Latent Trajectories and Risk Factors of Prenatal Stress, Anxiety, and Depression in Southwestern China-A Longitudinal Study

Int J Environ Res Public Health. 2023 Feb 21;20(5):3818. doi: 10.3390/ijerph20053818.

Abstract

(1) Background: Few studies have explored the heterogeneity of trajectories of stress, anxiety, and depressive symptoms during pregnancy. This study aimed to explore the trajectory groups of stress, anxiety, and depressive symptoms in women during pregnancy and the risk factors associated with those groups. (2) Methods: Data came from pregnant women recruited from January to September 2018 in four hospitals in Chongqing Province, China. A structured questionnaire was given to pregnant women, which collected basic information, including personal, family, and social information. The growth mixture model was applied to identify potential trajectory groups, and multinomial logistic regression was applied to analyze factors of trajectory groups. (3) Results: We identified three stress trajectory groups, three anxiety trajectory groups, and four depression trajectory groups. Less developed regions, inadequate family care, and inadequate social support were associated with a high risk of stress; residence, use of potentially teratogenic drugs, owning pets, family care, and social support were strongly associated with the anxiety trajectory group; family care and social support were the most critical factors for the depression trajectory group. (4) Conclusions: The trajectories of prenatal stress, anxiety, and depressive symptoms are dynamic and heterogeneous. This study may provide some critical insights into the characteristics of women in the high-risk trajectory groups for early intervention to mitigate worsening symptoms.

Keywords: growth mixture model; longitudinal trajectories; prenatal anxiety; prenatal depression; prenatal stress.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Anxiety*
  • China
  • Depression*
  • Female
  • Humans
  • Longitudinal Studies
  • Pregnancy
  • Risk Factors

Grants and funding

This work was supported by the National Natural Science Foundation of China (grant number 71573027).