Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits
The present study assessed the temporal associations of ~ 300 lifestyle exposures with nine cardiometabolic traits to identify exposures/exposure groups that might inform lifestyle interventions for the reduction of cardiometabolic diseaserisk. The analyses were undertaken in a longitudinal sample c...
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ftzenodo:oai:zenodo.org:6983404 2024-09-15T18:26:07+00:00 Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits Alaitz Poveda Hugo Pomares-Millan Yan Chen Azra Kurbasic Chirag J. Patel Frida Renström Göran Hallmans, Ingegerd Johansson Paul W. Franks 2022-03-08 https://doi.org/10.1038/s41598-022-08050-1 unknown Zenodo https://zenodo.org/communities/eu https://doi.org/10.1038/s41598-022-08050-1 oai:zenodo.org:6983404 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/article 2022 ftzenodo https://doi.org/10.1038/s41598-022-08050-1 2024-07-26T17:41:08Z The present study assessed the temporal associations of ~ 300 lifestyle exposures with nine cardiometabolic traits to identify exposures/exposure groups that might inform lifestyle interventions for the reduction of cardiometabolic diseaserisk. The analyses were undertaken in a longitudinal sample comprising > 31,000 adults living in northern Sweden. Linear mixed models were used to assess the average associations of lifestyle exposures and linear regression models were used to test associations with 10-year change in the cardiometabolic traits. ‘Physical activity’ and ‘General Health’ were the exposure categories containing the highest number of ‘tentative signals’ in analyses assessing the average association of lifestyle variables, while ‘Tobacco use’ was the topcategory for the 10-year change association analyses. Eleven modifiable variables showed a consistent average association among the majority of cardiometabolic traits. These variables belonged to the domains: (i) Smoking, (ii) Beverage (filtered coffee), (iii) physical activity, (iv) alcohol intake, and (v) specific variables related to Nordiclifestyle (hunting/fishing during leisure time and boiled coffeeconsumption). We used an agnostic, data-driven approach to assess a wide range of established and novel risk factors for cardiometabolic disease. Our findings highlight key variables, along with their respective effect estimates, that might be prioritised for subsequent prediction models and lifestyle interventions. Article in Journal/Newspaper Northern Sweden Zenodo Scientific Reports 12 1 |
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The present study assessed the temporal associations of ~ 300 lifestyle exposures with nine cardiometabolic traits to identify exposures/exposure groups that might inform lifestyle interventions for the reduction of cardiometabolic diseaserisk. The analyses were undertaken in a longitudinal sample comprising > 31,000 adults living in northern Sweden. Linear mixed models were used to assess the average associations of lifestyle exposures and linear regression models were used to test associations with 10-year change in the cardiometabolic traits. ‘Physical activity’ and ‘General Health’ were the exposure categories containing the highest number of ‘tentative signals’ in analyses assessing the average association of lifestyle variables, while ‘Tobacco use’ was the topcategory for the 10-year change association analyses. Eleven modifiable variables showed a consistent average association among the majority of cardiometabolic traits. These variables belonged to the domains: (i) Smoking, (ii) Beverage (filtered coffee), (iii) physical activity, (iv) alcohol intake, and (v) specific variables related to Nordiclifestyle (hunting/fishing during leisure time and boiled coffeeconsumption). We used an agnostic, data-driven approach to assess a wide range of established and novel risk factors for cardiometabolic disease. Our findings highlight key variables, along with their respective effect estimates, that might be prioritised for subsequent prediction models and lifestyle interventions. |
format |
Article in Journal/Newspaper |
author |
Alaitz Poveda Hugo Pomares-Millan Yan Chen Azra Kurbasic Chirag J. Patel Frida Renström Göran Hallmans, Ingegerd Johansson Paul W. Franks |
spellingShingle |
Alaitz Poveda Hugo Pomares-Millan Yan Chen Azra Kurbasic Chirag J. Patel Frida Renström Göran Hallmans, Ingegerd Johansson Paul W. Franks Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
author_facet |
Alaitz Poveda Hugo Pomares-Millan Yan Chen Azra Kurbasic Chirag J. Patel Frida Renström Göran Hallmans, Ingegerd Johansson Paul W. Franks |
author_sort |
Alaitz Poveda |
title |
Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
title_short |
Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
title_full |
Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
title_fullStr |
Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
title_full_unstemmed |
Exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
title_sort |
exposome-wide ranking of modifiable risk factors for cardiometabolic disease traits |
publisher |
Zenodo |
publishDate |
2022 |
url |
https://doi.org/10.1038/s41598-022-08050-1 |
genre |
Northern Sweden |
genre_facet |
Northern Sweden |
op_relation |
https://zenodo.org/communities/eu https://doi.org/10.1038/s41598-022-08050-1 oai:zenodo.org:6983404 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.1038/s41598-022-08050-1 |
container_title |
Scientific Reports |
container_volume |
12 |
container_issue |
1 |
_version_ |
1810466575047720960 |