Assessment of emotional status and risk factors in early pregnancy using multidimensional data: a cross-sectional...

Pregnancy-related emotional disorders are prevalent and significantly impact maternal and child health. Addressing these disorders and implementing effective interventions are essential for improving health outcomes. This study utilizes multidimensional data to assess the emotional state and risk factors during early pregnancy, providing evidence-based support for optimizing mental health management strategies and clinical decision-making for pregnant women.

Using a cross-sectional survey design, data were collected from 1,395 pregnant women via stratified sampling between April and September 2021. A structured questionnaire was administered to gather information on demographic characteristics, lifestyle habits, sleep quality, medication use, and psychological health indicators. One-way analysis of variance (ANOVA) and multiple linear regression models were utilized to identify independent factors influencing emotional anxiety and to construct a risk prediction model.

(1) Emotional Status: The prevalence of anxiety was 22.15%, with 75.13% of pregnant women expressing concerns about fetal health and 65.23% reporting significant psychological burden related to childbirth pain. (2) Univariate Analysis: Age stratification (F = 5.197, p = 0.006) and primiparity (t = - 2.219, p = 0.027) were significantly associated with emotional anxiety. Participants with sleep disorders (13.69%) had significantly higher anxiety scores (t = - 9.629, p < 0.001). Progesterone medications (t = 2.456, p = 0.014) and levothyroxine (t = 7.317, p < 0.001) were significantly negatively correlated with anxiety. In contrast, a history of smoking (F = 7.116, p = 0.001), alcohol consumption (F = 18.787, p < 0.001), and secondhand smoke exposure (t= -7.442, p < 0.001) were significantly positively correlated with anxiety. (3) Multivariate Model: Primiparity, sleep disorders, alcohol consumption, and secondhand smoke exposure were identified as independent risk factors for emotional anxiety (β > 0, p < 0.05).

The sample was limited to a specific region and time frame, which may have affected the generalizability of the findings.

Utilizing multidimensional data to assess the emotional state and risk factors of pregnant women, and conducting intelligent analysis can accurately identify emotional risks during pregnancy. In the future, integrating sleep interventions, lifestyle optimization, and social support networks could lead to the development of digital health tools for dynamic early warning. It is recommended to embed these tools into routine prenatal management processes to advance the precision and personalization of mental health services during pregnancy.