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dc.contributor.authorBrandkvist, Maria Charlotta
dc.contributor.authorBjørngaard, Johan Håkon
dc.contributor.authorØdegård, Rønnaug
dc.contributor.authorBrumpton, Ben Michael
dc.contributor.authorSmith, George Davey
dc.contributor.authorÅsvold, Bjørn Olav
dc.contributor.authorSund, Erik
dc.contributor.authorKvaløy, Kirsti
dc.contributor.authorWiller, Cristen J.
dc.contributor.authorVie, Gunnhild Åberge
dc.date.accessioned2021-03-18T12:31:34Z
dc.date.available2021-03-18T12:31:34Z
dc.date.created2021-01-18T17:44:30Z
dc.date.issued2020
dc.identifier.citationBrandkvist, M., Bjørngaard, J. H., Ødegård, R. A., Brumpton, B., Smith, G. D., Åsvold, B. O. ... Vie, G. Å. (2020). Genetic associations with temporal shifts in obesity and severe obesity during the obesity epidemic in Norway: A longitudinal population-based cohort (the HUNT Study). PLoS Medicine, 17(12): e1003452. doi:en_US
dc.identifier.issn1549-1676
dc.identifier.urihttps://hdl.handle.net/11250/2734225
dc.description.abstractBackground Obesity 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 findings A 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. Conclusions In 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.en_US
dc.language.isoengen_US
dc.publisherPLOSen_US
dc.relation.urihttps://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003452
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleGenetic associations with temporal shifts in obesity and severe obesity during the obesity epidemic in Norway : A longitudinal population-based cohort (the HUNT Study)en_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2020 The Author(s)en_US
dc.subject.nsiVDP::Medisinske Fag: 700en_US
dc.subject.nsiVDP::Medisinske Fag: 700::Helsefag: 800en_US
dc.subject.nsiVDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801en_US
dc.source.volume17en_US
dc.source.journalPLoS Medicineen_US
dc.source.issue12en_US
dc.identifier.doi10.1371/journal.pmed.1003452
dc.identifier.cristin1873619
dc.relation.projectNorges forskningsråd: 295989en_US
dc.relation.projectNorges forskningsråd: 250335en_US
dc.source.articlenumbere1003452en_US


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