Longitudinal trends in master track and field performance throughout the aging process: 83,209 results from Sweden in 16 athletics disciplines

Athletic Performance Decline Over the Life Span: Cross-Sectional and Longitudinal Analyses of Elite and Masters Track-and-Field Data

PURPOSE

Loss of muscle power has a significant impact on mobility in geriatric populations, so this study sought to determine the extent and time course of performance decline in power-centric events throughout the life span via retrospective analyses of masters and elite track-and-field data.

METHODS

Four track-and-field events were selected based on maximal power output: the 100-m dash, long jump, high jump, and triple jump. Elite and masters athlete data were gathered from the World Masters Outdoor Championships and the International Amateur Athletic Federation World Athletics Championships (17,945 individual results). Data were analyzed by fitting individual and group results to quadratic and linear models.

RESULTS

Average age of peak performance in all events was 27.8 (0.8) years for men and 28.3 (0.8) years for women. Athlete performance decline best matched a linear model for the 5 years following peak performance (mean R2 = .68 [.20]) and for ages 35-60, but best matched a quadratic model for ages 60-90 and 35-90 (mean R2 = .75 [.12]). The average rate of decline for the masters data ages 35-60 ranged from 0.55% per year for men's 100-m dash to 1.04% per year for women's long jump. A significant age × sex interaction existed between men and women, with men declining faster throughout life in all events except the 100-m dash.

CONCLUSIONS

Performance decline begins in the early 30s and is linear through middle age. This pattern of decline provides a basis for further research on power-decline pathophysiology and preventive measures starting in the 30s.

Effects of a similar amount of regular non-structured or competitive physical activity across late adulthood: a cross-sectional study

Introduction

Master athletes are examples of successful aging. It is not clear whether it is the competitive-oriented training or just the amount of total regular exercise that reduces the age-related decline in physiological functions. We aimed to compare health-related parameters in competitive (C) and physically active older adults (A) that performed the same weekly physical activity (PA) amount.

Methods

Seventeen C and 17 A were matched for age (8 and 9 male participants under and over 70 years old respectively, for both groups) and weekly PA amount (GPAQ). Body composition, leg and arm maximal strength, balance and reaction time were measured; moreover, leg and arm exercise efficiency, estimated VO2max, and VO2/HR relationships were evaluated. Perception of life and sleep quality was also assessed through specific questionnaires (SF-36 and PSQI). The effect of group (C vs. A), age (U70 vs. O70) and their interaction was examined through a Two-Way ANOVA test.

Results

C dedicated more time to vigorous PA compared to A (p = 0.03), while less to moderate daily work (p < 0.01) and active commuting (p = 0.06). C exhibited better body composition (all p < 0.05), higher leg maximal strength (p < 0.05) and a trend for elevated arm strength (p = 0.06). Reaction time, leg and arm cycling efficiency were similar in the two groups (all p > 0.05), while balance reduced in A O70. Estimated VO2max was higher for C in leg cycling (p = 0.05) and remained constant across ages (all p > 0.05). VO2/HR relationship, life and sleep quality did not differ for groups and ages.

Conclusions

Regular physical exercise of about 6,000 METs/week seems to have a beneficial effect on health-related parameters, both in non-structured and competitive PA, when compared to sedentary behaviour. However, the older adults engaged in competitive training exhibit further advantages: better body composition, higher arm and leg muscle strength, and higher leg VO2max. This study highlights the importance of encouraging active lifestyles for maintaining long-term health, high levels of life quality perception and reducing age-related decline. However, vigorous training suitability needs to be verified by a team of PA specialists.

A simple framework to distinguish 'individualistic' from a 'uniform rate' of ageing within or between study populations

Ageing is accompanied by a progressive decline in physiological functions. It is often argued that the rate of ageing differs between people and is 'highly individualistic'. This view is not unequivocally shared, and others have argued that the rate of ageing is rather 'uniform'. Distinguishing conclusively between these views requires longitudinal data, but these are difficult to obtain as they require decades of data collection from individuals. Here, a simple framework is proposed to assess in cross-sectional data whether in a given population the rate is 'highly individualistic' or rather 'uniform'. It is illustrated that an age-related decrease in the standard deviation (SD) of a certain parameter combined with a non-changing coefficient of variation (COVAR) reflects a 'uniform' rate of ageing, whilst an increase or decrease in COVAR with or without a concomitant increase in SD reflects a 'highly individualistic' rate of ageing. This framework is applied to some published data, focussing on muscle strength, power and physical function for the sake of illustration, and it is suggested that most studies do in fact show a 'highly individualistic' rate of ageing, perhaps apart from a 'uniform' rate of ageing in master athletes.

Comparing the Performance Gap Between Males and Females in the Older Age Groups in IRONMAN® 70.3: An Internet-Based Cross-Sectional Study of More Than 800,000 Race Records

BACKGROUND

The sex difference in the three split disciplines (swimming, cycling, and running) and overall race times in triathlon races has mainly been investigated for the Olympic distance and IRONMAN® triathlon formats, but not for the half IRONMAN® distance, i.e., the IRONMAN® 70.3. The aim of the present study was to investigate the sex differences in IRONMAN® 70.3 by age group in 5-year intervals for the split disciplines of this race. Data from 823,459 records (625,393 males and 198,066 females) of all age group finishers (in 5-year intervals) competing in all official IRONMAN® 70.3 races held worldwide between 2004 and 2020 were analyzed, and sex differences by age group and split disciplines were evaluated.

RESULTS

Males were faster than females in all split disciplines and all age groups. The sex difference was lower in swimming than in cycling and running and less pronounced for triathletes between 20 and 50 years of age. After the age of 60 years, females were able to reduce the sex difference to males in swimming and cycling, but not in running, where the reduction in the sex difference started after the age of 70 years. The lowest sex difference was in the age group 75 + years for swimming and cycling and in the age group 30-34 years for running. Across age groups, the sex difference was U-shaped in swimming and running, with an increase after 18-24 years in swimming and after 40-44 years in running. In contrast, the sex difference decreased continuously with the increasing age for cycling.

CONCLUSIONS

In conclusion, the study found that the sex difference in performance decreases with age in the IRONMAN® 70.3 race distance. However, females did not outperform males at older ages. Notably, sex differences were observed across different disciplines, with swimming displaying lower differences compared to cycling and running. These findings underscore the complex interplay between age, sex, and performance in endurance sports, emphasizing the need for additional research to understand the factors influencing these differences.

Emergence and Progression of Behavioral Motor Deficits and Skeletal Muscle Atrophy across the Adult Lifespan of the Rat

The facultative loss of muscle mass and function during aging (sarcopenia) poses a serious threat to our independence and health. When activities of daily living are impaired (clinical phase), it appears that the processes leading to sarcopenia have been ongoing in humans for decades (preclinical phase). Here, we examined the natural history of sarcopenia in male outbred rats to compare the occurrence of motor behavioral deficits with the degree of muscle wasting and to explore the muscle-associated processes of the preclinical and clinical phases, respectively. Selected metrics were validated in female rats. We used the soleus muscle because of its long duty cycles and its importance in postural control. Results show that gait and coordination remain intact through middle age (40-60% of median lifespan) when muscle mass is largely preserved relative to body weight. However, the muscle shows numerous signs of remodeling with a shift in myofiber-type composition toward type I. As fiber-type prevalence shifted, fiber-type clustering also increased. The number of hybrid fibers, myofibers with central nuclei, and fibers expressing embryonic myosin increased from being barely detectable to a significant number (5-10%) at late middle age. In parallel, TGFβ1, Smad3, FBXO32, and MuRF1 mRNAs increased. In early (25-month-old) and advanced (30-month-old) aging, gait and coordination deteriorate with the progressive loss of muscle mass. In late middle age and early aging due to type II atrophy (>50%) followed by type I atrophy (>50%), the number of myofibers did not correlate with this process. In advanced age, atrophy is accompanied by a decrease in SCs and βCatenin mRNA, whereas several previously upregulated transcripts were downregulated. The re-expression of embryonic myosin in myofibers and the upregulation of mRNAs encoding the γ-subunit of the nicotinic acetylcholine receptor, the neuronal cell adhesion molecule, and myogenin that begins in late middle age suggest that one mechanism driving sarcopenia is the disruption of neuromuscular connectivity. We conclude that sarcopenia in rats, as in humans, has a long preclinical phase in which muscle undergoes extensive remodeling to maintain muscle mass and function. At later time points, these adaptive mechanisms fail, and sarcopenia becomes clinically manifest.

Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races

Recent studies showed that female runners reduced the performance gap to male runners in endurance running with increasing age and race distance. However, the investigated samples were generally small. To investigate this further, the present study examined sex differences by age across various race distances (5, 10 km, half-marathon, marathon, and ultra-marathon) using a large dataset of over 1,100,000 race records from Switzerland over two decades (1999-2019). The study explored performance and participation disparities between male and female runners by employing diverse methods, such as descriptive statistics, histograms, scatter and line plots, correlations, and a predictive machine learning model. The results showed that female runners were more prevalent in shorter races (5, 10 km, half-marathon) and outnumbered male runners in 5 km races. However, as the race distance increased, the male-to-female ratio declined. Notably, the performance gap between sexes reduced with age until 70 years, after which it varied depending on the race distance. Among participants over 75 years old, ultra-marathon running exhibited the smallest sex difference in performance. Elderly female ultra-marathoners (75 years and older) displayed a performance difference of less than 4% compared to male ultra-marathoners, which may be attributed to the presence of highly selected outstanding female performers.

Effects of age, body height, body weight, body mass index and handgrip strength on the trajectory of the plantar pressure stance-phase curve of the gait cycle

The analysis of gait patterns and plantar pressure distributions via insoles is increasingly used to monitor patients and treatment progress, such as recovery after surgeries. Despite the popularity of pedography, also known as baropodography, characteristic effects of anthropometric and other individual parameters on the trajectory of the stance phase curve of the gait cycle have not been previously reported. We hypothesized characteristic changes of age, body height, body weight, body mass index and handgrip strength on the plantar pressure curve trajectory during gait in healthy participants. Thirty-seven healthy women and men with an average age of 43.65 ± 17.59 years were fitted with Moticon OpenGO insoles equipped with 16 pressure sensors each. Data were recorded at a frequency of 100 Hz during walking at 4 km/h on a level treadmill for 1 minute. Data were processed via a custom-made step detection algorithm. The loading and unloading slopes as well as force extrema-based parameters were computed and characteristic correlations with the targeted parameters were identified via multiple linear regression analysis. Age showed a negative correlation with the mean loading slope. Body height correlated with Fmean_load and the loading slope. Body weight and the body mass index correlated with all analyzed parameters, except the loading slope. In addition, handgrip strength correlated with changes in the second half of the stance phase and did not affect the first half, which is likely due to stronger kick-off. However, only up to 46% of the variability can be explained by age, body weight, height, body mass index and hand grip strength. Thus, further factors must affect the trajectory of the gait cycle curve that were not considered in the present analysis. In conclusion, all analyzed measures affect the trajectory of the stance phase curve. When analyzing insole data, it might be useful to correct for the factors that were identified by using the regression coefficients presented in this paper.

The Impact of Training on the Loss of Cardiorespiratory Fitness in Aging Masters Endurance Athletes

Elite masters endurance athletes are considered models of optimal healthy aging due to the maintenance of high cardiorespiratory fitness (CRF) until old age. Whereas a drop in VO2max in masters athletes has been broadly investigated, the modifying impact of training still remains a matter of debate. Longitudinal observations in masters endurance athletes demonstrated VO2max declines between -5% and -46% per decade that were closely related to changes in training volume. Here, using regression analyses, we show that 54% and 39% of the variance in observed VO2max decline in male and female athletes, respectively is explained by changes in training volume. An almost linear VO2max decrease was observed in studies on young and older athletes, as well as non-athletes, starting a few days after training cessation, with a decline of as much as -20% after 12 weeks. Besides a decline in stroke volume and cardiac output, training cessation was accompanied by considerable reductions in citrate synthase and succinate dehydrogenase activity (reduction in mitochondrial content and oxidative capacity). This reduction could largely be rescued within similar time periods of training (re)uptake. It is evident that training reduction or cessation leads to a considerably accelerated VO2max drop, as compared to the gradual aging-related VO2max decline, which can rapidly nullify many of the benefits of preceding long-term training efforts.

Acceleration of Longitudinal Track and Field Performance Declines in Athletes Who Still Compete at the Age of 100 Years

While physical performance decline rates accelerate after around the age of 70 years, longitudinal athletic performance trends in athletes older than 95 years are unknown. We hypothesized a further accelerated decline in human performance in athletes who still perform at the age of 100 years. To investigate this, longitudinal data of all athletes with results at or over the age of 100 years were collected from the “World Master Rankings” data base spanning 2006–2019 (138 results from 42 athletes; 5 women, 37 men; maximum 105 years) and compared to previously published longitudinal data from 80- to 96-year-old athletes from Sweden (1,134 results from 374 athletes). Regression statistics were used to compare performance decline rates between disciplines and age groups. On average, the individual decline rate of the centenarian group was 2.53 times as steep (100 m: 8.22x; long jump: 0.82x; shot put: 1.61x; discus throw: 1.04x; javelin throw: 0.98x) as that seen in non-centenarians. The steepest increase in decline was found in the 100-m sprint (t-test: p < 0.05, no sign. difference in the other disciplines). The pooled regression statistics of the centenarians are: 100 m: R = 0.57, p = 0.004; long jump: R = 0.90, p < 0.001; shot put: R = 0.65, p < 0.001; discus throw: R = 0.73, p < 0.001; javelin throw: R = 0.68, p < 0.001. This first longitudinal dataset of performance decline rates of athletes who still compete at 100 years and older in five athletics disciplines shows that there is no performance plateau after the age of 90, but rather a further acceleration of the performance decline.

Learning from machine learning: prediction of age-related athletic performance decline trajectories

Factors that determine individual age-related decline rates in physical performance are poorly understood and prediction poses a challenge. Linear and quadratic regression models are usually applied, but often show high prediction errors for individual athletes. Machine learning approaches may deliver more accurate predictions and help to identify factors that determine performance decline rates. We hypothesized that it is possible to predict the performance development of a master athlete from a single measurement, that prediction by a machine learning approach is superior to prediction by the average decline curve or an individually shifted decline curve, and that athletes with a higher starting performance show a slower performance decline than those with a lower performance. The machine learning approach was implemented using a multilayer neuronal network. Results showed that performance prediction from a single measurement is possible and that the prediction by a machine learning approach was superior to the other models. The estimated performance decline rate was highest in athletes with a high starting performance and a low starting age, as well as in those with a low starting performance and high starting age, while the lowest decline rate was found for athletes with a high starting performance and a high starting age. Machine learning was superior and predicted trajectories with significantly lower prediction errors compared to conventional approaches. New insights into factors determining decline trajectories were identified by visualization of the model outputs. Machine learning models may be useful in revealing unknown factors that determine the age-related performance decline.

Sarcopenia: What Is the Origin of This Aging-Induced Disorder?

We here review the loss of muscle function and mass (sarcopenia) in the framework of human healthspan and lifespan, and mechanisms involved in aging. The rapidly changing composition of the human population will impact the incidence and the prevalence of aging-induced disorders such as sarcopenia and, henceforth, efforts to narrow the gap between healthspan and lifespan should have top priority. There are substantial knowledge gaps in our understanding of aging. Heritability is estimated to account for only 25% of lifespan length. However, as we push the expected lifespan at birth toward those that we consider long-lived, the genetics of aging may become increasingly important. Linkage studies of genetic polymorphisms to both the susceptibility and aggressiveness of sarcopenia are still missing. Such information is needed to shed light on the large variability in clinical outcomes between individuals and why some respond to interventions while others do not. We here make a case for the concept that sarcopenia has a neurogenic origin and that in manifest sarcopenia, nerve and myofibers enter into a vicious cycle that will escalate the disease progression. We point to gaps in knowledge, for example the crosstalk between the motor axon, terminal Schwann cell, and myofiber in the denervation processes that leads to a loss of motor units and muscle weakness. Further, we argue that the operational definition of sarcopenia should be complemented with dynamic metrics that, along with validated biomarkers, may facilitate early preclinical diagnosis of individuals vulnerable to develop advanced sarcopenia. We argue that preventive measures are likely to be more effective to counter act aging-induced disorders than efforts to treat manifest clinical conditions. To achieve compliance with a prescription of preventive measures that may be life-long, we need to identify reliable predictors to design rational and convincing interventions.

Current Insights in the Age-related Decline in Sports Performance of the Older Athlete

The higher performance level of master athletes compared to non-athletes is often associated with better health throughout life. However, even the physical performance of master athletes declines with age, and this decline accelerates from about the age of 70 years onwards. A progressive loss of muscle mass, declines in force- and power-generating capacity, decreased flexibility, and the concomitant decline in specific tension characterize the muscular changes underlying performance declines. In the cardiovascular system, declines in stroke volume and cardiac output, and cardiac and vascular stiffness contribute to decreasing performance. Recent studies have shown that long-term endurance exercise in master athletes does not only have positive effects, but is associated with an increased incidence of atrial fibrillation, atherosclerotic plaques, and aortic dilation, and even more so in men than in women. Recently, larger longitudinal datasets were analysed and showed that the age-related decline in performance was similar in longitudinal and cross-sectional data. In conclusion, regular physical activity enhances the exercise capacity, and hence quality of life in old age, but it is not without risks.

Longitudinal Master Track and Field Performance Decline Rates Are Lower and Performance Is Better Compared to Athletes Competing Only Once

In master athletics research, cross-sectional data are easier to obtain than longitudinal data. While cross-sectional data give the age-related performance decline for a population, longitudinal data show individual trajectories. It is not known whether athletes who repeatedly compete have (a) a better performance and (b) a slower age-related decline in performance than that obtained from cross-sectional data from athletes competing only once. To investigate this, we analyzed 33 254 results of 14 118 male athletes from 8 disciplines in the database of "Swedish Veteran Athletics." For each discipline and for the pooled data of all disciplines, quadratic models of the evolution of performance over time were analyzed by ANCOVA/ANOCOVA using MATLAB. The performance was higher in athletes with 2 or more data points compared to those with only n = 1 (p < .001), with further increases in performance with an increasing number of data points per athlete. The estimated performance decline was lower in people with 2 or more results (sprint, 10 km, jumps; p < .001). In conclusion, we showed that longitudinal data are associated with higher performance and lower performance decline rates.