Evidence map›Paper›PMID 35399945›Full record

ArticleFrontiers in endocrinology2022

Shared Genetic Basis and Causal Relationship Between Television Watching, Breakfast Skipping and Type 2 Diabetes: Evidence From a Comprehensive Genetic Analysis.

Dongze Chen, Hanyu Wu, Xinpei Wang, Tao Huang, Jinzhu Jia

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 9% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

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  10. Sedentary Behavior Patterns of the Hungarian Adult Population.International journal of environmental research and public health · 2023
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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

5 authors at 1 institution in 1 country.

Dongze ChenDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China.
Hanyu WuDepartment of Bioinformatics, School of Life Science, Peking University, Beijing, China.
Xinpei WangDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China.
Tao HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Jinzhu JiaDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Epidemiological investigations have established unhealthy lifestyles, such as excessive leisurely sedentary behavior (especially TV/television watching) and breakfast skipping, increase the risk of type 2 diabetes (T2D), but the causal relationship is unclear. We aimed to understand how single nucleotide variants contribute to the co-occurrence of unhealthy lifestyles and T2D, thereby providing meaningful insights into disease mechanisms. Methods: Combining summary statistics from genome-wide association studies (GWAS) on TV watching ( Results: HDL-method showed that T2D shared a strong genetic correlation with TV watching ( Conclusions: Our findings provide strong evidence of shared genetics and causation between TV watching and T2D and facilitate our identification of common genetic architectures shared between them.

Indexed as

Diabetes Mellitus, Type 2Feeding BehaviorScreen TimeBreakfastGenome-Wide Association StudyHumansMendelian Randomization AnalysisTelevisionbreakfast skippinggenome genetic correlationMendelian randomizationTV watchingtype 2 diabetes

Identifiers

PMID35399945
PMCPMC8988136
OpenAlexW4221039398

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.