Do older athletes reach limits in their performance during marathon running?

The Physiology and Biomechanics of the Master Runner

The Master runner (age 35 y and above) represents a unique athletic patient. Lifelong participation in endurance running slows the inevitable age-related decline in aerobic function and muscular strength. Still, the Master runner does not escape the inevitable effects of aging. Master runners experience a steady decline in running performance, that is, typical and maximal running speeds, after the age of 50 years of age. Age-related declines in running performance are driven by a host of factors, including declining cardiovascular function, reduced muscular capacity, altered biomechanics, and greater susceptibility to running-related injury. This review discusses age-related changes in physiology, biomechanics, and running injury susceptibility and practical strategies to maximize running participation in the Master runner.

Pacing During and Physiological Response After a 12-Hour Ultra-Marathon in a 95-Year-Old Male Runner

In recent years, outstanding performances of elderly people up to 100 years have been reported. In this case study, pacing during and recovery after a 12-h ultra-marathon were described for a 95-year old runner. The athlete achieved a total distance of 52.987 km. Pacing followed a parabolic pattern (U-shaped), where the speed decreased till the middle of the race and then increased. However, no end spurt was observed. A large main effect of lap quartile on speed was observed, where the second quartile was slower than the first quartile and forth. The smallest variability was shown in the first quartile and the largest in the second quartile. During recovery, erythrocytes, hemoglobin and hematocrit increased whereas thrombocytes and leucocytes decreased. CRP, GOT, GPT, y-GT, CK, and LDH were increased post-race and decreased to reference range during recovery. Also, creatinine and urea decreased during recovery. Creatinine clearance increased during recovery. Sodium increased during recovery and remained constantly within the reference range. During recovery body fat and visceral fat mass decreased, whereas body water and lean body mass increased. In summary, a 95-year-old man was able to run during 12 h using a U-shaped pacing and achieving a total distance of nearly 53 km. Increased selected hematological and biochemical parameters returned to pre-race values within a recovery phase of 5 days.

Effects of Pacing Properties on Performance in Long-Distance Running

This article focuses on the performance of runners in official races. Based on extensive public data from participants of races organized by the Boston Athletic Association, we demonstrate how different pacing profiles can affect the performance in a race. An athlete's pacing profile refers to the running speed at various stages of the race. We aim to provide practical, data-driven advice for professional as well as recreational runners. Our data collection covers 3 years of data made public by the race organizers, and primarily concerns the times at various intermediate points, giving an indication of the speed profile of the individual runner. We consider the 10 km, half marathon, and full marathon, leading to a data set of 120,472 race results. Although these data were not primarily recorded for scientific analysis, we demonstrate that valuable information can be gleaned from these substantial data about the right way to approach a running challenge. In this article, we focus on the role of race distance, gender, age, and the pacing profile. Since age is a crucial but complex determinant of performance, we first model the age effect in a gender- and distance-specific manner. We consider polynomials of high degree and use cross-validation to select models that are both accurate and of sufficient generalizability. After that, we perform clustering of the race profiles to identify the dominant pacing profiles that runners select. Finally, after having compensated for age influences, we apply a descriptive pattern mining approach to select reliable and informative aspects of pacing that most determine an optimal performance. The mining paradigm produces relatively simple and readable patterns, such that both professionals and amateurs can use the results to their benefit.

Lower bone mineral density in older female endurance skiers - a cross-sectional, observational study

Background

Physical activity (PA) is generally beneficial for bone health, but the effect of high levels of PA over many years, in older women, is unknown.

Methods

T-score from Dual-energy X-ray absorptiometry (DXA), and self-reported baseline characteristics were recorded for 24 female, cross-country-skiing-competitors, aged 68-76 years, from the Birkebeiner Ageing Study. Data from 647 women in the same age range from the Tromso-6 population study, with recorded DXA findings, were used for comparison.

Results

The athletes reported a median(range) of 9(1-34) participations in the 54 km, yearly ski-race, indicating long-term PA. They also reported more moderate and high levels of PA than women in the general population (52% vs. 12 and 30% vs. 0%, respectively). The athletes had lower body mass index (BMI) than the controls (mean BMI 21.7 vs 26.9 kg/m², p < 0.001). As many as 22/24(92%) of the athletes and 477/647(74%) of the controls had a low bone mineral density (BMD) (T-score < - 1), p 0.048, Pearson chi square test. Odds ratio (OR) of low BMD was 3.9 in athletes vs. controls (p 0.048, logistic regression), but adjusting for BMI largely diminished the effect estimate, which was no longer statistically significant (aOR 1.81, p 0.432). The proportion of self-reported fractures was the same in the two groups.

Conclusions

This pilot study suggests that long-term, high levels of PA are associated with low bone mineral density in older women, and the finding might be due to differences in BMI. Despite the lower bone mineral density the athletes did not report more fractures.

Force-Velocity Characteristics, Muscle Strength, and Flexibility in Female Recreational Marathon Runners

Physical fitness components that relate with performance in marathon running, e.g., aerobic capacity and body composition, have been studied extensively. On the other hand, data on components of the health-related physical fitness, such as flexibility and muscle strength, were missing in this sport. Therefore, the aim of the present study was to profile force-velocity (F-v) characteristics, muscle strength and flexibility in female recreational marathon runners and to examine their relationship with age, race time and anthropometric characteristics (body fat percentage, fat-free mass - FFM, and total thigh muscle cross-sectional area - CSA). Thirty three female marathon runners (age 40.0 ± 8.9 years, body fat percentage 19.5 ± 4.6% and personal record 4:34 ± 0:39 h:min), separated into three age groups (<35, 35-45 and >45 years) and three performance groups (race time <4:15 h:min, 4:15-4:45 h:min and >4:45 h:min), performed sit-and-reach test (SAR), isometric muscle strength tests, squat jump, countermovement jump and F-v test on a cycle ergometer. The main findings of the present study were that (i) participants had moderate scores of body composition and physical fitness considering norms of the general population, (ii) the <35 age group had better jumping ability than 35-45 and >45 age group, and the older age group had lower F₀, Pmax and rPmax than their younger counterparts, (iii) the slowest performance group scored the highest in SAR, and (iv) isometric strength, F₀ and Pmax correlated largely with body mass and FFM. Considering the lack of existing data on anaerobic power and neuromuscular fitness of female marathon runners, the findings reported in this study would be useful for strength and conditioning trainers to monitor the training of their athletes. Even if these parameters were not related to race time, they should be monitored regularly as they were either component of health-related physical fitness (muscle strength and flexibility) or could help runners (anaerobic power) under specific circumstances such as ascends during a race.

The Limits of Cardiac Performance: Can Too Much Exercise Damage the Heart?

Routine moderate-intensity physical activity confers numerous cardiovascular benefits and reduces all-cause mortality. However, the health impact of exercise doses that exceed contemporary physical activity guidelines remains incompletely understood, and an emerging body of literature suggests that high levels of exercise may have the capacity to damage the cardiovascular system. This review focuses on the contemporary controversies regarding high-dose exercise and cardiovascular morbidity and mortality. We discuss the limitations of available studies, explore potential mechanisms that may mediate exercise-related cardiac injury, and highlight the gaps in knowledge for future research.

Lower Extremity Injuries in Novice Runners: Incidence, Types, Time Patterns, Sociodemographic and Motivational Risk Factors in a Prospective Cohort Study

SUMMARY – The aim was to determine types and incidence of running-related lower extremity injuries and identify sociodemographic and motivational risk factors in novice runners attending an eight-month running school. Between January 2011 and October 2014, 349 novice runners were included. Sociodemographic, anthropometric, and data on running motivation and self-perceived health and fitness were collected. Subjects were screened for lower extremity injuries at regular three-month intervals. The cohort mean age was 35.46±7.31 years, and 271 (79.5%) were female. There were 173 (49.9%) injuries recorded, less frequently among women (42.9% vs. 62.7%, p=0.016; OR 0.878, 95% CI 0.788-0.977). The mean body mass index was 23.89±3.88 kg/m² at baseline and 22.99±3.35 kg/m² post-school (p<0.001). Median self-perceived fitness level on a ten-point visual analog scale was 4 (interquartile range (IQR) 3-5) at baseline and 8 (IQR 7-8) post-school (p<0.001). Median self-perceived overall health was 6 (IQR 5-8) at baseline and 8 (IQR 7-9) post-school (p<0.001). The knee had a significantly higher rate of injuries compared to other anatomic regions (p<0.001). Subjects listed improvement of fitness as the most common motivation for entering the school (n=159; 45.7%). In conclusion, novice runners should include strengthening exercises for knee injury prevention into their training routine.

Marathon Pace Control in Masters Athletes

PURPOSE

Pacing strategies are key to overall performance outcome in distance-running events. Presently, no literature has examined pacing strategies used by masters athletes of all running levels during a competitive marathon. Therefore, this study aimed to examine masters athletes' pacing strategies, categorized by gender, age, and performance level.

METHODS

Data were retrieved from the 2015 TSC New York City Marathon for 31,762 masters athletes (20,019 men and 11,743 women). Seven performance-classification (PC) groupings were identified via comparison of overall completion time compared with current world records, appropriate to age and gender. Data were categorized via, age, gender, and performance level. Mean 5-km speed for the initial 40 km was calculated, and the fastest and slowest 5-km-split speeds were identified and expressed as a percentage faster or slower than mean speed. Pace range, calculated as the absolute sum of the fastest and slowest split percentages, was then analyzed.

RESULTS

Significant main effects were identified for age, gender, and performance level (P < .001), with performance level the most determining factor. Athletes in PC1 displayed the lowest pace range (14.19% ± 6.66%), and as the performance levels of athletes decreased, pace range increased linearly (PC2-PC7, 17.52% ± 9.14% to 36.42% ± 18.32%). A significant interaction effect was found for gender × performance (P < .001), with women showing a smaller pace range (-3.81%).

CONCLUSIONS

High-performing masters athletes use more-controlled pacing strategies than their lower-ranked counterparts during a competitive marathon, independent of age and gender.

Untargeted Metabolomics Profiling of an 80.5 km Simulated Treadmill Ultramarathon

Metabolomic profiling of nine trained ultramarathon runners completing an 80.5 km self-paced treadmill-based time trial was carried out. Plasma samples were obtained from venous whole blood, collected at rest and on completion of the distance (post-80.5 km). The samples were analyzed by using high-resolution mass spectrometry in combination with both hydrophilic interaction (HILIC) and reversed phase (RP) chromatography. The extracted putatively identified features were modeled using Simca P 14.1 software (Umetrics, Umea, Sweden). A large number of amino acids decreased post-80.5 km and fatty acid metabolism was affected with an increase in the formation of medium-chain unsaturated and partially oxidized fatty acids and conjugates of fatty acids with carnitines. A possible explanation for the complex pattern of medium-chain and oxidized fatty acids formed is that the prolonged exercise provoked the proliferation of peroxisomes. The peroxisomes may provide a readily utilizable form of energy through formation of acetyl carnitine and other acyl carnitines for export to mitochondria in the muscles; and secondly may serve to regulate the levels of oxidized metabolites of long-chain fatty acids. This is the first study to provide evidence of the metabolic profile in response to prolonged ultramarathon running using an untargeted approach. The findings provide an insight to the effects of ultramarathon running on the metabolic specificities and alterations that may demonstrate cardio-protective effects.

Pacing in a 94-year-old runner during a 6-hour run

It is well known that elderly people up to 90 years of age are able to finish a marathon. We have no knowledge, however, how runners at the age of 90 years or older pace during a long run. In this case report, we describe the pacing of a 94-year-old man competing in a 6-hour run in order to prepare for a marathon at the age of 95 years in category M95. In the “6-Stunden-Lauf ” held in Brugg, Switzerland, participants have to run as many laps of 0.934 km as possible on a completely flat circuit within 6 hours to achieve as many kilometers as possible. Before and after the competition we measured body weight, percentage of body fat, fat-free mass and percentage of body water using a bioelectrical impedance scale. On the day before the start, 24 hours after the finish and then every 24 hours for the following 4 days, capillary blood samples at a fingertip were drawn to determine hemoglobin, hematocrit, leukocytes, platelets, C-reactive protein, creatine kinase, creatinine and potassium and sodium. The runner achieved 26 laps during the 6 hours, equal to 24.304 km. Lap times increased continuously and running speed decreased nearly linearly. A large main effect of time point (hours) of the race on running speed was observed (p=0.015, η²=0.48) with running speed being slower in the last hour than that in the first hour (3.5±1.4 km/h versus 5.3±0.4 km/h). Body mass decreased by 0.6%, percent body fat by 1.4% and fat-free mass by 0.7%. During recovery, hemoglobin, hematocrit and the number of thrombocytes increased, whereas the number of leukocytes remained unchanged. C-reactive protein was highest on day 1 after the race and decreased by day 4 nearly to zero. Creatine kinase was slightly elevated pre-race, highest the day after the race and remained slightly elevated until day 4. Creatinine and potassium were increased pre-race but returned to normal values during recovery. Sodium remained within normal values on all days. Based on the linear decrease in running speed, we extrapolated for the marathon distance to run a marathon in age group M95 (i.e., male marathoners aged 95–99 years). In the worst-case scenario (i.e., the athlete develops maximal fatigue), he would stop the race before 40 km, in the best scenario (i.e., the athlete develops minimal fatigue), he would achieve an overall race time of ~8.3 hours and in the most probable scenario (i.e., the athlete can continue in the same manner), the final race time will be longer than 11 hours.

Age-related decline in endurance running performance – an example of a multiple World records holder

This study examined the age-related decline in endurance running performance of one of the greatest master runners ever, Ed Whitlock, who died recently. His running performances from 1500 m to marathon were analyzed for 5 periods of 5 years from 65–69 years to 85–89 years. Despite exceptional running performances for his advanced age, the rate of decline in his performances increased after 80 years and was drastically amplified after 85 years.

Pacing in age group marathoners in the "New York City Marathon"

The aim of the study was to investigate how women and men age group runners pace during a large city marathon. We analysed changes in running speed by splits of 5 km in 20,283 women and 28,282 men age group runners competing in the 2015 edition of the "New York City Marathon". A moderate split×sex interaction on running speed (p < 0.001, η² = 0.108) was observed with men showing a larger decrease in speed from the fastest split (5-10 km) to the slowest one (35-40 km) than women (21.1 vs. 16.7%), and a different pattern was observed in the 25-30 km split (increase in women, decrease in men). A trivial split×age group interaction on speed was observed in women (p < 0.001, η² = 0.003) and men (p < 0.001, η² = 0.004). In summary, men and women of all age groups reduced running speed during the marathon with a final spurt in the last segment (i.e. 40-42.2 km).

Surgical Management of the Aging Athlete

Epidemiologic data show that the number of middle aged (>40 yr) and elderly (>65 yr) individuals continues to increase steadily, creating an expanding need for sports medicine care. Management of injuries in this subset of patients is expanding well beyond sustaining a patient's ability to perform activities of daily living. In fact, many older individuals increasingly expect to maintain reasonably high activity levels throughout their lifespan as well as after musculoskeletal injury. While a number of the emerging physiologic benefits of physical activity in older patients have been outlined, no recent review has outlined the current best surgical techniques, rehabilitation protocols, and return-to-sport recommendations for older athletes after soft-tissue repair or reconstruction as well as joint replacement. The goal of orthopaedic care in the elderly patient is shifting from simple pain relief toward return to athletic activity.

Masters Athletes: Exemplars of Successful Aging?

Global population aging has raised academic interest in successful aging to a public policy priority. Currently there is no consensus regarding the definition of successful aging. However, a synthesis of research shows successful aging can be defined as a late-life process of change characterized by high physical, psychological, cognitive, and social functioning. Masters athletes systematically train for, and compete in, organized forms of team and individual sport specifically designed for older adults. Masters athletes are often proposed as exemplars of successful aging. However, their aging status has never been examined using a comprehensive multidimensional successful aging definition. Here, we examine the successful aging literature, propose a successful aging definition based on this literature, present evidence which suggests masters athletes could be considered exemplars of successful aging according to the proposed definition, and list future experimental research directions.

Performance Trends in Master Butterfly Swimmers Competing in the FINA World Championships

Performance trends in elite butterfly swimmers are well known, but less information is available regarding master butterfly swimmers. We investigated trends in participation, performance and sex differences in 9,606 female and 13,250 male butterfly race times classified into five-year master groups, from 25-29 to 90-94 years, competing in the FINA World Masters Championships between 1986 and 2014. Trends in participation were analyzed using linear regression analysis. Trends in performance changes were investigated using mixed-effects regression analyses with sex, distance and a calendar year as fixed variables. We also considered interaction effects between sex and distance. Participation increased in master swimmers older than ~30-40 years. The men-to-women ratio remained unchanged across calendar years and master groups, but was lower in 200 m compared to 50 m and 100 m. Men were faster than women from 25-29 to 85-89 years (p < 0.05), although not for 90-94 years. Sex and distance showed a significant interaction in all master groups from 25-29 to 90-94 years for 200m (p < 0.05). For 50 m and 100 m, a significant sex × distance interaction was observed from 25-29 to 75-79 years (p < 0.05), but not in the older groups. In 50 m, women reduced the sex difference in master groups 30-34 to 60-64 years (p < 0.05). In 100 m, women decreased the gap to men in master groups 35-39 to 55-59 years (p < 0.05). In 200 m, the sex difference was reduced in master groups 30-34 to 40-44 years (p < 0.05). In summary, women and men improved performance at all distances, women were not slower compared to men in the master group 90-94 years; moreover, women reduced the gap to men between ~30 and ~60 years, although not in younger or older master groups.

Effects of increased participation on veteran running performance

Contrary to elite performance that is approaching an asymptote, recent analyses suggested a trend for improvement in veterans. This might be attributable to a disproportionate increase in older age-group participation. We extracted 26 years (1987-2012) of men's results of a running event in Switzerland, "La Course de l'Escalade" (7.25 km). We investigated trends in performance by five-year age-groups, taking the 10, 20, 30, and 50 fastest in each group, and then the 1^st, 5^th, and 10^th percentiles. Taking the 10, 20, 30 or 50 fastest runners there was a trend for improvement ranging from 0.07 to 0.22 min·year^-1 (p < .0001; 95% CI -0.083 to -0.049 and p < .0001; 95% CI -0.250 to -0.196 respectively) in the elder age-groups. Taking the 1^st, 5^th, and 10^th percentiles there were no trends for improvement, and actual deteriorations up to 0.13 (p < .0001; 95% CI +0.119 to +0.138) min·year^-1. Mixed-effect models with repeated measures for runners, confirmed a global deteriorating trend with an estimate of +0.11 min·year^-1 (p < .0001; 95% CI +0.107 to +0.116). The results suggest that increases in performance in older runners arise from modifications of sampling from a growing population.

The age-related performance decline in marathon cross-country skiing - the Engadin Ski Marathon

Demographic and performance data from 197,825 athletes competing in "Engadin Ski Marathon" between 1998 and 2016 were analysed. When all finishers per age group were considered, there was no gender difference in time (2:59:00 in women versus 2:59:09 h:min:s in men; P = 0.914, η² < 0.001) and the main effect of age group on time was trivial (P < 0.001, η² = 0.007). When the top 10 finishers per age group were considered, men were faster than women (1:27:32 versus 1:34:19 h:min:s, respectively; P < 0.001, η² = 0.373), there was a large effect of age group on time (P < 0.001, η² = 0.590) and the gender difference was larger in the older than in the younger age groups (P < 0.001, η² = 0.534). The age of peak performance for all finishers by 1-year interval age group was 40.3 and 39.6 years in all women and men, respectively. The top 10 finishers by 1-year interval age group achieved their peak performance in the age of 38.4 and 42.2 years in women and men, respectively. The age of peak performance was older and the age-related performance decline occurred earlier in marathon cross-country skiing, compared to road-based marathon running.

A combination of routine blood analytes predicts fitness decrement in elderly endurance athletes

Endurance sports are enjoying greater popularity, particularly among new target groups such as the elderly. Predictors of future physical capacities providing a basis for training adaptations are in high demand. We therefore aimed to estimate the future physical performance of elderly marathoners (runners/bicyclists) using a set of easily accessible standard laboratory parameters. To this end, 47 elderly marathon athletes underwent physical examinations including bicycle ergometry and a blood draw at baseline and after a three-year follow-up period. In order to compile a statistical model containing baseline laboratory results allowing prediction of follow-up ergometry performance, the cohort was subgrouped into a model training (n = 25) and a test sample (n = 22). The model containing significant predictors in univariate analysis (alanine aminotransferase, urea, folic acid, myeloperoxidase and total cholesterol) presented with high statistical significance and excellent goodness of fit (R2 = 0.789, ROC-AUC = 0.951±0.050) in the model training sample and was validated in the test sample (ROC-AUC = 0.786±0.098). Our results suggest that standard laboratory parameters could be particularly useful for predicting future physical capacity in elderly marathoners. It hence merits further research whether these conclusions can be translated to other disciplines or age groups.

Prevalence of Subclinical Coronary Artery Disease in Masters Endurance Athletes With a Low Atherosclerotic Risk Profile

BACKGROUND

Studies in middle-age and older (masters) athletes with atherosclerotic risk factors for coronary artery disease report higher coronary artery calcium (CAC) scores compared with sedentary individuals. Few studies have assessed the prevalence of coronary artery disease in masters athletes with a low atherosclerotic risk profile.

METHODS

We assessed 152 masters athletes 54.4±8.5 years of age (70% male) and 92 controls of similar age, sex, and low Framingham 10-year coronary artery disease risk scores with an echocardiogram, exercise stress test, computerized tomographic coronary angiogram, and cardiovascular magnetic resonance imaging with late gadolinium enhancement and a 24-hour Holter. Athletes had participated in endurance exercise for an average of 31±12.6 years. The majority (77%) were runners, with a median of 13 marathon runs per athlete.

RESULTS

Most athletes (60%) and controls (63%) had a normal CAC score. Male athletes had a higher prevalence of atherosclerotic plaques of any luminal irregularity (44.3% versus 22.2%; P=0.009) compared with sedentary males, and only male athletes showed a CAC ≥300 Agatston units (11.3%) and a luminal stenosis ≥50% (7.5%). Male athletes demonstrated predominantly calcific plaques (72.7%), whereas sedentary males showed predominantly mixed morphology plaques (61.5%). The number of years of training was the only independent variable associated with increased risk of CAC >70th percentile for age or luminal stenosis ≥50% in male athletes (odds ratio, 1.08; 95% confidence interval, 1.01-1.15; P=0.016); 15 (14%) male athletes but none of the controls revealed late gadolinium enhancement on cardiovascular magnetic resonance imaging. Of these athletes, 7 had a pattern consistent with previous myocardial infarction, including 3(42%) with a luminal stenosis ≥50% in the corresponding artery.

CONCLUSIONS

Most lifelong masters endurance athletes with a low atherosclerotic risk profile have normal CAC scores. Male athletes are more likely to have a CAC score >300 Agatston units or coronary plaques compared with sedentary males with a similar risk profile. The significance of these observations is uncertain, but the predominantly calcific morphology of the plaques in athletes indicates potentially different pathophysiological mechanisms for plaque formation in athletic versus sedentary men. Coronary plaques are more abundant in athletes, whereas their stable nature could mitigate the risk of plaque rupture and acute myocardial infarction.

Excessive Exercise Habits in Marathoners as Novel Indicators of Masked Hypertension

Background. Excessive exercise such as marathon running increases the risk of cardiovascular events that may be related to myocardial infarction and sudden death. We aimed to investigate that the exercise characteristics can be used as a novel indicator of masked hypertension. Methods. A total of 571 middle-aged recreational male marathoners were assigned to a high blood pressure group (HBPG; n = 214) or a normal blood pressure group (NBPG; n = 357). A graded exercise test was used to examine the hemodynamic response and cardiac events, and the personal exercise characteristics were recorded. Results. Systolic blood pressure and diastolic blood pressure were higher in the HBPG than in the NBPG (p < 0.05, all). The marathon history, exercise intensity, and time were longer and higher, whereas the marathon completion duration was shorter in the HBPG than in NBPG (p < 0.05, all). HBPG showed a higher frequency of alcohol consumption than NBPG (p < 0.05). Conclusion. More excessive exercise characteristics than the normative individuals. If the individuals exhibit high blood pressure during rest as well as exercise, the exercise characteristics could be used as a novel indicator for masked hypertension.

Declines in marathon performance: Sex differences in elite and recreational athletes

The first aim of this study was to determine the age group at which marathon performance declines in top male and female runners and to compare that to the runners of average ability. Another aim of this of this study was to examine the age-related yearly decline in marathon performance between age group winners and the average marathon finisher. Data from the New York (NYC), Boston, and Chicago marathons from 2001–2016 were analyzed. Age, sex, and location were used in multiple linear regression models to determine the rate of decline in marathon times. Winners of each age group were assessed in 5-year increments from 16 through 74 years old (n = 47 per age group). The fastest times were between 25–34 years old, with overall champion males at 28.3 years old, and overall champion females at 30.8 years old (p = 0.004). At 35 years of age up to 74 years of age, female age group winners had a faster yearly decline in marathon finishing times compared to male age group winners, irrespective of marathon location [women = (min:sec) 2:33 per year, n = 336; men = 2:06 per year, n = 373, p < 0.01]. The median times between each age group only slowed beginning at 50 years old, thereafter the decline was similar between both men and women (women = 2:36, n = 140; men = 2:57, n = 150, p = 0.11). The median times were fastest at Boston and similar between Chicago and NYC. In conclusion, the rate of decline at 35 years old up to 74 years old is roughly linear (adjusted r² = 0.88, p < 0.001) with female age group winners demonstrating 27 s per year greater decline per year compared to male age group winners.

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.

Master Athletes Are Extending the Limits of Human Endurance

The increased participation of master athletes (i.e., >40 years old) in endurance and ultra-endurance events (>6 h duration) over the past few decades has been accompanied by an improvement in their performances at a much faster rate than their younger counterparts. Aging does however result in a decrease in overall endurance performance. Such age-related declines in performance depend upon the modes of locomotion, event duration, and gender of the participant. For example, smaller age-related declines in cycling performance than in running and swimming have been documented. The relative stability of gender differences observed across the ages suggests that the age-related declines in physiological function did not differ between males and females. Among the main physiological determinants of endurance performance, the maximal oxygen consumption (VO_2max) appears to be the parameter that is most altered by age. Exercise economy and the exercise intensity at which a high fraction of VO_2max can be sustained (i.e., lactate threshold), seem to decline to a lesser extent with advancing age. The ability to maintain a high exercise-training stimulus with advancing age is emerging as the single most important means of limiting the rate of decline in endurance performance. By constantly extending the limits of (ultra)-endurance, master athletes therefore represent an important insight into the ability of humans to maintain physical performance and physiological function with advancing age.

A technique to determine the fastest age-adjusted masters marathon world records

Introduction/Purpose

This study’s purpose was to develop and employ a technique to determine the fastest masters marathon world records (WR), ages 35–79 years, adjusted for age (WRadj).

Methods

From single-age WR data, a best-fit polynomial curve (WRpred1) was developed for the larger age range of 29–80 years for women and 30–80 years for men to improve curve stability in the 35–79 years range. Due to the relatively large degree of data scatter about the curve and the resultant age bias in favor of older runners, a subsample was constituted consisting of those with the lowest WR/WRpred1 ratio within each five-year age group (N = 11). A new polynomial best-fit curve (WRpred2) was developed from this subsample to become the standard against which WR would be compared across age. WRadj was computed from WR/WRpred2 for all runners, 35–79 years, from which the top ten fastest were then determined.

Results

The WRpred2 model reduced data scatter and eliminated the age bias. Tatyana Pozdniakova, 50 years, WR = 2:31:05, WRadj = 2:12:40; and Ed Whitlock, 73 years, WR = 2:54:48, WRadj = 1:59:57, had the fastest WRadj for women and men, respectively.

Conclusions

This technique of iterative curve-fitting may be an optimal way of determining the fastest masters WRadj and may also be useful in better understanding the upper limits of human performance by age.

Effects of age on marathon finishing time among male amateur runners in Stockholm Marathon 1979-2014

PURPOSE

The purpose of the present study was to investigate the age-related changes in the endurance performance among male amateur marathon runners.

METHODS

Subjects were taken from the 36 Stockholm Marathons held from 1979 through 2014, and age and finishing time were analyzed for a total of 312,342 male runners.

RESULTS

The relation was found to be a second-order polynomial, t = a + bx + cx ², which models 99.7% of the variation in the average running time t as a function of age x. The model shows that the marathon performance of the average runner improves up to age 34.3 ± 2.6 years, thereafter, the performance starts to decline. A quantification of the age's influence on running time shows that it accounts for 4.5% of the total variance seen in the performance data.

CONCLUSION

These outcomes indicate that the effect of age on performance in endurance running events is clearly measurable, quantifiable, and possible to describe. At the same time the findings indicate that other factors, such as training, affect the performance more. A comparison with the elite showed peak performance at the same age, but the rates of change in performance with age, improvement as well as degradation, was found to be higher among the elite.

Centenarian athletes: Examples of ultimate human performance?

BACKGROUND

some centenarians are engaged in regular physical activity and sometimes in sporting events.

OBJECTIVE

we aimed to identify world records of centenarian athletes in several sports and determine which represented the best performance when compared to all-age world records, all disciplines taken together.

METHODS

all of the best performances achieved by centenarians were identified and compared in three disciplines: athletics, swimming and cycling. The performances were considered as an average of the respective speeds, except for jumping and throwing events for which the maximum distances performed were considered. Within each discipline, the decline in performance of centenarian athletes was expressed as a percentage of the world record for that discipline. In total, 60 performances of centenarian athletes were found. These performances belong to 19 individuals: 10 in athletics, 8 in swimming and 1 in cycling.

RESULTS

the centenarian world record performed by Robert Marchand in one hour track cycling appears to be the best performance (-50.6% compared with the all-age world record in this discipline) achieved by a centenarian.

CONCLUSIONS

although the physiological characteristics of Robert Marchand are certainly exceptional, his remarkable performance could also be due to the lower age-related decline for cycling performances compared with running and swimming. Our observations offer new perspectives on how the human body can resist the deleterious effects of ageing.

Do women reduce the gap to men in ultra-marathon running?

The aim of the present study was to examine sex differences across years in performance of runners in ultra-marathons lasting from 6 h to 10 days (i.e. 6, 12, 24, 48, 72, 144, and 240 h). Data of 32,187 finishers competing between 1975 and 2013 with 93,109 finishes were analysed using multiple linear regression analyses. With increasing age, the sex gap for all race durations increased. Across calendar years, the gap between women and men decreased in 6, 72, 144 and 240 h, but increased in 24 and 48 h. The men-to-women ratio differed among age groups, where a higher ratio was observed in the older age groups, and this relationship varied by distance. In all durations of ultra-marathon, the participation of women and men varied by age (p < 0.001), indicating a relatively low participation of women in the older age groups. In summary, between 1975 and 2013, women were able to reduce the gap to men for most of timed ultra-marathons and for those age groups where they had relatively high participation.

Increased participation and improved performance in age group backstroke master swimmers from 25-29 to 100-104 years at the FINA World Masters Championships from 1986 to 2014

Participation and performance trends in age group athletes have been investigated for different sport disciplines, but not for master swimmers. The knowledge on this topic is still missing for a particular stroke such as backstroke. Changes in participation and performance of male and female age group backstroke swimmers (≥25 years) competing in 50, 100 and 200 m pool swimming at the FINA World Masters Championships held between 1986 and 2014 were investigated using mixed-effects regression analyses. The overall participation was n = 26,217 including n = 13,708 women and n = 12,509 men. In 50 m, female (age groups 85–89 years; p = 0.002) and male participation (age groups 55–59; p = 0.030 and 80–84 years; p = 0.002) increased, while female participation decreased in age groups 55–59 (p = 0.010) and 60–64 years (p = 0.050). In 100 and 200 m, participation increased in age groups 45–49, 50–54, 65–69, 70–74, 80–84 years. Swimmers in age groups 25–29 to 95–99 years improved performance over all distances. Women were slower than men in age groups 25–29 to 80–84 years, but not in age groups 85–89 to 95–99 years over all distances. In 50 m and 100 m, the sex difference decreased in age groups 40–44 (p = 0.007 and p = 0.005), 45–49 (p = 0.017 and p = 0.034), 50–54 (p = 0.002 and p = 0.040), to 55–59 years (p = 0.002 and p = 0.004). In 200 m, the sex difference decreased in age groups 40–44 (p = 0.044) and 90–94 (p = 0.011), but increased in age group 25–29 years (p = 0.006). In summary, in age group backstroke swimmers, (1) participation increased or remained unchanged (except women in age groups 55–59 and 60–64 years in 50 m), (2) swimming performance improved in all age groups from 25–29 to 95–99 years over all distances, (3) men were faster than women in age groups 25–29 to 80–84 years (except age groups 85–89 to 95–99 years) over time and all distances.

The Age in Swimming of Champions in World Championships (1994⁻2013) and Olympic Games (1992⁻2012): A Cross-Sectional Data Analysis

(1) Background: We investigated the age of swimming champions in all strokes and race distances in World Championships (1994–2013) and Olympic Games (1992–2012); (2) Methods: Changes in age and swimming performance across calendar years for 412 Olympic and world champions were analysed using linear, non-linear, multi-level regression analyses and MultiLayer Perceptron (MLP); (3) Results: The age of peak swimming performance remained stable in most of all race distances for world champions and in all race distances for Olympic champions. Longer (i.e., 200 m and more) race distances were completed by younger (~20 years old for women and ~22 years old for men) champions than shorter (i.e., 50 m and 100 m) race distances (~22 years old for women and ~24 years old for men). There was a sex difference in the age of champions of ~2 years with a mean age of ~21 and ~23 years for women and men, respectively. Swimming performance improved in most race distances for world and Olympic champions with a larger trend of increase in Olympic champions; (4) Conclusion: Swimmers at younger ages (<20 years) may benefit from training and competing in longer race distances (i.e., 200 m and longer) before they change to shorter distances (i.e., 50 m and 100 m) when they become older (>22 years).

Performance trends in master freestyle swimmers aged 25-89 years at the FINA World Championships from 1986 to 2014

Performance trends in elite freestyle swimmers are well known, but not for master freestyle swimmers. We investigated trends in participation, performance, and sex difference in performance of 65,584 freestyle master swimmers from 25-29 to 85-89 years competing in FINA World Masters Championships between 1986 and 2014. The men-to-women ratio was calculated for each age group, and the trend across age groups was analyzed using single linear regression analysis. Trends in performance changes were investigated using a mixed-effects regression model with sex, distance, and calendar year as fixed variables. Participation increased in women and men in older age groups (i.e., 40 years and older). Women and men improved race times across years in all age groups and distances. For age groups 25-29 to 75-79 years, women were slower than men, but not for age groups 80-84 to 85-89 years. In 50, 100, and 200 m, women reduced the sex difference from 1986 to 2014 in age groups 30-34 to 75-79 years. In 400 m, women reduced the gap to men across time in age groups 40-44, 45-49, and 55-59 years. In 800 m, sex difference became reduced across time in age groups 55-59 and 70-74 years. In summary, participation increased from 1986 to 2014 in women and men in older age groups, women and men improved across time performance in all distances, and women were not slower compared to men in age groups 80-84 to 85-89 years. We expect a continuous trend in increasing participation and improved performance in master freestyle swimmers.

Half-marathoners are younger and slower than marathoners

Age and performance trends of elite and recreational marathoners are well investigated, but not for half-marathoners. We analysed age and performance trends in 508,108 age group runners (125,894 female and 328,430 male half-marathoners and 10,205 female and 43,489 male marathoners) competing between 1999 and 2014 in all flat half-marathons and marathons held in Switzerland using single linear regression analyses, mixed-effects regression analyses and analyses of variance. The number of women and men increased across years in both half-marathons and marathons. There were 12.3 times more female half-marathoners than female marathoners and 7.5 times more male half-marathoners than male marathoners. For both half-marathons and marathons, most of the female and male finishers were recorded in age group 40-44 years. In half-marathons, women (10.29 ± 3.03 km/h) were running 0.07 ± 0.06 km/h faster (p < 0.001) than men (10.22 ± 3.06 km/h). Also in marathon, women (14.77 ± 4.13 km/h) were running 0.28 ± 0.16 km/h faster (p < 0.001) than men (14.48 ± 4.07 km/h). In marathon, women (42.18 ± 10.63 years) were at the same age than men (42.06 ± 10.45 years) (p > 0.05). Also in half-marathon, women (41.40 ± 10.63 years) were at the same age than men (41.31 ± 10.30 years) (p > 0.05). However, women and men marathon runners were older than their counterpart half-marathon runners (p < 0.001). In summary, (1) more athletes competed in half-marathons than in marathons, (2) women were running faster than men, (3) half-marathoners were running slower than marathoners, and (4) half-marathoners were younger than marathoners.

EFFECTS OF NORMAL AGING ON LOWER EXTREMITY LOADING AND COORDINATION DURING RUNNING IN MALES AND FEMALES

BACKGROUND

Runners sustain high injury rates. As greater numbers of individuals continue to run past the age of 60, normal physiological changes that occur with aging may further contribute to injuries. Male and female runners demonstrate different mechanics and injury rates. However, whether these mechanics further diverge as runners age and whether or not this potential divergence in mechanics may or may not be associated with a potential for increased injury risk is unknown.

HYPOTHESIS/PURPOSE

The purpose of this study was to compare measures of loading and lower extremity coupling during running with respect to age and sex. It was hypothesized that males and females would demonstrate increasingly diverging mechanics with increased age.

METHODS

Forty-one subjects were placed in four groups: younger males (n=13), younger females (n=6), older males (n=16), and older females (n=6). Ten running trials were collected and analyzed for each subject. Kinematic data were collected and reconstructed using a nine-camera motion analysis system and commercial software. Vertical loading rate (VLR), initial (GRF1) and peak vertical ground reaction force (GRF2) and lower leg joint coupling were calculated for each subject. Analysis was performed using a 2-factor ANOVA (sex X age) to determine differences between groups during the stance phase of running.

RESULTS

Compared to younger subjects, older subjects demonstrated higher GRF1 per body weight (Y: 1.70 (0.19), O: 1.96 (0.23), p < 0.01), higher VLR in body weight/second (Y: 44.17 (6.73), O: 52.76 (8.39), p < 0.01) and lower GRF2 per body weight (Y: 2.47 (0.18), O: 2.35 (0.18), p=0.04). However, no differences existed between males and females or further diverged in the older subjects. There were no differences between or within groups in joint coupling. Finally, no significant differences were seen between sexes and no interactions were found between any variables in the current study.

CONCLUSIONS

Older runners experience greater GRF1 and VLR and lower GRF2. These are factors previously associated with tibial loading and stress fractures. Males and females do not differ on these factors suggesting older female runners may be at no greater risk than younger runners or male runners for lower extremity bony injury based on normal mechanics.

LEVEL OF EVIDENCE

3.

Increase in participation but decrease in performance in age group mountain marathoners in the 'Jungfrau Marathon': a Swiss phenomenon?

Participation and performance trends for age group marathoners have been investigated for large city marathons such as the ‘New York City Marathon’ but not for mountain marathons. This study investigated participation and trends in performance and sex difference in the mountain marathon ‘Jungfrau Marathon’ held in Switzerland from 2000 to 2014 using single and mixed effects regression analyses. Results were compared to a city marathon (Lausanne Marathon) also held in Switzerland during the same period. Sex difference was calculated using the equation ([race time in women] − [race time in men]/[race time in men] × 100). Changes in sex differences across calendar years and were investigated using linear regression models. In ‘Jungfrau Marathon’, participation in all female and male age groups increased with exception of women in age groups 18–24 and men in age groups 30–34, 40–44 and 60–64 years where participation remained unchanged. In ‘Lausanne Marathon’, participation increased in women in age groups 30–34 to 40–44 years. In men, participation increased in age groups 25–29 to 44–44 years and 50–54 years. In ‘Jungfrau Marathon’ runners became slower across years in age groups 18–24 to 70–74 years. In ‘Lausanne Marathon’, runners became slower across years in age groups 18–24 and 30–34 to 65–69 years, but not for 25–29, 70–74 and 75–79 years. In ‘Jungfrau Marathon’, sex difference increased in age groups 25–29 (from 4 to 10 %) and 60–64 years (from 3 to 8 %) but decreased in age group 40–44 years (from 12 to 6 %). In ‘Lausanne Marathon’, the sex difference showed no changes. In summary, participation increased in most female and male age groups but performance decreased in most age groups for both the mountain marathon ‘Jungfrau Marathon’ and the city marathon ‘Lausanne Marathon’. The sex differences were lower in the ‘Jungfrau Marathon’ (~6–7 %) compared to the ‘Lausanne Marathon’ where the sex difference was ~10–12 % from age groups 18–24 to 55–59 years. These unexpected findings might be a typical Swiss phenomenon. Future studies need to investigate whether this trend can also be found in other endurance sports events held in Switzerland and other mountain marathons held in other countries.

Participation and performance trends in elderly marathoners in four of the world's largest marathons during 2004-2011

Performance and age of elite marathoners is well known. Participation and performance trends of elderly marathoners (75 years and older) are not well investigated. This study investigated participation and performance trends in elderly marathoners older than 75 years competing during 2004-2011 in four races (Berlin, New York, Chicago and Boston) of the 'World Marathon Majors' using mixed-effects regression models. Participation for women and men remained unchanged at 17 and 114, respectively, during the investigated period. For all finishers, marathon race times showed a significant and positive trend for gender, calendar year and age. For the annual fastest, calendar year and age showed a significant and positive trend. For the annual three fastest, gender, calendar year and age showed a significant and positive trend. The gender difference for the annual fastest and the annual three fastest showed no change across years. For the annual fastest and the annual three fastest, race times were fastest in the youngest age group (75-79 years) and slowest in the oldest age group (85-89 and 80-84 years, respectively). The gender difference in marathon race times remained unchanged across years at 19.7 ± 11.2, 28.1 ± 23.8 and 41.9 ± 22.6 % for the annual fastest in age groups 75-79, 80-84 and 85-89 years, respectively. For the annual three fastest men and women in age groups 75-79 and 80-84 years, the values were 23.7 ± 3.2 and 30.0 ± 13.2 %, respectively. In summary, for marathoners older than 75 years participating during 2004-2011 in four of the largest marathons in the world, participation for female and male runners remained unchanged, the fastest women and men became slower across years and the gender difference in performance remained unchanged. These findings might be the results of the relatively short period of time of 8 years. Future studies might investigate the performance trends in a large city marathon across a longer period of time.

Greater progression of athletic performance in older Masters athletes

BACKGROUND

The number of new world records has decreased substantially in most athletic events in recent years. There has been enormous growth in participation at Masters events, and older athletes have been competing at the highest levels with much younger athletes. However, the progression of athletic performance over time has not been well investigated in Masters athletes.

OBJECTIVE AND METHODS

To determine whether older Masters athletes improved athletic performance over time, running and swimming times from 1975 to 2013 were collected biennially. The running event of 100 m was chosen specifically, as it is one of the most popular track and field events that would have attracted a large number of competitors. The middle distance of 400 m as well as 100 m freestyle swimming were also examined to determine whether the results in 100 m sprint event can be confirmed in other events.

RESULTS

The improvements in fastest 100 m running times over time were not significant. However, all the Masters age-group records improved significantly over time. The slopes of improvements over the years were progressively greater at older age groups with the greatest progression observed at oldest age groups of 75-79 years examined. The general trends were similar for 400 m middle-distance running and 100 m freestyle swimming.

CONCLUSIONS

While younger athletes' performance has stagnated, Masters athletes improved their athletic performance significantly and progressively over the years. The magnitude of improvements was greater in older age groups gradually closing the gap in athletic performance between younger and older participants.

Performance trends in large 10-km road running races in the United States

Our study examines the current trends of runners participating in 10-km road races in the United States. Finish times and ages of all runners participating in 10 of the largest 10-km running races in the United States between 2002-2005 and 2011 were recorded. Linear regression analysis was performed to examine the trends for age, sex, and finishing time for all participants completing the course in <1 hour. A total of 408,296 runners were analyzed. There was a significant annual decrease in the ratio of men to women finishers (p < 0.001, r = 0.976). The average finishing time of the top 10 (men, p ≤ 0.05), 100 (men and women, p ≤ 0.05), and 1,000 (men and women, p < 0.01) significantly decreased annually. The total number of subhour finishers increased annually across all races (194 men per year, r = 0.584, p = 0.045; 161 women per year, r = 0.779, p = 0.008), whereas the percentage of overall finishers completing the course in less than an hour significantly declined for men and women (p ≤ 0.003). There was a significant trend toward younger men in all top groups except for the single fastest runner (p ≤ 0.017). Our study demonstrates that for large 10-km U.S. races: the top men and women seem to be getting faster; there are more subhour finishers, with increasingly more women accomplishing this feat compared with men; an increasingly lower percentage of overall finishers is finishing in <1 hour; and the fastest men are also increasingly younger.

Change of the age and performance of swimmers across World Championships and Olympic Games finals from 1992 to 2013 - a cross-sectional data analysis

The aims of the present study were to investigate the changes in the age and in swimming performance of finalists in World Championships (1994–2013) and Olympic Games (1992–2012) competing in all events/races (stroke and distance). Data of 3,295 performances from 1,615 women and 1,680 men were analysed using correlation analyses and magnitudes of effect sizes. In the World Championships, the age of the finalists increased for all strokes and distances with exception of 200 m backstroke in women, and 400 m freestyle and 200 m breaststroke in men where the age of the finalists decreased. The magnitudes of the effects were small to very large (mean ± SD 2.8 ± 2.7), but extremely large (13.38) for 1,500 m freestyle in women. In the Olympic Games, the age of the finalists increased for all strokes and distances with exception of 800 m freestyle in women and 400 m individual medley in men. The magnitudes of the effects were small to very large (mean ± SD 4.1 ± 7.1), but extremely large for 50 m freestyle in women (10.5) and 200 m butterfly in men (38.0). Swimming performance increased across years in both women and men for all strokes and distances in both the World Championships and the Olympic Games. The magnitudes of the effects were all extremely large in World Championships (mean ± SD 20.1 ± 8.4) and Olympic Games (mean ± SD 52.1 ± 47.6); especially for 100 m and 200 m breaststroke (198) in women in the Olympic Games. To summarize, in the last ~20 years the age of the finalists increased in both the World Championships and the Olympic Games with some minor exceptions (200 m backstroke in women, 400 m freestyle and 200 m breaststroke in men in World Championships and 800 m freestyle in women and 400 m individual medley in men in Olympic Games) and performance of the finalists improved.

What is the age for the fastest ultra-marathon performance in time-limited races from 6 h to 10 days?

Recent findings suggested that the age of peak ultra-marathon performance seemed to increase with increasing race distance. The present study investigated the age of peak ultra-marathon performance for runners competing in time-limited ultra-marathons held from 6 to 240 h (i.e. 10 days) during 1975-2013. Age and running performance in 20,238 (21%) female and 76,888 (79%) male finishes (6,863 women and 24,725 men, 22 and 78%, respectively) were analysed using mixed-effects regression analyses. The annual number of finishes increased for both women and men in all races. About one half of the finishers completed at least one race and the other half completed more than one race. Most of the finishes were achieved in the fourth decade of life. The age of the best ultra-marathon performance increased with increasing race duration, also when only one or at least five successful finishes were considered. The lowest age of peak ultra-marathon performance was in 6 h (33.7 years, 95% CI 32.5-34.9 years) and the highest in 48 h (46.8 years, 95% CI 46.1-47.5). With increasing number of finishes, the athletes improved performance. Across years, performance decreased, the age of peak performance increased, and the age of peak ultra-marathon performance increased with increasing number of finishes. In summary, the age of peak ultra-marathon performance increased and performance decreased in time-limited ultra-marathons. The age of peak ultra-marathon performance increased with increasing race duration and with increasing number of finishes. These athletes improved race performance with increasing number of finishes.

[Physical activity diminishes aging-related decline of physical and cognitive performance]

Aging-related decline of muscle force, walking speed, locomotor coordination, aerobic capacity and endurance exert prognostic impact on life expectancy. Proper use of training may diminish the aging process and it may improve the quality of life of elderly persons. This paper provides a brief summary on the impact of training on aging-related decline of physical and cognitive functions.

Relationship between age and elite marathon race time in world single age records from 5 to 93 years

BACKGROUND

The aims of the study were (i) to investigate the relationship between elite marathon race times and age in 1-year intervals by using the world single age records in marathon running from 5 to 93 years and (ii) to evaluate the sex difference in elite marathon running performance with advancing age.

METHODS

World single age records in marathon running in 1-year intervals for women and men were analysed regarding changes across age for both men and women using linear and non-linear regression analyses for each age for women and men.

RESULTS

The relationship between elite marathon race time and age was non-linear (i.e. polynomial regression 4(th) degree) for women and men. The curve was U-shaped where performance improved from 5 to ~20 years. From 5 years to ~15 years, boys and girls performed very similar. Between ~20 and ~35 years, performance was quite linear, but started to decrease at the age of ~35 years in a curvilinear manner with increasing age in both women and men. The sex difference increased non-linearly (i.e. polynomial regression 7(th) degree) from 5 to ~20 years, remained unchanged at ~20 min from ~20 to ~50 years and increased thereafter. The sex difference was lowest (7.5%, 10.5 min) at the age of 49 years.

CONCLUSION

Elite marathon race times improved from 5 to ~20 years, remained linear between ~20 and ~35 years, and started to increase at the age of ~35 years in a curvilinear manner with increasing age in both women and men. The sex difference in elite marathon race time increased non-linearly and was lowest at the age of ~49 years.

Age group performances in 100 km and 100 miles ultra-marathons

Improved performance has been reported for master runners (i.e. athletes older than 40 years) in both single marathons and single ultra-marathons. This study investigated performance trends of age group ultra-marathoners competing in all 100 km and 100 miles races held worldwide between 1971 and 2013. Changes in running speeds across years were investigated for the annual ten fastest 5-year age group finishers using linear, non-linear and multi-level regression analyses. In 100 km, running speed remained unchanged in women in 25–29 years, increased non-linearly in 30–34 to 55–59 years, and linearly in 60–64 years. In men, running speed increased non-linearly in 18–24 to 60–64 years and linearly in 65–69 to 75–79 years. In 100 miles, running speed increased in women linearly in 25–29 and 30–34 years, non-linearly in 35–39 to 45–49 years, and linearly in 50–54 and 55–59 years. For men, running speed increased linearly in 18–24 years, non-linearly in 25–29 to 45–49 years, and linearly in 50–54 to 65–69 years. Overall, the faster race times over the last 30 years are a result of all top ten finishers getting faster. These findings suggest that athletes in younger to middle age groups (i.e. 25–35 to 50–65 years depending upon sex and distance) have reached their limits due to a non-linear increase in running speed whereas runners in very young (i.e. younger than 25–35 years) and older age groups (i.e. older than 50–65 years) depending upon sex and distance might still improve their performance due to a linear increase in running speed.

Sex and age-related differences in performance in a 24-hour ultra-cycling draft-legal event - a cross-sectional data analysis

Background

The purpose of this study was to examine the sex and age-related differences in performance in a draft-legal ultra-cycling event.

Methods

Age-related changes in performance across years were investigated in the 24-hour draft-legal cycling event held in Schötz, Switzerland, between 2000 and 2011 using multi-level regression analyses including age, repeated participation and environmental temperatures as co-variables.

Results

For all finishers, the age of peak cycling performance decreased significantly (β = −0.273, p = 0.036) from 38 ± 10 to 35 ± 6 years in females but remained unchanged (β = −0.035, p = 0.906) at 41.0 ± 10.3 years in males. For the annual fastest females and males, the age of peak cycling performance remained unchanged at 37.3 ± 8.5 and 38.3 ± 5.4 years, respectively. For all female and male finishers, males improved significantly (β = 7.010, p = 0.006) the cycling distance from 497.8 ± 219.6 km to 546.7 ± 205.0 km whereas females (β = −0.085, p = 0.987) showed an unchanged performance of 593.7 ± 132.3 km. The mean cycling distance achieved by the male winners of 960.5 ± 51.9 km was significantly (p < 0.001) greater than the distance covered by the female winners with 769.7 ± 65.7 km but was not different between the sexes (p > 0.05). The sex difference in performance for the annual winners of 19.7 ± 7.8% remained unchanged across years (p > 0.05). The achieved cycling distance decreased in a curvilinear manner with advancing age. There was a significant age effect (F = 28.4, p < 0.0001) for cycling performance where the fastest cyclists were in age group 35–39 years.

Conclusion

In this 24-h cycling draft-legal event, performance in females remained unchanged while their age of peak cycling performance decreased and performance in males improved while their age of peak cycling performance remained unchanged. The annual fastest females and males were 37.3 ± 8.5 and 38.3 ± 5.4 years old, respectively. The sex difference for the fastest finishers was ~20%. It seems that women were not able to profit from drafting to improve their ultra-cycling performance.

Trends in Triathlon Performance: Effects of Sex and Age

The influences of sex and age upon endurance performance have previously been documented for both running and swimming. A number of recent studies have investigated how sex and age influence triathlon performance, a sport that combines three disciplines (swimming, cycling and running), with competitions commonly lasting between 2 (short distance: 1.5-km swim, 40-km cycle and 10-km run) and 8 h (Ironman distance: 3.8-km swim,180-km cycle and 42-km run) for elite triathletes. Age and sex influences upon performance have also been investigated for ultra-triathlons, with distances corresponding to several Ironman distances and lasting several days, and for off-road triathlons combining swimming, mountain biking and trail running. Triathlon represents an intriguing alternative model for analysing the effects of age and sex upon endurance and ultra-endurance ([6 h) performance because sex differences and age-related declines in performance can be analysed in the same individuals across the three separate disciplines. The relative participation of both females and masters athletes (age[40 years) in triathlon has increased consistently over the past 25 years. Sex differences in triathlon performance are also known to differ between the modes of locomotion adopted (swimming, cycling or running) for both elite and non-elite triathletes. Generally, time differences between sexes in swimming have been shown to be smaller on average than during cycling and running. Both physiological and morphological factors contribute to explaining these findings. Performance density (i.e. the time difference between the winner and tenth-placed competitor) has progressively improved (time differences have decreased) for international races over the past two decades for both males and females, with performance density now very similar for both sexes. For age-group triathletes, sex differences in total triathlon performance time increases with age. However,the possible difference in age-related changes in the physiological determinants of endurance and ultra-endurance performances between males and females needs further investigation. Non-physiological factors such as low rates of participation of older female triathletes may also contribute to the greater age-related decline in triathlon performance shown by females. Total triathlon performance has been shown to decrease in a curvilinear manner with advancing age. However, when triathlon performanceis broken down into its three disciplines, there is a smaller age-related decline in cycling performance than in running and swimming performances. Age-associated changes in triathlon performance are also related to the total duration of triathlon races. The magnitude of the declines in cycling and running performances with advancing age for short triathlons are less pronounced than for longer Ironman distance races. Triathlon distance is also important when considering how age affects the rate of the decline in performance. Off-road triathlon performances display greater decrements with age than road-based triathlons, suggesting that the type of discipline (road vs. mountain bike cycling and road vs. trail running) is an important factor in age-associated changes in triathlon performance.Finally, masters triathletes have shown relative improvements in their performances across the three triathlon disciplines and total triathlon event times during Ironman races over the past three decades. This raises an important issue as to whether older male and female triathletes have yet reached their performance limits during Ironman triathlons

The relationship between age and running time in elite marathoners is U-shaped

Several investigations have demonstrated that running performance gradually decreases with age by using runners >25 years grouped in 5-year age brackets. The aim of this study was to determine the relationship between race time in marathon and age in elite marathoners by including all ages and 1-year intervals. Running times of the top ten men and women at 1-year intervals (from 18 to 75 years) in the New York City marathon were analyzed for the 2010 and 2011 races. Gender differences in performance times were analyzed between 18 and 70 years of age. The relationship between running time and runner's age was U-shaped: the lowest race time was obtained at 27 years (149 ± 14 min) in men and at 29 years (169 ± 17 min) in women. Before this age (e.g., 27 years for men and 29 years for women), running time increased by 4.4 ± 4.0 % per year in men and 4.4 ± 4.3 % per year in women. From this age on, running time increased by 2.4 ± 8.1 % per year in men and 2.5 ± 9.9 % per year in women. The sex difference in running time remained stable at ~18.7 ± 3.1 % from 18 to 57 years of age. After this, sex difference progressively increased with advancing age. In summary, endurance runners obtained their best performance in the marathon at 27 years in men and 29 in women. Thus, elite marathon runners should program their long-term training to obtain maximal performance during their late 20s.