EXPLORING PSYCHOSOCIAL, BIOLOGICAL, AND ENVIRONMENTAL FACTORS CONTRIBUTING TO POSTPARTUM DEPRESSION AMONG WOMEN IN URBAN AND RURAL COMMUNITIES
DOI:
https://doi.org/10.71000/tjbd2069Keywords:
Depression, Female, Mental Health, Postnatal Care, Postpartum Period, Pregnancy, Psychosocial FactorsAbstract
Background: Postpartum depression (PPD) is a significant yet underrecognized public health issue that adversely affects maternal mental health and child development. The interplay of psychosocial, biological, and environmental factors contributes to its onset, particularly in resource-constrained settings like South Punjab.
Objective: To analyze key psychosocial, biological, and environmental factors contributing to postpartum depression among women in urban and rural communities of South Punjab, and to identify preventive strategies for improving maternal mental health outcomes.
Methods: A descriptive study was conducted over eight months among 384 postpartum women within six months of delivery in South Punjab. Participants were selected using multistage sampling. Data were collected through structured interviews using a pretested questionnaire and the Edinburgh Postnatal Depression Scale (EPDS). Statistical analysis was performed using SPSS version 26. Data were normally distributed; thus, t-tests, chi-square tests, and multivariate logistic regression were applied to explore associations and predictors.
Results: The prevalence of probable postpartum depression (EPDS ≥13) was 41.6%. Higher rates were observed among women with a history of depression (74.2%), low social support (68.5%), unemployment (63.3%), and rural residence (59.6%). Mean EPDS scores were significantly higher in rural women (12.4 ± 4.8) and those with low social support (13.7 ± 5.1). Multivariate analysis confirmed these factors as significant predictors.
Conclusion: Postpartum depression is highly prevalent among mothers in South Punjab, especially in rural areas and among socially unsupported women. Addressing these factors through targeted interventions is essential for improving maternal mental health and overall family well-being.
References
Doyle K. The Impact of Post-Partum Depression on Mothers and their Babies. 2025.
Lazarov HO. Parents’ Experiences With Postpartum Depression and Children’s Neurodevelopment: Alliant International University; 2025.
Rodríguez Muñoz MdlF, Motrico E, Míguez MC, Chaves C, Suso Ribera C, Duque A, et al. Perinatal depression in the Spanish context: Consensus report from the general council of psychology of Spain. 2023.
ACHIENG AL. Breastfeeding Practices and Infant Nutrition Status (6-23 Weeks) of Post-Partum Depressed Mothers in Mama Lucy Kibaki and Mbagathi Hospitals in Nairobi City County: Kenyatta University; 2024.
Dabach M. Effect of Cognitive Behavioral Therapy in the Treatment of Perinatal Anxiety: California Southern University; 2024.
Marowitz AJP, Approach PCAP-C. Assessment and Care at the Onset of Labor. 2023:443.
Mewara MD, Yadav KJJoNS. Social Factors Influencing Mental Health: Insights, Preventive Strategies, and Policy Recommendations. 2025;14(4s).
Alanazi AF. " Maternal Mental Health: Understanding and Addressing Postpartum Depression.
Vora V, Kanyal S, Chauhan A, Agarwal P, Sethi YJIJoG, Obstetrics. Cultural perceptions and social determinants of health in perinatal mental health: An obstetric‐psychiatric perspective. 2025.
Gupta A, Pajai S, Gupta A, Thakur AS, Muneeba S, Batra N, et al. In the shadows of motherhood: a comprehensive review of postpartum depression screening and intervention practices. 2024;16(2):e54245.
Modak A, Ronghe V, Gomase KP, Mahakalkar MG, Taksande VJC. A comprehensive review of motherhood and mental health: postpartum mood disorders in focus. 2023;15(9):e46209.
Kirkbride JB, Anglin DM, Colman I, Dykxhoorn J, Jones PB, Patalay P, et al. The social determinants of mental health and disorder: evidence, prevention and recommendations. 2024;23(1):58-90.
Dwivedi YK, Kshetri N, Hughes L, Slade EL, Jeyaraj A, Kar AK, et al. Opinion Paper:“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. 2023;71:102642.
Podell D, English Z, Lacey K, Blattmann A, Dockhorn T, Müller J, et al. Sdxl: Improving latent diffusion models for high-resolution image synthesis. 2023.
Bai J, Bai S, Chu Y, Cui Z, Dang K, Deng X, et al. Qwen technical report. 2023.
Rafailov R, Sharma A, Mitchell E, Manning CD, Ermon S, Finn CJAinips. Direct preference optimization: Your language model is secretly a reward model. 2023;36:53728-41.
Chowdhery A, Narang S, Devlin J, Bosma M, Mishra G, Roberts A, et al. Palm: Scaling language modeling with pathways. 2023;24(240):1-113.
Kirillov A, Mintun E, Ravi N, Mao H, Rolland C, Gustafson L, et al., editors. Segment anything. Proceedings of the IEEE/CVF international conference on computer vision; 2023.
Van Dyck CH, Swanson CJ, Aisen P, Bateman RJ, Chen C, Gee M, et al. Lecanemab in early Alzheimer’s disease. 2023;388(1):9-21.
Peebles W, Xie S, editors. Scalable diffusion models with transformers. Proceedings of the IEEE/CVF international conference on computer vision; 2023.
Liu H, Li C, Li Y, Lee YJ, editors. Improved baselines with visual instruction tuning. Proceedings of the IEEE/CVF conference on computer vision and pattern recognition; 2024.
Wang C-Y, Yeh I-H, Mark Liao H-Y, editors. Yolov9: Learning what you want to learn using programmable gradient information. European conference on computer vision; 2024: Springer.
Abramson J, Adler J, Dunger J, Evans R, Green T, Pritzel A, et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. 2024;630(8016):493-500.
Gu A, Dao T, editors. Mamba: Linear-time sequence modeling with selective state spaces. First Conference on Language Modeling; 2024.
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Copyright (c) 2025 Shakeela Bano, Fizza Shoaib, Fatima Akram Khan, Muhammad Shahroz Khan, Abdul Majid Asad, Rafi Ul Shan, Iqra Arshad (Author)

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