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Abstract：
UNASSIGNED: Postpartum fatigue (PPF) can impair the physical and mental well-being of women. The aims of this study were to assess the associations between fatigue and maternal health-related variables, specifically, sleep quality, depression symptoms, and resilience, and to explore the moderating role of resilience in the relationships between sleep quality, depression symptoms, and fatigue.
UNASSIGNED: This cross-sectional study used data collected from mothers during the postpartum period via an online platform. PPF was assessed using the Fatigue Severity Scale, whereas sleep quality and depression symptoms were assessed using the Pittsburgh Sleep Quality Index and Edinburgh Postnatal Depression Scale, respectively. The Brief Resilience Scale was used to assess resilience. Simple and multiple binary logistic regression analyses were performed to examine the association of each independent variable with PPF and to determine the most significant predictors of PFF. The data were analyzed using SPSS, and structural equation modeling was performed using AMOS 23. A moderation analysis was performed to explore the moderating role of resilience using the Hayes PROCESS macro.
UNASSIGNED: A total of 1,443 postpartum mothers were included in the analysis. The simple binary logistic regression analysis showed that having chronic disease (odds: 1.52; p = 0.02), mother\'s age (odds: 0.97; p = 0.03), mother\'s body mass index (BMI; odds: 1.03; p = 0.01), depression symptoms (odds: 1.09; p ≤ 0.0001), sleep quality (odds: 1.17; p ≤ 0.0001), and resilience (odds: 0.42; p ≤ 0.0001) all contributed to fatigue during postpartum. Multivariate logistic regression showed that the mother\'s BMI, sleep quality, depression symptoms, and resilience were significant predictors of PPF. Moderation analyses showed that resilience was not a significant moderator between the main effects of sleep quality and fatigue (interaction effect: β = 0.01, p = 0.31, 95% CI: -0.01 to 0.04) or between the main effects of depression symptoms and fatigue during postpartum (interaction effect: β = 0.01, p = 0.82, 95% CI: -0.01 to 0.02).
UNASSIGNED: Given the deleterious effects of PPF on maternal health outcomes, factors associated with PPF should be assessed regularly. In addition to mothers\' BMI, sleep quality, and depression symptoms, resilience could also be a crucial factor in predicting fatigue severity during this critical time for mothers even though it was not a significant moderator among this sample.
UNASSIGNED: This cross-sectional study used data collected from mothers during the postpartum period via an online platform. PPF was assessed using the Fatigue Severity Scale, whereas sleep quality and depression symptoms were assessed using the Pittsburgh Sleep Quality Index and Edinburgh Postnatal Depression Scale, respectively. The Brief Resilience Scale was used to assess resilience. Simple and multiple binary logistic regression analyses were performed to examine the association of each independent variable with PPF and to determine the most significant predictors of PFF. The data were analyzed using SPSS, and structural equation modeling was performed using AMOS 23. A moderation analysis was performed to explore the moderating role of resilience using the Hayes PROCESS macro.
UNASSIGNED: A total of 1,443 postpartum mothers were included in the analysis. The simple binary logistic regression analysis showed that having chronic disease (odds: 1.52; p = 0.02), mother\'s age (odds: 0.97; p = 0.03), mother\'s body mass index (BMI; odds: 1.03; p = 0.01), depression symptoms (odds: 1.09; p ≤ 0.0001), sleep quality (odds: 1.17; p ≤ 0.0001), and resilience (odds: 0.42; p ≤ 0.0001) all contributed to fatigue during postpartum. Multivariate logistic regression showed that the mother\'s BMI, sleep quality, depression symptoms, and resilience were significant predictors of PPF. Moderation analyses showed that resilience was not a significant moderator between the main effects of sleep quality and fatigue (interaction effect: β = 0.01, p = 0.31, 95% CI: -0.01 to 0.04) or between the main effects of depression symptoms and fatigue during postpartum (interaction effect: β = 0.01, p = 0.82, 95% CI: -0.01 to 0.02).
UNASSIGNED: Given the deleterious effects of PPF on maternal health outcomes, factors associated with PPF should be assessed regularly. In addition to mothers\' BMI, sleep quality, and depression symptoms, resilience could also be a crucial factor in predicting fatigue severity during this critical time for mothers even though it was not a significant moderator among this sample.
摘要：
■产后疲劳（PPF）会损害妇女的身心健康。这项研究的目的是评估疲劳和产妇健康相关变量之间的关联。具体来说,睡眠质量,抑郁症状,和韧性，并探讨韧性在睡眠质量关系中的调节作用，抑郁症状,和疲劳。
■这项横断面研究使用了通过在线平台从产后母亲那里收集的数据。PPF使用疲劳严重程度量表进行评估，而睡眠质量和抑郁症状使用匹兹堡睡眠质量指数和爱丁堡产后抑郁量表进行评估，分别。使用简短弹性量表评估弹性。进行了简单和多元二元逻辑回归分析，以检查每个自变量与PPF的关联，并确定PFF的最重要预测因子。使用SPSS对数据进行分析，并使用AMOS23进行结构方程建模。使用Hayes过程宏进行了适度分析，以探讨韧性的调节作用。
■共有1,443名产后母亲被纳入分析。简单二元logistic回归分析显示，患有慢性病（赔率：1.52；p=0.02），母亲的年龄（赔率：0.97；p=0.03），母亲的体重指数（BMI；赔率：1.03；p=0.01），抑郁症状（赔率：1.09；p≤0.0001），睡眠质量（赔率：1.17；p≤0.0001），和弹性（赔率：0.42;p≤0.0001）均导致产后疲劳。多因素logistic回归显示，母亲的BMI，睡眠质量,抑郁症状,和弹性是PPF的重要预测因子。适度分析表明，心理弹性在睡眠质量和疲劳的主要影响之间（交互作用：β=0.01，p=0.31，95％CI：-0.01至0.04）或在抑郁症状和产后疲劳的主要影响之间（交互作用：β=0.01，p=0.82，95％CI：-0.01至0.02）没有显着调节作用。
■鉴于PPF对产妇健康结局的有害影响，与PPF相关的因素应定期评估。除了母亲的BMI，睡眠质量,和抑郁症状，弹性也可能是预测母亲在这一关键时期疲劳严重程度的一个关键因素，尽管它不是该样本中的重要调节因素。
■这项横断面研究使用了通过在线平台从产后母亲那里收集的数据。PPF使用疲劳严重程度量表进行评估，而睡眠质量和抑郁症状使用匹兹堡睡眠质量指数和爱丁堡产后抑郁量表进行评估，分别。使用简短弹性量表评估弹性。进行了简单和多元二元逻辑回归分析，以检查每个自变量与PPF的关联，并确定PFF的最重要预测因子。使用SPSS对数据进行分析，并使用AMOS23进行结构方程建模。使用Hayes过程宏进行了适度分析，以探讨韧性的调节作用。
■共有1,443名产后母亲被纳入分析。简单二元logistic回归分析显示，患有慢性病（赔率：1.52；p=0.02），母亲的年龄（赔率：0.97；p=0.03），母亲的体重指数（BMI；赔率：1.03；p=0.01），抑郁症状（赔率：1.09；p≤0.0001），睡眠质量（赔率：1.17；p≤0.0001），和弹性（赔率：0.42;p≤0.0001）均导致产后疲劳。多因素logistic回归显示，母亲的BMI，睡眠质量,抑郁症状,和弹性是PPF的重要预测因子。适度分析表明，心理弹性在睡眠质量和疲劳的主要影响之间（交互作用：β=0.01，p=0.31，95％CI：-0.01至0.04）或在抑郁症状和产后疲劳的主要影响之间（交互作用：β=0.01，p=0.82，95％CI：-0.01至0.02）没有显着调节作用。
■鉴于PPF对产妇健康结局的有害影响，与PPF相关的因素应定期评估。除了母亲的BMI，睡眠质量,和抑郁症状，弹性也可能是预测母亲在这一关键时期疲劳严重程度的一个关键因素，尽管它不是该样本中的重要调节因素。
