Answered vital questions
Q: What did this study’s review of rest and health reveal?
A: An analysis of sleep data from over 88,000 people found that poor sleep patterns—especially irregular bedtimes and unstable circadian rhythms—were linked to elevated risk for 172 different diseases.
Which sleeping behaviors were the most dangerous?
A: Going to bed after 12:30 a.m. and having low sleep regularity significantly raised the risk for serious conditions like liver cirrhosis and gangrene, among many others.
Q: How about getting a longer nap? Was it harmful?
A: Contrary to prior belief, objective data showed long sleep wasn’t linked to poor health in most cases; many self-reported “long sleepers” were actually sleeping very little, just lying in bed longer.
Summary: In the most extensive study of its kind, scientists identified a link between irregular sleep patterns and a higher risk of 172 illnesses. The study used goal sleeping data from eeg devices worn by over 88, 000 people for almost seven decades to identify the most detrimental behaviors.
People who slept irregularly had significantly higher risk of developing serious diseases like infection and liver cirrhosis. The findings challenge earlier hypotheses about how much sleep can be harmful and highlight sleep regularity as a key component of long-term health, rather than just duration.
Important Information
- Common Impact: Bad sleep quality was linked to 172 illnesses.
- High Risk: Random bedtime increases the risk of liver cirrhosis 2.57 times, and lower rhythm stability increases the risk of gangrene 2.61 times.
- Myth discredited: The majority of “long sleeping” actually had less than average rest, not more.
Origin: Health Data Science
A groundbreaking global study, which was just published in Health Data Science, analyzed achievement sleep data from 88, 461 UK Biobanks, and found that sleep characteristics and 172 diseases were related to significant differences.
Rest regularity, such as sleep consistency and daily music stability, are identified by researchers from Peking University and Army Medical University as an underreported but important factor in the risk of developing disease.
Researchers found that over 20 % of 92 conditions ‘ danger was due to bad sleeping habits using actigraphy information over an average of 6.8 times. Notably, a 2.57-fold higher risk of liver cirrhosis was associated with irregular bedtime ( after 00:30 ), while a 2.61-fold higher risk of gangrene was associated with a 2.61-fold higher risk of gangrene.
Interestingly, the study challenges earlier promises that “long sleep” ( more than 9 hours ) are dangerous. Much sleep and heart disease have been linked to by personal research, but objective research just revealed this association in one disease. Classification may be to blame: 21.67 % of “long sleeping” actually slept less than 6 hours, which suggests that bed time is frequently confused with actual nap time.
Our results highlight the underreported value of regularity of rest, according to Prof. Shengfeng Wang, senior author of the study. It’s time to enhance our definition of good rest beyond just its length.
The team identified aggressive pathways as a potential genetic link and confirmed many associations in U.S. populations. Future research will examine the link between sleep interventions and severe illness results.
About this information on slumber and health
Author: Mai Wang
Source: Health Data Science
Contact: Mai Wang – Health Data Science
Image: The image is credited to Neuroscience News
Open access to original analysis
Yimeng , Wang et al.,” Phenome-wide analysis of diseases in relation to objectively measured sleeping attributes and contrast with personal sleep qualities in 88, 461 Grownups.” Data science for the wellness
Abstract
In 88, 461 adults, phenome-wide study of illnesses in relation to objectively measured sleeping parameters and a contrast with personal sleep parameters
Background: Although it has been suggested that sleep characteristics are related to a variety of diseases, the majority of research is based on personal sleep measurements.
We looked at whether the illness spectrum related to imperative sleep traits differs from that related to personal sleep traits in terms of associations between accelerometer-derived goal sleep traits and diseases across physiological systems.  ,
Methods: In 88, 461 UK Biobank ( UKB ) adults wearing accelerometers, multiple parameters of sleep were objectively determined: ( a ) nocturnal sleep duration and onset timing, ( b ) sleep rhythm ( relative amplitude and interdaily stability ), and ( c ) sleep fragmentation ( sleep efficiency and waking numbers ).
Using the Cox model, the estimated associations with 10th Revision-decoded disorders during a follow-up were compared to those from a published literature search of intuitively determined sleep qualities and conditions.
The newly identified associations that had previously been unreported by previous studies were validated using National Health and Nutrition Examination Survey ( NHANES ) data. Reanalysis was carried out in UKB using subjective sleep traits, stratified by objective measurements, for the meta-analysis-reported associations ( with subjective sleep traits ) that were negative ( with objective sleep traits ) in our study.  ,
Benefits: During the typical 6.8-year follow-up, 172 conditions were linked to sleeping characteristics. Among them, 42 showed at least doubled disease risk, including age-related physical debility ( lowest versus highest quartile of relative amplitude, hazard ratio]HR] = 3.36, 95 % confidence interval]CI]: 2.25, 5.02 ), gangrene ( lowest versus highest quartile of interdaily stability, HR = 2.61, 95 % CI: 1.41, 4.83 ), and fibrosis and cirrhosis of the liver ( sleep onset timing ≥0030 versus 2300 to 2330, HR = 2.57, 95 % CI: 1.42, 4.67 ).
A total of 92 diseases had >, 20 % burden attributable to sleep, such as Parkinson’s disease ( 37.05 %, 95 % CI: 21.02 %, 49.83 % ), type 2 diabetes ( 36.12 %, 95 % CI: 29.00 %, 42.52 % ), and acute kidney failure ( 21.85 %, 95 % CI: 13.47 %, 29.42 % ). Notably, 83 ( 48.3 % ) disease associations were sleep rhythm specific, which is unusual from the literature on sleep duration-focused subjective-measure studies.
Review in UKB revealed a contamination of realistically little sleepers in self-report much sleepers, which led to false-positive associations in personal meta-analyses, including those for ischemic heart disease and melancholy disorder.
NHANES successfully replicated the newly discovered associations of slumber pattern with four diseases, including diabetes and chronic obstructive pulmonary disease. Leukocytes, eosinophils, and C-reactive proteins all had significant contributions to these newly identified sleep-disease associations, according to a counseling analysis.  ,
Conclusions: According to Goal Sleep Traits, a illness spectrum comparable to but not identical to that of Personal Sleep Traits. Goal measurement may be a beneficial complement to sleep–disease studies because it may help to overcome false-positive associations brought on by misclassification bias in some personal measurement, such as sleep duration. Given that a significant amount of disease burden was attributed to various sleep traits, complete control of various sleep characteristics may become important for health.
