title: Collateral Damage: The Health Effects of Invasive Police Encounters in New York City.
abstract: The health effects of police surveillance practices for the community at-large are unknown. Using microlevel health data from the 2009-2012 New York City Community Health Survey (NYC-CHS) nested within mesolevel data from the 2009-2012 NYC Stop, Question, and Frisk (NYC-SQF) dataset, this study evaluates contextual and ethnoracially variant associations between invasive aspects of pedestrian stops and multiple dimensions of poor health. Results reveal that living in neighborhoods where pedestrian stops are more likely to become invasive is associated with worse health. Living in neighborhoods where stops are more likely to result in frisking show the most consistent negative associations. More limited deleterious effects can be attributed to living in neighborhoods where stops are more likely to involve use of force or in neighborhoods with larger ethnoracial disparities in frisking or use of force. However, the health effects of pedestrian stops vary by ethnoracial group in complex ways. For instance, minorities who live in neighborhoods with a wider ethno racial disparity in police behavior have poorer health outcomes in most respects, but blacks have lower odds of diabetes when they live in neighborhoods where they face a higher risk that a stop will involve use of force by police than do whites. The findings suggest that the consequences of the institutionalization of the carceral state are far-reaching.
authors.affiliation: Emory University, Atlanta, GA, USA. abigail.a.sewell@emory.edu.|University of Pennsylvania, Philadelphia, PA, USA. abigail.a.sewell@emory.edu.
authors.forename: Abigail A
authors.identifier: http://orcid.org/0000-0002-7146-3657
authors.initials: AA
authors.lastname: Sewell
authors.affiliation: Emory University, Atlanta, GA, USA.
authors.forename: Kevin A
authors.initials: KA
authors.lastname: Jefferson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D044383:Black People / Q000706:statistics & numerical data; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D035846:Law Enforcement / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009519:New York City / Q000453:epidemiology; D016495:Police / Q000706:statistics & numerical data*; D044469:Racial Groups / Q000706:statistics & numerical data*; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D014504:Urban Health / Q000706:statistics & numerical data*; D044465:White People / Q000706:statistics & numerical data; D055815:Young Adult; D001741:Black or African American
keywords: Ethnicity; Health; Health disparities; Neighborhoods; New York City; Police; Race