Back

Violence during pregnancy and mental health outcomes among women experiencing violence in rural Bangladesh

Mumu, R. T.; Shaikh, M. P.; Ayan, S. S.

2025-08-05 epidemiology
10.1101/2025.08.02.25332863 medRxiv
Show abstract

Violence during pregnancy is a significant public health issue, associated with serious mental health consequences, including antenatal depression and suicidal ideation. Although several studies in Bangladesh examined violence against women, there is a lack of research addressing its prevalence among pregnant women and the associated psychological outcomes. This study aims to assess the prevalence of violence among pregnant women in rural Bangladesh and the prevalence of depression and suicidal ideation among affected individuals. This study is a secondary analysis of cross-sectional data collected from January 8 to January 30, 2024, in a rural subdistrict in southern Bangladesh, involving 354 pregnant women. Data were collected using the Edinburgh Postnatal Depression Scale (EPDS) and analyzed with STATA version 17. The prevalence of domestic violence (DV), lifetime intimate partner violence (IPV), and IPV during pregnancy were 5.9% (n = 21; 95% CI: 3.7%-8.9%), 5.4% (n = 19; 95% CI: 3.3%-8.3%), and 9.9% (n = 35; 95% CI: 7.0%-13.5%), respectively. Among women exposed to DV, 66.7% (n = 14; 95% CI: 42.6%-84.3%) reported antenatal depression. Similarly, depression was reported by 68.4% (n = 13; 95% CI: 42.7%-86.3%) of those with a history of lifetime IPV and 42.9% (n = 15; 95% CI: 27.1%-60.3%) of those experiencing IPV during pregnancy. Suicidal ideation was present in 14.3% (n = 3; 95% CI: 4.2%-38.7%) of DV victims, 5.3% (n = 1; 95% CI: 0.6%-33.8%) of lifetime IPV victims, and 5.7% (n = 2; 95% CI: 1.3%-21.4%) of those experiencing IPV during their current pregnancy. These findings reveal a concerning prevalence of violence against pregnant women and associated mental health issues. Urgent targeted interventions-including policy reforms, health education, and community-based awareness initiatives- are essential to address this critical public health challenge.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.