Depression and Anxiety Drive Sleep Problems in Second-Trimester Pregnant Women, Path Analysis Finds

Sleep disturbance is one of the most common complaints of pregnancy, and a new study from China suggests that the psychological burden carried by expectant mothers may be a stronger driver of poor sleep than the physical discomforts alone. In a cross-sectional investigation published in Current Psychology, researchers led by Can Liu and Hongyu Li of Ningxia Medical University analyzed data from 997 second-trimester pregnant women receiving antenatal care at a tertiary hospital in Ningxia between December 2021 and June 2023. Using path analysis, an extension of structural equation modeling, the team mapped how depression, pregnancy-related anxiety, family functioning, stressful life events, and personality traits combine to shape sleep quality during mid-pregnancy.

The scale of the problem was striking. According to the Pittsburgh Sleep Quality Index, a validated instrument that scores sleep across seven domains including duration, latency, and disturbances, 16.25 percent of the participants met the threshold for severe sleep disturbance, defined as a global score of 8 or higher. Another 28.69 percent showed mild disturbance, with scores between 5 and 7. Taken together, nearly 45 percent of the women in their second trimester were experiencing sleep that was measurably compromised, a finding consistent with meta-analytic evidence that sleep quality deteriorates progressively across gestation.

What makes the new study distinctive is not simply the documentation of poor sleep but the disentangling of the causal-looking architecture behind it. The researchers administered a battery of validated instruments: the Edinburgh Postnatal Depression Scale for depressive symptoms, the Pregnancy-Associated Anxiety Questionnaire for pregnancy-specific worry, the Family APGAR Index for perceived family functioning, and the Life Event Scale for recent stressful experiences. Ordinal logistic regression was first used to screen candidate predictors, and path analysis was then applied to estimate both direct and indirect pathways linking psychological and contextual factors to sleep outcomes.

The path model identified four variables exerting direct effects on sleep quality. Prenatal depression carried the largest standardized effect, with a path coefficient of 0.181, followed closely by pregnancy-related anxiety at 0.165. Being pregnant for the first time showed a small negative coefficient of -0.070, while an introverted personality contributed a coefficient of 0.047. In practical terms, the model indicates that women with more depressive symptoms and stronger pregnancy-specific anxiety tended to report worse sleep, and that dispositional and obstetric characteristics added smaller but detectable contributions independent of mood.

Perhaps the most consequential finding concerns the variables that did not act directly. Family functioning and stressful life events influenced sleep quality only indirectly, operating through their effects on prenatal anxiety and depressive symptoms. This mediating structure suggests that the family environment and external stressors do not disturb sleep on their own; rather, they shape the emotional climate inside the mother, and it is that emotional state that erodes sleep. The distinction matters for intervention design, because it implies that strengthening family support and buffering life stress may improve sleep primarily by reducing anxiety and depression.

The statistical performance of the model lends credibility to these pathways. Fit indices fell within conventional benchmarks for a good-fitting structural model: the ratio of chi-square to degrees of freedom was 2.797, the root mean square error of approximation was 0.042, and the comparative fit index reached 0.942. These values indicate that the hypothesized network of relationships reproduced the observed correlations among the measured variables reasonably well, supporting the interpretation that mood symptoms sit at the hub of the pathways leading to disturbed sleep.

The results align with a growing body of perinatal sleep research. Meta-analyses have linked insomnia and poor sleep quality to perinatal depressive symptoms, and prospective cohort studies have shown that mid-pregnancy insomnia predicts later depressive episodes. Poor maternal sleep has also been associated with adverse obstetric outcomes, including preterm birth, and with impaired quality of life during pregnancy. By quantifying the relative weights of psychological predictors within a single integrated model, the Ningxia team adds a mechanistic layer to this literature, showing how distal factors funnel through proximal emotional states.

The authors argue that their findings carry a clear clinical message: routine screening for prenatal depression and pregnancy-related anxiety during the second trimester, combined with targeted psychosocial interventions, could effectively reduce maternal sleep disturbance and benefit fetal development. Because the second trimester precedes the period of steepest sleep deterioration, identifying women with elevated depressive or anxiety symptoms at this stage offers a window for prevention. Interventions such as sleep enhancement training, cognitive-behavioral approaches, and family-centered support programs could plausibly interrupt the pathways identified in the model before sleep problems become entrenched.

Several caveats temper the conclusions. The study was cross-sectional, so the direction of causality between mood and sleep cannot be definitively established; poor sleep may itself amplify depressive and anxious symptoms, creating a bidirectional loop that path analysis of a single time point cannot fully resolve. The sample was drawn from a single tertiary hospital in Ningxia, which may limit generalizability to other regions and care settings. All measures were self-reported, introducing the possibility of recall and reporting biases. The authors note that original survey data are available from the corresponding author upon reasonable written request, which may facilitate replication.

Even with these limitations, the study offers one of the more detailed maps to date of how psychological and social factors converge on sleep during the second trimester. Its core insight, that depression and pregnancy-related anxiety are the dominant direct predictors while family functioning and life stress act through them, reframes maternal sleep disturbance as an emotionally mediated phenomenon rather than an inevitable physical byproduct of gestation. For clinicians and public health planners, the implication is that protecting sleep in pregnancy may begin not in the bedroom but in the assessment of mood and the strengthening of the family systems that surround expectant mothers.

Subject of Research: Psychological predictors of sleep disturbance in second-trimester pregnant women analyzed with path analysis

Article Title: Relationships between psychological factors and sleep disturbance in second-trimester pregnant women: a path analysis

Article References: Liu, C., Li, H., Jia, J., Yang, D., Yu, Z., Wang, C., Wang, H., Ma, S., & Guan, S. (2026). Relationships between psychological factors and sleep disturbance in second-trimester pregnant women: a path analysis. Current Psychology, 45(20), Article 1627. https://doi.org/10.1007/s12144-026-10166-w

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10166-w

Keywords: pregnancy, sleep disturbance, prenatal depression, pregnancy-related anxiety, path analysis, second trimester, family functioning, Pittsburgh Sleep Quality Index, maternal health, structural equation modeling, psychosocial factors, Current Psychology