Tom J. Hazell

Effects of exercise intensity on plasma concentrations of appetite-regulating hormones: Potential mechanisms.

The physiological control of appetite regulation involves circulating hormones with orexigenic (appetite-stimulating) and anorexigenic (appetite-inhibiting) properties that induce alterations in energy intake via perceptions of hunger and satiety. As the effectiveness of exercise to induce weight loss is a controversial topic, there is considerable interest in the effect of exercise on the appetite-regulating hormones such as acylated ghrelin, peptide YY (PYY), glucagon-like peptide-1 (GLP-1), and pancreatic polypeptide (PP). Research to date suggests short-term appetite regulation following a single exercise session is likely affected by decreases in acylated ghrelin and increases in PYY, GLP-1, and PP. Further, this exercise-induced response may be intensity-dependent. In an effort to guide future research, it is important to consider how exercise alters the circulating concentrations of these appetite-regulating hormones. Potential mechanisms include blood redistribution, sympathetic nervous system activity, gastrointestinal motility, cytokine release, free fatty acid concentrations, lactate production, and changes in plasma glucose and insulin concentrations. This review of relevant research suggests blood redistribution during exercise may be important for suppressing ghrelin, while other mechanisms involving cytokine release, changes in plasma glucose and insulin concentrations, SNS activity, and muscle metabolism likely mediate changes in the anorexigenic signals PYY and GLP-1. Overall, changes in appetite-regulating hormones following acute exercise appear to be intensity-dependent, with increasing intensity leading to a greater suppression of orexigenic signals and greater stimulation of anorexigenic signals. However, there is less research on how exercise-induced responses in appetite-regulating hormones differ between sexes or different age groups. A better understanding of how exercise intensity and workload affect appetite across the sexes and life stages will be a powerful tool in developing more successful strategies for managing weight.

Vitamin D supplementation trial in infancy: body composition effects at 3 years of age in a prospective follow-up study from Montréal.

The impact of vitamin D status on body composition is not well understood.

Four weeks of running sprint interval training improves cardiorespiratory fitness in young and middle-aged adults

ABSTRACT The purpose of this study was to determine the effectiveness of a 4-week running sprint interval training protocol to improve both aerobic and anaerobic fitness in middle-aged adults (40–50 years) as well as compare the adaptations to younger adults (20–30 years). Twenty-eight inactive participants – 14 young 20–30-year-olds (n = 7 males) and 14 middle-aged 40–50-year-olds (n = 5 males) – completed 4 weeks of running sprint interval training (4 to 6, 30-s “all-out” sprints on a curved, self-propelled treadmill separated by 4 min active recovery performed 3 times per week). Before and after training, all participants were assessed for maximal oxygen consumption (VO2max), 2000 m time trial performance, and anaerobic performance on a single 30-s sprint. There were no interactions between group and time for any tested variable, although training improved relative VO2max (young = 3.9, middle-aged = 5.2%; P < 0.04), time trial performance (young = 5.9, middle-aged = 8.2%; P < 0.001), peak sprint speed (young = 9.3, middle-aged = 2.2%; P < 0.001), and average sprint speed (young = 6.8, middle-aged = 11.6%; P < 0.001) in both young and middle-aged groups from pre- to post-training on the 30-s sprint test. The current study demonstrates that a 4-week running sprint interval training programme is equally effective at improving aerobic and anaerobic fitness in younger and middle-aged adults.

Foot-to-foot bioelectrical impedance accurately tracks direction of adiposity change in overweight and obese 7- to 13-year-old children.

Body composition measurements are valuable when evaluating pediatric obesity interventions. We hypothesized that foot-to-foot bioelectrical impedance analysis (BIA) will accurately track the direction of adiposity change, but not magnitude, in part due to differences in fat patterning. The purposes of this study were to examine the accuracy of body composition measurements of overweight and obese children over time using dual-energy x-ray absorptiometry (DXA) and BIA and to determine if BIA accuracy was affected by fat patterning. Eighty-nine overweight or obese children (48 girls, 41 boys, age 7-13 years) participating in a randomized controlled trial providing a family-centered, lifestyle intervention, underwent DXA and BIA measurements every 3 months. Bland-Altman plots showed a poor level of agreement between devices for baseline percent body fat (%BF; mean, 0.398%; +2SD, 8.685%; -2SD, -7.889%). There was overall agreement between DXA and BIA in the direction of change over time for %BF (difference between visits 3 and 1: DXA -0.8 ± 0.5%, BIA -0.7 ± 0.5%; P = 1.000) and fat mass (FM; difference between visits 3 and 1: DXA 0.7 ± 0.5 kg, BIA 0.6 ± 0.5 kg; P = 1.000). Bioelectrical impedance analysis measurements of %BF and FM at baseline were significantly different in those with android and gynoid fat (%BF: 35.9% ± 1.4%, 32.2% ± 1.4%, P < .003; FM: 20.1 ± 0.8 kg, 18.4 ± 0.8, P < .013). Bioelectrical impedance analysis accurately reports the direction of change in FM and FFM in overweight and obese children; inaccuracy in the magnitude of BIA measurements may be a result of fat patterning differences.

Establishing a practical treadmill sprint as an alternative to the Wingate anaerobic test

ABSTRACT This study examined the validity and reliability of a 30-second running sprint test using two non-motorized treadmills compared to the established Wingate Anaerobic Test. Twenty-four participants completed three sessions in a randomized order on a: (1) manual mode treadmill (Woodway); (2) specialized interval training treadmill (HiTrainer); and (3) Wingate cycle ergometer. In a subset of 15 participants, 2 additional sessions were completed on both treadmills to establish the test–retest reliability. Peak (Woodway: r = .68; HiTrainer: r = .58; p < .003), average (Woodway: r = .82; HiTrainer: r = .72, p < .001), and minimum (Woodway: r = .64; HiTrainer: r = .42, p < .043) speed indices were moderately to very strongly correlated with corresponding Wingate Anaerobic Test outputs and had excellent test–retest reliability (all intraclass correlation coefficients > .75). Fatigue index during the Wingate Anaerobic Test (51.20 ± 7.14%) was moderately correlated with the Woodway (32.9 ± 10.9%, r = .55, p = .005) only. This 30-second running sprint test may be a valid and reliable mode-specific alternative to the Wingate Anaerobic Test.

Creatine co-ingestion with carbohydrate or cinnamon extract provides no added benefit to anaerobic performance

Abstract The insulin response following carbohydrate ingestion enhances creatine transport into muscle. Cinnamon extract is promoted to have insulin-like effects, therefore this study examined if creatine co-ingestion with carbohydrates or cinnamon extract improved anaerobic capacity, muscular strength, and muscular endurance. Active young males (n = 25; 23.7 ± 2.5 y) were stratified into 3 groups: (1) creatine only (CRE); (2) creatine+ 70 g carbohydrate (CHO); or (3) creatine+ 500 mg cinnamon extract (CIN), based on anaerobic capacity (peak power·kg−1) and muscular strength at baseline. Three weeks of supplementation consisted of a 5 d loading phase (20 g/d) and a 16 d maintenance phase (5 g/d). Pre- and post-supplementation measures included a 30-s Wingate and a 30-s maximal running test (on a self-propelled treadmill) for anaerobic capacity. Muscular strength was measured as the one-repetition maximum 1-RM for chest, back, quadriceps, hamstrings, and leg press. Additional sets of the number of repetitions performed at 60% 1-RM until fatigue measured muscular endurance. All three groups significantly improved Wingate relative peak power (CRE: 15.4% P = .004; CHO: 14.6% P = .004; CIN: 15.7%, P = .003), and muscular strength for chest (CRE: 6.6% P < .001; CHO: 6.7% P < .001; CIN: 6.4% P < .001), back (CRE: 5.8% P < .001; CHO: 6.4% P < .001; CIN: 8.1% P < .001), and leg press (CRE: 11.7% P = .013; CHO: 10.0% P = .007; CIN: 17.3% P < .001). Only the CRE (10.4%, P = .021) and CIN (15.5%, P < .001) group improved total muscular endurance. No differences existed between groups post-supplementation. These findings demonstrate that three different methods of creatine ingestion lead to similar changes in anaerobic power, strength, and endurance.

Excess Postexercise Oxygen Consumption and Fat Utilization Following Submaximal Continuous and Supramaximal Interval Running

ABSTRACT Purpose: Few studies have directly compared excess postexercise oxygen consumption (EPOC) and fat utilization following different exercise intensities, and the effect of continuous exercise exceeding 75% of maximal oxygen uptake (VO2max) on these parameters remains unexplored. The current study examined EPOC and fat utilization following acute moderate- and vigorous-intensity continuous training (MICT and VICT) and sprint interval training (SIT). Methods: Eight active young men performed 4 experimental sessions: (a) MICT (30 min of running at 65% VO2max); (b) VICT (30 min of running at 85% VO2max); (c) SIT (4 30-s “all-out” sprints with 4 min of rest); and (d) no exercise (REST). Excess postexercise oxygen consumption and fat oxidation were estimated from gas measurements (VO2 and carbon dioxide production [VCO2]) obtained during a 2-hr postexercise period. Results: Total EPOC was similar (p = .097; effect size [ES] = 0.3) after VICT (8.6 ± 4.7 L) and SIT (10.0 ± 4.2 L) and greater after both (VICT, p = .025, ES = 0.3, and SIT, p < .001, ES = 0.6) versus MICT (6.0 ± 4.3 L). Fat utilization increased after MICT (0.047 ± 0.018 g· min−1, p = .018, ES = 1.3), VICT (0.066 ± 0.020 g•min−1, p = .034, ES = 2.2), and SIT (0.115 ± 0.026 g•min−1, p < .001, ES = 4.0) versus REST (0.025 ± 0.018 g•min−1) and was greatest after SIT (p < .001, ES = 3.0 vs. MICT; p = .031, ES = 2.1 vs. VICT). Conclusion: Acute exercise increases EPOC and fat utilization in an intensity-dependent manner.

Modified sprint interval training protocols: Physiological and psychological responses to four weeks of training

Sprint interval training (SIT) protocols involving brief (≤15 s) work bouts improve aerobic and anaerobic performance, highlighting peak speed generation as a potentially important adaptive stimulus. To determine the physiological and psychological effects of reducing the SIT work bout duration, while maintaining total exercise and recovery time, 43 healthy males (n = 27) and females (n = 16) trained for 4 weeks (3 times/week) using one of the following running SIT protocols: (i) 30:240 (n = 11; 4-6 × 30-s bouts, 4 min rest); (ii) 15:120 (n = 11; 8-12 × 15-s bouts, 2 min rest); (iii) 5:40 (n = 12; 24-36 × 5-s bouts, 40 s rest); or (iv) served as a nonexercising control (n = 9). Protocols were matched for total work (2-3 min) and rest (16-24 min) durations, as well as the work-to-rest ratio (1:8 s). Pre- and post-training measures included a graded maximal oxygen consumption test, a 5-km time trial, and a 30-s maximal sprint test. Self-efficacy, enjoyment, and intentions were assessed following the last training session. Training improved maximal oxygen consumption (5.5%; P = 0.006) and time-trial performance (5.2%; P = 0.039), with a main effect of time for peak speed (1.7%; P = 0.042), time to peak speed (25%; P < 0.001), and body fat percentage (1.4%; P < 0.001) that appeared to be driven by the training. There were no group effects for self-efficacy (P = 0.926), enjoyment (P = 0.249), or intentions to perform SIT 3 (P = 0.533) or 5 (P = 0.951) times/week. This study effectively demonstrated that the repeated generation of peak speed during brief SIT work bouts sufficiently stimulates adaptive mechanisms promoting increases in aerobic and anaerobic capacity.

Changes in eating behavior and plasma leptin in children with obesity participating in a family-centered lifestyle intervention

The goal of childhood obesity lifestyle interventions are to positively change body composition, however it is unknown if interventions also modulate factors that are related to energy intake. This study aimed to examine changes in eating behaviors and plasma leptin concentrations in overweight and obese children participating in a 1-year family-centered lifestyle intervention. Interventions were based on Canadian diet and physical activity (PA) guidelines. Children were randomized to 1 of 3 groups: Control (Ctrl; no intervention), Standard treatment (StnTx: 2 servings milk and alternatives/day (d), 3x/wk weight-bearing PA), or Modified treatment (ModTx: 4 servings milk and alternatives/day; daily weight-bearing PA). Study visits occurred every 3-months for 1-y; interventions were held once a month for 6-months with one follow-up visit at 8-months. Ctrl received counselling after 1-y. Caregivers completed the Childrens Eating Behavior Questionnaire (CEBQ) and reported on diet and activity. Plasma leptin were measured from morning fasted blood samples. Seventy-eight children (mean age 7.8 ± 0.8 y; mean BMI 24.4 ± 3.3 kg/m2) participated; 94% completed the study. Compared to baseline, at 6-months StnTx reduced Emotional Overeating and Desire to Drink scores (p < 0.05) while Food Responsiveness scores were reduced in both StnTx and ModTx (p < 0.05). At 1-year, scores for Desire to Drink in StnTx remained reduced compared to baseline (p < 0.05). Plasma leptin concentrations were significantly lower in ModTx at 6-months compared to baseline (p < 0.05). This study resulted in intervention groups favorably changing eating behaviors, supporting the use family-centered lifestyle interventions using Canadian diet and PA recommendations for children with obesity.

Commentary: Why sprint interval training is inappropriate for a largely sedentary population

Hardcastle et al. (2014) argued that an inactive population is unlikely to engage in sprint interval training (SIT) due to poor affective responses, low self-efficacy and motivation, and increased challenges to self-regulation. Their opinion article offers reasonable critiques to the potential broader effectiveness of SIT vis-a-vis the efficacy demonstrated within laboratory trials. However, three commentary responses (Del Vecchio et al., 2015; Astorino and Thum, 2016; Jung et al., 2016) have since been published with one common thread being to question the assumption that low affective perceptions necessarily accompany engagement in SIT. We have followed this debate with interest, in particular regarding affective responses to SIT [and, more broadly, high-intensity interval training (HIIT)]1. Building on the current debate, we further propose that in order to advance the research agenda, and specifically our understanding of “the acceptability of, and affective responses to, SIT programs” (Hardcastle et al., 2014, p. 2), a discussion of how and when affective responses are measured is warranted. Affect is believed to be related to, but distinct from, both emotion and mood (Ekkekakis, 2013). Ekkekakis (2013) further noted that “[e]xamples of core affect include pleasure, displeasure, tension, calmness, energy, and tiredness. A person experiences core affect constantly, although the nature and intensity of affect varies over time” (p. 38). The relationship between affect (and other psychological responses) and engagement in HIIT/SIT was examined in a recent scoping review (Stork et al., 2017). The review authors identified inconsistencies in the timing of when measures of affect were given across the included 42 studies, which resulted in some difficulty for comparisons across studies (Stork et al., 2017). In addition to timing, they also observed that “[m]any different measures were used to evaluate the same psychological constructs” (Stork et al., 2017, p. 25). It is this heterogeneity in measures we suggest requires further discussion and more purposeful consideration in future studies, in particular as it relates to replication. In the 17 studies that measured affect, Stork et al. (2017) reported that six different measures were used with the most common measure of affect being the Feeling Scale (FS; Hardy and Rejeski, 1989). Another psychological indicator, enjoyment, was assessed in 22 studies with five different