Prevalence and contributory factors of anxiety and depression among pregnant women in the post-pandemic era of COVID-19 in Shenzhen, China

Abstract

Background: Pregnant women are emotionally vulnerable and have suffered great psychological impacts. Following the coronavirus disease 2019 (COVID-19) outbreak, a study was undertaken of the prevalence of, and factors contributing to, symptoms of anxiety and depression among pregnant women in Shenzhen, China.

Methods: A cross-sectional study on pregnant women was conducted from September to December 2020 in Shenzhen, using a random-recruit method. The General Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) surveys were used to evaluate symptoms of anxiety and depression. A multivariate logistic regression model was developed to explore factors potentially associated with symptoms of anxiety and depression during pregnancy.

Results: A total of 3,434 pregnant women aged 15 to 59 years were enrolled. Symptoms of anxiety and depression were present in 9.8% and 6.9%, respectively. Logistic regression analysis using a stepwise procedure revealed that an increased risk of symptoms of anxiety and depression was associated with unmarried/divorced/widowed, unemployed, received professional psychological counseling, family dysfunction, the first trimester of pregnancy, pregnancy complications and vaginal bleeding, unplanned pregnancy, decline in household income and disputes between partners caused by the COVID-19 pandemic, consumption of alcoholic drinks by women and their partners, smoking, lack of exercise and sedentary lifestyle. Women with education from junior high school through college were less likely to experience symptoms of prenatal depression.

Conclusions: Our study revealed factors associated with psychological symptoms among pregnant women in the post-COVID-19-pandemic era. These results should help to update guidance for psychological interventions for pregnant women during the period of COVID-19.

Keywords: Anxiety; Covid-19; Depression; Pregnancy.

Fig. 1

Geographic distribution of participants in Shenzhen City, China. The map of China and the inset showing the distribution of participants from ten districts in Shenzhen were obtained from online sources (https://www.wikiwand.com/ and https://wenku.baidu.com/, respectively). Sample sizes are shown below the names of each region.