Maximal Estimated Cardiorespiratory Fitness, Cardiometabolic Risk Factors, and Metabolic Syndrome in the Aerobics Center Longitudinal Study
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Objective To examine the relationship between estimated maximal cardiorespiratory fitness (CRF) and metabolic syndrome (MetSyn).Patients and methods We performed a cross-sectional analysis of 38,659 Aerobics Center Longitudinal Study participants seen between January 1, 1979, and December 31, 2006, to examine CRF levels defined as low (lower 20%), moderate (middle 40%), and high (upper 40%) of age- and sex-specific distributions vs National Cholesterol Education Program-derived MetSyn expressed as a summed z-score continuous variable. We used a general linear model for continuous variables, the χ(2) test for distribution of categorical variables, and multiple linear regression for single and cumulative MetSyn scores adjusted for body mass index, smoking status, alcohol intake, and family history of cardiovascular disease.Results We observed significant inverse trends for MetSyn vs CRF in both sexes (P for trend <.001). The CRF associations vs individual components were as follows: waist circumference-men: β=-.14, r(2)=0.78; women: β=-.04, r(2)=0.71; triglycerides-men: β=-.29, r(2)=0.18; women: β=-.17, r(2)=0.18; high-density lipoprotein cholesterol-men: β=.25, r(2)=0.17; women: β=.08, r(2)=0.19; fasting glucose-men: β=-.09, r(2)=0.09; women: β=.09, r(2)=0.01; systolic blood pressure-men: β=-.09, r(2)=0.09; women: β=-.01, r(2)=0.21; and diastolic blood pressure-men: β=-.07, r(2)=0.12; women: β=-.05, r(2)=0.14. All associations except for systolic blood pressure (both sexes) and glucose (women) are significant (P<.001).Conclusion Cardiorespiratory fitness demonstrated a strong inverse relationship with MetSyn in both sexes, with the strongest single associative component being waist circumference.
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Exercise may increase blood lipid consumption, thereby decreasing lipid levels.
“Although the mechanism of exercise-induced lipid changes is unclear, exercise itself may increase blood lipid consumption hence to decrease lipids levels [60].”
From Effects of aerobic exercise on lipids and lipoproteins (2017) · cites this paper as [60]
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- Authors
- Earnest, C. P., Artero, E. G., Sui, X., Lee, D.-C., Church, T. S., & Blair, S. N.
- Affiliations
- University of Bath (GB)
- University of South Carolina (US)
- Iowa State University (US)
- Pennington Biomedical Research Center (US)
- Corresponding author
- Earnest, Conrad P.
- ORCID
- Venue
- Mayo Clinic Proceedings
- Publisher
- Elsevier BV
- Published
- 2013-03
- Volume
- 88
- Issue
- 3
- Pages
- 259-270
- ISSN
- 0025-6196 (ISSN-L)
- PMC
- PMC3622904
- OpenAlex
- W1966415391
- Cited by
- 170
- References
- 38
- Citations by year
- 2026: 1 · 2025: 14 · 2024: 23 · 2023: 25 · 2022: 8 · 2021: 11 · 2020: 15 · 2019: 20 · 2018: 13 · 2017: 14 · 2016: 11 · 2015: 5 · 2014: 7 · 2013: 3
- FWCI
- 6.03
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Mayo Clinic Proceedings (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Department of Defense
- American Heart Association
- Ministerio de Educación, Cultura y Deporte (EX-2010-1008)
- National Institutes of Health (AG06945, HL62508, R21DK088195)
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Health Sciences › Medicine › Complementary and alternative medicine › Cardiovascular and exercise physiology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- cardiorespiratory fitness, metabolic syndrome, cardiometabolic risk factors, waist circumference, triglycerides, HDL cholesterol, fasting blood glucose, blood pressure, Aerobics Center Longitudinal Study, sex differences
- MeSH terms
- Adult, Aged, Blood Glucose, Blood Pressure, Cross-Sectional Studies, Exercise Test, Female, Humans, Cholesterol, HDL, Male, Middle Aged, Oxygen Consumption, Physical Fitness, Risk Factors, Triglycerides, Biomarkers, Chi-Square Distribution, Linear Models, Metabolic Syndrome, Waist Circumference
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