This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.
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http://dx.doi.org/10.1073/pnas.2402547121 | DOI Listing |
Br J Hosp Med (Lond)
December 2024
School of Nursing and Midwifery, Queen's University Belfast, Medical Biology Centre, Belfast, UK.
Health inequities exist in cardiovascular care and outcomes, especially among women, older people, individuals from racial and ethnic minorities, lower income and rural communities often those most vulnerable to adverse health outcomes. Such diverse groups form most of the patient population but they are rarely reflected in the composition of the cardiovascular care workforce. Yet a diverse cardiovascular health care workforce can enhance access to care, reduce health disparities and inequities, and improve quality of care and research for such underserved populations.
View Article and Find Full Text PDFAm J Prev Med
January 2025
Surveillance and Health Equity Science, American Cancer Society, Atlanta, Georgia.
Introduction: This study aimed to examine the association of county-level racial and economic residential segregation with mortality rates in the U.S. between 2018 and 2022.
View Article and Find Full Text PDFSci Adv
January 2025
Department of Political Science, George Washington University, Washington, DC 20052, USA.
In this paper, we examine whether mayors' partisan affiliations lead to differences in crime and policing. We use a large new dataset on mayoral elections and three different modern causal inference research designs (a regression discontinuity design centered around close elections and two robust difference-in-differences methods) to determine the causal effect of mayoral partisanship on crime, arrests, and racial differences in arrest patterns in medium and large US cities. We find no evidence that mayoral partisanship affects police employment or expenditures, police force or leadership demographics, overall crime rates, or numbers of arrests.
View Article and Find Full Text PDFObesity (Silver Spring)
January 2025
Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA.
Objective: The objective of this study was to evaluate potential sources of heterogeneity in the effect of calorie labeling on fast-food purchases among restaurants located in areas with different neighborhood characteristics.
Methods: In a quasi-experimental design, using transaction data from 2329 Taco Bell restaurants across the United States between 2008 and 2014, we estimated the relationships of census tract-level income, racial and ethnic composition, and urbanicity with the impacts of calorie labeling on calories purchased per transaction.
Results: Calorie labeling led to small, absolute reductions in calories purchased across all population subgroups, ranging between -9.
J Urban Health
January 2025
Department of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1057, New York, NY, 10029, USA.
Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging.
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