Back

Community-based causal evidence that high habitual caffeine consumption alters distinct polysomnography-derived sleep variables

Stucky, B.; Henckel, L.; Maathuis, M. H.; Haba-Rubio, J.; Marques-Vidal, P.; Siclari, F.; Heinzer, R.; Landolt, H.-P.

2024-12-13 public and global health
10.1101/2024.12.11.24318776 medRxiv
Show abstract

Caffeine is the most widely consumed psychoactive substance in the World and acutely impairs sleep quality when studied in the laboratory. The repercussions on sleep of chronic caffeine intake, which is common in society, are unknown. Because adequate sleep is important for general health, we explored causal effects of habitual caffeine intake on objective and subjective sleep quality with two-sample Mendelian Randomization and matching methods. We analyzed large community-based datasets taken from the UK Biobank (n=485,511) and HypnoLaus (n=1,702) cohorts. We consistently show that intake of four or more caffeinated beverages daily shortens total sleep time compared to three or fewer caffeinated drinks per day. While we found shorter sleep with all models, the estimated reductions varied from 11-229 minutes, likely due to modest instrument strengths. A concurrent increase in sleep intensity indicates at least partial compensation. The findings suggest that high daily caffeine intake causally alters sleep patterns in the general population.

Published in Journal of Psychopharmacology (predicted rank #10) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 9%
18.3%
Similar papers in this journal
2
Scientific Reports
○ 3612 papers in training set
Top 2%
14.7%
Similar papers in this journal
3
eLife
● 5828 papers in training set
Top 8%
11.8%
Similar papers in this journal
4
Sleep
◐ 58 papers in training set
Top 0.2%
6.2%
Similar papers in this journal
50% of probability mass above
5
Sleep Medicine
○ 19 papers in training set
Top 0.1%
6.2%
Similar papers in this journal
6
BMC Medicine
○ 176 papers in training set
Top 0.8%
4.0%
7
Communications Biology
○ 993 papers in training set
Top 5%
3.4%
8
npj Digital Medicine
○ 118 papers in training set
Top 1%
3.2%
9
iScience
○ 1154 papers in training set
Top 10%
2.6%
Journal of Psychopharmacology · published here
○ 17 papers in training set
Top 0.1%
2.1%
11
Nature Genetics
○ 286 papers in training set
Top 3%
1.7%
12
Translational Psychiatry
○ 260 papers in training set
Top 3%
1.7%
13
Science Advances
● 1243 papers in training set
Top 22%
1.5%
14
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 31%
1.4%
15
CHEST
○ 14 papers in training set
Top 0.3%
1.1%
16
PLOS ONE
● 5266 papers in training set
Top 53%
1.1%
17
PLOS Genetics
● 862 papers in training set
Top 9%
1.1%
18
Nature Medicine
○ 125 papers in training set
Top 3%
1.1%
19
eClinicalMedicine
○ 77 papers in training set
Top 2%
1.0%
20
Communications Medicine
○ 113 papers in training set
Top 4%
0.8%
21
Sleep Advances
◐ 11 papers in training set
Top 0.3%
0.8%
22
Psychiatry and Clinical Neurosciences
○ 11 papers in training set
Top 0.3%
0.6%
23
eBioMedicine
○ 183 papers in training set
Top 8%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.