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Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study
BACKGROUND: Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948415/ https://www.ncbi.nlm.nih.gov/pubmed/36823523 http://dx.doi.org/10.1186/s12877-023-03789-2 |
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author | Loef, Bette Herber, Gerrie-Cor M. Wong, Albert Janssen, Nicole A. H. Hoekstra, Jurriaan Picavet, H. Susan J. Verschuren, W. M. Monique |
author_facet | Loef, Bette Herber, Gerrie-Cor M. Wong, Albert Janssen, Nicole A. H. Hoekstra, Jurriaan Picavet, H. Susan J. Verschuren, W. M. Monique |
author_sort | Loef, Bette |
collection | PubMed |
description | BACKGROUND: Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations. METHODS: Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20–29/30–39/40–49/50–59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46–85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors. RESULTS: The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model’s performance was modest with an R(2) of 17%. CONCLUSIONS: Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-03789-2. |
format | Online Article Text |
id | pubmed-9948415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99484152023-02-24 Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study Loef, Bette Herber, Gerrie-Cor M. Wong, Albert Janssen, Nicole A. H. Hoekstra, Jurriaan Picavet, H. Susan J. Verschuren, W. M. Monique BMC Geriatr Research BACKGROUND: Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations. METHODS: Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20–29/30–39/40–49/50–59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46–85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors. RESULTS: The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model’s performance was modest with an R(2) of 17%. CONCLUSIONS: Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-03789-2. BioMed Central 2023-02-23 /pmc/articles/PMC9948415/ /pubmed/36823523 http://dx.doi.org/10.1186/s12877-023-03789-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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. |
spellingShingle | Research Loef, Bette Herber, Gerrie-Cor M. Wong, Albert Janssen, Nicole A. H. Hoekstra, Jurriaan Picavet, H. Susan J. Verschuren, W. M. Monique Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study |
title | Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study |
title_full | Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study |
title_fullStr | Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study |
title_full_unstemmed | Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study |
title_short | Predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the Doetinchem Cohort Study |
title_sort | predictors of healthy physiological aging across generations in a 30-year population-based cohort study: the doetinchem cohort study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948415/ https://www.ncbi.nlm.nih.gov/pubmed/36823523 http://dx.doi.org/10.1186/s12877-023-03789-2 |
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