Association of COVID-19 Lockdown during the Perinatal Period with Postpartum Depression: Evidence from Rural Areas of Western China

ABSTRACT

COVID-19 lockdown has posed unique challenges to postpartum women, but its association with postpartum depression is not well understood in the Global South. This study aims to evaluate the association between COVID-19 lockdown and postpartum depression in rural areas of western China. A multi-stage random cluster sampling method was used to select a cohort of pregnant and postpartum women with infants aged 0–6 months. We conducted an in-person survey before the COVID-19 lockdown and a phone survey right after the lockdown ended. We used multivariate regression models to evaluate the association between lockdown and postpartum depression. Subgroup analysis was performed to explore the role of social support. The overall prevalence of postpartum depression was 13.3%. Postpartum women who experienced the lockdown were less likely to be depressed than those who did not (adjusted odds ratio (aOR) = .43, 95% confidence interval (CI) = [.27, .70]). Lockdown was negatively associated with postpartum depression among postpartum women with low level of social support (aOR = .30, 95% CI = [.18, .51]). COVID-19 lockdown was associated with lower likelihood of postpartum depression, potentially due to increased support from family. Future research is needed to explore targeted interventions to prevent postpartum depression among women from migrant worker families in rural China.

Acknowledgments

The authors would like to acknowledge the Science & Technology Department of Sichuan Province and Stanford University Research Foundation. We also thank the investigators for their hard work and dedication.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets are available from the corresponding author on reasonable request.

Contributors

Conceptualization: Huan Zhou, Yuju Wu

Formal analysis: Yuju Wu, Ruixue Ye

Writing—original draft: Yuju Wu, Huan Zhou, Wei Chang

Writing—review and editing: Yuju Wu, Ruixue Ye, Qingzhi Wang, Chang Sun, Yadong Ji, Huan Zhou, Wei Chang

All authors contributed to the development of the manuscrip

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Additional information

Funding

The authors are supported by the Science & Technology Department of Sichuan Province [Grant Number: 2021JDKP0042] and Stanford University Research Foundation [Grant Number: 0040405502159].