Introduction

In Masters sport, the athletes are individuals who, usually over 35 years old, continue to participate in competitions or who return to compete in a determined period of their life ¹ . After the 1970s, there was an increasing number of sporting events for Masters categories and this population (e.g. middle- and older-aged adult) has been further studied by researchers of sports science ² . As in triathlon, several other sports also distribute Masters athletes in five-year intervals (e.g. 40–44 years, 45–49 years, 50-54 years, and so on) with age categories labelled ‘Year 1’ (i.g. 40, 45, 50, 55...), ‘Year 2’ (i.g. 41, 46, 51, 56...), ‘Year 3’ (i.g. 42, 47, 52, 57...), ‘Year 4’ (i.g. 43, 48, 53, 58...), and ‘Year 5’ (i.g. 44, 49, 54, 59...). The aim of these age categories in Masters Athletes is to provide a fair playing field and, consequently, promote continuity in sports participation ³ . Also, this categorization of age is important for Masters competitors because associated with the promotion of physical, psychological and social well-being ³ .

The established method for age categorization is a common strategy of organization in sport; however, though somewhat speculative, such a strategy has been a complex challenge in a sports context ⁴ . Grouping by age, whether in juvenile or older athletes, proposes to equal and fairness competition levels among participants based on a cut-off date ³ . However, Medic and colleagues ³ suggested that, the individual who are relatively younger in any age group are more likely to perceive advantages and opportunities within a competitive category and are thus more likely to approach competition whereas those who are relatively older in a category are more likely to perceive disadvantages, compromised opportunities within a competitive sphere, and will be more likely to avoid. This age-related disparity, associated with competitive disadvantages, opportunities, and sports participation, was defined as relative age effect ^{3, 5, 6} . This relative age effect in Masters sport, which is attributed to the participation- and performance–related advantage, was previously termed the constituent year effect ³ .

Recent studies suggest there are problems related to age categorization practices in Masters athletes, indicating an age-related disparity that would be may be associated with psychosocial factors and, consequently, indicate the possible disruption of participation patterns ^7,8 . This phenomenon, that incurs personal and social disparities in Masters sport, has been studied recently among Masters swimming and track and field athletes. The authors proposed that the relative age disparity can provide consequences for sports participation of Masters athletes in events and competitions due to anticipated disadvantages related to age-related decline and the motivational profile that this related to psychological mechanism ^3,7,8 . Another study ³ , it has been suggested that the participation-related constituent year effect in the Masters sport may exist, but it depends on gender, age, and type of sport. Therefore, it is important to analyze how the constituent year effect could influence the participation of Masters athletes in other sports, such as Triathlon.

Triathlon is an endurance sport with short and long-distance events (between 2 and 8 hours, respectively) that combine three consecutive modalities (e.g. swimming, cycling, and running) ⁹ . In the last three decades, the Masters triathletes have been of increased interest among researchers ^10,11,12 ; however, it is not yet known how the constituent year effect could affect the participation of Masters athletes in triathlon. Investigating this phenomenon in Masters triathletes is important because it may lead to promote effective strategies to attenuate the participation-related constituent year effect.

Previously, researchers suggested that age and gender seem to influence the performance of triathletes ¹³ , but they did not evaluate or compare how a participation-related constituent year effect could be associated with the performance of Masters athletes. Previous studies proposed that the constituent year effect may also be associated with athletic performance ¹⁴ . In this study ¹⁴ , the participants of the first constituent year presented higher performance than athletes of the third, fourth and fifth years of an age category. The authors claimed that younger athletes have higher levels of strength and cardiorespiratory capacity when compared to older athletes. Knowing the importance of cardiorespiratory parameters for triathletes ¹⁵ , it is important to analyze not only a participation-related constituent year effect, but also other aspects associated with the performance of Masters athletes; for example, score obtained through performance in competitions.

Based on previous evidence ^7,8 , it was found that a participation-related constituent year effect existed was stronger for males than for females. Other studies suggest that this difference between genders is associated with the number of participants ¹⁶ and competitiveness in sport ^{2, 17} . Thus, we hypothesized that the constituent year effect be stronger for males than females Masters Triathletes. Also, it was suggested that athletes from the first constituent years, due to relative age disparities, may have a higher ranking score compared to older participants within the five-year age category. Therefore, the aim of this study was to examine whether a participation- and performance–related constituent year effect exists among Brazilian Masters Triathletes competitors.

Method

Results

Participation

Table 1 shows expected and observed frequency of distribution for participation in competitions in each constituent year of the collapsed five–year age category distribution for a total sample, as well as by gender and decade of life (fourth, fifth, and sixth decade) separately. Chi-square test results for a total sample of athletes Brazilian Masters Triathletes competitors indicated the existence of a participation-related constituent year effect ( ${\chi }_4^2=\mathrm{36,298}$, p < 0.0001). Specifically, we found that significantly more triathletes competed in the Brazilian Masters Championships if they were in the first and second year of an age category and significantly fewer in the fourth and fifth year (effect sizes largest) of an age category.

Table 1.Frequency distribution, values, p values and effect sizes for total sample, gender and for decade of life. 

		Observed frequency	Expected frequency	d.f.	${\chi }^2$	p	Effect size
Total sample	Year 1	399	347.6	1	7.60	0.006*	0.92
	Year 2	394	347.6	1	6.19	0.01*	0.83
	Year 3	367	347.6	1	1.06	0.3	0.35
	Year 4	306	347.6	1	4.96	0.03*	0.74
	Year 5	272	347.6	1	16.44	0.0001*	1.35
Male	Year 1	335	288.8	1	7.39	0.0007*	0.98
	Year 2	325	288.8	1	4.54	0.03*	0.77
	Year 3	304	288.8	1	0.80	0.3	0.32
	Year 4	255	288.8	1	3.96	0.05*	0.72
	Year 5	225	288.8	1	14.09	0.0002*	1.35
Female	Year 1	64	58.8	1	0.46	0.5	0.56
	Year 2	69	58.8	1	1.77	0.1	1.09
	Year 3	63	58.8	1	0.30	0.5	0.45
	Year 4	51	58.8	1	1.03	0.3	0.84
	Year 5	47	58.8	1	2.37	0.1	1.26
Fourth decade	Year 1	261	234.2	1	3.07	0.08	0.74
	Year 2	264	234.2	1	3.79	0.05*	0.83
	Year 3	254	234.2	1	1.67	0.2	0.55
	Year 4	208	234.2	1	2.93	0.09	0.73
	Year 5	184	234.2	1	10.76	0.001*	1.39
Fifth decade	Year 1	108	89.2	1	3.96	0.05*	1.21
	Year 2	102	89.2	1	1.84	0.1	0.83
	Year 3	86	89.2	1	0.11	0.7	0.20
	Year 4	79	89.2	1	1.17	0.2	0.66
	Year 5	71	89.2	1	3.71	0.05*	1.17
Sixth decade	Year 1	30	24.2	1	1.39	0.2	1.00
	Year 2	28	24.2	1	0.60	0.4	0.65
	Year 3	27	24.2	1	0.32	0.5	0.48
	Year 4	19	24.2	1	1.12	0.2	0.90
	Year 5	17	24.2	1	2.14	0.1	1.24

${\chi }^2$ = Chi square, d.f. = Degrees of freedom, p = p-value

* significant

Results also presented in Table 1 show a participation-related constituent year effect for male ( ${\chi }_4^2=\mathrm{30,778}$, p < 0.0001), but not in the female ( ${\chi }_4^2=\mathrm{5,932}$, p = 0.20) Masters athletes. Specifically in male athletes, the findings show significantly fewer triathlete competitors in the fourth and fifth constituent year of a category and more compete when they are in the first and second year of the same age category. As seen from Figure 1, both for total sample and gender male, it appears that there was a lower percentage of triathlete participation in the last years compared to the first years of an age category.

Figure 1.Percentage of the total sample by gender of the Brazilian triathletes as a function of the constituent year. 

Results presented in Figure 2 suggest a participation-related constituent year effect across age. Findings indicated that a participation-related constituent year effect exists for triathletes who competed in the Brazilian Masters Championships during the fourth (n = 1171, ${\chi }_4^2=\mathrm{22,224}$, p < 0.000) and fifth (n = 446, ${\chi }_4^2=\mathrm{10,794}$, p = 0.029) decade of life, but does not exist during the sixth (n = 121, ${\chi }_4^2=\mathrm{5,570}$, p = 0.234). Also, table 1 specifically shows a greater number of athletes competing in the first and second constituent year (fifth and fourth decade of life, respectively) and a number significantly lower of triathlon participants in the last year (fourth and fifth decade of life) of an age category.

Figure 2.Percentage by decade of life of Brazilian triathletes as a function of the constituent year. 

Discussion

In our study, we sought to analyze, as well as previous studies ^7,14 , the constituent year effect in Masters sport by utilizing data on Masters Triathletes. Our results are consistent with recent studies ^7,8 , indicating that there is a participation-related constituent year effect for a total sample of Brazilian triathletes; significantly that more triathletes compete in Triathlon Championships when they are in their first and second constituent year than athletes in the fourth and fifth year of the same age category.

The results also indicated that participation-related constituent year effect was observed in males, specifically that fewer triathletes participate in competitions when they are in the last constituent year and less in the early constituent years of any five-year age category. Just like these findings, other studies that analyzed individual sports (i.g. swimming and athletics) indicated a stronger constituent year effect in men than women ^3,7,8 . Other authors have argued that this difference between gender participation is associated with the number of athletes practicing sports ¹⁶ and competitive level ^2,17 . Thus, it is suggested that this effect in triathletes is due to the competitive level and greater number of male (n = 1444) participants than females (n = 294).

The participation-related constituent year effect across age as a moderating factor, indicated this phenomenon exists for fourth and fifth decade of life, but not for triathlete competitors who are in the sixth decade of life. Thus, the likelihood of participating in the first and second year of an age category (specifically, in the fourth and fifth decade of life) was higher, whereas the likelihood of participating during the fifth year of an age category (specifically, in the fourth and fifth decade of life) was lower. These results are similar to other findings that showed a participation-related constituent year effect more observed from the fourth decade of life ³ . This phenomenon most evident in the last decades of life (fourth and fifth) can be explained by physiological mechanisms (i.e. i.e. maximal oxygen consumption, lactate threshold and exercise economy) associated with increasing age ²⁰ . Thus, we proposed older athletes participate less when they are in the fifth year of an age category owing to possible changes in age-related performance. Also, it is suggested that this effect in triathletes was not found in the sixth decade of life due to the small number of participants.

Another aim of this study was to compare the ranking score of these triathletes as a function on the three best athletes of each constituent year. When comparing scores as a function of the triathlete constituent year, we did not find significant differences between years of an age category. Triathlete ranking scores are associated with performance obtained in these competitions. Nevertheless, although a participation-related constituent year effect was evident in Brazilian triathletes, we suggest performance would not be associated with this phenomenon. Previous findings have shown that athletes have significantly improved their performance over age, especially in older categories ²¹ .

Importantly, some recent studies have evaluated a participation-related constituent year effect ^7,8 . So, we also suggest that future studies should analyze both the participation-related constituent year effect of athletes in sport, and the performance variables between the constituent years, or to assess whether the increase in age could negatively influence the athlete’s performance in Masters categories. Also, it would be interesting for future studies to analyze other factors that could be associated with a participation-related constituent year effect in Masters triathletes; for example motivation, increasing mortality rate ⁷ , increased risk of cardiovascular diseases (endurance modalities) ²² , and increased frequency of injuries throughout age ²³ .

The present study had a cross-sectional character, which may be a limitation, because longitudinal studies ²⁴ seem to examine better the dynamics of within-individual decisions to participate in relation to the constituent years of any five-year age category. However, the results of this study are relevant both for sports science and for coaches and Masters triathlon athletes. According to the findings, we suggest some strategies to resolve a participation-related constituent year effect in triathlon athletes. The first suggestion would be to reduce the distribution of age categorization from five-years to three-years in an age category, especially after the fourth and fifth decade of life. Knowing that motivation is a predominant factor related to the participation of Masters athletes ⁷ , we also suggest triathlon coaches encourage ²⁵ their athletes to participate in competitions and events. Also, we propose that coaches should guide and encourage their triathletes, so that older athletes (i.e., the last years of the category) continue to participate in competitions.

In conclusion, this study was the first to show a participation-related constituent year effect on triathlon athletes. We also evidence this phenomenon exists in male, but not in female triathletes. However, across decades of life, a participation-related constituent year effect was confirmed only in the fourth and fifth decade of life, but not in the sixth decade of life. These results propose the categorization of age in 5 years is causing a discontinuity in the participation of athletes in competitions, especially the fourth and fifth decade of life. Therefore, since performance has not changed through scoring, we suggest coaches further encourage their Masters triathletes to participate in competitions.