Evidence map›Paper›PMID 30957776›Full record

ArticleBMJ (Clinical research ed.)2019

Body mass index and all cause mortality in HUNT and UK Biobank studies: linear and non-linear mendelian randomisation analyses.

Yi-Qian Sun, Stephen Burgess, James R Staley, Angela M Wood, Steven Bell, Stephen K Kaptoge, Qi Guo, Thomas R Bolton, Amy M Mason, Adam S Butterworth and 6 more

Open access · hybridAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ (Clinical research ed.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
111citing papers in PubMed, 7 pooled it
22.4field-weighted citation impact, top 1% 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

111 citing papers in PubMed, 7 syntheses or guidelines pooled it, 205 citations in OpenAlex.

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  17. Deriving Mendelian Randomization-Based Causal Networks of Brain Imaging Phenotypes and Bipolar Disorder.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026
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51 more citing papers are in PubMed but not listed here.

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

16 authors at 4 institutions in 3 countries.

Yi-Qian SunDepartment of Clinical and Molecular Medicine (IKOM), NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
Stephen BurgessMRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge CB2 0SR, UK sb452@medschl.cam.ac.uk.ORCID 0000-0001-5365-8760
James R StaleyCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Angela M WoodCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Steven BellCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Stephen K KaptogeCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Qi GuoCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Thomas R BoltonCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Amy M MasonCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Adam S ButterworthCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Emanuele Di AngelantonioCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Gunnhild Å VieDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
Johan H BjørngaardDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
Jonas Minet KingeNorwegian Institute of Public Health, Oslo, Norway.
Yue ChenSchool of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
Xiao-Mei MaiDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.
University of Cambridge · GBNorwegian University of Science and Technology · NONorwegian Institute of Public Health · NOUniversity of Ottawa · CA

Funding

British Heart Foundation CH/12/2/29428British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946Medical Research Council MC_UU_00002/7Medical Research Council MR/L003120/1Wellcome Trust 204623
6 · The paper itself

Abstract

EDITOR'S NOTE: Please see the Editor's Note (doi: https://doi.org/10.1136/bmj.l1042) on Methodological Criticism and an Updated Analysis

objectiveTo investigate the shape of the causal relation between body mass index (BMI) and mortality.

designLinear and non-linear mendelian randomisation analyses.

settingNord-Trøndelag Health (HUNT) Study (Norway) and UK Biobank (United Kingdom).

participantsMiddle to early late aged participants of European descent: 56 150 from the HUNT Study and 366 385 from UK Biobank.

main outcome measuresAll cause and cause specific (cardiovascular, cancer, and non-cardiovascular non-cancer) mortality.

results12 015 and 10 344 participants died during a median of 18.5 and 7.0 years of follow-up in the HUNT Study and UK Biobank, respectively. Linear mendelian randomisation analyses indicated an overall positive association between genetically predicted BMI and the risk of all cause mortality. An increase of 1 unit in genetically predicted BMI led to a 5% (95% confidence interval 1% to 8%) higher risk of mortality in overweight participants (BMI 25.0-29.9) and a 9% (4% to 14%) higher risk of mortality in obese participants (BMI ≥30.0) but a 34% (16% to 48%) lower risk in underweight (BMI <18.5) and a 14% (-1% to 27%) lower risk in low normal weight participants (BMI 18.5-19.9). Non-linear mendelian randomisation indicated a J shaped relation between genetically predicted BMI and the risk of all cause mortality, with the lowest risk at a BMI of around 22-25 for the overall sample. Subgroup analyses by smoking status, however, suggested an always-increasing relation of BMI with mortality in never smokers and a J shaped relation in ever smokers.

conclusionsThe previously observed J shaped relation between BMI and risk of all cause mortality appears to have a causal basis, but subgroup analyses by smoking status revealed that the BMI-mortality relation is likely comprised of at least two distinct curves, rather than one J shaped relation. An increased risk of mortality for being underweight was only evident in ever smokers.

Indexed as

Body Mass IndexCause of DeathAdultAgedCardiovascular DiseasesFemaleHumansMaleMendelian Randomization AnalysisMiddle AgedNeoplasmsNorwayObesityRisk FactorsSex DistributionThinness

Identifiers

PMID30957776
PMCPMC6434515
OpenAlexW2916194715

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.