Bangladeshi Women Postpartum Depression Prediction Dataset

This dataset includes 766 postpartum women from Bangladesh and explores the prevalence and risk factors of postpartum depression (PPD). Participants, aged 18–41, were recruited from urban, rural, and hospital outpatient settings within 24 months of childbirth. Data were collected between March and June 2025 at LABAID Diagnostics, Pabna, following ethical guidelines and ensuring anonymity. Mental health was assessed using standardized tools—PHQ-2, PHQ-9, and EPDS—with 40.47% of mothers screening positive for depression during pregnancy.

The dataset includes sociodemographic, economic, family, clinical, obstetric, psychosocial, and neonatal variables. Key features include Age, Residence, Education Level, Marital Status, Occupation before/after latest pregnancy, Monthly Income/Current monthly income, Husband's Education Level, Husband's monthly income, Family type, Number of household members, Relationship with husband/in-laws, Emotional support, Parity, Pregnancy number, Gestation length, Delivery Mode, Pregnancy complications, History of pregnancy loss, Disease before pregnancy, Newborn age/gender, Newborn complications, Breastfeeding status, Sleep and rest patterns, and Emotional changes after childbirth.

The dataset, provided in CSV format, supports research on postpartum depression prediction, risk factor analysis, and explainable AI. It enables modeling of maternal mental health outcomes across social, cultural, and economic factors, and can be used to develop predictive models, clinical decision support tools, and public health interventions.