Relationship of menopausal status and climacteric symptoms to sleep in women undergoing chemotherapy

Goals of workThe goal of this study was to examine the relationship between menopausal symptoms, sleep quality, and mood as measured by actigraphy and self-report prior to treatment and at the end of four cycles of chemotherapy in women with breast cancer.Patients and methodsData on sleep quality (measured using actigraphy and self-report) and mood were collected prior to treatment and 12 weeks later at the end of four cycles of chemotherapy in 69 women with newly diagnosed breast cancer. In addition, each filled out the Greene Climacteric Scale. Based on reported occurrence of menses, participants were categorized post hoc into three menopausal status groups: pre-menopausal before and after chemotherapy (Pre-Pre), pre-menopausal or peri-menopausal before and peri-menopausal after chemotherapy (Pre/Peri-Peri), and post-menopausal before and after chemotherapy (Post-Post).Main resultsResults suggested that women within the Pre-Pre group evidenced more fragmented sleep with less total sleep time (TST) after chemotherapy compared to baseline. Compared to the other groups, the Pre-Pre group also experienced less TST and more awakenings before and after chemotherapy. Although the Pre/Peri-Peri group evidenced a greater increase in vasomotor symptoms after chemotherapy, there was no relationship with sleep. All groups evidenced more depressive symptoms after chemotherapy, but depression was not related to measures of sleep.ConclusionsContrary to the study hypothesis, these results suggest that women who are pre-menopausal or having regular menses before and after four cycles of chemotherapy have worse sleep following chemotherapy. Those women who maintain or become peri-menopausal (irregular menses) experience an increase in climacteric symptoms but do not experience an associated worsening of sleep. These results are preliminary and more research is necessary to further explain these findings

CROSS-SECTIONAL AND LONGITUDINAL RELATIONSHIPS BETWEEN REST-ACTIVITY RHYTHMS AND INFLAMMATION IN OLDER MEN

Abstract Sleep disturbances and physical inactivity have been associated with chronic inflammation, an important risk factor for cognitive decline in the aging population. However most previous studies focused on the cross-sectional relationships between sleep and physical activity and inflammation. In the Outcomes of Sleep Disorders in Older Men (MrOS Sleep) study, we studied both the cross-sectional and prospective associations between characteristics of 24-hour rest-activity rhythms measured by actigraphy and inflammation index measured by multiple circulating markers. In cross-sectional analysis, a lower amplitude is associated with elevated inflammation (Odds ratio Q4 vs Q1 (95% Confidence interval): 1.65 (1.22, 2.24)). In prospective analysis, an earlier acrophase (<12:30) is associated with a two-fold increase in the risk of developing elevated inflammation over four years of follow up (2.08 (1.02, 4.23)). No individual inflammatory markers are associated with rest-activity rhythms. Our findings suggest that rest-activity rhythm characteristics predicts elevated inflammation

The association between sleep patterns and obesity in older adults.

BackgroundReduced sleep duration has been increasingly reported to predict obesity. However, timing and regularity of sleep may also be important. In this study, the cross-sectional association between objectively measured sleep patterns and obesity was assessed in two large cohorts of older individuals.MethodsWrist actigraphy was performed in 3053 men (mean age: 76.4 years) participating in the Osteoporotic Fractures in Men Study and 2985 women (mean age: 83.5 years) participating in the Study of Osteoporotic Fractures. Timing and regularity of sleep patterns were assessed across nights, as well as daytime napping.ResultsGreater night-to-night variability in sleep duration and daytime napping were associated with obesity independent of mean nocturnal sleep duration in both men and women. Each 1 h increase in the standard deviation of nocturnal sleep duration increased the odds of obesity 1.63-fold (95% confidence interval: 1.31-2.02) among men and 1.22-fold (95% confidence interval: 1.01-1.47) among women. Each 1 h increase in napping increased the odds of obesity 1.23-fold (95% confidence interval: 1.12-1.37) in men and 1.29-fold (95% confidence interval: 1.17-1.41) in women. In contrast, associations between later sleep timing and night-to-night variability in sleep timing with obesity were less consistent.ConclusionsIn both older men and women, variability in nightly sleep duration and daytime napping were associated with obesity, independent of mean sleep duration. These findings suggest that characteristics of sleep beyond mean sleep duration may have a role in weight homeostasis, highlighting the complex relationship between sleep and metabolism

The roles of TNF-α and the soluble TNF receptor I on sleep architecture in OSA

Patients with obstructive sleep apnea (OSA) have been described to have increased levels of inflammatory cytokines (particularly TNF-α) and have severely disturbed sleep architecture. Serum inflammatory markers, even in normal individuals, have been associated with abnormal sleep architecture. Not much is known about the role the TNF receptor plays in the inflammation of OSA nor if it is associated with changes in sleep architecture or arousals during the night. We hypothesized that the TNF receptor might play an important role in the inflammation as well as sleep architecture changes in patients with OSA. Thirty-six patients with diagnosed (AHI > 15) but untreated OSA were enrolled in this study. Baseline polysomnograms as well as TNF-α and soluble TNF receptor I (sTNF-RI) serum levels were obtained on all patients. We evaluated the association between serum levels of TNF-α and sTNF-RI with various polysomongraphic characteristics, including sleep stages and EEG arousals. sTNF-RI levels were significantly correlated with snore arousals (r value 0.449, p value 0.009), spontaneous movement arousals (r value 0.378, p value 0.025), and periodic limb movement arousals (r value 0.460, p value 0.008). No statistically significant correlations were observed with TNF-α to any polysomnographic variables. To control for statistical significance with multiple comparisons, a MANOVA was performed with TNF-α and sTNF-RI as dependent variables and sleep architecture measures and arousals as independent variables. The model for sTNF-RI was statistically significant (F value 2.604, p value 0.03), whereas the model for TNF-α was not, suggesting sleep quality significantly affects sTNF-RI. Hierarchal linear regression analysis demonstrated that sTNF-RI was independently associated with spontaneous movement arousal index scores after controlling for age, body mass index, and sleep apnea severity. These findings suggest that sTNF-RI is associated with arousals during sleep, but not with other measures in patients with OSA

Principles of practice parameters for the treatment of sleep disordered breathing in the elderly and frail elderly: the consensus of the International Geriatric Sleep Medicine Task Force

Sleep disordered breathing (SDB) is a leading cause of morbidity worldwide. Its prevalence increases with age. Due to the demographic changes in industrial societies, pulmonologists and sleep physicians are confronted with a rapidly growing number of elderly SDB patients. For many physicians, it remains unclear how current guidelines for SDB management apply to elderly and frail elderly patients. The goal of this consensus statement is to provide guidance based on published evidence for SDB treatment in this specific patient group. Clinicians and researchers with expertise in geriatric sleep medicine representing several countries were invited to participate in a task force. A literature search of PubMed from the past 12 years and a systematic review of evidence of studies deemed relevant was performed. Recommendations for treatment management of elderly and frail elderly SDB patients based on published evidence were formulated via discussion and consensus. In the last 12 years, there have been surprisingly few studies examining treatment of SDB in older adults and even fewer in frail older adults. Studies that have been conducted on the management of SDB in the older patient population were rarely stratified for age. Studies in SDB treatment that did include age stratification mainly focused on middle-aged and younger patient groups. Based on the evidence that is available, this consensus statement highlights the treatment forms that can be recommended for elderly SDB patients and encourages treatment of SDB in this large patient group

Sleep-Disordered Breathing in Alcoholics: Association with Age

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66156/1/j.1530-0277.1993.tb05224.x.pd

Sleep analysis for elderly care using a low-resolution visual sensor network

Nearly half of the senior citizens report difficulty initiating and maintaining sleep. Frequent visits to the bathroom in the middle of the night is considered as one of the major reasons for sleep disorder. This leads to serious diseases such as depression and diabetes. In this paper, we propose to use a network of cheap low-resolution visual sensors (30 x 30 pixels) for long-term activity analysis of a senior citizen in a service flat. The main focus of our research is on elderly behaviour analysis to detect health deterioration. Specifically, this paper treats the analysis of sleep patterns. Firstly, motion patterns are detected. Then, a rule-based approach on the motion patterns is proposed to determine the wake up time and sleep time. The nightly bathroom visit is identified using a classification-based model. In our evaluation, we performed experiments on 10 months of real-life data. The ground truth is collected from the diaries in which the senior citizen wrote down his sleep time and wake up time. The results show accurate extraction of the sleep durations with an overall Mean Absolute Error (MAE) of 22.91 min and Spearman correlation coefficient of 0.69. Finally, the nightly bathroom visits analysis indicate sleep disorder in several nights