To explore socio-behavioral, clinical, and imaging findings associated with antepartum intimate partner violence (IPV) and aid in risk stratification of at-risk individuals.
Methods:
We analyzed electronic medical records during indexed pregnancies for 108 pregnant patients who self-reported antepartum IPV (cases) and 106 age-matched pregnant patients who did not self-report antepartum IPV (controls). Sociodemographic, clinical, and radiology data were analyzed via chi-squared and Fisher’s exact tests with p < 0.05 as the threshold for significance. Stepwise logistic regression was applied to derive a risk prediction model.
Results:
The proportion of cases reporting emotional IPV (76% vs. 52%) and/or physical IPV (45% vs. 31%) during pregnancy significantly increased from prior to pregnancy. Cases were significantly more likely to report prepregnancy substance use (odds ratio [OR] = 2.60; 95% confidence interval [CI]: 1.13–5.98), sexually transmitted infections (OR = 3.48; 95%CI: 1.64–7.37), abortion (OR = 3.17; 95%CI: 1.79, 5.59), and preterm birth (OR = 5.97; 95%CI: 1.69–21.15). During pregnancy, cases were more likely to report unstable housing (OR = 5.26; 95%CI: 2.67–10.36), multigravidity (OR = 2.83; 95%CI: 1.44–5.58), multiparity (OR = 3.75; 95%CI: 1.72–8.20), anxiety (OR = 3.35; 95%CI: 1.85–6.08), depression (OR = 5.58; 95%CI: 3.07–10.16), substance use (OR = 2.92; 95%CI: 1.28–6.65), urinary tract infection (UTI) (OR = 3.26; 95%CI: 1.14–9.32), intrauterine growth restriction (OR = 10.71; 95%CI: 1.35–85.25), and cesarean delivery (OR = 2.25; 95%CI: 1.26–4.02). Cases had significantly more OBGYN abnormalities on imaging and canceled more radiological studies (OR = 5.31). Logistic regression found housing status, sexually transmitted infection history, preterm delivery history, abortion history, depression, and antepartum UTI predictive of antepartum IPV. The risk prediction model achieved good calibration with an area under the curve of 0.79.
Conclusions:
This study identifies significant disparities among patients experiencing antepartum IPV, and our proposed risk prediction model can inform risk assessment in this setting.
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