| 刘思齐,蔡舒,梁云芳,谭颖瑶.孕早期女性睡眠潜在剖面及影响因素[J].四川精神卫生杂志,2025,38(1):46-52.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 |
| 孕早期女性睡眠潜在剖面及影响因素 |
| Analysis of latent profiles and influencing factors of sleep in first-trimester pregnant women |
| 投稿时间：2024-10-02 |
| DOI：10.11886/scjsws20241002002 |
| 中文关键词: 睡眠质量 孕早期女性 潜在剖面分析 抑郁 社会资本 |
| 英文关键词:Sleep quality Women in the first trimester of pregnancy Latent profile analysis Depression Social capital |
| 基金项目: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） |
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| 中文摘要: |
| 背景 睡眠障碍是孕早期女性常见的健康问题，既往研究主要以量表评定结果反映这一群体的总体睡眠质量，难以精准地体现不同睡眠障碍群组间的差异。目的 探讨孕早期女性睡眠质量潜在剖面，分析不同剖面生理-心理-社会方面的影响因素，以期为制定个性化睡眠干预措施提供参考。方法 选取2021年10月—2022年10月在深圳市某三级甲等医院产科门诊就诊的1 066名孕早期女性为研究对象。采用基本资料调查问卷、匹兹堡睡眠质量指数量表（PSQI）、爱丁堡产后抑郁量表（EPDS）、中文版国际体力活动问卷短卷（IPAQ-S-C）和孕妇社会资本评估量表（SCAT-MH）进行调查。通过潜在剖面分析探讨睡眠剖面，采用回归混合模型的稳健三步法分析不同睡眠剖面的影响因素。结果 孕早期女性睡眠质量分为3个剖面：睡眠质量良好组732例（68.67%）、睡眠效率低组87例（8.16%）、日间功能障碍组247例（23.17%）。相比于睡眠质量良好组，年龄较小（OR=0.951，95% CI：0.922~0.980）、受教育程度为本科及以上（OR=1.869，95% CI：1.260~2.773）以及社会资本水平低（OR=0.962，95% CI：0.951~0.973）的孕早期女性更可能属于睡眠效率低组；年龄较大（OR=1.072，95% CI：1.027~1.120）、抑郁水平高（OR=1.166，95% CI：1.115~1.218）者更可能属于日间功能障碍组；职业为工人（OR=0.507，95% CI：0.293~0.876）者属于日间功能障碍组的可能性较小。结论 孕早期女性睡眠质量存在3个潜在剖面，具有明显异质性，抑郁和社会资本水平是孕早期女性睡眠质量的主要影响因素。 |
| 英文摘要: |
| 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）］ |
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