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Associations of physical activity and sleep with cardiometabolic risk in older women
In this study, we investigate the associations of objectively measured waking (sedentary, light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) and sleep duration and quality characteristics with cardiometabolic risk among older women. Participants from the Healthy Women S...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093830/ https://www.ncbi.nlm.nih.gov/pubmed/32226729 http://dx.doi.org/10.1016/j.pmedr.2020.101071 |
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author | Lee, Joowon Walker, Maura E. Matthews, Karen A. Kuller, Lewis H. Ranjit, Nalini Gabriel, Kelley Pettee |
author_facet | Lee, Joowon Walker, Maura E. Matthews, Karen A. Kuller, Lewis H. Ranjit, Nalini Gabriel, Kelley Pettee |
author_sort | Lee, Joowon |
collection | PubMed |
description | In this study, we investigate the associations of objectively measured waking (sedentary, light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) and sleep duration and quality characteristics with cardiometabolic risk among older women. Participants from the Healthy Women Study 2010–11 follow-up visit (n = 136, age = 73 ± 2 years, white = 91.9%) concurrently wore an ActiGraph GT1M accelerometer and Actiwatch-2 for seven days. A composite cardiometabolic risk score was calculated by transforming metabolic syndrome (MetS) components and summing z-scores. Multivariable regression models were fitted to relate waking and sleep estimates with the MetS z-score after adjustment for covariates. Compositional data analysis was used to predict the MetS z-score when fixed durations of time were reallocated from one characteristic to another. MVPA (per 10 min/day increase; β = −7.80, P < 0.01), LPA (per 30 min/day increase; β = −0.29, P = 0.04), and sleep efficiency (β = −0.10, P = 0.04) were inversely associated with MetS z-score, while sedentary time (per 30 min/day increase; β = 0.34, P = 0.01) was positively associated with MetS z-score. Reallocation of 5 min from MVPA to sleep, sedentary, or LPA resulted in the greatest predicted change in MetS z-score. On average, the reallocation of 5 min from MVPA to other characteristics predicted an 11% increase in triglycerides, 6% decrease in HDL-C, and 5% increase in waist circumference. Lastly, reallocating 30 min of sedentary time to LPA was associated with a modestly lower predicted MetS z-score. This study suggests that MVPA is the most important contributor of MetS and that maintaining MVPA and increasing LPA may be beneficial for reducing cardiometabolic risk among older women. |
format | Online Article Text |
id | pubmed-7093830 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-70938302020-03-27 Associations of physical activity and sleep with cardiometabolic risk in older women Lee, Joowon Walker, Maura E. Matthews, Karen A. Kuller, Lewis H. Ranjit, Nalini Gabriel, Kelley Pettee Prev Med Rep Regular Article In this study, we investigate the associations of objectively measured waking (sedentary, light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) and sleep duration and quality characteristics with cardiometabolic risk among older women. Participants from the Healthy Women Study 2010–11 follow-up visit (n = 136, age = 73 ± 2 years, white = 91.9%) concurrently wore an ActiGraph GT1M accelerometer and Actiwatch-2 for seven days. A composite cardiometabolic risk score was calculated by transforming metabolic syndrome (MetS) components and summing z-scores. Multivariable regression models were fitted to relate waking and sleep estimates with the MetS z-score after adjustment for covariates. Compositional data analysis was used to predict the MetS z-score when fixed durations of time were reallocated from one characteristic to another. MVPA (per 10 min/day increase; β = −7.80, P < 0.01), LPA (per 30 min/day increase; β = −0.29, P = 0.04), and sleep efficiency (β = −0.10, P = 0.04) were inversely associated with MetS z-score, while sedentary time (per 30 min/day increase; β = 0.34, P = 0.01) was positively associated with MetS z-score. Reallocation of 5 min from MVPA to sleep, sedentary, or LPA resulted in the greatest predicted change in MetS z-score. On average, the reallocation of 5 min from MVPA to other characteristics predicted an 11% increase in triglycerides, 6% decrease in HDL-C, and 5% increase in waist circumference. Lastly, reallocating 30 min of sedentary time to LPA was associated with a modestly lower predicted MetS z-score. This study suggests that MVPA is the most important contributor of MetS and that maintaining MVPA and increasing LPA may be beneficial for reducing cardiometabolic risk among older women. 2020-03-04 /pmc/articles/PMC7093830/ /pubmed/32226729 http://dx.doi.org/10.1016/j.pmedr.2020.101071 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Regular Article Lee, Joowon Walker, Maura E. Matthews, Karen A. Kuller, Lewis H. Ranjit, Nalini Gabriel, Kelley Pettee Associations of physical activity and sleep with cardiometabolic risk in older women |
title | Associations of physical activity and sleep with cardiometabolic risk in older women |
title_full | Associations of physical activity and sleep with cardiometabolic risk in older women |
title_fullStr | Associations of physical activity and sleep with cardiometabolic risk in older women |
title_full_unstemmed | Associations of physical activity and sleep with cardiometabolic risk in older women |
title_short | Associations of physical activity and sleep with cardiometabolic risk in older women |
title_sort | associations of physical activity and sleep with cardiometabolic risk in older women |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093830/ https://www.ncbi.nlm.nih.gov/pubmed/32226729 http://dx.doi.org/10.1016/j.pmedr.2020.101071 |
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