Liu Siqi,Cai Shu,Liang Yunfang,Tan Yingyao,Analysis of latent profiles and influencing factors of sleep in first-trimester pregnant women[J].SICHUAN MENTAL HEALTH,2025,38(1):46-52
Analysis of latent profiles and influencing factors of sleep in first-trimester pregnant women
DOI:10.11886/scjsws20241002002
English keywords:Sleep quality  Women in the first trimester of pregnancy  Latent profile analysis  Depression  Social capital
Fund projects:中国高校产学研创新基金(项目名称:基于智能化平台的妊娠糖尿病高危孕妇身体活动干预模式的构建和实证研究,项目编号:2023HT018)
Author NameAffiliationPostcode
Liu Siqi School of Nursing Guangdong Pharmaceutical University Guangzhou 510000 China 510000
Cai Shu* School of Nursing Guangdong Pharmaceutical University Guangzhou 510000 China 510000
Liang Yunfang The First Affiliated Hospital of Guangdong Pharmaceutical University Guangzhou 510000 China 510000
Tan Yingyao Longgang District Maternity & Child Healthcare Hospital of Shenzhen City Longgang District Maternity and Child Institute of Shantou University Medical College Shenzhen 518000 China 518000
Hits:
Download times:
English abstract:
      Background Sleep disorder in the first trimester is a fairly common health problem, and previous studies have mainly reflected the overall sleep quality through scale assessments, which may not accurately capture the differences among various subtypes.Objective To explore the latent profiles of sleep quality in first-trimester pregnant women and identify the physiological, psychological and social factors, in order to provide practical references for the development of personalized interventions for sleep disorders in first-trimester pregnant women.Methods A total of 1 066 first-trimester pregnant women who visited the obstetric outpatient clinic of a tertiary A hospital in Shenzhen from October 2021 to October 2022 were investigated using the general information questionnaire, Pittsburgh Sleep Quality Index (PSQI), Edinburgh Postnatal Depression Scale (EPDS), Chinese version of short International Physical Activity Questionnaire (IPAQ-S-C) and Social Capital Assessment Tool in Pregnancy for Maternal Health (SCAT-MH). Then the sleep profiles were identified through latent profile analysis, and the robust mixture regression model was employed to determine the influencing factors of sleep profiles.Results A 3-profile solution showed the best fit: 732 cases (68.67%) of good sleep quality group, 87 cases (8.16%) of low sleep efficiency group, and 247 cases (23.17%) of daytime dysfunction group. In comparison with subjects in good sleep quality group, first-trimester pregnant women in low sleep efficiency group were at a younger age (OR=0.951, 95% CI: 0.922~0.980), held a Bachelor's degree or above (OR=1.869, 95% CI: 1.260~2.773) and exhibited lower levels of social capital (OR=0.962, 95% CI: 0.951~0.973), while those in daytime dysfunction group were at an older age (OR=1.072, 95% CI: 1.027~1.120) and had higher levels of depression (OR=1.166, 95% CI: 1.115~1.218). Pregnant women who were workers (OR=0.507, 95% CI: 0.293~0.876) were less likely to report daytime dysfunction.Conclusion Three latent profiles with significant heterogeneity are derived from the sleep quality of first-trimester pregnant women, and levels of depression and social capital are the main influencing factors of sleep quality. [Funded by Industry-University-Research Innovation Fund for Chinese Universities (number, 2023HT018)]
View Full Text   View/Add Comment  Download reader
Close