Harlow Siobán D, Karvonen-Gutierrez Carrie, Elliott Michael R, Bondarenko Irina, Avis Nancy E, Bromberger Joyce T, Brooks Maria Mori, Miller Janis M, Reed Barbara D
Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Suite 6610 SPH I, Ann Arbor, MI 48109-2029, USA.
Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, USA.
Womens Midlife Health. 2017;3. doi: 10.1186/s40695-017-0021-y. Epub 2017 Jul 27.
Patterns of symptom clustering in midlife women may suggest common underlying mechanisms or may identify women at risk of adverse health outcomes or, conversely, likely to experience healthy aging. This paper assesses symptom clustering in the Study of Women's Health Across the Nation (SWAN) longitudinally by stage of reproductive aging and estimates the probability of women experiencing specific symptom clusters. We also evaluate factors that influence the likelihood of specific symptom clusters and assess whether symptom clustering is associated with women's self-reported health status.
This analysis includes 3289 participants in the multiethnic SWAN cohort who provided information on 58 symptoms reflecting a broad range of physical, psychological and menopausal symptoms at baseline and 7 follow-up visits over 16 years. We conducted latent transition analyses to assess symptom clustering and to model symptomatology across the menopausal transition (pre, early peri-, late peri- and post-menopausal). Joint multinomial logistic regression models were used to identify demographic characteristics associated with premenopausal latent class membership. A partial proportional odds regression model was used to assess the association between latent class membership and self-reported health status.
We identified six latent classes that ranged from highly symptomatic (LC1) across most measured symptoms, to moderately symptomatic across most measured symptoms (LC2), to moderately symptomatic for a subset of symptoms (vasomotor symptoms, pain, fatigue, sleep disturbances and physical health symptoms) (LC3 and LC5) with one class (LC3) including interference in life activities because of physical health symptoms, to numerous milder symptoms, dominated by fatigue and psychological symptoms (LC4), to relatively asymptomatic (LC6). In pre-menopause, 10% of women were classified in LC1, 16% in LC2, 14% in LC3 and LC4, 26% in LC5, and 20% in LC6. Intensity of vasomotor and urogenital symptoms as well as sexual desire) differed minimally by latent class. Classification into the two most symptomatic classes was strongly associated with financial strain, White race/ethnicity, obesity and smoking status. Over time, women were most likely to remain within the same latent class as they transitioned through menopause stages (range 39-76%), although some women worsened or improved. The probability of moving between classes did not differ substantially by menopausal stage. Women in the highly symptomatic classes more frequently rated their health as fair to poor compared to women in the least symptomatic class.
Clear patterns of symptom clustering were present early in midlife, tended to be stable over time, and were strongly associated with self-perceived health. Notably, vasomotor symptoms tended to cluster with sleep disturbances and fatigue, were present in each of the moderate to highly symptomatic classes, but were not a defining characteristic of the symptom clusters. Clustering of midlife women by symptoms may suggest common underlying mechanisms amenable to interventions. Given that one-quarter of midlife women were highly or moderately symptomatic across all domains in the pre-menopause, addressing symptom burden in early midlife is likely critical to ameliorating risk in the most vulnerable populations.
中年女性的症状聚类模式可能提示共同的潜在机制,或者识别出有不良健康结局风险的女性,反之,也可能识别出可能经历健康衰老的女性。本文通过生殖衰老阶段对全国女性健康研究(SWAN)中的症状聚类进行纵向评估,并估计女性经历特定症状聚类的概率。我们还评估了影响特定症状聚类可能性的因素,并评估症状聚类是否与女性自我报告的健康状况相关。
该分析纳入了多民族SWAN队列中的3289名参与者,她们在基线时以及16年中的7次随访中提供了关于58种症状的信息,这些症状反映了广泛的身体、心理和更年期症状。我们进行了潜在转变分析,以评估症状聚类并对更年期过渡(绝经前、围绝经期早期、围绝经期晚期和绝经后)的症状学进行建模。联合多项逻辑回归模型用于识别与绝经前潜在类别成员相关的人口统计学特征。部分比例优势回归模型用于评估潜在类别成员与自我报告的健康状况之间的关联。
我们识别出六个潜在类别,从在大多数测量症状上症状严重(LC1),到在大多数测量症状上症状中等(LC2),到对一部分症状(血管舒缩症状、疼痛、疲劳、睡眠障碍和身体健康症状)症状中等(LC3和LC5),其中一个类别(LC3)包括由于身体健康症状对生活活动的干扰,到许多较轻症状,以疲劳和心理症状为主(LC4),到相对无症状(LC6)。在绝经前,10%的女性被归类为LC1,16%为LC2,14%为LC3和LC4,26%为LC5,20%为LC6。血管舒缩和泌尿生殖系统症状以及性欲的强度在潜在类别之间差异最小。分类到两个症状最严重的类别与经济压力、白人种族/族裔、肥胖和吸烟状况密切相关。随着时间推移,女性在经历更年期各阶段时最有可能保持在同一潜在类别中(范围为39 - 76%),尽管有些女性症状加重或改善。不同更年期阶段在类别之间转换的概率没有实质性差异。与症状最轻类别的女性相比,症状严重类别的女性更频繁地将自己的健康评为一般到较差。
中年早期存在明显的症状聚类模式,随时间趋于稳定,并且与自我感知的健康密切相关。值得注意的是,血管舒缩症状往往与睡眠障碍和疲劳聚类,在每个中度到高度症状类中都存在,但不是症状聚类的决定性特征。中年女性按症状聚类可能提示适合干预的共同潜在机制。鉴于四分之一的中年女性在绝经前在所有领域都有高度或中度症状,解决中年早期的症状负担可能对改善最脆弱人群的风险至关重要。