Association between depression, sleep disturbance, and irregular menstrual cycles: insights from the NHANES 2005-2018

抑郁症、睡眠障碍和月经周期不规律之间的关联:来自 NHANES 2005-2018 年的见解

阅读:1

Abstract

INTRODUCTION: This paper examines the connection among sleep disturbances, depressive symptoms, and menstrual cycle irregularities. Given the high prevalence of sleep disturbances and depression among women of reproductive age, understanding their impact on menstrual cycles is crucial for developing effective interventions. METHODS: NHANES data of American women from 2005 to 2018 were utilized. Weighted multivariate logistic regression models were utilized to estimate the odds of menstrual irregularities in relation to depressive symptoms, sleep disturbances, and their combined effects. Restricted cubic spline analyses were used to assess potential nonlinear relationships. Subgroup analyses were conducted based on demographic and lifestyle factors. Mediation analysis was performed to evaluate the potential indirect pathways through fasting blood glucose (FBG) and triglycerides (TG). RESULTS: Three thousand five hundred ninety-four participants were included in adjusted analyses. Both depressive symptoms (OR = 1.58; 95% CI: 1.13-2.23) and sleep disturbance (OR = 1.69; 95% CI: 1.23-2.34; P = 0.002) were associated with higher odds of menstrual irregularities. Participants with both sleep disturbances and depressive symptoms had higher odds of menstrual irregularities (OR = 1.86; 95% CI: 1.29-2.67; P = 0.001). In mediation analyses, the indirect association via FBG accounted for 1.56% of the total association, and the indirect association via TG accounted for 4.31%. CONCLUSION: Sleep disturbances and depressive symptoms were independently and jointly associated with higher odds of menstrual irregularities, and the risk was higher when both were present. Statistically significant indirect associations were observed via FBG and TG.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。