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

被引：5

作者：

Leskinen, Tuija ^{[1
,2
,3
,15
]}

Passos, Valeria Lima ^{[4
,5
,6
]}

Dagnelie, Pieter C. ^{[7
,8
]}

Savelberg, Hans H. C. M. ^{[9
,10
]}

De Galan, Bastiaan E. ^{[7
,8
,11
]}

Eussen, Simone J. P. M. ^{[7
,12
,13
]}

Stehouwer, Coen D. A. ^{[7
,8
]}

Stenholm, Sari ^{[1
,2
,3
]}

Koster, Annemarie ^{[13
,14
]}

机构：

[1] Univ Turku, Dept Publ Hlth, Turku, Finland

[2] Turku Univ Hosp, Turku, Finland

[3] Univ Turku, Ctr Populat Hlth Res, Turku, Finland

[4] Maastricht Univ, Dept Methodol & Stat, Maastricht, Netherlands

[5] Maastricht Univ, Care & Publ Hlth Res Inst CAPHRI, Maastricht, Netherlands

[6] Royal Coll Surg Ireland RCSI, Sch Pharm & Biomol Sci, Dublin, Ireland

[7] Maastricht Univ, Sch Cardiovasc Dis, Cardiovasc Res Inst Maastricht, Maastricht, Netherlands

[8] Maastricht Univ, Med Ctr, Dept Internal Med, Maastricht, Netherlands

[9] Maastricht Univ, Dept Nutr & Movement Sci, Maastricht, Netherlands

[10] Maastricht Univ, NUTRIM Sch Nutr & Translat Res Metab, Maastricht, Netherlands

[11] Radboud Univ Nijmegen, Med Ctr, Dept Internal Med, Nijmegen, Netherlands

[12] Maastricht Univ, Dept Epidemiol, Maastricht, Netherlands

[13] Maastricht Univ, CAPRHI Care & Publ Hlth Res Inst, Maastricht, Netherlands

[14] Maastricht Univ, Dept Social Med, Maastricht, Netherlands

[15] Univ Turku, Dept Publ Hlth, FI-20014 Turku, Finland

来源：

MEDICINE & SCIENCE IN SPORTS & EXERCISE | 2023年 / 55卷 / 05期

基金：

芬兰科学院;

关键词：

PHYSICAL ACTIVITY; TRAJECTORY MODELING; CARDIOMETABOLIC HEALTH; BIOMARKERS; TYPE; 2; DIABETES; SEDENTARY BEHAVIOR; RISK-FACTORS; ACCELEROMETRY; PARADOX; DISEASE; ADULTS; AGE;

D O I：

10.1249/MSS.0000000000003108

中图分类号：

G8 [体育];

学科分类号：

04 ; 0403 ;

摘要：

PurposeThis study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design.MethodsOverall 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.ResultsOverall, 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.ConclusionsThe 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.

引用

页码：837 / 846

页数：10

共 36 条

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