Citation: Motevalli, M.; Tanous, D.;
Wirnitzer, G.; Leitzmann, C.;
Rosemann, T.; Knechtle, B.; Wirnitzer,
K. Sex Differences in Racing History
of Recreational 10 km to Ultra
Runners (Part B)—Results from the
NURMI Study (Step 2). Int. J. Environ.
Res. Public Health 2022, 19, 13291.
https://doi.org/10.3390/
ijerph192013291
Academic Editors: Stacy T. Sims and
Christopher T. Minson
Received: 18 August 2022
Accepted: 11 October 2022
Published: 14 October 2022
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International  Journal  of
Environmental Research
and Public Health
Article
Sex Differences in Racing History of Recreational 10 km to Ultra
Runners (Part B)—Results from the NURMI Study (Step 2)
Mohamad Motevalli 1,2
, Derrick Tanous 1,2
, Gerold Wirnitzer 3, Claus Leitzmann 4, Thomas Rosemann 5
,
Beat Knechtle 5,6,*
and Katharina Wirnitzer 1,2,7
1
Department of Sport Science, Leopold-Franzens University of Innsbruck, 6020 Innsbruck, Austria
2
Department of Research and Development in Teacher Education, University College of Teacher Education,
Tyrol, 6010 Innsbruck, Austria
3
adventureV & change2V, 6135 Stans, Austria
4
Institute of Nutrition, University of Gießen, 35390 Gießen, Germany
5
Institute of Primary Care, University of Zurich, 8000 Zurich, Switzerland
6
Medbase St. Gallen Am Vadianplatz, 9000 St. Gallen, Switzerland
7
Research Center Medical Humanities, Leopold-Franzens University of Innsbruck, 6020 Innsbruck, Austria
*
Correspondence: beat.knechtle@hispeed.ch
Abstract: Sex differences in anatomy and physiology are the primary underlying factor for dis-
tinctions in running performance. Overall participation in recreational running events has been
dominated by males, although increasing female participation has been reported in recent years.
The NURMI study participants ﬁlled in a survey following the cross-sectional study design with
questions on sociodemographic data, running and racing motivations, training behaviors, and racing
history and experience. Data analysis included 141 female and 104 male participants aged 39 (IQR
17) with a healthy median BMI (21.7 kg/m2; IQR 3.5). Statistical analyses revealed sex differences
with the males performing faster at half-marathon (p < 0.001) and marathon (p < 0.001) events but no
difference at ultra-marathons (p = 0.760). Mediation analyses revealed no signiﬁcant sex differences
in the performance of half-marathon and marathon when considering training behaviors (p > 0.05),
racing history (p > 0.05), or racing experience (p > 0.05). Differences in recreational performance may
be more closely related to social constraints and expectations of females rather than the physiological
advantages of the male athlete. Health professionals who guide and support recreational runners
as well as the runners themselves and their coaches may beneﬁt from this study’s results in order
to improve the best time performance through a deeper understanding of the areas that mediate
sex differences.
Keywords: running; marathon; gender; female; competition; performance; behavior; habit; endurance
1. Introduction
Previous research has identified a clear sex-based difference in running performance [1–3],
which underlies the separation of sexes at running competitions [4], although this dif-
ference has been reported to diminish with distances beyond that of a marathon [5,6].
Runner training and preparation, however, appear to be crucial for racing performance
regardless of sex [7]. To date, several studies have investigated the sex-based differences
in the performance of recreational runners of speciﬁc distances [8–10], but to the best
of the authors knowledge, no study has assessed sex-speciﬁc differences in recreational
10-kilometer (10 km), half-marathon (HM), marathon (M), and ultra-marathon (UM) run-
ners in a single analysis.
Anatomical (e.g., overall body size and weight, anthropometrics, body composition) [2,8]
and physiological sex differences (e.g., aerobic capacity, muscular strength) [11] are reported
to contribute to an advantage for the male runner. Thus, a biological advantage in favor of
the male runner in the best time marathon performance of approximately 9-11% has been
Int. J. Environ. Res. Public Health 2022, 19, 13291. https://doi.org/10.3390/ijerph192013291
https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022, 19, 13291
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reported [12–14] and appears to be due to various factors related to sex (e.g., greater body
fat percentage and proportion of extremity vs. trunk fat in females, smaller hearts among
females, and lower serum iron among females), potentially leading to a greater submaximal
volume of oxygen consumption, increased lactate levels, and a higher heart rate when
gradually increasing the running workload [1,11,12,15]. However, social circumstances
may unnecessarily hinder female performance [11]. For example, overall running event
participation has been dominantly male [16]. In addition, the antiquated biases that
were once widely accepted in most developed countries in the 1960s may still linger
across societies today regarding women’s athletic abilities, such as that long-distance
endurance running is unhealthy and even harmful to the female anatomy [16]. Nowadays,
running participation is reported as healthy for both sexes based on conclusive, detailed
analyses [17–20]. Despite the previous misconceptions, women’s participation in running
races has been steadily increasing to nearly match that of men today [21].
In addition to health [19,20,22], running event participants are often oriented towards
racing through leisure or performance motivations [23,24], and participating in distance
running events (10 km, HM, M, or UM) provides an opportunity for focusing on personal
goals. The racing environment, the season of event, as well as individual characteris-
tics such as anthropometrics, personality and motivations, nutritional status, and racing
history/experience all contribute to the best time performances [7,25,26]. Therefore, the
objective of this study is to analyze sex-related differences in racing history, experience, and
performance of recreational 10 km to ultra-distance runners for the ﬁrst time and whether
training behaviors, racing history, or racing experience mediate a potential performance
relationship. As there seems to be contradictions and inconsistency of results regarding
the differences and similarities in endurance runners between the sexes in the available
literature, especially based on the previous literature [8–10], this investigation hypothe-
sizes there is a difference in best time race performance between the sexes of recreational
distance runners.
2. Materials and Methods
The proﬁle of the present investigation methodology has been described previously
(see Part A of the sequenced paper) [27] and detailed information for interested readers
are available elsewhere [22,28]. In summary, the Nutrition and Running High Mileage
(NURMI) study followed a protocol [29] approved by the ethics board of St. Gallen,
Switzerland on 6 May 2015 (EKSG 14/145) and has the trial registration number of IS-
RCTN73074080, which was registered retrospectively. The subjects, who were distance
runners competing over 10 km to UM, were required to provide informed consent prior to
participating in the NURMI study. Then, participants completed an online survey contain-
ing questions on sociodemographic information and a complete proﬁle of running- and
performance-related data.
The participants characteristics are presented in Table 1. The interested reader is
kindly referred to the Part A publication for the participants’ recruitment and study proce-
dures [27]. Figure 1 shows the enrollment and categorization of participants.
The race performances and training behaviors of active female and male distance
runners were described using the subsequential details: total and respective number
of completed running events (HM, M/UM, 10 km); number of years of active running
completed without break; racing history (age at ﬁrst race; ﬁrst race distance: 10 km, HM,
M, UM; successful completion of HM, M, UM in last two years; ratio of completed HM/M
to other events; best HM time, best M time, best UM time), running training (frequency of
training, and daily and weekly span of training (hours, km) related to periodized phases and
stages of training, respectively) and preparation for the main event (professional training
resource; total duration). Running performance was linked to a normalized aggregate
mean considering the best ﬁnishing time of HM and M and transformed to an index range
(0–100).
Int. J. Environ. Res. Public Health 2022, 19, 13291
3 of 10
Int. J. Environ. Res. Public Health 2022, 19, 13291 
3 of 11 
 
 
 
Figure 1. Flow Chart of Participants’ Enrollment by Race Distance and Sex. BMI—body mass index. 
HM—half-marathon. M/UM—marathon/ultra-marathon. 10 km—10 kilometers. 
The race performances and training behaviors of active female and male distance 
runners were described using the subsequential details: total and respective number of 
completed running events (HM, M/UM, 10 km); number of years of active running com-
pleted without break; racing history (age at first race; first race distance: 10 km, HM, M, 
UM; successful completion of HM, M, UM in last two years; ratio of completed HM/M to 
other events; best HM time, best M time, best UM time), running training (frequency of 
training, and daily and weekly span of training (hours, km) related to periodized phases 
and stages of training, respectively) and preparation for the main event (professional 
training resource; total duration). Running performance was linked to a normalized ag-
gregate mean considering the best finishing time of HM and M and transformed to an 
index range (0–100). 
R software (version 3.6.2 Core Team 2019: R Foundation for Statistical Computing, 
Vienna, Austria) was used to perform all the statistical analyses. Descriptive statistics (me-
dian, interquartile range (IQR); mean, standard deviation (SD)) were used for the explor-
atory analysis. PCA was used in identifying the two latent factors. 
Significant differences in racing activity (history, training, racing, etc.) between race 
distance and sex were calculated with a non-parametric test. Associations between varia-
bles were performed by Chi-square test (χ²; nominal scale) and Wilcoxon test (ordinal and 
metric scale) and were approximated by using the F distributions with ordinary least 
squares. 
Multiple linear regression analysis and multivariate linear regression were used to 
test differences in the performance, health, and leisure motivations of female and male 
runners. The results of the regression are displayed as effect plots (95% confidence interval 
(95%-CI)). 
The level of statistical significance was set at p ≤ 0.05. 
 
 
Figure 1. Flow Chart of Participants’ Enrollment by Race Distance and Sex. BMI—body mass index.
HM—half-marathon. M/UM—marathon/ultra-marathon. 10 km—10 kilometers.
R software (version 3.6.2 Core Team 2019: R Foundation for Statistical Computing,
Vienna, Austria) was used to perform all the statistical analyses. Descriptive statistics
(median, interquartile range (IQR); mean, standard deviation (SD)) were used for the
exploratory analysis. PCA was used in identifying the two latent factors.
Signiﬁcant differences in racing activity (history, training, racing, etc.) between race
distance and sex were calculated with a non-parametric test. Associations between variables
were performed by Chi-square test (χ2; nominal scale) and Wilcoxon test (ordinal and metric
scale) and were approximated by using the F distributions with ordinary least squares.
Multiple linear regression analysis and multivariate linear regression were used to
test differences in the performance, health, and leisure motivations of female and male
runners. The results of the regression are displayed as effect plots (95% conﬁdence interval
(95%-CI)).
The level of statistical signiﬁcance was set at p ≤ 0.05.
3. Results
A total of 317 distance runners completed the questionnaire. Following data clearance,
72 participants did not meet the inclusion criteria; therefore, 245 runners (141 female, and
104 male) made up the ﬁnal sample with a median body weight of 65 kg (IQR 14.2), height
of 1.7 m (IQR 0.01), BMI of 21.7 kg/m2 (IQR 3.5), and age of 39 (IQR 17) years. The runners
resided in various countries such as Germany (72%), Austria (18%), Switzerland (5%), or
other (4%).
There were signiﬁcant differences between the sexes regarding body weight (p < 0.001),
height (p < 0.001), and BMI (p < 0.001), with the males being heavier (73 kg, IQR 11.9),
taller (1.8 m, IQR 0.1), and having a higher BMI (22.8, IQR 3.16). Moreover, 15 (67%
female) participants were divorced (or separated), 164 (52% female) were married (or living
with partner) and 66 (68% female) were single. Concerning the participants’ educational
background, there were 44 females (vs. 39 males) with a high school degree or equivalent,
49 females (vs. 34 males) with a graduate degree (university level), and 31 females (vs.
22 males) with A-Level or equivalent; one female had no degree, while a total of 25 runners
Int. J. Environ. Res. Public Health 2022, 19, 13291
4 of 10
provided no answer. A signiﬁcant sex difference was found regarding exercise focus
(p = 0.044), where 81 females (vs. 52 males) were leisure focused, with more males (44%;
n = 46) focused on sports performance (30%) compared to females (30%; n = 43). A total of
154 participants were included as NURMI-runners racing at the HM or M/UM distance,
including a greater proportion of males (52% male), and an additional 91 participants
(26% male) were 10 km runners (p < 0.001). The males had completed more 10 km (8, IQR
15), HM (10, IQR 15), and M/UM (10, IQR 11) races than females (6, IQR 7; 6, IQR 6; 10,
IQR 10, respectively). Characteristics of participants with racing motivation, history, and
preferences of females and males, including racing experience, are shown in Table 1. Further
details on the proﬁle of the total sample and the sex-speciﬁc subsamples are provided in
Part A [27].
Table 1. Distance Runner Characteristics, including Racing Motivation, Preferences, and Experience
Displayed by Sex.
Total
Female
Male
Statistics
100% (245)
58% (141)
42% (104)
Age (years)
39 (IQR 17)
37 (IQR 16)
43 (IQR 18)
F(1, 243) = 7.03
p = 0.009
BMI (kg/m2)
21.7 (IQR 3.5)
20.9 (IQR 3.01)
22.8 (IQR 3.16)
F(1, 243) = 28.72
p < 0.001
Marital Status
Divorced/Separated
6% (15)
7% (10)
5% (5)
χ2(2) = 5.32
p = 0.70
Married/With Partner
67% 164
61% (86)
75% (78)
Single
27% (66)
32% (45)
20% (21)
Racing Distance
10 km
37% (91)
48% (67)
23% (24)
χ2(2) = 19.55
p < 0.001
HM
36% (89)
35% (49)
38% (40)
M/UM
27% (65)
18% (25)
38% (40)
Racing Motivation
Leisure
46% (106)
50% (65)
41% (41)
χ2(1) = 1.70
p = 0.193
Sport Performance
54% (125)
50% (66)
59% (59)
Favorite Race Season
Winter
<1% (2)
2% (2)
/
χ2(3) = 4.45
p = 0.216
Spring
46% (106)
47% (62)
44% (44)
Summer
23% (52)
18% (24)
28% (28)
Autumn
31% (71)
33% (43)
28% (28)
Years Active in Running
7 (IQR 7)
5 (IQR 7)
8 (IQR 11)
F(1, 242) = 10.75
p = 0.001
First Race Age (years)
10 km
30 (IQ 16)
31 (IQR 16)
29 (IQR 15)
F(1, 152) = 1.62
p = 0.205
HM
32 (IQR 16)
33 (IQR 15)
32 (IQR 16)
F(1, 217) = 0.13
p = 0.720
M
35 (IQR 13)
35 (IQR 14)
34 (IQR 12)
F(1, 136) = 0.38
p = 0.539
UM
40 (IQR 11)
41 (IQR 8)
38 (IQR 12)
F(1, 46) = 0.75
p = 0.391
Total
30 (IQR 16)
31 (IQR 16)
30 (IQR 18)
F(1, 240) = 0.05
p = 0.831
First Race Distance
10 km
65% (157)
70% (97)
58% (60)
χ2(2) = 4.21
p = 0.122
HM
27% (65)
24% (33)
31% (32)
M
9% (21)
6% (9)
12% (12)
Races Completed in Total
8 (IQR 11)
7 (IQR 9)
10 (IQR 13)
F(1, 243) = 6.75
p = 0.010
Ratio of HM/M to Other
Completed Events
40 (IQR 50)
40 (IQR 51)
40 (IQR 48)
F(1, 243) = 0.07
p = 0.791
Best Finishing
Time (minutes)
HM
111 ± 33
122 ± 39
98 ± 14
F(1, 215) = 72.41
p < 0.001
M
230 ± 45
252 ± 49
213 ± 32
F(1, 130) = 28.57
p < 0.001
UM
628 ± 489
662 ± 579
614 ± 454
F(1, 44) = 0.09
p = 0.760
Note. Results are presented as percentage (%), total numbers, median (IQR), and mean ± SD. χ2 statistic
calculated by Pearson’s Chi-squared test and F statistic calculated by Wilxocon test. 10 km—10 kilometers.
HM—half-marathon. M/UM—marathon/ultra-marathon.
Int. J. Environ. Res. Public Health 2022, 19, 13291
5 of 10
No signiﬁcant differences were found between the sexes in the motivation for racing
(p = 0.193) or the current running motivation (p = 0.356). The favored season for running
events did not differ between females and males (p = 0.216), participants most frequently
preferred racing (n = 106; 42% male) in the springtime. Signiﬁcant differences were found
between the sexes racing history based on: (i) years fully active in running (p = 0.001),
where males ﬁnished more complete years of running (8, IQR 11) than females (5, IQR
7); (ii) total races completed (p = 0.010), where males ﬁnished more events (10, IQR 13)
than females (7, IQR 9); (iii) best ﬁnishing time over the HM distance (p < 0.001), in which
males were faster on average (98 ± 14 min) compared to females (122 ± 39 min); (iv) best
ﬁnishing time over the M distance (p < 0.001), in which males were faster on average
(213 ± 32 min) compared to females (252 ± 49 min); (v) successful completion of planned
M events over the previous two years (p < 0.001), where males ﬁnished more events (1, IQR
3) than females (0, IQR 1); and (vi) successful completion of planned UM events over the
last two years (p < 0.001), where males ﬁnished more events (0, IQR 1) than females (0, IQR
0). No signiﬁcant differences were observed for racing experience/history considering the
age at the ﬁrst time participating in a running event (p = 0.831), also for each race distance
separately (10 km, HM, M, UM; p > 0.05), the ﬁrst event race distance–whether 10 km, HM,
M/UM—(p = 0.122), the best ﬁnishing time over the UM distance (females 662 ± 579 min
vs. males 614 ± 454 min; p = 0.760), or the successful completion of planned HM events
(p = 0.728).
A sex difference was identiﬁed by a multivariate linear regression, with the male
runners being signiﬁcantly more sport performance motivated than the females (b = 9.6;
95% CI [0.02–19.2]; p < 0.05). No sex differences in health (b = −5.46; 95% CI [−12.9–1.93];
p > 0.05) or leisure motives (b = −2.5; 95% CI [−9.87–4.86]; p > 0.05) were identiﬁed by
multivariate linear regression, as displayed by Figure 2.
Int. J. Environ. Res. Public Health 2022, 19, 13291 
6 of 11 
 
 
Figure 2. Effect plots with 95%-CI displaying the differences between female and male running ex-
ercise/racing motives (n = 231): performance, health, and leisure. Note. 95%-CIs were computed us-
ing the multivariate regression analyses (Wald approximation). 
Multivariate linear regression analyses were used to predict the best HM and M run-
ning time performance based on the following confounders: (i) the participants’ sex and 
training behavior–preparatory stage 3 (weekly training frequency, mileage and hours, and 
daily training mileage and hours), preparatory stage 4 (weekly training frequency, mile-
age and hours, and daily training mileage and hours), weekly mileage of preparatory 
stage 1, professional advice sought, and pre-event training duration, which explained 22% 
of the variance (adjusted R2 = 0.22) with no significant difference found for sex (b = −0.295; 
95% CI [−7.7–7.11]; p > 0.05); (ii) the participants’ sex, and racing history (years fully active 
in running and age at first running event), in which the model explains 16% of the variance 
(adjusted R2 = 0.16), and no significant difference was found for sex (b = −1.46; 95% CI 
[−8.93–6]; p > 0.05); and (iii) the participants’ sex and racing experience (HM races com-
pleted, M races completed, the ratio of HM/M to total events completed, and total events 
completed), which explains 14% of the variance (adjusted R2 = 0.14) with no significant 
difference found for sex (b = −1.72; 95% CI [−9.14–5.7]; p > 0.05). 
4. Discussion 
Figure 2. Effect plots with 95%-CI displaying the differences between female and male running
exercise/racing motives (n = 231): performance, health, and leisure. Note. 95%-CIs were computed
using the multivariate regression analyses (Wald approximation).
Multivariate linear regression analyses were used to predict the best HM and M
running time performance based on the following confounders: (i) the participants’ sex and
training behavior–preparatory stage 3 (weekly training frequency, mileage and hours, and
daily training mileage and hours), preparatory stage 4 (weekly training frequency, mileage
and hours, and daily training mileage and hours), weekly mileage of preparatory stage
1, professional advice sought, and pre-event training duration, which explained 22% of
the variance (adjusted R2 = 0.22) with no signiﬁcant difference found for sex (b = −0.295;
95% CI [−7.7–7.11]; p > 0.05); (ii) the participants’ sex, and racing history (years fully
active in running and age at ﬁrst running event), in which the model explains 16% of the
variance (adjusted R2 = 0.16), and no signiﬁcant difference was found for sex (b = −1.46;
95% CI [−8.93–6]; p > 0.05); and (iii) the participants’ sex and racing experience (HM
races completed, M races completed, the ratio of HM/M to total events completed, and
Int. J. Environ. Res. Public Health 2022, 19, 13291
6 of 10
total events completed), which explains 14% of the variance (adjusted R2 = 0.14) with no
signiﬁcant difference found for sex (b = −1.72; 95% CI [−9.14–5.7]; p > 0.05).
4. Discussion
This study aimed to identify sex differences in racing history, experience, and race
performance among recreational 10 KM to UM distance runners. The most important
ﬁndings were (1) males weighed more, were taller, and had a higher BMI than female
runners; (2) there was no sex difference in racing motivation; however, when the running
motivations (initial, current, racing) were combined with exercise focus, a signiﬁcant
sex difference was identiﬁed, with males being signiﬁcantly more sport performance
motivated; (3) males accumulated signiﬁcantly more years of active running and completed
signiﬁcantly more races, especially for marathons and ultra-marathons within the last
2 years; (4) a signiﬁcant sex difference in best time performance with males being faster on
average at HM and M distances. Therefore, this investigation veriﬁes the initial hypothesis
that there is a sex difference in racing best time performance of recreational distance runners
with males being signiﬁcantly faster on average at HM and M events. (5) However, when
considering best time performance as an index and including various mediators (training
behavior, racing history, or racing experience) within multivariate linear regression models,
no signiﬁcant sex differences in performance were found.
The ﬁndings of the anthropometric proportions of this study’s participants (weight,
height, BMI) are consistent with previous reports [8], indicating that males have generally
larger bodies and thus greater body weight than females. Females normally have a greater
body fat percentage than males [30], and this has been reported to be a factor limiting
long-distance running performance [1]. Excess weight, in particular, likely contributes to a
disadvantage for the long-distance runner’s best time performance independent of sex, con-
sidering that each additional gram must be actively transported, resulting in greater energy
expenditure [11,20,31]. Although possible participants with obesity were excluded from
this investigation based on the WHO criteria [32,33], the male runners (73 kg) remained
signiﬁcantly heavier than the females (59.5 kg). Likewise, the male BMI was signiﬁcantly
larger (+1.9 kg/m2) within the present sample. However, the BMI calculation does not take
body composition into account [32,33], excluding potential confounders such as skeletal
and lean body mass regarding the classiﬁcation of individuals [34]. Moreover, the present
sample is based on runners of predominantly long (HM) or very long (M/UM) distances
who are well known to measure around the lower boundaries of body fat percentage
compared to less active populations [35,36], which could indicate a greater skeletal and lean
body mass among the males that is known to positively affect performance [11,20,31,34].
Indeed, reports of female runners developing eating disorders due to a strategy to min-
imize body fat are not uncommon [20,37], which is linked to malnourishment and the
co-occurrence of menstrual dysfunction and osteopenia [20,37]. However, this outcome
may be limited only to sport performance motivated females [22]. Thus, there may be less
of a psychological burden for male runners concerning body composition, which likely
transfers to a higher level of psychological well-being, especially for performing in racing
events [38].
Regarding the ﬁnding that motivations for racing were similar between the sexes,
previous research has found males to be more sport performance oriented [39]. However,
within the regression model, including all of the motives as covariates (initial running,
exercise, current running, racing), the male dominance in sports performance motivation
was in line with previous research [39]. This ﬁnding may be related to the fact that males
generally tend to be more competitive than females, especially in athletics [40]. In addition,
the present study found that the males had completed signiﬁcantly more years fully
active in running than their female counterparts, which is also consistent with previous
ﬁndings [41]; however, this may be due to the fact that the males were signiﬁcantly older in
this sample. Likewise, the males had completed signiﬁcantly more events, which shows
that they are more dedicated and established in running and ﬁnishing races, possibly due to
Int. J. Environ. Res. Public Health 2022, 19, 13291
7 of 10
their greater level of focus on competition and sport performance and age experience [39,40].
In turn, this ﬁnding is likely also related to the successful completion of marathon and
ultra-marathon events within the previous two years, where the males ﬁnished signiﬁcantly
more long-distance events than the females. However, there were signiﬁcantly more males
within the present sample racing at the M/UM distances, which appears to contradict
previous reports of increasing female participation in distance races [21]. Although, it
could be possible that more females were participating in distance events (HM, M/UM)
within this sample but had not successfully completed an event to date, which would
have led to their exclusion from the present analyses. Interestingly, runners of extreme
distances (UM) have been reported to separate from their partners or divorce due to a lack
of support in running, considering the high amount of time spent training and performing
in events [42]. Regarding the marital status of the present runner sample, no sex differences
were identiﬁed even though more males were racing at the UM distance (40 males vs.
25 females).
It was found that male runners performed signiﬁcantly better than the females in HM
and M events, considering their best times in which the males were 24 min and 39 min
faster on average, respectively. This ﬁnding is consistent with the previous literature
comparing sex differences in performance of recreational runners that show a 10% differ-
ence at the minimum [43]. However, it is interesting to ﬁnd that there was no sex-based
performance difference in the best time to complete an ultra-marathon, but this analysis
did not take into account the exact UM distance, which could have been any distance
≥50 km. Therefore, this result most likely suggests that the males were racing at longer
UM distances than the females [2,3,5,6]. Furthermore, when controlling the best HM and M
runtimes with the basic underlying factor of training behavior (including training duration,
professional support, and speciﬁc variables within the main training preparatory period),
no performance difference remained between the sexes. Previously, when sex differences in
performances of elite runners were analyzed, males have been found to be faster regardless
of matched training [12], and the present data on recreational runners appear to contradict
that, possibly due to a more heterogeneous study sample in terms of performance ability
(e.g., anthropometrics, skeletal muscle ﬁber composition) [13].
In addition, another multivariate linear regression model, including the covariates of
racing history (age at ﬁrst running event), indicated no sex difference in HM and M best
time performance. This ﬁnding suggests that the males had a more robust background
in racing and therefore running, which is inconsistent among other reports [8,44], but is
reﬂected by the males having a signiﬁcantly greater age than the females in this study. The
connection to best time performance may be a result of long-term running adaptations due
to a comparable involvement in completing the overarching periodization scheme for each
sex, including main competitions over the years [8,45].
Lastly, a third multivariate linear regression model based on racing experience (number
of completed HM and M events and the proportion of total events completed) also showed
no sex difference in HM and M best time performance. Thus, being successful in completing
running events is an important contributor for best time performance, regardless of sex, as
seen previously [46]. Therefore, considering the best time performances of distance runners,
males are generally faster; however, this sex difference was superﬁcial in recreational
distance runners when considering several modiﬁable areas that mediate performance,
especially the training behaviors within Phase 2: the main preparatory period, considering
that this model explained 22% of the variance (vs. racing history 16% vs. racing experience
14%). These ﬁndings may indicate that physiological sex differences are negligent regarding
HM and M performance in recreational distance runners, and that social circumstances
may play a considerable role in best time running performance.
Based on the cross-sectional design of the study, the ﬁndings of the present investi-
gation include limitations that must be considered, such as that no causative conclusions
can be drawn from these results. The primary limitation to be addressed is that self-report
is a common feature of the questionnaire approach that is well-known to result in a mis-
Int. J. Environ. Res. Public Health 2022, 19, 13291
8 of 10
representation of answers, likely due to social views. As a means to limit the effect of
misreporting, control questions were included throughout the survey, and, likewise, the
participants were highly motivated distance runners, which may have enhanced the re-
liability of their answers and the dataset. In addition, while 245 distance runners were
included within the ﬁnal analysis, the sample size was relatively modest, and the race
distances were unevenly distributed, including more males in the longer distances (M/UM).
Moreover, several factors of race events were not considered in the analyses, such as the
race environment and conditions (inclement or mild weather along with temperature and
relative humidity), time of day, season, and the event location; however, the best time
reports were veriﬁed retrospectively. Another limitation of the present investigation is that
nutritional status was not controlled for, or the type of nutrition followed by the runners,
which is a well-known factor affecting performance [25,26,29]. However, the NURMI study
has included participant nutritional data that have or will be reported in subsequent papers
due to publication requirements.
Considering the limitations of this investigation, valuable insights may be taken by
female and male recreational distance running athletes, as well as their coaches, athletic
trainers, exercise physiologists, physical therapists, and physicians, regarding essential
factors contributing to a healthy best performance at running events. Future studies are
suggested to investigate sex differences of recreational runners of long distances (HM, M,
UM) in best time performance considering the main underlying focus of sport performance
and controlling for mediators of running and racing history, professional support, and
racing experience.
5. Conclusions
This study was the ﬁrst with the aim of investigating sex-associated differences in
racing history, experience, and performance of recreational 10 km, HM, M, and UM dis-
tance runners. The ﬁndings of the present study reveal males are faster in their best time
performances at HM and M events and report a more robust background in running and
racing history and experience. However, recreational female distance runners compete
comparably with males considering the best time performance of HM and M events when
statistically controlling for training behaviors or similar backgrounds in racing experi-
ence/history. Thus, partaking in and, most importantly, ﬁnishing running events is key in
improving best time performances for females and males alike. The results of this investi-
gation provide a critical insight into the crucial differences in female and male recreational
distance runner performance over several long distances (HM, M/UM, 10 km), which may
be necessary for lifting the current societal circumstances (training/racing opportunities,
performance expectations) and understandings of health and exercise professionals (athletic
trainers, exercise physiologists, sports medicine doctors, physical therapists) in supporting
or limiting female participation. Moreover, competitive runners, health professionals and
coaches who supervise and counsel recreational runners may beneﬁt from these ﬁndings in
order to improve best time performance through a deeper understanding of the areas that
mediate sex differences.
Author Contributions: K.W. conceptualized and designed the study and the questionnaires together
with B.K., C.L. and K.W. conducted data analysis and M.M. and D.T. provided statistical expertise.
M.M., T.R., K.W. and D.T. drafted the manuscript. T.R., C.L., B.K. and K.W. critically reviewed it. G.W.
provided technical support through data acquisition and data management. All authors have read
and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: The study protocol is available online via https://springerplus.
springeropen.com/articles/10.1186/s40064-016-2126-4 (accessed on 17 August 2022) and was ap-
proved by the ethics board of St. Gallen, Switzerland on 6 May 2015 (EKSG 14/145). The study
was conducted in accordance with the ethical standards of the institutional review board, medical
professional codex, and with the 1964 Helsinki declaration and its later amendments as of 1996, the
Int. J. Environ. Res. Public Health 2022, 19, 13291
9 of 10
Data Security Laws, and good clinical practice guidelines. Study participation was voluntary and
could be canceled at any time without the provision of reasons or negative consequences.
Informed Consent Statement: Informed consent was obtained from all individual participants
included in the study considering the data collected, used, and analyzed exclusively and only in the
context of the NURMI Study for scientiﬁc publication.
Data Availability Statement: The data sets generated during and/or analyzed during the current
study are not publicly available but may be made available upon reasonable request. Subjects will
receive a brief summary of the results of the NURMI Study if desired.
Acknowledgments: There are no professional relationships with companies or manufacturers who
will beneﬁt from the results of the present study. Moreover, this research did not receive any speciﬁc
grant or funding from funding agencies in the public, commercial, or non-proﬁt sectors.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
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Sex Differences in Racing History of Recreational 10 km to Ultra Runners (Part B)-Results from the NURMI Study (Step 2).
Motevalli, Mohamad,Tanous, Derrick,Wirnitzer, Gerold,Leitzmann, Claus,Rosemann, Thomas,Knechtle, Beat,Wirnitzer, Katharina