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

The aim of the present study was to examine the age-related di erences in performance and pacing in a half-marathon compared to a marathon. All nishers (n=9137) in the Ljubljana 2017 half-marathon (n=7258) and marathon (n=1853) with available data on split times during the races, were analysed for pacing. Half-marathoners were slower than marathoners among women, (2.77 0.35 versus 2.86 0.39 m s 1 respectively,p<0.001), but faster among men (3.14 0.45 versus 3.08 0.46 m s 1 respectively,p<0.001). In both race distances, the<25 age group was the fastest and the>54 age group the slowest (p<0.001). All age groups presented a positive pacing in both race distances and genders, with each segment being slower than the previous one. However, an end spurt was observed in the marathon, but not in the half-marathon. A more even pace in the half-marathon than in the marathon was shown for most age groups. In summary, age-group nishers in the half-marathon decreased running speed across the race, presented a more even pacing than marathoners, and did not show an end spurt. Keywords:aging; endurance; gender; master athlete; performance 1. Introduction Endurance exercise has been shown to play a bene cial role for health, e.g., it has been suggested that it reduces the risk of cardiovascular disease, stroke, diabetes, several cancers, depression, and falls [1]. This bene cial role of endurance exercise might explain the increased participation, especially of older age groups, in endurance races [2,3], and the

performance 1. Introduction Endurance exercise has been shown to play a bene cial role for health, e.g., it has been suggested that it reduces the risk of cardiovascular disease, stroke, diabetes, several cancers, depression, and falls [1]. This bene cial role of endurance exercise might explain the increased participation, especially of older age groups, in endurance races [2,3], and the increased scienti c interest in studying participation and performance characteristics of master athletes [4]. Considering endurance running races, the half-marathon has been a race distance of increasing popularity. For instance, the number of nishers in the half-marathon in Switzerland increased from the year 2000 to 2010, by 299% in women and 231% in men [3]. Compared to the marathon, the number of annual races and nishers in the USA in the half-marathon was three and four times higher, respectively. [5]. So far, several aspects of the half-marathon have been studied, e.g., rates of participation, trends in performance, gender di erences [6], perception of e ort [7], heart rate response [8], biomechanics [9], and pacing of recreational [10] and elite runners [11]. However, no information was available on the pacing of age groups of half-marathon runners. Such information would be of great practical interest, since half-marathon runners compete usually in ve-year age groups [3]. The variation of pacing by age group has been well-studied in marathon runners [12–17]. Older runners adopted a more even pacing (de ned as the quotient of the speed in the last 9.7 km Int. J. Environ. Res. Public Health2019,16, 1777; doi:10.3390 /ijerph16101777 /journal/ijerph

Int. J. Environ. Res. Public Health2019,16, 1777 2 of 10 divided by the rst 32.5 km) in a Midwestern USA marathon [12]. The relationship of pacing (considered either as the percentage di erence between the fastest and slowest split, or as the percentage change of speed in consecutive splits) with age was also identi ed in two analyses of the New York City marathon, showing a more even pacing in the older runners [13,14]. This trend was also observed in the Chicago marathon [17], 14 USA marathons [16], and in a recent study in the Athens marathon [15]. The above-mentioned studies have indicated that the older runners presented less variation in their speed compared to their younger counterparts, as well as that women had more even pacing than men. Although these studies [12–15] have improved our understanding of age- and gender-related di erences in pacing in endurance running, they were conducted in marathons and their ndings might not be “transferred” to the half-marathon. Compared to the marathon, the half-marathon has been a more “massive” sport event [5], presenting slower race speed [18] and inducing smaller muscle fatigue, muscle ber damage, perceived muscle pain [19], and in ammation [20]. Since it has been suggested that age-related decrease in performance is dependent on race duration [21,22], it would be reasonable to assume that age-related di erences in pacing might also vary by race distance. The knowledge about potential di erences among age groups would be of great practical value for the sports medicine team (e.g., tness trainers, exercise physiologist, coach) working with master endurance runners. Therefore, the aim of the present study was to examine age-related di erences in performance and pacing in the half-marathon and the marathon. 2. Materials and Methods 2.1. Participants and Data Acquisition This study was approved by the Institutional Review Board of Kanton St. Gallen, Switzerland, with a waiver of the requirement for informed consent of the participants as the study involved the analysis of publicly available data. The study was conducted in accordance with recognized ethical standards, according to the Declaration of Helsinki adopted in 1964

2.1. Participants and Data Acquisition This study was approved by the Institutional Review Board of Kanton St. Gallen, Switzerland, with a waiver of the requirement for informed consent of the participants as the study involved the analysis of publicly available data. The study was conducted in accordance with recognized ethical standards, according to the Declaration of Helsinki adopted in 1964 and revised in 2013. For the purpose of this study, we have included o cial results and split times from the publicly available “Ljubljana Marathon” website (http: //vw-ljubljanskimaraton.si). Participants who did not nish the race, or did not have a record of any of the split times were excluded from the study. Finally, 1853 nishers of the 2017 Ljubljana marathon, and 7258 nishers of the 2017 Ljubljana half-marathon (total 9137 nishers) were included in this study. We chose the “Ljubljana Marathon” in particular, since both the marathon and the half-marathon were held on the same day and on the same track, thus eliminating the potential in uence of the environmental conditions. Moreover, the half marathon race was entirely contained within the marathon race. Both the marathon and the half-marathon were considered at, with the elevation di erence of only 29 m (ranging from 295 m to 324 m). For comparison, the Berlin marathon has an ascent of 21 m and a course record for men of 2:01:39, h:min:s, set in 2018 by Eliud Kipchoge [23], and the New York City marathon has a total ascent of 390 m with a course record of 2:05:06, h:min:s, set in 2011 by Geo rey Kiprono Mutai [24]. The temperature ranged from 4.2 C to 15.4 C on the race day, without excess humidity or strong wind. 2.2. Data Analysis In the rst step of data analysis, we have calculated the mean speed for the entire race for each participant in the half-marathon and the marathon. Additionally, we have calculated the mean running speed in ve race segments, for both the marathon and the half-marathon [10] that correspond to: Segment 1—Mean running speed from 0–23.7% of the race (0–5 km for the half-marathon and

of data analysis, we have calculated the mean speed for the entire race for each participant in the half-marathon and the marathon. Additionally, we have calculated the mean running speed in ve race segments, for both the marathon and the half-marathon [10] that correspond to: Segment 1—Mean running speed from 0–23.7% of the race (0–5 km for the half-marathon and 0–10 km for the marathon) Segment 2—Mean running speed from 23.7–47.4% of the race (5–10 km for the half–marathon and 10–20 km for the marathon)

Int. J. Environ. Res. Public Health2019,16, 1777 3 of 10 Segment 3—Mean running speed from 47.4–71.1% of the race (10–15 km for the half–marathon and 20–30 km for the marathon) Segment 4—Mean running speed from 71.1–94.8% of the race (15–20 km for the half–marathon and 30–40 km for the marathon) Segment 5—Mean running speed from 94.8–100% of the race (20–21.0975 km for the half- marathon and 40–42.195 km for the marathon) Mean race speed—Mean running race speed 0–100% (0–21.0975 km for the half–marathon and 0–42.195 km for the marathon) The aforementioned segments were subsequently expressed as a percentage faster or slower than the mean segment speed. The fastest segment for each individual was then named the “positive range,” (PR), while the slowest segment was named the “negative range” (NR). The absolute sum of the positive range and negative range was then calculated and named the “pace range”. This allowed for normalized speed comparisons between all athletes, as well as between the marathon and the half-marathon. Finally, to examine the nal 2.195 km for the marathon and 1.0975 km for the half-marathon, the end spurt was de ned as when the speed at segment 5 was faster than that at segment 4. 2.3. Statistical Analysis To test di erences in the pace range between marathon and half-marathon runners in eight age groups, two two-way analyses of variance (ANOVA) were performed (separately for men and women). Main e ects of race (marathon and half-marathon), age group (<24; 25–29; 30–34; 35–39; 40–44; 45–49; 50–54; 55+), and their interaction (race age group) were performed. An additional two two-way analyses of variance (ANOVA) were performed (separately for men and women) to test di erences in pacing between marathon and half-marathon runners in nine age groups. Main e ects of race (marathon and half-marathon), age group (<24; 25–29; 30–34; 35–39; 40–44; 45–49; 50–54; 55+), and their interaction (race age group) were performed. For all ANOVAs, a Bonferroni post-hoc test was performed. E ect size was presented via eta squared ( 2), where the values of 0.01, 0.06, and above 0.14 were considered small, medium, and large,

Main e ects of race (marathon and half-marathon), age group (<24; 25–29; 30–34; 35–39; 40–44; 45–49; 50–54; 55+), and their interaction (race age group) were performed. For all ANOVAs, a Bonferroni post-hoc test was performed. E ect size was presented via eta squared ( 2), where the values of 0.01, 0.06, and above 0.14 were considered small, medium, and large, respectively [25]. The men-to-women ratio (MWR) was calculated as the quotient of men divided by women nishers, and was used to describe the variation of gender participation by race distance and age group. A chi-square ( 2) examined the association of gender with race distance and age group, and Cramer's phi (') evaluated the magnitude of these associations. Alpha level was set atp<0.05. All statistical tests were performed using Microsoft O ce Excel 2007 (Microsoft Corporation, Redmond, WA, USA) and SPSS 20 (IBM, Armonk, NY, USA). 3. Results 3.1. Participation by Gender, Race Distance, and Age Group The number of men and women in each race distance and age group are presented in Table. The total MWR of nishers in both race distances was 1.82. A gender race distance association on participation was observed ( 2=234.37,p<0.001,'=0.16), with the MWR being higher in the marathon (3.94) than in the half-marathon (1.54). In the half-marathon, a gender age group association in participation was shown ( 2=41.66,p<0.001,'=0.08), with the largest MWR being in the>54 age group (2.42) and the lowest in the age group 25–29 years (1.32). In the marathon, a gender age group association in participation was found ( 2=29.98,p<0.001,'=0.13) with the largest MWR being in the age group>54 years (14.42) and the lowest in the age group<25 years (2.35).

Int. J. Environ. Res. Public Health2019,16, 1777 4 of 10 Table 1.Distribution of men and women in each race and age group. Age Groups Men Women Marathon Half-Marathon Total Marathon Half-Marathon Total <25 47 268 315 20 199 219 25–29 99 433 532 28 329 357 30–34 179 589 768 53 393 446 35–39 292 753 1045 68 504 572 40–44 297 785 1082 84 540 624 45–49 231 646 877 71 436 507 50–54 160 441 601 39 248 287 >54 173 491 664 12 203 215 Total 1478 4406 5884 375 2852 3227 3.2. Running Speed by Gender and Race Distance A small main e ect of gender on running speed was observed (p<0.001, 2=0.052), with men (3.12 0.45 m s 1 ) being faster than women (2.78 0.36 m s 1 ) by 12.2% (Figure). No main e ect of race distance on running speed was shown (p=0.348, 2<0.001). A trivial gender race distance interaction on race speed was found (p<0.001, 2=0.004), with gender di erence being higher in the half-marathon (+13.4%) than in the marathon (+7.6%). Half-marathoners were slower than marathoners among women (2.77 0.35 versus 2.86 0.39 m s 1 respectively,p<0.001), but faster among men (3.14 0.45 versus 3.08 0.46 m s 1 respectively,p<0.001).Int. J. Environ. Res. Public Health 2019, 16, x 4 of 10 Table 1. Distribution of men and women in each race and age group. Age Groups Men Women Marathon Half-Marathon Total Marathon Half-Marathon Total <25 47 268 315 20 199 219 25–29 99 433 532 28 329 357 30–34 179 589 768 53 393 446 35–39 292 753 1045 68 504 572 40–44 297 785 1082 84 540 624 45–49 231 646 877 71 436 507 50–54 160 441 601 39 248 287 >54 173 491 664 12 203 215 Total 1478 4406 5884 375 2852 3227 3.2. Running Speed by Gender and Race Distance A small main effect of gender on running speed was observed (p < 0.001, η 2 = 0.052), with men (3.12 ± 0.45 m·s −1 ) being faster than women (2.78 ± 0.36 m·s −1 )

248 287 >54 173 491 664 12 203 215 Total 1478 4406 5884 375 2852 3227 3.2. Running Speed by Gender and Race Distance A small main effect of gender on running speed was observed (p < 0.001, η 2 = 0.052), with men (3.12 ± 0.45 m·s −1 ) being faster than women (2.78 ± 0.36 m·s −1 ) by 12.2% (Figure 1). No main effect of race distance on running speed was shown (p = 0.348, η 2 < 0.001). A trivial gender × race distance interaction on race speed was found (p < 0.001, η 2 = 0.004), with gender difference being higher in the half-marathon (+13.4%) than in the marathon (+7.6%). Half-marathoners were slower than marathoners among women (2.77 ± 0.35 versus 2.86 ± 0.39 m·s −1 respectively, p < 0.001), but faster among men (3.14 ± 0.45 versus 3.08 ± 0.46 m·s −1 respectively, p < 0.001). Figure 1. Race speed by race distance, gender, and age group. Error bars represent standard deviations, * p < 0.05; ‡ p < 0.001. 3.3. Age by Gender and Race Distance A trivial main effect of gender on age was observed (p < 0.001, η 2 = 0.003), with men (41.2 ± 10.7 years) being older than women (39.5 ± 10.0 years) by 4.2%. A trivial main effect of race distance on age was shown (p = 0.004, η 2 = 0.001), with marathon runners (41.7 ± 9.8 years) being older than their half-marathon peers (40.3 ± 10.7 years) by 3.5%. No gender × race distance interaction on age was found (p = 0.268, η 2 < 0.001). Marathon runners were older than half-marathon runners in men (p < 0.001), but not in women (p = 0.297). Figure 1. Race speed by race distance, gender, and age group. Error bars represent standard deviations, *p<0.05; z p<0.001. 3.3. Age by Gender and Race Distance A trivial main effect of gender on age was observed (p<0.001, 2=0.003), with men(41.2 10.7 years) being older than women (39.5 10.0 years) by 4.2%. A trivial main e ect of race distance on age

1. Race speed by race distance, gender, and age group. Error bars represent standard deviations, *p<0.05; z p<0.001. 3.3. Age by Gender and Race Distance A trivial main effect of gender on age was observed (p<0.001, 2=0.003), with men(41.2 10.7 years) being older than women (39.5 10.0 years) by 4.2%. A trivial main e ect of race distance on age was shown (p=0.004, 2=0.001), with marathon runners (41.7 9.8 years) being older than their half-marathon peers (40.3 10.7 years) by 3.5%. No gender race distance interaction on age was found (p=0.268, 2<0.001). Marathon runners were older than half-marathon runners in men (p<0.001), but not in women (p=0.297). 3.4. Race Speed by Age Group In the half-marathon, a small main e ect of age group on running speed (p<0.001, 2=0.018) was observed for all nishers, with the age group<25 years being the fastest (3.08 0.48 m s 1 ), and the age group>54 years being the slowest (2.89 0.42 m s 1 ). The gender di erence ranged from+12.2% (age

Int. J. Environ. Res. Public Health2019,16, 1777 5 of 10 group 30–34 years) to+15.7% (age group 25–29 years), however, no gender age group interaction on running speed was shown (p=0.112, 2=0.002). In the marathon, a small main e ect of age group on running speed (p<0.001, 2=0.023) was found for all nishers, with the age group<25 years being the fastest (3.19 0.68 m s 1 ), and the age group>54 years being the slowest(2.87 0.37 m s 1 ) . The gender di erence ranged from+3.3% (age group>55 years) to+11.4% (age group 45–49 years). Nevertheless, no gender age group interaction on running speed was observed (p=0.525, 2 =0.003). A small main e ect of age group on running speed was observed in women half-marathon runners (p<0.001, 2=0.022), with the age group<25 years being the fastest (2.83 0.36 m s 1 ), and the age group>54 years being the slowest (2.63 0.36 m s 1 ). A main e ect of age group on running speed was also shown in men half-marathon runners (p<0.001, 2=0.023), with the age group<25 years being the fastest (3.25 0.47 m s 1 ), and the age group>54 years being the slowest(2.99 0.40 m s 1 ) . A moderate main e ect of age group on running speed was found in women marathon runners (p<0.001, 2 =0.075), with the age group 25–29 years being the fastest (3.10 0.60 m s 1 ), and the age group 50–54 years being the slowest (2.74 0.29 m s 1 ). A main e ect of age group on running speed was also observed in men marathon runners (p<0.001, 2=0.039), with the age group<25 years being the fastest (3.23 0.70 m s 1 ), and the age group>54 years being the slowest (2.88 0.37 m s 1 ). 3.5. Running Speed by Segment The average running speeds for four segments, as well as end spurt, are presented in Table. From the descriptive data in Table, we can observe a gradual decrease in average speed through the race segments for both genders, in both the marathon and the half-marathon, and

being the slowest (2.88 0.37 m s 1 ). 3.5. Running Speed by Segment The average running speeds for four segments, as well as end spurt, are presented in Table. From the descriptive data in Table, we can observe a gradual decrease in average speed through the race segments for both genders, in both the marathon and the half-marathon, and for all age groups with a characteristic end spurt. Moreover, we can observe the absence of an end spurt in half-marathon runners. When pace range in men runners was observed, results showed signi cant main e ects of race (smaller pace range in half-marathon than marathon, 2=0.12,p<0.01), age group ( 2<0.01,p<0.01), and race age group interaction ( 2<0.01,p<0.01). Within each race distance, a main e ect of age group on pacing was observed for the half-marathon (p=0.022, 2=0.004) and for the marathon (p=0.031, 2 =0.010), however, post-hoc comparisons did not reveal any signi cant di erence. When pace range in women runners was considered, the results showed signi cant main e ects of race (smaller pace range in the half-marathon than the marathon, 2=0.02,p<0.01), and age group ( 2=0.01,p=0.01). A signi cant main e ect of the race age group interaction was not obtained ( 2<0.01,p=0.07). Within each race distance, a main e ect of age group on pacing was shown in the half-marathon (p<0.001, 2=0.015), but not in the marathon (p=0.357, 2=0.021). In the half-marathon, the age group 30–34 years had less pace range than the age group<25 years ( 2.1%), the age group 25–29 years ( 1.9%), the age group 50–54 years ( 2.4%), and the age group>54 years ( 3.2%). The age group>54 years had a larger pace range than the age group 35–39 years (+1.8%), the age group 40–44 years (+2.2%), and the age group 45–49 years (+1.8%). With regards to the appearance of an end spurt (i.e., faster at segment 5 than at segment 4), an end spurt race distance association was observed ( 2=1065.2,p<0.001,'=0.342), with more marathon runners (71.1%) showing an end spurt than half-marathon runners (29.8%) (Figure). In the half-marathon, an end spurt

This study analyzes performance and pacing differences among age groups in half-marathon and marathon events.