Soria-Contreras Diana C, Wang Siwen, Mitsunami Makiko, Liu Jiaxuan, Lawn Rebecca B, Shifren Jan L, Purdue-Smithe Alexandra C, Oken Emily, Chavarro Jorge E
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.
Am J Obstet Gynecol. 2025 Jan 23. doi: 10.1016/j.ajog.2025.01.025.
Menstrual cycle characteristics are potential indicators of hormonal exposures and may also signal cardiovascular disease risk factors, both of which are relevant to cognitive health. However, there is scarce epidemiological evidence on the association between cycle characteristics and cognitive function.
We studied the associations of menstrual cycle characteristics at 3 stages of a woman's reproductive lifespan with cognitive function in midlife.
We studied participants from the Nurses' Health Study II, an ongoing longitudinal cohort of female nurses initially enrolled in 1989. Exposures were cycle regularity at 14 to 17 and 18 to 22 years, and cycle length (the interval between 2 consecutive cycles) at 18 to 22 years (all retrospectively reported at enrollment), and current cycle regularity and length at 29 to 46 years (reported in 1993). Outcomes were composite z scores measuring psychomotor speed/attention and learning/working memory obtained with 1 self-administered Cogstate Brief Battery assessment, measured among a subset of participants in 2014 to 2022. We included 19,904 participants with data on at least 1 menstrual cycle characteristic and a cognitive assessment. We estimated mean differences (β, 95% confidence intervals) using linear regression models adjusted for age at cognitive assessment, race and ethnicity, participants' education, wave of cognitive assessment, parental education and occupation, neighborhood socioeconomic status, age at menarche, adiposity, oral contraceptive use, and lifestyle factors (smoking, alcohol intake, physical activity, diet quality).
In the analytical sample, the mean (standard deviation [SD]) age at cognitive assessment was 62.0 (4.9) years. Women with irregular cycles at 29 to 46 years scored lower in learning/working memory (β, -0.05 SD; 95% confidence interval, -0.08 to -0.01) than those with very regular cycles. We did not observe associations for cycle regularity at 14 to 17 or 18 to 22 years. Women with cycle length ≤25 days at 18 to 22 years scored lower in learning/working memory in later life (β, -0.05 SD; -0.09 to -0.02) than those with cycles 26 to 31 days. We did not observe associations of cycle length at 29 to 46 years with later cognitive function. In a secondary analysis, women whose cycles were regular at 14 to 17 or 18 to 22 years but became irregular by 29 to 46 years also had lower learning/working memory scores, compared to women whose cycles remained regular across time points.
In this large longitudinal study, cycles ≤25 days at 18 to 22 years and irregular cycles at 29 to 46 years were associated with lower performance in learning/working memory. Future studies in other populations should confirm our findings and investigate the biological processes underlying these associations.
月经周期特征是激素暴露的潜在指标,也可能预示心血管疾病风险因素,这两者均与认知健康相关。然而,关于月经周期特征与认知功能之间关联的流行病学证据匮乏。
我们研究了女性生殖寿命三个阶段的月经周期特征与中年认知功能之间的关联。
我们对护士健康研究II的参与者进行了研究,这是一个始于1989年的持续进行的女性护士纵向队列研究。暴露因素为14至17岁和18至22岁时的月经周期规律性,以及18至22岁时的月经周期长度(两个连续周期之间的间隔)(均在入组时回顾性报告),以及29至46岁时当前的月经周期规律性和长度(1993年报告)。结局指标是通过1次自我管理的Cogstate简明电池评估获得的综合z分数,用于测量心理运动速度/注意力以及学习/工作记忆,于2014年至2022年在一部分参与者中进行测量。我们纳入了19904名至少有一项月经周期特征数据和认知评估数据的参与者。我们使用线性回归模型估计平均差异(β,95%置信区间),该模型针对认知评估时的年龄、种族和族裔、参与者的教育程度、认知评估波次、父母的教育程度和职业、邻里社会经济地位、初潮年龄、肥胖、口服避孕药使用情况以及生活方式因素(吸烟、饮酒、体育活动、饮食质量)进行了调整。
在分析样本中,认知评估时的平均(标准差[SD])年龄为62.0(4.9)岁。29至46岁月经周期不规律的女性在学习/工作记忆方面的得分(β,-0.05 SD;95%置信区间,-0.08至-0.01)低于月经周期非常规律的女性。我们未观察到14至17岁或18至22岁时月经周期规律性与认知功能之间的关联。18至22岁月经周期长度≤25天的女性在晚年学习/工作记忆方面的得分(β,-0.05 SD;-0.09至-0.02)低于月经周期为26至31天的女性。我们未观察到29至46岁时月经周期长度与后期认知功能之间的关联。在一项次要分析中,与整个时间点月经周期均保持规律的女性相比,14至17岁或18至22岁月经周期规律但到29至46岁变得不规律的女性学习/工作记忆得分也较低。
在这项大型纵向研究中,18至22岁时月经周期≤25天以及29至46岁时月经周期不规律与学习/工作记忆表现较低相关。未来在其他人群中的研究应证实我们的发现,并调查这些关联背后的生物学过程。