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An Exploration of Clinical, Behavioral, and Community Factors Associated with Sleep Duration and Efficiency Among Middle-aged Black/African American Smokers

Overview
Journal Sleep Health
Specialty Psychiatry
Date 2021 Mar 20
PMID 33741321
Citations 2
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Abstract

Study Objectives: We examined the most important correlates to sleep duration and efficiency from a comprehensive array of multilevel factors.

Methods: Baseline data from a cohort of 216 Black/African American smokers aged 40-65 years were examined. The binary outcomes of healthy sleep duration (6-8 h/night) and efficiency (≥85%) were ascertained from 14 consecutive days of actigraphy. Seventy-three independent variables from socio-demographic, individual behavioral, individual physiological, interpersonal, and community domains were assessed. Random survival forest decision trees were generated for each outcome, and variable importance metrics used to rank the predictive abilities of exposure variables. The 5 most predictive exposure variables for each outcome were entered into a regression model of the respective outcome (with age and sex).

Results: Study participants (N = 216) had a mean age of 54.57 years (SD = 6.17) and 57% were male. Healthy sleep duration was achieved by 56.5% and healthy sleep efficiency by 13.6% of the sample. Regression models showed every additional minute of light physical activity was associated with 1% increased odds, while every unit decrease in the inflammation marker of interleukin-8 was associated with 12% increased odds, of achieving a healthy sleep duration. Every unit increase in total social support was associated with a 34% increased odds, while every unit increase in the hazardous drinking score corresponded with 30% decreased odds, of achieving healthy sleep efficiency.

Conclusions: Light physical activity, social support, and alcohol consumption may be key modifiable intervention targets to improving sleep duration and sleep efficiency in this population.

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#NoJusticeNoSleep: Critical intersections of race-ethnicity, income, education, and social determinants in sleep health disparities.

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