Evidence map›Paper›PMID 39968409›Full record

ArticleFrontiers in psychiatry2024

Association between weekend catch-up sleep and hypertension of the United States population from 2017 to 2020: a cross-sectional study.

Yan Luo, Qingyuan Li, Tong Feng, Shasha Meng, Ran Duan

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yan LuoRespiratory Department, Chengdu Xindu District Second People's Hospital, Chengdu, China.
Qingyuan LiSchool of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Tong FengThe Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Shasha MengSchool of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Ran DuanSchool of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hypertension is a prevalent cardiovascular risk factor that significantly contributes to morbidity and mortality worldwide. Previous studies have highlighted the role of inadequate sleep during weekdays in the development of hypertension. However, the potential mitigative effects of weekend catch-up sleep (WCS) on hypertension have been less explored. Methods: This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2017-2020, focusing on American adults. We assessed the association between WCS (defined as the difference in sleep duration between weekend and weekday) and the presence of hypertension. Participants were classified into two groups based on their WCS duration: none (below 1 hours), yes (over 1 hours). Multivariable logistic regression models adjusted for potential confounders such as age, gender, Body mass index (BMI), and lifestyle factors were utilized to explore this association. A Generalized Additive Model (GAM) was employed to generate smooth curves for a nuanced analysis of the nonlinear relationship. Results: The findings indicated that moderate WCS (less than 4 hours) was significantly associated with a reduced risk of hypertension, while excessive WCS (greater than 4 hours) showed no significant protective benefits. Conclusion: Moderate weekend catch-up sleep could serve as an effective intervention to mitigate hypertension risk, especially in populations with restricted weekday sleep. These results suggest the potential for integrating sleep management strategies into public health recommendations to address hypertension. Future longitudinal studies are needed to confirm these findings and clarify the mechanisms underlying the relationship between WCS and hypertension risk.

Indexed as

cross-sectional studyhypertensionNHANESsleep patternsweekend catch-up sleep

Identifiers

PMID39968409
PMCPMC11833448

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.