Evidence map›Paper›PMID 35135690›Full record

ArticleMayo Clinic proceedings2022

The Lifestyle-Related Cardiovascular Risk Is Modified by Sleep Patterns.

Qiying Song, Mengying Wang, Tao Zhou, Dianjianyi Sun, Hao Ma, Xiang Li, Yoriko Heianza, Lu Qi

Open access · greenAbstract read
In one paragraph

Article in Mayo Clinic proceedings, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.9field-weighted citation impact, top 3% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

19 citing papers in PubMed, 30 citations in OpenAlex.

  1. Shift work, genetic risk, and incident gout: a prospective cohort study in the UK Biobank.Archives of public health = Archives belges de sante publique · 2026
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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

8 authors at 1 institution in 2 countries.

Qiying SongDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA; Maternal-Fetal Medicine Institute, Shenzhen Baoan Women's and Children's Hospital, Jinan University, Shenzhen; Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.
Mengying WangDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA; Department of Epidemiology and Biostatistic, School of Public Health, Peking University, Beijing, China.
Tao ZhouDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA.
Dianjianyi SunDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA; Department of Epidemiology and Biostatistic, School of Public Health, Peking University, Beijing, China.
Hao MaDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA.
Xiang LiDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA.
Yoriko HeianzaDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA.
Lu QiDepartment of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA. Electronic address: lqi1@tulane.edu.
Tulane University · US

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Ning Liu · 2016 to 2026
$25.3M
RISK FACTORS FOR CVD IN WOMENR01HL034594 · NHLBI · TULANE UNIVERSITY OF LOUISIANA · PI JoAnn Elisabeth Manson, Lu Qi · 1985 to 2026
$13.8M
Nutrigenetics and Nutrigenomics for Precision Weight-Loss Diet InterventionsR01DK115679 · NIDDK · TULANE UNIVERSITY OF LOUISIANA · PI Lu Qi · 2018 to 2026
$5.3M
Common Genetic Variation and Quantitative Diabetes TraitsR01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2008 to 2014
$5.0M
Genetic Markers of CHD in Type 2 DiabetesR01HL071981 · NHLBI · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI QI, LU · 2003 to 2012
$4.9M
Obesity Genes, Energy Regulation in Response to Weight-Loss DietsR01DK091718 · NIDDK · TULANE UNIVERSITY OF LOUISIANA · PI QI, LU · 2012 to 2021
$4.5M
Weight-Loss Diet Intervention on Cardiometabolic Factors of Gut MicrobiotaR01DK100383 · NIDDK · TULANE UNIVERSITY OF LOUISIANA · PI QI, LU · 2014 to 2024
$4.2M
TOPMed Omics of Type 2 Diabetes and Quantitative TraitsUM1DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MANNING, ALISA KNODLE · 2021 to 2025
$3.8M
Rare Sequence Variation and Diabetes Quantitative TraitsU01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2015 to 2019
$3.6M
Genome-wide interactions with diet patterns on long-term weight changeR21HL126024 · NHLBI · TULANE UNIVERSITY OF LOUISIANA · PI QI, LU · 2015 to 2016
$421k
Dissecting the impact of forced displacement on Type Two DiabetesR21TW010790 · FIC · LEBANESE AMERICAN UNIVERSITY · PI QI, LU, ZALLOUA, PIERRE · 2018 to 2019
$308k
FIC NIH HHS R21 TW010790NHLBI NIH HHS R01 HL034594NHLBI NIH HHS R01 HL071981NHLBI NIH HHS R21 HL126024NIDDK NIH HHS R01 DK078616NIDDK NIH HHS R01 DK091718NIDDK NIH HHS R01 DK100383NIDDK NIH HHS R01 DK115679NIDDK NIH HHS U01 DK078616NIDDK NIH HHS UM1 DK078616NIGMS NIH HHS P20 GM109036
6 · The paper itself

Abstract

objectiveTo prospectively assess whether sleep patterns modified lifestyle-associated cardiovascular disease (CVD) risk. PATIENTS AND

methodsThis study included 393,690 participants without CVD at baseline measurements between March 13, 2006, and October 1, 2010, from UK Biobank. A lifestyle score was calculated on the basis of the 4 lifestyle factors (smoking, alcohol consumption, physical activity, and diet), and sleep patterns were constructed based on sleep duration, chronotype, insomnia, snoring, and daytime dozing.

resultsDuring a median follow-up of 8.93 years, we observed 10,218 incident CVD events, including 6595 myocardial infarctions (MIs) and 3906 strokes. We found that sleep patterns significantly modified the relations of the lifestyle score with incident CVD (P for interaction =.007) and MI (P for interaction =.004). Among participants with a poor sleep pattern, unfavorable lifestyle (per score increase) was associated with 25% (95% CI, 13% to 39%) and 29% (95% CI, 13% to 47%) increased risks for CVD and MI, while among participants with a healthy sleep pattern, unfavorable lifestyle was associated with 18% (95% CI, 15% to 21%) and 17% (95% CI, 13% to 21%) increased risks for CVD and MI.

conclusionOur results indicate that adherence to a healthy sleep pattern may attenuate the CVD risk associated with an unfavorable lifestyle.

Indexed as

Cardiovascular DiseasesHeart Disease Risk FactorsHumansLife StyleProspective StudiesRisk FactorsSleep

Identifiers

PMID35135690
PMCPMC8898293
OpenAlexW4210760202

What OpenQuestion holds

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Registered trials

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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.