Citation

Goin DE, Rudolph KE, Gomez AM, Ahern J. Am. J. Epidemiol. 2020; ePub(ePub): ePub.

Affiliation

Division of Epidemiology & Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, California.

Copyright

(Copyright © 2020, Oxford University Press)

DOI

10.1093/aje/kwaa046

PMID

32219366

Abstract

Firearm violence may indirectly affect health among pregnant women living in neighborhoods where it is endemic. We used birth, death, emergency department, and hospitalization data from California from 2007-2011 to estimate the association between living in a neighborhood with high firearm violence and preterm delivery, and assessed whether there was mediation by diagnoses of pregnancy complications and health behaviors during pregnancy. We used an ensemble machine learning algorithm to predict the propensity for neighborhoods to be classified as high firearm violence. Risk differences (RD) for the total effect and stochastic direct and indirect effects were estimated using targeted maximum likelihood. Residence in high violence neighborhoods was associated with higher prevalence of preterm birth [RD = 0.46 (95% CI: 0.13, 0.80)], infections [RD = 1.34 (95% CI: -0.17, 2.86)], asthma [RD = 0.76 (95% CI: 0.03, 1.48)], and substance use [RD=0.74 (95% CI: 0.00, 1.47)]. The largest indirect effects between violence and preterm birth were observed for infection [0.04 (95% CI: 0.00, 0.08)] and substance use [0.04 (95% CI: 0.01, 0.06)]. Firearm violence was associated with risk of preterm delivery, and this association was partially mediated by infection and substance use.

© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Language: en

Keywords

causal mediation analysis; firearm violence; pregnancy complications; preterm birth