Half-marathoners are younger and slower than marathoners

A preliminary exploration of the regression equation for performance in amateur half-marathon runners: a perspective based on respiratory muscle function

This document presents a study on the relationship between physical characteristics, respiratory muscle capacity, and performance in amateur half-marathon runners. The aim of this study was to establish a preliminary predictive model to provide insights into training and health management for runners. Participants were recruited from the 2023 Beijing Olympic Forest Park Half-Marathon, comprising 233 individuals. Personal information including age, gender, height, weight, and other relevant factors were collected, and standardized testing methods were used to measure various parameters. Correlation analysis revealed significant associations between gender, height, weight, maximum expiratory pressure, maximal inspiratory pressure, and half-marathon performance. Several regression equations were developed to estimate the performance of amateur marathon runners, with a focus on gender, weight, maximum expiratory pressure, and height as predictive factors. The study found that respiratory muscle training can delay muscle fatigue and improve athletic performance. Evaluating the level of respiratory muscle capacity in marathon athletes is crucial for defining the potential speed limitations and achieving optimal performance. The information from this study can assist amateur runners in optimizing their training methods and maintaining their physical wellbeing.

Predictors of half-marathon performance in male recreational athletes

Few research has been conducted on predictors of recreational runners' performance, especially in half-marathon running. The purpose of our study was (a) to investigate the relationship of half-marathon race time with training, anthropometry and physiological characteristics, and (b) to develop a formula to predict half-marathon race time in male recreational runners. Recreational runners (n=134, age 44.2±8.7 years; half-marathon race time 104.6±16.2 min) underwent a physical fitness battery consisting of anthropometric and physiological tests. The participants were classified into five performance groups (fast, 73-92 min; above average, 93-99 min; average 100-107 min; below average, 108-117 min; slow group, 118-160 min). A prediction equation was developed in an experimental group (EXP, n=67), validated in a control group (CON, n=67) and prediction bias was estimated with 95 % confidence intervals (CI). Performance groups differed in half-marathon race time, training days, training distance, age, weight, (body mass index) BMI, body fat (BF) and maximum oxygen uptake (VO2max) (p≤0.001, η2≥0.132), where faster groups had better scores than the slower groups. Half-marathon race time correlated with physiological, anthropometric and training characteristics, with the faster the runner, the better the score in these characteristics (e.g., VO2max, r=0.59; BMI, r=-0.55; weekly running distance, r=-0.53, p<0.001). Race time in EXP might be calculated (R2=0.63, standard error of the estimate=9.9) using the equation 'Race time (min)=80.056+2.498×BMI-0.594×VO2max-0.191×weekly training distance in km'. Validating this formula in CON, no bias was shown (difference between observed and predicted value 2.3±12.8 min, 95 % CI -0.9, 5.4, p=0.153). Half-marathon race time was related to and could be predicted by BMI, VO2max and weekly running distance. Based on these relationships, a prediction formula for race time was developed providing a practical tool for recreational runners and professionals working with them.

Participation and performance characteristics in half-marathon run: a brief narrative review

Half-marathon (HM) is a running sport of increasing popularity in both sexes and in all age groups worldwide during the last years. Many studies have examined several aspects of HM, such as performance and participation trends, sex and age differences, physiological correlates, and training; however, no comprehensive review has ever been contacted to summarize the recently accumulated knowledge. Therefore, the aim of the present study was to review all previous research in this sport, focusing on participation and performance aspects. It was shown that HM runners had similar anthropometric and physiological characteristics as full-marathon runners which should be attributed to the affinity of these two races in terms of metabolic demands. Performance in HM was related with superior scores in aerobic capacity (maximal oxygen uptake, anaerobic threshold and running economy) and training characteristics (sport experience, weekly distance, training speed, frequency of sessions and long single endurance run distance), and lower scores in adiposity-related scores (e.g. body mass, body mass index, body fat percentage and skinfold thickness). Considering the popularity of HM race and the lack of many original studies (compared to FM race), this is an exciting field for scientific research with a large potential for practical applications, since the majority of HM runners are amateur runners in need of sex-, age- and performance-tailored exercise prescription.

Correlation between Cardiopulmonary Indices and Running Performance in a 14.5 km Endurance Running Event

BACKGROUND

Running is a common recreational activity, and the number of long-distance-race participants is continuously growing. It is well-established that regular physical activity can prevent and manage non-communicable diseases and benefit public health. Training for a long-distance race requires development of specific aerobic abilities and should generate the desired race performance. The purpose of this study was to support the training design and motivation of recreational endurance runners, by investigating whether a 14.5 km race performance of long-distance runners correlates with their cardiopulmonary indices measured in the laboratory.

METHODS

To examine the relationships of a 14.5 km running performance with the cardiopulmonary parameters of amateur runners, a cross-sectional study design was applied. Fifteen (eleven men and four women) recreational long-distance runners (aged 41.3 ± 9.2 years) from Northern Greece were included in the study and were evaluated in the laboratory within one week before an endurance running race-the 14.5 km Philip Road race, in Greece. The laboratory-based examinations of the athletes consisted of a comprehensive medical pre-participation screening and maximal cardiopulmonary exercise testing.

RESULTS

The results showed that the 14.5 km race performance time (73.8 ± 9.7 min) significantly correlated with the cardiopulmonary-exercise-testing speed-related indices at specific submaximal and maximal workloads (p < 0.01, p < 0.05), while the cardiopulmonary indices of oxygen uptake did not reliably predict race running time (p > 0.05).

CONCLUSIONS

There is a better correlation of the 14.5 km running performance of recreational long-distance runners with the cardiopulmonary-exercise-testing speed-related indices at specific workloads than with the indices of oxygen uptake, running economy or respiratory economy. When preparing a training strategy, amateur long-distance runners should mostly rely on specific running-speed-related laboratory data rather than on oxygen-uptake values.

Benefits on Hematological and Biochemical Parameters of a High-Intensity Interval Training Program for a Half-Marathon in Recreational Middle-Aged Women Runners

(1) Background: half-marathon races are popular among recreational runners, with increases in participation among middle-aged and women. We aimed to determine the effects of two half-marathon training programs on hematological and biochemical markers in middle-aged female recreational runners; (2) Methods: ten women (40 ± 7 years) followed moderate intensity continuous training (MICT), based on running volume below 80% V˙O₂max, and another ten women followed high intensity interval training (HIIT) at 80%–100% V˙O₂max, with less volume, and combined with eccentric loading exercise. Hematology, plasma osmolality, and plasma markers of metabolic status, muscle damage, inflammatory, and oxidative stress were measured before (S1) and after (S2) training and 24 h after the half-marathon (S3); (3) Results: both training programs had similar moderate effects at S2. However, the acute response at S3 induced different alterations. There was a greater decrease in cholesterol and triglyceride levels in MICT and reductions in markers of damage and inflammation in HIIT. Greater variability in some plasma markers at S3 in MICT suggests that there is inter-individual variability in the response to training; (4) Conclusions: HIIT led to better adaptation to the competition maybe because of the repeated exposure to higher oxygen consumption and eccentric loading exercise.

Changes in segment coordination variability and the impacts of the lower limb across running mileages in half marathons: Implications for running injuries

BACKGROUND

Segment coordination variability (CV) is a movement pattern associated with running-related injuries. It can also be adversely affected by a prolonged run. However, research on this topic is currently limited. The purpose of this study was to investigate the effects of a prolonged run on segment CV and vertical loading rates during a treadmill half marathon.

METHODS

Fifteen healthy runners ran a half marathon on an instrumental treadmill in a biomechanical laboratory. Synchronized kinematic and kinetic data were collected every 2 km (from 2 km until 20 km), and the data were processed by musculoskeletal modeling. Segment CVs were computed from the angle-angle plots of selected pelvis-thigh, thigh-shank, and shank-rearfoot couplings using a modified vector coding technique. The loading rate of vertical ground reaction force was also calculated. A one-way MANOVA with repeated measures was performed on each of the outcome variables to examine the main effect of running mileage.

RESULTS

Significant effects of running mileage were found on segment CVs (p ≤ 0.010) but not on loading rate (p = 0.881). Notably, during the early stance phase, the CV of pelvis frontal vs. thigh frontal was significantly increased at 20 km compared with the CV at 8 km (g = 0.59, p = 0.022). The CV of shank transverse vs. rearfoot frontal decreased from 2 km to 8 km (g = 0.30, p = 0.020) but then significantly increased at both 18 km (g = 0.05, p < 0.001) and 20 km (g = 0.36, p < 0.001).

CONCLUSION

At the early stance, runners maintained stable CVs on the sagittal plane, which could explain the unchanged loading rate throughout the half marathon. However, increased CVs on the frontal/transverse plane may be an early sign of fatigue and indicative of possible injury risk. Further studies are necessary for conclusive statements in this regard.

Development and Validation of Prediction Equation of "Athens Authentic Marathon" Men's Race Speed

Aim

Despite the increasing popularity of outdoor endurance running races of different distances, little information exists about the role of training and physiological characteristics of recreational runners. The aim of the present study was (a) to examine the role of training and physiological characteristics on the performance of recreational marathon runners and (b) to develop a prediction equation of men’s race time in the “Athens Authentic Marathon.”

Methods

Recreational male marathon runners (n = 130, age 44.1 ± 8.6 years)—who finished the “Athens Authentic Marathon” 2017—performed a series of anthropometry and physical fitness tests including body mass index (BMI), body fat percentage (BF), maximal oxygen uptake (VO₂max), anaerobic power, squat, and countermovement jump. The variation of these characteristics was examined by quintiles (i.e., five groups consisting of 26 participants in each) of the race speed. An experimental group (EXP, n = 65) was used to develop a prediction equation of the race time, which was verified in a control group (CON, n = 65).

Results

In the overall sample, a one-way ANOVA showed a main effect of quintiles on race speed on weekly training days and distance, age, body weight, BMI, BF, and VO₂max (p ≤ 0.003, η² ≥ 0.121), where the faster groups outscored the slower groups. Running speed during the race correlated moderately with age (r = −0.36, p < 0.001) and largely with the number of weekly training days (r = 0.52, p < 0.001) and weekly running distance (r = 0.58, p < 0.001), but not with the number of previously finished marathons (r = 0.08, p = 0.369). With regard to physiological characteristics, running speed correlated largely with body mass (r = −0.52, p < 0.001), BMI (r = −0.60, p < 0.001), BF (r = −0.65, p < 0.001), VO₂max (r = 0.67, p < 0.001), moderately with isometric muscle strength (r = 0.42, p < 0.001), and small with anaerobic muscle power (r = 0.20, p = 0.021). In EXP, race speed could be predicted (R² = 0.61, standard error of the estimate = 1.19) using the formula “8.804 + 0.111 × VO₂max + 0.029 × weekly training distance in km −0.218 × BMI.” Applying this equation in CON, no bias was observed (difference between observed and predicted value 0.12 ± 1.09 km/h, 95% confidence intervals −0.15, 0.40, p = 0.122).

Conclusion

These findings highlighted the role of aerobic capacity, training, and body mass status for the performance of recreational male runners in a marathon race. The findings would be of great practical importance for coaches and trainers to predict the average marathon race time in a specific group of runners.

No Trends in the Age of Peak Performance among the Best Half-Marathoners and Marathoners in the World between 1997-2020

Background and Objectives: We examined the possible trend in the age of peak performance in elite endurance athletes according to sex, continent of athletes’ national citizenship, and ranking position. Since performance is a multifactorial trait, this information can be used to guide the long-term training and to plan the strategies related to the selection process of athletes. Materials and methods: Information of 1852 professional athletes, classified as top 20 performance of each year in marathon and half-marathon events between 1997 and 2020 were considered. Analysis of variance was computed to test differences in age between sex, continent, and rank position. Results: A significant difference between groups in the mean age of peak performance was observed (F (3, 1884) = 42,31; p < 0.001). For both sexes, half-marathoners were younger than marathoners (male, 25.6 ± 3.6 years vs. 28.0 ± 3.9 years; female, 27.5 ± 4.4 years vs. 28.4 ± 4.1). Female half-marathoners in 2004 presented the highest mean age (31.1 ± 4.8 years) compared to their peers in the years 1997, 2001, 2018 and 2019; among male half-marathoners, those in 1999 presented the highest mean age when compared to 2011, 2018, and 2019. Differences between the continents of athletes’ national citizenship were observed (F (4, 1884) = 62,85,601; p < 0,001). Asian runners presented the lowest mean age (26.5 ± 3.7 years), while their European peers presented the highest (31.1 ± 3.9 years). No significant interaction between sex and ranking position was verified. Differences were observed between sexes for categories “4th–10th positions” and “11th–20th” (F (1, 1879) = 23,114; p < 0.001). Conclusions: Over the last two decades, no clear trend was observed in the changes in the age of peak performance among endurance athletes of both sexes, but, in general, female half-marathoners tended to be significantly older than their male peers.

Inter-Individual Different Responses to Continuous and Interval Training in Recreational Middle-Aged Women Runners

A crucial subject in sports is identifying the inter-individual variation in response to training, which would allow creating individualized pre-training schedules, improving runner’s performance. We aimed to analyze heterogeneity in individual responses to two half-marathon training programs differing in running volume and intensity in middle-aged recreational women. 20 women (40 ± 7 years, 61 ± 7 kg, 167 ± 6 cm, and VO₂max = 48 ± 6 mL⋅kg^–1⋅min^–1) underwent either moderate-intensity continuous (MICT) or high-intensity interval (HIIT) 12-week training. They were evaluated before and after training with maximal incremental tests in the laboratory (VO₂max) and in the field (time to exhaustion, TTE; short interval series and long run). All the women participated in the same half-marathon and their finishing times were compared with their previous times. Although the improvements in the mean finishing times were not significant, MICT elicited a greater reduction (3 min 50 s, P = 0.298), with more women (70%) improving on their previous times, than HIIT (reduction of 2 min 34 s, P = 0.197, 50% responders). Laboratory tests showed more differences in the HIIT group (P = 0.008), while both groups presented homogeneous significant (P < 0.05) increases in TTE. Both in the short interval series and in the long run, HIIT induced better individual improvements, with a greater percentage of responders compared to MICT (100% vs 50% in the short series and 78% vs 38% in the long run). In conclusion, variability in inter-individual responses was observed after both MICT and HIIT, with some participants showing improvements (responders) while others did not (non-responders) in different performance parameters, reinforcing the idea that individualized training prescription is needed to optimize performance.

Post-Exercise Hypotension and Reduced Cardiac Baroreflex after Half-Marathon Run: In Men, but Not in Women

We examined whether trained women exhibit similar cardiovascular and cardiac baroreflex alterations after a half-marathon compared to men. Thirteen women (39.1 ± 9.3 years; 165 ± 6 cm; 58.2 ± 7.5 kg; maximal aerobic speed (MAS): 13.7 ± 2.2 km·h^-1) and 12 men (45.7 ± 10.5 years; 178 ± 7 cm; 75.0 ± 8.3 kg; MAS: 15.8 ± 2.2 km·h^-1) ran an official half-marathon. Before and 60-min after, cardiovascular variables, parasympathetic (heart rate variability analysis) modulation and cardiac baroreflex function (transfer function and sequence analyses) were assessed during supine rest and a squat-stand test. Running performance was slower in women than in men (120 ± 19 vs. 104 ± 14 min for women and men, respectively). However, when expressed as a percentage of MAS, it was similar (78.1 ± 4.6% and 78.2 ± 5.4% of MAS for women and men, respectively). Before the run, women exhibited lower mean blood pressure (BP), cardiac output (CO) and stroke volume (SV) compared to men, together with higher parasympathetic indexes. After the race, parasympathetic indexes decreased in both sexes, but remained higher in women. Reduced SV, systolic BP and cardiac baroreflex were observed in men but not in women. Contrary to men, a competitive half-marathon did not trigger post-exercise hypotension and a reduced cardiac baroreflex in women.

Training for a (half-)marathon: Training volume and longest endurance run related to performance and running injuries

OBJECTIVE

Examine the associations of training volume and longest endurance run with (half-)marathon performance and running-related injuries (RRIs) in recreational runners.

MATERIALS AND METHODS

During the preparation for and directly after the running event, 556 participants of a half marathon and 441 participants of a marathon completed three questionnaires on RRIs, average weekly training volume and the longest endurance run. With finish time, decline in pace during the running event and RRIs as dependent variables, linear and logistic regression analyses were performed to test the associations with weekly training volume and the longest endurance run.

RESULTS

In half-marathon runners, a high training volume (>32 km/wk) (β -4.19, 95% CI: -6.52;-1.85) and a long endurance run (>21 km) (β -3.87, 95% CI: -6.31;--1.44) were associated with a faster finish time, while a high training volume (β -1.81, 95% CI: -3.49;-0.12) and a long endurance run (β -1.89, 95% CI: -3.65;-0.12) were also related to less decline in pace. In marathon runners, a low training volume (<40 km/wk) was related to a slower finish time (β 6.33, 95% CI: 0.18;12.48) and a high training volume (>65 km/wk) to a faster finish time (β -14.09, 95% CI: -22.47;-5.72), while a longest endurance run of <25 km was associated with a slower finish time (β 13.44, 95% CI: 5.34;21.55). No associations between training characteristics and RRIs were identified.

CONCLUSIONS

Preparation for a (half-)marathon with a relatively high training volume and long endurance runs associates with a faster finish time, but does not seem related to an increased injury risk.

High-intensity interval versus moderate-intensity continuous half-marathon training programme for middle-aged women

PURPOSE

To test the effectiveness on recreational female middle-aged runners of a programme of high-intensity interval training (HIIT) for a half-marathon race contrasted to a conventional moderate-intensity continuous training (MICT).

METHODS

Twenty recreational female runners (40 ± 7 years) followed MICT or HIIT schedules for training a half-marathon. The MICT group trained a mean of 32 km/week at intensities below 80% VO₂max. The HIIT group ran 25 km/week at intensities between 80 and 100% VO₂max, combined with uphill running and resistance training. Women following HIIT ran 21% less distance and invested 17% less time than those from MICT group. All the women were evaluated at the beginning and end of the training and participated in the same half-marathon run.

RESULTS

Women following both schedules reduced their previous finishing times by 2-3%, which for HIIT group would have meant rising up to 90 positions out of 1454 participants in the local half-marathon race. The high intensity performed during series of high power output (200 m and 400 m) and resistance sessions in HIIT programme promoted changes that allowed modifying efficiency at high workloads. At the same time, the HIIT training programme elicited changes in oxygen uptake and transport as indicated the cardiorespiratory parameters obtained during recovery in lab tests. Moreover, HIIT registered a 14% baseline decrease in heart rate contrasting to the not significant 6% decrease in MICT.

CONCLUSIONS

Runners following HIIT training obtained similar registers as with a traditional MICT schedule, expending less time and running shorter distances, yet improving their anaerobic and aerobic power.

Participation and Performance Trends in the Oldest 100-km Ultramarathon in the World

Participation and performance trends in ultramarathon running have been investigated for large datasets and long period of times with an increase in participants and an improvement in performance. However, the analysis of ultramarathons across many decades is missing. We analyzed these trends for 96,036 athletes (88,286 men and 7750 women) from 67 countries competing between 1956 and 2019 in ‘100 km Lauf Biel’ in Switzerland, the oldest 100-km ultramarathon in the world. More men than women participated in all years. The number of male participants reached a peak at around 1985 and a decline in participation occurred thereafter. Women started competing in 1962. Men were always faster than women and both women and men reduced their race times over years. After about 1985, both overall women and men and both female and male winners were not able to improve race times. For men, athletes from all age groups below the age of 49 years old reached a peak of participation in the 1980s, and showed a decrease since then. Regarding age groups, the decrease first started in age group 20–29 years, followed by 30–39, 40–49, 50–59, and 60–69 years. For athletes in age groups 70–79 and 80–89 years, no decrease occurred. For women, age group athletes in age groups 40–49, 50–59, and 60–69 years increased their participation, whereas age groups 20–29 and 30–39 peaked in the late 1980s and started to decrease or stabilize, respectively. Switzerland, Germany, and France were the countries with the highest numbers of participants throughout the history of the race. In men, race times increased after about 1990 for most nationalities; only runners from Germany seemed to stabilize their performance. In women, runners from Italy, France, and Austria improved their performance over the years. In summary, the analysis of the oldest 100-km ultramarathon in the world showed a decrease in participation and an impairment in performance in the last 60 years. These changes were due to a decrease in the number of male ultramarathoners in around the 1980s, where mainly the number of age group runners younger than 70 years decreased.

Number of finishers and performance of age group women and men in long-distance running: comparison among 10km, half-marathon and marathon races in Oslo

The aim of the present study was to examine the number of finishers and performance trends in 10 km, half-marathon and marathon races in Oslo. Data (total 115,725 finishers; women, n = 50,595; men, n = 65,130) from 10 km, half-marathon and marathon races in Oslo from 2008 to 2018 were analysed considering number, sex, age and running speed of finishers. The total men-to-women ratio was the smallest in the 10 km race (0.60) and the largest in the marathon (3.86) (p < 0.01, φ = 0.28). In both women and men, the slowest running speed was shown in the older age groups (p < 0.01). Based on the findings of the present study, it was concluded that relatively more women finished a 10 km and less a half-marathon and a marathon. Our results indicated that the sex difference in performance was attenuated in the longer race distances and older age groups.

Critical velocity estimates running velocity in a 10-km running race in recreational runners

Abstract The aim of this study was to compare the estimated running velocity in a critical velocity (CV) test with the real running velocity in a 10-km race. This is a cross-sectional study with a convenience sample of 34 runners, 20 males and 14 females (42,4 ± 11,0). The participants attended two days of testing and one day to participate in an official 10-km race. During the visits, the following tests were performed: i) 400-meter running track test and ii) 2000 meter running track test. They were randomly selected and held in official athletics track with at least 48 hours rest between them. The athletes were instructed to participate in the study properly recovered, fed and hydrated. The CV was calculated as the linear relation between distance and race time, corresponding to the slope of the linear regression line. Both tests occurred in similar climatic situations. We found good agreement between the velocities estimated through the CV test and the real running velocity of a 10-km race. Although there was a difference in velocities estimated by the CV test and the real 10-km race, the variation delta was low. Thus, these data indicate that the CV test seems to be a good tool for estimating the velocity of a 10-km race. The CV determined in the field with two fixed distances 400 and 2000 meter was valid to estimate the running velocity of a 10-km race.

What Motivates Successful Marathon Runners? The Role of Sex, Age, Education, and Training Experience in Polish Runners

The aim of this study was to compare the motivations of successful marathon finishers (n = 1,243) and inexperienced runners (control group, n = 296). A total of 1,537 runners with 380 women (24.7%) and 1,157 men (75.3%) completed the motivations of marathoners scales (MOMS) questionnaire and the relationships between general motivation categories and selected demographic (e.g., gender, age, and education) and training characteristics were analyzed. Successful marathon finishers did not differ significantly in motivations from the control group (p > 0.05). Trivial to small correlations with age, educational level, and training characteristics were observed. Female marathon finishers exceeded men on the motivational scales for weight concern, affiliation, psychological coping, life meaning, and self-esteem and they scored lower on competitive motivation (p < 0.05). There was also a significant relationship of some motivational aspects with level of education, experience and training frequency. These findings confirmed that age and gender differentiate motivations in both successful female and male marathon finishers and controls.

Performance and Pacing of Age Groups in Half-Marathon and Marathon

The aim of the present study was to examine the age-related differences in performance and pacing in a half-marathon compared to a marathon. All finishers (n = 9137) in the Ljubljana 2017 half-marathon (n = 7258) and marathon (n = 1853) with available data on split times during the races, were analysed for pacing. Half-marathoners were slower than marathoners among women, (2.77 ± 0.35 versus 2.86 ± 0.39 m·s⁻¹ respectively, p < 0.001), but faster among men (3.14 ± 0.45 versus 3.08 ± 0.46 m·s⁻¹ respectively, p < 0.001). In both race distances, the <25 age group was the fastest and the >54 age group the slowest (p < 0.001). All age groups presented a positive pacing in both race distances and genders, with each segment being slower than the previous one. However, an end spurt was observed in the marathon, but not in the half-marathon. A more even pace in the half-marathon than in the marathon was shown for most age groups. In summary, age-group finishers in the half-marathon decreased running speed across the race, presented a more even pacing than marathoners, and did not show an end spurt.

Influence of speed and heel-to-toe drop in running shoes for female recreational runners: A cross-sectional study

In recent years, the popularity of running has boomed and the number of women runners has risen sharply. However, little research has been conducted into the running cycle as concerns female runners. The aim of this study is to analyse, in women runners, the relationships between spatiotemporal parameters in the running cycle, the heel drop in running shoes and a progressive increase in training speed, when running on a treadmill.Thirty-eight female runners were recruited from the Malaga University Athletics Club and Nerja Athletics Club. All were at least 18 years old, recreationally active (3-4 running sessions per week) and able to run 5 km in less than 25 min. Their running performance on a treadmill was recorded and spatiotemporal parameters assessed using the OptoGait system.As the running speed increased (8-12-15 km/h) the spatiotemporal parameters of the running cycle altered: the flight time increased (P < .001) and the contact time decreased (P = .05). Heel drop (4-12 mm) was not significantly associated with any of the parameters (phase 1: P = .198; phase 2: P = .191; phase 3: P = .242).A progressive increase in training speed on a treadmill directly influences the spatiotemporal parameters of the running cycle in women runners.

Pacing of Women and Men in Half-Marathon and Marathon Races

Background and objective: Half-marathon is the most popular endurance running race in terms of number of races and runners competing annually; however, no study has compared pacing strategies for this race distance with marathon. The aim of the present study was to profile pacing in half-marathon, compare half-marathon and marathon for pacing, and estimate sex differences in pacing. Materials and methods: A total of 9137 finishers in the half-marathon (n = 7258) and marathon race (n = 1853) in Ljubljana 2017 were considered for their pacing in five race segments (0–23.7%, 23.7–47.4%, 47.4–71.1%, 71.1–94.8%, and 94.8–100% of the race. Results: Half-marathon runners followed a positive pacing with every segment being slower than its previous one without the presence of an endspurt. Compared to marathon (where the average percent of change in speed (ACS) was 5.71%), a more even pacing was observed in half-marathon (ACS = 4.10%). Moreover, women (ACS = 4.11%) had similar pacing as men (ACS = 4.09%) in half-marathons. Conclusions: In summary, running a half-marathon followed a unique pattern that differentiated this race distance from marathon, with the former showing a more even pacing with an absence of endspurt, and sex difference compared to the latter. Consequently, runners should be advised to adopt a less variable pacing when competing in a half-marathon, regardless of their sex. To the best of our knowledge, the more even pacing in half-marathon, than in marathon, was a novel finding, as it was the first study to compare the two race distances for this characteristic.

World Records in Half-Marathon Running by Sex and Age

The relationship between age and elite marathon race times is well investigated, but little is known for half-marathon running. This study investigated the relationship between half-marathon race times and age in 1-year intervals by using the world single age records in half-marathon running and the sex difference in performance from 5 to 91 years in men and 5 to 93 years in women. We found a fourth-order polynomial relationship between age and race time for both women and men. Women achieve their best half-marathon race time earlier in life than men, 23.89 years compared with 28.13 years, but when using a nonlinear regression analysis, the age of the fastest race time does not differ between men and women, with 26.62 years in women and 26.80 years in men. Moreover, the sex difference in half-marathon running performance increased with advancing age.

How much further for the sub-2-hour marathon?

The sub-2-hour marathon is a new barrier in endurance running performance, and it has been widely debated in the scientific community. In this review we present a mathematical model to estimate the possible year when a male could break through the sub-2-hour barrier, and also an estimation of when a female could break Paula Radcliffe’s marathon running record. Further, we present several aspects (ie, physiology, nationality, age, biomechanics, pacing, and drafting) that are associated with marathon running performance in elite runners and, finally, the possible characteristics of the male to break the sub-2-hour barrier. In summary, with the results of the developed equations, it is possible that a male athlete can break through the sub-2-hour barrier in the next decade (with Nike^® Breaking2 performance 1920–2018 [NBP]: y =0.0417x²–14.18x +3,128; year of 2026; without NBP 1920–2018: y =0.045x²–15.12x +3,194; year of 2027). This marathoner will possibly have a maximal oxygen uptake >85 mL∙kg⁻¹∙min⁻¹ and should perform the race at a pacing higher than 85% of maximal oxygen uptake. In addition, this runner should pay more attention to strength training, endurance strength, speed training, and focus on running training at an intensity above the anaerobic threshold. Most likely, this runner originates from East Africa (especially from Ethiopia) and will have an age of ~27 years. For the females, there is poor evidence regarding the physiological profile of the female marathoner who will break Radcliffe’s record, but the available literature suggests that it will not happen any time soon.

Sex and Age Differences in Trail Half Marathon Running

Female participation is growing in trail running races. The purpose was to evaluate sex and age differences in top finishers of a trail running half marathon. Velocity differences between males (M) and females (F) were determined for the top 10 finishers of the Moab Trail Half Marathon from 2012 - 2015 across age, and by finishing place. Differences between age category and between sexes were determined through ANOVA with significance accepted at P < 0.05. A significant difference for running velocity was present between sexes at each age category (20-29 yr F = 2.9±0.3, M = 3.4±0.4 m·sec^-1; 30-39 yr F = 2.8±0.3, M = 3.3±0.3; 40-49 yr F = 2.7±0.3, M = 3.0±0.5; 50-59 yr F = 2.3±0.2, M = 2.8±0.3; 60-69 yr F = 1.6±0.3, M = 2.2±0.4; P < 0.0001). Sex difference in trail running velocity was consistent (~13%) among all age categories with exception of the oldest group (33%, P = 0.0001). There were significantly greater female finishers in every age category (20 - 29 yr F = 107±18, M = 56±1;, 30 - 39 yr F = 150±34, M = 84±21; 40 - 49 yr F = 112±17, M = 64±16; P < 0.01) until 50 - 59 yr (F = 48±13, M = 41±14; P = 0.50). These data indicate that the widening gap in sex differences observed in road races are ameliorated in a trail running environment that has a larger number of female participants.

Running Performance, Nationality, Sex, and Age in the 10-km, Half-Marathon, Marathon, and the 100-km Ultramarathon IAAF 1999-2015

Nikolaidis PT, Onywera VO, and Knechtle B. Running performance, nationality, sex, and age in the 10-km, half-marathon, marathon, and the 100-km ultramarathon IAAF 1999-2015. J Strength Cond Res 31(8): 2189-2207, 2017-The aim of this study was to examine the performance of the world's best runners in the 10-km, half-marathon, marathon, and 100-km races by age, sex, and nationality during 1999-2015, using data from the International Association of Athletics Federations (IAAF). A total of 38,895 runners (17,136 women and 21,759 men) were evaluated, with 2,594 (1,360 women and 1,234 men) in the 10-km; 11,595 (5,225 women and 6,370 men) in the half-marathon; 23,973 (10,208 women and 13,765 men) in the marathon; and 733 (343 women and 390 men) in 100-km events. Most runners in the 10-km event (women 40%, men 67%) and the half-marathon (women 30%, men 57%) were Kenyans. In the marathon, most female and male runners were Ethiopians (women 17%, men 14%) and Kenyans (women 15%, men 43%), respectively. In the 100-km event, most runners were Japanese (20% women, and 80% men). Women were older than the men in the 10-km (32.0 ± 6.0 vs. 25.3 ± 4.3 years, p < 0.001), half-marathon (27.5 ± 4.7 vs. 25.9 ± 4.1 years, p < 0.001), and marathon events (29.5 ± 5.5 vs. 29.1 ± 4.3 years, p < 0.001), but not in 100-km event (36.6 ± 6.1 vs. 35.9 ± 5.5 years, p = 0.097). Men were faster than the women in the 10-km (28:04 ± 0:17 vs. 32:08 ± 0.31 (minutes:seconds), p < 0.001), half-marathon (1:01:58 ± 0:00:52 vs. 1:11:21 ± 0:01:18 (hours:minutes:seconds), p < 0.001), marathon (2:13:42 ± 0:03:01 vs. 2:35:04 ± 0:05:21 (hours:minutes:seconds), p < 0.001), and 100-km events (6:48:01 ± 0:11:29 vs. 7:53:51 ± 0:16:37 (hours:minutes:seconds), p < 0.001). East Africans were not the fastest compared with athletes originating from other countries where only the Ethiopian men were faster than all other men in the marathon. In summary, (a) in the 10-km, half-marathon and marathon events, most runners were from Kenya and Ethiopia, and from Japan and Russia in the 100-km event; (b) women were older than the men in all distance events except the 100-km event;

Sex- and age-related differences in half-marathon performance and competitiveness in the world's largest half-marathon - the GöteborgsVarvet

In road runners, the age-related performance decline has been well investigated for marathoners, but little is known for half-marathoners. We analysed data from 138,616 runners (48,148 women and 90,469 men) competing between 2014 and 2016 in GöteborgsVarvet, the world's largest half-marathon. The men-to-women ratio in participants increased with age, the fastest race times were observed in age groups ˂35 and 35-39 years in women and in age group 35-39 years in men, the main effect of sex and the sex × age group interaction on race time were trivial, and the competitiveness was denser in men and in the younger age groups. In summary, in half-marathon running in the largest half-marathon in the world, the GöteborgsVarvet, women achieved the fastest race time at an earlier age compared to men where the fastest race times were observed in women in age groups ˂35 and 35-39 years and in men in age group 35-39 years.

Performance trends in age-group runners from 100 m to marathon-The World Championships from 1975 to 2015

This study examined changes in performance in age-group track runners across years from 1975 to 2015 for 100, 200, 400, 800, 1500, 5000, 10 000 m, and marathon and the corresponding sex differences. Athletes were ranked in 5-year age-group intervals from 35-39 to 95-99 years. For all races and all years, the eight female and male finalists for each age-group were included. Men were faster than women and this observation was more pronounced in the shorter distances. The younger age-groups were faster than the older age-groups and age exerted the largest effect on speed in 800 m and the smallest in marathon. There was a small variation of speed by calendar years. The competition density varied by sex and race distance. Half of participants were from USA, Germany, Australia, and Great Britain, but the participants' nationality varied by sex and race distance. In summary, the variation of competitiveness by sex in short race distances might be important for athletes and coaches. Considering the event's competitiveness and that athletes are participating in both 100 and 200 m or in 200 and 400 m, master women should be oriented to 200 m and master men should be oriented to 100 and 400 m.