# Factors associated with insomnia, anxiety, and depression among antenatal women in China: A cross-sectional hospital-based study

## TL;DR

This study identifies factors like geography and living situation that contribute to insomnia, anxiety, and depression in pregnant women in China.

## Contribution

The study introduces a multidimensional model linking geographic, social, and demographic factors to mental health outcomes in antenatal women.

## Key findings

- Geographic location, education, and household composition significantly predict insomnia, anxiety, and depression in antenatal women.
- Insomnia was found to strongly predict both anxiety and depression.
- Structural Equation Modeling showed a strong model fit and explained a significant portion of variance in mental health outcomes.

## Abstract

Mental health challenges, including insomnia, anxiety, and depression, are common among antenatal women and can affect both maternal and fetal outcomes. This study explores the determinants of these conditions in antenatal women in China, aiming to inform the design of mental health interventions and preventive strategies for this population.

A cross-sectional survey design was employed in this hospital-based study targeting antenatal women at a tertiary hospital in China, conducted from May 2024 to March 2025 during routine antenatal visits. Validated questionnaires assessed insomnia, anxiety, and depression. Multiple linear and logistic regression analyses identified factors associated with symptom severity and occurrence, while Structural Equation Modeling (SEM) was used to explore the relationships and mediating effects between biological and social factors, insomnia, anxiety, and depression.

The participants had a mean age of 31.48 ± 6.94 years, with most being married (90.7%), living in urban areas (74.3%), and having undergraduate/college education (45.8%). Significant predictors of insomnia included geographical location, with those in central (OR = 1.818, 95% CI: 1.500–2.204) and southern areas (OR = 1.368, 95% CI: 1.143–1.637) showing higher odds compared to the northern region. Living in rural areas (OR = 0.796, 95% CI: 0.718–0.845) and higher education levels (OR = 1.544, 95% CI: 1.012–2.355) were associated with lower odds. Other significant factors included the number of live births and household composition. For anxiety, older age (OR = 0.955, 95% CI: 0.937–0.973) and rural living (OR = 0.675, 95% CI: 0.539–0.845) decreased odds, while living with others (OR = 3.726, 95% CI: 2.463–5.639) increased the risk. Significant predictors of depression included geographical location (central areas: OR = 1.508, 95% CI: 1.106–2.055), income level, and number of live births. The logistic regression Area Under the Curve (AUC) were 0.579 for insomnia, 0.603 for anxiety, and 0.567 for depression. SEM demonstrated an excellent model fit (CFI = 0.994, TLI = 0.999, RMSEA = 0.014). Insomnia was strongly predicted by geographic location, education, and number of live births. In turn, insomnia significantly predicted anxiety (β = 0.741) and depression (β = 0.138). The model explained 54.9% of the variance in anxiety and 70.6% of the variance in depression, indicating partial mediation.

This study identifies the multidimensional factors influencing antenatal women’s insomnia, anxiety, and depression in China, particularly highlighting the roles of geographical location, current living situation, and household composition. These factors were consistently associated with all three outcomes. Targeted interventions targeting these specific risk factors are recommended to improve the mental health of antenatal women.