Michael V. Fedewa

Effect of exercise training on C-reactive protein: a systematic review and meta-analysis of randomised and non-randomised controlled trials

Purpose C-reactive protein (CRP) is a marker of chronic systemic inflammation frequently used in cardiovascular disease risk assessment. The purpose of this meta-analysis was to provide a quantitative estimate of the magnitude of change in CRP following participation in physical exercise interventions. Methods All studies included in the meta-analysis were peer reviewed and published in English. Human participants were assigned to a non-exercise comparison group or exercise training group, with the intervention lasting ≥2 weeks. CRP levels were measured at baseline, during and/or after completion of the exercise training programme. Random-effects models were used to aggregate a mean effect size (ES), 95% CIs and potential moderators. Results 83 randomised and non-randomised controlled trials met the inclusion criteria and resulted in 143 effects (n=3769). The mean ES of 0.26 (95% CI 0.18 to 0.34, p<0.001) indicated a decrease in CRP following exercise training. A decrease in body mass index (BMI; β=1.20, SE=0.25, p<0.0001) and %Fat (β=0.76, SE=0.21, p=0.0002) were associated with a decrease in CRP, independently accounting for 11.1% and 6.6% of the variation in response, respectively. Exercise training led to a greater reduction in CRP when accompanied by a decrease in BMI (ES=0.38, 95% CI 0.26 to 0.50); however, a significant improvement in CRP occurred in the absence of weight loss (ES=0.19, 95% CI 0.10 to 0.28; both p<0.001). Conclusions These results suggest that engaging in exercise training is associated with a decrease in CRP levels regardless of the age or sex of the individual; however, greater improvements in CRP level occur with a decrease in BMI or %Fat.

Effect of Exercise Training on Non-Exercise Physical Activity: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BackgroundMany overweight and obese individuals use exercise when attempting to lose weight. However, the improvements in weight and body composition are often far less than expected. Levels of physical activity outside of the structured exercise program are believed to change and may be responsible for the unsuccessful weight loss.ObjectiveThe purpose of this meta-analysis was to provide a quantitative estimate of the change in non-exercise physical activity (NEPA) during exercise interventions.MethodsAll studies included in the meta-analysis were peer-reviewed and published in English. Participants were randomized to a non-exercise comparison group or exercise training group with an intervention lasting ≥2 weeks. NEPA was measured at baseline and at various times during the study. Hedges’ d effect size (ES) was used to adjust for small sample bias, and random-effects models were used to calculate the mean ES and explore potential moderators.ResultsThe cumulative results of 44 effects gathered from ten studies published between 1997 and 2015 indicated that NEPA did not change significantly during exercise training (ES = 0.02, 95% confidence interval [CI] −0.09 to 0.13; p = 0.723). Duration of the exercise session (β = −0.0039), intervention length (β = 0.0543), and an age × sex (β = −0.0005) interaction indicated that the increase in NEPA may be attenuated in older women during exercise training and during shorter exercise interventions with longer sessions (all p < 0.005).ConclusionOn average, no statistically or clinically significant mean change in NEPA occurs during exercise training. However, session duration and intervention length, age, and sex should be accounted for when designing exercise programs to improve long-term sustainability and improve the likelihood of weight loss success, as the initial decrease in NEPA appears to dissipate with continued training.

Validity of Selected Bioimpedance Equations for Estimating Body Composition in Men and Women: A Four-compartment Model Comparison

Abstract Nickerson, BS, Esco, MR, Bishop, PA, Schumacker, RE, Richardson, MT, Fedewa, MV, Wingo, JE, and Welborn, BA. Validity of selected bioimpedance equations for estimating body composition in men and women: a four-compartment model comparison. J Strength Cond Res 31(7): 1963–1972, 2017—The purpose of this study was to compare body fat percentage (BF%) and fat-free mass (FFM) values from bioelectrical impedance analysis (BIA) equations to values determined from a 4-compartment (4C) model. Eighty-two adults (42 men and 40 women) volunteered to participate (age = 23 ± 5 years). Body fat percentage and FFM were estimated from previously developed BIA equations by Chumlea et al. (BIACH), Deurenberg et al. (BIADE), Kyle et al. (BIAKYLE), and Sun et al. (BIASUN). Four-compartment model body composition was derived from underwater weighing for body density, dual-energy X-ray absorptiometry for bone mineral content, and bioimpedance spectroscopy for total body water. The standard error of estimate (SEE) for group BF% and FFM ranged from 3.0 to 3.8% and 2.1 to 2.7 kg, respectively. The constant error (CE) was significantly higher and lower for BF% and FFM (p < 0.001), respectively, for 3 BIA equations (BIACH, CE = 3.1% and −2.2 kg; BIADE, CE = 3.7% and −2.9 kg; BIAKYLE, CE = 2.3% and −1.9 kg), but was not significant for BF% (p = 0.702) and FFM (p = 0.677) for BIASUN (CE = −0.1% and 0.1 kg). The 95% limits of agreement were narrowest for BIACH (±5.9%; ±4.2 kg) and largest for BIADE (±7.4%; ±6.2 kg). The significant CE yielded by BIACH, BIADE, and BIAKYLE indicates these equations tend to overpredict group BF% and underestimate group FFM. However, all BIA equations produced low SEEs and fairly narrow limits of agreement. When the use of a 4C model is not available, practitioners might consider using one of the selected BIA equations, but should consider the associated CE.

Impact of Measured vs. Predicted Residual Lung Volume on Body Fat Percentage Using Underwater Weighing and 4-Compartment Model

Abstract Nickerson, BS, Esco, MR, Bishop, PA, Schumacker, RE, Richardson, MT, Fedewa, MV, Wingo, JE, and Welborn, BA. Impact of measured vs. predicted residual lung volume on body fat percentage using underwater weighing and 4-compartment model. J Strength Cond Res 31(9): 2519–2527, 2017—The purpose of this study was to compare underwater weighing (UWW) and 4-compartment (4C) model body fat percentage (BF%) for predicted vs. simultaneously measured residual lung volume (RLV). Forty-seven women and 33 men (age = 22 ± 5 years) had UWW and 4C model BF% determined using Boren et al. (RLVBOREN), Goldman and Becklake (RLVGB), and Miller et al. (RLVMILLER) RLV prediction equations. Criterion UWW BF% included body density (BD) values with simultaneous RLV. Criterion 4C model BF% included BD through UWW with simultaneous RLV, total body water through bioimpedance spectroscopy, and bone mineral content through dual-energy x-ray absorptiometry. The standard error of estimate (SEE) for UWW and 4C model BF% determined through RLV prediction equations varied from 2.0 to 2.6% and from 1.3 to 1.5%, respectively. The constant error (CE) was significantly different for UWW BF% when using RLVBOREN, RLVGB, and RLVMILLER (all p < 0.016; CE = 0.7, −2.0, 1.0%, respectively). However, the CEs for RLVBOREN and RLVMILLER were not significant in the 4C model (p = 0.73 and 0.11; CE = 0.1 and 0.2%, respectively), whereas RLVGB remained significantly different (p < 0.001; CE = −1.5%). The 95% limits of agreement were less than ±5.2% for UWW BF% and less than ±3.1% for the 4C model when using the 3 RLV equations. When used in a 4C model, the RLV equations yielded a smaller CE, SEE, and 95% limits of agreement than UWW BF% results. However, because of the range of individual error shown in the current study, caution should be employed when using the 4C model as a criterion method with predicted RLV.

Moderate, but not vigorous, intensity exercise training reduces C-reactive protein

Abstract Background: Sprint interval cycle training is a contemporary popular mode of training but its relative efficacy, under conditions of matched energy expenditure, to reduce risk factors for cardiometabolic disease is incompletely characterised, especially in young women. The purpose of this investigation was to determine the relative efficacy of six weeks of moderate-intensity cycling (MOD-C) and vigorous sprint-interval cycling (VIG-SIC) on lipid profile, insulin (INS) and insulin resistance using the homeostatic model assessment (HOMA-IR) and C-reactive protein (CRP) in inactive, overweight/obese (OW/OB) young women. Methods: Participants (BMI ≥25 kg/m2, waist circumference ≥88 cm) were randomly assigned to MOD-C (20–30 min at 60–70% of heart rate reserve(HRR)) or VIG-SIC (5–7 repeated bouts 30-second maximal effort sprints, followed by four minutes of active recovery) supervised training three days/week for six weeks, with each group matched on energy expenditure. Adiposity (%Fat) was measured using dual x-ray absorptiometry. Results: Forty-four participants (20.4 ± 1.6 years, 65.9% Caucasian, 29.8 ± 4.1 kg/m2) were included in the analysis. The improvement in CRP observed in the MOD-C group was larger than the VIG-C group (p = .034). Overall, high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) levels improved following training (p < .05); however, total cholesterol, triglyceride, INS and HOMA-IR did not improve (p > .05). Conclusion: These results indicate MOD-C training may be more effective in reducing CRP than VIG-SIC.

Interactive associations of physical activity, adiposity, and oral contraceptive use on C-reactive protein levels in young women

ABSTRACT Oral contraceptives (OCs) are the most frequently used type of birth control among young women. OC-users have higher C-reactive protein (CRP) values, an indicator of systemic inflammation, than do non-OC-users. In addition, adiposity (percent fat) is positively associated with CRP, and physical activity (PA) is inversely associated with CRP. The present study determined the interactive associations of PA, percent fat, and OC-use with CRP. Data were collected during 2012–2015 at the University of Georgia. Objective PA was measured via pedometers. Percent fat was measured via dual X-ray absorptiometry. The current OC-use was self-reported. High-sensitivity (hs) CRP was determined using venipuncture. Multivariate linear regression determined the interactive associations of percent fat, OC-use, and PA with hs-CRP. Participants (n = 247; mean age 18.9 ± 1.4 years, 60.7 percent white) accumulated a mean of 10,075.7 ± 3,593.4 steps/day. One-third of participants were categorized as overweight/obese by BMI (mean = 24.5 ± 4.8 kg/m2, mean percent fat = 35.2 ± 6.8). The current OC-use was reported by 26.2 percent of the sample (n = 61). A significant three-way interaction (β = 0.01, p = .03) indicated that higher PA was associated with lower hs-CRP in non-OC-users with higher percent fat, but not among OC-users with higher percent fat. These results highlight the need to measure and account for the current OC-use in studies examining the relationship between PA and CRP.

Author’s Reply to Nunes et al.: Comment on: “Comparison of Periodized and Non-Periodized Resistance Training on Maximal Strength: A Meta-Analysis”

We appreciate the opportunity to respond to Nunes et al. [1]. The primary aim of our article [2] was to examine the current literature comparing periodized training to nonperiodized training and to quantify the effect periodized training has on 1-repetition maximum (1RM). We do not dispute Nunes et al.’s [1] argument that the principle of specificity may have influenced the strength outcomes in the studies included in our analysis. We agree that the programs utilizing greater loads will be more mechanically specific and drive adaptations for strength development. However, this concept is a central tenet of periodization. In the traditional model of periodization, training specificity gradually increases throughout the macrocycle and peaks prior to competition or testing session [3]. A program lacking training variation but adhering to the principle of specificity would require individuals to frequently train at high intensities (i.e., 1–5RM). This approach is not recommended, especially for advanced trainees, for a few reasons. First, training at high intensity for a long period of time may predispose an individual to accommodation or stagnation [4]. Variation in training loads is an important factor in breaking up the mechanical monotony that may occur during long-term linear loading [3]. Secondly, training variation is necessary for proper fatigue management [5]. Implementing ‘light’ days into a microcycle will allow for adequate volume to be achieved while also enhancing recovery efforts, which may lead to higher training intensities during the ‘heavy’ training days. Lastly, training at high intensity with low repetitions makes it difficult to accumulate adequate training volume. Advanced trainees typically require a greater amount of work performed in order to continue to develop higher levels of fitness. Variation in training allows for fluctuations in repetition ranges across a microcycle, making it easier to accumulate training volume. In a non-varied plan, more sets will need to be performed to reach a desired training volume due to the low number of repetitions completed per set. While the same volume can be achieved, training with a higher number of repetitions per set will increase the training density. Schoenfeld et al. [6] noted that a low repetition group (7 9 3RM) was able to accomplish the same volume load as the high repetition group (3 9 10RM), yet the high repetition group completed the sessions in a much shorter time than the low repetition group [6]. Varying the training loads and repetitions offers a more feasible approach to accumulating training volume, while still incorporating high-load training within a microcycle. Nunes et al. [1] noted that several of the studies included in our analysis compared a non-periodized single-set program with a periodized multi-set program. We do not disagree with their suggestion that this may have contributed to differences in strength gains. This point was identified in Sect. 4.6 as a limitation of our meta-analysis. Additionally, we performed a funnel plot and sensitivity & Tyler D. Williams twilli11@samford.edu

A novel method of utilizing skinfolds and bioimpedance for determining body fat percentage via a field-based three-compartment model

Background/objectivesThe purpose was to determine if skinfolds (SF) and bioelectrical impedance analysis (BIA) could provide accurate estimates of body volume (BV) and total body water (TBW), respectively, for use in a 3-compartment (3-C) model to estimate percent body fat (BF%) when compared to laboratory derived measures.Subjects/methodsA sample of sixty-four men (age = 22.9 ± 5.4 years) and 59 women (age = 21.6 ± 4.3 years) participated in the study. Laboratory 3-C (3CLAB) model BF% was determined with underwater weighing for body volume (BV) and bioimpedance spectroscopy for total body water (TBW). The 3-C field (3CFIELD) estimates of BF% included BV from the 7-site SF technique and TBW from hand-to-foot BIA.ResultsA significant difference in BF% (p < 0.01) was found between the 3CLAB and 3CFIELD in the entire sample and within the men, but the effect sizes (ES) were small (0.09 and 0.17, respectively). The difference between means was not significant in the women (ES = 0.05, p = 0.332). Compared to the 3CLAB, the total error (TE) ranged 2.2–2.4% for 3CFIELD, 5.7–5.8% for SF, and 4.0–4.6% for BIA.ConclusionsThe findings suggest that BV and TBW derived from SF and BIA, respectively, can be used in a 3CFIELD model to increase the accuracy of BF% estimates over SF and BIA alone.

Relative accuracy of body adiposity index and relative fat mass in participants with and without down syndrome

Background/ObjectivesThe body adiposity index (BAI) and relative fat mass (RFM) are anthropometric measures developed to estimate body composition (%Fat). There is limited research validating these methods of body composition assessment in adults with Down syndrome (DS). The aim of this study was to examine the accuracy of the BAI and RFM in a sample of adults with- and without DS. We hypothesize that the RFM would provide greater accuracy than the BAI when estimating %Fat.Subjects/MethodsBAI and RFM were assessed in a sample of adults (n = 235, 50.2% female, 20.0% DS, 23.1 ± 6.7 years). %Fat assessed using dual-energy X-ray absorptiometry served as the criterion method of body composition. Between-group differences were assessed using a two-way (SEX × DS) analysis of variance.ResultsBAI overestimated %Fat in men without DS, but underestimated %Fat in women without DS (4.1 ± 4.5%Fat vs. −3.5 ± 4.6%Fat, respectively, p < 0.001). BAI overestimated %Fat in men and women with DS (4.7 ± 7.8%Fat vs. 0.8 ± 7.5%Fat, respectively, p = 0.090). RFM slightly overestimated %Fat in male and female participants without DS, and did not vary by sex (0.9 ± 4.0%Fat vs. 0.2 ± 4.2%Fat, respectively, p = 0.248). RFM underestimated %Fat in men and women with DS, with no differences observed between sexes (−2.1 ± 5.3%Fat vs. −2.2 ± 6.9%Fat, respectively, p = 0.953).ConclusionsThe BAI and RFM can be used to estimate body composition in individuals with- and without DS, however, the RFM yields greater accuracy and is recommended when more advanced methods of body composition assessment are unavailable or create unwanted participant burden.

Authors’ reply to Medeiros et al.: Make it easier! Evaluation of the ‘vagal-sympathetic effect’ in different conditions with R–R intervals monitoring

Abbreviations HRV Heart rate variability LF Low frequency power LF:HF Low frequency to high frequency ratio RMSSD Root mean square of successive normalto-normal interval differences SDNN Standard deviation of normal-to-normal R–R intervals SDNN:RMSSD The ratio between standard deviation of normal-to-normal R–R intervals to root mean square of successive normal-tonormal interval differences Dear Editor,