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Badiya PK, Siddabattuni S, Dey D, Javvaji SK, Nayak SP, Hiremath AC, Upadhyaya R, Madras L, Nalam RL, Prabhakar Y, Vaitheswaran S, Manjjuri AR, Jk KK, Subramaniyan M, Raghunatha Sarma R, Ramamurthy SS. Identification of clinical and psychosocial characteristics associated with perinatal depression in the south Indian population. Gen Hosp Psychiatry 2020; 66:161-170. [PMID: 32871347 DOI: 10.1016/j.genhosppsych.2020.08.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 08/06/2020] [Accepted: 08/06/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Longitudinal perinatal depression (PND) data is sparsely available in the Indian population. We have employed Edinburgh Postnatal Depression Scale (EPDS) to assess the prevalence and identify characteristics associated with PND in the south Indian population. PND was assessed longitudinally using EPDS scores with traditional cut-off approach as well as a novel method of latent class mixture modeling (LCMM). The LCMM method, to the best of our knowledge, has been used for the first time in the Indian population. METHODS Three hundred and forty seven women, predominantly from economically-weaker sections of rural and urban South India were longitudinally assessed for antenatal depression (AD) and postnatal depression (PD) using EPDS cutoff-scores ≥13 and ≥10, respectively. Uni/multivariable analyses were used to identify PND associated characteristics. LCMM was then implemented, followed by risk characteristics identification. RESULTS PND prevalence from traditional approach was 24.50 % (12.68 % AD; 18.16% PD). Characteristics associated with PND were urban-site and recent adverse life events. Irregular menstrual history and chronic health issues were associated with AD and PD, respectively. Three distinct PND trajectories were observed from LCMM-analysis: low-risk (76.08%), medium-risk (19.89%) and high-risk (4.04%). Urban-site, recent adverse life events, irregular menstrual history and pregnancy complications were associated with medium-risk/high-risk trajectories. LIMITATIONS EPDS is a screening tool and not a diagnostic tool for depression. Since the study population included women from economically-weaker sections, the results need verification in other socio-economic groups. CONCLUSIONS Both the traditional cut-off-based approach and LCMM provided very similar conclusions regarding the prevalence of PND and characteristics associated with it. Higher PND prevalence was observed in urban women compared to rural women. In low-income countries, identifying risk characteristics associated with PND is a critical component in designing prevention strategies for PND related conditions because of the limited access to mental health resources.
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Affiliation(s)
- Pradeep Kumar Badiya
- STAR Laboratory, Department of Chemistry, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India
| | - Sasidhar Siddabattuni
- STAR Laboratory, Department of Chemistry, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India
| | | | - Sai Kiran Javvaji
- Department of Laboratory Medicine & Cardiology, Sri Sathya Sai Institute of Higher Medical Sciences, Whitefield, Bangalore 560066, India
| | - Sai Prasad Nayak
- Department of Chemistry, Sri Sathya Sai Institute of Higher Learning, Brindavan Campus, Kadugodi, Bangalore 560067, Karnataka, India
| | - Akkamahadevi C Hiremath
- Department of Obstetrics and Gynecology, Sri Sathya Sai General Hospital, Whitefield, Bangalore 560066, India
| | - Rajani Upadhyaya
- Department of Obstetrics and Gynecology, Sri Sathya Sai General Hospital, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India
| | - Loukya Madras
- Department of Obstetrics and Gynecology, Sri Sathya Sai General Hospital, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India
| | - Raj Lakshmi Nalam
- Department of Obstetrics and Gynecology, Sri Sathya Sai General Hospital, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India
| | - Yendluri Prabhakar
- Department of Psychiatry, Government medical college/Government general hospital, Anantapur 515001, Andhra Pradesh, India
| | - Sridhar Vaitheswaran
- Dementia Care, Schizophrenia Research Foundation, Chennai 600101, Tamil Nadu, India
| | - A R Manjjuri
- College of Nursing, Sri Sathya Sai Institute of Higher Medical Sciences, Whitefield, Bangalore 560066, India
| | - Kiran Kumar Jk
- Department of Chemistry, Sri Sathya Sai Institute of Higher Learning, Brindavan Campus, Kadugodi, Bangalore 560067, Karnataka, India
| | - M Subramaniyan
- Department of Telemedicine & Hospital Management Information Systems, Sri Sathya Sai Institute of Higher Medical Sciences, Whitefield, 560066 Bangalore, India
| | - R Raghunatha Sarma
- Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India
| | - Sai Sathish Ramamurthy
- STAR Laboratory, Department of Chemistry, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, 515134 Anantapur, Andhra Pradesh, India.
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