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Many Non-elite Endurance Multisport Athletes Do Not Meet

Sports Nutritional Recommendations for Carbohydrates

Journal: Applied Physiology, Nutrition, and Metabolism

Manuscript ID apnm-2015-0599.R1

Manuscript Type: Article

Date Submitted by the Author: 08-Jan-2016

Complete List of Authors: Masson, Geneviève; INAF - Universite Laval, Faculty of Agriculture and Food Sciences Lamarche, Benoît; Université Laval, INAF

Keyword: dietary intake < diet, sports nutrition < nutrition, triathlon, carbohydrate, protein

https://mc06.manuscriptcentral.com/apnm-pubs

Applied Physiology, Nutrition, and Metabolism

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Many Non-elite Endurance Multisport Athletes Do Not Meet Sports Nutritional

Recommendations for Carbohydrates

Authors

Geneviève Masson1, Benoît Lamarche1

1. Institute of Nutrition and Functional Foods (INAF), Laval University, 2440 Hochelaga

Blvd, Quebec, QC, Canada

Corresponding author:

Benoît Lamarche Ph.D. Institute of Nutrition and Functional Foods (INAF) Pavillon des Services, bureau 2549 2440 Hochelaga Blvd. Quebec, Canada G1V 0A6 Tel.: (418) 656-2131 ext. 4355, Fax: (418) 656-5877 E-Mail: [email protected] GM: [email protected] BM: [email protected]

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Abstract

Little is known regarding the dietary intakes of non-elite athletes involved in endurance

multisport events. The primary objective of this observational study was to characterize

the dietary intake of non-elite athletes participating in winter triathlon (snowshoeing,

skating and cross-country skiing), winter pentathlon (winter triathlon sports + cycling and

running), Ironman (IM- swimming, cycling, running) and half-distance Ironman (IM70.3)

in relation with current sports nutrition recommendations. A total of 116 non-elite athletes

(32 women and 84 men) who have participated in one of those events in 2014 were

included in the analyses. Usual dietary intake was assessed using an online validated

food frequency questionnaire. Participants (22-66 years old) trained on average (± SD)

14.8 ± 5.3 hours/week. Only 45.7% [95% confidence interval, 36.4-55.2%] of all athletes

reported consuming the recommended intakes for CHO, with highest proportions

(66.7%) seen in IM athletes. On the other hand, 87.1% [79.6-92.6%] of all non-elite

athletes reported consuming at least 1.2 g protein/kg/d while 66.4% [57.0-74.9%]

reported consuming more than 1.6 g protein/kg/d, again with highest values (84.6%)

among IM athletes. There was no difference in the proportion of athletes achieving the

CHO and protein intakes between men and women. These findings suggest that many

endurance multisport non-elite athletes do not meet the current recommendations for

carbohydrates, emphasizing the need for targeted nutritional education. Further

research is needed to examine how under-reporting of food intake may have affected

those estimates.

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Keywords

Endurance sports nutrition, triathlon, multisport event, dietary intake, carbohydrate,

protein.

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Résumé

Peu d’études ont documenté les apports alimentaires d’athlètes d’endurance de niveau

non-élites participant à des épreuves multisports. Cette étude visait à évaluer les

apports alimentaires d’athlètes non-élites prenant part à un triathlon d’hiver (raquette,

patinage et ski de fond), pentathlon des neiges (sports du triathlon d’hiver + vélo et

course à pied), Ironman (IM – natation, vélo et course à pied) et demi-Ironman (IM70,3)

par rapport aux plus récentes recommandations en nutrition sportive. Au total, 116

athlètes non-élites (32 femmes et 84 hommes) ayant participé à une des ces épreuves

en 2014 ont été inclus dans les analyses. Les apports usuels ont été évalués à l’aide

d’un questionnaire de fréquence alimentaire en ligne validé. Les participants (22-66 ans)

s’entrainaient en moyenne (±É-T) 14,8±5,3 heures/semaine. Seulement 45,7%

[intervalle de confiance 95%, 36,4-55,2%] des athlètes ont rapporté avoir des apports en

glucides supérieurs à la valeur recommandée pour les sports d’endurance (6 g/kg/j). Par

ailleurs, 87.1% [79.6-92.6%] et 66.4% [57.0-74.9%] des athlètes non-élites ont rapporté

consommer plus de 1.2 g protéines/kg/j et 1.6 g protéines/kg/j respectivement. Les

athlètes IM sont ceux qui rencontrent en plus grande proportion les recommandations

en glucides (66.7%) et en protéines (84.6%). Il n’y avait pas de différence dans le

pourcentage d’hommes et de femmes qui rencontraient les recommandations en

glucides et protéines. Ces résultats suggèrent que plusieurs athlètes d’endurance

multisports non-élites ne rencontrent pas les recommandations en glucides, soulignant

les besoins en éducation nutritionnelle dans cette population. L’impact possible d’une

sous-estimation des apports alimentaires doit être investigué davantage.

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Mots clés

Triathlon, sports d’endurance, évènement multisports, protéine, glucide, apport

alimentaire

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Introduction

Endurance multisport events have recently gained in popularity. The number of

long distance triathlon events such as half-Ironman (IM 70.3) (1.9 km swim, 90 km bike,

21.1 km run) and Ironman (IM) (3.8 km swim, 180 km bike, 42.2 km run) has increased

in the past years, attracting more and more non-elite athletes (Whyte 2014).

Competitions combining different sports held in winter conditions also attract more non-

elite athletes than ever before. The Pentathlon des Neiges (PENT) is a relatively new

winter event that is not yet as standardized as the IM events, consisting of cycling (with

distance ranging from 9-15 km), running (3.6-5.5 km), cross-country skiing (4.9-8 km),

ice-skating (5-8.4 km) and snowshoeing (3.4-5.1 km). The Quebec ITU Winter Triathlon

(ITU TRI) includes 5 km of snowshoeing, 12 km of ice-skating and 8 km of cross-country

skiing).

In order to compete in such multisport endurance events, athletes have to train

for different sports (i.e. swimming, biking and running) over long hours, sometimes with

multiple exercise sessions a day (Jeukendrup et al. 2005). With an average weekly

training time of 14 hours (Gianoli et al. 2012; Rust et al. 2013), non-elite endurance

multisport athletes have high energy expenditures (Bentley et al. 2008; Jeukendrup et al.

2005). Athletes are advised to consume a nutrient dense diet that provides enough

energy to achieve energy balance (Rodriguez et al. 2009) while maximizing training

adaptions and optimizing recovery between exercise sessions.

Authors have suggested that recommendations regarding dietary carbohydrates

should be expressed relative to body weight rather than as a proportion of the daily

energy intake (Burke et al. 2001). Daily carbohydrate needs of endurance athletes who

train between 1 to 3 hours a day have been estimated at 6 to 10 g/kg of body weight

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(Burke et al. 2011; Rodriguez et al. 2009). Recommendations for daily protein intake for

endurance athletes range from 1.2 to 1.4 g/kg of body weight (Rodriguez et al. 2009).

However, some athletes may need as much as 1.6 g protein/kg of body weight to

achieve neutral nitrogen balance (Brouns et al. 1989a; Brouns et al. 1989b; Friedman

and Lemon 1989; Tarnopolsky 2004; Tarnopolsky et al. 1988).

Although dietary intakes of elite and non-elite cyclists and runners during training

have been documented quite extensively, less is known regarding dietary intakes of

non-elite multisport endurance athletes. To the best of our knowledge, no study has yet

documented the dietary intake of winter multisport endurance athletes. The main

purpose of this observational study was to assess the dietary intake of non-elite

multisport endurance athletes during the weeks leading to their competition, with

particular focus on proteins and carbohydrates. More specifically, we assessed the

degree to which participants meet the most recent dietary recommendations for

endurance sports, with interest in potential differences between male and female

athletes and among multisport endurance events. We hypothesized that a majority of

non-elite multisport endurance athletes meets the recommended intakes for protein and

carbohydrates and that intake is influenced by sex and event type.

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Methods

Participants

To be eligible for this study, athletes had to be 18 years and older. They also had

to compete in an age-group category of one of the following multisport endurance

events: Pentathlon des Neiges 2014 tandem or solo categories (PENT) (9-15 km of

cycling, 3.6-5.5 km of running, 4.9-8 km of cross-country skiing, 5-8.4 km of ice skating

and 3.4-5.1 km snowshoeing), Quebec ITU Winter Triathlon in 2014 (ITU TRI) (5 km of

snowshoeing, 12 km of ice skating and 8 km of cross-country skiing), Ironman 70.3

triathlon held in Mont-Tremblant in 2014 (IM 70.3), Ironman 70.3 World Championships

held in Mont-Tremblant in 2014 (WC IM 70.3) or in the Ironman Triathlon held in Mont-

Tremblant in 2014 (IM). Athletes were recruited through events’ emailing list, Triathlon

Québec (Quebec Federation of Triathlon) members’ emailing list and by the presence of

one of the investigators on competition site. A total of 297 athletes were recruited. Of

this number, 160 subjects completed all questionnaires. All participants provided

informed consent either online or in written form. The Clinical Research Ethics

Committee of Laval University approved this study protocol (#2013-274).

Questionnaires

Athletes had to complete different online questionnaires, which were available in

French and in English. A general information questionnaire was used to obtain socio-

demographic information and to assess medical condition. A validated online food

frequency questionnaire (FFQ) available both in French and English was used to assess

food intake during the previous month (Labonte et al. 2012). A sports food and

supplement questionnaire was used to assess the frequency of use in the previous

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month as well as quantity of sports food and supplements typically consumed by

endurance athletes: sports gel and candies or chews, caffeine pills, sodium tabs,

hydration drinks and bars. An average nutritional value was calculated for each type of

supplement by using the nutritional facts of different brands of products available in

Canada and/or the United States. Energy and macronutrients intakes were calculated by

adding the dietary intakes provided by the FFQ and intakes related to the consumption

of sports foods and supplements. Training habits and history over the preceding month

were also assessed. More specifically, subjects reported total and sport-specific training

time along with the proportion of training done at intensity perceived as being higher

than 80% of maximal capacity. Subjects enrolled in the study provided their full names

and identified the sport event they participated in. The performance rank was calculated

as a percentile of the participant’s rank position in his/her age and sex category using

data publicly available on the Sportstats.ca website.

Statistical Analysis

All statistical analyses were performed with SAS (version 9.3; SAS Institute Inc., Cary,

NC, USA). A total of 41 participants completed the FFQ more than 14 days after

competing in their multisport event. They were excluded from the analyses because of

highly probable changes in dietary habit post event. The winter multisport events

(Pentathlon and ITI Triathlon) were combined as WINTER since type and duration of

events are similar, thereby increasing the sample size of the winter multisport event

group. Differences among sport event’s groups (groups) were assessed by ANOVA for

parametric variables and by Chi-Square for non-parametric variables. In case of

statistically difference with ANOVA, Duncan tests were also used to assess between-

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group differences. Student’s unpaired T-test and Chi-square test were used to assess

differences between sexes. Logistic regression analysis (P < 0.15 inclusion method) was

used to estimate the odds of meeting the dietary recommendations for carbohydrates

and proteins in the various groups. Models were adjusted for energy intake and

WINTER athletes were used as the reference group. Multiple regression analysis was

used to identify the main correlates of energy intake relative to body weight. Self-

reported energy intakes exceeding the group mean by two SD or more were considered

improbable and subjects with such values were excluded (N=3). To account for the

possibility of under-reporting, a sensitivity analysis was undertaken while considering

only participants with self-reported energy intake above their estimated energy

requirement (EER) based on conservative physical activity coefficients (PAL) for both

low active (EER LOW) and active (EER ACTIVE) levels for each participants (Health

Canada 2010). Two-tailed P values <0.05 were considered significant.

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Results

Subjects’ characteristics are presented in Table 1. More than one quarter of the

subjects included in the analyses were women (27.6%), the lowest proportion being in

the IM group. The majority of subjects (73.0%) were Canadians although differences in

nationality were observed among groups. Athletes recruited were aged from 22 to 66

years without significant difference in mean age between groups. Weekly training time

was significantly higher in athletes competing in IM and WC IM 70.3 than in other

groups. The WINTER group trained fewer hours than the other three groups, although

in relative terms at the highest perceived intensity. The mean performance rank by age

category (44% to 52%) was similar among all groups, and values reflected the non-elite

status of the participants. Most athletes (70.7%) occupied a full-time job at the time of

investigation. Small proportions of athletes reported having food intolerance (17.0%) or

particular food habits such as vegetarianism (12.7%), without difference among event

groups (P=0.31 and P=0.27, respectively, not shown). Women were more likely to report

having food intolerance (34.5% vs. 9.9%, P<0.01) and particular food habits (23.3% vs.

8.8%, P=0.04) in comparison with men.

Self-reported dietary intake data are shown in Table 2. On average, participants

completed the dietary questionnaires 6.4 days after the multisport event although the

completion time varied between 11 days before the sporting event to 14 days after. Total

energy intake (kcal/d) in IM athletes was significantly higher than in WINTER and IM

70.3 athletes, but similar to that reported by WC IM 70.3 athletes. Carbohydrate intakes

(in g/d and in g/kg/day) were significantly higher in IM athletes than in the other three

multisport groups. Protein intakes in g/kg/d were higher in WC IM 70.3 and IM athletes

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than in WINTER athletes. Sports food and supplements contributed approximately 8.3%

of total energy intake, mostly in the form of carbohydrates. Sports food and supplements

contributed only 2.8% of total protein intake, without significant differences among

groups. The different categories of supplements used by athletes are shown in

supplementary table S1. Dietary fat contributed to a significantly greater proportion of

total energy intake in WC IM 70.3 athletes than in the other three multisport groups.

Alcohol intake in relative terms, but not in absolute terms, contributed a greater

proportion of energy intake among WINTER and IM 70.3 athletes than among IM

athletes.

Total energy intake was higher in men than in women (3501 ± 1192 kcal vs. 2652

± 731 kcal, P<0.01), but energy intakes relative to body weight were similar between

sexes (men 47.7 ± 17.0 vs. women 45.4 ± 13.5 kcal/kg/d, P=0.50). Carbohydrate intakes

relative to body weight did not differ by sex (men 6.3 ± 2.5 g/kg/d vs. women 5.9 ± 2.1

g/kg/d, P=0.43), as were protein intakes relative to body weight (2.0 ± 0.7 g/kg vs. 1.8 ±

0.6 g/kg, P=0.21).

As shown in Figure 1 and Table 3, only 45.7% [95% confidence interval (CI),

36.4-55.2%] of athletes reported consuming the recommended intakes for CHO (≥ 6

g/kg/d), with no difference between sexes (P=0.50). Non-elite athletes competing in IM

and WC IM 70.3 showed the highest proportions of meeting the recommended intakes

for CHO (Figure 2). Energy intake relative to body weight was a significant correlate of

consuming 6 g CHO/kg/d or more (OR=1.31 per kcal/kg/day, 95%CI 1.17-1.45, P<0.01).

Thus, compared with WINTER athletes and after adjustment for energy intake in

kcal/kg/d, IM and WC IM 70.3 athletes were not more likely to report consuming 6 g

CHO/kg/d or more (OR=0.87 [95%CI 0.10-7.59] and 0.08 [95%CI 0.01-1.07]

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respectively). Neither self-reported food intolerance (P=0.43) nor particular food habits

(P=0.25) were associated with meeting the CHO recommendations.

As shown in Figure 1 and Table 3, 87.1% (95%CI 79.6-92.6%) of all non-elite

athletes reported consuming at least 1.2 g protein/kg/d while 66.4% (95%CI 57.0-74.9%)

reported consuming more than 1.6 g protein/kg/d. There was no significant difference

between men and women in the proportions of athletes meeting these recommendations

for dietary protein. Similarly, there was no difference among multisport groups for the

proportion of athletes meeting the 1.2g/kg/d recommendation for protein intake (P=0.96,

Figure 2). Energy intake relative to body weight was also a strong correlate of meeting

the recommended intakes for proteins, both at the lower limit of 1.2 g/kg/d (OR 1.58 per

kcal/kg/d, 95% CI 1.23-2.01, P<0.01) and at the upper-limit of 1.6 g/kg/d (OR 1.26 per

kcal/kg/d, 95% CI 1.15-1.38, P<0.01). Athletes who competed in IM (OR 23.1, 95%CI

2.1-261.6) and in WC IM 70.3 (OR 12.8, 95%CI 1.5-110.4) were more likely to achieve

the upper-limit of the recommended intakes for protein than WINTER athletes, even

after adjustment for energy intake in kcal/kg/d. Having particular food habits was not

associated with the prevalence of meeting the recommendations for proteins at the

lower-limit (P=1.00) or upper-limit (P=0.86). However, athletes with self-reported food

intolerance were less likely to reach the upper-limit of the protein intake recommendation

than those without food intolerance (P=0.02). When adjusted for sex and age, weekly

training volume in hours was a significant correlate of energy intake in kcal/kg,

explaining 13.7% of its variance (P <0.01).

Finally, as shown in Table 3, when considering only participants among whom

self-reported energy intake exceeded EER LOW (N=70) and EER ACTIVE (N=61), the

proportions of non-elite multisport athletes with CHO intake above the 6g/kg/d

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recommendation ranged from 73% to 77%. This implies that approximately 25% of non-

elite athletes are not achieving an intake of 6g CHO/kg/d even when the possibility of

under-reporting of food intake is taken into consideration. On the other hand, all non-

elite endurance athletes reported consuming 1.2g protein/kg/d or more once potential

under-reporters were excluded in this sensitivity analysis (Table 3). Interestingly, the

proportion of total energy provided as CHO and proteins was not influenced by the

purported degree of under-reporting (Table 3). This is consistent with the observation

that energy intake is the key determinant of achieving the recommended CHO and

protein intakes in endurance athletes.

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Discussion

To our knowledge, this is the first study to compare the dietary habits of non-elite

athletes participating in different multisport endurance events, including summer and

winter multisport events, during the training period leading to their competition. Only

46% of participants reported consuming carbohydrates in amounts equal to or above the

6g/kg/d recommendation for endurance athletes. On the other hand, the majority (88-

84%) of non-elite male and female athletes met the lower limit of the recommended

protein intake (1.2 g/kg). Those proportions were slightly lower (70% for men vs. 56% for

women) when considering the upper target of protein intake (1.6 g/kg). Athletes

competing in IM and WC IM 70.3 were more likely to meet the recommendations for

carbohydrates and the upper-limit of protein intakes than those competing in IM 70.3

and WINTER.

Suboptimal intake of CHO for endurance events is of great concern considering

the role of this key nutrient in performance (Hawley and Hopkins 1995), fuelling and

recovery (Achten et al. 2004; Simonsen et al. 1991). Athletes with sub-optimal

carbohydrate intakes may also be at increased risk of a perturbed immune function

(Burke et al. 2006), which may impaired both the quality of training and sport

performance in competition. A low proportion of non-elite athletes achieving adequate

CHO intake for endurance events has been observed previously (Burke et al. 2001).

However, unlike in previous studies (Burke et al. 2001; Burke et al. 2003) (Nogueira and

Da Costa 2004), there was no difference between men and women in self-reported

carbohydrates intakes (in g/kg/d) and in the proportion of athletes achieving the

recommended intakes.

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There was also no significant difference in self-reported intakes of protein relative

to body weight between male and female athletes, which is consistent with some

(Papadopoulou et al. 2012) but not all studies (Burke et al. 2003; McKenzie et al. 2000;

Nogueira and Da Costa 2004). Predictably, energy intake is the main factor predicting

protein intake in our sample, as previously observed (Tarnopolsky 2004). An inverse

association between food intolerance and the prevalence of meeting the upper-limit of

protein intake was also observed. Whether this association is due to intolerances to

specific protein-rich foods (such as intolerance to dairy or lactose) or to a reduced

variety of food consumed remains unclear. Two out of three of the multisport endurance

non-elite athletes in this study (66.4%) consumed more proteins than is currently

recommended for endurance athletes. The perceived advantage of a high protein intake

by athletes has been documented in the past (Fox et al. 2011) and is consistent with

field observations of endurance athletes by the authors. Such high intakes of dietary

protein intakes may partly compensate the low CHO intakes in a context of low energy

availability during a period of endurance training by preventing lean mass loss

(Haakonssen et al. 2013). However, there is an opportunity for further educational efforts

to emphasize the importance of CHO in place of protein and possibly of fat as well to

optimize performance in multisport events, even in non-elite athletes.

Unsurprisingly, energy intake was a key factor predicting a high CHO intake, as

shown previously (Burke et al. 2001). The main correlate of energy intake was training

volume in hours per week. The training regimen of non-elite athletes from the WINTER

group was about half that of other non-elite athletes, which partially explains the low

prevalence of achieving CHO recommendations in this group. Consistent with this

observation, a positive relationship between training load and energy expenditure has

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been observed previously (Rodriguez et al. 2009). On the other hand, residual fatigue

from training has been shown to decrease appetite (Bentley et al. 2008; Tarnopolsky et

al. 2005). A busy training schedule may also limit the opportunities to eat (Nogueira and

Da Costa 2004). Nevertheless, training towards a full IM and for the WC IM 70.3 implies

more dedication and seriousness, which is directly reflected by better-adapted dietary

intake.

Over- and under-reporting of food intake is possible when relying on self-reported

data. Underestimation of food intake in athletes has been shown to range from 10 to

20% (Burke et al. 2001). Specific foods such as snacks and alcoholic beverages, which

are non trivial sources of CHO in athletes, are more likely to be under-reported (Mertz et

al. 1991). Under-reporting has also been associated with a busy lifestyle (Burke et al.

2001), which is likely a characteristic of most participants in this study considering that

71% have reported being employed full-time. On the other hand, over-reporting of food

intake based on self-report dietary assessment tools has also been observed in the

general population (Lutomski et al. 2011), particularly among younger individuals and

those with a low BMI (Johansson et al. 1998; Lutomski et al. 2011; Mattisson et al.

2005). In our study, participants who reported energy intakes exceeding the group mean

by two SD (N=3) were excluded from the statistical analysis as a way to exclude over-

reporting subjects. Sensitivity analyses were undertaken to account for the potential

impact of under-reporting of food intake on the estimated prevalence of athletes

achieving the recommendations for CHO and protein. To do so, athletes were excluded

if their reported energy intake was below an estimated energy requirements for “low

active” and “active” people (Health Canada 2010). Even using this rather conservative

approach, almost one out of every 4 non-elite athletes did not achieve the recommended

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intake of 6g CHO/kg/d. On the other hand, using the same conservative approach, all

athletes achieved the lower recommendation for protein intake. The small number of

individuals in this sensitivity analysis did not allow us to compare the various multisport

events using this approach.

This study design has several strengths. The recruitment of a large number of

non-elite athletes from various geographical regions and countries through web-based

questionnaires yields greater generalizability of the results. Furthermore, the proportion

of women in our study sample is representative of the proportion of women in multisport

endurance events. In addition to recruiting athletes competing in many sport events, this

study included winter multisport events athletes, which, to our knowledge, had not been

done before. Some limitations of the study also need to be mentioned. The web-FFQ

used in this study has been validated in French (Labonte et al. 2012) but not in English

and not in populations other than French Canadians. However, recent studies by our

group have shown that intake of dairy as determined by the web-FFQ correlated with

blood biomarkers of intake in an ethnic diverse population (Abdullah et al. 2015).

Moreover, statistical analysis performed in the Canadian subjects yielded results that

were very similar to those seen in the entire group of participants (not shown). Most

subjects completed the FFQ after their sporting event, which implies that the race and

immediate post-race intakes are included in the reported food intakes. Finally, dietary

assessment through an FFQ does not provide information regarding the timing of food

intake, which is another key element of an athlete’s diet.

In conclusion, results of the present study suggest that between 23% and 54% of

non-elite multisport endurance men and women do not consume the recommended

amounts of carbohydrates to maximize fuelling for training and recovery processes

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during the training period leading to their sporting event. The findings of the present

study suggest the need for targeted education in this highly physically active population

in order to optimize carbohydrate intake, and this is particularly relevant in the context of

the current negative messages about carbohydrates. On the other hand, these findings

also raise the question whether the current carbohydrate recommendations for

endurance athletes are adequately adapted to the specific needs of the non-elite

athletes training for multisport events, particularly for those training in colder conditions

towards multisport winter events. In contrast, the recommended intakes for proteins are

achieved by a majority of athletes, and in greater proportions in longer and more

strenuous events such as IM and WC IM 70.3, even in this population of non-elite

athletes. Further investigations on dietary intakes including the timing of food

consumption are warranted in endurance multisport non-elite athletes. The extent to

which nutrition recommendations Individualized and group nutritional interventions may

benefit non-elite multisport endurance athletes who do not meet their nutritional needs.

Improving dietary strategies may maximize training adaptabilities on the long-term,

potentially enhancing performance even in this group of non-elite athletes.

Acknowledgement

The authors would like to thank Triathlon Quebec and the Pentathlon des Neiges

for their help with subjects’ recruitment. GM and BL designed the study; data were

collected by GM; data analysis, interpretation and manuscript preparation were done by

both authors. Authors have no disclosures.

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Table 1 Characteristics of study participants a

WINTER: Athletes who competed in the Pentathlon des Neiges and/or in the ITU Winter Triathlon 2014; IM70.3: Ironman 70.3 in Mont-Tremblant 2014; WC IM70.3: Ironman 70.3 World Championship in Mont-Tremblant, 2014; IM: Ironman in Mont-Tremblant, 2014. *P values for differences between multisport events groups, as determined by ANOVA, except otherwise indicated. 1 different from WINTER, 2 different from IM70.3, 3 different from WC IM70.3 (all P<0.05) as determined by Duncan test; aValues are presented as means ± SD unless stated otherwise. bComparison between groups, as determined by Chi-Square test. cComparison between groups, as determined by Fisher’s exact test. dTraining time includes all cardiovascular-oriented training (cycling, running, swimming, speed skating, cross-country skiing, snowshoeing, fitness classes, strength training) and team sports (badminton, hockey, soccer) but excludes walking, yoga, rock climbing and alpine skiing time. eSelf-reported proportion of training time performed at ≥80% of maximum capacity

Multisport Event Total WINTER IM70.3 WC IM70.3 IM P-value*

N 116 12 22 43 39 Womenb, % 27.6 41.7 36.4 34.9 10.3 0.03 Canadianc, % 73.0 100 100 45.2 79.5 0.01 Full-time employmentb, % 70.7 50.0 77.3 62.8 82.1 0.08 Age, years 40.3 ± 11.0 39.8 ± 13.3 37.4 ± 7.3 40.9 ± 12.1 41.4 ± 10.9 0.56 BMI, kg/m 23.2 ± 2.2 22.9 ± 2.1 23.7 ± 2.2 22.4 ± 2.03 23.8 ± 2.3 0.02 Training timed, hr/week 14.8 ± 5.3 7.5 ± 3.8 13.0 ± 4.2 1 16.0 ± 5.01,2 16.7 ± 4.5 1,2 <0.01 Proportion of training at high intensitye, %

30.8 ± 22.5 55.8 ± 27.1 34.3 ± 21.51 24.6 ± 16.21 27.8 ± 22.51 <0.01

Rank, % of age/sex category

49.5 ± 28.4 43.9 ± 25.9 47.2 ± 24.7 51.9 ± 27.7 48.8 ± 31.9 0.85

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Table 2 Self-reported dietary Intakes according to multisport event in non-elite athletesa

WINTER: Athletes who competed in the Pentathlon des Neiges and/or in the ITU Winter Triathlon 2014; IM70.3: Ironman 70.3 in Mont-Tremblant 2014; WC IM70.3: Ironman 70.3 World Championship in Mont-Tremblant, 2014; IM: Ironman in Mont-Tremblant, 2014. a Values are presented as means ± SD bBW, Body weight;

Multisport Event

WINTER IM70.3 WC IM70.3 IM P-value*

Energy kcal/day 2739 ± 920 2925 ± 754 3193 ± 1224 3703 ± 11871,2 0.01 kcal/kg BW/dayb 40.9 ± 11.7 41.4 ± 11.7 48.0 ± 18.0 51.1 ± 16.1 0.07 %kcal from sports supplementsc 5.3 ± 0.4 8.4 ± 1.01 5.9 ± 1.1 9.0 ± 0.91 0.02

CHOd % energy 53.9 ± 5.4 53.6 ± 5.8 47.7 ± 9.11,2 57.7 ± 7.43 <0.01 g/day 365 ± 112 390 ± 106 381 ± 159 528.9 ± 1771,2,3 <0.01 g/kg BW/day 5.5 ± 1.5 5.5 ± 1.7 5.8 ± 2.5 7.3 ± 2.51,2,3 <0.01 % from sports supplements 8.0 ± 4.3 13.7 ± 7.8 11.3 ± 7.7 14.1 ± 8.2 0.06 Fibres, g/day 36.1 ± 14.3 40.6 ± 17.1 40.1 ± 14.7 50.0 ± 19.81 0.02

Proteins % energy 15.6 ± 1.7 16.0 ± 2.6 17.5 ± 2.71 16.4 ± 2.4 0.04 g/day 106.9 ± 37.3 118.9 ± 45.7 138.5 ± 53.51 151.4 ± 49.11,2 0.02 g/kg BW/day 1.6 ± 0.5 1.7 ± 0.6 2.1 ± 0.81 2.1 ± 0.61 0.02 From sports supplementsc, g/day 2.3 ± 0.1 4.3 ± 0.9 2.8 ± 1.4 4.4 ± 1.0 0.12 % from sports supplementsc 2.4 ± 0.2 4.0 ± 1.0 2.3 ± 1.2 3.0 ± 0.7 0.23

Fat % energy 32.1 ± 4.3 31.0 ± 5.8 36.3 ± 8.31,2 28.2 ± 5.83 <0.01 g/day 99.7 ± 44.3 101.0 ± 34.2 130.0 ± 60.5 118.1 ± 47.5 0.10 % from sports supplementsc 2.7 ± 0.3 3.4 ± 0.9 1.7 ± 0.9 3.1 ± 0.7 0.07

Alcohol % energyc 1.7 ± 0.2 1.9 ± 0.8 1.2 ± 0.5 0.8 ± 0.31,2 0.04 g/dayc 6.6 ± 0.8 7.4 ± 3.4 5.2 ± 2.0 4.2 ± 1.7 0.30

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cValues are square transformed. Geometrical means and SD are presented; dCHO, Carbohydrate; *P values for differences between sports events groups, as determined by ANOVA. 1 different from WINTER, 2 different from IM70.3, 3 different from WC IM70.3 (all P<0.05) as determined by Duncan test;

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Table 3 Self-reported dietary intakes in non-elite athletes according to their estimated energy requirementsa

WINTER: Athletes who competed in the Pentathlon des Neiges and/or in the ITU Winter Triathlon 2014; IM70.3: Ironman 70.3 in Mont-Tremblant 2014; WC IM70.3: Ironman 70.3 World Championship in Mont-Tremblant, 2014; IM: Ironman in Mont-Tremblant, 2014. a Values are means ± SD unless stated otherwise b Participants with self-reported energy intake exceeding their estimated energy requirements based on a physical activity (PA) coefficient defined as low active (EER LOW). c Participants with self-reported energy intake higher than their estimated energy requirements based on a physical activity coefficient defined as active (EER ACTIVE). dCHO, Carbohydrate; eBW, Body weight; fValues in brakets are 95% confidence Intervals gValues are square transformed. Geometrical means and SD are presented;

Total ≥ EER LOWb ≥ EER ACTIVEc

N 116 70 61 Energy

kcal/day 3267 ± 1147 3918 ± 994 4088 ± 947 kcal/kg /day 47.1 ± 16.1 56.9 ± 12.6 59.3 ± 11.7 %kcal from sports supplements 8.3 ± 6.0 6.7 ± 4.3 6.6 ± 4.2

CHOd % energy 52.8 ± 8.7 52.2 ± 8.7 52.3 ± 8.3 g/day 430.8 ± 166.7 513.1 ± 158.1 535.5 ± 153.4 g/kg BW/daye 6.2 ± 2.4 7.5 ± 2.1 7.8 ± 2.0 From sports supplements, g/day 52.0 ± 37.1 53.0 ± 35.4 54.3 ± 35.3 % with CHO intake ≥6g/kgf 45.7 [36.4-55.2] 72.9 [60.9-82.8] 77.1 [64.5-86.9]

Proteins % energy 16.7 ± 2.5 16.5 ± 2.4 16.5 ± 2.3 g/day 135.9 ± 50.8 161.5 ± 46.9 168.4 ± 45.6 g/kg BW/daye 2.0 ± 0.7 2.3 ± 0.6 2.4 ± 0.6 From sports supplementsg, g/day 3.5 ± 1.1 3.5 ± 1.0 3.5 ± 1.1 % with protein intake ≥1.2g/kgf 87.1 [79.6-92.6] 100.0 [94.9-100] 100.0 [94.1-100] % with protein intake ≥1.6g/kgf 66.4 [57.0-74.9] 91.4 [82.3-96.8] 95.1 [86.3-99.0]

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FIGURES

Figure 1. Proportion of male and female non-elite multisport endurance athletes

meeting the recommended intakes for protein (≥ 1.2 or ≥ 1.6 g/kg/d) and carbohydrates

(≥6 g/kg/d) for endurance sports.

Figure 2. Difference among the multisport groups in the proportion of endurance athletes

meeting the recommended intakes for proteins (≥ 1.2 or ≥ 1.6 g/kg/d) and carbohydrates

for endurance sports.

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