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The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study
The aims of this study were (1) to develop a comprehensive risk-of-death and life expectancy (LE) model and (2) to provide data on the effects of multiple risk factors on LE. We used data for Canada from the Global Burden of Disease (GBD) Study. To create period life tables for males and females, we...
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/PMC9332720/ https://www.ncbi.nlm.nih.gov/pubmed/35897329 http://dx.doi.org/10.3390/ijerph19158958 |
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author | Kopec, Jacek A. Sayre, Eric C. Shams, Benajir Li, Linda C. Xie, Hui Feehan, Lynne M. Esdaile, John M. |
author_facet | Kopec, Jacek A. Sayre, Eric C. Shams, Benajir Li, Linda C. Xie, Hui Feehan, Lynne M. Esdaile, John M. |
author_sort | Kopec, Jacek A. |
collection | PubMed |
description | The aims of this study were (1) to develop a comprehensive risk-of-death and life expectancy (LE) model and (2) to provide data on the effects of multiple risk factors on LE. We used data for Canada from the Global Burden of Disease (GBD) Study. To create period life tables for males and females, we obtained age/sex-specific deaths rates for 270 diseases, population distributions for 51 risk factors, and relative risk functions for all disease-exposure pairs. We computed LE gains from eliminating each factor, LE values for different levels of exposure to each factor, and LE gains from simultaneous reductions in multiple risk factors at various ages. If all risk factors were eliminated, LE in Canada would increase by 6.26 years for males and 5.05 for females. The greatest benefit would come from eliminating smoking in males (2.45 years) and high blood pressure in females (1.42 years). For most risk factors, their dose-response relationships with LE were non-linear and depended on the presence of other factors. In individuals with high levels of risk, eliminating or reducing exposure to multiple factors could improve LE by several years, even at a relatively advanced age. |
format | Online Article Text |
id | pubmed-9332720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93327202022-07-29 The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study Kopec, Jacek A. Sayre, Eric C. Shams, Benajir Li, Linda C. Xie, Hui Feehan, Lynne M. Esdaile, John M. Int J Environ Res Public Health Article The aims of this study were (1) to develop a comprehensive risk-of-death and life expectancy (LE) model and (2) to provide data on the effects of multiple risk factors on LE. We used data for Canada from the Global Burden of Disease (GBD) Study. To create period life tables for males and females, we obtained age/sex-specific deaths rates for 270 diseases, population distributions for 51 risk factors, and relative risk functions for all disease-exposure pairs. We computed LE gains from eliminating each factor, LE values for different levels of exposure to each factor, and LE gains from simultaneous reductions in multiple risk factors at various ages. If all risk factors were eliminated, LE in Canada would increase by 6.26 years for males and 5.05 for females. The greatest benefit would come from eliminating smoking in males (2.45 years) and high blood pressure in females (1.42 years). For most risk factors, their dose-response relationships with LE were non-linear and depended on the presence of other factors. In individuals with high levels of risk, eliminating or reducing exposure to multiple factors could improve LE by several years, even at a relatively advanced age. MDPI 2022-07-23 /pmc/articles/PMC9332720/ /pubmed/35897329 http://dx.doi.org/10.3390/ijerph19158958 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 Kopec, Jacek A. Sayre, Eric C. Shams, Benajir Li, Linda C. Xie, Hui Feehan, Lynne M. Esdaile, John M. The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study |
title | The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study |
title_full | The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study |
title_fullStr | The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study |
title_full_unstemmed | The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study |
title_short | The Impact of 51 Risk Factors on Life Expectancy in Canada: Findings from a New Risk Prediction Model Based on Data from the Global Burden of Disease Study |
title_sort | impact of 51 risk factors on life expectancy in canada: findings from a new risk prediction model based on data from the global burden of disease study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332720/ https://www.ncbi.nlm.nih.gov/pubmed/35897329 http://dx.doi.org/10.3390/ijerph19158958 |
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