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Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality
People appear to vary in their susceptibility to lifestyle risk factors for cardiometabolic disease; determining a priori who is most sensitive may help optimize the timing, design, and delivery of preventative interventions. We aimed to ascertain a person’s degree of resilience or sensitivity to ad...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370461/ https://www.ncbi.nlm.nih.gov/pubmed/35956347 http://dx.doi.org/10.3390/nu14153171 |
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author | Pomares-Millan, Hugo Poveda, Alaitz Atabaki-Pasdar, Naemieh Johansson, Ingegerd Björk, Jonas Ohlsson, Mattias Giordano, Giuseppe N. Franks, Paul W. |
author_facet | Pomares-Millan, Hugo Poveda, Alaitz Atabaki-Pasdar, Naemieh Johansson, Ingegerd Björk, Jonas Ohlsson, Mattias Giordano, Giuseppe N. Franks, Paul W. |
author_sort | Pomares-Millan, Hugo |
collection | PubMed |
description | People appear to vary in their susceptibility to lifestyle risk factors for cardiometabolic disease; determining a priori who is most sensitive may help optimize the timing, design, and delivery of preventative interventions. We aimed to ascertain a person’s degree of resilience or sensitivity to adverse lifestyle exposures and determine whether these classifications help predict cardiometabolic disease later in life; we pooled data from two population-based Swedish prospective cohort studies (n = 53,507), and we contrasted an individual’s cardiometabolic biomarker profile with the profile predicted for them given their lifestyle exposure characteristics using a quantile random forest approach. People who were classed as ‘sensitive’ to hypertension- and dyslipidemia-related lifestyle exposures were at higher risk of developing cardiovascular disease (CVD, hazards ratio 1.6 (95% CI: 1.3, 1.91)), compared with the general population. No differences were observed for type 2 diabetes (T2D) risk. Here, we report a novel approach to identify individuals who are especially sensitive to adverse lifestyle exposures and who are at higher risk of subsequent cardiovascular events. Early preventive interventions may be needed in this subgroup. |
format | Online Article Text |
id | pubmed-9370461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93704612022-08-12 Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality Pomares-Millan, Hugo Poveda, Alaitz Atabaki-Pasdar, Naemieh Johansson, Ingegerd Björk, Jonas Ohlsson, Mattias Giordano, Giuseppe N. Franks, Paul W. Nutrients Article People appear to vary in their susceptibility to lifestyle risk factors for cardiometabolic disease; determining a priori who is most sensitive may help optimize the timing, design, and delivery of preventative interventions. We aimed to ascertain a person’s degree of resilience or sensitivity to adverse lifestyle exposures and determine whether these classifications help predict cardiometabolic disease later in life; we pooled data from two population-based Swedish prospective cohort studies (n = 53,507), and we contrasted an individual’s cardiometabolic biomarker profile with the profile predicted for them given their lifestyle exposure characteristics using a quantile random forest approach. People who were classed as ‘sensitive’ to hypertension- and dyslipidemia-related lifestyle exposures were at higher risk of developing cardiovascular disease (CVD, hazards ratio 1.6 (95% CI: 1.3, 1.91)), compared with the general population. No differences were observed for type 2 diabetes (T2D) risk. Here, we report a novel approach to identify individuals who are especially sensitive to adverse lifestyle exposures and who are at higher risk of subsequent cardiovascular events. Early preventive interventions may be needed in this subgroup. MDPI 2022-08-01 /pmc/articles/PMC9370461/ /pubmed/35956347 http://dx.doi.org/10.3390/nu14153171 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pomares-Millan, Hugo Poveda, Alaitz Atabaki-Pasdar, Naemieh Johansson, Ingegerd Björk, Jonas Ohlsson, Mattias Giordano, Giuseppe N. Franks, Paul W. Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality |
title | Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality |
title_full | Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality |
title_fullStr | Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality |
title_full_unstemmed | Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality |
title_short | Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality |
title_sort | predicting sensitivity to adverse lifestyle risk factors for cardiometabolic morbidity and mortality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370461/ https://www.ncbi.nlm.nih.gov/pubmed/35956347 http://dx.doi.org/10.3390/nu14153171 |
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