Estimation of energy consumed by middle-aged recreational marathoners during a marathon using accelerometry-based devices

Training Behaviors and Periodization Outline of Omnivorous, Vegetarian, and Vegan Recreational Runners (Part A)-Results from the NURMI Study (Step 2)

Runners train for long-distance competitions based on underlying motivations, which may be similar to individual dietary motivations (e.g., well-being and performance). Fundamental training differences may arise in recreational runners following different diet types (omnivore, vegetarian, vegan) considering possible motive variations. Following a cross-sectional design, distance runners completed a survey (online), including a thorough assessment of training behaviors with generic training details and periodization specifics in three phases: 1. an intermediary and rebound stage, 2. a main preparatory stage, and 3. a main event stage (tapering or interim event level/s). Kruskal-Wallis and chi-squared tests were used in the statistical analysis. A total of 245 fit recreational runners following omnivore (n = 109), vegetarian (n = 45), and vegan diets (n = 91) were included. Significant differences in the initial running motivation were found across dietary subgroups (p = 0.033) as well as for current motivations (p = 0.038), with vegetarians being the least health motivated (27% and 9%, respectively). No differences in each of the specific periods were found between diet types across the outline (p > 0.05). The present evidence shows that there is a lack of fundamental training differences based on recreational runners following different generic types of diets. The results of the present investigation may be especially relevant for future studies on safety, sustainability, and performance-enhancing dietary practices among athletes.

Interventions for Body Composition and Upper and Lower Extremity Muscle Strength in Older Adults in Rural Taiwan: A Horizontal Case Study

The purpose of this study was to understand the effects of a physical activity program and high-protein supplementation on body composition and upper and lower extremity muscle strength in male older adults in rural areas. In this study, 60 healthy male older adults (mean age 77.5 ± 4.6 years) from rural areas were recruited and randomly assigned to experimental group A (intervention of the physical activity program and high-protein supplementation), experimental group B (daily routine, with only intervention of high-protein supplementation), or control group C (daily routine). Experimental group A (EGa) carried out a physical activity plan three times a week, with an exercise intensity and calorie consumption of 250 kcal (5METs × ⅔hr × 75) for 3 months and drank a high-protein supplement (1.3 g/kg BW/day) after each exercise; experimental group B (EGb) followed only the intervention of high-protein supplementation. All the participants underwent pre- and post-tests for body composition, waist–hip circumference (WC, HC), handgrip strength (HS), 30 s dominant arm curl, 30 s sit to stand, and 2 min step tests. The results of the study showed that EGa significantly decreased body mass index (BMI), body fat mass (BFM), body fat percentage (BFP), WC, HC, and waist-to-hip ratio (WHR) and increased basal metabolic rate and muscle mass. Although both EGa and EGb used high-protein supplementation, EGa’s added three-month intervention of a physical activity program made it easier for that group to increase muscle mass and muscle strength. The WHR decreased from 1.015 to 0.931, representing a decrease of 8.28%, and an obvious weight loss effect was achieved. Thus, we concluded that the best way to maintain muscle strength in older adults is through physical activity with resistance and protein supplementation, which can reduce muscle loss in older adults.

Renal Function Recovery Strategies Following Marathon in Amateur Runners

Long distance races have a physiological impact on runners. Up to now, studies analyzing these physiological repercussions have been mainly focused on muscle and cardiac damage, as well as on its recovery. Therefore, a limited number of studies have been done to explore acute kidney failure and recovery after performing extreme exercises. Here, we monitored renal function in 76 marathon finishers (14 females) from the day before participating in a marathon until 192 h after crossing the finish line (FL). Renal function was evaluated by measuring serum creatinine (sCr) and the glomerular filtration rate (GFR). We randomly grouped our cohort into three intervention groups to compare three different strategies for marathon recovery: total rest (REST), continuous running at their ventilatory threshold 1 (VT1) intensity (RUN), and elliptical workout at their VT1 intensity (ELLIPTICAL). Interventions in the RUN and ELLIPTICAL groups were performed at 48, 96, and 144 h after marathon running. Seven blood samples (at the day before the marathon, at the FL, and at 24, 48, 96, 144, and 192 h post-marathon) and three urine samples (at the day before the marathon, at the finish line, and at 48 h post-marathon) were collected per participant. Both heart rate monitors and triaxial accelerometers were used to control the intensity effort during both the marathon race and the recovery period. Contrary to our expectations, the use of elliptical machines for marathon recovery delays renal function recovery. Specifically, the ELLIPTICAL group showed a significantly lower ∆GFR compared to both the RUN group (p = 4.5 × 10−4) and the REST group (p = 0.003). Hence, we encourage runners to carry out an active recovery based on light-intensity continuous running from 48 h after finishing the marathon. In addition, full resting seems to be a better strategy than performing elliptical workouts.

Training, Anthropometric, and Physiological Characteristics in Men Recreational Marathon Runners: The Role of Sport Experience

The aim of the present study was to examine the physiological and training characteristics in marathon runners with different sport experiences (defined as the number of finishes in marathon races). The anthropometry and physiological characteristics of men recreational endurance runners with three or less finishes in marathon races (novice group, NOV; n = 69, age 43.5 ± 8.0 years) and four or more finishes (experienced group, EXP; n = 66, 45.2 ± 9.4 years) were compared. EXP had faster personal best marathon time (3:44 ± 0:36 vs. 4:20 ± 0:44 h:min, p < 0.001, respectively); lower flexibility (15.9 ± 9.3 vs. 19.3 ± 15.9 cm, p = 0.022), abdominal (20.6 ± 7.9 vs. 23.8 ± 9.0 mm, p = 0.030) and iliac crest skinfold thickness (16.7 ± 6.7 vs. 19.9 ± 7.9 mm, p = 0.013), and body fat assessed by bioimpedance analysis (13.0 ± 4.4 vs. 14.6 ± 4.7%, p = 0.047); more weekly training days (4.6 ± 1.4 vs. 4.1 ± 1.0 days, p = 0.038); and longer weekly running distance (58.8 ± 24.0 vs. 47.2 ± 16.1 km, p = 0.001) than NOV. The findings indicated that long-term marathon training might induce adaptations in endurance performance, body composition, and flexibility.

Inflammation, muscle damage and postrace physical activity following a mountain ultramarathon

BACKGROUND

The study aimed at exploring whether muscle membrane disruption, as a surrogate for muscle damage, and inflammation recovery following a mountain ultramarathon (MUM) was related with race performance and postrace physical activity.

METHODS

Blood samples were obtained from thirty-four athletes (29 men and 5 women) before a 118-km MUM, immediately after and three- and seven-days postrace. Creatine kinase (CK), lactate dehydrogenase (LDH) and C-reactive protein (CRP) were compared between faster (FR) and slower (SR) runners. Physical activity performed during the week following the MUM was objectively analyzed using accelerometers and compared between FR and SR.

RESULTS

CK was significantly higher in FR at 3 days postrace (P<0.012, d=1.17) and LDH was significantly higher in FR at 3- and 7-days postrace (P=0.005, d=1.01; P<0.015, d=1.05 respectively), as compared to SR. No significant differences were identified in postrace physical activity levels between FR and SR. Significant relationships were found between race time and CK and LDH concentrations at 3 days postrace (r<inf>s</inf>=-0.41, P=0.017; r<inf>s</inf>=-0.52, P=0.002 respectively) and 7 days postrace (r<inf>s</inf>=-0.36, P=0.039; r<inf>s</inf>=-0.46. P=0.007 respectively). However, postrace physical activity was not associated with muscle damage and inflammation recovery, except for light intensity and CRP at 3 days postrace (r<inf>s</inf>=-0.40, P=0.025).

CONCLUSIONS

Race time appeared to have a higher influence on muscle damage recovery than the intensity of physical activities performed in the week after running a MUM. Inflammatory activity takes longer to normalize than muscle damage following a MUM, it is not related with race time and lightly related with postrace physical activity.

Using Accelerometry for Evaluating Energy Consumption and Running Intensity Distribution Throughout a Marathon According to Sex

The proportion of females participating in long-distance races has been increasing in the last years. Although it is well-known that there are differences in how females and males face a marathon, higher research may be done to fully understand the intrinsic and extrinsic factors affecting sex differences in endurance performance. In this work, we used triaxial accelerometer devices to monitor 74 males and 14 females, aged 30 to 45 years, who finished the Valencia Marathon in 2016. Moreover, marathon split times were provided by organizers. Several physiological traits and training habits were collected from each participant. Then, we evaluated several accelerometry- and pace-estimated parameters (pacing, average change of speed, energy consumption, oxygen uptake, running intensity distribution and running economy) in female and male amateur runners. In general, our results showed that females maintained a more stable pacing and ran at less demanding intensity throughout the marathon, limiting the decay of running pace in the last part of the race. In fact, females ran at 4.5% faster pace than males in the last kilometers. Besides, their running economy was higher than males (consumed nearly 19% less relative energy per distance) in the last section of the marathon. Our results may reflect well-known sex differences in physiology (i.e., muscle strength, fat metabolism, VO_2max), and in running strategy approach (i.e., females run at a more conservative intensity level in the first part of the marathon compared to males). The use of accelerometer devices allows coaches and scientific community to constantly monitor a runner throughout the marathon, as well as during training sessions.

Physiological and Race Pace Characteristics of Medium and Low-Level Athens Marathon Runners

This study examined physiological and race pace characteristics of medium- (finish time < 240 min) and low-level (finish time > 240 min) recreational runners who participated in a challenging marathon route with rolling hills, the Athens Authentic Marathon. Fifteen athletes (age: 42 ± 7 years) performed an incremental test, three to nine days before the 2018 Athens Marathon, to determine maximal oxygen uptake (VO2 max), maximal aerobic velocity (MAV), energy cost of running (ECr) and lactate threshold velocity (vLTh), and were analyzed for their pacing during the race. Moderate- (n = 8) compared with low-level (n = 7) runners had higher (p < 0.05) VO2 max (55.6 ± 3.6 vs. 48.9 ± 4.8 mL·kg-1·min-1), MAV (16.5 ± 0.7 vs. 14.4 ± 1.2 km·h-1) and vLTh (11.6 ± 0.8 vs. 9.2 ± 0.7 km·h-1) and lower ECr at 10 km/h (1.137 ± 0.096 vs. 1.232 ± 0.068 kcal·kg-1·km-1). Medium-level runners ran the marathon at a higher percentage of vLTh (105.1 ± 4.7 vs. 93.8 ± 6.2%) and VO2 max (79.7 ± 7.7 vs. 68.8 ± 5.7%). Low-level runners ran at a lower percentage (p < 0.05) of their vLTh in the 21.1-30 km (total ascent/decent: 122 m/5 m) and the 30-42.195 km (total ascent/decent: 32 m/155 m) splits. Moderate-level runners are less affected in their pacing than low-level runners during a marathon route with rolling hills. This could be due to superior physiological characteristics such as VO2 max, ECr, vLTh and fractional utilization of VO2 max. A marathon race pace strategy should be selected individually according to each athlete's level.