Association Between Physical Activity Timing and Metabolic Syndrome in Korea: A Functional Principal Component Approach
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Source and Study Design
2.2. Study Participants
2.3. Physical Activity
- (1)
- Inactive: 0 min/week;
- (2)
- Insufficiently active: 1–149 min/week;
- (3)
- Active: 150–299 min/week;
- (4)
- Highly active: ≥300 min/week.
2.4. Diagnostic Criteria for Metabolic Syndrome
2.5. Confounding Factors
3. Statistical Analysis
3.1. Participant Characteristics by Metabolic Syndrome Status
3.2. Functional Principal Component Analysis of Physical Activity
3.3. Association Between Functional Principal Component Scores and Metabolic Syndrome
4. Results
4.1. Participant Characteristics
4.2. Temporal Variation in Physical Activity
4.3. Association Between Principal Component Scores and Metabolic Syndrome
- (1)
- Model 1: A simple logistic regression model including only the FPCA scores (PC1–PC4) as independent variables to estimate unadjusted odds ratios.
- (2)
- Model 2: Adjusted for key demographic confounding variables—age, sex, family income, alcohol consumption, and smoking status.
- (3)
- Model 3: Further included occupation type and work schedule type—in addition to model 2.
- (4)
- Model 4: Additionally included MVPA-based activity groups (i.e., inactive, insufficiently active, active, and highly active) to account for physical activity volume.
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristic | Without MetS (n = 1347) | MetS (n = 549) | Total (n = 1896) | p-Value |
---|---|---|---|---|
Age, mean (SD) | 41.9 (12.5) | 49.4 (9.4) | 43.5 (12.3) | <0.001 |
Sex, no. (%) | ||||
Male | 406 (30.1) | 306 (55.7) | 712 (37.6) | <0.001 |
Female | 941 (69.9) | 243 (44.3) | 1184 (62.4) | |
Family income, no. (%) | ||||
1st quartile | 186 (13.8) | 109 (19.9) | 295 (15.6) | <0.001 |
2nd quartile | 365 (27.1) | 176 (32.1) | 541 (28.5) | |
3rd quartile | 420 (31.2) | 129 (23.5) | 549 (29.0) | |
4th quartile | 376 (27.9) | 135 (24.6) | 511 (27.0) | |
Smoking status, no. (%) | ||||
Non-smoker | 984 (73.1) | 281 (51.2) | 1265 (66.7) | <0.001 |
Former smoker | 201 (14.9) | 163 (29.7) | 364 (19.2) | |
Current smoker | 162 (12.0) | 105 (19.1) | 267 (14.1) | |
Alcohol consumption, no. (%) | ||||
Non-drinker | 289 (21.5) | 115 (20.9) | 404 (21.3) | <0.001 |
1 or less times/week | 492 (36.5) | 149 (27.1) | 641 (33.8) | |
2–4 times/month | 342 (25.4) | 133 (24.2) | 475 (25.1) | |
2–3 times/week | 176 (13.1) | 100 (18.2) | 276 (14.6) | |
4 or more times/week | 48 (3.6) | 52 (9.5) | 100 (5.3) | |
Occupation type, no. (%) | ||||
Non-manual worker | 703 (52.2) | 204 (37.2) | 907 (47.8) | <0.001 |
Manual worker | 554 (41.1) | 284 (51.7) | 838 (44.2) | |
Economically inactive | 90 (6.7) | 61 (11.1) | 151 (8.0) | |
Work schedule type, no. (%) | ||||
Day shift | 822 (61.0) | 402 (73.2) | 1224 (64.6) | <0.001 |
Evening/night shift | 150 (11.1) | 34 (6.2) | 184 (9.7) | |
Rotating shift | 42 (3.1) | 19 (3.5) | 61 (3.2) | |
Other | 5 (0.4) | 4 (0.7) | 9 (0.5) | |
Not employed | 328 (24.4) | 90 (16.4) | 418 (22.0) | |
Activity group, no. (%) | ||||
Inactive (0 min/week) | 318 (23.6) | 129 (23.4) | 447 (23.6) | 0.994 |
Insufficiently active (1–149 min/week) | 829 (61.5) | 340 (61.9) | 1169 (61.6) | |
Active (150–299 min/week) | 150 (11.1) | 61 (11.1) | 211 (11.1) | |
Highly active (≥300 min/week) | 50 (3.7) | 19 (3.4) | 69 (3.6) | |
Metabolic syndrome factors | ||||
SBP, mean (SD) | 109.3 (11.5) | 125.9 (14.5) | 114.1 (14.5) | <0.001 |
DBP, mean (SD) | 72.0 (8.0) | 82.6 (9.9) | 75.1(9.8) | <0.001 |
GLU, median (IQR) | 91.0 (9.0) | 104.0 (17.0) | 93.0 (13.0) | <0.001 |
WC, mean (SD) | 76.6 (7.9) | 88.7 (8.6) | 80.1 (9.8) | <0.001 |
TG, median (IQR) | 81.0 (59.0) | 171.0 (109.0) | 99.0 (89.0) | <0.001 |
HDL-C, mean (SD) | 55.2 (12.6) | 46.0 (10.4) | 52.5 (12.7) | <0.001 |
Variable | Model 1 | Model 2 | Model 3 | Model 4 | ||||
---|---|---|---|---|---|---|---|---|
Unadjusted OR (95% CI) | p-Value | Adjusted OR (95% CI) | p-Value | Adjusted OR (95% CI) | p-Value | Adjusted OR (95% CI) | p-Value | |
PC1 | 1.016 (0.921, 1.121) | 0.750 | 1.061 (0.952, 1.182) | 0.285 | 1.048 (0.939, 1.167) | 0.406 | 1.050 (0.941, 1.171) | 0.381 |
PC2 | 1.004 (0.911, 1.107) | 0.930 | 0.979 (0.881, 1.089) | 0.705 | 0.974 (0.875, 1.084) | 0.629 | 0.976 (0.877, 1.086) | 0.650 |
PC3 | 1.061 (0.963, 1.169) | 0.232 | 1.105 (0.993, 1.230) | 0.067 | 1.118 (1.004, 1.246) | 0.042 | 1.117 (1.003, 1.244) | 0.044 |
PC4 | 1.036 (0.939, 1.142) | 0.481 | 1.010 (0.909, 1.123) | 0.848 | 1.009 (0.908, 1.123) | 0.856 | 1.008 (0.906, 1.121) | 0.884 |
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Park, S.; Jee, H.-J. Association Between Physical Activity Timing and Metabolic Syndrome in Korea: A Functional Principal Component Approach. Healthcare 2025, 13, 1384. https://doi.org/10.3390/healthcare13121384
Park S, Jee H-J. Association Between Physical Activity Timing and Metabolic Syndrome in Korea: A Functional Principal Component Approach. Healthcare. 2025; 13(12):1384. https://doi.org/10.3390/healthcare13121384
Chicago/Turabian StylePark, Suah, and Hee-Jung Jee. 2025. "Association Between Physical Activity Timing and Metabolic Syndrome in Korea: A Functional Principal Component Approach" Healthcare 13, no. 12: 1384. https://doi.org/10.3390/healthcare13121384
APA StylePark, S., & Jee, H.-J. (2025). Association Between Physical Activity Timing and Metabolic Syndrome in Korea: A Functional Principal Component Approach. Healthcare, 13(12), 1384. https://doi.org/10.3390/healthcare13121384