Evidence map›Paper›PMID 39476038›Full record

ArticleArquivos brasileiros de cardiologia2024

Causal Relationship between Television Viewing Time, Cardiovascular Diseases, and Potential Mechanisms.

Mengjin Hu, Boyu Li, Jinggang Xia, Chunlin Yin, Yuejin Yang

Abstract read
In one paragraph

Article in Arquivos brasileiros de cardiologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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.

Mengjin HuXuanwu Hospital, Capital Medical University, Beijing - China.ORCID 0000-0003-0473-6077
Boyu LiXuanwu Hospital, Capital Medical University, Beijing - China.
Jinggang XiaXuanwu Hospital, Capital Medical University, Beijing - China.
Chunlin YinXuanwu Hospital, Capital Medical University, Beijing - China.
Yuejin YangFuwai Hospital, State Key Laboratory of Cardiovascular Disease, Beijing - China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the predominant leisure-time sedentary behavior, television viewing was documented to increase cardiovascular diseases in observational studies, yet the causal relationship and potential mechanisms remain to be determined.

objectivesTo systematically investigate the causal relationship between television viewing time, cardiovascular diseases, and potential mechanisms.

methodsWe conducted a two-sample Mendelian randomization (MR) analysis to estimate causal associations with cardiovascular diseases and biomarkers of cardiometabolic risk. The random inverse-variance weighted method was used as the primary estimate. To account for multiple comparisons, a Bonferroni correction p value for cardiovascular diseases and biomarkers of cardiometabolic risk was 0.0045 and 0.0024, respectively.

resultsGenetically instrumented television viewing time was associated with higher risks of type 2 diabetes (odd ratio [OR]=2.51; 95% confidence interval [CI]: 1.89-3.33; p<0.00001), hypertension (OR=2.11; 95% CI: 1.67-2.66; p<0.00001), coronary heart disease (OR=1.53; 95% CI: 1.23-1.91; p=0.00015), and heart failure (OR=1.42; 95% CI: 1.18-1.70; p=0.00017). Suggestive evidence of harmful associations was also observed for peripheral artery disease (OR=1.58; 95% CI: 1.07-2.34; p=0.02253) and ischemic stroke (OR=1.34; 95% CI: 1.10-1.63; p=0.00328). Biomarkers of cardiometabolic risk, including interleukin 10, leptin, visceral adipose, abdominal subcutaneous adipose, liver fat, body mass index, waist circumference, triglycerides, and C-reactive protein, were increased. Systolic blood pressure, heart rate, low-density lipoprotein, and total cholesterol were potentially increased while high-density lipoprotein was decreased. However, television viewing time had no effect on venous thromboembolism or pulmonary embolism.

conclusionTelevision viewing time was causally associated with increased risks of cardiovascular diseases, which may be explained by metabolic and inflammatory mechanisms.

backgroundAn overview of the effect of television viewing time on cardiovascular diseases and biomarkers of cardiometabolic risk.

Indexed as

Cardiovascular DiseasesScreen TimeTelevisionBiomarkersDiabetes Mellitus, Type 2Leisure ActivitiesPolymorphism, Single NucleotideSedentary BehaviorUK BiobankBiomarkers

Identifiers

PMID39476038
PMCPMC11634206

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LicenceCC BY
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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.