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 having a high level of firearm violence. Risk differences 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 (risk difference (RD) = 0.46, 95% confidence interval (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 for the association between violence and preterm birth were observed for infection (stochastic indirect effect = 0.04, 95% CI: 0.00, 0.08) and substance use (stochastic indirect effect = 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.