Leisure-time running reduces all-cause and cardiovascular mortality risk

BACKGROUND

Although running is a popular leisure-time physical activity, little is known about the long-term effects of running on mortality. The dose-response relations between running, as well as the change in running behaviors over time, and mortality remain uncertain.

OBJECTIVES

We examined the associations of running with all-cause and cardiovascular mortality risks in 55,137 adults, 18 to 100 years of age (mean age 44 years).

METHODS

Running was assessed on a medical history questionnaire by leisure-time activity.

RESULTS

During a mean follow-up of 15 years, 3,413 all-cause and 1,217 cardiovascular deaths occurred. Approximately 24% of adults participated in running in this population. Compared with nonrunners, runners had 30% and 45% lower adjusted risks of all-cause and cardiovascular mortality, respectively, with a 3-year life expectancy benefit. In dose-response analyses, the mortality benefits in runners were similar across quintiles of running time, distance, frequency, amount, and speed, compared with nonrunners. Weekly running even <51 min, <6 miles, 1 to 2 times, <506 metabolic equivalent-minutes, or <6 miles/h was sufficient to reduce risk of mortality, compared with not running. In the analyses of change in running behaviors and mortality, persistent runners had the most significant benefits, with 29% and 50% lower risks of all-cause and cardiovascular mortality, respectively, compared with never-runners.

CONCLUSIONS

Running, even 5 to 10 min/day and at slow speeds <6 miles/h, is associated with markedly reduced risks of death from all causes and cardiovascular disease. This study may motivate healthy but sedentary individuals to begin and continue running for substantial and attainable mortality benefits.

Locomotor Adaptations During RaceRunning in People With Neurological Motor Disorders

The aim of this study was to examine strategies to absorb impact shock during RaceRunning in participants with neurological motor disorders. For this purpose, 8 RaceRunning athletes (4 male and 4 female) voluntarily took part in the study. Each participant performed a series of 100-m sprints with a RaceRunning bike. Acceleration of the tibia and head was measured with 2 inertial measurement units and used to calculate foot-impact shock measures. Results showed that RaceRunning pattern was characterized by a lack of impact peak in foot-ground contact time and the existence of an active peak after foot contact. Due to the ergonomic properties of the RaceRunning bike, shock is attenuated throughout the stance phase. In conclusion, the results revealed that RaceRunning athletes with neurological motor disorders are capable of absorbing impact shock during assisted RaceRunning using a strategy that mimics runners without disabilities.

Using statistical parametric mapping to assess the association of duty factor and step frequency on running kinetic

Duty factor (DF) and step frequency (SF) were previously defined as the key running pattern determinants. Hence, this study aimed to investigate the association of DF and SF on 1) the vertical and fore-aft ground reaction force signals using statistical parametric mapping; 2) the force related variables (peaks, loading rates, impulses); and 3) the spring-mass characteristics of the lower limb, assessed by computing the force-length relationship and leg stiffness, for treadmill runs at several endurance running speeds. One hundred and fifteen runners ran at 9, 11, and 13 km/h. Force data (1000 Hz) and whole-body three-dimensional kinematics (200 Hz) were acquired by an instrumented treadmill and optoelectronic system, respectively. Both lower DF and SF led to larger vertical and fore-aft ground reaction force fluctuations, but to a lower extent for SF than for DF. Besides, the linearity of the force-length relationship during the leg compression decreased with increasing DF or with decreasing SF but did not change during the leg decompression. These findings showed that the lower the DF and the higher the SF, the more the runner relies on the optimization of the spring-mass model, whereas the higher the DF and the lower the SF, the more the runner promotes forward propulsion.

Inter-Individual Variability in Muscle Fiber-Type Distribution Affects Running Economy but Not Running Gait at Submaximal Running Speeds

Running economy is an important determinant of endurance running performance, yet insights into characteristics contributing to its inter-individual variability remain limited. Although slow-twitch muscle fibers are more energy-efficient than fast-twitch fibers during the (near-)isometric contractions common during submaximal running, current literature lacks a consensus on whether a relationship between muscle fiber-type distribution and running economy exists. This study aims to resolve the ongoing debate by addressing potential confounding factors often overlooked in prior research, such as the effect of different running speeds, the homogeneity of investigated groups, and the potential impact of the adopted running gait. We selected two groups with predetermined distinct muscle fiber-type distribution in their triceps surae muscle by measurement of carnosine via 1H-MRS, one predominantly slow (ST; n = 11; carnosine z-score = -1.31) and the other predominantly fast (FT; n = 10; z-score = 0.83). Across a range of running speeds (2-4 m/s), we measured running economy (W/kg) through indirect calorimetry, along with running kinematics, kinetics and muscle activity of the lower limb. The ST-group exhibited, on average, 7.8% better running economy than the FT-group (p = 0.01) and this difference was consistent across speeds. Both groups demonstrated almost identical kinematics, kinetics, and muscle activity patterns across submaximal running speeds. Overall, our findings indicate that distinct muscle fiber-type distribution explains some of the observed variability in running economy, for which a predominance of energy-efficient slow-twitch fibers appear beneficial. In contrast, muscle fiber-type distribution does not affect running gait substantially.

KeepRunning: A MoCap-Based Rapid Test to Prevent Musculoskeletal Running Injuries

The worldwide popularisation of running as a sport and recreational practice has led to a high rate of musculoskeletal injuries, usually caused by a lack of knowledge about the most suitable running technique for each runner. This running technique is determined by a runner's anthropometric body characteristics, dexterity and skill. Therefore, this study aims to develop a motion capture-based running analysis test on a treadmill called KeepRunning to obtain running patterns rapidly, which will aid coaches and clinicians in assessing changes in running technique considering changes in the study variables. Therefore, a review and proposal of the most representative events and variables of analysis in running was conducted to develop the KeepRunning test. Likewise, the minimal detectable change (MDC) in these variables was obtained using test-retest reliability to demonstrate the reproducibility and viability of the test, as well as the use of MDC as a threshold for future assessments. The test-retest consisted of 32 healthy volunteer athletes with a running training routine of at least 15 km per week repeating the test twice. In each test, clusters of markers were placed on the runners' body segments using elastic bands and the volunteers' movements were captured while running on a treadmill. In this study, reproducibility was defined by the intraclass correlation coefficient (ICC) and MDC, obtaining a mean value of ICC = 0.94 ± 0.05 for all variables and MDC = 2.73 ± 1.16° for the angular kinematic variables. The results obtained in the test-retest reveal that the reproducibility of the test was similar or better than that found in the literature. KeepRunning is a running analysis test that provides data from the involved body segments rapidly and easily interpretable. This data allows clinicians and coaches to objectively provide indications for runners to improve their running technique and avoid possible injury. The proposed test can be used in the future with inertial motion capture and other wearable technologies.

Erratum: Using statistical parametric mapping to assess the association of duty factor and step frequency on running kinetic

[This corrects the article DOI: 10.3389/fphys.2022.1044363.].