Postpartum depression symptoms in survey-based research: a structural equation analysis

Abstract

Background Since the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis. In this research, we introduced a new framework for postpartum depression modeling for women. Methods We structured the model of this research to take into consideration the Malaysian culture in particular. A total of 387 postpartum women have completed the questionnaire. The symptoms of postpartum depression were examined using the Edinburgh Postnatal Depression Scale (EPDS), and they act as a dependent variable in this research model. Results Four hundred fifty mothers were invited to participate in this research. 86% of the total distributed questionnaire received feedback. The majority of 79.6% of respondents were having depression symptoms. The highest coefficients of factor loading analysis obtained in every latent variable indicator were income (β = 0.77), screen time (β = 0.83), chips (β = 0.85), and anxiety (β = 0.88). Lifestyle, unhealthy food, and BMI variables were directly affected by the dependent variable. Based on the output, respondents with a high level of depression symptoms tended to consume more unhealthy food and had a high level of body mass indexes (BMI). The highest significant impact on depression level among postpartum women was unhealthy food consumption. Based on our model, the findings indicated that 76% of the variances stemmed from a variety of factors: socio-demographics, lifestyle, healthy food, unhealthy food, and BMI. The strength of the exogenous and endogenous variables in this research framework is strong. Conclusion The prevalence of postpartum women with depression symptoms in this study is considerably high. It is, therefore, imperative that postpartum women seek medical help to prevent postpartum depressive symptoms from worsening.

States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model

“…Postpartum depression (PPD) is defined as a non-psychotic depressive episode beginning in or extending to the postpartum period [ 1 ]. In addition to the similar symptoms of depression at other times of life such as loss of interest, insomnia, irritability, exhaustion, poor concentration, low self-respect, and thoughts of suicide, women who have PPD also experience guilty feelings about taking care of their new baby [ 2 , 3 , 4 , 5 ]. Due to the high incidence worldwide, PPD has been recognized as a severe public health problem during the last decades [ 3 , 6 ].…”

“…In addition to the similar symptoms of depression at other times of life such as loss of interest, insomnia, irritability, exhaustion, poor concentration, low self-respect, and thoughts of suicide, women who have PPD also experience guilty feelings about taking care of their new baby [ 2 , 3 , 4 , 5 ]. Due to the high incidence worldwide, PPD has been recognized as a severe public health problem during the last decades [ 3 , 6 ]. Longitudinal and epidemiological studies have found the at the prevalence of PPD in different countries varied from 10% to more than 25% in the first year postpartum [ 7 , 8 , 9 ].…”

“…In addition to its high incidence, PPD can lead to several detrimental consequences in the longer terms not only for the mother, but for the infant and the family as a whole [ 12 ]. First, PPD is associated with the hazards for the mother’s mental and physical wellbeing [ 3 , 13 ]. PPD was found to be one of the leading causes of maternal morbidity and mortality in various countries [ 3 ].…”

“…First, PPD is associated with the hazards for the mother’s mental and physical wellbeing [ 3 , 13 ]. PPD was found to be one of the leading causes of maternal morbidity and mortality in various countries [ 3 ]. Second, PPD is related to the impairment of mother–infant attachment [ 14 ] and maternal self-efficacy [ 15 , 16 ], which could lead to the longer-term disruption of motional and cognitive development of the infant [ 14 , 17 ].…”

“…[ 26 , 27 ]. From the perspective of risk factor discovery, regression and structural equation analysis have been widely used in PPD studies to explore the factors [ 3 , 15 , 16 , 28 ]. However, the above analysis offers little information about the dynamic process of disease evaluation [ 29 ].…”