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Why CVD risk is linked to poor sleep quality

researchsnappy by researchsnappy
February 26, 2020
in Healthcare Research
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Why CVD risk is linked to poor sleep quality
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Women who have poor sleep quality are also eating more food and have lower-quality diets – all of which are factors that increase cardiovascular disease (CVD) risk. Sleep quality includes several factors related to the ability to fall asleep and stay asleep.

The cross-sectional study appeared in the Journal of the American Heart Association. The authors aimed to examine the associations of both subclinical and clinical measures of sleep quality (including overall sleep quality, sleep-onset latency, and insomnia) with energy and macronutrient intakes as well as with intake of specific food associated with CVD risk. 

Methods
Data for the study were obtained from women who were enrolled in a 1-year prospective cohort study of sleep and CVD risk as part of the American Heart Association Go Red for Women Strategically Focused Research Network. Eligible participants were nonpregnant women between ages 20 and 79 who were recruited from New York-Presbyterian Hospital/Columbia University Irving Medical Center. 

The authors measured habitual sleep quality at baseline through two validated, self-report tools: the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI). The PQSI assesses sleep patterns over the past month, while the ISI is composed of seven items measuring five different components of insomnia (severity of insomnia symptoms, satisfaction with current sleep, extent to which current sleep interferes with daily function, perception of sleep problems, and the extent to which sleep problems are worrisome). Diet was assessed using the Block Brief Food Frequency Questionnaire (FFQ), which includes a list of approximately 70 food items that are consumed by multiple racial and ethnic groups and measures how frequently each item was consumed over the past year and the amount eaten. The authors used linear regression models adjusted for confounding variables to test relationships between sleep and diet variables. 

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