Citation: Tanous, D.; Motevalli, M.;
Wirnitzer, G.; Leitzmann, C.;
Rosemann, T.; Knechtle, B.; Wirnitzer,
K. Sex Differences in Training
Behaviors of 10 km to
Ultra-Endurance Runners (Part
A)—Results from the NURMI Study
(Step 2). Int. J. Environ. Res. Public
Health 2022, 19, 13238. https://
doi.org/10.3390/ijerph192013238
Academic Editors: Paul B.
Tchounwou, 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 Training Behaviors of 10 km to
Ultra-Endurance Runners (Part A)—Results from the NURMI
Study (Step 2)
Derrick Tanous 1,2
, Mohamad Motevalli 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, 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: Training for running events is fundamental for successful participation in various running
events such as 10 km, half-marathon, marathon, or ultra-marathon distances. Training behaviors
are likely based on runner motivations and social constraints, particularly for females. Participants
completed a questionnaire following a cross-sectional approach, including questions on sociode-
mographics, general training behaviors, and periodization training strategies. The ﬁnal sample
included 245 participants (141 females, 104 males), mostly from Germany (72%), Austria (18%), and
Switzerland (5%), with a median age of 39 years (IQR 17) and a BMI of 21.7 kg/m2 (IQR 3.5). Males
more often trained alone and independently, whereas females were most likely to follow an external
resource (p = 0.037). Non-parametric ANOVA revealed signiﬁcant training differences between sexes
in daily training mileages and durations at each phase and stage (p < 0.05) as well as in weekly
training mileages and durations for general basic training and race-speciﬁc training (p < 0.05). Critical
sex differences in training behaviors may arise from physiological differences and social expectations,
which may be related to the distances they prefer to race at as well as their motivations for running
and racing. This study provides a wide overview of training behaviors for endurance runners or
professionals guiding healthy running performance.
Keywords: running; marathon; female; motive; recreational athlete; endurance exercise; habit
1. Introduction
Running has been well-established as a healthy physical activity for females and males
across adulthood [1–3]. While many similar training habits exist between female and
male endurance runners, a multitude of factors remain distinguishable between the sexes,
including primarily physiological and social differences [4–7]. Numerous studies have
investigated sex differences in the training behaviors of endurance runners [8–15]. To the
best of the authors’ knowledge, no investigation has analyzed sex-related running training
behaviors considering diverse distances, including 10 km (10 km) up to ultra-marathon
(UM) distances in one study.
Parallel to health beneﬁts, frequent runners often follow various personal motivations
for running, primarily for leisure or sports performance [3,4,16]. Females generally report
higher running motives for psychological health reasons (body weight concern, a sense
Int. J. Environ. Res. Public Health 2022, 19, 13238. https://doi.org/10.3390/ijerph192013238
https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022, 19, 13238
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of belonging, life meaning, fulﬁllment/harmony), whereas males are mostly competition-
focused [17]. Training provides the structure for progress in meeting the individual’s
motivational goals [15,18] independent of sex.
Considering the anatomical (e.g., anthropometric, hormonal, maximum muscular
strength) [19,20] and societal (e.g., expectations, motives) differences between females and
males [6,21], further sex differences in runner training behaviors may arise, including
general training (training duration, external resource, other sports participation) and
speciﬁc training measures (weekly frequency, weekly and daily mileages and durations,
type of training from basic- to competition-speciﬁc, and various intensities) as well as the
distances they prefer to run (10 km, half-marathon, marathon/UM) [9,15,17,18]. Regardless
of the endurance runner’s motives, athletes typically adhere to periodization strategies
when training for running events, including recognizable training phases that may unfold
throughout the duration of up to a year before an event [22,23]. Different periods of training
(regeneration and transitional period, main preparatory period, competition period) are
followed to build and/or maximize beneﬁcial training adaptations, mainly to improve the
maximal volume of oxygen consumption in runners to maintain a faster pace for better
ﬁnishing times [22–24].
Contrariwise to the sex differences in the training behaviors of endurance runners
identiﬁed by the previous literature [8–15], similarities between the sexes are also commonly
observed that appear contradictory [8,9,11–14]. However, this occurrence may be due to
the previous study designs, the strict inclusion of pre-speciﬁed race distances, and the
methodological heterogeneity between the studies at the population level [8–15]. Therefore,
this study is the ﬁrst aiming to assess the relationships between training behaviors of female
and male recreational endurance runners over 10 km up to UM distances. The present
investigation hypothesized that there are critical training differences between the sexes
of recreational endurance runners of various distances (half-marathon, marathon/UM,
10 km).
2. Materials and Methods
The study protocol of the Nutrition and Running High Mileage (NURMI) Study [25] was
approved by the ethics board of St. Gallen, Switzerland on 6 May 2015 (EKSG 14/145). The
trial registration number is ISRCTN73074080 (retrospectively registered). Detailed information
about the methods of the NURMI Study Step 2 has been described elsewhere [3,4,7,26–30].
The NURMI Study was conducted in three steps following a cross-sectional design.
Endurance runners were mainly recruited from Austria, Germany, and Switzerland and
were contacted primarily via social media, websites of the organizers of marathon events,
online running communities, email lists, and runners’ magazines, as well as via magazines
for health, nutrition and lifestyle, trade fairs on sports, plant-based nutrition and lifestyle,
and through personal contacts. The characteristics of the subjects are presented in Table 1.
Participants completed an online survey within the NURMI Study Step 2 that was
available from February 2015 to December 2015 in German and English at www.nurmi-
study.com (accessed on 17 August 2022). Prior to completing the questionnaire on physical
and psychological health (including the basic assignment to an area of sports, motivation
and aim of running activities, and other sports to balance for running in order to better dif-
ferentiate between predominant health, leisure, or sport performance-orientated approach
to running), participants were provided with a written description of the procedures and
participants gave their informed consent to take part in the study.
For complete participation in the study, the following inclusion criteria were required:
(1) written informed consent, (2) at least 18 years of age, (3) questionnaire Step 2 completed,
and (4) completion of at least a half-marathon distance running event within the past two
years. However, as an additional criterion in this study, participants had to (5) select an
event as the NURMI running event, including either a half-marathon (HM) or marathon
(M) distance that they prepared for and subsequently ﬁnished in Step 3 (main NURMI
Study: Step 2 linked to Step 3) [25].
Int. J. Environ. Res. Public Health 2022, 19, 13238
3 of 14
An additional group of 91 highly motivated runners provided accurate and pragmatic
answers with plenty of high-quality data and had not successfully participated in either a
HM or M but in a 10 km race instead. To avoid an irreversible loss of these valuable data
sets, those who met all inclusion criteria but named a 10 km race as their running event
were kept as an additional race distance subgroup.
To control for measures of (1) running activity (history, motivation, training, racing,
etc.) and (2) diet, we included control questions in different survey sections. Incomplete,
inconsistent, and conﬂicting data sets were excluded from the data analysis. Moreover,
to control for a minimal status of health linked to a minimum level of ﬁtness and further
enhance the reliability of data sets, the body mass index (BMI) approach followed the World
Health Organization (WHO) [31,32]. With a BMI ≥ 30, other health protective and weight
loss strategies alongside running are foremost necessary to safely reduce body weight.
Regarding the UM distance, the shortest UM reported was 50 km, and the longest
was 160 km. Figure 1 shows the categorization of participants according to sex and race
distance subgroups: HM, M/UM, and 10 km (M/UM data were pooled since the marathon
distance is within an ultra-marathon). Additionally, the involved reader is kindly referred
to the Part B publication for the subsequential linking of training behaviors with race
performances [33].
nviron. Res. Public Health 2022, 19, x FOR PEER REVIEW 
3 of 15 
(5) select an event as the NURMI running event, including either a half-marathon (HM) 
or marathon (M) distance that they prepared for and subsequently finished in Step 3 (main 
NURMI Study: Step 2 linked to Step 3) [25].  
An additional group of 91 highly motivated runners provided accurate and prag-
matic answers with plenty of high-quality data and had not successfully participated in 
either a HM or M but in a 10 km race instead. To avoid an irreversible loss of these valu-
able data sets, those who met all inclusion criteria but named a 10 km race as their running 
event were kept as an additional race distance subgroup.  
To control for measures of (1) running activity (history, motivation, training, racing, 
etc.) and (2) diet, we included control questions in different survey sections. Incomplete, 
inconsistent, and conflicting data sets were excluded from the data analysis. Moreover, to 
control for a minimal status of health linked to a minimum level of fitness and further 
enhance the reliability of data sets, the body mass index (BMI) approach followed the 
World Health Organization (WHO) [31,32]. With a BMI ≥ 30, other health protective and 
weight loss strategies alongside running are foremost necessary to safely reduce body 
weight. 
Regarding the UM distance, the shortest UM reported was 50 km, and the longest 
was 160 km. Figure 1 shows the categorization of participants according to sex and race 
distance subgroups: HM, M/UM, and 10 km (M/UM data were pooled since the marathon 
distance is within an ultra-marathon). Additionally, the involved reader is kindly referred 
to the Part B publication for the subsequential linking of training behaviors with race per-
formances [33]. 
 
Figure 1. Enrollment and Categorization of Participants by Sex. BMI—body mass index. HM—half-
marathon. M/UM—marathon/ultra-marathon. 10 km—10 kilometers. 
Training behaviors of active female and male endurance running participants were 
described by the following items linked to sex: running motivations (health, leisure, sport 
performance); preferred time of day and preferred season for running activity (indoor vs. 
outdoor); training duration for the main event; external training resource followed (none, 
professional, other); participation in other sports activities to balance running (summer, 
Figure 1. Enrollment and Categorization of Participants by Sex. BMI—body mass index. HM—half-
marathon. M/UM—marathon/ultra-marathon. 10 km—10 kilometers.
Training behaviors of active female and male endurance running participants were
described by the following items linked to sex: running motivations (health, leisure, sport
performance); preferred time of day and preferred season for running activity (indoor vs.
outdoor); training duration for the main event; external training resource followed (none,
professional, other); participation in other sports activities to balance running (summer,
winter); periodized running training (weekly frequency of training, daily and weekly
mileages and durations of training (km, hours) related to phase and stage of training,
respectively).
Int. J. Environ. Res. Public Health 2022, 19, 13238
4 of 14
The statistical software R version 3.6.2 Core Team 2019 (R Foundation for Statistical
Computing, Vienna, Austria) performed all statistical analyses. Exploratory analysis
was performed by descriptive statistics (median and interquartile range (IQR); mean and
standard deviation (SD)).
Signiﬁcant differences in running activity (training behaviors) between race distance
and sex were calculated by using a non-parametric ANOVA. Chi-square test (χ2; nominal
scale) examined the association between variables, and the Wilcoxon test and/or Kruskal–
Wallis test (ordinal and metric scale) approximated F distributions with ordinary least
squares.
Differences in weekly and daily training with the mileages of female and male runners
are displayed as box plots.
The level of statistical signiﬁcance was set at p ≤ 0.05.
3. Results
The survey was completed by 317 endurance runners. A total of 72 participants
were excluded from the initial sample due to satisfying the exclusion criteria (i.e., three
participants with a BMI ≥ 30) or disagreement with the inclusion criteria. After data
clearance, a total of 141 (58%) females and 104 (42%) males (n = 245) comprised the ﬁnal
sample with a combined age of 39 (IQR 17) years, a body weight of 65 kg (IQR 14.2),
and a BMI of 21.7 kg/m2 (IQR 3.5) from several countries, including Austria (n = 44),
Germany (n = 177), Switzerland (n = 13), and some other countries (n = 11: Belgium, Brazil,
Canada, Italy, Luxemburg, Netherlands, Poland, Spain, United Kingdom). There were
154 NURMI-Runners (48% female) and 91 runners (74% female) competing at the 10 km
distance.
The female participants were signiﬁcantly shorter (p < 0.001) and had a lower body
weight (p < 0.001) and BMI (p < 0.001) than the males. Regarding the highest academic
qualiﬁcation achieved, participants reported a high school diploma or equivalent (53%
female), an A Levels or equivalent (58% female), a university degree or higher (59% female),
and some provided no answer (64% female). A signiﬁcant difference (p = 0.044) was
identiﬁed between the sexes in terms of exercise focus, where females were largely focused
on leisure (57% female vs. 50% male), with a smaller proportion of females being sport
performance-oriented (30% female vs. 44% male). Participants reported their marital status
as single (32% of females vs. 20% of males), married or living with a partner (61% of females
vs. 75% of males), or divorced/separated (7% of females vs. 5% of males). Characteristics
of participants are further presented in Table 1, and more details on the characteristics of
participants are provided in Part B of the sequenced paper [33].
Table 1. Characteristics of Endurance Runners 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 †
Body Weight (kg)
65 (IQR 14.2)
59.5 (IQR 10.9)
73 (IQR 11.9)
F(1, 243) = 191.23
p < 0.001 ‡
Height (m)
1.7 (IQR 0.1)
1.7 (IQR 0.1)
1.8 (IQR 0.1)
F(1, 243) = 228.04
p < 0.001 ‡
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 ‡
Int. J. Environ. Res. Public Health 2022, 19, 13238
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Table 1. Cont.
Total
Female
Male
Statistics
Academic
Qualiﬁcation
No qualiﬁcation
<1% (1)
<1% (1)
/
χ2(4) = 1.96
p = 0.744
High school diploma/
Technical qualiﬁcation/
GCSE or equivalent
34% (83)
31% (44)
38% (39)
A Levels or equivalent
22% (53)
22% (31)
21% (22)
University degree/
Graduate degree
34% (83)
35% (49)
33% (34)
No answer
10% (25)
11% (16)
9% (9)
Country of
Residence
Austria
18% (44)
11% (16)
27% (28)
χ2(3) = 11.32
p = 0.010 *
Germany
72% (177)
79% (112)
62% (65)
Switzerland
5% (13)
4% (6)
7% (7)
Other
4% (11)
5% (7)
4% (4)
Exercise Focus
Health
Leisure
Sport performance
9% (23)
54% (133)
36% (89)
12% (17)
57% (81)
30% (43)
6% (6)
50% (52)
44% (46)
χ2(2) = 6.24
p = 0.044 *
Racing Distance
HM
M/UM
10 km
36% (89)
27% (65)
37% (91)
35% (49)
18% (25)
48% (67)
38% (40)
38% (40)
23% (24)
χ2(2) = 19.55
p < 0.001 ‡
Initial Running
Motivation
Health
Leisure
44% (108)
56% (137)
46% (65)
54% (76)
41% (43)
59% (61)
χ2(1) = 0.55
p = 0.459
Current Running
Motivation
Health
Leisure
Sport performance
19% (47)
46% (113)
35% (85)
21% (30)
48% (67)
31% (44)
16% (17)
44% (46)
39% (41)
χ2(2) = 2.06
p = 0.356
Note. *, †, or ‡ denote statistical signiﬁcance at the levels p < 0.05, p < 0.01, or p < 0.001, respectively. Results are
presented as percentage (%), total numbers, and median (IQR). χ2 statistic calculated by Pearson’s Chi-squared
test and F statistic calculated by Kruskal–Wallis test. HM—half-marathon. M/UM—marathon/ultra-marathon.
10 km—10 kilometers.
No signiﬁcant differences were found between the sexes for the initial running motiva-
tion (p = 0.459) or the current running motivation (p = 0.356). Seasonal running preferences
did not differ between females and males, including the preferred indoor (p = 0.312) or
outdoor running season (p = 0.727) and the ideal time of day for running, whether indoor
(p = 0.419) or outdoor (p = 0.592). From the total sample, most participants preferred out-
door running (n = 145; 57% female) in the springtime and most often during the morning
(n = 75; 57% female) but had no indoor running preference for a season (n = 178; 54%
female) or time of day (n = 168; 54% female).
Table 2 displays the general training behaviors for recreation runners for females
and males. A signiﬁcant difference was identiﬁed (p = 0.037) in which males were more
likely to train alone (84% male vs. 71% female), whereas females were more likely to train
under the direction of a professional (24% female vs. 12% male) or another resource (11%
female vs. 4% male). Men were signiﬁcantly more likely to participate in fell/trail running
(p = 0.021) and ski-touring (p = 0.029); no additional sex-based participation differences
were identiﬁed in other sports to balance running: cycling, swimming, rambling, triathlon,
skiing, cross-country skiing, or snowboarding. No signiﬁcant differences were observed
between training duration for the main event and sex (p = 0.833) shown in Figure 2.
Int. J. Environ. Res. Public Health 2022, 19, 13238
6 of 14
Table 2. General Training Behaviors, including Total Duration, Resource, and Other Sports by Sex.
Total
Female
Male
Statistics
100% (245)
58% (141)
42% (104)
Training Duration for Main Event
1–2 months
3–4 months
4–6 months
7–8 months
9–10 months
>12 months
20% (46)
52% (122)
21% (48)
4% (9)
2% (5)
2% (4)
17% (22)
55% (73)
21% (28)
4% (5)
2% (3)
2% (2)
24% (24)
49% (49)
20% (20)
4% (4)
2% (2)
2% (2)
χ2(2) = 2.12; p = 0.833
Training Resource for Running Events
Alone and independently
76% (179)
71% (94)
84% (85)
χ2(2) = 6.57; p = 0.037 *
Under the direction of a professional
15% (36)
24% (18)
12% (12)
Other
8% (19)
11% (15)
4% (4)
Other Sports Activities to Balance for Running
Summer
Cycling
53% (130)
51% (72)
56% (58)
χ2(1) = 0.57; p = 0.451
Fell/Trail running
31% (75)
25% (35)
39% (40)
χ2(1) = 5.32; p = 0.021 *
Swimming
31% (75)
29% (41)
33% (34)
χ2(1) = 0.39; p = 0.535
Rambling
31% (75)
34% (47)
27% (28)
χ2(1) = 1.13; p = 0.287
Triathlon
19% (46)
17% (24)
21% (22)
χ2(1) = 0.69; p = 0.407
Winter
Skiing
14% (34)
13% (18)
16% (16)
χ2(1) = 0.35; p = 0.552
Cross country skiing
11% (26)
10% (14)
12% (12)
χ2(1) = 0.17; p = 0.681
Snowboarding
7% (16)
7% (10)
6% (6)
χ2(1) = 0.17; p = 0.682
Ski-touring
4% (9)
1% (2)
7% (7)
χ2(1) = 4.79; p = 0.029 *
Note. * denotes statistical signiﬁcance at the level p < 0.05. Results are presented as percentage (%) and total
numbers. χ2 statistic calculated by Pearson’s Chi-squared test and F statistic calculated by Kruskal–Wallis test.
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 
6 of
 
 
Table 2. General Training Behaviors, including Total Duration, Resource, and Other Sports by S
 
Total 
Female 
Male 
Statistics 
 
100% (245) 
58% (141) 
42% (104) 
 
Training Duration for Main Event 
1–2 months 
3–4 months 
4–6 months 
7–8 months 
9–10 months 
>12 months 
20% (46) 
52% (122) 
21% (48) 
4% (9) 
2% (5) 
2% (4) 
17% (22) 
55% (73) 
21% (28) 
4% (5) 
2% (3) 
2% (2) 
24% (24) 
49% (49) 
20% (20) 
4% (4) 
2% (2) 
2% (2) 
χ2(2) = 2.12; p = 0.833 
Training Resource for Running Events 
Alone and independently 
76% (179) 
71% (94) 
84% (85) 
χ2(2) = 6.57; p = 0.037 *
Under the direction of a professional 
15% (36) 
24% (18) 
12% (12) 
Other 
8% (19) 
11% (15) 
4% (4) 
Other Sports Activities to Balance for Running 
Summer 
Cycling 
53% (130) 
51% (72) 
56% (58) 
χ2(1) = 0.57; p = 0.451 
 
Fell/Trail running 
31% (75) 
25% (35) 
39% (40) 
χ2(1) = 5.32; p = 0.021 *
 
Swimming 
31% (75) 
29% (41) 
33% (34) 
χ2(1) = 0.39; p = 0.535 
 
Rambling 
31% (75) 
34% (47) 
27% (28) 
χ2(1) = 1.13; p = 0.287 
 
Triathlon 
19% (46) 
17% (24) 
21% (22) 
χ2(1) = 0.69; p = 0.407 
Winter 
Skiing 
14% (34) 
13% (18) 
16% (16) 
χ2(1) = 0.35; p = 0.552 
 
Cross country skiing 
11% (26) 
10% (14) 
12% (12) 
χ2(1) = 0.17; p = 0.681 
 
Snowboarding 
7% (16) 
7% (10) 
6% (6) 
χ2(1) = 0.17; p = 0.682 
 
Ski-touring 
4% (9) 
1% (2) 
7% (7) 
χ2(1) = 4.79; p = 0.029 *
Note. * denotes statistical significance at the level p < 0.05. Results are presented as percentage 
and total numbers. χ2 statistic calculated by Pearson’s Chi-squared test and F statistic calculated
Kruskal–Wallis test. 
 
Figure 2. Sex-based differences in the prevalence of training duration (displayed in six categori
for main events. Data are presented by percentage. 
Table 3 displays the periodized training phases by sex, including the regenerati
stage and transitional period (Phase A), the main preparatory period (Phase B), and t
main competition period (Phase C) based on the weekly training frequencies and t
weekly and daily training mileages and durations. No significant differences were o
served for weekly training frequency and sex, regardless of the phase (p > 0.05). Prepa
tory Stage 4 showed the greatest average difference in weekly mileage (+11.4 km/week 
Figure 2. Sex-based differences in the prevalence of training duration (displayed in six categories) for
main events. Data are presented by percentage.
Table 3 displays the periodized training phases by sex, including the regeneration stage
and transitional period (Phase A), the main preparatory period (Phase B), and the main
competition period (Phase C) based on the weekly training frequencies and the weekly and
daily training mileages and durations. No signiﬁcant differences were observed for weekly
training frequency and sex, regardless of the phase (p > 0.05). Preparatory Stage 4 showed
the greatest average difference in weekly mileage (+11.4 km/week for males; p = 0.030) and
duration (+1.71 h/day for males; p = 0.032). Signiﬁcant differences were found between the
sexes in terms of daily training mileage and daily training duration for every phase and
stage (p < 0.05), with a highly signiﬁcant difference identiﬁed in stage 1 (phase B) for daily
training mileage (+2.94 km/day for males; p < 0.001) and duration (+0.14 h/day for males;
Int. J. Environ. Res. Public Health 2022, 19, 13238
7 of 14
p < 0.001). Figures 3–5 depict the training mileages and weekly training frequency by sex
based on the training periodization phases.
Table 3. Periodization Training Behavior, including Frequency, Mileages, and Durations Displayed
by Sex.
Total
Female
Male
Statistics
100% (245)
58% (141)
42% (104)
Phase A—Regeneration Stage and Transitional Period
Weekly training frequency
Weekly training mileage (km)
Weekly training duration (hours)
3 (IQR 1)
22.4 ± 18.9
1.21 ± 1.03
2 (IQR 1)
20.6 ± 19
1.12 ± 1.03
3 (IQR 1)
24.6 ± 18.7
1.33 ± 1.02
F(1, 220) = 0.29; p = 0.590
F(1, 220) = 3.77; p = 0.053
F(1, 220) = 3.58; p = 0.060
Daily training mileage (km)
Daily training duration (hours)
7.06 ± 5.86
0.26 ± 0.21
6.24 ± 5.33
0.23 ± 0.19
8.12 ± 6.36
0.30 ± 0.23
F(1, 220) = 7.26; p = 0.008 †
F(1, 220) = 6.28; p = 0.013 *
Phase B—Main Preparatory Period
Preparatory Stage 1 (general basic training, mainly at low intensity)
Weekly training frequency
Weekly training mileage (km)
Weekly training duration (hours)
3 (IQR 2)
30.2 ± 24.6
4.63 ± 3.76
3 (IQR 2)
27.2 ± 23.1
4.16 ± 3.54
3 (IQR 2)
34.1 ± 25.9
5.22 ± 3.96
F(1, 220) = 0.01; p = 0.931
F(1, 220) = 4.40; p = 0.037 *
F(1, 220) = 4.67; p = 0.032 *
Daily training mileage (km)
Daily training duration (hours)
8.74 ± 6.61
0.4 ± 0.3
7.46 ± 6.13
0.34 ± 0.28
10.4 ± 6.86
0.48 ± 0.31
F(1, 220) = 14.93; p < 0.001 ‡
F(1, 220) = 14.70; p < 0.001 ‡
Preparatory Stage 2 (speciﬁc basic training, build-up training, low-to-moderate intensity)
Weekly training frequency
Weekly training mileage (km)
Weekly training duration (hours)
3 (IQR 2)
33.5 ± 27.5
4.82 ± 3.96
3 (IQR 2)
31 ± 26
4.46 ± 3.74
3 (IQR 3)
36.7 ± 29.2
5.28 ± 4.2
F(1, 220) = 0.02; p = 0.902
F(1, 220) = 2.15; p = 0.144
F(1, 220) = 2.21; p = 0.138
Daily training mileage (km)
9.42 ± 7.29
0.41 ± 0.32
8.39 ± 7.09
0.36 ± 0.31
10.8 ± 7.37
0.47 ± 0.32
F(1, 220) = 7.91; p = 0.005 †
F(1, 220) = 7.85; p = 0.006 †
Daily training duration (hours)
Preparatory Stage 3 (competition training, intervals, pace, moderate-to-high intensity)
Weekly training frequency
4 (IQR 2)
37.1 ± 31.1
5.65 ± 4.73
4 (IQR 1)
34.2 ± 29.5
5.2 ± 4.48
4 (IQR 3)
40.9 ± 32.9
6.22 ± 5
F(1, 220) = 0.04; p = 0.850
F(1, 220) = 2.41; p = 0.122
F(1, 220) = 2.57; p = 0.110
Weekly training mileage (km)
Weekly training duration (hours)
Daily training mileage (km)
9.98 ± 7.86
0.41 ± 0.32
9.01 ± 7.78
0.37 ± 0.32
11.24 ± 7.82
0.47 ± 0.32
F(1, 220) = 8.37; p = 0.004 †
F(1, 220) = 8.20; p = 0.005 †
Daily training duration (hours)
Preparatory Stage 4 (race-speciﬁc training, test competition, moderate-to-high intensity)
Weekly training frequency
4 (IQR 2)
39.5 ± 35.8
5.95 ± 5.39
4 (IQR 1)
34.6 ± 30.6
5.2 ± 4.6
4 (IQR 2)
46 ± 40.9
6.91 ± 6.15
F(1, 220) = 1.49; p = 0.223
F(1, 220) = 4.74; p = 0.030 *
F(1, 220) = 4.65; p = 0.032 *
Weekly training mileage (km)
Weekly training duration (hours)
Daily training mileage (km)
10.7 ± 8.31
0.5 ± 0.39
9.47 ± 7.93
0.45 ± 0.37
12.29 ± 8.56
0.58 ± 0.4
F(1, 220) = 10.13; p = 0.002 †
F(1, 220) = 9.58; p = 0.002 †
Daily training duration (hours)
Phase C—Competition Period (incl. tapering and interim race stages)
Weekly training frequency
3 (IQR 2)
32.2 ± 27.7
4.41 ± 3.8
3 (IQR 2)
28.8 (24.4)
3.95 (3.33)
4 (IQR 2)
36.6 (31.1)
5.01 (4.26)
F(1, 220) = 3.30; p = 0.071
F(1, 220) = 2.94; p = 0.088
F(1, 220) = 2.48; p = 0.117
Weekly training mileage (km)
Weekly training duration (hours)
Daily training mileage (km)
9.35 ± 8.7
0.41 ± 0.37
8.46 ± 8.33
0.37 ± 0.36
10.5 ± 9.07
0.45 ± 0.39
F(1, 220) = 5.21; p = 0.023 *
F(1, 220) = 4.47; p = 0.036 *
Daily training duration (hours)
Note. *, †, or ‡ denote statistical signiﬁcance at the levels p < 0.05, p < 0.01, or p < 0.001, respectively. Results are
presented as median (IQR) and mean (SD). F statistic calculated by Kruskal–Wallis test. km—kilometer.
Int. J. Environ. Res. Public Health 2022, 19, 13238
8 of 14
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 
8 of 15 
 
 
Note. *, †, or ‡ denote statistical signiﬁcance at the levels p < 0.05, p < 0.01, or p < 0.001, respectively. 
Results are presented as median (IQR) and mean (SD). F statistic calculated by Kruskal–Wallis test. 
km—kilometer. 
 
Figure 3. Box plots displaying sex differences in weekly training frequencies in different training 
periodization phases and stages. 
 
Figure 4. Box plots displaying sex differences in weekly training mileages (km) in different training 
periodization phases and stages. 
Figure 3. Box plots displaying sex differences in weekly training frequencies in different training
periodization phases and stages.
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 
8 of 15 
 
 
Note. *, †, or ‡ denote statistical signiﬁcance at the levels p < 0.05, p < 0.01, or p < 0.001, respectively. 
Results are presented as median (IQR) and mean (SD). F statistic calculated by Kruskal–Wallis test. 
km—kilometer. 
 
Figure 3. Box plots displaying sex differences in weekly training frequencies in different training 
periodization phases and stages. 
 
Figure 4. Box plots displaying sex differences in weekly training mileages (km) in different training 
periodization phases and stages. 
Figure 4. Box plots displaying sex differences in weekly training mileages (km) in different training
periodization phases and stages.
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 
9 of 15 
 
 
Figure 5. Box plots displaying sex differences in daily training unit (km/unit) in different training 
periodization phases and stages. 
4. Discussion 
The objective of this study was to investigate sex differences in training behavior 
among endurance runners; the present investigation was conducted to assess the relation-
ships between training behaviors of female and male recreational runners from 10 km up 
U
d
h
f
d
f
l
h d
l
b d
h
d
Figure 5. Box plots displaying sex differences in daily training unit (km/unit) in different training
periodization phases and stages.
Int. J. Environ. Res. Public Health 2022, 19, 13238
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4. Discussion
The objective of this study was to investigate sex differences in training behavior
among endurance runners; the present investigation was conducted to assess the relation-
ships between training behaviors of female and male recreational runners from 10 km up
to UM distances. The main ﬁndings were (1) female runners had a lower body weight and
height and thus a lower BMI than the males; (2) a signiﬁcant sex difference was found in
main event racing distance; (3) signiﬁcantly more females reported following an external
training resource but no sex difference was found in the training duration for the main event;
(4) weekly training frequencies were similar for females and males across periodization
phases (including all stages of Phase B); (5) various discrepancies were identiﬁed between
the sexes for weekly mileages and durations depending on each phase/stage; (6) males
were signiﬁcantly more active at all phases/stages considering daily mileage and duration;
(7) males had a greater exercise focus on sport performance but no signiﬁcant differences
were found between sexes for the initial or current running motivations. While similarities
exist between the training behaviors of female and male endurance runners [8–15], the
results of the present investigation uphold the hypothesis that there are critical training
differences between the sexes of recreational endurance runners of various distances (HM,
M/UM, 10 km).
Based on the previous literature concerning female and male runner anthropometric
differences [12], the present ﬁndings are consistent, indicating that females are generally
smaller than their male counterparts. Moreover, the participants’ anthropometrics (body
weight, height, BMI), especially of the females, highlight the general knowledge of recre-
ational runners being a slim, ﬁt, and healthy population [2–4,28,34]. All the while, only 3 of
the initial participants (<0.01% of the sample) reported having obesity and were excluded
from this study due to the required WHO-based BMI criteria [31,32]; thus, the typical
healthy runner training and race preparation lifestyle is reﬂected by the participants’ BMI
within this study [2–4,28,34].
A signiﬁcant difference was found in this study in the proportions of race distance
subgroups between the sexes, with the largest proportion of females being 10 km runners
and a remarkably larger proportion of males being M or UM runners. Until recent years,
female event participation in very long distances (HM, M, or UM) has been trailing that of
males [35], and this result may be a reﬂection that this difference between the sexes has not
been completely mitigated. Considering that the males were more heavily proportioned
among the longer-distance racing subgroups (HM, M/UM), and that the previous litera-
ture has shown considerable variation in runner training behaviors based on this factor
alone [15], it could be expected that there are signiﬁcant critical sex differences in training
behavior of endurance runners.
Furthermore, it was found that signiﬁcantly more females were training under the
direction of a professional (whether a sport scientist, doctor of sports medicine, or trainer)
or followed another resource rather than training alone and independently, which was
more common among the males. This ﬁnding could be related to a generally higher level
of health consciousness among females, while professional support is well-known to be
beneﬁcial for the health of runners and especially injury prevention [3,4,36]. In addition,
while participation was similar in most other sports activities to balance running (cycling,
swimming, rambling, triathlon, skiing, cross country skiing, and snowboarding), a sex
difference for fell/trail running and ski-touring was detected. Regarding the ﬁnding of
signiﬁcantly more male participation in fell/trail running, a previous study found the
opposite [37]; however, that report only analyzed runners of a speciﬁc trail race, and the
current sample was more general [25]. Ski-touring, on the other hand, predominantly takes
place in the backcountry with advanced-level terrain and increased avalanche risk; thus,
one possible explanation for more male ski-touring participation may be a higher risk-
seeking tendency among males [38]. Furthermore, no sex difference in the training duration
for the main event was found, which could be considered the overarching periodization
scheme [22]. This ﬁnding may be due to the fact that participating in an endurance running
Int. J. Environ. Res. Public Health 2022, 19, 13238
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event requires a minimal preparatory period to safely complete each event, which is likely
dependent upon the event race distance (e.g., 10 km, HM, M, or UM) [15,39].
Regarding the breakdown of the training periodization into three distinct phases
(Phase A: Regeneration Stage and Transitional Period; Phase B: Preparatory Period; Phase
C: Main Competition Period), no sex difference in the weekly frequencies of training was
detected. Therefore, regardless of sex, participants trained regularly throughout each week
and training phase, possibly due to the fact that regular exercise is well-accepted as being
healthy and provides a plethora of beneﬁts to each individual [34,40]. Within Phase A,
no sex differences in weekly training mileage or duration were found, which is likely
due to this particular phase having a main focus of recovery to avoid overloading as it
comes directly after participating in the previous main event [41]. Therefore, it would
be expected that the participants’ characteristics are somewhat unrelated to training in
this phase, as the major goal of this phase is proper regeneration and a smooth transition
to the main preparatory period [41]. However, signiﬁcant differences between the sexes
regarding their daily training mileages and daily training durations in Phase A were found,
suggesting that males run a greater distance per day and also spend a greater amount
of time running per day than females during this period. This ﬁnding is possibly due to
the greater professional advice sought by females, as more resting is highly advisable for
achieving maximal recovery during this period, which may be a concern of overuse injury
or burnout for males who are seeking less professional support for training [41,42].
Within Phase B, there are four preparatory stages with distinct training characteristics.
Weekly training mileages and durations were similar for females and males during Prepara-
tory Stages 2 and 3, whereas signiﬁcant sex differences were found for Stages 1 and 4.
Considering the training similarities between the sexes in Stage 2 (build-up training, includ-
ing speciﬁc basic training, and at a low-to-moderate intensity) and Stage 3 (intervals, pace,
speciﬁc competition training, and moderate-to-high intensity), it appears that the training
run distance and duration are unrelated to sex. Therefore, these particular types of weekly
exercises may be integral to the training plans of endurance runners regardless of sex,
which is consistent with previous reports [8,11]. For Stage 1 (general basic training at a low
intensity mainly) and Stage 4 (test competition, race-speciﬁc training, and moderate-to-high
intensity); however, the discrepancies between the sexes for weekly mileages and durations
are likely related to the previously mentioned result of more females racing in the shorter
distance (10 km) and more males racing in longer distances (M/UM) [15]. Furthermore,
and in connection, both the daily training mileages and daily training durations showed
signiﬁcant differences between the sexes across all four stages of Phase B. Considering that
runners of longer distances have been shown to run further mileage while training [15],
these Phase B mileage differences between the sexes likely arise from the result that the
males race over longer distances. Regarding Stage 1, the general basic training at a low in-
tensity is dominant in the long-distance runner’s training plan (M/UM) [15,43,44], and the
present results show that males run remarkably more during this period with an additional
2.94 km per day (+0.14 h). Previous research has found performance and health beneﬁts to
sustained loads of low-intensity training, including left ventricular hypertrophy and the
consequential enhancements to stroke volume, maximal volume of oxygen consumption,
and thus lower resting heart rate [45]. Indeed, moderate-to-high intensity training at Stage
4 would require extensively longer bouts of mileage and duration for the longer-distance
runner to meet their adaptive training thresholds for building mitochondrial density and
capillarization [44,46]. Previous research has not found any major link between sex and
volume of oxygen consumption training adaptations [46]. For Stage 4, the speciﬁc training
types (including test competition and race-speciﬁc training) are less likely to be related
to beneﬁcial physical adaptations but are rather mental preparations, which are highly
important for the longer-distance runner, as very long distances (M/UM) require extensive
durations of focus [47,48]. Therefore, the training durations (weekly or daily) would appear
to be dependent upon the mileages (weekly or daily), as increases in the distance load
require more time to complete with a speciﬁed running intensity [15].
Int. J. Environ. Res. Public Health 2022, 19, 13238
11 of 14
Results for Phase C, which was considered the main competition period and included
tapering and interim race stage/s, show that there was no sex difference for weekly
training mileage or duration, which may be due to this phase including tapering, and the
consequential drastic reduction in weekly training volume for both females and males
compared to the prior phases [49]. However, considering that this phase also included
interim race stage/s, which are likely related to the main event race distance, there may
be a connection to the signiﬁcant sex differences identiﬁed for daily training mileage and
duration [15].
Exercise motivations may underlie much of the participatory behavior in endurance
running [3,50]. The present results are in line with previous ﬁndings, that the male exercise
focus is more sport performance-oriented than females and that females are more focused
on health [50]. Regarding the ﬁnding of leisure as the female’s main exercise focus, this
result is somewhat inconsistent with previous literature [50], which suggests that females
are primarily health-focused. However, no signiﬁcant sex difference was identiﬁed in terms
of the participants’ current running motivations, which could partly explain why there
were also some training similarities between the sexes within the current results. Therefore,
it is possible that a small fraction of participants considered themselves to be athletes of
another main sport instead of running.
Causal ascriptions have been suggested as the foundation for developing a theory
of motivation and emotion [51]. Therefore, it appears achievement-related projections,
which are plausibly socio-bounded, have a major inﬂuence on the exercise focus differences
among females and males [50,51]. In our sample, 96% of participants were from Austria,
Germany, and Switzerland, suggesting a rather homogenous group in terms of social
culture [52]. Those German-speaking countries are reported to have advanced economies
even compared to other western nations, and the results indicate no sex difference in
academic qualiﬁcation, including a predominantly white-caucasian population with high-
income levels, high quality of life, and a high life expectancy [52,53].
Comparable to other studies that follow a cross-sectional design, the presented results
include some limitations that should be addressed when interpreting the ﬁndings. The
sample size was relatively small, and considering the sex-based approach of the present
investigation, there was an unequal distribution of sexes per se (58% females), and also
within the race distances, including more females (48% vs. 23% of males) as 10 km runners.
However, most of the participants were racing at the HM distance, marathon, or ultra-
marathon distance. As the results are based on self-reporting survey methods, over-
and under-reporting of answers are possible based on the sociological expectations of the
participants’ cultures; however, control questions (e.g., race distance) were used to minimize
this effect. Lastly, most participants were from Germany, Austria, and Switzerland, which
may limit the interpretation of some of our ﬁndings to Western and European running
cultures.
While the present investigation includes some limitations, the results have the potential
to add light to this speciﬁc gap in the current literature on sex differences in training
behaviors of 10 km up to ultra distance recreational runners. Upon careful consideration,
the ﬁndings may be particularly beneﬁcial for athletic trainers, physical therapists, coaches,
team physicians, exercise physiologists, and endurance runner athletes to reﬁne the vital
understanding of planning and applying an optimal, health-based training regimen for
successfully running races. Furthermore, the underrepresentation of females in previous
athletic samples studied regarding targeted sex-speciﬁc approaches and personalization
to training and performance requirements is evident [5,6,22]. In addition, future studies
should consider investigating sex differences of endurance runners by controlling for main
event race distance associated with runner motives.
5. Conclusions
In summary, this is the ﬁrst study aiming to investigate sex differences in training
and race preparation behaviors of recreational runners of various distances, including HM,
Int. J. Environ. Res. Public Health 2022, 19, 13238
12 of 14
M/UM, and 10 km participants. The results indicate that: female runners are more likely
to train with an external resource; male runners train at a higher volume (greater daily
mileages and durations at every periodization phase; greater or null weekly mileages and
durations at each phase); females exercise with more leisure focus; and males concentrate
more on sports performance. It can be concluded that sex differences in training behaviors,
which may originate from physiological differences and social expectations, can be related
to the distances runners prefer to race and their motivations for running and racing. The
results of this study provide a wide overview of the fundamental training behaviors of
female and male recreational endurance runners of various distances (HM, M, UM, 10 km)
that may be remarkably supportive for carefully designing and implementing a thorough
training plan for endurance runners themselves or by their coaches, exercise physiologists,
athletic trainers, physical therapists, sport scientists, or sports medicine doctors.
Author Contributions: K.W. conceptualized and designed the study and the questionnaires together
with B.K. and C.L. K.W. conducted data analysis and D.T. and M.M. provided statistical expertise.
D.T., K.W., T.R. and B.K. drafted the manuscript. T.R., M.M., C.L. and K.W. critically reviewed it. G.W.
provided technical support and aided in data acquisition and 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 May 6, 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
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 Training Behaviors of 10 km to Ultra-Endurance Runners (Part A)-Results from the NURMI Study (Step 2).
Tanous, Derrick,Motevalli, Mohamad,Wirnitzer, Gerold,Leitzmann, Claus,Rosemann, Thomas,Knechtle, Beat,Wirnitzer, Katharina