Perinatal depression in Nigeria: perspectives of women, family caregivers and health care providers

Abstract

Abstract Background Perinatal maternal depression is common and undertreated in many sub-Saharan African countries, including Nigeria. While culture shapes the social determinants and expression of depressive symptoms, there is a dearth of research investigating these processes in African contexts. Methods To address this gap, we conducted in-depth interviews with 14 women with perinatal depression, 14 of their family caregivers and 11 health providers, using the McGill Illness Narrative Interview as part of a larger trial of a stepped-care intervention. Interpretation of themes was guided by cultural constructivist and critical anthropological perspectives that situate perinatal depression in its complexity as a disorder that is embedded in webs of social relations and embodied practices. Results Study respondents used idioms of distress that identified perinatal conditions that consist of somatic, affective, cognitive and behavior symptoms found in depressive disorders. Respondents viewed mental health problems in the perinatal period as tied to sociomoral concerns over gender roles and women’s position within the household. Conflict between women’s effort to be assertive to address interpersonal problems, while needing to be seen as non-aggressive contributed to their distress. Causal explanations for depression included husband’s lack of care, family problems, “spiritual attack”, having a female child when a male child was desired, and not resting sufficiently after childbirth. Guilt about breaching social norms for women’s conduct contributed to self blame, and feelings of shame. Conclusions Clinical assessment and interventions as well as public health prevention strategies for perinatal depression in global mental health need to consider local social contexts and meanings of depression, which can be explored with narrative-based methods.

Keywords

• Nigeria
• Perinatal depression
• Qualitative interviews
• Illness explanatory models