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Sökning: onr:"swepub:oai:DiVA.org:his-19508" > Age-dependent effec...

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FältnamnIndikatorerMetadata
00006622naa a2200769 4500
001oai:DiVA.org:his-19508
003SwePub
008210303s2020 | |||||||||||000 ||eng|
009oai:DiVA.org:hj-50085
009oai:prod.swepub.kib.ki.se:143952061
024a https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-195082 URI
024a https://doi.org/10.1186/s12916-020-01600-22 DOI
024a https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-500852 URI
024a http://kipublications.ki.se/Default.aspx?queryparsed=id:1439520612 URI
040 a (SwePub)hisd (SwePub)hjd (SwePub)ki
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
100a Karlsson, Ida K.u Karolinska Institutet,Jönköping University,HHJ, Institutet för gerontologi,HHJ. ARN-J (Aging Research Network - Jönköping),Institute of Gerontology and Aging Research Network – Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Sweden ; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden4 aut0 (Swepub:hj)karida
2451 0a Age-dependent effects of body mass index across the adult life span on the risk of dementia :b A cohort study with a genetic approach
264 c 2020-06-09
264 1b BioMed Central,c 2020
338 a electronic2 rdacarrier
500 a CC BY 4.0CC0 1.0The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
520 a Background: While a high body mass index (BMI) in midlife is associated with higher risk of dementia, high BMI in late-life may be associated with lower risk. This study combined genetic designs with longitudinal data to achieve a better understanding of this paradox. Methods: We used longitudinal data from 22,156 individuals in the Swedish Twin Registry (STR) and 25,698 from the Health and Retirement Study (HRS). The STR sample had information about BMI from early adulthood through late-life, and the HRS sample from age 50 through late-life. Survival analysis was applied to investigate age-specific associations between BMI and dementia risk. To examine if the associations are influenced by genetic susceptibility to higher BMI, an interaction between BMI and a polygenic score for BMI (PGSBMI) was included in the models and results stratified into those with genetic predisposition to low, medium, and higher BMI. In the STR, co-twin control models were applied to adjust for familial factors beyond those captured by the PGSBMI. Results: At age 35-49, 5 units higher BMI was associated with 15% (95% CI 7-24%) higher risk of dementia in the STR. There was a significant interaction (p = 0.04) between BMI and the PGSBMI, and the association present only among those with genetic predisposition to low BMI (HR 1.38, 95% CI 1.08-1.78). Co-twin control analyses indicated genetic influences. After age 80, 5 units higher BMI was associated with 10-11% lower risk of dementia in both samples. There was a significant interaction between late-life BMI and the PGSBMI in the STR (p = 0.01), but not the HRS, with the inverse association present only among those with a high PGSBMI (HR 0.70, 95% CI 0.52-0.94). No genetic influences were evident from co-twin control models of late-life BMI. Conclusions: Not only does the association between BMI and dementia differ depending on age at BMI measurement, but also the effect of genetic influences. In STR, the associations were only present among those with a BMI in opposite direction of their genetic predisposition, indicating that the association between BMI and dementia across the life course might be driven by environmental factors and hence likely modifiable. © 2020 The Author(s).
650 7a MEDICIN OCH HÄLSOVETENSKAPx Annan medicin och hälsovetenskapx Gerontologi, medicinsk/hälsovetenskaplig inriktning0 (SwePub)305022 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Other Medical and Health Sciencesx Gerontology, specialising in Medical and Health Sciences0 (SwePub)305022 hsv//eng
653 a Body mass index
653 a Dementia
653 a Life span
653 a Longitudinal
653 a Obesity paradox
653 a Polygenic score
653 a Twin design
653 a adult
653 a adulthood
653 a age
653 a aged
653 a Article
653 a body mass
653 a cohort analysis
653 a female
653 a genetic predisposition
653 a genetic susceptibility
653 a human
653 a lifespan
653 a major clinical study
653 a male
653 a register
653 a risk assessment
653 a sensitivity analysis
653 a survival analysis
653 a very elderly
700a Lehto, Kelliu National Institute for Health Development, Tallinn, Estonia ; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden4 aut
700a Gatz, Margaretu Department of Psychology, University of Southern California, Los Angeles, CA, United States ; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden4 aut
700a Reynolds, Chandra A.u Department of Psychology, University of California, Riverside, United States4 aut
700a Dahl Aslan, Anna K.,d 1975-u Karolinska Institutet,Jönköping University,HHJ, Institutet för gerontologi,HHJ. ARN-J (Aging Research Network - Jönköping),Institute of Gerontology and Aging Research Network – Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Sweden ; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden4 aut0 (Swepub:hj)daan
710a Jönköping Universityb HHJ, Institutet för gerontologi4 org
773t BMC Medicined : BioMed Centralg 18:1q 18:1x 1741-7015
856u https://doi.org/10.1186/s12916-020-01600-2y Fulltext
856u https://his.diva-portal.org/smash/get/diva2:1533041/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
856u https://bmcmedicine.biomedcentral.com/track/pdf/10.1186/s12916-020-01600-2
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19508
8564 8u https://doi.org/10.1186/s12916-020-01600-2
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-50085
8564 8u http://kipublications.ki.se/Default.aspx?queryparsed=id:143952061

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