Minority Breast Cancer Survivors: The Association between Race/Ethnicity, Objective Sleep Disturbances, and Physical and Psychological Symptoms

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Abstract

Background . Limited research has been conducted on the moderating effect of race/ethnicity on objective sleep disturbances in breast cancer survivors (BCSs). Objective . To explore racial/ethnic differences in objective sleep disturbances among BCSs and their relationship with self-reported symptoms. Intervention/Methods . Sleep disturbance and symptoms were measured using actigraphy for 72 hours and self-reported questionnaires, respectively, among 79 BCSs. Analysis of covariance, Pearson’s correlation, and multivariate regression were used to analyze data. Results . Sixty (75.9%) participants listed their ethnicity as white, non-Hispanic and 19 (24.1%) as minority. Total sleep time was 395.9 minutes for white BCSs compared to 330.4 minutes for minority BCSs. Significant correlations were seen between sleep onset latency (SOL) and depression, SOL and fatigue, and sleep efficiency (SE) and fatigue among minority BCSs. Among white BCSs, significant correlations were seen between SE and pain and wake after sleep onset (WASO) and pain. The association between depression and SOL and fatigue and SOL appeared to be stronger in minority BCSs than white BCSs. Conclusions . Results indicate that white BCSs slept longer than minority BCSs, and race/ethnicity modified the effect of depression and fatigue on SOL, respectively. Implications for Practice . As part of survivorship care, race/ethnicity should be included as an essential component of comprehensive symptom assessments.

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Recent epidemiologic studies have found that self-reported duration of sleep is associated with obesity, diabetes, hypertension, and mortality. The extent to which self reports of sleep duration are similar to objective measures and whether individual characteristics influence the degree of similarity are not known. Eligible participants at the Chicago site of the Coronary Artery Risk Development in Young Adults Study were invited to participate in a 2003-2005 ancillary sleep study; 82% (n = 669) agreed. Sleep measurements collected in 2 waves included 3 days each of wrist actigraphy, a sleep log, and questions about usual sleep duration. We estimate the average difference and correlation between subjectively and objectively measured sleep by using errors-in-variables regression models. Average measured sleep was 6 hours, whereas the average from subjective reports was 6.8 hours. Subjective reports increased on average by 34 minutes for each additional hour of measured sleep. Overall, the correlation between reported and measured sleep duration was 0.47. Our model suggests that persons sleeping 5 hours over-reported their sleep duration by 1.2 hours, and those sleeping 7 hours over-reported by 0.4 hours. The correlations and average differences between self-reports and measured sleep varied by health, sociodemographic, and sleep characteristics. In a population-based sample of middle-aged adults, subjective reports of habitual sleep are moderately correlated with actigraph-measured sleep, but are biased by systematic over-reporting. The true associations between sleep duration and health may differ from previously reported associations between self-reported sleep and health.

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Jodie M Dodd, Richard Lee, Karen Humphreys … (2001)

Since the publication of the original Symptom Management Model (Larson et al. 1994), faculty and students at the University of California, San Francisco (UCSF) School of Nursing Centre for System Management have tested this model in research studies and expanded the model through collegial discussions and seminars. In this paper, we describe the evidence-based revised conceptual model, the three dimensions of the model, and the areas where further research is needed. The experience of symptoms, minor to severe, prompts millions of patients to visit their healthcare providers each year. Symptoms not only create distress, but also disrupt social functioning. The management of symptoms and their resulting outcomes often become the responsibility of the patient and his or her family members. Healthcare providers have difficulty developing symptom management strategies that can be applied across acute and home-care settings because few models of symptom management have been tested empirically. To date, the majority of research on symptoms was directed toward studying a single symptom, such as pain or fatigue, or toward evaluating associated symptoms, such as depression and sleep disturbance. While this approach has advanced our understanding of some symptoms, we offer a generic symptom management model to provide direction for selecting clinical interventions, informing research, and bridging an array of symptoms associated with a variety of diseases and conditions. Finally, a broadly-based symptom management model allows the integration of science from other fields.