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Poor sleep quality and lipid profile in a rural cohort (The Baependi Heart Study). | LitMetric

AI Article Synopsis

  • The study aimed to investigate the connection between cardiometabolic risk factors and subjective sleep quality, using the Pittsburgh Sleep Quality Index (PSQI), while controlling for factors like obstructive sleep apnea (OSA) and sleep duration.
  • A total of 573 participants from Brazil revealed that 50% experienced poor sleep quality, linking high PSQI scores to elevated levels of very-low-density lipoprotein (VLDL) and triglycerides, even after adjusting for OSA and other variables.
  • The findings suggest that poor lipid profiles are independently associated with poor sleep quality, particularly highlighting the impacts of sleep disturbances and daytime dysfunction on VLDL and triglyceride levels.

Article Abstract

Aim: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration.

Methods: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration).

Results: The sample mean age was 43 ± 16 years, 66% were female, and mean body mass index (BMI) was 26 ± 5 kg/m. Only 20% were classified as obese (BMI ≥30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score ≥5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apnea-hypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004).

Conclusion: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status.

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Source
http://dx.doi.org/10.1016/j.sleep.2018.12.028DOI Listing

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