Evidence map›Paper›PMID 33315864›Full record

Observational studyPLoS medicine2020

Genetic associations with temporal shifts in obesity and severe obesity during the obesity epidemic in Norway: A longitudinal population-based cohort (the HUNT Study).

Maria Brandkvist, Johan Håkon Bjørngaard, Rønnaug Astri Ødegård, Ben Brumpton, George Davey Smith, Bjørn Olav Åsvold, Erik R Sund, Kirsti Kvaløy, Cristen J Willer, Gunnhild Åberge Vie

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in PLoS medicine, 2020. 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
2.2field-weighted citation impact, top 12% 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, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Cohort Profile Update: The HUNT Study, Norway.International journal of epidemiology · 2023
    Article
  9. Article
  10. Article
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

10 authors at 3 institutions in 3 countries.

Maria BrandkvistDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0002-3916-7313
Johan Håkon BjørngaardDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0002-2646-2954
Rønnaug Astri ØdegårdChildren's Clinic, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.ORCID 0000-0003-3471-8881
Ben BrumptonK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0002-3058-1059
George Davey SmithMedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.ORCID 0000-0002-1407-8314
Bjørn Olav ÅsvoldK.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0003-3837-2101
Erik R SundFaculty of Nursing and Health Sciences, Nord University, Levanger, Norway.ORCID 0000-0002-0736-5139
Kirsti KvaløyDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0002-8038-917X
Cristen J WillerDepartment of Human Genetics, Internal Medicine, and Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.
Gunnhild Åberge VieDepartment of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0003-1552-5291
Norwegian University of Science and Technology · NOUniversity of Bristol · GBUniversity of Michigan · US

Funding

Using Genetics to Inform Mechanism of Cardiovascular DiseaseR35HL135824 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WILLER, CRISTEN J · 2017 to 2022
$5.4M
Medical Research Council MC_UU_00011/1NHLBI NIH HHS R35 HL135824
6 · The paper itself

Abstract

backgroundObesity has tripled worldwide since 1975 as environments are becoming more obesogenic. Our study investigates how changes in population weight and obesity over time are associated with genetic predisposition in the context of an obesogenic environment over 6 decades and examines the robustness of the findings using sibling design. METHODS AND

findingsA total of 67,110 individuals aged 13-80 years in the Nord-Trøndelag region of Norway participated with repeated standardized body mass index (BMI) measurements from 1966 to 2019 and were genotyped in a longitudinal population-based health study, the Trøndelag Health Study (the HUNT Study). Genotyping required survival to and participation in the HUNT Study in the 1990s or 2000s. Linear mixed models with observations nested within individuals were used to model the association between a genome-wide polygenic score (GPS) for BMI and BMI, while generalized estimating equations were used for obesity (BMI ≥ 30 kg/m2) and severe obesity (BMI ≥ 35 kg/m2). The increase in the average BMI and prevalence of obesity was steeper among the genetically predisposed. Among 35-year-old men, the prevalence of obesity for the least predisposed tenth increased from 0.9% (95% confidence interval [CI] 0.6% to 1.2%) to 6.5% (95% CI 5.0% to 8.0%), while the most predisposed tenth increased from 14.2% (95% CI 12.6% to 15.7%) to 39.6% (95% CI 36.1% to 43.0%). Equivalently for women of the same age, the prevalence of obesity for the least predisposed tenth increased from 1.1% (95% CI 0.7% to1.5%) to 7.6% (95% CI 6.0% to 9.2%), while the most predisposed tenth increased from 15.4% (95% CI 13.7% to 17.2%) to 42.0% (95% CI 38.7% to 45.4%). Thus, for 35-year-old men and women, respectively, the absolute change in the prevalence of obesity from 1966 to 2019 was 19.8 percentage points (95% CI 16.2 to 23.5, p < 0.0001) and 20.0 percentage points (95% CI 16.4 to 23.7, p < 0.0001) greater for the most predisposed tenth compared with the least predisposed tenth, defined using the GPS for BMI. The corresponding absolute changes in the prevalence of severe obesity for men and women, respectively, were 8.5 percentage points (95% CI 6.3 to 10.7, p < 0.0001) and 12.6 percentage points (95% CI 9.6 to 15.6, p < 0.0001) greater for the most predisposed tenth. The greater increase in BMI in genetically predisposed individuals over time was apparent after adjustment for family-level confounding using a sibling design. Key limitations include a slightly lower survival to date of genetic testing for the older cohorts and that we apply a contemporary genetic score to past time periods. Future research should validate our findings using a polygenic risk score constructed from historical data.

conclusionsIn the context of increasingly obesogenic changes in our environment over 6 decades, our findings reveal a growing inequality in the risk for obesity and severe obesity across GPS tenths. Our results suggest that while obesity is a partially heritable trait, it is still modifiable by environmental factors. While it may be possible to identify those most susceptible to environmental change, who thus have the most to gain from preventive measures, efforts to reverse the obesogenic environment will benefit the whole population and help resolve the obesity epidemic.

Indexed as

EpidemicsGene-Environment InteractionAdolescentAdultAgedAged, 80 and overBody Mass IndexFemaleGenetic Association StudiesGenetic Predisposition to DiseaseHealth SurveysHeredityHumansLongitudinal StudiesMaleMiddle Aged

Identifiers

PMID33315864
PMCPMC7735641
OpenAlexW3111328969

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.