation Index (ADI) has been routinely used by researchers to measure a global construct of neighborhood socioeconomic deprivation and to investigate how living in neighborhoods of different levels of socioeconomic deprivation affects individuals' health. We empirically tested the ADI's dimensionality, using 2013–2017 American Community Survey tract-level estimates (N = 73,056), and the stability of its performance across time and place. Factor analysis findings illuminated three distinct dimensions, the ADI-3, consisting of neighborhood financial strength, economic hardship and inequality, and educational attainment. The prior-assumed unidimensional ADI measure fails standard tests of construct validity. Findings from multigroup structural equation modeling across 2009 and 2017 and between New York and Minnesota suggest that the ADI performs with only partial stability across time and place. In order to most precisely understand the complex role of neighborhood socioeconomic position in health, public health researchers must integrate construct-valid and regionally and temporally relevant measures. [ABSTRACT FROM AUTHOR]