目的:睡眠问题在孕妇中很常见,怀孕期间睡眠会发生变化。然而,睡眠轨迹模式与不良母婴结局之间的关联尚不清楚.本研究旨在通过前瞻性队列研究确定睡眠轨迹模式,并探讨其与不良围产期结局的关系。
方法:天津孕妇(N=232)在孕期每三个月完成匹兹堡睡眠质量指数,中国。从医院分娩记录中提取围产期结局。潜在类别增长分析(LCGA)描述了睡眠时间的轨迹,持续时间,和效率。采用多变量线性回归和多变量逻辑回归来评估睡眠轨迹模式与围产期结局之间的关联。
结果:确定了就寝时间的轨迹(早期,49.1%;延迟,50.9%),起床时间(早,样本的82.8%;晚期,17.2%),持续时间(短,5.2%;适当的78.0%;过量,16.8%),和效率(高,88.4%;下降,11.6%)。与睡眠更理想的女性相比,那些在起床后期的人,持续时间过长,效率降低组的婴儿出生长度较短(β范围,-0.50至-0.28,p<0.05)。此外,效率降低组的妇女出生体重较低的婴儿(β,-0.44;p<0.05)。推迟就寝时间组的女性早产的可能性更大(OR,4.57;p<0.05),而效率降低组的剖宫产几率更大(OR,3.12;p<0.05)。
结论:怀孕期间睡眠轨迹模式不太理想与围产期结局相关。因此,孕妇在孕期睡眠的早期评估对于识别高危妇女和启动干预措施以降低围产期结局具有重要意义.
OBJECTIVE: Sleep problems are common in pregnant women and sleep is altered during pregnancy. However, the associations between sleep trajectory patterns and adverse maternal and neonatal outcomes are unclear. The current study aims to identify sleep trajectory patterns and explore their associations with adverse perinatal outcomes in a prospective cohort study.
METHODS: Pregnant women (N = 232) completed the Pittsburgh Sleep Quality Index each trimester during pregnancy in Tianjin,
China. Perinatal outcomes were extracted from the hospital delivery records. Latent class growth analysis (LCGA) described the trajectories of sleep
timing, duration, and efficiency. Multivariable linear regression and multivariable logistic regression were employed to evaluate associations between sleep trajectory patterns and perinatal outcomes.
RESULTS: Trajectories were identified for bedtime (early, 49.1%; delaying, 50.9%), wake-up time (early, 82.8% of the sample; late, 17.2%), duration (short, 5.2%; adequate 78.0%; excessive, 16.8%), and efficiency (high, 88.4%; decreasing, 11.6%). Compared with women in more optimal sleep groups, those in the late wake-up, excessive duration, and decreasing efficiency groups had babies with shorter birth lengths (β range, -0.50 to -0.28, p < 0.05). Moreover, women in the decreasing efficiency group had babies with lower birth weight (β, -0.44; p < 0.05). Women in the delaying bedtime group had greater odds of preterm delivery (OR, 4.57; p < 0.05), while those in the decreasing efficiency group had greater odds of cesarean section (OR, 3.12; p < 0.05).
CONCLUSIONS: Less optimal sleep trajectory patterns during pregnancy are associated with perinatal outcomes. Therefore, early assessment of maternal sleep during pregnancy is significant for identifying at-risk women and initiating interventions to reduce perinatal outcomes.