RESUMO
BACKGROUND: Several factors can contribute to the development of postpartum depression (PPD) and negatively affect mothers' mental and physical well-being. The objective of this study was to determine the relationship between fatigue, sleep quality, resilience, and the risk of PPD development. METHODS: A cross-sectional study was conducted using an online questionnaire distributed to mothers during their postpartum period. The risk of PPD was assessed using the Edinburgh Postnatal Depression Scale (EPDS), postpartum fatigue (PPF) was assessed using the Fatigue Severity Scale (FSS), sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and resilience was assessed using the Brief Resilience Scale (BRS). The Pearson correlation coefficient was calculated to determine the relationship between the study variables. Simple and multiple linear regression analyses were performed to explain the contributions of PPF, sleep quality, and resilience as independent predictors of PPD development. RESULTS: A total of 1409 postpartum women were included in the analysis, with 75% of the participants reporting a risk of PPD, 61% reporting PPF, 97% reporting having sleep problems, and 36% being in the "low resilience level" category. In terms of correlations, the scores of FSS and the PSQI showed moderate positive relationships with the EPDS scores (r = 0.344 and r = 0.447, respectively, p = .000). The BRS scores were negatively associated with the EPDS scores (r = -0.530, p = 0.000). Fatigue, sleep quality, and resilience were predictors of depressive symptoms (ß = 0.127, ß = 0.262, and ß = -0.393, respectively, R2 = 0.37, p = 0.000). The association remained significant in the regression model after adjusting for mother's age, mother's BMI, child's age, smoking status, full-term pregnancy, having a chronic disease, and taking anti-depressant. CONCLUSIONS: Mothers with higher levels of fatigue, poor sleep quality, and low resilience levels were at high risk of developing PPD. Healthcare providers should identify these factors and thus set better rehabilitation goals to improve overall maternal health.
