Physical training and personality factors as predictors of marathon time and training injury

Personality of marathon runners: a narrative review of recent findings

Participation in marathons has dramatically increased over the last few years. Marathon running has many proven beneficial effects, especially on cardiovascular health and fitness. Most research has focused on physiologic and pathophysiologic adaptations in connection with endurance exercise. Nevertheless, marathon running also has a major impact on psychological aspects and positively influences mental health, which has only recently attracted research interest. The present narrative review aimed to review the personality traits of marathon runners with an emphasis on recent literature. Marathon runners show a distinct personality and highly characteristic personality traits needed to successfully finish such a demanding race, i.e., a strong sense of vigor, self-sufficiency, and intelligence as well as low scores in anger, fatigue, tension, and depression. Furthermore, personality differences are detectable between runners of different sexes, ages, and performance level groups. This has significant clinical implications for athletes, coaches and competition organizers, as these groups show different patterns of personality traits. Future studies should focus on changes in cognition and mood states pre-, during, and post-endurance events, as well as during training periods. Large-scale studies comparing personality differences by sex, age, and performance are also important for better clinical guidance. See also the graphical abstract(Fig. 1).

Training and Racing Behavior of Recreational Runners by Race Distance-Results From the NURMI Study (Step 1)

The present study investigated pre-race preparation of a large sample of recreational runners competing in different race distances (e.g., shorter than half-marathon, half-marathon, marathon and ultra-marathon). An online questionnaire was used and a total of 3,835 participants completed the survey. Of those participants, 2,864 (75%) met the inclusion criteria and 1,628 (57%) women and 1,236 (43%) men remained after data clearance. Participants were categorized according to race distance in half-marathon (HM), and marathon/ultra-marathon (M/UM). Marathon and ultra-marathon data were pooled since the marathon distance is included in an ultra-marathon. The most important findings were (i) marathon and ultra-marathon runners were more likely to seek advice from a professional trainer, and (ii) spring was most commonly reported across all subgroups as the planned season for racing, (iii) training volume increased with increasing race distance, and (iv) male runners invested more time in training compared to female runners. In summary, runners competing in different race distances prepare differently for their planned race.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier ISRCTN73074080. Retrospectively registered 12th June 2015.

Skinfold Thickness Distribution in Recreational Marathon Runners

The relationship of body fat (BF) percentage with performance of elite marathon runners has been well studied; however, less information is available about the variation of skinfold thickness by sex and performance in non-elite marathon runners. The aim of the present study was to examine the variation of skinfold thickness by sex and performance in recreational marathon runners. Participants included 32 female (age 40.1 ± 9.0 years, BF 19.6 ± 4.7%, and training volume 47.7 ± 22.6 km) and 134 male marathon runners (44.3 ± 8.8 years, 17.6 ± 4.0%, and 53.0 ± 21.2 km, respectively). The largest skinfold thickness was the abdomen in both sexes, whereas the smallest was biceps in men, and chins in women (p < 0.001). The largest sex difference in skinfold thickness was observed in triceps being the fattest in women (p < 0.001). The largest difference in skinfold thickness among men’s performance groups was observed in the iliac crest, and the smallest in the patella and proximal calf (p < 0.001). In summary, skinfold measurements indicated that women had more fat in both their upper and lower limbs, while men had more fat in their trunk. With regards to the role of performance level, the slowest runners presented relatively more fat in the upper limbs and trunk anatomical sites, i.e., away from the active muscles of legs.

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

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

An evaluation of the training determinants of marathon performance: A meta-analysis with meta-regression

OBJECTIVES

Marathoners rely on expert-opinion and the anecdotal advice of their peers when devising their training plans for an upcoming race. The accumulation of results from multiple scientific studies has the potential to clarify the precise training requirements for the marathon. The purpose of the present study was to perform a systematic review, meta-analysis and meta-regression of available literature to determine if a dose-response relationship exists between a series of training behaviours and marathon performance.

DESIGN

Systematic review, meta-analysis and meta-regression.

METHODS

A systematic search of multiple literature sources was undertaken to identify observational and interventional studies of elite and recreational marathon (42.2km) runners.

RESULTS

Eighty-five studies which included 137 cohorts of runners (25% female) were included in the meta-regression, with average weekly running distance, number of weekly runs, maximum running distance completed in a single week, number of runs ≥32km completed in the pre-marathon training block, average running pace during training, distance of the longest run and hours of running per week used as covariates. Separately conducted univariate random effects meta-regression models identified a negative statistical association between each of the above listed training behaviours and marathon performance (R² 0.38-0.81, p<0.001), whereby increases in a given training parameter coincided with faster marathon finish times. Meta-analysis revealed the rate of non-finishers in the marathon was 7.27% (95% CI 6.09%-8.65%).

CONCLUSIONS

These data can be used by athletes and coaches to inform the development of marathon training regimes that are specific to a given target finish time.

Prediction Equations for Marathon Performance: A Systematic Review

PURPOSE

Despite the volume of available literature focusing on marathon running and the prediction of performance, no single prediction equations exists that is accurate for all runners of varying experiences and abilities. Indeed the relative merits and utility of the existing equations remain unclear. Thus, the aim of this study was to collate, characterize, compare, and contrast all available marathon prediction equations.

METHODS

A systematic review was conducted to identify observational research studies outlining any kind of prediction algorithm for marathon performance.

RESULTS

Thirty-six studies with 114 equations were identified. Sixty-one equations were based on training and anthropometric variables, whereas 53 equations included variables that required laboratory tests and equipment. The accuracy of these equations was denoted via a variety of metrics; r2 values were provided for 68 equations (r2 = .10-.99), and an SEE was provided for 19 equations (SEE 0.27-27.4 min).

CONCLUSION

Heterogeneity of the data precludes the identification of a single "best" equation. Important variables such as course gradient, sex, and expected weather conditions were often not included, and some widely used equations did not report the r2 value. Runners should therefore be wary of relying on a single equation to predict their performance.

A Brief Review of Personality in Marathon Runners: The Role of Sex, Age and Performance Level

The participation of recreational runners in sport events ranging from 5 km to ultra-endurance races have increased dramatically during the last decades and this phenomenon has attracted scientific interest. Most research has focused on the physiological characteristics of these runners and less in their psychological characteristics. Therefore, the aim of the present study was to review the existing knowledge with regards to the personality of recreational endurance runners and the role of sex, age and performance. It was concluded that limited information was available with regards to the personality of recreational marathon runners. So far, our knowledge on the personality of marathon runners relied on studies conducted a few decades ago, mostly on competitive marathon runners, highlighting the need for original research on recreational runners.

Risk and Protective Factors for Middle- and Long-Distance Running-Related Injury

BACKGROUND

Despite a rapidly growing body of research, a systematic evidence compilation of the risk and protective factors for middle- and long-distance running-related injury (RRI) was lacking.

OBJECTIVES

Our objective was to compile the evidence about modifiable and non-modifiable training-related and behavioral risk and protective factors for middle- and long-distance RRI.

METHODS

We searched five databases (PubMed, CINAHL, MEDLINE, SPORTDiscus, and PsycINFO) for the dates 1 January 1970 to 31 December 2015, inclusive, for original peer-reviewed articles. The eligible designs were cross-sectional, case-control, longitudinal observational studies, and randomized controlled trials involving runners competing at distances from ≥800 m to ≤42.2 km. Outcomes were any specific and/or general RRI, and exposures included training-related and behavioral factors. We extracted authors and date, study design, injury type(s), descriptors and comparators for each exposure, and results and measures of association from the selected studies. Methodological quality was independently appraised using two separate checklists: a modified checklist for observational study designs and the Physiotherapy Evidence Database (PEDro) scale for randomized controlled trials.

RESULTS

Among 73 articles eligible for inclusion, 19 (26.0%) and 30 (41.0%) were of high or satisfactory methodological quality, respectively. As a non-modifiable exposure, a history of previous injury was found to be associated with an increased risk of both general and specific RRI. In terms of modifiable exposures, irregular and/or absent menstruation was found to be associated with an increased risk of stress fracture development, whereas the use of oral contraceptives was found to be associated with a decreased risk. High clinical, methodological, and statistical heterogeneity meant it was not feasible to estimate a pooled effect size across similar studies.

CONCLUSIONS

A history of previous injury was associated with an increased risk of both general and specific RRI. The use of oral contraceptives was found to be associated with a decreased risk of skeletal stress fracture. Conversely, irregular and/or absent menstruation was associated with an increased risk. The varied effect directions and/or a number of statistically insignificant results associated with the majority of factors hindered our ability to draw any definitive conclusions about their relationship to RRI risk.

What are the Differences in Injury Proportions Between Different Populations of Runners? A Systematic Review and Meta-Analysis

BACKGROUND

Many runners suffer from injuries. No information on high-risk populations is available so far though.

OBJECTIVES

The aims of this study were to systematically review injury proportions in different populations of runners and to compare injury locations between these populations.

DATA SOURCES

An electronic search with no date restrictions was conducted up to February 2014 in the PubMed, Embase, SPORTDiscus and Web of Science databases. The search was limited to original articles written in English. The reference lists of the included articles were checked for potentially relevant studies.

STUDY ELIGIBILITY CRITERIA

Studies were eligible when the proportion of running injuries was reported and the participants belonged to one or more homogeneous populations of runners that were clearly described. Study selection was conducted by two independent reviewers, and disagreements were resolved in a consensus meeting.

STUDY APPRAISAL AND SYNTHESIS METHODS

Details of the study design, population of runners, sample size, injury definition, method of injury assessment, number of injuries and injury locations were extracted from the articles. The risk of bias was assessed with a scale consisting of eight items, which was specifically developed for studies focusing on musculoskeletal complaints.

RESULTS

A total of 86 articles were included in this review. Where possible, injury proportions were pooled for each identified population of runners, using a random-effects model. Injury proportions were affected by injury definitions and durations of follow-up. Large differences between populations existed. The number of medical-attention injuries during an event was small for most populations of runners, except for ultra-marathon runners, in which the pooled estimate was 65.6%. Time-loss injury proportions between different populations of runners ranged from 3.2% in cross-country runners to 84.9% in novice runners. Overall, the proportions were highest among short-distance track runners and ultra-marathon runners.

LIMITATIONS

The results were pooled by stratification of studies according to the population, injury definition and follow-up/recall period; however, heterogeneity was high.

CONCLUSIONS

Large differences in injury proportions between different populations of runners existed. Injury proportions were affected by the duration of follow-up. A U-shaped pattern between the running distance and the time-loss injury proportion seemed to exist. Future prospective studies of injury surveillance are highly recommended to take running exposure and censoring into account.

Distance running as an ideal domain for showing a sex difference in competitiveness

Men are over-represented in the arts, sciences, and sports. This has been hypothesized to reflect an evolved male predisposition for enduring competitiveness or long-term motivation to improve one's performance and "show-off." Evidence for this hypothesis is equivocal, however, because there are viable alternative explanations for men's dominance in most cultural display domains. Here, I argue that distance running is an ideal domain for addressing this issue. Distance running is ideal because it indicates enduring competitiveness, allows objective comparisons, and is accessible, acceptable, and popular for both men and women. I review recent studies and present new data showing that substantially more men than women run relatively fast in the U.S., that this sex difference in relative performance can be attributed, at least in part, to men's greater training motivation, and that this pattern has been stable for several decades. Distance running thus provides compelling evidence for an evolved male predisposition for enduring competitiveness. I conclude with suggestions regarding how variation in achievement motivation can be informed by considering how evolved predispositions interact with environmental and social conditions.

Comparison of anthropometric and training characteristics between recreational male marathoners and 24-hour ultramarathoners

Background

Of the anthropometry and training variables used to predict race performance in a 24-hour ultrarun, the personal best marathon time is the strongest predictor in recreational male 24-hour ultramarathoners. This finding raises the question of whether similarities exist between male recreational 24-hour ultramarathoners and male recreational marathoners.

Methods

The association between age, anthropometric variables (ie, body mass, body height, body mass index, percent body fat, skeletal muscle mass, limb circumference, and skinfold thickness at the pectoral, mid axillary, triceps, subscapular, abdominal, suprailiac, front thigh, and medial calf sites), previous experience and training characteristics (ie, volume, speed, and personal best time), and race time for 79 male recreational 24-hour ultramarathoners and 126 male recreational marathoners was investigated using bivariate and multivariate analysis.

Results

The 24-hour ultramarathoners were older (P < 0.05), had a lower circumference at both the upper arm (P < 0.05) and thigh (P < 0.01), and a lower skinfold thickness at the pectoral, axillary, and suprailiac sites (P < 0.05) compared with the marathoners. During training, the 24-hour ultramarathoners were running for more hours per week (P < 0.001) and completed more kilometers (P < 0.001), but were running slower (P < 0.01) compared with the marathoners. In the 24-hour ultramarathoners, neither anthropometric nor training variables were associated with kilometers completed in the race (P > 0.05). In the marathoners, percent body fat (P < 0.001) and running speed during training (P < 0.0001) were related to marathon race times.

Conclusion

In summary, differences in anthropometric and training predictor variables do exist between male recreational 24-hour ultramarathoners and male recreational marathoners for race performance.

Is body fat a predictor of race time in female long-distance inline skaters?

PURPOSE

The aim of this study was to evaluate predictor variables of race time in female ultra-endurance inliners in the longest inline race in Europe.

METHODS

We investigated the association between anthropometric and training characteristics and race time for 16 female ultra-endurance inline skaters, at the longest inline marathon in Europe, the 'Inline One-eleven' over 111 km in Switzerland, using bi- and multivariate analysis.

RESULTS

The mean (SD) race time was 289.7 (54.6) min. The bivariate analysis showed that body height (r=0.61), length of leg (r=0.61), number of weekly inline skating training sessions (r=-0.51) and duration of each training unit (r=0.61) were significantly correlated with race time. Stepwise multiple regressions revealed that body height, duration of each training unit, and age were the best variables to predict race time.

CONCLUSION

Race time in ultra-endurance inline races such as the 'Inline One-eleven' over 111 km might be predicted by the following equation (r(2)=0.65): Race time (min)=-691.62+521.71 (body height, m)+0.58 (duration of each training unit, min)+1.78 (age, yrs) for female ultra-endurance inline skaters.

Comparison between Recreational Male Ironman Triathletes and Marathon Runners

Recent investigations described a personal best marathon time as a predictor variable for an Ironman race time in recreational male Ironman triathletes. Similarities and differences in anthropometry and training were investigated between 83 recreational male Ironman triathletes and 81 recreational male marathoners. Ironman triathletes were significantly taller and had a higher body mass and a higher skin-fold thickness of the calf compared to the marathoners. Weekly training volume in hours was higher in Ironman triathletes. In the Ironman triathletes, percent body fat was related to overall race time and both the split time in cycling and running. The weekly swim kilometres were related to the split time in swimming, and the speed in cycling was related to the bike split time. For the marathoners, the calf skin-fold thickness and running speed during training were related to marathon race time. Although personal best marathon time was a predictor of Ironman race time in male triathletes, anthropometric and training characteristics of male marathoners were different from those of male Ironman triathletes, probably due to training of different muscle groups and metabolic endurance beyond marathon running, as the triathletes are also training for high-level performance in swimming and cycling. Future studies should compare Olympic distance triathletes and road cyclists with Ironman triathletes.

Similarities and differences in anthropometry and training between recreational male 100-km ultra-marathoners and marathoners

Several recent investigations showed that the best marathon time of an individual athlete is also a strong predictor variable for the race time in a 100-km ultra-marathon. We investigated similarities and differences in anthropometry and training characteristics between 166 100-km ultra-marathoners and 126 marathoners in recreational male athletes. The association of anthropometric variables and training characteristics with race time was assessed by using bi- and multi-variate analysis. Regarding anthropometry, the marathoners had a significantly lower calf circumference (P < 0.05) and a significantly thicker skinfold at pectoral (P < 0.01), axilla (P < 0.05), and suprailiacal sites (P < 0.05) compared to the ultra-marathoners. Considering training characteristics, the marathoners completed significantly fewer hours (P < 0.001) and significantly fewer kilometres (P < 0.001) during the week, but they were running significantly faster during training (P < 0.001). The multi-variate analysis showed that age (P < 0.0001), body mass (P = 0.011), and percent body fat (P = 0.019) were positively and weekly running kilometres (P < 0.0001) were negatively related to 100-km race times in the ultra-marathoners. In the marathoners, percent body fat (P = 0.002) was positively and speed in running training (P < 0.0001) was negatively associated with marathon race times. In conclusion, these data suggest that performance in both marathoners and 100-km ultra-marathoners is inversely related to body fat. Moreover, marathoners rely more on speed in running during training whereas ultra-marathoners rely on volume in running training.

Age, Training, and Previous Experience Predict Race Performance in Long-Distance Inline Skaters, Not Anthropometry

The association of characteristics of anthropometry, training, and previous experience with race time in 84 recreational, long-distance, inline skaters at the longest inline marathon in Europe (111 km), the Inline One-eleven in Switzerland, was investigated to identify predictor variables for performance. Age, duration per training unit, and personal best time were the only three variables related to race time in a multiple regression, while none of the 16 anthropometric variables were related. Anthropometric characteristics seem to be of no importance for a fast race time in a long-distance inline skating race in contrast to training volume and previous experience, when controlled with covariates. Improving performance in a long-distance inline skating race might be related to a high training volume and previous race experience. Also, doing such a race requires a parallel psychological effort, mental stamina, focus, and persistence. This may be reflected in the preparation and training for the event. Future studies should investigate what motivates these athletes to train and compete.

Personal best time and training volume, not anthropometry, is related to race performance in the 'Swiss Bike Masters' mountain bike ultramarathon

We investigated in 73 male ultraendurance mountain bikers, with (mean and SD) age 39.1 (8.6) years, weight 74.4 (8.3) kg, height 1.78 (0.07) m, and a body mass index of 23.3 (1.9) kg·m⁻², whether variables of anthropometry, training, or prerace experience were associated with race time using bi and multivariate analysis. Our investigation was conducted at the "Swiss Bike Masters," which covers a distance of 120 km and an altitude of 5,000 m. In the bivariate analysis, body mass index (r = 0.29), circumference of upper arm (r = 0.28), sum of upper body skinfolds (r = 0.38), sum of lower body skinfolds (r = 0.25), sum of 8 skinfolds (r = 0.36), percent body fat (r = 0.41), total cycling kilometers per year (r = -0.47), yearly volume in both mountain bike (r = -0.33) and road cycling (r = -0.52), number of training units per week (r = -0.48), distance per unit in road cycling (r = -0.33), average speed during training in road cycling (r = -0.33), and personal best time in the "Swiss Bike Masters"(r = 0.67) were related to race time. In the multiple linear regression analysis, personal best time in the "Swiss Bike Masters" (p = 0.000), total yearly cycling kilometers (p = 0.004), and yearly training kilometers in road cycling (p = 0.017) were related to race time. When the personal best time was the dependent variable in a separate regression model, total yearly cycling kilometers (p = 0.002) remained the single predictor variable. We concluded that finishing a particular mountain bike ultramarathon does not seem to require a special anthropometry but rather a specific skill and experience for this selective kind of race coupled with a high training volume. For practical use, we concluded that successful athletes in a mountain bike ultramarathon, in a special environment and using sophisticated equipment, need prerace experience coupled with high training volume, rather than any special anthropometry.

Race performance in male mountain ultra-marathoners: anthropometry or training?

The association of anthropometric variables, training volume, and prerace experience with race time was investigated in 25 male mountain ultra-marathoners (M age = 44.5 yr., SD = 7.0; M body mass = 73.0 kg, SD = 7.8; M body height = 1.78 m, SD = 0.07; M Body Mass Index = 22.9 kg/m2, SD = 1.8) in a 7-day mountain ultra-marathon over 350 km with a total 11,000 m of altitude gained and lost. The relationship of anthropometry (body mass, body height, Body Mass Index, percent body fat, circumferences of limbs, and thicknesses of skin-folds), training, and prerace experience (years as active runner, average training volume in hours and kilometres per week, average running speed in training, and personal best time in marathon running) with total race time was investigated using bivariate correlation analysis. None of the variables of anthropometry were related to total race time. Average speed in running during training and personal best time in marathon running were associated with total race time. Speed in running during training was correlated with personal best time in marathon running. The finding that average speed in running during training and personal best marathon time were related to race performance suggests that training and especially intensity might be of increased importance in these ultra-runners compared to anthropometry.

The prevention of shin splints in sports: a systematic review of literature

PURPOSE

To review the published and unpublished evidence regarding risk factors associated with shin splints, assess the effectiveness of prevention strategies, and offer evidence-based recommendations to coaches, athletes, and researchers.

METHODS

We searched electronic data bases without language restriction, identified citations from reference sections of research papers retrieved, contacted experts in the field, and searched the Cochrane Collaboration. Of the 199 citations identified, we emphasized results of the four reports that compared methods to prevent shin splints. We assessed the methodologic quality of these reports by using a standardized instrument.

RESULTS

The use of shock-absorbent insoles, foam heel pads, heel cord stretching, alternative footwear, as well as graduated running programs among military recruits have undergone assessment in controlled trials. There is no strong support for any of these interventions, and each of the four controlled trials is limited methodologically. Median quality scores in these four studies ranged from 29 to 47, and serious flaws in study design, control of bias, and statistical methods were identified.

CONCLUSION

Our review yielded little objective evidence to support widespread use of any existing interventions to prevent shin splints. The most encouraging evidence for effective prevention of shin splints involves the use of shock-absorbing insoles. However, serious flaws in study design and implementation constrain the work in this field thus far. A rigorously implemented research program is critically needed to address this common sports medicine problem.

The influence of psychological factors on sports injuries. Review of the literature

The influence of psychological factors on sports injuries has been demonstrated in numerous empirical studies. Almost all investigations have been based on stress theory or a personality-profile approach. Although the majority of studies have employed different methods, the results are in general agreement that "life events" can influence the risk of injury in athletes. In this context, social support appears to have a buffering effect. According to existing results, the influence of stress-coping strategies is somewhat questionable. From the numerous psychological attributes that have been investigated in relation to sports injuries, only competitive anxiety has been shown to be associated with injury occurrence. A personality profile typical of the "injury-prone" athlete does not exist. However, several studies have shown a certain readiness to take risks (lack of caution, adventurous spirit) on the part of injured athletes. In this review, the current knowledge regarding the relationship between psychological factors and sports injuries is presented and a stress theory model is developed.

Prescribed and self-reported seasonal training of distance runners

A survey of 123 distance-running coaches and their best runners was undertaken to describe prescribed seasonal training and its relationship to the performance and self-reported training of the runners. The runners were 43 females and 80 males, aged 24 +/- 8 years (mean +/- S.D.), training for events from 800 m to the marathon, with seasonal best paces of 86 +/- 6% of sex- and age-group world records. The coaches and runners completed a questionnaire on typical weekly volumes of interval and strength training, and typical weekly volumes and paces of moderate and hard continuous running, for build-up, pre-competition, competition and post-competition phases of a season. Prescribed training decreased in volume and increased in intensity from the build-up through to the competition phase, and had similarities with 'long slow distance' training. Coaches of the faster runners prescribed longer build-ups, greater volumes of moderate continuous running and slower relative paces of continuous running (r = 0.19-0.36, P < 0.05), suggesting beneficial effects of not training close to competition pace. The mean training volumes and paces prescribed by the coaches were similar to those reported by the runners, but the correlations between prescribed and reported training were poor (r = 0.2-0.6). Coaches may therefore need to monitor their runners' training more closely.

On the epidemiology of running injuries. The 1984 Bern Grand-Prix study

Using a survey questionnaire design, we investigated the incidence, site, and nature of jogging injuries among all participants of a popular 16 km race. The response rate was 83.6%. Of 4,358 male joggers, 45.8% had sustained jogging injuries during the 1 year study period, 14.2% had required medical care, and 2.3% had missed work because of jogging injuries. Occurrence of jogging injuries was independently associated with higher weekly mileage (P less than 0.001), history of previous running injuries (P less than 0.001), and competitive training motivation (P = 0.03). Higher mileage was also associated with more frequent medical consultations due entirely to jogging-related injuries. In 33 to 44 year olds (N = 1,757), the number of years of running was inversely related to incidence of injuries (P = 0.02). Injuries were not significantly related to race running speed, training surface, characteristics of running shoes, or relative weight. Achillodynia and calf muscle symptoms were the two most common overuse injuries and occurred significantly more often among older runners with increased weekly mileage. We conclude that jogging injuries are frequent, that the number of firmly established etiologic factors is low, and that, in recommending jogging, moderation should be the watchword.