Prevalence of Female and Male Vegan and Non-Vegan Endurance Runners and the Potential Associations of Diet Type and BMI with Performance—Results from the NURMI Study (Step 1)

study aims to investigate vegetarian and mixed diet type prevalences among distance runners at running events around the world and associations with running-related patterns and performance. Following a cross-sectional approach, linear regression analyses were carried out to identify potential associations among body mass index (BMI), diet type, and average best performance times of half-marathon and marathon events for males and females. From a sample of 3835 runners who completed an online questionnaire, 2864 all-distance runners (age: 37 years; 57% females) were included in inferential analyses

performance. Following a cross-sectional approach, linear regression analyses were carried out to identify potential associations among body mass index (BMI), diet type, and average best performance times of half-marathon and marathon events for males and females. From a sample of 3835 runners who completed an online questionnaire, 2864 all-distance runners (age: 37 years; 57% females) were included in inferential analyses and categorized into dietary subgroups according to self-reports: 994 vegans (34.7%), 598 vegetarians (20.9%), and 1272 omnivores (44.4%). Signi cant associations were identi ed between kind of diet and best average time to nish (i) half-marathons in females where vegans (p= 0.001) took longer than omnivores, (ii) half-marathons in males where vegans (p< 0.001)and vegetarians (p= 0.002) took longer than omnivores, and (iii) marathons in males where vegans (p< 0.001) and vegetarians (p= 0.043) averaged slower than omnivores. Increased units of BMI (+1.0) in males in uenced best runtimes: 2.75 (3.22–2.27) min slower for HM and 5.5 (5.69–4.31) min slower for M. The present study did not take detailed confounders into account such as runner motives or training behaviors; however, the results may provide valuable insight for running event organizers, nutrition experts, coaches, and trainers advising runners who adhere to a general diet type regarding the basic question of who participates in running events around the world. Keywords: plant-based; diet; recreational; training; performance; running; half-marathon; marathon; ultra-marathon 1. Introduction Distance running is a highly popular sport and healthy activity with millions of participants worldwide [1]. There are a variety of distance events (mainly 5 km, 10 km, half- marathon, marathon, and ultra-marathons) to take part in for accommodating every interest and physique [2]. Globally, a data report from the Strava 2021 Year in Sport, which included 95 million athletes, revealed that runners logged a total of 2.4 billion miles [3], and other reports have found that more than 100 million Europeans and US Americans combined are Nutrients2022,14, 3803.

Nutrients2022,14, 3803 2 of 16 active runners [4,5]. Among the top ve greatest marathon events on the global scale, the New York City Marathon ranks number 1, breaking the 50,000 benchmark with a total of more than 50,770 starters [6]. With such great interest, it is not surprising that the World Marathon Majors series includes six-city marathon events in Tokyo, Berlin, London, Boston, New York, and Chicago, comprising a total of more than 221,000 participants at the starting lines with over 180,000 completing all six events [7,8]. The massive participation and wide sociodemographic variety make distance running a particularly interesting area within endurance sports for scienti c investigations [9]. According to the largest study of race results ever recorded up to 2018, running event participation has increased by 57% over the last decade [10]. In addition, the average nish- ing times have dramatically changed for females and males across race distances since 1986, even though groundbreaking technologies such as `carbon ber plate shoes' from sports companies may have led to the fastest marathon times ever recorded [10,11]. The slower average run times are likely due to a shift in the main motives of running participation in the direction of health (10%) and leisure (54%) instead of performance (36%) [12,13]. The most vital motive for running across sexes and all ages is the general health orientation and expectation of marked improvements to health [13,14], considering older runners at or above the age of 50 mainly follow running regimes for health maintenance and for preventing lifestyle diseases [15]. According to a recent survey conducted by ASICS, the tremendous impact of the COVID-19 pandemic in societies worldwide appears to have pushed the running motive shift even further toward the bene ts for mental health [16]. As a natural low-intensive locomotion pattern, distance running requires, on the one hand, the appropriate fuel to perform best and most comfortably, and—as outrunning competitors is the goal of the sport—on the other hand, the motto, `higher, faster, further' applies [13,17]. Nutrition is a basic variable to consider for every runner. Currently, the inconsistency of recommendations on what

health [16]. As a natural low-intensive locomotion pattern, distance running requires, on the one hand, the appropriate fuel to perform best and most comfortably, and—as outrunning competitors is the goal of the sport—on the other hand, the motto, `higher, faster, further' applies [13,17]. Nutrition is a basic variable to consider for every runner. Currently, the inconsistency of recommendations on what to eat for athletes and for health is overwhelm- ing among major sports and nutritional bodies, such as the American College of Sports Medicine [18] or the British Dietetic Association [19]. However, in the world of running, reports of general diet type categories prevail among athletes, such as vegan (plant-based, excluding all animal products), vegetarian (partially plant-based, excluding animal esh), or omnivorous diets (inclusive of plant and animal sources, including animal esh, sh, dairy, egg, etc.) [20]. A current study that analyzed over 2 million Facebook posts across 132 countries found the sustainable, plant-based lifestyle interest as high as 18%, con rming the increasing trends forecasted previously by major analysts [21]. While the popularity of plant-based kind of diets is spreading faster than expected [22], anecdotal evidence among competitive athletes promoting vegan and vegetarian nutri- tion may be driving this accumulation [17]. Hence, vegan–vegetarian diets are currently booming in recreational and competitive sports [17]. Professional vegan endurance runners include Fiona Oakes (ultra-marathon running, set her fourth marathon world record in 2018) [23] and Scott Jurek (set multiple records, including the fastest Appalachian Trail completion of 2189 miles in 46 days, 8 h, 7 min in 2015) [24]. As cumulative evidence connecting the safety and bene ts of plant-based diets for endurance sports arises, the consequence is that every social group or sports team will consist of at least one vegan person or athlete [17,25]. It is often believed among the public that when prepping for long-distance events, it is necessary to train with lengthy endurance runs the days and weeks before the planned running event to meet the high workload demands [26,27]. Inadequately increasing the training load may result in adverse health outcomes, including chronic pain and running- induced injuries

person or athlete [17,25]. It is often believed among the public that when prepping for long-distance events, it is necessary to train with lengthy endurance runs the days and weeks before the planned running event to meet the high workload demands [26,27]. Inadequately increasing the training load may result in adverse health outcomes, including chronic pain and running- induced injuries [28], rather than enhancing performance and guaranteeing success [1]. Considering the physical and physiological differences between male and female endurance athletes [29], sex has been reported to be an indicator of training/racing behaviors and nutritional patterns of endurance athletes [30,31]. Speci cally, evidence shows that sex- based differences in endurance performance may be in uenced by race distance [32] and diet type [33]. Regardless of sex, consultation with a specialized professional in

Nutrients2022,14, 3803 3 of 16 running could be highly bene cial for health, training adaptations, and performance in runners [34,35]. In this regard, it has been reported that endurance athletes of lengthy distances, marathoners and ultra-marathoners, for example, are more likely to consult with performance specialists such as sport scientists and sports medicine doctors [36]. A recent study found around 10% prevalence of vegan or vegetarian diets among marathoners [37]. While there is an expanding prevalence of plant-based diets, notably among endurance runners, there are only limited data considering this topic [38,39]. Given the background numbers, plant-based athletes are no longer a fringe group, and thus, the importance of providing data to overcome the lack of information as well as practical knowledge for expanding individualized training and nutritional strategies appears to be crucial to examine the associations between diet type and running-related characteristics in a large sample of vegan and non-vegan endurance runners. To date, there have been several studies conducted on endurance performance linked to vegan/vegetarian diets [12,25,40–44], but the results are yet to be conclusive and have found little to no differences. Moreover, investigations have also studied the training habits of distance runners among various race lengths, whether distinctly [45,46] or comparatively [36,40]. However, no study has, to date, examined the prevalence of different diet types among distance runners attending running events worldwide and their associations with running performance concerning women and men separately. Therefore, the present study aimed to investigate the prevalence, sociodemographic, and anthropometric comparisons of endurance runners from anywhere in the world and identify potential relationships with racing performance among females and males following vegan and non-vegan diets based on a large sample. The present investigation hypothesizes that there is a difference in best time racing performance at half-marathon and marathon recreational events based on diet type. 2. Materials and Methods With a cross-sectional design, The Nutrition and Running High Mileage (NURMI) Study was arranged in three steps. It was created as a follow-up to a previous study on vegan ultra-endurance mountain biking over eight consecutive stages [47,48] and is considered the largest study of

racing performance at half-marathon and marathon recreational events based on diet type. 2. Materials and Methods With a cross-sectional design, The Nutrition and Running High Mileage (NURMI) Study was arranged in three steps. It was created as a follow-up to a previous study on vegan ultra-endurance mountain biking over eight consecutive stages [47,48] and is considered the largest study of running in Europe (www.nurmi-study.com/en, accessed on 14 September 2022). The methodology of NURMI Study Step 1 was described in detail (ethics approval, participant recruitment, etc.) elsewhere [49]; in short, as preliminary study using a cross-sectional approach, Step 1 aimed to evaluate the prevalence and basic characteristics of running and racing behavior of vegan and non-vegan recreational runners who are active in events (all distances, all levels from recreational to elite). The interested reader is referred to all NURMI Step 1 publications for further details [36,38,40]. A short online survey offered in English and German within the NURMI Study Step 1 had to be completed by participants. Although the core regions for study sample recruitment were European countries, the NURMI Study's information, including an online survey, was spread across the globe for the international runner community. The survey was introduced with a written procedural description, and informed consent of participants was required to take part in the study. Afterwards, they completed the survey, which included basic and complementary questions and controlled for diet type and running activity. Basic questions were on sociodemographic attributes, current adherence to a speci c diet type (with a minimum adherence of at least six months), and distances being active in running (training, races). Along with the basic questions for the classi cation of participants, including (i) adherence to current diet (mixed, vegetarian, vegan) along with its duration of ad- herence and (ii) the preferred running distance for events, runners were asked to provide complementary data about their sociodemographic and anthropometric characteristics, food intake of speci c items, dietary (inclusive uid) intake on race days, weekly time spent in running training), period of time to prepare for the main running event, aim of partaking in a running

duration of ad- herence and (ii) the preferred running distance for events, runners were asked to provide complementary data about their sociodemographic and anthropometric characteristics, food intake of speci c items, dietary (inclusive uid) intake on race days, weekly time spent in running training), period of time to prepare for the main running event, aim of partaking in a running race (performance vs. enjoyment approach), preparation strategies for com- petition, event participation over several distances (<21 km, half-/full-/ultra-marathon),

Nutrients2022,14, 3803 4 of 16 number of successfully completed speci c distances, and individual best runtime over the respective distances. All basic and complementary data were collected based on a self-report approach using online questionnaires. Diet quality and personal running moti- vations were not included as a part of this investigation. For successful study participation, ve inclusion criteria were initially required to be ful lled in order to be included in the nal sample: written informed consent (1), minimal age of 18 years (2), Step 1 questionnaire completed (3), participating and completing at least one running event over 5 km distance in the past two years (4), and being active in running-related physical activities associated with the self-reported race distance (5). Participants meeting all inclusion criteria were registered in the study to avoid a permanent loss of valuable data, which aided in a larger sample and increased the data representation provided for the current results. For exclusion criteria, the BMI-associated approach based on the WHO [50,51] was implemented to regulate for a minimum status of health and a minimal level of tness and further aid in enhancing the reliability of data sets. According to the WHO [50,51], increased health risk results from a body mass index (BMI) higher than BMINORM(range: 18.50–24.90 kg/m 2 ; that corresponds to achieving an optimum state of health) is specified for co-morbidities at a BMI of 25.0–29.9 kg/m 2 and moderate-to-severe co-morbidities at a BMI > 30 kg/m 2 [50,51]. Other health protective strategies besides running are required for people with a BMI 30 to safely reduce body weight (BW) first [43]. Therefore, the calculated BMI (BMICALC) was classified into three categories (kg/m 2 ): 18.49 < BMINORM 25, and participants with a BMI 30 were excluded. Additionally, as a second exclusion criterion for the present investigation, runners must have reported their best time for completing a half-marathon or marathon. Dietary subgroup classi cation of participants was based on the following groups: omnivorous (also known as the Western diet, includes no dietary restriction), vegetarian (no consumption of meat or sh), or vegan (no consumption of

were excluded. Additionally, as a second exclusion criterion for the present investigation, runners must have reported their best time for completing a half-marathon or marathon. Dietary subgroup classi cation of participants was based on the following groups: omnivorous (also known as the Western diet, includes no dietary restriction), vegetarian (no consumption of meat or sh), or vegan (no consumption of products from animal origin: meat, processed meat, sh, seafood, shell sh, milk, dairy products, eggs, or honey) [20]. Participants must have followed their respective diet for the minimum duration of 6 months to be included in the omnivore, vegetarian, or vegan subgroup. Moreover, participants were initially categorized into three subgroups regarding race distances: half-marathon (HM), marathon (M), and ultra-marathon (UM, distances longer than a marathon). The minimum ultra-marathon race completed was 50 km, and the longest race was 160 km. To regulate for HM or M race completion, the participants best HM or M times were checked and con rmed by random sample selection. In addition, 622 highly motivated runners that had not successfully nished at least a half-marathon race before but instead competed in shorter distances (<21 km, mainly 5 km, 8 km, and 10 km) provided accurate and high-quality data. To avoid a permanent data loss of the shorter than half-marathon distance runners, those who met all inclusion criteria were pooled together as an additional race distance subgroup. Statistical analysis was performed by the statistical software R version 4.1.1(2021-08-10), Core Team 2021 (R Foundation for Statistical Computing, Vienna, Austria). The descriptive statistics were summarized using means and standard deviations (SD) as well as medians and interquartile ranges (IQR). Univariate analysis was used to describe the distribution of recreational runners considering diet type and was conducted with the Chi-square test ( 2; nominal items) and Kruskal–Wallis test (ordinal and metric items) to examine the association between dietary subgroups (F distribution was used for approximation). Multiple linear regression analyses were used to examine signi cant differences in performance of races (best time over the half-marathon and marathon distances) and were strati ed by sex, while BMI was considered the potential

test ( 2; nominal items) and Kruskal–Wallis test (ordinal and metric items) to examine the association between dietary subgroups (F distribution was used for approximation). Multiple linear regression analyses were used to examine signi cant differences in performance of races (best time over the half-marathon and marathon distances) and were strati ed by sex, while BMI was considered the potential confounder. Inspection of the graphs of predicted vs. residual and normal Q-Q residual plot was performed to verify the assumptions of the regression analysis. Dietary subgroup-related differences by race distance of runners are shown with

Nutrients2022,14, 3803 5 of 16 effect plots strati ed by sex (con dence interval set at 95% (95%-CI)); predictor effects and 95%-CI were calculated with the R effects package. The statistical signi cance level was set atp 0.05. 3. Results A total of 3835 runners submitted the survey with complete statements and a returning response rate of 52% of all that started lling in the online survey. Of these, 43 participants were excluded due to inconsistent or con icting data sets, and 833 participants did not meet the basic inclusion criteria, 95 of whom were excluded due to reporting a BMI of 30. Ultimately, 2959 all-distance runners were considered the sample for descriptive analysis, and 95 runners were excluded before regression analysis due to the lack of information on running races and/or half-marathon and marathon best times. The nal sample of endurance runners in the statistical analysis included 2864 t participants (57% female) from around the world, including Europeans (n= 2789) primarily but also a total of 75 non-Europeans: North and South Americans (n= 70), Asians (n= 4), and one answer was not speci ed. Figure Step 1.Nutrients 2022, 14, x FOR PEER REVIEW 5 of 16 analyses were used to examine significant differences in performance of races (best time over the half-marathon and marathon distances) and were stratified by sex, while BMI was considered the potential confounder. Inspection of the graphs of predicted vs. resid- ual and normal Q-Q residual plot was performed to verify the assumptions of the regres- sion analysis. Dietary subgroup-related differences by race distance of runners are shown with effect plots stratified by sex (confidence interval set at 95% (95%-CI)); predictor ef- fects and 95%-CI were calculated with the R effects package. The statistical significance level was set at p ≤ 0.05. 3. Results A total of 3835 runners submitted the survey with complete statements and a return- ing response rate of 52% of all that started filling in the online survey. Of these, 43 partic- ipants were excluded due to inconsistent or conflicting data sets, and 833 participants did not meet the basic inclusion

The study examines diet types among endurance runners and their impact on performance.