RESUMO
INTRODUCTION: Postpartum depression (PPD) represents a considerable health problem affecting women and their families. The aims of this study were to: (a) compare female patients with PPD to normal controls with regard to some biopsychosocial variables, (b) correlate between the severity of PPD and some clinical and biological variables, and (c) to predict some risk factors for PPD. METHOD: Sixty female patients with PPD were compared with 60 healthy postpartum females (control group). Patient and controls were subjected to: (1) a complete psychiatric and obstetric examination, (2) psychometric studies using the Edinburgh Postnatal Depression Scale, Fahmy and El-Sherbini's Social Classification Scale for Egyptian socioeconomic classification and Horowitz et al's Impact of Event Scale, (3) quantities of thyroid hormone (T3), cortisol hormone, and estrogen were assessed. RESULTS: There were high statistical differences between PPD females and controls as regard psychosocial stressors, level of (estradiol, thyroxin [T3], and cortisol), marital status, residence, parity, method of delivery, complicated puerperium, positive history of premenstrual tension syndrome and baby variables (eg, unwelcomed, with a negative attitude of parents toward the baby, underweight, female, artificially feeding, unhealthy baby). While there were moderate statistical differences in attitude toward spouse and social support and mild statistical difference in socioeconomic status between them. Severity of depression is positively highly correlated with onset of depression, psychosocial stress, levels of T3 and cortisol. However, severity of depression is negatively high when correlated with socioeconomic status. Stepwise linear regression indicated that PPD was significantly predicted by social support, socioeconomic status, feeding of baby, and prior psychiatric problems. CONCLUSION: Many factors may lead to development of PPD. These factors include some psychosocial, socioeconomic, obstetric, and hormonal variables. Early detection of these factors could help in prediction of the development of PPD.
