60 research outputs found

    Racism and the Political Economy of COVID-19: Will We Continue to Resurrect the Past?

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    COVID-19 is not spreading over a level playing field; structural racism is embedded within the fabric of American culture, infrastructure investments, and public policy, and fundamentally drives inequities. The same racism that has driven the systematic dismantling of the American social safety-net has also created the policy recipe for American structural vulnerability to the impacts of this and other pandemics. The Bronx provides an important case study for investigating the historical roots of structural inequities showcased by this pandemic; current lived experiences of Bronx residents are rooted in the racialized dismantling of New York City’s public infrastructure and systematic disinvestment. The story of the Bronx is repeating itself, only this time with a novel virus. In order to address the root causes of inequities in cases and deaths due to COVID-19, we need to focus not just on restarting the economy, but on reimagining the economy, divesting of systems rooted in racism and the devaluation of Black and Brown lives

    Structural Racism and Severe Maternal Morbidity in New York State

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    ABSTRACT Objective: We examined the association between county-level structural racism indicators and the odds of severe maternal morbidity (SMM) in New York State. Design: We merged individual-level hospitalization data from the New York State Department of Health Statewide Planning and Research Cooperative System (SPARCS) with county-level data from the American Community Survey and the Vera Institute of Justice from 2011 to 2013 (n = 244 854). Structural racism in each county included in our sample was constructed as the racial inequity (ratio of black to white population) in female educational attainment, female employment, and incarceration.ReSulT S: Multilevel logistic regression analysis estimated the association between each of these structural racism indicators and SMM, accounting for individual- and hospital-level characteristics and clustering in facilities. In the models adjusted for individual- and hospital-level factors, county-level racial inequity in female educational attainment was associated with small but statistically significant higher odds of SMM (odds ratio [OR] = 1.17, 95% confidence interval [CI] = 1.47, 1.85). County-level structural racism indicators of female employment inequity and incarceration inequity were not statistically significant. Interaction terms examining potential effect measure modification by race with each structural racism indicator also indicated no statistical difference. Conclusions: Studies of maternal disparities should consider multiple dimensions of structural racism as a contributing cause to SMM and as an additional area for potential intervention

    Housing stability and diabetes among people living in New York city public housing

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    Public housing provides affordable housing and, potentially, housing stability for low-income families. Housing stability may be associated with lower incidence or prevalence and better management of a range of health conditions through many mechanisms. We aimed to test the hypotheses that public housing residency is associated with both housing stability and reduced risk of diabetes incidence, and the relationship between public housing and diabetes risk varies by levels of housing stability. Using 2004-16 World Trade Center Health Registry data, we compared outcomes (housing stability measured by sequence analysis of addresses, self-reported diabetes diagnoses) between 730 New York City public housing residents without prevalent diabetes at baseline and 730 propensity score-matched non-public housing residents. Sequence analysis found 3 mobility patterns among all 1460 enrollees, including stable housing (65%), limited mobility (27%), and unstable housing patterns (8%). Public housing residency was associated with stable housing over 12 years. Diabetes risk was not associated with public housing residency; however, among those experiencing housing instability, a higher risk of diabetes was found among public housing versus non-public housing residents. Of those stably housed, the association remained insignificant. These findings provide important evidence for a health benefit of public housing via housing stability among people living in public housing

    Carceral epidemiology: mass incarceration and structural racism during the COVID-19 pandemic

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    The COVID-19 pandemic and the ongoing epidemic of mass incarceration are closely intertwined, as COVID-19 entered US prisons and jails at astounding rates. Although observers warned of the swiftness with which COVID-19 could devastate people who are held and work in prisons and jails, their warnings were not heeded quickly enough. Incarcerated populations were deprioritised, and COVID-19 infected and killed those in jails and prisons at rates that outpaced the rates among the general population. The COVID-19 pandemic highlighted what has been long-known: mass incarceration is a key component of structural racism that creates and exacerbates health inequities. It is imperative that the public health, particularly epidemiology, public policy, advocacy, and medical communities, are catalysed by the COVID-19 pandemic to drastically rethink the USA's criminal legal system and the public health emergency that it has created and to push for progressive reform

    Shouting into the Wind: Being a Black Epidemiologist in 2020

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    Invited Commentary: What Social Epidemiology Brings to the Table-Reconciling Social Epidemiology and Causal Inference

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    In response to the Galea and Hernan article, "Win-Win: Reconciling Social Epidemiology and Causal Inference" (Am J Epidemiol. 2020;189(3):167-170), we offer a definition of social epidemiology. We then argue that methodological challenges most salient to social epidemiology have not been adequately addressed in quantitative causal inference, that identifying causes is a worthy scientific goal, and that quantitative causal inference can learn from social epidemiology's methodological innovations. Finally, we make 3 recommendations for quantitative causal inference
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