Association of sleep disturbance with Parkinson disease: evidence from the Women's Health Initiative

Cardiovascular disease, bone fracture, and all-cause mortality risks among postmenopausal women by arthritis and veteran status: A multistate Markov transition analysis

Arthritis, a chronic inflammatory condition linked to cardiovascular disease (CVD) and bone fracture, is more frequent among military veterans and postmenopausal women. This study examined correlates of arthritis and relationships of arthritis with risks of developing CVD, bone fractures, and mortality among postmenopausal veteran and non-veteran women. We analyzed longitudinal data on 135,790 (3,436 veteran and 132,354 non-veteran) postmenopausal women from the Women's Health Initiative who were followed-up for an average of 16 years between enrollment (1993-1998) and February 17, 2024. Regression and multistate Markov modeling were applied to meet study objectives. The prevalence of arthritis at enrollment (1993-1998) did not differ by veteran status in a fully adjusted logistic model. Variable selection yielded 5 key predictors of prevalent arthritis among veterans and 15 key predictors among non-veterans. In fully-adjusted Cox models, prevalent arthritis was associated with CVD (hazard ratio [HR] = 1.08, 95% confidence interval [CI]: 1.05, 1.10) and all-cause mortality (HR = 1.03, 95% CI: 1.01, 1.05) risks among non-veterans only, but was not associated with bone fracture risk irrespective of veteran status. Transition probabilities between health and CVD and between bone fracture and death were higher among women with vs. without arthritis. The latter transition was more strongly related to arthritis among non-veteran vs. veteran women. In conclusion, among postmenopausal women, prevalent arthritis was associated with greater probabilities of transitioning from a healthy state to CVD and from bone fracture to death, with worse prognosis after bone fracture among those who did not serve in the military.

Reducing Parkinson's disease incidence in patients with insomnia through acupuncture: A cohort study

Background

Parkinson's disease (PD) is a prevalent neurodegenerative condition characterized primarily by motor symptoms, often accompanied by non-motor manifestations such as insomnia. Acupuncture, an increasingly popular alternative therapy, has shown promise in the prevention and alleviation of PD motor symptoms. However, the specific impact of acupuncture on the risk of developing PD in insomnia patients remains uncertain.

Methods

In this retrospective study, we identified and matched 152,585 newly diagnosed insomnia patients from Taiwan's National Health Insurance Research Database (NHIRD) from 2000 to 2010. Using a 1:1 propensity score matching method, we ensured the comparability of two groups: patients who received acupuncture treatment and those who did not. It resulted in a final cohort of 20,112 patients in both the acupuncture and non-acupuncture groups.

Results

Our analysis revealed that insomnia patients who underwent acupuncture treatment exhibited a significantly reduced risk of developing PD. The adjusted hazard ratio (aHR) was 0.44 (95 % confidence interval = 0.39-0.50) compared to those who did not receive acupuncture. Furthermore, the cumulative incidence of PD in the acupuncture group was significantly lower, as evidenced by the log-rank test (p < 0.001).

Conclusion

In conclusion, our study provides evidence suggesting that acupuncture treatment is associated with a decreased risk of PD in patients with insomnia. However, further research is warranted to strengthen the evidence supporting these findings.

Association Between Sleep Characteristics and Likelihood of Prodromal Parkinson's Disease: A Cross-Sectional Analysis in the HABIT Study

Background

Sleep is critical in health problems including Parkinson's disease (PD). This study examined the association between sleep characteristics and the likelihood of prodromal PD.

Methods

At baseline examination of the Heart and Brain Investigation in Taicang (HABIT) study, potential PD biomarkers were obtained for 8777 participants aged over 50 years, and the probability of prodromal PD was assessed based on the Chinese expert consensus and Movement Disorder Society (MDS) criteria. General and component sleep characteristics were evaluated by the Pittsburgh Sleep Quality Index (PSQI). Median regression was applied to examine the association between sleep and the probability of prodromal PD, adjusting for age, sex, education level, physical activity, obesity, fast plasma glucose, lipids, and hypertension.

Results

Based on China criteria, a higher level of PSQI score was significantly associated with a higher probability of prodromal PD (β = 0.02, 95% CI: 0.01-0.03) and a higher risk of having an increased probability of prodromal PD (OR = 1.04, 95% CI: 1.02-1.05). Compared to participants with good quality sleep, those with poor quality sleep had a 0.07% increased probability of prodromal PD (95% CI: 0.01-0.13) and a 19% increased risk of having a high prodromal PD probability (95% CI: 1.04-1.20). Similar associations between sleep quality and the probability of prodromal PD were also observed using the MDS criteria. Subjective sleep quality, sleep latency, habitual sleep efficiency, daytime dysfunction, and use of sleep medications were also associated with the probability of prodromal PD.

Conclusion

Poor sleep quality was associated with a high probability of prodromal PD. Sleep may be helpful for understanding and intervention of prodromal PD.

Neurologic Disorders in Women and Sleep

Sleep disorders in women remain underrecognized and underdiagnosed mainly because of gender bias in researching and characterizing sleep disorders in women. Symptoms of common sleep disorders are frequently missed in the general female population and are expected to be further overlooked because of overlapping symptoms in women with neurologic disorders. Given the bidirectional relationship with sleep and neurologic disorders, it remains critical to be aware of the presentation and impact of sleep disorders in this patient population. This article reviews available data on sleep disorders in women with neurologic disorders and discusses their distinctive features.

State-of-the-art review of the clinical research on menopause and hormone replacement therapy association with Parkinson's disease: What meta-analysis studies cannot tell us

The menopause is a midlife endocrinological process that greatly affects women's central nervous system functions. Over the last 2 decades numerous clinical studies have addressed the influence of ovarian hormone decline on neurological disorders like Parkinson's disease and Alzheimer's disease. However, the findings in support of a role for age at menopause, type of menopause and hormone replacement therapy on Parkinson's disease onset and its core features show inconsistencies due to the heterogeneity in the study design. Here, we provide a unified overview of the clinical literature on the influence of menopause and ovarian hormones on Parkinson's disease. We highlight the possible sources of conflicting evidence and gather considerations for future observational clinical studies that aim to explore the neurological impact of menopause-related features in Parkinson's disease.

Sleep and affective disorders in relation to Parkinson's disease risk among older women from the Women's Health Initiative

OBJECTIVES

To evaluate sleep and affective (mood/anxiety) disorders as clinical predictors of incident Parkinson's disease (PD) among women ≥65 years of age.

METHODS

We performed secondary analyses with available data from the Women's Health Initiative Clinical Trials and Observational Study linked to Medicare claims. Sleep, mood and anxiety disorders at baseline were defined using diagnostic codes. Incident PD was defined using self-reported PD, first PD diagnosis, use of PD medications, and/or deaths attributed to PD. Cox regression was applied to estimate hazard ratios (HR) with 95 % confidence intervals (CI), controlling for socio-demographic/lifestyle/health characteristics. Time-to-event was calculated from baseline (1993-1998) to year of PD event, loss to follow-up, death, or December 31, 2018, whichever came first.

RESULTS

A total of 53,996 study-eligible WHI participants yielded 1756 (3.25 %) PD cases over ~14.39 (±6.18) years of follow-up. The relative risk for PD doubled among women with affective disorders (HR = 2.05, 95 % CI: 1.84, 2.27), mood disorders (HR = 2.18, 95 % CI: 1.97, 2.42) and anxiety disorders (HR = 1.97, 95 % CI: 1.75, 2.22). Sleep disorders alone (without affective) were not significantly associated with PD risk (HR = 0.85, 95 % CI: 0.69, 1.04), whereas affective disorders alone (without sleep) (HR = 1.93, 95 % CI: 1.72, 2.17) or in combination with sleep disorders (HR = 2.18, 95 % CI: 1.85, 2.56) were associated with twice the PD risk relative to no sleep/affective disorders.

LIMITATIONS

Observational design; Selection bias; Information bias; Generalizability.

CONCLUSIONS

Among older women, joint sleep/affective disorders and affective disorders alone are strong clinical predictors of incident PD over 14 years.