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Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study

PURPOSE: This study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design. METHODS: Overall 6072 participants (mean age, 60.2 yr; SD 8.6 yr, 50% women) from The Maastricht Study provided daily physical activity data col...

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Autores principales: LESKINEN, TUIJA, LIMA PASSOS, VALÉRIA, DAGNELIE, PIETER C., SAVELBERG, HANS H. C. M., DE GALAN, BASTIAAN E., EUSSEN, SIMONE J. P. M., STEHOUWER, COEN D. A., STENHOLM, SARI, KOSTER, ANNEMARIE
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090323/
https://www.ncbi.nlm.nih.gov/pubmed/36728772
http://dx.doi.org/10.1249/MSS.0000000000003108
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author LESKINEN, TUIJA
LIMA PASSOS, VALÉRIA
DAGNELIE, PIETER C.
SAVELBERG, HANS H. C. M.
DE GALAN, BASTIAAN E.
EUSSEN, SIMONE J. P. M.
STEHOUWER, COEN D. A.
STENHOLM, SARI
KOSTER, ANNEMARIE
author_facet LESKINEN, TUIJA
LIMA PASSOS, VALÉRIA
DAGNELIE, PIETER C.
SAVELBERG, HANS H. C. M.
DE GALAN, BASTIAAN E.
EUSSEN, SIMONE J. P. M.
STEHOUWER, COEN D. A.
STENHOLM, SARI
KOSTER, ANNEMARIE
author_sort LESKINEN, TUIJA
collection PubMed
description PURPOSE: This study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design. METHODS: Overall 6072 participants (mean age, 60.2 yr; SD 8.6 yr, 50% women) from The Maastricht Study provided daily physical activity data collected with thigh-worn activPAL3 accelerometers. The patterns of daily physical activity over weekdays and weekend days were identified by using Group Based Trajectory Modeling. Cardiometabolic biomarkers included body mass index, waist circumference, office blood pressure, glucose, HbA1c, and cholesterol levels. Associations between the physical activity patterns and cardiometabolic outcomes were examined using the analyses of covariance adjusted for sex, age, education, smoking, and diet. Because of statistically significant interaction, the analyses were stratified by type 2 diabetes status. RESULTS: Overall, seven physical activity patterns were identified: consistently inactive (21% of participants), consistently low active (41%), active on weekdays (15%), early birds (2%), consistently moderately active (7%), weekend warriors (8%), and consistently highly active (6%). The consistently inactive and low active patterns had higher body mass index, waist, and glucose levels compared with the consistently moderately and highly active patterns, and these associations were more pronounced for participants with type 2 diabetes. The more irregular patterns accumulated moderate daily total activity levels but had rather similar cardiometabolic profiles compared with the consistently active groups. CONCLUSIONS: The cardiometabolic profile was most favorable in the consistently highly active group. All patterns accumulating moderate to high levels of daily total physical activity had similar health profile suggesting that the amount of daily physical activity rather than the pattern is more important for cardiometabolic health.
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spelling pubmed-100903232023-04-13 Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study LESKINEN, TUIJA LIMA PASSOS, VALÉRIA DAGNELIE, PIETER C. SAVELBERG, HANS H. C. M. DE GALAN, BASTIAAN E. EUSSEN, SIMONE J. P. M. STEHOUWER, COEN D. A. STENHOLM, SARI KOSTER, ANNEMARIE Med Sci Sports Exerc Basic Sciences PURPOSE: This study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design. METHODS: Overall 6072 participants (mean age, 60.2 yr; SD 8.6 yr, 50% women) from The Maastricht Study provided daily physical activity data collected with thigh-worn activPAL3 accelerometers. The patterns of daily physical activity over weekdays and weekend days were identified by using Group Based Trajectory Modeling. Cardiometabolic biomarkers included body mass index, waist circumference, office blood pressure, glucose, HbA1c, and cholesterol levels. Associations between the physical activity patterns and cardiometabolic outcomes were examined using the analyses of covariance adjusted for sex, age, education, smoking, and diet. Because of statistically significant interaction, the analyses were stratified by type 2 diabetes status. RESULTS: Overall, seven physical activity patterns were identified: consistently inactive (21% of participants), consistently low active (41%), active on weekdays (15%), early birds (2%), consistently moderately active (7%), weekend warriors (8%), and consistently highly active (6%). The consistently inactive and low active patterns had higher body mass index, waist, and glucose levels compared with the consistently moderately and highly active patterns, and these associations were more pronounced for participants with type 2 diabetes. The more irregular patterns accumulated moderate daily total activity levels but had rather similar cardiometabolic profiles compared with the consistently active groups. CONCLUSIONS: The cardiometabolic profile was most favorable in the consistently highly active group. All patterns accumulating moderate to high levels of daily total physical activity had similar health profile suggesting that the amount of daily physical activity rather than the pattern is more important for cardiometabolic health. Lippincott Williams & Wilkins 2023-05 2022-12-27 /pmc/articles/PMC10090323/ /pubmed/36728772 http://dx.doi.org/10.1249/MSS.0000000000003108 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Basic Sciences
LESKINEN, TUIJA
LIMA PASSOS, VALÉRIA
DAGNELIE, PIETER C.
SAVELBERG, HANS H. C. M.
DE GALAN, BASTIAAN E.
EUSSEN, SIMONE J. P. M.
STEHOUWER, COEN D. A.
STENHOLM, SARI
KOSTER, ANNEMARIE
Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study
title Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study
title_full Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study
title_fullStr Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study
title_full_unstemmed Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study
title_short Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study
title_sort daily physical activity patterns and their associations with cardiometabolic biomarkers: the maastricht study
topic Basic Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090323/
https://www.ncbi.nlm.nih.gov/pubmed/36728772
http://dx.doi.org/10.1249/MSS.0000000000003108
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