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  • Author: L. Gagliardi x
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Background: The Edinburgh Postnatal Depression Scale (EPDS) is a widely used instrument for screening for postpartum depression, but it might also detect anxiety symptoms.

Objective: To investigate the factor structure of the EPDS administered immediately after delivery and to understand which factors predict a high EPDS score 3 months later.

Methods: A cohort of 594 Italian mothers delivering a healthy baby at Versilia Hospital completed the EPDS at two points in time: 2 days after delivery (T0) and 3 months later (T1) by telephone interview.

Results: EPDS scores were higher at T0 than at T1. Overall, 15.7% of women at 2 days postpartum and 7.6% at 3 months later reported a score >9. The factor analysis of EPDS at T0 indicated a three-factor structure: “depression” (items 7–10), “anxiety” (items 3–6) and “anhedonia” (items 1–2). Anxious symptoms were quantitatively more important than depressive ones (mean 3.9 vs. 1.2) but tended to spontaneously ameliorate at T1, whereas total EPDS score at T1 was better predicted by depressive symptoms at T0 (discriminative ability 0.75 vs. 0.68).

Conclusions: This study suggests that EPDS subscales immediately after delivery help understand the spectrum of maternal postpartum psychological problems. Anxious symptoms immediately after delivery are frequent but transient, linked probably to maternity blues or atypical depression, whereas the presence of depressive symptomatology at T0 suggests higher risk of later depressive disorders.


The aim of this study was to verify the power of VO2max, peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO2max and PTV; 2) a constant submaximal run at 12 km·h−1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO2max, PTV and RE) and adjusted variables (VO2max 0.72, PTV0.72 and RE0.60) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO2max. Significant correlations (p < 0.01) were found between 10 km running time and adjusted and unadjusted RE and PTV, providing models with effect size > 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV0.72 and RE0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.