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November–December, 2016Volumes 27-28, Pages 1–8
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Racial disparities in sleep: the role of neighborhood disadvantage

Thomas E. Fuller-Rowell
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Thomas E. Fuller-Rowell
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Affiliations

  • Department of Human Development and Family Studies, Auburn University, AL, USA

Correspondence

  • Corresponding author. Department of Human Development and Family Studies, 203 Spidle Hall, Auburn University, Auburn, AL, 36849, USA. Fax: +1 334 844 4515.
'Correspondence information about the author Thomas E. Fuller-Rowell
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Thomas E. Fuller-Rowell
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Affiliations

  • Department of Human Development and Family Studies, Auburn University, AL, USA

Correspondence

  • Corresponding author. Department of Human Development and Family Studies, 203 Spidle Hall, Auburn University, Auburn, AL, 36849, USA. Fax: +1 334 844 4515.
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David S. Curtis
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David S. Curtis
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Affiliations

  • Department of Human Development and Family Studies, Auburn University, AL, USA
,
Mona El-Sheikh
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Mona El-Sheikh
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  • Department of Human Development and Family Studies, Auburn University, AL, USA
,
David H. Chae
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David H. Chae
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  • Department of Human Development and Family Studies, Auburn University, AL, USA
,
Jennifer Morozink Boylan
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Jennifer Morozink Boylan
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Affiliations

  • Department of Health and Behavioral Sciences, University of Colorado Denver, USA
,
Carol D. Ryff
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Carol D. Ryff
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Affiliations

  • Department of Psychology, University of Wisconsin – Madison, WI, USA
Racial disparities in sleep: the role of neighborhood disadvantage
DOI: https://doi.org/10.1016/j.sleep.2016.10.008
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Highlights

  • •Racial disparities in sleep latency, duration, and efficiency were evident.
  • •Neighborhood disadvantage predicted waking after sleep onset (WASO).
  • •Neighborhood disadvantage accounted for 24% of race differences in WASO.
  • •Addressing neighborhood inequities may be key to reducing sleep disparities.

Abstract

Objective

Disparities in sleep duration and efficiency between Black/African American (AA) and White/European American (EA) adults are well-documented. The objective of this study was to examine neighborhood disadvantage as an explanation for race differences in objectively measured sleep.

Methods

Data were from 133 AA and 293 EA adults who participated in the sleep assessment protocol of the Midlife in the United States (MIDUS) study (57% female; Mean Age = 56.8 years, SD = 11.4). Sleep minutes, onset latency, and waking after sleep onset (WASO) were assessed over seven nights using wrist actigraphy. Neighborhood characteristics were assessed by linking home addresses to tract-level socioeconomic data from the 2000 US Census. Multilevel models estimated associations between neighborhood disadvantage and sleep, and the degree to which neighborhood disadvantage mediated race differences in sleep controlling for family socioeconomic position and demographic variables.

Results

AAs had shorter sleep duration, greater onset latency, and higher WASO than EAs (ps < 0.001). Neighborhood disadvantage was significantly associated with WASO (B = 3.54, p = 0.028), but not sleep minutes (B = -2.21, p = 0.60) or latency (B = 1.55, p = 0.38). Furthermore, race was indirectly associated with WASO via neighborhood disadvantage (B = 4.63, p = 0.035), which explained 24% of the race difference. When measures of depression, health behaviors, and obesity were added to the model, the association between neighborhood disadvantage and WASO was attenuated by 11% but remained significant.

Conclusion

Findings suggest that neighborhood disadvantage mediates a portion of race differences in WASO, an important indicator of sleep efficiency.

Keywords:

Health inequalities, Race, Sleep disparities, Sleep efficiency, Actigraphy, Neighborhood inequality

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☆This research was funded in part by an NIH R01 grant from the National Institute on Aging (1RO1AG047154-01A1). The MIDUS 1 study (Midlife in the U.S.) was supported by the John D. and Catherine T. MacArthur Foundation Research Network on Successful Midlife Development. MIDUS 2 research was supported by a grant from the National Institute on Aging ( P01-AG020166 ) to conduct a longitudinal follow-up of the MIDUS 1 investigation. Biomarker and sleep data were further supported by the following grants: M01-RR023942 (Georgetown) and M01-RR00865 (UCLA) from the General Clinical Research Centers Program, and UL1TR000427 (UW) from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health.

© 2016 Elsevier B.V. All rights reserved.
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November–December, 2016Volumes 27-28, Pages 1–8