Evidence map›Paper›PMID 35606845›Full record

ArticleBMC medicine2022

Genetic susceptibility, screen-based sedentary activities and incidence of coronary heart disease.

Youngwon Kim, Shiu Lun Au Yeung, Stephen J Sharp, Mengyao Wang, Haeyoon Jang, Shan Luo, Soren Brage, Katrien Wijndaele

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 21 citations in OpenAlex.

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  8. Mode of transport, genetic susceptibility, and incidence of coronary heart disease.The international journal of behavioral nutrition and physical activity · 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

8 authors at 3 institutions in 2 countries.

Youngwon KimSchool of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Pokfulam, Hong Kong SAR, China. youngwon.kim@hku.hk.ORCID 0000-0002-7846-7191
Shiu Lun Au YeungSchool of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Pokfulam, Hong Kong SAR, China.
Stephen J SharpMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, Cambridgeshire, CB2 0QQ, UK.
Mengyao WangSchool of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Pokfulam, Hong Kong SAR, China.
Haeyoon JangSchool of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Pokfulam, Hong Kong SAR, China.
Shan LuoSchool of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Pokfulam, Hong Kong SAR, China.
Soren BrageMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, Cambridgeshire, CB2 0QQ, UK.
Katrien WijndaeleMRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, Cambridgeshire, CB2 0QQ, UK.
University of Hong Kong · HKUniversity of Cambridge · GBHKU-Pasteur Research Pole · HK

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MC_UU_00006/4
6 · The paper itself

Abstract

backgroundWhether the associations of time spent in screen-based sedentary activities with CHD vary by genetic susceptibility is currently unknown. The objective of this study was to examine the interplay of genetic susceptibility to CHD and two prevalent types of screen-based sedentary activities (television [TV] viewing and computer use) for CHD incidence.

methodsThis prospective cohort study included 373,026 individuals of European ancestry without prevalent CHD/stroke from UK Biobank data. Genetic susceptibility to CHD was assessed using weighted polygenic risk scores, calculated by summing the number of risk-increasing alleles among 300 single-nucleotide polymorphisms, multiplied by their corresponding effect estimates. TV viewing and computer use were assessed through touch-screen questionnaires. CHD incidence (n=9185) was adjudicated over a median 12.6-year follow-up.

resultsCompared with ≥4h/day of TV viewing, the hazard ratio of CHD was 0.84 (95% confidence interval [CI] 0.79-0.90) and 0.94 (0.90-0.99) for ≤1h/day and 2-3h/day of TV viewing, respectively, after adjusting for confounders including the genetic risk. CHD hazards were higher for medium and high genetic risk than for low genetic risk. Across all levels of genetic risk including high-genetic risk, ≤1h/day of TV viewing had lower CHD hazards, compared with ≥4h/day: no evidence of interaction between genetic risk and TV viewing (p value: 0.362). Estimates of the population attributable fraction (PAF) suggested that 10.9% (95% CI 6.1-15.3%) of CHD could be prevented if TV viewing time were reduced to ≤1h/day, assuming causality. The PAF values were relatively larger for medium-to-high genetic risk than for low genetic risk, although the CIs were wide and overlapping. No associations were observed for computer use.

conclusionsLess TV viewing time was associated with lower CHD risk independently of genetic risk. Clinical trials targeted at individuals with high genetic susceptibility should consider reducing TV viewing as as a behavioural target for prevention of an early onset of cardiovascular events.

Indexed as

Coronary DiseaseTelevisionGenetic Predisposition to DiseaseHumansIncidenceProspective StudiesSedentary BehaviorComputer useCoronary heart diseaseGenetic riskPolygenic risk scoresTV viewingUK Biobank

Identifiers

PMID35606845
PMCPMC9126635
OpenAlexW4281389703

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.