Participation and performance trends of East-African runners in Swiss half-marathons and marathons held between 2000 and 2010

  • Marco Cribari1,

    Affiliated with

    • Christoph A Rüst1,

      Affiliated with

      • Thomas Rosemann1,

        Affiliated with

        • Vincent Onywera2,

          Affiliated with

          • Romuald Lepers3 and

            Affiliated with

            • Beat Knechtle1, 4Email author

              Affiliated with

              BMC Sports Science, Medicine and Rehabilitation20135:24

              DOI: 10.1186/2052-1847-5-24

              Received: 14 February 2013

              Accepted: 25 November 2013

              Published: 1 December 2013

              Abstract

              Background

              This study examined the changes in participation, performance and age of East African runners competing in half-marathons and marathons held in Switzerland between 2000 and 2010.

              Methods

              Race times, sex, age and origin of East African versus Non-African finishers of half-marathon and marathon finishers were analyzed.

              Results

              Across time, the number of Kenyan and Ethiopian finishers remained stable (P > 0.05) while the number of Non-African finishers increased for both women and men in both half-marathons and marathons (P < 0.05). In half-marathons, the top ten African women (71 ± 1.4 min) and top three (62.3 ± 0.6 min) and top ten (62.8 ± 0.4 min) African men were faster than their Non-African counterparts (P < 0.05). In marathons, however, there was no difference in race times between the top three African men (130.0 ± 0.0 min) and women (151.7 ± 2.5 min) compared to Non-African men (129.0 ± 1.0 min) and women (150.7 ± 1.2 min) (P > 0.05). In half-marathons and marathons was no difference in age between the best Non-African and the best African runners (P > 0.05).

              Conclusions

              During the last decade in Switzerland, the participation of Kenyan and Ethiopian runners in half- and full- marathons remained stable. In marathons there was no difference in age and performance between the top African and the top Non-African runners. Regarding half-marathons, the top African runners were faster but not younger than the top Non-African runners. Future insight should be gained by comparing the present results with participation, performance and age trends for East African runners competing in marathons held in larger countries.

              Keywords

              Running East African runners Nationality Aging Gender Marathon

              Background

              Over the last years, participation and performance trends in long-distance running such as half- marathon and marathon running have been extensively analyzed [112]. It has been demonstrated that age [16], sex [2, 47], training [2, 4, 8], anthropometry [2, 4, 8] and nationality [9] were crucial determining factors for long-distance running performance.

              For instance, it has been shown for the ‘New York City Marathon’ that participation increased in the last decades [1, 2] especially for women [6] and master athletes [1]. The participation of master athletes – defined as athletes older than 35 years [10] – increased in half-marathons [2, 11], marathons [1, 2, 6, 11, 12] and ultra-marathons [13]. Leyk et al. [2, 4] suggested that health promoting behaviour and the ability of finishing a marathon with only a short running history might be a potential explanation for this phenomenon. More than 25% of master athletes aged between 50 and 69 years started running no more than five years before their first participation in a marathon [4]. They further reported that a high number of running kilometres and high running frequencies were needed to successfully finish a marathon compared to their younger counterparts [4]. Nevertheless, running performance is related to age-dependent physiological changes [3, 10, 1419]. Recent studies showed that best marathon times in general population will be achieved before the age of forty years [1, 3, 6].

              The question of a relationship between performance and origin in marathon runners has also been raised [8, 9, 2023]. In addition, the top list of the International Association of Athletics Federations (IAAF) in half-marathon and marathon runners [24] in 2011, especially for men, indicated that all the top 20 performances in marathons and half-marathons were achieved by East African runners originating from Kenya, Ethiopia and Eritrea. The dominance of these East African athletes in long-distance running is a well-known phenomenon [9, 25]. Specific advantageous factors such as favourable genetic endowment [9] and a better running economy [8, 21, 22] have been suggested for the success of East African runners. The anecdotal finding of travelling a long way to school each day was postulated as another important factor for the great success of East African runners. Both Onywera et al. [26] and Scott et al. [25] reported that most of the national and international elite runners from Kenya and Ethiopia run every day more than five kilometres to school. They further showed an association between the distance travelled to school and the performance in long-distance running [25, 26].

              Beside these factors, also unique sociocultural and psychological conditions were suggested as an important reason of the success of East African runners [9, 22, 26]. Kenyans have an advantageous motivation to become a competitive athlete [26, 27]. Poverty and unemployment are major problems in most African countries [26, 27]. Therefore, running might be the only chance for a successful life and to raise money in order to help their families and parents [26, 27]. Supported by western countries, running became more professional in Kenya and Ethiopia [8, 26, 27]. So in the last years the possibility of both earning money and becoming a successful runner increased [8, 26, 27]. In western countries with a high gross domestic product (GDP) such as Switzerland and a large general income [28], we assume a greater sponsorship at several larger races comparing to other countries with a lower GDP. Therefore, earning money with promotional fees and prize money could be an important motivation for East African elite runners to compete in Swiss long-distance running events.

              To the best of our knowledge, the changes in participation and performance trends of East African runners have not been analyzed in all half-marathon and marathon races held within an entire country. Therefore, the aims of this study were to analyze (i) the participation trends of East African versus Non-African runners in all Swiss half-marathons and marathons held between 2000 and 2010, and (ii) the trends in performance and the age of peak performance of African and Non-African athletes for both women and men during the studied period. Regarding the general increase in participation in long-distance running events and the increasing influence of western countries in Kenyan and Eritrean running culture, we hypothesized an increase in the participation of East African runners. Based on previous reports of East-African dominance in long-distance running, we also hypothesized better performances for top African runners compared to top Non-African runners. According to this and based on age-related peak performances in long-distance running events, we further assumed that top African runners would be younger than top Non-African runners in both half-marathons and marathons over the last decade.

              Methods

              All runners who ever finished a half-marathon and a marathon in Switzerland between 2000 and 2010 were analyzed with the focus on participation, sex, nationality and age. The data set for this study was obtained from http://​www.​datasport.​ch and the race directors. The study was approved by the Institutional Review Board of St. Gallen, Switzerland, with waiver of the requirement for informed consent given that the study involved the analysis of publicly available data.

              During this period, data from 313,173 athletes were available with 226,754 finishers in half-marathons and 86,419 finishers in marathons from a total of 90 marathons and 145 half-marathons. Out of these two groups, eight subgroups (i.e. four subgroups for each distance) were generated and sorted by nationality (i.e. African or Non-African) and sex (i.e. men or women). Africans, i.e. Ethiopians and Kenyans, were analyzed more specifically. In order to find trends in the annual number of male and female finishers per race distance, the number of finishers was determined and analyzed for African and Non-African athletes separately. Since Ethiopia and Kenya were the two African nations providing the highest number of African finishers, the participation trends for athletes originating from these two countries were in addition analyzed separately. For Non-African finishers, no detailed information about their nationality was extracted. Therefore, data from 226,518 Non-African athletes (i.e. 162,288 men and 64,230 women) and 236 African athletes (i.e. 169 men and 67 women) were available in half-marathons. In marathons, data from 86,182 Non-African athletes (i.e. 71,200 men and 14,982 women) and 237 African athletes (i.e. 183 men and 54 women) could be analysed (Table 1). In order to compare African with Non-African athletes, the overall top (i.e. fastest race time), the top three (i.e. three fastest race times) and the top ten (i.e. ten fastest race times) male and female athletes were determined for African and Non-African athletes in both half-marathons and marathons during the studied period. The athletes were then analyzed and compared regarding their race performance and age.
              Table 1

              History of half-marathons and marathons held in Switzerland between 2000 and 2010 with the number of African and Non-African finishers

              Half-marathon

              African men

              African women

              Total Africans

              Non-African men

              Non-African women

              Total Non-Africans

              Total runners

              Greifenseelauf

              69

              32

              101

              57,847

              24,978

              82,825

              82,926

              Lausanne Marathon

              14

              2

              16

              23,497

              8,946

              32,443

              32,459

              Hallwilerseelauf

              40

              17

              57

              22,461

              8,489

              30,950

              31,007

              Lucerne Marathon

              1

              2

              3

              10,880

              5,665

              16,545

              16,548

              Maratona Ticino

              3

               

              3

              10,038

              2,588

              12,626

              12,629

              Genève Marathon for UNICEF

              30

              8

              38

              8,636

              3,561

              12,197

              12,235

              Winterthur Marathon

              2

               

              2

              6,284

              2,322

              8,606

              8,608

              Basler Marathontage/Run to the Beat

                 

              3,880

              1,439

              5,319

              5,319

              Dreiländerlauf Basel

                 

              3,822

              983

              4,805

              4,805

              Bieler Lauftage

              2

              1

              3

              2,930

              1,030

              3,960

              3,963

              Brienzerseelauf

                 

              1,935

              943

              2,878

              2,878

              Rhylauf

              3

              2

              5

              2,043

              535

              2,578

              2,583

              Run und Walk Event Rothenburg

                 

              1,343

              532

              1,875

              1,875

              Halbmarathon SM 2000 Schwyz

              2

              1

              3

              1,278

              296

              1,574

              1,577

              Virgin Runners Halbmarathon

                 

              1,118

              332

              1,450

              1,450

              Sempachersee Halbmarathon

                 

              765

              312

              1,077

              1,077

              Basel City

                 

              728

              344

              1,072

              1,072

              Emmentaler Halbmarathon

                 

              617

              193

              810

              810

              Pfäffikerseelauf

                 

              634

              142

              776

              776

              Neujahrsmarathon

                 

              386

              208

              594

              594

              Halbmarathon Schweizermeisterschaft 2002 Brittnau

              3

              2

              5

              396

              93

              489

              494

              Wiedlisbacher Halbmarathon

                 

              203

              80

              283

              283

              Cuorsa dil Rein Disentis

                 

              164

              62

              226

              226

              Semi marathon Côte de l'orbe

                 

              131

              72

              203

              203

              Int. Halbmarathon Full-Reuenthal

                 

              119

              35

              154

              154

              Halbmarathon Gürbetal

                 

              106

              38

              144

              144

              Sri Chinmoy Self Transcendence Marathon Winterthur Halbmarathon

                 

              47

              12

              59

              59

              Total Half-marathon

              169

              67

              236

              162,288

              64,230

              226,518

              226,754

              Marathon

                     

              Zürich Marathon

              96

              24

              120

              31,277

              6,799

              38,076

              38,196

              Lausanne Marathon

              59

              23

              82

              13,017

              2,606

              15,623

              15,705

              Lucerne Marathon

              2

              1

              3

              7,063

              1,713

              8,776

              8,779

              Genève Marathon for UNICEF

              17

              3

              20

              4,319

              758

              5,077

              5,097

              Winterthur Marathon

               

              2

              2

              4,297

              798

              5,095

              5,097

              Maratona Ticino

              2

               

              2

              2,607

              399

              3,006

              3,008

              Basel City

              4

              1

              5

              2,288

              572

              2,860

              2,865

              Basler Marathontage/Run to the Beat

              1

               

              1

              1,809

              336

              2,145

              2,146

              Frauenfeld

                 

              1,649

              342

              1,991

              1,991

              Bieler Lauftage

                 

              1,529

              374

              1,903

              1,903

              Rund um den Bielersee

                 

              752

              164

              916

              916

              Neujahrsmarathon Schlieren

              2

               

              2

              590

              120

              710

              712

              Sri Chinmoy Self Transcendence Marathon Winterthur

                 

              3

              1

              4

              4

              Total Marathon

              183

              54

              237

              71,200

              14,982

              86,182

              86,419

              Statistical analysis

              In order to increase the reliability of our data analysis, each set of data was tested for normal distribution as well as homogeneity of variances in advance. Normal distribution was tested using a D’Agostino and Pearson omnibus normality test, homogeneity of variances using a Levene’s test in case of two groups and with a Bartlett’s test in case of more than two groups. In order to find significant changes in a variable across years, single linear regression analysis was used. To find significant differences between two groups, a Student’s t-test was used. Statistical analyses were performed using IBM SPSS Statistics (Version 19, IBM SPSS, Chicago, IL, USA) and GraphPad Prism (Version 5, GraphPad Software, La Jolla, CA, USA). Significance was accepted at P < 0.05 (two-sided for t-tests). Data in the text are given as mean ± standard deviation (SD).

              Results

              Participation trends

              In marathons, 0.2% of all finishers were African men and 0.1% African women during the 2000–2010 period (Table 2). In African finishers, 23.3% (overall finishers: 0.1%) were Ethiopian men, 38.4% (0.1%) Kenyan men, 16.9% (0.1%) Ethiopian women and 3.4% (0.01%) were Kenyan women (Figure 1A). In half-marathons, 0.1% of all finishers were African men and <0.1% were African women (Table 1). In African finishers, 27.1% (overall finishers: <0.1%) were Ethiopian men, 20.8% (<0.1%) were Kenyan men, 11.9% (<0.1%) were Ethiopian women and 11.9% (<0.1%) were Kenyan women (Figure 1B).
              Table 2

              Absolute and relative number of finishers in marathons and half-marathons in Switzerland sorted by nationality and gender during the 2000–2010 period

               

              Ethnicity

              Gender

              Number of finishers

              Percent of finishers

              Marathon

                

              86,419

              100.00%

               

              Non-African

              Men

              71,200

              82.39%

               

              Non-African

              Women

              14,982

              17.34%

               

              African

              Men

              183

              0.21%

               

              Ethiopian

              Wen

              55

              0.06%

               

              Kenyan

              Men

              91

              0.11%

               

              African

              Women

              54

              0.06%

               

              Ethiopian

              Women

              40

              0.05%

               

              Kenyan

              Women

              8

              0.01%

              Half-marathon

                

              226,754

              100.00%

               

              Non-African

              Men

              162,288

              71.57%

               

              Non-African

              Women

              64,230

              28.33%

               

              African

              Men

              169

              0.07%

               

              Ethiopian

              Men

              64

              0.03%

               

              Kenyan

              Men

              49

              0.02%

               

              African

              Women

              67

              0.03%

               

              Ethiopian

              Women

              28

              0.01%

               

              Kenyan

              Women

              28

              0.01%

              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig1_HTML.jpg
              Figure 1

              Percent of Ethiopian and Kenyan men and women in overall African runners for marathons (Panel A) and half-marathons (Panel B). Ken = Kenya, ETH = Ethiopia.

              In half-marathons, the number of Non-African male finishers (14,753 ± 4,492) was higher than the number of Non-African female finishers (5,839 ± 2,122 finishers) (P < 0.05). For African men, the annual number of half-marathon finishers increased (P < 0.01) (Figure 2A). The number of Non-African male and female finishers increased over the last decade in half-marathons by 131.1% for men and by 199.6% for women (P < 0.01) (Figure 2B). In marathons, the number of Non-African male finishers (6,473 ± 2,966) was higher than the number of Non-African female finishers (1,362 ± 670.7) (P < 0.05). Only African men increased their annual number of marathon finishers (P = 0.01) (Figure 2C). Non-African men (P < 0.01) and women (P = 0.02) increased their annual number of marathon finishers by 160.9% for men and by 134.4% for women over the last decade (Figure 2D). In half-marathons, there was no difference between the number of African male (15.4 ± 7.7) and African female (6.1 ± 2.5) finishers (P > 0.05). Also for marathons, there was no difference between the number of African male (16.6 ± 9.1) and African female (4.9 ± 3.3) finishers (P > 0.05).
              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig2_HTML.jpg
              Figure 2

              Change in the number of male and female African (Panels A&C) and Non-African (Panels B&D) finishers in half-marathon (Panels A&B) and marathon (Panels C&D), respectively, during the 2000–2010 period.

              Participation trends of Ethiopian and Kenyan athletes

              In half-marathons, the annual number of male Ethiopian finishers (5.8 ± 3) was higher (P < 0.05) than the annual number of female Ethiopian (2.5 ± 1.9) finishers (Figure 3A). In Kenyan athletes, there was no difference (P > 0.05) between the annual number of male (4.5 ± 2.2) and female (2.5 ± 1.1) finishers (Figure 3B). In Ethiopian as well as in Kenyan finishers, neither men nor women showed a significant change in the number of annual finishers across years (P > 0.05). In marathons, the mean number of male Ethiopians (5.5 ±1.8) was not different (P > 0.05) from the number of female Ethiopians (4 ± 1.8) (Figure 3C). In Kenyans, the number of male finishers (9.1 ± 5) was higher (P < 0.05) than the number of female finishers (0.8 ± 0.6) (Figure 3D). In both Ethiopians and Kenyans, neither men nor women showed a significant change in the number of finishers across the years (P > 0.05).
              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig3_HTML.jpg
              Figure 3

              Change in the number of male and female Ethiopian (A&C) and Kenyan (B&D) finishers in half-marathon (A&B) and marathon (C&D), respectively, during the 2000–2010 period.

              Participation trends for specific races held in Switzerland

              The change in participation for East African runners in specific races held in Switzerland is presented in Figure 4 for half-marathons and in Figure 5 for marathons. For men, a significant decrease in both Ethiopian and Kenyan marathoners in ‘Lausanne Marathon’ was found (Figure 5B) whereas for women, only the number of Ethiopian athletes decreased (Figure 5E). In contrast, the number of both male Ethiopian and male Kenyan runners increased in the same period in ‘Zurich Marathon’ (Figure 5C).
              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig4_HTML.jpg
              Figure 4

              Change in participation for female and male East African runners in specific half-marathons in Switzerland for men in Genève Marathon for UNICEF (Panel A), Greifenseelauf (Panel B) and Hallwilerseelauf (Panel C) and for women in Genève Marathon for UNICEF (Panel D), Greifenseelauf (Panel E) and Hallwilerseelauf (Panel F).

              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig5_HTML.jpg
              Figure 5

              Change in participation in specific marathons in Switzerland for female and male East African runners for men in Genève Marathon for UNICEF (Panel A), Lausanne Marathon (Panel B) and Zürich Marathon (Panel C) and for women in Genève Marathon for UNICEF (Panel D), Lausanne Marathon (Panel E) and Zürich Marathon (Panel F).

              Comparison of African and Non-African runners’ performance

              In half-marathons, the overall top three race times of African women (69.3 ± 1.2 min) were not faster than those of Non-African women (71 ± 1.7 min). In contrast, the top ten race times in African women (71 ± 1.4 min) were faster than those of Non-African women (72.7 ± 1.6 min). African men were faster than Non-African men regarding the top three (P = 0.04) and the top ten (P < 0.01) race times (Figure 6A).
              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig6_HTML.jpg
              Figure 6

              Running time of the overall top, the overall top three and the overall top ten African and Non-African women and men in half-marathon (Panel A) and marathon (Panel B). P-values indicate whether the difference between African and Non-African athletes was significant or not (‘NS’ = not significant).

              The average race times for African men were 130 ± 0 min for the top three and 130.2 ± 0.4 min for the top ten. Compared to top three (129.0 ± 1.0 min) and top ten (131.0 ± 1.9 min) race times in Non-African men there was no difference in performance (P > 0.05). The same was found for women (P > 0.05). The African top three women finished in 151.6 ± 2.5 min compared to Non-African top three women 150.6 ± 1.2 min. The mean race time for top ten African women was 154.6 ± 2.7 min compared to 152.8 ± 1.7 min for top ten Non-African women (Figure 6B). Comparing the race times of all African and Non-African finishers in half-marathons and marathons, African women (126 ± 52 min) were faster than Non-African women (145 ± 54 min) (P < 0.01). The average race time of all female finishers was 145 ± 54 min. Comparing African men (113 ± 49 min) and Non-African men (143 ± 62 min) there was also no difference in performance (P < 0.01). The mean race time of all male finishers was 143 ± 62 min. Comparing all finishers, men and women, African athletes (116 ± 50 min) were faster than Non-African athletes (144 ± 60 min) (P < 0.01). The mean finishing time of all finishers was 144 ± 60 min (Table 3).
              Table 3

              Race time and number of Africans and Non-Africans finishers in marathons and half-marathons between 2000 and 2010 in Switzerland

               

              Non-African

              African

              Overall

               

              Race time (min)

              Number of finishers

              Race time (min)

              Number of finishers

              Race time (min)

              Number of finishers

              Women

              145 ± 54

              79,212

              126 ± 52

              121

              145 ± 54

              79,333

              Men

              143 ± 62

              233,488

              113 ± 49

              352

              143 ± 62

              233,840

              Total

              144 ± 60

              312,700

              116 ± 50

              473

              144 ± 60

              313,173

              Results are presented as mean ± SD.

              Comparison of African and top Non-African runners age

              In half-marathons, the top three African women (32.3 ± 1.5 years) and men (27.3 ± 5 years) were not younger than the top three Non-African women (33 ± 2 years; P = 0.67) and men (26.3 ± 4.2 years; P = 0.80). Also in men’s top ten there was no difference in age between African (26.1 ± 3.9 years) and Non-African (25.7 ± 4 years) athletes (P = 0.82). Comparing the top ten finishers for African (27 ± 6.4 years) and Non-African (32 ± 3.5 years) women, African women were younger (P = 0.04; Figure 7A) than Non-African women. In marathons, comparing the top three and top ten finishers, there was no difference in age between African and Non-African men, and between African and Non-African women (Figure 7B).
              http://static-content.springer.com/image/art%3A10.1186%2F2052-1847-5-24/MediaObjects/13102_2013_22_Fig7_HTML.jpg
              Figure 7

              Age of the overall top, the overall top three and the overall top ten African and Non-African women and men in half-marathon (Panel C) and marathon (Panel D). P-values indicate whether the difference between African and Non-African athletes was significant or not (‘NS’ = not significant).

              Discussion

              The first aim of the present study was to analyze participation trends of East African runners in Swiss half-marathons and marathons held between 2000 and 2010. The second aim was to compare performance and age of African runners and Non-African runners. The main findings were (i) a stable annual number of Kenyan and Ethiopian finishers in both half- and full-marathons while the number of Non-African finishers increased for both men and women, (ii) a higher number of male African finishers compared to female African finishers, (iii) faster race times for African athletes in half-marathons for both men and women, (iv) similar race times for Africans and Non-Africans for both sexes for marathons, and (v) no difference in the age of peak performance for top African and top Non-African runners for both sexes in half-marathons and marathons.

              Participations of East African runners remained stable in the last decade

              In contrast to our hypothesis, the number of Kenyan and Ethiopian finishers remained stable for both men and women in both half-marathons and marathons. The increase of African men in half-marathon and marathon was due to other African countries, which were not analysed in details. In contrast, the numbers of male and female finishers in Non-Africans increased in both marathons and half-marathons. This finding correlates with results presented by Jokl et al. [6] reporting an increased participation in general over the last 30 years in a large city marathon such as the ‘New York City Marathon’.

              Regarding the studied running events, African mainly competed at larger marathon and half-marathon events (e.g. Greifenseelauf, Lausanne Marathon, Hallwilerseelauf, Genève Marathon for UNICEF and Zürich Marathon). In all other races, there were five or fewer Africans competing during this period. We assume for smaller events lower budgets and these events were less prestigious. Interestingly, the ‘Lucerne Marathon’, the ‘Maratona Ticino’ and the ‘Winterthur Marathon’ were all among the seven largest running events for half-marathons and marathons. However, fewer than four Africans were participating annually per race between 2000 and 2010. In personal conversation with the race directors from the ‘Lucerne Marathon’ and the ‘Winterthur Marathon’ we learned that prize money was less than 200 Swiss francs (i.e. about 220 US dollars) and no promotional fees were offered either for African or for Non-African athletes. They further reported a decline of the prize money over years leading to less attraction for elite African athletes. Therefore, they races become more attractive for regional marathoners and half-marathoners. So in common beliefs the opportunity to win the race increased in absence of the elite East African athletes. Other personal communications with the race directors of the ‘Greifenseelauf’, the ‘Hallwilerseelauf’, the ‘Zurich Marathon’ and the ‘Lausanne Marathon’ (i.e. races with a high number of African participants) revealed that special prize money and promotional fee (especially for board and lodge) for elite African athletes were offered. They specially invited elite athletes in general to make their competition more interesting. Perhaps from the ‘Maratona Ticino’ and the other races no data for prize money were available and beside the ‘Winterthur Marathon’ only from the ‘Lausanne Marathon’ an amount of the prize money was given [29].

              According to poverty and unemployment in East African countries, Onywera [27] and Onywera et al.[26] reported that the motivation to become a competitive athlete was mainly based on economic reasons for Kenyan elite athletes especially for 39% of all national athletes and 33% for international athletes. The international success of the East African running pioneers such as Mike Boit, Kipchoge Keino and others implicated a ‘westernation’ of the culture, especially in Kenya [27]. Therefore, running became more professional and more popular in Kenya. Affected by the great international success of the East African running pioneers, young athletes know about the possibility of becoming a successful international athlete. Motivation of competitive running therefore increased and young East-African athletes became support by managers of Western countries. So the East African athletes came closer to the Western civilisation and according to this theory of closeness the chance to make money with competitive running increased. Based on this sociocultural background and according to our different findings in participation of East African athletes in Swiss long-distance running events and personal conversation with the race directors the question about a correlation between prize money and participation went up. In addition, the respondent race directors from running events with a large number of Africans reported a stable budget for invited elite athletes. Therefore, the possibility to make money with competitive running in Switzerland is limited and the annual number of Kenyan and Ethiopian participants remains stable. For further studies it would be interesting to analyse potential correlations between prize money and participation of African elite athletes in larger countries (e.g. USA).

              Kenyan and Ethiopian participation

              During the studied period there were more African men than African women competing. The same can be reported for Non-African athletes. Participation differences between men and women are common findings in sports events. In 1988 at the Olympic Games in Seoul (KOR) only 26.1% of all participants were women [30]. Compared to the XXIX Olympic Games in Beijing (CHN) in 2008 women increased their percentage of participants up to 42.4% [30]. So, especially in earlier years there were restrictions on female athletes. In Kenya, women were banned from international competitions until the 1970s [27]. Regarding the percentage of female participants at the Olympic Games in Seoul, 5.5% of the Kenyan team were women. They increased their participation also up to 39.1% in the Olympic Games in Beijing (2008) [31]. Therefore, the female running culture has not such a long time history as that of men. The Kenyan men were well established in long-distance running since years. But today, a female running culture is growing in Kenya and it is also a great honour for female athletes to represent their country in international competitions [27]. Participation of Kenyan woman increased with a delay of several years compared to Kenyan men. Also in Ethiopia, there was a similar development. Comparing Olympic Games in 1980 (Ethiopia took not part in the Olympic Games in 1988 and 1984) and 2008, Ethiopian women increased their participation from 4.9% to 48.1% [31]. These reports may explain the difference between female and male participation trends of Kenyan athletes in marathons and Ethiopian athletes in half-marathons.

              More interesting seems the fact of the difference in participation in male Ethiopian and Kenyan athletes in both half-marathons and marathons. Compared to their Ethiopian counterparts, more Kenyan men were participating in marathons and fewer in half-marathons. A possible explanation for this might be differences in anthropometry between Kenyan and Ethiopian runners. Ethiopians are more mesomorphic in somatotype, which includes more muscle mass especially expressed in a high thigh circumference [32]. Kenyans in contrast are more ectomorphic with slender legs [32]. Zillmann et al.[33] showed differences in anthropometric characteristics between recreational marathoners and recreational half-marathoners competing in Switzerland. They reported for half-marathoners a thicker thigh circumference compared to marathoners [33]. To the best of our knowledge anthropometric characteristics of Ethiopian runners have not been analysed yet. Based on reported differences in anthropometry between Ethiopians and Kenyans [32] we can only speculate that Ethiopian runners were more predestined for running half-marathons than marathons. Therefore, we had a higher number of Ethiopian participants in half-marathons than in marathons. Also in the IAAF top list from 2011 in marathons and half-marathons there was a significant difference between the number of Ethiopian and Kenyan runners for the top 20 race times [24]. In the top 20 marathoners there were 20 Kenyans [24]. In half-marathons there were 13 Kenyans and 9 Ethiopians ranked [24]. Future studies need to analyse anthropometric differences between Ethiopian and Kenyan long-distance runners.

              In the two largest marathons held in Switzerland, the ‘Zurich Marathon’ and the ‘Lausanne Marathon’, a reverse trend was found regarding the participation of male East African marathoners. While the participation decreased in the ‘Lausanne Marathon’, it increased in the ‘Zurich Marathon’. Most probably the prize money was higher in ‘Zurich Marathon’ compared to ‘Lausanne Marathon’ during this period.

              Elite African marathoners were not faster than elite Non-African marathoners

              There was no difference in race times between elite African finishers and elite Non-African finishers in marathons. This finding does not support the hypothesis of a better running performance of elite African runners compared to Non-African runners and was not in line with the anecdotal well-known African dominance in the literature regarding long-distance running [8, 9, 2023]. Comparing maximum oxygen uptake (VO2max) between elite Kenyan and elite Non-African runners, disparate findings were reported [8, 2123]. Therefore, VO2max as an important predictor variable of performance was critically discussed and in general there is no difference between Kenyan and Non-African runners [8]. Also, no differences were found in proportion of muscle fibers and muscle oxidative enzymes [8, 21]. Running economy, defined as the steady-state of submaximal oxygen uptake at a given running velocity, was further critically discussed as an important factor of performance [8]. Saltin et al.[34] reported a better running economy for Kenyans while Bosch et al.[35] reported no difference in the oxygen uptake at given performance levels. In summary, no significant physiological differences between elite African runners and elite Non-African runners could have been found yet and this goes in line with our unique results in marathons.

              Nevertheless, regarding the IAAF top list of marathons and half-marathons and corresponding to common beliefs, East African runners had better running performances than Non-African runners [24]. Why do marathon events in Switzerland differ to marathons held in other countries? A plausible explanation might be the thesis that not the top of the top East African athletes were competing in Swiss long-distance running events because they were less prestigious and there was less prize money to win. For example in the Lausanne marathon there were about 2,150 U.S. Dollar (i.e. 2,000 Swiss francs) for winning the marathon [29]. Comparing to the ‘New York City Marathon’ as the most prestigious marathon event worldwide the winner got about 100’000 U.S. Dollars [36]. To confirm this thesis about ‘second class’ elite East African runners in Swiss marathons further studies should analyze East African performance trends in larger countries. Especially performance findings of East African athletes from the World Marathon Majors (i.e. a collective of the worlds’ largest marathon events) should be compared to our data of smaller country with smaller races.

              Top African runners were faster than top Non-African runners in half-marathons

              Interestingly, elite African athletes were faster than elite Non-African athletes in half-marathons. This finding reflects the general opinion, anecdotal findings and international top lists of the IAAF [24] and goes not in line with our results found for marathons. Based on scientific literature we cannot explain this fact with physiological differences between Africans and Non-Africans. An explanation might be different sociocultural backgrounds and differences in running experience. A recent study compared a variety of predictor variables for performance between half-marathons and marathons [33]. The authors reported that marathoners had a larger number of completed long-distance competitions in their running history than half-marathoners. So in Switzerland, marathoners start their running career with half-marathons to gain experience [33]. Relatively to the world records 2011 in half-marathons and marathons [37] Non-African half-marathoners differ to Non-African marathoners in race times. The top Non-African race time in men’s half-marathons was 7.3% away of the world record. In marathons, however, there was only a gap of 3.4%. In Swiss long-distance events Non-African marathoners were better than half-marathoners in the worldwide ranking. More newcomers and recreational runners were competing in Swiss half-marathons might be a possible explanation for this. Non-African recreational runners were motivated for running by health benefits [2, 4]. It is possible to run a favorable performance beside a workaday life because not as many training kilometers and training units are needed for half-marathons compared to marathons [33] which is essential in Switzerland. Therefore, with a lot of newcomers in Non-Africans the possible top race time have not been reached yet. In contrary, top African runners were professional runners with a large running history since childhood and they were also driven by economical reasons to compete in Swiss half-marathons [2527]. So, they run better performances compared to Non-African athletes in half-marathons.

              Elite African runners were not younger than elite Non-African runners

              In contrast to our second hypothesis, elite African finishers were not younger than elite Non-African finishers neither in half-marathons nor in marathons. First, the majority of African runners in Switzerland between 2000 and 2010 were elite East African runners (76.7%) from Ethiopia (39.5%) and Kenya (37.21%). Performance is limited by age-related physiological changes. The maximal oxygen uptake (VO2max), as one of the most important factors, declines with age [3, 10, 14, 16, 18]. In addition to VO2max, the maximum heart rate (HRmax), the lactate threshold and the running economy change with age. HRmax significantly decreases with age [10, 15, 16], the lactate threshold, as the exercise intensity (%VO2max), increases significantly with age [10, 17, 19]. Top performances in long-distance running events will be achieved at younger ages (<40 years) [1, 3, 6] for both Africans and Non-Africans. Therefore, we can explain the same age of top performances comparing African and Non-African athletes in marathons and half-marathons. Especially in half-marathons, there was no age difference but a significant difference in performance between Africans and Non-Africans. This could be explained by an age-dependent loss in performance as well. The correlation between age and performance is relatively and not absolutely. So, within each group peak performance will be achieved at the same age regardless of a difference in performance between these two groups. The difference in performance would be explained by the fact that Non-African athletes have not reached their possible peak performance yet and not by age-differences.

              Strength, weakness, limitations and implications for future research

              A strength of the present study is the high number of runners analyzed in marathons and half-marathons from one country for an entire decade. To date, a demographical analysis about participation in marathons and half-marathons in such a way is unique. However, this study is limited in that determining factors for performance such as training, anthropometry, physiology, nutrition and motivation were not included. A limitation is also that data about prize money only was given in personal conversations with the race directors. Future studies should investigate participation, age and performance trends in marathoners and half-marathoners in larger countries such as the United States of America in order to strengthen demographic research. In addition, psychological and sociocultural backgrounds of the motivation of East African runners in relation to participation trends in half marathons and marathons should be analyzed in-depth.

              Conclusion

              Participation in East African runners remained stable over the last decade in Swiss half-marathons and marathons while the number of Non-African men and women increased. There was no difference in race times of the top three African and the top three Non-African marathoners. The dominance of East-African runners in marathons documented in literature remains anecdotal for marathons held in Switzerland between 2000 and 2010. Future studies need to analyze participation, age and performance trends of East-African runners in larger countries such as the United States of America to become a better insight of the East-African runners phenomena in long-distance running.

              Declarations

              Acknowledgement

              The authors thank the race directors for providing all race data.

              Funding

              This research received no grant from any funding agency in the public, commercial or not-for-profit sectors.

              Authors’ Affiliations

              (1)
              Institute of General Practice and for Health Services Research, University of Zurich
              (2)
              Department of Recreation Management and Exercise Science, Kenyatta University
              (3)
              INSERM U1093, Faculty of Sport Sciences, University of Burgundy
              (4)
              Facharzt FMH für Allgemeinmedizin

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              © Cribari et al.; licensee BioMed Central Ltd. 2013

              This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.