Structural racism and racial health disparities at the state level: A latent variable approach.

Introduction Structural racism is increasingly being recognized as a fundamental cause of racial health disparities. We used a novel measure of structural racism at the state level to examine the relationship between structural racism and disparities in death rates from firearm homicide, infant mortality, HIV, diabetes, stroke, hypertension, asthma, and kidney disease between non-Hispanic Black and non-Hispanic White people in the United States. Methods We used confirmatory factor analysis to measure the latent construct of structural racism for all 50 states. The model included seven indicators across the structural racism domains of residential segregation, economic status/employment, education, incarceration, political participation and representation, environmental racism, and racial equity inclusion. Weights for each of the indicators were determined by examining alternative models and selecting the model with the best fit statistics. The resulting factor scores, representing the level of structural racism in each state across the seven domains, were then used as predictor variables in a series of linear regressions with the ratio of Black to White death rates for each health outcome as the dependent variables. Results We found significant relationships between higher levels of the latent structural racism measure and greater disparities between non-Hispanic Black and non-Hispanic White people in age-adjusted death rates for firearm homicide, infant mortality, HIV, asthma, and obesity. The magnitude of this relationship was greatest for firearm homicide, with each one standard deviation increase in a state's structural racism factor score being associated with an increase of 4.54 (95% CI, 2.91-6.17) in that state's Black-White firearm homicide rate ratio. Conclusions This research provides further evidence that structural racism is a fundamental cause of racial health disparities and that to repair these inequities, macro-level changes in societal structures, institutions, resource allocation, representation, and power will be necessary.

Using a Latent Variable Method to Develop a Composite, Multidimensional Measure of Structural Racism at the City Level.

INTRODUCTION: Although structural racism is strongly related to racial health disparities, we are not aware of any composite, multidimensional measure of structural racism at the city level in the United States. However, many of the policies, programs, and institutions that create and maintain structural racism are located at the city level. To expand upon previous research, this paper uses a novel measure to measure structural racism at the city level for the non-Hispanic Black population. METHODS: We used confirmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status. We generated factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each city. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. RESULTS: There were profound differences in the magnitude of structural racism across cities. There were also striking differences in the magnitude of the racial disparity in firearm homicide across cities. Structural racism was a significant predictor of the magnitude of these racial disparities in firearm homicide. Each one standard deviation increase in the structural racism factor score increased the firearm homicide rate ratio by a factor of approximately 1.2 (95% confidence interval, 1.1-1.3). CONCLUSIONS: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.

Measuring Structural Racism and Its Association with Racial Disparities in Firearm Homicide.

INTRODUCTION: Structural racism is strongly related to racial health disparities. However, surprisingly few studies have developed empirical tools to measure structural racism. In addition, the few measures that have been employed have only considered structural racism at the neighborhood level. To expand upon previous studies, this paper uses a novel measure to measure structural racism at the county level for the non-Hispanic Black population. METHODS: We used confirmatory factor analysis to create a model to measure the latent construct of structural racism for 1181 US counties. The model included five indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status/wealth. Structural equation modeling and factor analysis were used to generate factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each county. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. RESULTS: Our calculations revealed striking geographic differences across counties in the magnitude of structural racism, with the highest values generally being observed in the Midwest and Northeast. Structural racism was significantly associated with higher Black firearm homicide rates, lower White homicide rates, and a higher Black-White racial disparity in firearm homicide. CONCLUSIONS: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the county level.

Public Interest in COVID-19 Therapeutics for High-Risk Populations During the Omicron Era: A Google Trends Analysis.

Therapies for COVID-19 prevention or treatment continue to play a significant role for individuals who are not able to mount an adequate immune response after COVID-19 vaccination and/or in patients who are at high-risk for severe outcomes of COVID-19 infection. As these modalities have become more available, it is important to assess the public's interest in these agents to ensure both patients and physicians are aware of the therapeutics available to them. Google Trends is a freely available tool that researchers can use for monitoring public interest by analyzing trends in search queries during disease outbreaks. In this descriptive study, we used Google Trends to investigate the public interest in two COVID-19 therapeutics which received Food and Drug Administration (FDA) emergency use authorization in December 2021: Paxlovid, an antiviral medication used for COVID-19 treatment, and Evusheld, a combination of two monoclonal antibodies against COVID-19 used for COVID-19 prophylaxis. We analyzed search queries in the first half of 2022. Our analysis included search queries that include ''Paxlovid'', ''Evusheld'', ''COVID treatment'' and ''COVID prophylaxis'' at the national and state levels in the US. We found that while the number of COVID-19 cases rose during the period of interest, Evusheld searches remained stagnant despite a concurrent increase in Paxlovid searches. These findings potentially represent low public interest or awareness about Evusheld, which can be addressed through public health initiatives to ensure improved distribution.

Functional Implications of miR-19 in the Migration of Newborn Neurons in the Adult Brain.

Altered microRNA profiles have been implicated in human brain disorders. However, the functional contribution of individual microRNAs to neuronal development and function is largely unknown. Here, we report biological functions for miR-19 in adult neurogenesis. We determined that miR-19 is enriched in neural progenitor cells (NPCs) and downregulated during neuronal development in the adult hippocampus. By manipulating miR-19 in NPCs for gain- and loss-of-function studies, we discovered that miR-19 regulates cell migration by directly targeting Rapgef2. Concordantly, dysregulation of miR-19 in NPCs alters the positioning of newborn neurons in the adult brain. Furthermore, we found abnormal expression of miR-19 in human NPCs generated from schizophrenic patient-derived induced pluripotent stem cells (iPSCs) that have been described as displaying aberrant migration. Our study demonstrates the significance of posttranscriptional gene regulation by miR-19 in preventing the irregular migration of adult-born neurons that may contribute to the etiology of schizophrenia.