TY - JOUR
T1 - Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers
T2 - The Maastricht Study
AU - Leskinen, Tuija
AU - Lima Passos, Valéria
AU - Dagnelie, Pieter C.
AU - Savelberg, Hans H.C.M.
AU - De Galan, Bastiaan E.
AU - Eussen, Simone J.P.M.
AU - Stehouwer, Coen D.A.
AU - Stenholm, Sari
AU - Koster, Annemarie
N1 - Funding Information:
The Maastricht Study was supported by the European Regional Development Fund via OP-Zuid, the Province of Limburg, the Dutch Ministry of Economic Affairs (grant 31O.041), Stichting De Weijerhorst (Maastricht, The Netherlands), the Pearl String Initiative Diabetes (Amsterdam, the Netherlands), the Cardiovascular Center (CVC, Maastricht, The Netherlands), CARIM School for Cardiovascular Diseases (Maastricht, The Netherlands), CAPHRI Care and Public Health Research Institute (Maastricht, The Netherlands), NUTRIM School for Nutrition and Translational Research in Metabolism (Maastricht, The Netherlands), Stichting Annadal (Maastricht, the Netherlands), Health Foundation Limburg (Maastricht, The Netherlands) and by unrestricted grants from Janssen-Cilag B. V. (Tilburg, The Netherlands), Novo Nordisk Farma B. V. (Alphen aan den Rijn, The Netherlands) and Sanofi-Aventis Netherlands B. V. (Gouda, The Netherlands). The work was also supported by the Academy of Finland (grant 332030 to SS). No conflicts of interest or financial disclosures were reported. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate datamanipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
Funding Information:
The Maastricht Study was supported by the European Regional Development Fund via OP-Zuid, the Province of Limburg, the Dutch Ministry of Economic Affairs (grant 31O.041), Stichting De Weijerhorst (Maastricht, The Netherlands), the Pearl String Initiative Diabetes (Amsterdam, the Netherlands), the Cardiovascular Center (CVC, Maastricht, The Netherlands), CARIM School for Cardiovascular Diseases (Maastricht, The Netherlands), CAPHRI Care and Public Health Research Institute (Maastricht, The Netherlands), NUTRIM School for Nutrition and Translational Research in Metabolism (Maastricht, The Netherlands), Stichting Annadal (Maastricht, the Netherlands), Health Foundation Limburg (Maastricht, The Netherlands) and by unrestricted grants from Janssen-Cilag B. V. (Tilburg, The Netherlands), Novo Nordisk Farma B. V. (Alphen aan den Rijn, The Netherlands) and Sanofi-Aventis Netherlands B. V. (Gouda, The Netherlands). The work was also supported by the Academy of Finland (grant 332030 to SS). No conflicts of interest or financial disclosures were reported. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
Publisher Copyright:
Copyright © 2021 by the American College of Sports Medicine.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - 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.
AB - 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.
KW - Biomarkers
KW - Cardiometabolic Health
KW - Physical Activity
KW - Trajectory Modeling
KW - Type 2 Diabetes
U2 - 10.1249/MSS.0000000000003108
DO - 10.1249/MSS.0000000000003108
M3 - Article
C2 - 36728772
SN - 0195-9131
VL - 55
SP - 837
EP - 846
JO - Medicine and Science in Sports and Exercise
JF - Medicine and Science in Sports and Exercise
IS - 5
ER -