BS Summary: This article contains 20 faulty reasoning types, including Representativeness Heuristic, Optimism Bias, and Confirmation Bias, with Appeal to Authority as the most egregious example at 14.7% saturation with 92 hits. Analysis detected 806 faulty-reasoning hits from 627 analyzed words, generating a BS Score of 36.2% and a BS Rank of 23% (16,943 of 21,886 articles). This article is better (less manipulative) than 77.40% of the article peer group.
Early bird, night owl or something else?
Five patterns may define how we sleep
New research identifies five distinct sleep subtypes, revealing links between brain patterns, behavior and health
By Kate Graham-Shaw edited by Sarah Lewin Frasier
ArtistGNDphotography/Getty Images
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For decades, many scientists thought our sleeping habits fit neatly into two categories: we were either night owls or early birds , with the latter group considered healthier overall.
New research, though, shows there's more to it than that.
In a study published in Nature Communications, researchers found five different sleeping pattern subtypes , each with its own distinct brain-imaging patterns, behaviors and health outcomes.
These findings could be useful for understanding how modern sleep patterns affect our health, says Sonja Schütz, a neurologist who studies sleep medicine at University of Michigan Health.
Researchers at McGill University trained a machine-learning algorithm to analyze neuroimaging data, questionnaire answers and health reports from 27,000 U.K.
Biobank participants.
The algorithm examined participants' chronotypes, or typical sleep and wake patterns over 24-hour periods, and found patterns in brain imaging corresponding to five distinct groups.
The marked differences piqued the interest of the study's lead author, neuroscientist Le Zhou: The participants "actually have different biological patterns showing in their brain images."
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Three of the five subtypes were different flavors of night owls, and two were early birds-each with a grab bag of different properties.
The first night owl subtype, which Zhou refers to as "high-performance night owls," was more likely to engage in risky behaviors and have emotional regulation difficulties but also higher cognitive performance.
In contrast, the second subtype, which he calls "vulnerable night owls," demonstrated more laid-back tendencies, with less physical activity and a greater chance of smoking.
This subtype was associated with the most health issues, including depression, heart disease and diabetes, consistent with preexisting ideas about the overall "night owl" group.
The final, "male-biased" night owl subtype skewed more toward men and was associated with higher cigarette and alcohol consumption, higher testosterone levels and higher cannabis use than other subtypes.
This specific subtype could help to explain the traditional night owl chronotype's commonness in men.
The "classical early bird" subtype, as Zhou puts it, matched traditional early bird traits, showing efficient brain networks, low alcohol and smoking rates, low risk-taking and more emotional stability.
People in this group were the healthiest overall.
The "female-biased" early bird subtype, however, which was skewed toward women, was linked to higher rates of depression symptoms, lower testosterone levels and more menstrual issues than the classical early bird.
These chronotypes likely come from complex interactions between people's genetics, hormone fluctuations and environment, which includes aspects such as their work schedules or light exposure.
But it's unclear exactly how all those factors cause a specific sleep pattern.
Johns Hopkins University School of Medicine neurologist Charlene Gamaldo, who also specializes in sleep and was not involved in the study, notes that the research highlights how machine learning and large datasets can help advance our understanding of sleep chronotypes.
She also emphasizes that because the study relied on participants' self-reported sleep information and associations instead of cause-and-effect relationships, more research is needed to determine whether the chronotype itself explains the brain differences found or whether other factors may be responsible.
"We cannot say from this data alone whether the brain differences or health outcomes are cause or the consequences," Zhou adds.
His team is now comparing the genetic data of people with different chronotypes to further investigate such factors.
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86%flagged-word coverageLe Zhou
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