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DOI 10.1080/0167482x.2023.2256470

Медицинская библиотека · Journal of psychosomatic obstetrics and gynaecology · 2023

Trajectories of cognitive reactivity and its predictive value on postpartum depression in Chinese women: a latent class growth modeling analysis.

Fu Yanqing, Lin Xiujing, Li Yonglin, Zhang Minfang, Chen Wei-Ti, Huang Feifei

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Many women are experiencing postpartum depression (PPD) after giving birth. How to recognize and intervene in high-risk PPD women early and effectively remains unknown. Our objective is to describe the latent trajectory groups of cognitive reactivity (CR) in perinatal women, and their relationship to demographic and disease-related factors, as well as investigate the associations with PPD. Data from 321 perinatal women who were evaluated in urban tertiary hospitals in China at three-time points: 32-35 weeks of pregnancy, 1 week postpartum, and 6 weeks postpartum. Latent class growth modeling was used to identify the trajectory patterns of CR and logistic regression was used to explore the association between demographic and disease-related factors, CR trajectories, and depression. Three trajectory groups were identified: the continuing deterioration group (17.2%), the postpartum deterioration group (22.1%), and the consistent resilient group (60.7%). Participants with a bachelor's degree or higher and with gestational diabetes diagnosis were more likely to be in the continuing deterioration group. Those who were from only-child families were more likely to be in the postpartum deterioration group. Women in the continuing deterioration group and postpartum deterioration group were more likely to experience PPD. Targeted interventions should be developed based on trajectory group of CR.

Для цитирования: Fu Yanqing, Lin Xiujing, Li Yonglin, Zhang Minfang, Chen Wei-Ti, Huang Feifei. Trajectories of cognitive reactivity and its predictive value on postpartum depression in Chinese women: a latent class growth modeling analysis.. Journal of psychosomatic obstetrics and gynaecology. 2023. DOI: 10.1080/0167482x.2023.2256470.

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