Intimate Partner Violence Against Women Before, During, and After Pregnancy: A Meta-Analysis.
Xiao-Yan ChenCamilla Kin Ming LoQiqi ChenShuling GaoFrederick K HoDouglas Austin BrownridgeWing Cheong LeungPatrick IpDouglas A BrownridgePublished in: Trauma, violence & abuse (2024)
Intimate partner violence (IPV) against pregnant women negatively impacts women's and infants' health. Yet inconsistent results have been found regarding whether pregnancy increases or decreases the risk of IPV. To answer this question, we systematically searched for studies that provided data on IPV against women before pregnancy, during pregnancy, and after childbirth. Nineteen studies met our selection criteria. We meta-analyzed the nineteen studies for the pooled prevalence of IPV across the three periods and examined study characteristics that moderate the prevalence. Results showed the pooled prevalence estimates of IPV were 21.2% before pregnancy, 12.8% during pregnancy and 14.7% after childbirth. Although these findings suggest a reduction in IPV during pregnancy, our closer evaluation of the prevalence of IPV after childbirth revealed that the reduction does not appear to persist. The prevalence of IPV increased from 12.8% within the first year after childbirth to 24.0% beyond the first year. Taken together, we should not assume pregnancy protects women from IPV, as IPV tends to persist across a longer-term period. Future studies are needed to investigate if IPV transits into other less obvious types of violence during pregnancy. Moderator analyses showed the prevalence estimates significantly varied across countries by income levels and regions.
Keyphrases
- intimate partner violence
- pregnancy outcomes
- risk factors
- pregnant women
- polycystic ovary syndrome
- preterm birth
- public health
- mental health
- healthcare
- type diabetes
- randomized controlled trial
- case control
- physical activity
- preterm infants
- machine learning
- insulin resistance
- risk assessment
- single cell
- metabolic syndrome
- breast cancer risk
- cervical cancer screening
- health information
- deep learning