Xiaochen Lin, MS,1 Xi Zhang, PhD,3 Jianjun Guo, MD,4 Christian K Roberts, PhD,5 Steve McKenzie, PhD,6 Wen-Chih Wu, MD,1,2 Simin Liu, MD, ScD,1,2,7 and Yiqing Song, MD, ScD3
Xiaochen Lin
1Department of Epidemiology, School of Public Health, Brown University, Providence, RI
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Xi Zhang
3Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN
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Jianjun Guo
4Center for the Youth Sport Research and Development, China Institute of Sport Science, Beijing, China
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Christian K Roberts
5Geriatrics, Research, Education and Clinical Centers, VA Greater Los Angeles Healthcare System, Los Angeles, CA
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Steve McKenzie
6Department of Kinesiology, Center for Physical Activity in Wellness and Prevention, Indiana University-Purdue University at Indianapolis, IN
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Wen-Chih Wu
1Department of Epidemiology, School of Public Health, Brown University, Providence, RI
2Division of Cardiology and Veterans Affairs Medical Center, Department of Medicine, Alpert Medical School, Brown University, Providence, RI
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Simin Liu
1Department of Epidemiology, School of Public Health, Brown University, Providence, RI
2Division of Cardiology and Veterans Affairs Medical Center, Department of Medicine, Alpert Medical School, Brown University, Providence, RI
7Division of Endocrinology, Department of Medicine, Rhode Island Hospital, Providence, RI
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Yiqing Song
3Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN
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Author information Article notes Copyright and License information Disclaimer
1Department of Epidemiology, School of Public Health, Brown University, Providence, RI
2Division of Cardiology and Veterans Affairs Medical Center, Department of Medicine, Alpert Medical School, Brown University, Providence, RI
3Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN
4Center for the Youth Sport Research and Development, China Institute of Sport Science, Beijing, China
5Geriatrics, Research, Education and Clinical Centers, VA Greater Los Angeles Healthcare System, Los Angeles, CA
6Department of Kinesiology, Center for Physical Activity in Wellness and Prevention, Indiana University-Purdue University at Indianapolis, IN
7Division of Endocrinology, Department of Medicine, Rhode Island Hospital, Providence, RI
Correspondence to: Simin Liu, MD, ScD, Department of Epidemiology and Medicine, Brown University, 121 South Main St, Providence, RI 02903. E-mail: ude.nworb@uil_nimiS and Yiqing Song, MD, ScD, Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, 714 North Senate Avenue, Indianapolis, IN 46202. E-mail: ude.ui@gnosqiy
Received 2015 Apr 2; Accepted 2015 Apr 30.
Copyright © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Abstract
Background
Guidelines recommend exercise for cardiovascular health, although evidence from trials linking exercise to cardiovascular health through intermediate biomarkers remains inconsistent. We performed a meta-analysis of randomized controlled trials to quantify the impact of exercise on cardiorespiratory fitness and a variety of conventional and novel cardiometabolic biomarkers in adults without cardiovascular disease.
Methods and Results
Two researchers selected 160 randomized controlled trials [7487 participants] based on literature searches of Medline, Embase, and Cochrane Central [January 1965 to March 2014]. Data were extracted using a standardized protocol. A random-effects meta-analysis and systematic review was conducted to evaluate the effects of exercise interventions on cardiorespiratory fitness and circulating biomarkers. Exercise significantly raised absolute and relative cardiorespiratory fitness. Lipid profiles were improved in exercise groups, with lower levels of triglycerides and higher levels of high-density lipoprotein cholesterol and apolipoprotein A1. Lower levels of fasting insulin, homeostatic model assessment–insulin resistance, and glycosylated hemoglobin A1c were found in exercise groups. Compared with controls, exercise groups had higher levels of interleukin-18 and lower levels of leptin, fibrinogen, and angiotensin II. In addition, we found that the exercise effects were modified by age, sex, and health status such that people aged 10 hours of fasting.
Data Synthesis and Analysis
Methodological quality was assessed by 2 investigators [X.L., X.Z.] using the Cochrane Collaboration’s tool for assessing risk of bias.29 This included random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other sources of bias. For each trial, the risk of bias was reported as low risk, unclear risk, or high risk. Disagreement was resolved by discussion. All eligible comparisons from each trial were extracted separately according to exercise intensity. The criteria for classifying exercise interventions as moderate exercise or vigorous exercise are summarized in TableTable2.2. If the intensity measures were not reported in individual studies, maximum heart rate, maximum heart rate percentage, speed of running, metabolic equivalent, oxygen uptake, or relative metabolic rate were used to classify exercise intensity. To maintain independence, the most vigorous intervention and the control group in each trial were included in the primary analysis if multiple training groups of different intensities were compared with a single control group. Sensitivity analyses were performed by conducting separate analyses of all eligible comparisons for moderate and vigorous exercise interventions, respectively.
Table 2
Criteria Used for Exercise Intensity Classification
ModerateVigorousMaximum heart rate, beats/min