Evidence map›Paper›PMID 36071625›Full record

ArticleScandinavian journal of public health2024

Marital status and genetic liability independently predict coronary heart disease incidence.

Karri Silventoinen, Hannu Lahtinen, Kaarina Korhonen, George Davey Smith, Samuli Ripatti, Tim Morris, Pekka Martikainen

Open access · hybridAbstract read
In one paragraph

Article in Scandinavian journal of public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
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

7 authors at 3 institutions in 5 countries.

Karri SilventoinenFaculty of Social Sciences, University of Helsinki, Finland.ORCID 0000-0003-1759-3079
Hannu LahtinenFaculty of Social Sciences, University of Helsinki, Finland.ORCID 0000-0003-0910-823X
Kaarina KorhonenFaculty of Social Sciences, University of Helsinki, Finland.
George Davey SmithPopulation Health Sciences, Bristol Medical School, University of Bristol, UK.
Samuli RipattiFaculty of Medicine, University of Helsinki, Finland.
Tim MorrisPopulation Health Sciences, Bristol Medical School, University of Bristol, UK.
Pekka MartikainenFaculty of Social Sciences, University of Helsinki, Finland.
University of Helsinki · FIUniversity of Bristol · GBBroad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsMarried individuals have a lower coronary heart disease (CHD) risk than non-married, but the mechanisms behind this are not fully understood. We analyzed whether genetic liability to CHD may affect these associations.

methodsMarital status, a polygenic score of CHD (PGS-CHD), and other risk factors for CHD were measured from 35,444 participants (53% female) in Finnish population-based surveys conducted between 1992 and 2012. During the register-based follow-up until 2020, there were 2439 fatal and non-fatal incident CHD cases. The data were analyzed using linear and Cox regression models.

resultsDivorced and cohabiting men and women had a higher genetic risk of CHD than married individuals, but the difference was very small (0.023-0.058 standard deviation of PGS-CHD,

conclusionsWe showed minor differences between the marital status categories in PGS-CHD and demonstrated that marital status and genetic liability predicted CHD incidence largely independently. This emphasizes the need to measure multiple risk factors when predicting CHD risk.

Indexed as

Coronary DiseaseFamily CharacteristicsFemaleHumansIncidenceMaleMarital StatusRisk Factorscoronary diseasegeneticsMarital statussocioeconomic factors

Identifiers

PMID36071625
PMCPMC10845822
OpenAlexW4294943793

What OpenQuestion holds

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LicenceCC BY
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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.