Breast Cancer Collaborative Registry informs understanding of factors predicting sleep quality

Research output: Contribution to journalArticle

Abstract

Significance: Poor sleep quality is a common and persistent problem reported by women with breast cancer (BC). Empirical evidence identifies many risk factors for self-reported sleep deficiency, but inconsistencies limit translation to practice. Purpose: To increase understanding of risk factors predicting self-reported poor sleep quality in women with BC who completed the Breast Cancer Collaborative Registry (BCCR) questionnaire. Methods: This cross-sectional study recruited women with a first diagnosis of BC (n = 1302) at five sites in Nebraska and South Dakota. Women completed the BCCR that includes numerous variables as well as the Pittsburgh Sleep Quality Index (PSQI) and SF36v2 (n = 1260). Descriptive statistics and non-parametric correlations were used to determine associations and create predictive models of sleep quality with BCCR variables and SF36v2 subscales. Results: Most women were white (93.7%) and married (71.5%); mean age was 60.1 (21–90) years. Poor sleep was self-reported by 53% of women. Seven variables were highly associated with sleep quality (p ≤ 0.001). The first model found younger age, lower physical activity, and higher fatigue were the strongest combined and independent variables predicting poor sleep quality (F = 23.0 (p <.001), R2 = 0.103). Participants self-reported lower health status on most SF36v2 subscales [Z = 44.9 (11.6) to 49.1 (10.1)]. A second model found that all subscales were predictors of poor sleep; vitality, mental health, bodily pain, and general health were the strongest predictors (F = 101.3 (p <.001), R2 = 0.26). Conclusions: Results confirm previously identified risk factors and reveal inconsistencies in other variables. Clinicians need to routinely screen for the identified risk factors of self-reported poor sleep quality.

Original languageEnglish (US)
JournalSupportive Care in Cancer
DOIs
StateAccepted/In press - Jan 1 2018

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Registries
Sleep
Breast Neoplasms
Nonparametric Statistics
Health Status
Fatigue
Mental Health
Cross-Sectional Studies
Exercise
Pain
Health

Keywords

  • Mental health
  • Physical health
  • Quality of life
  • Sleep deficiency
  • Sleep quality
  • Symptoms

ASJC Scopus subject areas

  • Oncology

Cite this

@article{aa6edd4d019f4d20a3fe57ecb4279407,
title = "Breast Cancer Collaborative Registry informs understanding of factors predicting sleep quality",
abstract = "Significance: Poor sleep quality is a common and persistent problem reported by women with breast cancer (BC). Empirical evidence identifies many risk factors for self-reported sleep deficiency, but inconsistencies limit translation to practice. Purpose: To increase understanding of risk factors predicting self-reported poor sleep quality in women with BC who completed the Breast Cancer Collaborative Registry (BCCR) questionnaire. Methods: This cross-sectional study recruited women with a first diagnosis of BC (n = 1302) at five sites in Nebraska and South Dakota. Women completed the BCCR that includes numerous variables as well as the Pittsburgh Sleep Quality Index (PSQI) and SF36v2 (n = 1260). Descriptive statistics and non-parametric correlations were used to determine associations and create predictive models of sleep quality with BCCR variables and SF36v2 subscales. Results: Most women were white (93.7{\%}) and married (71.5{\%}); mean age was 60.1 (21–90) years. Poor sleep was self-reported by 53{\%} of women. Seven variables were highly associated with sleep quality (p ≤ 0.001). The first model found younger age, lower physical activity, and higher fatigue were the strongest combined and independent variables predicting poor sleep quality (F = 23.0 (p <.001), R2 = 0.103). Participants self-reported lower health status on most SF36v2 subscales [Z = 44.9 (11.6) to 49.1 (10.1)]. A second model found that all subscales were predictors of poor sleep; vitality, mental health, bodily pain, and general health were the strongest predictors (F = 101.3 (p <.001), R2 = 0.26). Conclusions: Results confirm previously identified risk factors and reveal inconsistencies in other variables. Clinicians need to routinely screen for the identified risk factors of self-reported poor sleep quality.",
keywords = "Mental health, Physical health, Quality of life, Sleep deficiency, Sleep quality, Symptoms",
author = "Berger, {Ann Malone} and Kupzyk, {Kevin A} and Djalilova, {Dilorom M.} and Cowan, {Kenneth H}",
year = "2018",
month = "1",
day = "1",
doi = "10.1007/s00520-018-4417-5",
language = "English (US)",
journal = "Supportive Care in Cancer",
issn = "0941-4355",
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TY - JOUR

T1 - Breast Cancer Collaborative Registry informs understanding of factors predicting sleep quality

AU - Berger, Ann Malone

AU - Kupzyk, Kevin A

AU - Djalilova, Dilorom M.

AU - Cowan, Kenneth H

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Significance: Poor sleep quality is a common and persistent problem reported by women with breast cancer (BC). Empirical evidence identifies many risk factors for self-reported sleep deficiency, but inconsistencies limit translation to practice. Purpose: To increase understanding of risk factors predicting self-reported poor sleep quality in women with BC who completed the Breast Cancer Collaborative Registry (BCCR) questionnaire. Methods: This cross-sectional study recruited women with a first diagnosis of BC (n = 1302) at five sites in Nebraska and South Dakota. Women completed the BCCR that includes numerous variables as well as the Pittsburgh Sleep Quality Index (PSQI) and SF36v2 (n = 1260). Descriptive statistics and non-parametric correlations were used to determine associations and create predictive models of sleep quality with BCCR variables and SF36v2 subscales. Results: Most women were white (93.7%) and married (71.5%); mean age was 60.1 (21–90) years. Poor sleep was self-reported by 53% of women. Seven variables were highly associated with sleep quality (p ≤ 0.001). The first model found younger age, lower physical activity, and higher fatigue were the strongest combined and independent variables predicting poor sleep quality (F = 23.0 (p <.001), R2 = 0.103). Participants self-reported lower health status on most SF36v2 subscales [Z = 44.9 (11.6) to 49.1 (10.1)]. A second model found that all subscales were predictors of poor sleep; vitality, mental health, bodily pain, and general health were the strongest predictors (F = 101.3 (p <.001), R2 = 0.26). Conclusions: Results confirm previously identified risk factors and reveal inconsistencies in other variables. Clinicians need to routinely screen for the identified risk factors of self-reported poor sleep quality.

AB - Significance: Poor sleep quality is a common and persistent problem reported by women with breast cancer (BC). Empirical evidence identifies many risk factors for self-reported sleep deficiency, but inconsistencies limit translation to practice. Purpose: To increase understanding of risk factors predicting self-reported poor sleep quality in women with BC who completed the Breast Cancer Collaborative Registry (BCCR) questionnaire. Methods: This cross-sectional study recruited women with a first diagnosis of BC (n = 1302) at five sites in Nebraska and South Dakota. Women completed the BCCR that includes numerous variables as well as the Pittsburgh Sleep Quality Index (PSQI) and SF36v2 (n = 1260). Descriptive statistics and non-parametric correlations were used to determine associations and create predictive models of sleep quality with BCCR variables and SF36v2 subscales. Results: Most women were white (93.7%) and married (71.5%); mean age was 60.1 (21–90) years. Poor sleep was self-reported by 53% of women. Seven variables were highly associated with sleep quality (p ≤ 0.001). The first model found younger age, lower physical activity, and higher fatigue were the strongest combined and independent variables predicting poor sleep quality (F = 23.0 (p <.001), R2 = 0.103). Participants self-reported lower health status on most SF36v2 subscales [Z = 44.9 (11.6) to 49.1 (10.1)]. A second model found that all subscales were predictors of poor sleep; vitality, mental health, bodily pain, and general health were the strongest predictors (F = 101.3 (p <.001), R2 = 0.26). Conclusions: Results confirm previously identified risk factors and reveal inconsistencies in other variables. Clinicians need to routinely screen for the identified risk factors of self-reported poor sleep quality.

KW - Mental health

KW - Physical health

KW - Quality of life

KW - Sleep deficiency

KW - Sleep quality

KW - Symptoms

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JO - Supportive Care in Cancer

JF - Supportive Care in Cancer

SN - 0941-4355

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