Open Access

Male and female Ethiopian and Kenyan runners are the fastest and the youngest in both half and full marathon

  • Beat Knechtle1, 2Email author,
  • Pantelis T. Nikolaidis3,
  • Vincent O. Onywera4,
  • Matthias A. Zingg2,
  • Thomas Rosemann2 and
  • Christoph A. Rüst2
SpringerPlus20165:223

https://doi.org/10.1186/s40064-016-1915-0

Received: 29 November 2015

Accepted: 17 February 2016

Published: 29 February 2016

Abstract

In major marathon races such as the ‘World Marathon Majors’, female and male East African runners particularly from Ethiopia and Kenya are the fastest. However, whether this trend appears for female and male Ethiopians and Kenyans at recreational level runners (i.e. races at national level) and in shorter road races (e.g. in half-marathon races) has not been studied yet. Thus, the aim of the present study was to examine differences in the performance and the age of female and male runners from East Africa (i.e. Ethiopians and Kenyans) between half- and full marathons. Data from 508,108 athletes (125,894 female and 328,430 male half-marathoners and 10,205 female and 43,489 male marathoners) originating from 126 countries and competing between 1999 and 2014 in all road-based half-marathons and marathons held in one country (Switzerland) were analysed using Chi square (χ2) tests, mixed-effects regression analyses and one-way analyses of variance. In half-marathons, 48 women (0.038 %) and 63 men (0.019 %) were from Ethiopia and 80 women (0.063 %) and 134 men (0.040 %) from Kenya. In marathons, three women (0.029 %) and 15 men (0.034 %) were from Ethiopia and two women (0.019 %) and 33 men (0.075 %) from Kenya. There was no statistically significant association between the nationality of East Africans and the format of a race. In both women and men, the fastest race times in half-marathons and marathons were achieved by East African runners (p < 0.001). Ethiopian and Kenyan runners were the youngest in both sexes and formats of race (p < 0.001). In summary, women and men from Ethiopia and Kenya, despite they accounted for <0.1 % in half-marathons and marathons, achieved the fastest race times and were the youngest in both half-marathons and marathons. These findings confirmed in the case of half-marathon the trend previously observed in marathon races for a better performance and a younger age in East African runners from Ethiopia and Kenya.

Keywords

Age Athletes Endurance Sex Long-distance Nationality Running

Background

Marathon and half-marathon races are very popular running events held all over the world with an increasing number of both races and participants during the last decades. For instance, in the USA, there were more than 1200 marathons held in 2014 compared to about 300 marathons held in 2000 (www.runningusa.org/2015-national-runner-survey). The number of successful marathon finishers increased from 25,000 in 1976 to the all-time high of 550,637 in 2014. Compared to marathons, however, most of the runners competed in the USA in half-marathons. The number of successful half-marathoners increased from 303,000 in 1990 to the all-time high of 2,046,600 in 2014 (www.runningusa.org/half-marathon-report-2015). In fact, 3.7 times more half-marathoners than marathoners competed in the USA in 2014. In smaller countries such as Switzerland in Europe, a total of 226,754 half-marathoners and 86,419 marathoners competed between 2000 and 2010 (Anthony et al. 2014). In other terms, 2.6 times more half-marathoners competed than marathoners. In 2010, 8690 women and 21,583 men finished a half-marathon in comparison to 2904 female and 9333 male finishers in 2000, respectively, corresponding to an increase of 299 % for women and of 231 % for men over 10 years. In contrast, the number of male and female full marathoners increased until 2005 only and decreased thereafter (Anthony et al. 2014).

The dominance of East-African women and men in marathon running is well known (Hamilton 2000; Onywera et al. 2006; Tucker et al. 2015; Wilber and Pitsiladis 2012). Athletes from both Ethiopia and Kenya dominate marathon running for a long time (www.iaaf.org). In the top list of the International Association of Athletics Federations (IAAF) for male marathoners, the first best 37 marathon race times were achieved by athletes from Ethiopia and Kenya (www.iaaf.org/records/toplists/road-running/marathon/outdoor/men/senior). In women, however, the three fastest marathon race times were achieved by an athlete from Great Britain followed by two female marathoners from Kenya (www.iaaf.org/records/toplists/road-running/marathon/outdoor/women/senior). In the ‘World Marathon Majors’ with the largest city marathons worldwide, female and male champions are exclusively from East African particularly from Ethiopia and Kenya (www.worldmarathonmajors.com/champions/current-champions).

The reasons for the dominance of East-African runners in long and middle distance running events such as marathons included environmental conditions such as a specific geographic background (Onywera et al. 2006; Scott et al. 2003; Tucker et al. 2015). The dominance of East-African distance runners is primarily a Kenyan phenomenon, with majority of the Kenyan runners originating from the Kalenjin tribe in general and the Nandi sub-tribe in particular (Onywera et al. 2006; Tucker et al. 2015). Similar to Kenyan runners, elite Ethiopian runners are also of a distinct environmental background where marathoners mainly originate from the altitudinous regions of Arsi and Shewa (Scott et al. 2003).

However, there is paucity of information with regards to basic characteristics such as age and trends in performance of East-African half-marathoners (Aschmann et al. 2013; Cribari et al. 2013). These studies investigated all African half- and full marathoners competing in one country (Switzerland) together without a separation of East-African runners in their nationalities (Aschmann et al. 2013) or investigated a limited sample of the best athletes (Cribari et al. 2013). Indeed, East African runners particularly those from Ethiopia and Kenya account for the largest percentage of African runners in half-marathon and marathon (Aschmann et al. 2013). A recent study showed different barriers across both sex and distance (Wegner et al. 2015); hence, these trends might vary between half-marathon and marathon. The knowledge of East African’s basic characteristics such as age, participation and performance trends might help coaches, fitness trainers and sports scientists to improve their understanding of half-marathon’s demands.

Therefore, the aim of this study was to investigate performance and age of Ethiopian and Kenyan half- and full marathoners who competed between 1999 and 2014 in races held within one country (Switzerland) in a sample of more than 500,000 successful finishers. We hypothesized that female and male runners from Ethiopia and Kenya would also be the fastest in half-marathon races.

Methods

Ethics

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.

Data collection and data analysis

All half-marathons and marathons held in Switzerland from 1999 to 2014 were identified by using ‘Laufkalender Schweiz’ (www.laufkalender.ch). Since 1999, all running races in Switzerland started with an electronic chip system and full race results (i.e. name, age, sex, nationality and race time of the finishers) were available since then on the website of the specific races. Of all races, only those half-marathons and marathons were considered which were held on a road, not on a trail. No mountain marathons were included; start and finish of the race had to be on the same altitude. Athletes with missing age and/or missing nationality were excluded from data analysis. In order to avoid a selection bias due to a limitation to top runners, we considered all finishers from all countries. To investigate a trend in participation and performance, athletes from countries where at least one women and/or one man competed in at least 8 years (i.e. half of the investigated period of time) were considered.

Statistical analysis

Each set of data was tested for normal distribution (D’Agostino and Pearson omnibus normality test) and for homogeneity of variances (Levine’s test) prior to statistical analyses. Trends in participation across calendar years were analysed using regression analysis with linear growth equation models. Differences in the participation of East African runners by nationality and sex to half-marathons and marathon were examined by using Chi square (χ2) test. To investigate changes in performance across calendar years, we used a mixed-effects regression model with running speed as the dependent variable. We analysed women and men separately for each country for both half-marathon and marathon and included calendar year, sex, centered age, and squared centered age as fixed variables. To investigate changes in age across calendar years, we used a mixed-effects regression model with age as the dependent variable. For the change in age over time, we combined women and men for each country and included sex and calendar year as fixed variables. Differences in age and performance between athletes from multiple countries were compared using one-way analysis of variance (ANOVA) with subsequent Tukey’s multiple comparison tests with a single pooled variance. Statistical analyses were performed using IBM SPSS Statistics (Version 22, IBM SPSS, Chicago, IL, USA) and GraphPad Prism (Version 6.01, GraphPad Software, La Jolla, CA, USA). Significance was accepted at p < 0.05 (two-sided for t tests). Data in the text and tables are given as mean ± standard deviation (SD).

Results

Participation

Data from a total of 508,108 (125,894 female and 328,430 male half-marathoners and 10,205 female and 43,489 male marathoners) athletes was considered. These runners originated from a total of 126 countries spread around the globe. Table 1 summarizes the athletes from the considered countries for data analysis across calendar years in half-marathons (35 countries) and marathons (15 countries).
Table 1

Number of women and men considered by nationality for half-marathons and marathons, sorted by the overall participation

Country

Number of years

Number of women

Number of men

Overall

Half-marathon

    

 Ethiopia

14

24

48

72

 Kenya

14

80

134

214

 Switzerland

15

108,509

283,353

391,862

 Germany

15

5782

16,332

22,114

 France

15

5889

14,511

20,400

 Italy

15

984

2820

3804

 Austria

15

897

2141

3038

 Great Britain

15

872

2124

2996

 USA

15

331

909

1240

 Liechtenstein

15

304

675

979

 Belgium

14

180

567

747

 Spain

15

227

483

710

 Canada

15

208

411

619

 Netherlands

15

163

438

601

 Japan

15

167

398

565

 Sweden

14

111

246

357

 Finland

13

85

223

308

 Poland

14

100

199

299

 Portugal

15

56

190

246

 Denmark

15

60

186

246

 Luxembourg

15

85

146

231

 Hungary

14

51

175

226

 Czech Republic

15

62

162

224

 Australia

14

48

139

187

 Russia

14

62

109

171

 Norway

15

55

110

165

 Brazil

10

40

86

126

 Mexico

10

28

71

99

 Greece

12

20

74

94

 Republic of South Africa

11

32

44

76

 Israel

8

12

57

69

 India

8

23

45

68

 Ireland

14

11

24

35

 Argentina

8

13

22

35

 Slovenia

8

7

20

27

Marathon

    

 Ethiopia

8

3

15

18

 Kenya

13

2

33

35

 Switzerland

15

8376

35,084

43,460

 Germany

15

683

3319

4002

 France

15

539

2428

2967

 Austria

15

119

375

494

 Great Britain

15

97

389

486

 Italy

15

67

357

424

 USA

11

40

268

308

 Japan

15

48

119

167

 Belgium

8

14

123

137

 Canada

12

30

103

133

 Liechtenstein

11

25

78

103

 Spain

8

18

57

75

 Poland

8

14

52

66

In half-marathons, 48 women (0.038 %) and 63 men (0.019 %) originated from Ethiopia and 80 women (0.063 %) and 134 men (0.040 %) from Kenya. In marathons, three women (0.029 %) and 15 men (0.034 %) were from Ethiopia and two women (0.019 %) and 33 men (0.075 %) from Kenya. There was no statistically significant association between the nationality of East Africans and the format of the race [χ2(1) = 0.001, p = 0.978]; that was, both Ethiopians and Kenyans equally participated to half-marathons versus marathons. Also, there was no association between male East Africans and the format of the race [χ2(1) = 0.001, p = 0.922]; i.e. both male Ethiopians and Kenyans accounted equally to the two formats.

Most of the successful finishers originated from Switzerland, Germany and France in both half-marathons and marathons. In half-marathons, the number of women (r2 = 0.98, p < 0.0001) and men (r2 = 0.98, p < 0.0001) increased significantly. Similarly, the number of women (r2 = 0.46, p = 0.0041) and men (r2 = 0.51, p = 0.0019) increased significantly in marathons. Regarding the considered countries, the number of female half-marathoners from Canada (r2 = 0.81, p = 0.002), Germany (r2 = 0.97, p = 0.005), Switzerland (r2 = 0.97, p = 0.005) and Belgium (r2 = 0.72, p < 0.0001) increased significantly. For male half-marathoners, the number of participants from France (r2 = 0.97, p = 0.018), Great Britain (r2 = 0.88, p = 0.036), Principality of Liechtenstein (r2 = 0.87, p < 0.0001), Poland (r2 = 0.65, p < 0.0001), South Africa (r2 = 0.63, p = 0.006) and Argentina (r2 = 0.70, p < 0.0001) increased significantly. In marathoners, there was no significant increase in the number of men regarding the country. In women, however, participants from France (r2 = 0.46, p = 0.0275) and Japan (r2 = 0.47, p = 0.0039) increased significantly their numbers.

Trends in performance and age across calendar years

Table 2 shows the running speed of the female and male half-marathoners. Running speed decreased significantly in women from France, Switzerland, and Australia, but increased in women from Norway and Portugal (Table 3). In men, running speed decreased in athletes from Germany (Table 4). Table 5 presents running speed of female and male marathoners. Running speed remained unchanged in female marathoners (Table 6) but increased in British men (Table 7). Table 8 presents the age of the female and male half-marathoners. Age increased significantly across calendar years in women from Austria and Norway and in men from Japan and Norway (Table 9). In marathoners (Table 10), age decreased significantly in men from Italy and Principality of Liechtenstein, but increased significantly in men from Poland (Table 11).
Table 2

Running speed (km/h) with mean ± SD for the annual fastest female and male East-African and Non-African half-marathoners

 

1999

2000

2001

2002

2003

2004

2005

2006

Women

        

 Ethiopia

8.60

14.66 ± 7.42

8.10

 

19.57

19.59

19.63

14.14 ± 5.27

 Kenya

 

14.79 ± 7.29

 

9.43 ± 0.35

14.99 ± 8.04

14.18 ± 4.69

16.52 ± 3.36

18.84 ± 1.89

 Austria

7.49 ± 3.04

8.02 ± 3.64

7.84 ± 3.30

8.02 ± 3.06

7.98 ± 2.98

8.78 ± 3.59

8.44 ± 3.43

8.99 ± 3.54

 Canada

 

5.07 ± 1.30

7.78 ± 4.39

7.16 ± 3.70

5.86 ± 2.10

9.13 ± 4.75

7.76 ± 2.72

7.01 ± 2.56

 Czech Republic

5.09 ± 1.34

4.51

8.13 ± 4.82

5.63 ± 0.79

8.85 ± 3.83

10.83 ± 2.99

8.11 ± 3.16

10.13

 Denmark

 

10.81 ± 0.83

7.23 ± 4.15

8.84 ± 4.10

10.42 ± 1.16

9.58 ± 3.40

7.49 ± 2.77

6.87 ± 2.85

 Spain

9.87 ± 3.23

10.25 ± 2.32

10.53 ± 4.01

10.02 ± 3.15

11.01 ± 1.86

9.78 ± 2.81

10.07 ± 3.05

10.69 ± 2.29

 France

10.21 ± 3.23

9.99 ± 3.02

9.47 ± 3.25

9.94 ± 3.28

9.72 ± 3.17

9.68 ± 3.40

9.70 ± 3.48

9.27 ± 3.42

 Great Britain

9.81 ± 1.99

9.83 ± 2.84

9.18 ± 3.29

8.33 ± 3.13

10.38 ± 3.03

9.63 ± 3.20

10.26 ± 2.93

9.38 ± 3.08

 Germany

8.49 ± 2.97

8.35 ± 3.47

8.46 ± 3.15

8.39 ± 3.22

8.61 ± 3.35

8.31 ± 3.27

8.48 ± 3.40

8.31 ± 3.17

 Italy

9.76 ± 3.07

10.02 ± 3.26

10.4 ± 3.10

11.7 ± 2.62

10.01 ± 3.31

11.35 ± 2.92

10.68 ± 3.10

10.98 ± 3.11

 Japan

6.21 ± 2.80

6.15 ± 2.47

7.35 ± 2.53

7.94 ± 2.95

6.57 ± 3.37

6.20 ± 2.48

6.52 ± 1.96

8.09 ± 2.77

 Liechtenstein

10.21 ± 2.09

10.17 ± 2.32

11.49 ± 2.51

11.51 ± 2.25

10.96 ± 2.63

10.85 ± 3.55

11.26 ± 1.50

9.94 ± 2.66

 Luxembourg

5.87 ± 1.58

7.80 ± 3.15

8.15 ± 4.64

8.19 ± 3.56

8.25 ± 3.33

6.86 ± 2.39

7.45 ± 1.22

8.61 ± 3.06

 Netherlands

10.90 ± 1.25

11.56 ± 2.30

10.79 ± 1.16

11.47 ± 2.19

9.51 ± 2.63

10.12 ± 2.68

10.45 ± 4.47

8.97 ± 3.29

 Norway

 

6.83 ± 3.05

7.12 ± 4.66

9.7 ± 1.93

4.56

9.59 ± 3.81

10.27 ± 3.84

8.45 ± 4.13

 Portugal

 

10.97

13.53

8.41 ± 3.32

11.08 ± 2.74

10.12 ± 3.31

10.15 ± 3.98

11.52 ± 3.36

 Switzerland

10.59 ± 2.97

10.75 ± 2.87

10.63 ± 2.91

10.63 ± 2.92

10.58 ± 2.90

10.57 ± 2.90

10.45 ± 2.93

10.51 ± 2.90

 USA

12.05 ± 0.61

9.50 ± 2.92

9.39 ± 3.02

8.67 ± 3.46

7.90 ± 3.10

8.58 ± 3.60

8.34 ± 3.27

8.88 ± 2.62

 Australia

 

10.96

9.08 ± 4.03

9.89 ± 3.60

9.85 ± 4.61

 

8.09 ± 3.28

8.12 ± 3.14

 Belgium

8.22 ± 3.49

 

9.62 ± 5.59

7.70 ± 2.50

9.50 ± 1.87

7.88 ± 2.19

8.99 ± 3.28

7.83 ± 3.10

 Hungary

8.44

9.09

 

8.46

11.79

10.96

11.62

10.07 ± 3.41

 Ireland

9.44 ± 4.42

11.13

10.45 ± 0.33

8.60 ± 3.12

11.12 ± 3.02

10.49 ± 2.69

 

11.99 ± 1.66

 Poland

8.19 ± 5.46

 

5.17 ± 1.00

4.39

9.58 ± 3.89

7.41 ± 2.78

7.49 ± 2.98

7.80 ± 3.18

 Russia

11.19

9.73 ± 0.24

9.60

8.00

 

9.05 ± 3.13

7.31 ± 2.71

8.42 ± 2.99

 Sweden

5.04

 

7.05 ± 3.13

11.66 ± 1.29

9.58 ± 3.82

10.02 ± 2.09

9.35 ± 3.67

7.47 ± 2.66

 Finland

10.80 ± 0.50

5.07

 

8.42 ± 4.75

 

6.76 ± 3.14

6.14 ± 2.01

7.43 ± 0.33

 Greece

    

5.82

6.39

10.65

12.02

 South Africa

   

6.76 ± 2.45

11.59

12.73

5.32

5.06 ± 0.12

 Brazil

9.95 ± 0.67

12.10 ± 2.16

 

5.49

10.28

11.06

8.72 ± 4.37

 

 Mexico

     

9.76

 

10.07 ± 1.18

 Argentina

   

9.74

   

10.44

 India

 

9.74

   

10.48

9.63 ± 1.48

10.62 ± 1.09

 Israel

     

4.37

4.50

 

 Slovenia

      

5.06

 

Men

        

 Ethiopia

9.71 ± 2.04

19.11

13.41 ± 6.70

8.13 ± 0.79

12.93 ± 7.40

10.84 ± 5.18

8.39 ± 0.39

12.24 ± 5.34

 Kenya

12.76 ± 4.68

14.62 ± 5.32

12.24 ± 5.38

14.7 ± 5.13

12.31 ± 6.99

10.78 ± 4.83

15.35 ± 5.68

11.47 ± 4.39

 Austria

 

9.36 ± 3.57

11.77 ± 2.60

9.87 ± 3.42

8.97 ± 2.26

11.03 ± 1.91

8.98 ± 3.12

7.38 ± 2.43

 Canada

7.81 ± 3.15

6.99 ± 2.69

8.32 ± 3.28

7.78 ± 3.05

8.95 ± 3.65

7.29 ± 2.87

6.35 ± 2.61

5.91 ± 2.34

 Czech Republic

8.06 ± 2.00

10.45 ± 3.87

10.3 ± 2.72

11.15 ± 3.54

8.85 ± 4.47

10.01 ± 2.75

9.63 ± 3.10

8.94 ± 2.96

 Denmark

 

6.68 ± 1.70

7.04 ± 2.49

8.65 ± 2.96

6.91 ± 2.03

8.25 ± 2.94

8.65 ± 2.90

9.15 ± 3.74

 Spain

10.63 ± 3.75

11.23 ± 1.76

9.84 ± 3.25

8.32 ± 3.01

9.24 ± 2.84

8.88 ± 3.00

8.41 ± 3.41

9.07 ± 2.89

 France

9.82 ± 3.37

9.43 ± 3.35

9.47 ± 3.33

9.72 ± 3.37

9.49 ± 3.29

9.39 ± 3.32

9.56 ± 3.35

9.83 ± 3.33

 Great Britain

9.49 ± 2.92

9.32 ± 3.16

9.31 ± 3.16

9.34 ± 3.09

9.89 ± 2.84

9.06 ± 3.04

9.19 ± 3.16

9.37 ± 3.11

 Germany

8.58 ± 3.26

8.56 ± 3.25

8.42 ± 3.16

8.58 ± 3.28

8.35 ± 3.23

8.44 ± 3.21

8.28 ± 3.23

8.60 ± 3.18

 Italy

10.55 ± 3.16

10.55 ± 3.01

10.73 ± 3.05

10.54 ± 2.86

10.59 ± 3.17

10.64 ± 3.23

10.82 ± 3.00

10.68 ± 3.18

 Japan

4.14 ± 0.31

6.47 ± 3.61

6.51 ± 3.43

5.55 ± 2.22

7.03 ± 2.61

7.03 ± 3.97

7.03 ± 3.03

5.93 ± 2.90

 Liechtenstein

10.92 ± 2.10

10.09 ± 2.76

10.61 ± 2.48

10.57 ± 2.78

11.17 ± 1.84

10.76 ± 2.48

10.57 ± 3.07

10.84 ± 2.37

 Luxembourg

9.41 ± 3.96

7.14 ± 3.04

6.82 ± 2.23

6.88 ± 2.58

6.85 ± 2.40

8.23 ± 2.93

8.04 ± 3.00

7.48 ± 3.02

 Netherlands

10.39 ± 4.64

9.52 ± 2.15

10.99 ± 3.41

9.02 ± 3.67

8.85 ± 3.23

9.75 ± 3.09

9.02 ± 3.05

10.63 ± 4.05

 Norway

12.91

7.29 ± 0.30

10.91 ± 2.32

9.11 ± 2.42

8.20 ± 3.73

9.20 ± 2.66

9.96 ± 1.05

9.71 ± 3.80

 Portugal

12.04 ± 1.87

12.87 ± 0.62

12.37 ± 2.79

11.63 ± 3.25

9.60 ± 2.92

11.82 ± 1.97

9.39 ± 3.48

11.76 ± 2.08

 Switzerland

10.31 ± 3.05

10.52 ± 2.96

10.50 ± 2.94

10.38 ± 2.96

10.43 ± 2.98

10.43 ± 2.95

10.41 ± 2.98

10.44 ± 2.99

 USA

7.44 ± 3.01

7.83 ± 3.35

7.44 ± 3.07

7.79 ± 3.31

8.02 ± 2.75

8.25 ± 2.69

8.97 ± 2.72

8.41 ± 3.20

 Australia

 

9.36 ± 3.57

11.77 ± 2.60

9.87 ± 3.42

8.97 ± 2.26

11.03 ± 2.91

8.98 ± 3.12

7.38 ± 2.43

 Belgium

9.57 ± 3.14

9.7 ± 2.92

9.93 ± 3.16

8.68 ± 3.45

9.00 ± 3.16

9.54 ± 3.40

9.93 ± 2.43

9.17 ± 3.37

 Hungary

 

12.34

11.70 ± 1.26

8.79 ± 3.02

10.93 ± 3.01

9.21 ± 2.83

11.46 ± 2.42

11.23 ± 2.74

 Ireland

9.17 ± 5.65

9.84 ± 2.78

7.95 ± 2.65

7.14 ± 3.44

8.15 ± 3.25

7.55 ± 3.84

8.57 ± 3.16

8.48 ± 3.58

 Poland

6.20 ± 1.79

5.52 ± 0.84

8.77 ± 2.71

8.69 ± 5.06

11.68 ± 3.38

9.43 ± 5.84

9.28 ± 2.95

8.93 ± 2.87

 Russia

 

8.17 ± 4.61

8.53 ± 3.25

9.29 ± 2.78

7.45 ± 2.53

8.18 ± 2.56

8.61 ± 2.09

9.26 ± 2.81

 Sweden

8.29 ± 4.64

7.26 ± 4.06

9.08 ± 2.67

7.36 ± 3.64

7.98 ± 3.01

8.33 ± 3.71

7.95 ± 3.48

8.04 ± 3.23

 Finland

7.66 ± 4.62

7.36 ± 2.81

7.37 ± 2.67

6.95 ± 2.59

5.22 ± 1.75

7.56 ± 2.68

8.10 ± 2.65

8.24 ± 3.08

 Greece

5.65

5.60

6.52 ± 0.82

6.52 ± 3.20

11.17 ± 1.66

9.93 ± 4.58

8.53 ± 3.53

8.40 ± 4.46

 South Africa

4.24

  

4.80

 

7.93 ± 3.70

10.72

7.91 ± 4.32

 Brazil

5.21 ± 0.56

7.45 ± 3.02

8.91 ± 3.46

 

6.97 ± 3.01

  

6.70 ± 1.90

 Mexico

10.67

10.56

6.32

7.00 ± 2.84

8.26 ± 3.64

6.28 ± 2.79

5.68

11.90 ± 0.42

 Argentina

    

9.24

6.13

4.24

5.96

 India

 

9.57 ± 2.06

9.86 ± 0.45

7.89

9.92 ± 0.88

 

9.93 ± 0.78

9.58 ± 0.88

 Israel

 

10.44 ± 3.74

 

6.05 ± 0.69

13.25 ± 0.04

7.88 ± 4.88

5.88

6.13 ± 1.58

 Slovenia

 

5.75

6.89

5.58 ± 1.53

11.48

11.62

8.49 ± 5.25

8.89 ± 3.77

 

2007

2008

2009

2010

2011

2012

2013

2014

Women

        

 Ethiopia

9.90 ± 3.96

15.01 ± 4.45

12.86 ± 5.72

13.86 ± 5.98

11.05 ± 4.50

15.73 ± 5.65

10.44 ± 5.79

12.03 ± 4.74

 Kenya

13.44 ± 4.18

16.39 ± 4.74

16.66 ± 5.50

13.39 ± 7.36

11.63 ± 4.81

14.07 ± 5.28

15.96 ± 5.42

12.08 ± 5.73

 Austria

7.71 ± 2.64

7.63 ± 2.90

7.56 ± 2.55

8.10 ± 3.15

7.79 ± 3.13

8.27 ± 3.31

7.82 ± 3.26

7.84 ± 3.14

 Canada

6.09 ± 3.02

7.10 ± 3.19

7.88 ± 3.84

7.86 ± 4.29

7.45 ± 3.47

7.14 ± 3.04

7.13 ± 2.98

7.59 ± 3.34

 Czech Republic

7.09 ± 2.73

12.49 ± 1.72

9.53 ± 4.79

9.46 ± 7.30

9.44 ± 3.61

8.54 ± 3.36

14.24 ± 5.94

10.53 ± 2.73

 Denmark

7.86 ± 3.89

5.19

6.82 ± 2.96

9.61 ± 2.48

7.86 ± 2.83

9.65 ± 3.71

8.04 ± 3.40

10.24 ± 3.50

 Spain

9.87 ± 3.40

9.55 ± 3.32

9.55 ± 2.86

11.20 ± 2.95

9.26 ± 3.37

10.49 ± 2.88

9.54 ± 3.55

9.56 ± 3.45

 France

9.35 ± 3.40

9.82 ± 3.32

9.58 ± 3.37

9.45 ± 3.31

9.44 ± 3.32

9.54 ± 3.17

9.40 ± 3.26

9.28 ± 3.31

 Great  Britain

8.35 ± 3.58

9.53 ± 2.97

9.48 ± 3.21

9.63 ± 3.01

9.03 ± 3.13

8.79 ± 3.13

8.73 ± 3.00

9.14 ± 3.28

 Germany

8.58 ± 3.24

8.43 ± 3.09

8.61 ± 3.23

8.39 ± 3.08

8.31 ± 3.13

8.50 ± 3.19

8.16 ± 3.27

8.42 ± 3.21

 Italy

10.91 ± 3.34

11.17 ± 2.97

11.30 ± 3.06

10.91 ± 3.55

10.82 ± 3.13

10.00 ± 3.40

10.74 ± 3.07

10.47 ± 2.92

 Japan

5.93 ± 2.94

6.03 ± 2.53

5.64 ± 1.97

6.55 ± 2.41

5.72 ± 2.53

5.41 ± 1.78

5.55 ± 2.90

6.95 ± 3.00

 Liechtenstein

11.17 ± 1.82

10.81 ± 1.91

11.11 ± 2.31

10.36 ± 2.96

11.28 ± 2.94

11.16 ± 2.53

10.63 ± 2.92

11.33 ± 2.54

 Luxembourg

8.11 ± 2.34

8.14 ± 3.27

9.20 ± 2.78

8.36 ± 2.96

10.69 ± 2.62

8.00 ± 3.03

7.80 ± 3.28

7.23 ± 2.42

 Netherlands

9.01 ± 3.60

9.18 ± 3.27

8.96 ± 3.39

8.96 ± 3.48

9.19 ± 3.50

9.45 ± 3.83

9.54 ± 3.35

9.85 ± 3.10

 Norway

9.03 ± 3.29

7.62 ± 3.02

8.66 ± 0.69

11.22 ± 5.16

10.88 ± 1.43

12.37 ± 0.60

11.79 ± 1.32

11.12 ± 2.75

 Portugal

10.08 ± 3.62

13.55 ± 5.79

13.38 ± 1.35

12.12 ± 0.72

12.47

15.11 ± 3.09

10.49 ± 4.48

12.28 ± 2.50

 Switzerland

10.35 ± 2.97

10.48 ± 2.92

10.55 ± 2.90

10.50 ± 2.92

10.53 ± 2.94

10.46 ± 2.94

10.43 ± 2.95

10.41 ± 2.95

 USA

8.80 ± 3.00

8.81 ± 3.73

9.07 ± 3.17

8.69 ± 3.81

8.54 ± 2.97

9.19 ± 3.06

8.78 ± 2.88

8.20 ± 3.29

 Australia

8.24 ± 3.18

8.71

10.99 ± 0.60

7.37 ± 3.14

10.75 ± 2.72

6.52 ± 1.65

6.99 ± 3.22

7.60 ± 2.60

 Belgium

7.98 ± 3.11

7.27 ± 2.86

8.29 ± 3.30

8.01 ± 3.48

8.66 ± 3.23

9.60 ± 3.07

8.23 ± 3.12

9.32 ± 3.10

 Hungary

9.16 ± 1.44

11.03

10.16 ± 2.24

11.68

9.79 ± 3.84

12.71 ± 2.62

11.64 ± 1.45

10.94 ± 2.68

 Ireland

10.68

10.91

9.53 ± 2.66

9.55 ± 4.34

8.61 ± 3.35

9.73 ± 2.70

10.25 ± 3.59

8.47 ± 3.34

 Poland

7.86 ± 3.43

10.36 ± 3.87

8.64 ± 2.75

8.07 ± 4.13

11.18 ± 3.66

7.73 ± 5.63

10.67 ± 3.45

8.29 ± 2.65

 Russia

6.06

8.62 ± 1.93

11.04 ± 4.56

11.40 ± 2.66

10.26 ± 2.10

8.33 ± 2.18

9.97 ± 3.41

10.18 ± 0.66

 Sweden

7.31 ± 3.34

7.16 ± 2.98

9.39 ± 3.78

9.73 ± 3.90

7.98 ± 2.84

7.57 ± 2.82

7.36 ± 3.03

8.42 ± 3.20

 Finland

8.74 ± 6.63

5.40 ± 1.36

6.50 ± 3.09

5.54 ± 1.03

5.97 ± 2.95

6.18 ± 1.90

5.90 ± 1.85

8.03 ± 3.53

 Greece

10.02 ± 1.19

7.17

5.08

9.06

6.80

7.71 ± 3.94

11.79 ± 1.20

9.14 ± 2.16

 South Africa

11.31 ± 1.03

8.83 ± 2.10

8.22 ± 2.89

 

9.44 ± 1.14

9.04 ± 3.87

7.47 ± 3.19

7.43

 Brazil

9.84 ± 2.47

9.45 ± 2.48

9.95 ± 1.26

6.80 ± 3.46

7.80 ± 3.30

10.23 ± 1.14

9.27 ± 1.28

8.98 ± 2.97

 Mexico

10.97 ± 0.92

9.24 ± 0.15

11.97 ± 2.03

7.75 ± 2.36

6.81 ± 2.78

7.82 ± 3.91

7.45

9.25 ± 1.79

 Argentina

12.68

 

11.85

4.50 ± 0.25

4.98

10.69 ± 1.09

12.53 ± 2.37

10.44 ± 1.89

 India

9.85 ± 0.91

 

9.09

 

10.01 ± 0.93

 

10.92 ± 1.75

10.8 ± 1.75

 Israel

  

13.38

9.64

5.41 ± 0.18

8.74

8.56 ± 3.24

13.18 ± 1.01

 Slovenia

5.61

 

9.28 ± 4.70

 

7.82 ± 3.48

  

5.54

Men

        

 Ethiopia

10.80 ± 4.09

15.38 ± 5.10

9.87 ± 4.18

8.75 ± 0.70

11.34 ± 4.62

7.94 ± 0.52

13.60 ± 4.71

10.78 ± 4.94

 Kenya

14.85 ± 5.54

12.67 ± 5.10

13.56 ± 4.77

11.77 ± 4.17

11.58 ± 4.70

10.86 ± 4.81

10.42 ± 3.17

13.14 ± 4.80

 Austria

9.36 ± 3.01

10.55 ± 2.78

11.75 ± 2.30

9.81 ± 2.90

8.21 ± 2.92

9.43 ± 3.00

8.31 ± 3.18

9.25 ± 2.82

 Canada

6.79 ± 3.43

6.33 ± 3.14

7.63 ± 3.17

7.77 ± 3.07

7.24 ± 2.77

7.5 ± 3.20

7.62 ± 3.15

8.29 ± 3.34

 Czech Republic

8.35 ± 3.03

8.47 ± 3.99

8.23 ± 4.09

9.64 ± 3.40

6.25 ± 1.60

7.84 ± 2.92

7.51 ± 2.93

9.10 ± 3.82

 Denmark

9.08 ± 2.97

9.36 ± 2.55

8.59 ± 3.08

7.92 ± 2.65

5.99 ± 2.49

7.08 ± 2.70

8.41 ± 3.14

8.02 ± 2.96

 Spain

9.76 ± 2.91

10.74 ± 2.85

10.30 ± 2.59

8.74 ± 2.87

8.61 ± 3.40

10.22 ± 2.92

9.76 ± 3.37

8.79 ± 3.03

 France

9.56 ± 3.34

9.48 ± 3.26

9.46 ± 3.33

9.52 ± 3.33

9.43 ± 3.35

9.38 ± 3.30

9.50 ± 3.34

9.54 ± 3.30

 Great Britain

9.29 ± 2.94

8.88 ± 3.06

8.51 ± 3.06

8.88 ± 3.16

9.00 ± 3.12

8.95 ± 3.29

8.63 ± 3.24

8.66 ± 3.16

 Germany

8.75 ± 3.26

8.57 ± 3.25

8.79 ± 3.32

8.34 ± 3.13

8.35 ± 3.17

8.34 ± 3.24

8.39 ± 3.15

8.29 ± 3.17

 Italy

10.56 ± 3.32

10.90 ± 3.04

10.54 ± 3.27

10.41 ± 3.14

10.24 ± 3.32

10.10 ± 3.27

10.09 ± 3.28

10.18 ± 3.37

 Japan

6.95 ± 3.17

5.64 ± 2.41

6.15 ± 2.52

6.94 ± 3.02

7.00 ± 3.13

7.32 ± 3.23

6.37 ± 2.84

6.20 ± 2.44

 Liechtenstein

10.65 ± 3.20

10.17 ± 2.68

10.84 ± 2.43

10.83 ± 2.81

10.86 ± 2.80

10.41 ± 2.80

10.23 ± 2.89

10.18 ± 2.81

 Luxembourg

9.47 ± 3.24

8.76 ± 3.63

7.81 ± 2.80

8.34 ± 2.30

8.43 ± 2.69

7.60 ± 2.54

6.68 ± 2.23

8.15 ± 3.89

 Netherlands

9.21 ± 3.14

9.34 ± 3.31

9.71 ± 3.49

9.27 ± 3.03

10.31 ± 3.35

8.90 ± 3.29

9.65 ± 3.06

8.94 ± 3.51

 Norway

8.12 ± 2.09

8.86 ± 0.28

10.53 ± 2.96

7.19 ± 3.29

7.84 ± 2.91

9.80 ± 3.54

8.92 ± 3.32

10.12 ± 3.20

 Portugal

11.48 ± 2.40

10.45 ± 2.55

11.52 ± 2.59

10.86 ± 3.65

11.52 ± 4.09

11.34 ± 1.68

9.84 ± 3.66

10.65 ± 2.92

 Switzerland

10.43 ± 2.99

10.46 ± 2.96

10.45 ± 2.95

10.41 ± 2.98

10.43 ± 2.96

10.38 ± 2.99

10.39 ± 3.02

10.44 ± 2.99

 USA

8.41 ± 2.91

8.05 ± 2.93

7.87 ± 2.89

8.65 ± 2.76

8.38 ± 3.18

8.01 ± 3.03

7.74 ± 3.15

8.08 ± 3.16

 Australia

9.36 ± 3.01

10.55 ± 2.78

11.75 ± 2.30

9.81 ± 2.90

8.21 ± 2.92

9.43 ± 3.00

8.31 ± 3.18

9.25 ± 2.82

 Belgium

9.49 ± 2.92

8.46 ± 3.22

9.20 ± 2.78

8.41 ± 3.00

8.43 ± 3.07

7.31 ± 2.52

8.33 ± 2.85

8.86 ± 2.86

 Hungary

8.52 ± 3.40

9.11 ± 4.00

9.54 ± 2.78

9.24 ± 2.79

9.74 ± 2.76

9.55 ± 3.17

11.73 ± 1.69

10.21 ± 2.69

 Ireland

8.90 ± 2.50

9.31 ± 2.85

8.80 ± 3.29

10.25 ± 3.17

9.36 ± 3.08

8.56 ± 2.93

7.67 ± 2.97

8.59 ± 3.40

 Poland

7.48 ± 3.00

9.23 ± 3.36

9.01 ± 4.29

8.18 ± 3.84

7.52 ± 2.96

8.20 ± 3.84

8.28 ± 3.32

9.37 ± 3.35

 Russia

11.05 ± 2.22

8.55 ± 3.57

7.65 ± 3.03

8.00 ± 2.78

7.89 ± 2.98

8.16 ± 2.96

7.98 ± 2.77

8.61 ± 2.32

 Sweden

7.43 ± 2.89

9.01 ± 3.11

6.64 ± 2.25

8.04 ± 2.67

7.86 ± 3.25

8.58 ± 3.32

9.12 ± 3.17

8.45 ± 3.39

 Finland

8.05 ± 3.47

7.84 ± 2.48

7.84 ± 3.20

7.78 ± 3.31

6.35 ± 1.99

6.58 ± 2.74

6.30 ± 1.72

6.01 ± 2.14

 Greece

8.29 ± 3.10

7.10 ± 2.30

9.98 ± 3.77

7.81 ± 2.91

8.60 ± 6.27

7.78 ± 2.60

10.31 ± 2.36

8.35 ± 2.92

 South Africa

8.63 ± 1.61

10.38 ± 1.53

9.37 ± 3.48

7.06 ± 3.19

6.71 ± 3.78

10.31 ± 4.19

8.00 ± 4.50

6.10 ± 2.32

 Brazil

7.31 ± 2.50

8.41 ± 3.06

7.60 ± 2.82

10.22 ± 3.11

7.94 ± 3.19

7.34 ± 3.03

9.36 ± 2.94

7.78 ± 2.68

 Mexico

9.04 ± 3.93

10.32 ± 2.81

9.71 ± 6.11

9.19 ± 3.75

9.57 ± 3.57

8.97 ± 3.36

8.01 ± 3.50

6.99 ± 3.16

 Argentina

10.55

5.85

9.55 ± 3.14

7.25 ± 3.00

4.63 ± 0.21

11.09 ± 3.30

11.16 ± 0.53

8.67 ± 3.14

 India

5.40

10.78 ± 3.92

6.87 ± 2.68

6.38 ± 2.90

9.44 ± 1.51

9.65 ± 0.17

8.22 ± 3.74

8.58 ± 2.95

 Israel

8.7 ± 2.60

8.93 ± 4.48

8.78 ± 3.51

10.09 ± 3.80

7.13 ± 2.68

8.91 ± 2.18

9.42 ± 3.68

10.21 ± 4.32

 Slovenia

  

9.50 ± 3.82

4.58

10.82

7.16 ± 3.24

8.06 ± 4.48

 

Data for Non-African runners are sorted in order of the number of finishers of each country

Table 3

Results of the mixed-effects regression analyses for change in running speed in female half-marathoners across years

Parameter

Estimate

SE

DF

T

p value

95 % CI

Upper

Lower

Ethiopia

       

 Constant term

293.167388

371.574985

43.863

0.789

0.434

−455.758951

1042.093726

 Year

−0.140332

0.184932

43.873

−0.759

0.452

−0.513068

0.232405

 Cage

−0.173148

0.135294

36.958

−1.280

0.209

−0.447291

0.100995

 Cage2

−0.004387

0.006022

27.717

−0.728

0.472

−0.016727

0.007954

Kenya

       

 Constant term

−21.426837

150.844832

36.330

−.0142

0.888

−327.257984

284.404310

 Year

0.017207

0.075087

36.326

0.229

0.820

−0.135029

0.169443

 Cage

−0.144332

0.060829

27.148

−2.373

0.025

−0.269111

−0.019552

 Cage2

−0.003215

0.003653

30.133

−0.880

0.386

−0.010674

0.004243

Austria

       

 Constant term

31.578045

29.443671

597.888

1.072

0.284

−26.247547

89.403637

 Year

−0.011598

0.014658

597.871

−0.791

0.429

−0.040386

0.017190

 Cage

−0.028602

0.006916

600.177

−4.136

0.000

−0.042184

−0.015021

 Cage2

0.000663

0.000536

608.882

1.237

0.217

−0.000390

0.001716

Canada

       

 Constant term

−125.514888

73.115253

155.945

−1.717

0.088

−269.938931

18.909154

 Year

0.066249

0.036396

155.933

1.820

0.071

−0.005644

0.138143

 Cage

−0.020679

0.014519

170.268

−1.424

0.156

−0.049340

0.007982

 Cage2

7.822872E−5

0.001161

162.137

0.067

0.946

−0.002214

0.002370

Czech Republic

 Constant term

−220.270108

155.839548

40.611

−1.413

0.165

−535.086061

94.545845

 Year

0.113694

0.077609

40.610

1.465

0.151

−0.043086

0.270474

 Cage

−0.080535

0.051903

45.473

−1.552

0.128

−0.185044

0.023974

 Cage2

0.003476

0.004529

46.743

0.768

0.447

−0.005637

0.012589

Denmark

       

 Constant term

−144.099673

142.620810

55.173

−1.010

0.317

−429.897999

141.698652

 Year

0.076052

0.070989

55.174

1.071

0.289

−0.066203

0.218308

 Cage

−.012618

0.030636

58.407

−0.412

0.682

−0.073934

0.048697

 Cage2

−.000446

0.002495

59.214

−0.179

0.859

−0.005439

0.004546

Spain

       

 Constant term

−5.366288

67.028907

141.702

−0.080

0.936

−137.872163

127.139587

 Year

0.007615

0.033366

141.702

0.228

0.820

−0.058344

0.073574

 Cage

0.001968

0.014710

129.823

0.134

0.894

−0.027134

0.031069

 Cage2

−0.000865

0.001169

144.790

−0.740

0.461

−0.003175

0.001445

France

       

 Constant term

51.171466

15.295732

4653.214

3.345

0.001

21.184581

81.158350

 Year

−0.020670

0.007613

4653.140

−2.715

0.007

−0.035595

−0.005744

 Cage

−0.023120

0.003408

4755.183

−6.783

0.000

−0.029801

−0.016438

 Cage2

−0.000602

0.000252

4810.855

−2.392

0.017

−0.001095

−0.000109

Great Britain

 Constant term

28.901729

42.017402

749.113

0.688

0.492

−53.584137

111.387595

 Year

−0.009779

0.020917

749.099

−0.468

0.640

−0.050842

0.031283

 Cage

0.009513

0.009652

844.541

0.986

0.325

−0.009432

0.028457

 Cage2

−0.001723

0.000775

871.578

−2.222

0.027

−0.003245

−0.000201

Germany

       

 Constant term

15.158368

14.956731

4456.047

1.013

0.311

−14.164251

44.480986

 Year

−0.003244

0.007446

4455.945

−0.436

0.663

−0.017841

0.011353

 Cage

−0.023479

0.002955

3893.061

−7.946

0.000

−0.029272

−0.017686

 Cage2

−0.000163

0.000198

3910.190

−0.822

0.411

−0.000551

0.000225

Italy

       

 Constant term

55.277603

39.067728

844.859

1.415

0.157

−21.403589

131.958795

 Year

−0.022114

0.019449

844.831

−1.137

0.256

−0.060287

0.016060

 Cage

−0.049367

0.010292

954.174

−4.797

0.000

−0.069565

−0.029169

 Cage2

−0.001914

0.000776

961.174

−2.467

0.014

−0.003436

−0.000391

Japan

       

 Constant term

70.707877

63.986213

101.377

1.105

0.272

−56.217842

197.633596

 Year

−0.031946

0.031855

101.405

−1.003

0.318

−.0095133

0.031242

 Cage

−0.047542

0.017703

159.965

−2.685

0.008

−0.082504

−0.012579

 Cage2

0.001527

0.000930

166.855

1.641

0.103

−0.000310

0.003363

Principality of Liechtenstein

 Constant term

10.483455

64.869741

255.178

0.162

0.872

−117.264786

138.231696

 Year

0.000233

0.032291

255.155

0.007

0.994

−0.063358

0.063823

 Cage

−0.012747

0.013132

275.553

−0.971

0.333

−0.038598

0.013105

 Cage2

−0.001544

0.001094

290.811

−1.411

0.159

−0.003697

0.000610

Luxembourg

 Constant term

−47.666634

97.322485

48.909

−0.490

0.626

−243.252737

147.919469

 Year

0.027753

0.048451

48.906

0.573

0.569

−0.069617

0.125123

 Cage

−0.023725

0.013396

31.814

−1.771

0.086

−0.051017

0.003567

 Cage2

0.001603

0.001046

30.499

1.533

0.136

−0.000532

0.003737

Netherlands

 Constant term

133.938661

125.455169

149.777

1.068

0.287

−113.951882

381.829205

 Year

−0.062003

0.062457

149.769

−0.993

0.322

−0.185413

0.061407

 Cage

−0.011427

0.021283

105.363

−0.537

0.592

−0.053626

0.030771

 Cage2

0.000320

0.001177

84.597

0.272

0.786

−0.002020

0.002660

Norway

       

 Constant term

−487.272616

173.193914

54.820

−2.813

0.007

−834.386566

−140.158666

 Year

0.247478

0.086290

54.821

2.868

0.006

0.074537

0.420419

 Cage

−0.115170

0.020554

36.162

−5.603

0.000

−0.156850

−0.073491

 Cage2

0.002664

0.001240

33.459

2.150

0.039

0.000144

0.005185

Portugal

       

 Constant term

−474.101901

231.004145

55.403

−2.052

0.045

−936.968950

−11.234851

 Year

0.241610

0.114974

55.397

2.101

0.040

0.011234

0.471987

 Cage

−0.006509

0.059010

54.339

−0.110

0.913

−0.124800

0.111783

 Cage2

0.004436

0.005816

53.398

0.763

0.449

−0.007227

0.016100

Switzerland

 Constant term

17.415465

3.082751

85,158.813

5.649

0.000

11.373300

23.457631

 Year

−0.003429

0.001535

85,155.422

−2.235

0.025

−0.006437

−0.000422

 Cage

−0.010236

0.000499

71,948.591

−20.518

0.000

−0.011214

−0.009259

 Cage2

−0.000417

3.413093E−5

70,505.318

−12.217

0.000

−0.000484

−0.000350

United States of America

 Constant term

−102.180938

71.308524

295.142

−1.433

0.153

−242.518553

38.156677

 Year

0.055053

0.035488

295.135

1.551

0.122

−0.014789

0.124895

 Cage

−0.011404

0.012867

301.169

−0.886

0.376

−0.036725

0.013917

 Cage2

0.001037

0.000928

305.711

1.118

0.265

−0.000789

0.002863

Australia

 Constant term

535.990276

98.301322

13.686

5.453

0.000

324.700562

747.279990

 Year

−0.262740

0.048925

13.688

−5.370

0.000

−0.367899

−0.157580

 Cage

0.063641

0.055873

47.462

1.139

0.260

−0.048733

0.176014

 Cage2

−0.002360

0.002842

46.702

−0.830

0.411

−0.008078

0.003358

Belgium

 Constant term

7.038611

107.628613

165.205

0.065

0.948

−205.466290

219.543511

 Year

0.000697

0.053552

165.225

0.013

0.990

−0.105038

0.106433

 Cage

0.000626

0.015637

117.693

0.040

0.968

−0.030341

0.031593

 Cage2

0.000700

0.001032

108.364

0.678

0.499

−0.001345

0.002745

Hungary

 Constant term

−275.257629

154.694094

51.000

−1.779

0.081

−585.818982

35.303724

 Year

0.142544

0.076947

51.000

1.853

0.070

−0.011933

0.297021

 Cage

−0.083478

0.047940

51.000

−1.741

0.088

−0.179721

0.012765

 Cage2

0.000717

0.002086

51.000

0.344

0.732

−0.003470

0.004904

Ireland

       

 Constant term

−33.859940

165.743508

57.989

−0.204

0.839

−365.633001

297.913121

 Year

0.021718

0.082524

57.993

0.263

0.793

−0.143473

0.186909

 Cage

−0.036636

0.037101

37.244

−0.987

0.330

−0.111793

0.038521

 Cage2

−0.000562

0.003459

32.491

−0.162

0.872

−0.007603

0.006480

Poland

       

 Constant term

−72.726997

104.051935

60.961

−0.699

0.487

−280.794379

135.340384

 Year

0.040347

0.051798

60.974

0.779

0.439

−0.063230

0.143924

 Cage

−0.053476

0.023476

65.801

−2.278

0.026

−0.100351

−0.006601

 Cage2

−0.001860

0.001865

69.955

−0.997

0.322

−0.005579

0.001859

Russia

       

 Constant term

−106.441127

155.565229

42.567

−0.684

0.498

−420.260572

207.378318

 Year

0.057206

0.077443

42.538

0.739

0.464

−0.099022

0.213434

 Cage

−0.072584

0.042398

55.257

−1.712

0.093

−0.157542

0.012374

 Cage2

0.004846

0.003169

47.538

1.529

0.133

−0.001528

0.011219

Sweden

       

 Constant term

75.820147

143.966277

104.839

0.527

0.600

−209.643494

361.283787

 Year

−0.033856

0.071641

104.838

−0.473

0.637

−0.175909

0.108197

 Cage

−0.016537

0.020415

67.482

−0.810

0.421

−0.057279

0.024206

 Cage2

0.001067

0.001713

108.162

0.623

0.535

−0.002328

0.004462

Finland

       

 Constant term

−46.926724

100.378904

55.066

−0.467

0.642

−248.085146

154.231697

 Year

0.027006

0.049943

55.068

0.541

0.591

−0.073079

0.127091

 Cage

−0.053711

0.015750

46.121

−3.410

0.001

−0.085411

−0.022011

 Cage2

0.001208

0.001076

44.445

1.123

0.268

−0.000960

0.003376

Greece

       

 Constant term

−105.607974

339.956176

18.425

−0.311

0.760

−818.651669

607.435721

 Year

0.056703

0.169175

18.428

0.335

0.741

−0.298130

0.411535

 Cage

0.011301

0.080214

18.335

0.141

0.889

−0.157002

0.179604

 Cage2

0.005226

0.004315

20.000

1.211

0.240

−0.003776

0.014227

Republic of South Africa

 Constant term

195.281269

261.100120

30.776

0.748

0.460

−337.393318

727.955856

 Year

−0.093079

0.130031

30.771

−0.716

0.479

−0.358359

0.172201

 Cage

−0.033597

0.065427

31.996

−0.514

0.611

−0.166869

0.099674

 Cage2

0.000214

0.003268

27.237

0.066

0.948

−0.006488

0.006916

Brazil

       

 Constant term

178.944876

212.772674

32.077

0.841

0.407

−254.418110

612.307863

 Year

−0.084760

0.105910

32.083

−0.800

0.429

−0.300469

0.130949

 Cage

−0.054561

0.036085

32.952

−1.512

0.140

−0.127981

0.018860

 Cage2

0.003708

0.002066

37.833

1.795

0.081

−0.000475

0.007891

Mexico

       

 Constant term

−208.359308

343.548300

13.049

−0.606

0.555

−950.268215

533.549600

 Year

0.108288

0.170848

13.048

0.634

0.537

−0.260670

0.477246

 Cage

0.017053

0.033477

1.149

0.509

0.691

−0.297964

0.332070

 Cage2

−0.004284

0.002132

1.006

−2.009

0.293

−0.031003

0.022435

Argentina

       

 Constant term

171.161142

449.529264

12.527

0.381

0.710

−803.726404

1146.048688

 Year

−0.080710

0.223646

12.527

−0.361

0.724

−0.565727

0.404306

 Cage

−0.121342

0.107487

7.809

−1.129

0.292

−0.370266

0.127582

 Cage2

0.004002

0.011220

5.403

0.357

0.735

−0.024206

0.032210

India

       

 Constant term

−180.991329

118.481416

23.000

−1.528

0.140

−426.088812

64.106153

 Year

0.095159

0.058967

23.000

1.614

0.120

−0.026822

0.217141

 Cage

0.034212

0.026224

23.000

1.305

0.205

−0.020037

0.088460

 Cage2

0.002970

0.002305

23.000

1.288

0.210

−0.001798

0.007737

Israel

       

 Constant term

1791.341424

749.677965

4.526

2.389

0.068

−198.063460

3780.746308

 Year

−0.884457

0.372205

4.522

−2.376

0.069

−1.872464

0.103550

 Cage

−0.130351

0.107475

8.468

−1.213

0.258

−0.375823

0.115121

 Cage2

−0.026869

0.011891

11.589

−2.260

0.044

−0.052880

−0.000858

Slovenia

       

 Constant term

−31.714993

134.226844

13.547

−0.236

0.817

−320.508524

257.078539

 Year

0.020363

0.066884

13.547

0.304

0.765

−0.123540

0.164266

 Cage

−0.084123

0.046744

8.409

−1.800

0.108

−0.191009

0.022763

 Cage2

−0.001050

0.002818

9.076

−0.373

0.718

−0.007416

0.005317

Data for Non-African runners are sorted in order of the number of finishers of each country

Cage centered age, Cage 2 centered age squared

Table 4

Results of the mixed-effects regression analyses for change in running speed in male half-marathoners across years

Parameter

Estimate

SE

DF

T

p value

95 % CI

Upper

Lower

Ethiopia

       

 Constant term

98.099117

174.871376

30.494

0.561

0.579

−258.793601

454.991835

 Year

−0.043552

0.087058

30.500

−0.500

0.620

−0.221226

0.134123

 Cage

−0.250494

0.185335

45.246

−1.352

0.183

−0.623723

0.122734

 Cage2

−0.012719

0.007260

42.721

−1.752

0.087

−0.027363

0.001925

Kenya

       

 Constant term

88.307393

103.114750

61.076

0.856

0.395

−117.878135

294.492921

 Year

−0.037470

0.051349

61.091

−0.730

0.468

−0.140145

0.065205

 Cage

−0.066120

0.029956

133.511

−2.207

0.029

−0.125371

−0.006870

 Cage2

−0.002035

0.001386

133.757

−1.469

0.144

−0.004776

0.000706

Austria

       

 Constant term

8.193904

15.718906

1374.455

0.521

0.602

−22.641739

39.029547

 Year

0.000216

0.007826

1374.306

0.028

0.978

−0.015136

0.015568

 Cage

−0.016008

0.004315

1443.906

−3.710

0.000

−0.024471

−0.007544

 Cage2

−0.000501

0.000294

1458.820

−1.702

0.089

−0.001078

7.633939E−5

Canada

       

 Constant term

−21.298964

52.088221

337.247

−0.409

0.683

−123.757696

81.159769

 Year

0.014351

0.025943

337.200

0.553

0.580

−0.036679

0.065382

 Cage

−0.024635

0.011096

359.294

−2.220

0.027

−0.046457

−0.002814

 Cage2

0.000544

0.000695

362.647

0.783

0.434

−0.000822

0.001910

Czech Republic

       

 Constant term

154.008680

81.928758

100.744

1.880

0.063

−8.520953

316.538313

 Year

−0.072109

0.040820

100.777

−1.767

0.080

−0.153086

0.008869

 Cage

−0.003265

0.013101

75.567

−0.249

0.804

−0.029361

0.022830

 Cage2

−0.002162

0.000996

78.010

−2.171

0.033

−0.004144

−0.000179

Denmark

       

 Constant term

73.075047

85.575129

152.801

0.854

0.394

−95.988101

242.138195

 Year

−0.032295

0.042595

152.782

−0.758

0.450

−0.116447

0.051857

 Cage

0.004069

0.013983

120.832

0.291

0.772

−0.023615

0.031752

 Cage2

−0.002067

0.000851

124.782

−2.429

0.017

−0.003752

−0.000383

Spain

       

 Constant term

73.070026

58.997907

419.804

1.239

0.216

−42.898085

189.038138

 Year

−0.031824

0.029368

419.811

−1.084

0.279

−0.089550

0.025902

 Cage

−0.015581

0.013136

435.510

−1.186

0.236

−0.041399

0.010238

 Cage2

0.001634

0.000911

471.708

1.793

0.074

−0.000156

0.003425

France

       

 Constant term

2.152551

8.424878

11,440.730

0.255

0.798

−14.361653

18.666754

 Year

0.003734

0.004195

11,440.223

0.890

0.373

−0.004488

0.011956

 Cage

−0.024520

0.002065

11,842.861

−11.874

0.000

−0.028568

−0.020472

 Cage2

−0.000555

0.000144

11,634.921

−3.864

0.000

−0.000837

−0.000274

Great Britain

 Constant term

37.386616

22.952563

1729.593

1.629

0.104

−7.631084

82.404316

 Year

−0.014237

0.011430

1729.576

−1.246

0.213

−0.036654

0.008181

 Cage

−0.007171

0.005013

1775.835

−1.430

0.153

−0.017003

0.002662

 Cage2

−0.000507

0.000363

1811.205

−1.399

0.162

−0.001218

0.000204

Germany

       

 Constant term

26.340398

7.339500

12,201.868

3.589

0.000

11.953816

40.726980

 Year

−0.008802

0.003654

12,201.252

−2.409

0.016

−0.015965

−0.001639

 Cage

−0.015672

0.001614

11,817.685

−9.708

0.000

−0.018836

−0.012508

 Cage2

−0.000337

0.000106

11,885.807

−3.164

0.002

−0.000545

−0.000128

Italy

       

 Constant term

32.563297

20.328196

2372.545

1.602

0.109

−7.299571

72.426164

 Year

−0.010999

0.010122

2372.366

−1.087

0.277

−0.030847

0.008850

 Cage

−0.045951

0.005681

2514.295

−8.089

0.000

−0.057090

−0.034812

 Cage2

−0.000765

0.000380

2470.087

−2.015

0.044

−0.001510

−2.039314E−5

Japan

       

 Constant term

14.867692

48.121533

316.697

0.309

0.758

−79.810599

109.545984

 Year

−.003770

0.023954

316.650

−.157

0.875

−.050900

0.043360

 Cage

−.058721

0.010081

397.745

−5.825

0.000

−.078540

−.038902

 Cage2

4.080624E−5

0.000449

341.270

0.091

0.928

−.000843

0.000924

Fürstentum Liechtenstein

 Constant term

36.488409

42.462409

604.502

0.859

0.391

−46.903349

119.880168

 Year

−0.012766

0.021142

604.548

−0.604

0.546

−0.054287

0.028756

 Cage

−0.001820

0.009507

565.166

−0.191

0.848

−0.020492

0.016853

 Cage2

−0.001896

0.000777

592.741

−2.438

0.015

−0.003422

−0.000369

Luxembourg

 Constant term

−15.253456

80.615224

92.293

−0.189

0.850

−175.355473

144.848561

 Year

0.011431

0.040137

92.287

0.285

0.776

−0.068280

0.091143

 Cage

−0.065466

0.021046

112.887

−3.111

0.002

−0.107162

−0.023770

 Cage2

0.002067

0.001460

76.329

1.415

0.161

−0.000842

0.004975

Netherlands

 Constant term

43.412228

54.590318

317.931

0.795

0.427

−63.991689

150.816144

 Year

−0.016855

0.027175

317.960

−0.620

0.536

−0.070321

0.036612

 Cage

−0.029740

0.011819

303.713

−2.516

0.012

−0.052998

−0.006482

 Cage2

−0.001104

0.000799

294.009

−1.382

0.168

−0.002675

0.000468

Norway

       

 Constant term

−108.473099

87.956547

66.260

−1.233

0.222

−284.071127

67.124929

 Year

0.058583

0.043794

66.285

1.338

0.186

−0.028848

0.146014

 Cage

0.003335

0.021397

98.282

0.156

0.876

−0.039125

0.045796

 Cage2

−0.001692

0.001159

78.629

−1.460

0.148

−0.004000

0.000615

Portugal

       

 Constant term

67.632099

92.672293

171.225

0.730

0.467

−115.295174

250.559373

 Year

−0.028137

0.046162

171.263

−0.610

0.543

−0.119256

0.062982

 Cage

0.009515

0.023055

186.876

0.413

0.680

−0.035968

0.054997

 Cage2

−0.001022

0.001966

185.843

−0.520

0.604

−0.004900

0.002855

Switzerland

 Constant term

8.817285

1.667403

223,427.050

5.288

0.000

5.549219

12.085351

 Year

0.000791

0.000830

223,414.735

0.953

0.340

−0.000836

0.002418

 Cage

−0.010964

0.000294

204,230.290

−37.270

0.000

−0.011540

−0.010387

 Cage2

−0.000368

2.032780E−5

202,092.789

−18.089

0.000

−0.000408

−0.000328

United States of America

 Constant term

54.392263

32.424867

708.442

1.677

0.094

−9.268067

118.052594

 Year

−0.023017

0.016143

708.387

−1.426

0.154

−0.054711

0.008677

 Cage

−0.009382

0.006245

705.174

−1.502

0.133

−0.021643

0.002878

 Cage2

−0.000283

0.000441

689.741

−0.641

0.521

−0.001149

0.000583

Australia

 Constant term

52.302602

107.606779

108.032

0.486

0.628

−160.991990

265.597194

 Year

−0.021678

0.053582

108.089

−0.405

0.687

−0.127885

0.084529

 Cage

−0.013969

0.030696

133.451

−0.455

0.650

−0.074683

0.046745

 Cage2

−0.000317

0.002070

136.856

−0.153

0.878

−0.004411

0.003776

Belgium

 Constant term

107.524420

49.224327

501.956

2.184

0.029

10.813323

204.235517

 Year

−0.049210

0.024501

501.911

−2.008

0.045

−0.097348

−0.001073

 Cage

−0.033350

0.009176

447.125

−3.635

0.000

−0.051383

−0.015317

 Cage2

−7.340408E−5

0.000666

417.563

−0.110

0.912

−0.001382

0.001235

Hungary

 Constant term

5.737883

94.942100

159.346

0.060

0.952

−181.769287

193.245052

 Year

0.002193

0.047257

159.320

0.046

0.963

−0.091137

0.095523

 Cage

−0.021118

0.020068

158.936

−1.052

0.294

−0.060752

0.018515

 Cage2

0.001436

0.001087

174.946

1.320

0.188

−0.000710

0.003582

Ireland

       

 Constant term

138.624168

77.025730

130.753

1.800

0.074

−13.753783

291.002120

 Year

−0.064935

0.038349

130.724

−1.693

0.093

−0.140799

0.010930

 Cage

0.012905

0.020461

147.172

0.631

0.529

−0.027530

0.053340

 Cage2

0.001772

0.001597

146.087

1.110

0.269

−0.001384

0.004928

Poland

       

 Constant term

86.086931

104.182157

192.160

0.826

0.410

−119.400506

291.574369

 Year

−0.038832

0.051868

192.148

−0.749

0.455

−0.141137

0.063472

 Cage

−0.092905

0.018121

167.220

−5.127

0.000

−0.128680

−0.057130

 Cage2

0.001517

0.001224

171.169

1.239

0.217

−0.000899

0.003933

Russia

       

 Constant term

211.097501

112.913539

96.255

1.870

0.065

−13.026515

435.221517

 Year

−0.100778

0.056233

96.273

−1.792

0.076

−0.212397

0.010840

 Cage

−0.066677

0.024282

81.019

−2.746

0.007

−0.114991

−0.018364

 Cage2

−0.004585

0.001957

62.648

−2.343

0.022

−0.008497

−0.000674

Sweden

       

 Constant term

23.098100

70.780786

194.032

0.326

0.745

−116.500399

162.696600

 Year

−0.007622

0.035234

193.992

−0.216

0.829

−0.077113

0.061870

 Cage

−0.041879

0.012513

177.901

−3.347

0.001

−0.066573

−0.017186

 Cage2

−0.000214

0.000893

193.338

−0.239

0.811

−0.001976

0.001548

Finland

       

 Constant term

8.266275

52.736089

163.256

0.157

0.876

−95.866485

112.399036

 Year

−0.000566

0.026249

163.232

−0.022

0.983

−0.052397

0.051266

 Cage

−0.041553

0.011615

170.064

−3.578

0.000

−0.064481

−0.018625

 Cage2

0.000222

0.000718

147.558

0.309

0.758

−0.001197

0.001640

Greece

       

 Constant term

−61.629272

138.778354

63.917

−0.444

0.658

−338.877861

215.619317

 Year

0.034774

0.069126

63.920

0.503

0.617

−0.103324

0.172871

 Cage

−0.045672

0.029991

67.495

−1.523

0.132

−0.105525

0.014181

 Cage2

0.001362

0.002210

66.813

0.616

0.540

−0.003050

0.005774

Republic of South Africa

 Constant term

97.835143

206.579371

37.822

0.474

0.639

−320.427710

516.097997

 Year

−0.045155

0.102815

37.832

−0.439

0.663

−0.253323

0.163012

 Cage

−0.114764

0.045331

42.716

−2.532

0.015

−0.206201

−0.023327

 Cage2

0.002014

0.003936

43.893

0.512

0.611

−0.005919

0.009947

Brazil

       

 Constant term

69.573202

122.101031

76.685

0.570

0.570

−173.576935

312.723340

 Year

−0.030992

0.060774

76.687

−0.510

0.612

−0.152015

0.090032

 Cage

−0.005665

0.035651

84.804

−0.159

0.874

−0.076551

0.065221

 Cage2

0.000800

0.002584

85.927

0.310

0.758

−0.004337

0.005937

Mexico

       

 Constant term

41.878671

159.784287

57.808

0.262

0.794

−277.986904

361.744245

 Year

−0.016374

0.079565

57.848

−0.206

0.838

−0.175650

0.142902

 Cage

0.004652

0.037631

61.634

0.124

0.902

−0.070580

0.079884

 Cage2

0.000324

0.002948

56.403

0.110

0.913

−0.005580

0.006229

Argentina

 Constant term

−280.869673

275.764919

14.061

−1.019

0.326

−872.087719

310.348372

 Year

0.143819

0.137206

14.060

1.048

0.312

−0.150341

0.437979

 Cage

−0.105665

0.095288

20.398

−1.109

0.280

−0.304184

0.092855

 Cage2

−0.008941

0.013370

20.476

−0.669

0.511

−0.036788

0.018907

India

       

 Constant term

184.538334

187.481998

40.972

0.984

0.331

−194.097033

563.173702

 Year

−0.087437

0.093418

40.964

−0.936

0.355

−0.276104

0.101229

 Cage

−0.043125

0.036785

44.595

−1.172

0.247

−0.117232

0.030982

 Cage2

−0.000763

0.003355

41.543

−0.228

0.821

−0.007536

0.006009

Israel

       

 Constant term

23.126668

168.388173

45.039

0.137

0.891

−316.016346

362.269682

 Year

−0.006935

0.083826

45.030

−0.083

0.934

−0.175766

0.161896

 Cage

−0.016089

0.022043

28.717

−0.730

0.471

−0.061192

0.029014

 Cage2

−0.000399

0.001451

29.170

−0.275

0.785

−0.003365

0.002567

Slovenia

       

 Constant term

449.153792

328.346727

19.574

1.368

0.187

−236.722979

1135.030562

 Year

−0.219405

0.163419

19.579

−1.343

0.195

−0.560762

0.121952

 Cage

−0.078618

0.063055

11.412

−1.247

0.237

−0.216792

0.059557

 Cage2

0.003187

0.005660

11.316

0.563

0.584

−0.009229

0.015603

Data for Non-African runners are sorted in order of the number of finishers of each country

Cage centered age, Cage 2 centered age squared

Table 5

Running speed (km/h) with mean ± SD for female and male East-African and Non-African marathoners

 

1999

2000

2001

2002

2003

2004

2005

2006

Women

        

 Ethiopia

      

18.64

 

 Kenya

     

18.26

  

 Austria

16.42 ± 1.62

18.32 ± 1.81

12.34

13.83 ± 5.78

12.36 ± 2.18

9.80 ± 0.21

12.65 ± 3.26

12.39 ± 2.43

 France

13.70 ± 4.13

13.77 ± 4.01

13.83 ± 4.05

13.72 ± 3.88

12.42 ± 3.98

13.38 ± 3.97

13.82 ± 4.43

13.27 ± 4.05

 Great Britain

 

10.50 ± 1.45

12.73 ± 4.45

13.14 ± 5.02

12.96 ± 3.95

13.46 ± 4.35

14.47 ± 4.58

12.72 ± 2.65

 Germany

11.68 ± 2.24

11.17 ± 2.63

13.90 ± 3.79

12.20 ± 3.77

12.63 ± 3.78

12.11 ± 3.34

13.04 ± 3.68

13.00 ± 3.60

 Italy

17.10

19.19 ± 0.52

19.64 ± 1.30

12.67 ± 5.70

11.93 ± 3.77

15.39 ± 4.39

12.06 ± 4.28

18.78 ± 1.77

 Japan

14.13

10.96

11.72 ± 5.02

7.88 ± 1.11

18.28

13.34 ± 4.69

14.27 ± 5.01

18.70

 Switzerland

14.46 ± 4.34

15.30 ± 4.19

14.74 ± 4.13

15.03 ± 4.06

15.60 ± 4.01

15.44 ± 4.09

15.08 ± 4.14

15.20 ± 4.12

 Canada

   

9.31

10.29 ± 5.82

8.00 ± 1.63

12.51

12.85 ± 7.29

 Liechtenstein

 

11.65

9.92 ± 2.39

 

16.05 ± 5.43

 

18.13 ± 1.01

19.75 ± 0.15

 USA

 

17.95

   

17.17 ± 4.07

13.92 ± 4.10

9.85 ± 1.43

 Belgium

10.77

   

19.87 ± 0.49

10.95 ± 0.37

11.65 ± 1.62

10.90 ± 0.79

 Spain

      

12.48

 

 Poland

   

11.24 ± 0.64

8.85

   

Men

        

 Ethiopia

  

17.47 ± 2.28

     

 Kenya

 

18.81

17.95 ± 1.44

 

17.61 ± 1.97

17.43 ± 1.62

17.28

 

 Austria

  

12.66 ± 0.09

9.10

19.37

16.18

14.40 ± 7.02

15.59 ± 5.27

 France

14.08 ± 4.06

13.47 ± 3.67

13.17 ± 3.75

13.17 ± 3.30

13.28 ± 3.79

13.41 ± 3.84

13.50 ± 3.89

12.87 ± 3.48

 Great Britain

9.27 ± 0.96

12.54 ± 3.61

12.01 ± 3.57

15.21 ± 2.94

15.02 ± 4.05

14.08 ± 3.79

14.15 ± 4.51

13.26 ± 3.82

 Germany

12.51 ± 3.32

13.02 ± 3.78

12.67 ± 3.28

12.60 ± 3.48

12.89 ± 3.70

13.00 ± 3.66

12.49 ± 3.55

12.89 ± 3.65

 Italy

16.23 ± 4.37

12.51 ± 3.77

12.85 ± 2.99

12.49 ± 4.01

12.50 ± 3.24

14.23 ± 4.04

13.66 ± 3.90

15.14 ± 3.86

 Japan

15.09

14.42

12.84 ± 5.70

11.47

11.45 ± 3.85

11.09 ± 4.17

12.92 ± 4.63

11.53 ± 3.41

 Switzerland

14.41 ± 3.99

14.84 ± 4.09

14.73 ± 4.07

14.77 ± 4.09

14.93 ± 4.11

14.71 ± 4.08

14.76 ± 4.04

14.83 ± 4.06

 Canada

14.00 ± 0.72

18.98

12.22 ± 4.96

12.37 ± 4.83

10.50 ± 3.91

10.90 ± 3.36

11.12 ± 4.09

13.14 ± 4.06

 Liechtenstein

  

18.70

17.56 ± 1.45

19.11 ± 1.21

15.41 ± 4.16

17.42 ± 3.08

17.80 ± 1.43

 USA

12.39 ± 3.85

10.79 ± 1.55

11.25 ± 3.38

13.62 ± 3.72

12.12 ± 3.55

12.65 ± 4.21

12.14 ± 3.48

12.86 ± 4.29

 Belgium

 

12.23

 

14.97 ± 5.32

14.80 ± 4.67

13.65 ± 4.98

12.71 ± 4.02

12.70 ± 3.91

 Spain

 

13.08

19.33

18.87 ± 1.06

13.90 ± 5.05

12.63 ± 2.21

13.37 ± 4.71

14.10 ± 2.28

 Poland

 

10.07

 

11.65 ± 1.73

9.05

10.36 ± 2.31

9.73

17.70 ± 2.29

 

2007

2008

2009

2010

2011

2012

2013

2014

Women

        

 Ethiopia

    

18.78

19.24

  

 Kenya

    

18.49

   

 Austria

11.84 ± 2.64

12.88 ± 3.92

12.48 ± 1.87

14.49 ± 4.76

11.09 ± 1.30

13.21 ± 3.31

11.29 ± 2.23

11.40 ± 2.61

 France

13.09 ± 3.75

14.14 ± 4.36

13.60 ± 4.05

13.04 ± 3.72

13.37 ± 3.81

13.48 ± 3.89

14.01 ± 3.65

13.47 ± 4.22

 Great Britain

14.06 ± 4.43

12.85 ± 4.03

13.15 ± 0.79

13.31 ± 4.35

14.81 ± 4.85

11.46 ± 5.80

14.10 ± 3.80

12.67 ± 3.57

 Germany

13.71 ± 3.85

12.97 ± 3.48

12.89 ± 3.93

13.47 ± 4.39

12.81 ± 3.56

13.24 ± 3.62

13.45 ± 4.25

12.94 ± 3.87

 Italy

16.34 ± 3.92

17.44 ± 3.70

12.78 ± 3.09

18.82 ± 1.04

17.47 ± 1.84

16.90 ± 4.52

18.56 ± 0.80

16.05 ± 4.56

 Japan

13.33 ± 4.01

14.24 ± 4.74

19.90

13.66 ± 1.15

11.80 ± 4.36

18.00 ± 0.39

18.49 ± 0.20

19.47 ± 1.09

 Switzerland

15.20 ± 4.07

14.90 ± 4.16

15.21 ± 4.08

14.98 ± 4.27

15.03 ± 4.09

14.72 ± 4.14

15.24 ± 4.14

14.76 ± 4.02

 Canada

17.99

18.53 ± 0.86

14.73 ± 6.33

9.44 ± 1.67

12.47 ± 3.63

8.06 ± 2.00

12.10 ± 3.62

11.97 ± 6.90

 Liechtenstein

18.78 ± 0.79

18.31 ± 2.04

16.96 ± 4.11

12.09

16.55

16.95 ± 3.38

 

18.56 ± 0.24

 USA

12.12 ± 4.17

13.84 ± 3.76

10.03 ± 0.19

9.39 ± 0.59

10.36 ± 1.59

15.87

 

12.08 ± 5.31

 Belgium

11.66

9.07

 

13.07

9.30

   

 Spain

17.96 ± 1.64

10.75

12.95 ± 1.50

 

11.79 ± 1.48

12.19 ± 0.21

19.09

12.79 ± 1.39

 Poland

  

12.25

10.67

11.69 ± 0.57

18.01 ± 0.67

15.50 ± 3.96

12.10 ± 1.93

Men

        

 Ethiopia

15.67 ± 3.28

16.26

17.34 ± 1.61

15.87 ± 0.21

15.13

 

15.91 ± 1.04

15.18

 Kenya

16.88 ± 2.65

18.43 ± 0.25

18.50 ± 0.19

18.10 ± 0.58

17.49 ± 0.47

17.96

18.15 ± 1.28

17.47 ± 1.68

 Austria

17.87 ± 0.91

15.28 ± 5.19

 

10.60

  

20.29

12.44 ± 3.74

 France

13.12 ± 3.79

13.69 ± 4.00

13.61 ± 3.96

13.21 ± 3.77

13.21 ± 3.67

13.21 ± 3.86

13.34 ± 3.66

13.70 ± 3.82

 Great Britain

13.08 ± 4.04

13.28 ± 4.01

12.66 ± 3.74

13.39 ± 3.95

12.97 ± 3.97

12.64 ± 3.82

13.63 ± 3.90

12.48 ± 3.49

 Germany

13.05 ± 3.77

12.64 ± 3.50

12.93 ± 3.62

13.07 ± 3.80

12.98 ± 3.69

13.07 ± 3.70

13.07 ± 3.54

13.27 ± 3.93

 Italy

14.54 ± 4.07

15.13 ± 4.17

14.34 ± 4.05

12.79 ± 3.71

12.93 ± 4.05

13.30 ± 4.03

13.40 ± 4.10

12.38 ± 3.35

 Japan

11.22 ± 2.74

12.79 ± 3.82

11.81 ± 4.02

10.66 ± 3.95

11.61 ± 4.59

11.73 ± 4.31

14.45 ± 5.00

12.46 ± 7.03

 Switzerland

14.78 ± 4.07

14.87 ± 4.09

14.77 ± 4.08

14.83 ± 4.11

14.87 ± 4.12

14.75 ± 4.01

14.89 ± 4.08

14.69 ± 4.07

 Canada

10.77 ± 3.77

11.27 ± 4.86

11.81 ± 5.97

10.40 ± 3.80

15.25 ± 4.45

 

15.17 ± 3.47

11.91 ± 3.81

 Liechtenstein

17.17 ± 4.41

14.70 ± 4.35

17.54 ± 3.04

14.28 ± 3.91

15.47 ± 3.96

17.08 ± 3.03

13.58 ± 2.56

12.86 ± 6.57

 USA

12.66 ± 4.14

13.53 ± 4.23

14.33 ± 4.11

13.08 ± 3.48

11.93 ± 3.60

12.98 ± 4.14

12.05 ± 4.83

13.13 ± 3.79

 Belgium

14.31 ± 3.42

15.03 ± 4.37

15.70 ± 3.87

14.64 ± 4.89

15.56 ± 4.04

15.47 ± 4.08

14.05 ± 4.00

13.10 ± 3.38

 Spain

15.98 ± 3.85

12.45 ± 4.53

15.46 ± 3.52

13.76 ± 4.25

15.59 ± 6.41

12.84 ± 3.40

15.76 ± 5.81

13.19 ± 3.71

 Poland

13.60 ± 5.11

12.51 ± 2.25

10.35 ± 1.28

10.29 ± 0.05

13.84 ± 3.37

13.04 ± 4.68

10.45 ± 0.69

11.93

Data for Non-African runners are sorted in order of the number of finishers of each country

Table 6

Results of the mixed-effects regression analyses for change in running speed across years in female marathoners

Parameter

Estimate

SE

DF

T

p value

95 % CI

Upper

Lower

Ethiopia

       

 Constant term

147.793813

321.794557

36.803

0.459

0.649

−504.341821

799.929446

 Year

−0.067200

0.160260

36.789

−0.419

0.677

−0.391981

0.257581

 Cage

−0.041199

0.045279

39.863

−0.910

0.368

−0.132721

0.050323

 Cage2

−0.000791

0.001556

27.290

−0.508

0.615

−0.003983

0.002401

Kenya

       

 Constant term

12.643951

134.413655

31.473

0.094

0.926

−261.327748

286.615651

 Year

0.001310

0.067007

31.470

0.020

0.985

−0.135269

0.137890

 Cage

0.004584

0.031623

33.197

0.145

0.886

−0.059740

0.068908

 Cage2

0.000926

0.001504

28.885

0.616

0.543

−0.002150

0.004002

Austria

       

 Constant term

319.000059

151.126310

115.787

2.111

0.037

19.669554

618.330564

 Year

−0.152749

0.075258

115.782

−2.030

0.045

−0.301810

−0.003688

 Cage

−0.059867

0.033352

105.113

−1.795

0.076

−0.125998

0.006264

 Cage2

0.003428

0.002369

91.358

1.447

0.151

−0.001277

0.008132

France

       

 Constant term

−69.668517

73.011026

423.181

−0.954

0.341

−213.177937

73.840903

 Year

0.041647

0.036362

423.171

1.145

0.253

−0.029825

0.113119

 Cage

−0.007736

0.019534

524.950

−0.396

0.692

−0.046111

0.030640

 Cage2

−0.000529

0.001375

513.572

−0.385

0.701

−0.003230

0.002172

Great Britain

 Constant term

−32.852390

202.043235

96.505

−.163

0.871

−433.878261

368.173481

 Year

0.023039

0.100666

96.499

0.229

0.819

−0.176769

0.222846

 Cage

0.057327

0.032752

62.676

1.750

0.085

−0.008129

0.122782

 Cage2

0.001266

0.003499

87.271

0.362

0.718

−0.005689

0.008220

Germany

       

 Constant term

−57.013601

61.704926

558.626

−0.924

0.356

−178.215628

64.188427

 Year

0.035049

0.030733

558.613

1.140

0.255

−0.025317

0.095415

 Cage

−0.018041

0.010289

360.049

−1.754

0.080

−0.038274

0.002192

 Cage2

−0.000917

0.000669

425.048

−1.370

0.172

−0.002232

0.000399

Italy

       

 Constant term

12.643951

134.413655

31.473

0.094

0.926

−261.327748

286.615651

 Year

0.001310

0.067007

31.470

0.020

0.985

−0.135269

0.137890

 Cage

0.004584

0.031623

33.197

0.145

0.886

−0.059740

0.068908

 Cage2

0.000926

0.001504

28.885

0.616

0.543

−0.002150

0.004002

Japan

       

 Constant term

−556.744907

324.548340

44.540

−1.715

0.093

−1210.605221

97.115408

 Year

0.284663

0.161722

44.521

1.760

0.085

−0.041159

0.610486

 Cage

0.002091

0.056456

36.733

0.037

0.971

−0.112328

0.116511

 Cage2

−0.001140

0.002306

47.736

−.494

0.623

−0.005776

0.003496

Switzerland

       

 Constant term

19.166945

16.359822

5730.128

1.172

0.241

−12.904491

51.238380

 Year

−0.001923

0.008148

5729.834

−0.236

0.813

−0.017896

0.014051

 Cage

0.000169

0.002164

3789.103

0.078

0.938

−0.004074

0.004412

 Cage2

−0.000271

0.000151

3903.532

−1.798

0.072

−0.000566

2.449756E−5

Canada

       

 Constant term

−84.838438

294.677013

21.509

−0.288

0.776

−696.771246

527.094370

 Year

0.049412

0.146619

21.493

0.337

0.739

−0.255073

0.353897

 Cage

−0.016467

0.105620

20.899

−0.156

0.878

−0.236180

0.203247

 Cage2

−0.005069

0.008542

26.178

−0.593

0.558

−0.022621

0.012484

Principality of Liechtenstein

 Constant term

134.396574

114.930718

8.628

1.169

0.274

−127.312878

396.106027

 Year

−0.058934

0.057365

8.641

−1.027

0.332

−0.189530

0.071661

 Cage

0.000824

0.052738

11.742

0.016

0.988

−0.114363

0.116012

 Cage2

−0.000182

0.005460

13.149

−0.033

0.974

−0.011963

0.011599

United States of America

 Constant term

147.793813

321.794557

36.803

0.459

0.649

−504.341821

799.929446

 Year

−0.067200

0.160260

36.789

−0.419

0.677

−0.391981

0.257581

 Cage

−0.041199

0.045279

39.863

−0.910

0.368

−0.132721

0.050323

 Cage2

−0.000791

0.001556

27.290

−0.508

0.615

−0.003983

0.002401

Belgium

       

 Constant term

832.877872

481.304102

14.000

1.730

0.106

−199.416758

1865.172502

 Year

−0.409025

0.239884

14.000

−1.705

0.110

−0.923525

0.105475

 Cage

0.113307

0.073728

14.000

1.537

0.147

−0.044823

0.271437

 Cage2

−0.008065

0.005950

14.000

−1.356

0.197

−0.020826

0.004695

Spain

       

 Constant term

578.599477

459.378710

18.000

1.260

0.224

−386.519821

1543.718775

 Year

−0.280844

0.228570

18.000

−1.229

0.235

−0.761053

0.199365

 Cage

0.085302

0.054009

9.306

1.579

0.148

−0.036264

0.206868

 Cage2

−0.006105

0.004734

8.582

−1.290

0.231

−0.016894

0.004684

Poland

       

 Constant term

−1007.316625

429.834844

14.000

−2.343

0.034

−1929.220678

−85.412573

 Year

0.507475

0.213730

14.000

2.374

0.032

0.049069

0.965881

 Cage

−0.022253

0.077353

14.000

−0.288

0.778

−0.188158

0.143652

 Cage2

0.001802

0.005561

14.000

0.324

0.751

−0.010126

0.013730

Data for Non-African runners are sorted in order of the number of finishers of each country

Cage centered age, Cage 2 centered age squared

Table 7

Results of the mixed-effects regression analyses for change in running speed across years in male marathoners

Parameter

Estimate

SE

DF

T

p value

95 % CI

Upper

Lower

Austria

       

 Constant term

119.014606

78.665485

352.571

1.513

0.131

−35.698004

273.727215

 Year

−0.053124

0.039182

352.518

−1.356

0.176

−0.130183

0.023936

 Cage

−0.053906

0.018537

374.501

−2.908

0.004

−0.090356

−0.017456

 Cage2

0.002858

0.001180

374.482

2.423

0.016

0.000538

0.005179

France

       

 Constant term

12.224516

32.400764

1943.299

0.377

0.706

−51.319391

75.768423

 Year

0.000774

0.016138

1943.341

0.048

0.962

−0.030876

0.032424

 Cage

−0.042530

0.007858

2185.277

−5.412

0.000

−0.057940

−0.027119

 Cage2

0.001220

0.000546

2369.390

2.235

0.025

0.000150

0.002290

Great Britain

 Constant term

168.008185

77.417245

265.471

2.170

0.031

15.578253

320.438116

 Year

−0.076916

0.038558

265.527

−1.995

0.047

−0.152834

−0.000997

 Cage

−0.003050

0.013447

228.557

−0.227

0.821

−0.029546

0.023446

 Cage2

0.000290

0.001143

251.114

0.254

0.800

−0.001961

0.002541

Germany

       

 Constant term

−26.616836

25.282326

2510.280

−1.053

0.293

−76.193187

22.959515

 Year

0.019883

0.012593

2510.229

1.579

0.114

−0.004811

0.044578

 Cage

−0.007977

0.005083

2186.239

−1.570

0.117

−0.017944

0.001990

 Cage2

0.000147

0.000344

2231.865

0.427

0.669

−0.000528

0.000822

Italy

       

 Constant term

82.322203

91.156734

288.896

0.903

0.367

−97.093338

261.737745

 Year

−0.033932

0.045393

288.917

−0.748

0.455

−0.123275

0.055411

 Cage

−0.058144

0.019311

261.042

−3.011

0.003

−0.096169

−0.020119

 Cage2

0.000191

0.001214

322.202

0.157

0.875

−0.002199

0.002580

Japan

       

 Constant term

49.803604

170.811818

103.019

0.292

0.771

−288.960603

388.567811

 Year

−0.018372

0.085088

103.003

−0.216

0.829

−0.187123

0.150380

 Cage

−0.086555

0.031059

107.375

−2.787

0.006

−0.148123

−0.024987

 Cage2

0.001926

0.001684

107.206

1.144

0.255

−0.001412

0.005264

Switzerland

 Constant term

25.878076

7.195438

22,373.993

3.596

0.000

11.774513

39.981639

 Year

−0.005404

0.003584

22,373.571

−1.508

0.132

−0.012428

0.001620

 Cage

−0.002664

0.001012

17,294.094

−2.633

0.008

−0.004647

−0.000681

 Cage2

−0.000235

6.583543E−5

17,295.657

−3.565

0.000

−0.000364

−0.000106

Canada

       

 Constant term

−106.659105

171.420255

81.342

−0.622

0.536

−447.709874

234.391663

 Year

0.059022

0.085420

81.336

0.691

0.492

−0.110927

0.228971

 Cage

−0.050496

0.030360

68.401

−1.663

0.101

−0.111073

0.010080

 Cage2

0.006306

0.001988

62.037

3.172

0.002

0.002332

0.010280

Principality of Liechtenstein

 Constant term

236.267620

241.570336

77.992

0.978

0.331

−244.662729

717.197969

 Year

−0.109511

0.120377

77.993

−0.910

0.366

−0.349164

0.130142

 Cage

0.034908

0.042003

73.075

0.831

0.409

−0.048802

0.118618

 Cage2

0.001951

0.003222

72.523

0.606

0.547

−0.004471

0.008373

United States of America

 Constant term

179.260596

91.774367

188.890

1.953

0.052

−1.773750

360.294941

 Year

−0.082585

0.045712

188.881

−1.807

0.072

−0.172757

0.007587

 Cage

0.003829

0.014234

167.444

0.269

0.788

−0.024273

0.031931

 Cage2

0.000319

0.000945

149.574

0.338

0.736

−0.001548

0.002186

Belgium

       

 Constant term

220.791210

167.798520

108.714

1.316

0.191

−111.789810

553.372230

 Year

−0.102767

0.083486

108.675

−1.231

0.221

−0.268238

0.062704

 Cage

−0.029095

0.030424

119.603

−0.956

0.341

−0.089335

0.031145

 Cage2

0.000194

0.002163

96.384

0.090

0.929

−0.004099

0.004486

Spain

       

 Constant term

−130.890461

169.416654

5.528

−0.773

0.471

−554.170969

292.390047

 Year

0.072247

0.084311

5.528

0.857

0.427

−0.138405

0.282899

 Cage

−0.050933

0.030883

5.028

−1.649

0.160

−0.130185

0.028319

 Cage2

0.001306

0.004902

56.210

0.266

0.791

−0.008513

0.011125

Poland

       

 Constant term

−173.031933

285.748419

50.731

−0.606

0.548

−746.769620

400.705753

 Year

0.092292

0.142290

50.736

0.649

0.520

−0.193403

0.377986

 Cage

−0.019397

0.026881

30.284

−0.722

0.476

−0.074273

0.035480

 Cage2

−0.000780

0.001881

35.444

−0.414

0.681

−0.004597

0.003038

Kenya

       

 Constant term

31.727578

85.570347

33.000

0.371

0.713

−142.366603

205.821759

 Year

−0.007558

0.042603

33.000

−0.177

0.860

−0.094234

0.079119

 Cage

−0.192695

0.042007

33.000

−4.587

0.000

−0.278159

−0.107230

 Cage2

−0.005855

0.002387

33.000

−2.453

0.020

−0.010712

−0.000999

Ethiopia

       

 Constant term

185.271970

155.298262

15.000

1.193

0.251

−145.738439

516.282379

 Year

−0.085404

0.077000

15.000

−1.109

0.285

−0.249526

0.078718

 Cage

−0.708418

0.358618

15.000

−1.975

0.067

−1.472793

0.055957

 Cage2

−0.034788

0.014889

15.000

−2.337

0.034

−0.066522

−0.003053

Data for Non-African runners are sorted in order of the number of finishers of each country

Cage centered age, Cage 2 centered age squared

Table 8

Age (years) with mean ± SD of female and male East-African and Non-African half-marathoners

 

1999

2000

2001

2002

2003

2004

2005

2006

Women

        

 Ethiopia

20

26 ± 1

30

 

36

37

35

26 ± 10

 Kenya

 

29 ± 9

 

35 ± 6

37 ± 1

29 ± 6

28 ± 7

28 ± 5

 Austria

 

40

50 ± 8

44 ± 3

37 ± 8

 

38 ± 7

44 ± 1

 Canada

 

49 ± 4

44 ± 10

40 ± 9

44 ± 9

53 ± 7

41 ± 13

35 ± 6

 Czech Republic

37 ± 14

49

31 ± 5

33 ± 18

34 ± 7

34 ± 5

35 ± 5

27

 Denmark

 

36 ± 0

34 ± 4

36 ± 5

33 ± 9

42 ± 12

48 ± 9

46 ± 7

 Spain

43 ± 22

40 ± 16

36 ± 5

37 ± 7

38 ± 8

37 ± 9

43 ± 9

37 ± 9

 France

42 ± 10

43 ± 10

41 ± 9

41 ± 9

42 ± 9

42 ± 10

42 ± 10

42 ± 10

 Great Britain

37 ± 7

39 ± 10

41 ± 12

39 ± 9

39 ± 8

36 ± 8

38 ± 9

39 ± 10

 Germany

43 ± 10

43 ± 9

45 ± 10

43 ± 9

44 ± 9

44 ± 9

43 ± 9

43 ± 10

 Italy

41 ± 9

48 ± 9

46 ± 11

41 ± 9

42 ± 11

42 ± 9

42 ± 10

39 ± 9

 Japan

36 ± 13

57 ± 22

61 ± 7

50 ± 15

50 ± 12

54 ± 12

49 ± 15

48 ± 18

 Liechtenstein

44 ± 4

46 ± 10

41 ± 6

45 ± 8

40 ± 8

39 ± 9

40 ± 8

44 ± 10

 Luxembourg

47 ± 21

42 ± 11

35 ± 7

40 ± 7

44 ± 12

42 ± 14

37 ± 8

45 ± 7

 Netherlands

44 ± 6

47 ± 1

43 ± 13

40 ± 7

43 ± 11

45 ± 11

40 ± 11

43 ± 10

 Norway

 

60 ± 1

55 ± 16

39 ± 16

56

41 ± 13

45 ± 15

50 ± 13

 Portugal

 

54

41

44 ± 14

46 ± 9

36 ± 9

38 ± 10

36 ± 8

 Switzerland

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

 USA

26 ± 3

35 ± 9

36 ± 10

44 ± 19

34 ± 12

36 ± 10

42 ± 12

41 ± 13

 Australia

 

40

50 ± 8

44 ± 3

37 ± 8

 

38 ± 7

44 ± 1

 Belgium

53 ± 21

 

47 ± 21

38 ± 16

44 ± 10

37 ± 10

38 ± 11

44 ± 7

 Hungary

68

65

 

72

43

41

33

46 ± 7

 Ireland

37 ± 7

44

38 ± 1

43 ± 2

42 ± 11

36 ± 6

 

41 ± 5

 Poland

44 ± 12

 

43 ± 7

30

36 ± 11

39 ± 10

45 ± 11

34 ± 5

 Russia

52

29 ± 5

28

30

 

42 ± 11

38 ± 12

32 ± 5

 Sweden

27

 

42 ± 12

48 ± 11

34 ± 7

38 ± 6

43 ± 16

44 ± 13

 Finland

33 ± 1

44

 

44 ± 18

 

40 ± 10

44 ± 12

40 ± 4

 Greece

    

39

48

32

33

 South Africa

   

47 ± 11

35

52

36

44 ± 1

 Brazil

45 ± 16

50 ± 4

 

40

41

46

50 ± 4

 

 Mexico

     

37

 

38 ± 6

 Argentina

   

38

   

32

 India

 

29

   

47

36 ± 7

43 ± 11

 Israel

     

64

59

 

 Slovenia

      

47

 

Men

        

 Ethiopia

30 ± 6

27

30 ± 3

27 ± 4

23 ± 1

24 ± 2

25 ± 6

28 ± 3

 Kenya

26 ± 1

26 ± 5

30 ± 3

29 ± 5

32 ± 2

37 ± 20

32 ± 18

27 ± 5

 Austria

 

43 ± 5

38 ± 5

38 ± 13

40 ± 11

42 ± 12

35 ± 7

41 ± 6

 Canada

40 ± 10

39 ± 12

40 ± 16

36 ± 11

39 ± 12

40 ± 10

42 ± 14

37 ± 10

 Czech Republic

37 ± 6

37 ± 13

31 ± 10

33 ± 6

40 ± 13

38 ± 8

35 ± 9

37 ± 11

 Denmark

 

47 ± 8

47 ± 14

41 ± 12

33 ± 9

47 ± 14

40 ± 9

43 ± 14

 Spain

35 ± 11

42 ± 8

34 ± 7

42 ± 10

42 ± 11

43 ± 10

43 ± 11

42 ± 10

 France

41 ± 10

42 ± 10

41 ± 9

42 ± 10

42 ± 10

41 ± 10

42 ± 10

41 ± 9

 Great Britain

40 ± 10

40 ± 10

41 ± 11

39 ± 10

41 ± 11

39 ± 10

41 ± 10

43 ± 11

 Germany

44 ± 10

44 ± 10

43 ± 10

43 ± 10

43 ± 10

43 ± 10

43 ± 10

43 ± 10

 Italy

44 ± 11

42 ± 8

43 ± 10

42 ± 10

43 ± 9

41 ± 9

42 ± 8

41 ± 9

 Japan

66 ± 5

51 ± 16

48 ± 13

54 ± 11

47 ± 19

46 ± 15

55 ± 14

44 ± 17

 Liechtenstein

38 ± 7

40 ± 8

44 ± 9

41 ± 11

40 ± 9

41 ± 9

41 ± 11

41 ± 10

 Luxembourg

43 ± 14

37 ± 3

37 ± 6

43 ± 11

43 ± 10

43 ± 9

42 ± 9

42 ± 11

 Netherlands

50 ± 10

41 ± 16

35 ± 9

39 ± 11

36 ± 8

38 ± 12

38 ± 7

39 ± 10

 Norway

33

28 ± 6

43 ± 14

40 ± 13

39 ± 8

32 ± 9

34 ± 7

44 ± 19

 Portugal

45 ± 8

46 ± 8

41 ± 9

38 ± 9

39 ± 11

37 ± 8

38 ± 6

39 ± 10

 Switzerland

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

 USA

41 ± 12

43 ± 12

39 ± 11

41 ± 11

41 ± 13

41 ± 10

40 ± 9

40 ± 12

 Australia

 

43 ± 5

38 ± 5

38 ± 13

40 ± 11

42 ± 12

35 ± 7

41 ± 6

 Belgium

43 ± 16

44 ± 11

43 ± 9

42 ± 10

40 ± 11

36 ± 10

42 ± 13

42 ± 11

 Hungary

 

41

46 ± 16

39 ± 10

48 ± 15

47 ± 14

42 ± 16

43 ± 13

 Ireland

34 ± 10

38 ± 6

42 ± 9

42 ± 7

40 ± 11

37 ± 5

35 ± 4

37 ± 6

 Poland

40 ± 12

38 ± 8

40 ± 7

37 ± 9

32 ± 16

37 ± 17

38 ± 13

39 ± 11

 Russia

 

38 ± 9

34 ± 11

33 ± 8

40 ± 15

41 ± 7

40 ± 12

34 ± 6

 Sweden

47 ± 13

45 ± 19

40 ± 8

43 ± 10

46 ± 14

40 ± 13

42 ± 11

43 ± 12

 Finland

61 ± 8

41 ± 10

47 ± 13

40 ± 10

44 ± 16

43 ± 13

43 ± 11

42 ± 13

 Greece

37

31

43 ± 4

31 ± 9

34 ± 7

37 ± 6

44 ± 13

33 ± 4

 South Africa

40

  

52

 

39 ± 6

38

41 ± 17

 Brazil

46 ± 18

53 ± 13

44 ± 14

 

42 ± 11

  

47 ± 6

 Mexico

46

40

52

38 ± 13

40 ± 8

47 ± 13

46

30 ± 10

 Argentina

    

39

30

51

39

 India

 

40 ± 9

48 ± 2

34

42 ± 7

 

38 ± 9

36 ± 8

 Israel

 

46 ± 6

 

50 ± 4

36 ± 2

31 ± 4

39

43 ± 26

 Slovenia

 

62

35

48 ± 6

39

44

39 ± 3

37 ± 2

 

2007

2008

2009

2010

2011

2012

2013

2014

Women

        

 Ethiopia

29 ± 5

41 ± 14

34 ± 8

28 ± 6

29 ± 7

27 ± 7

33 ± 8

27 ± 5

 Kenya

27 ± 6

29 ± 5

29 ± 8

29 ± 0

34 ± 9

30 ± 4

30 ± 6

29 ± 4

 Austria

53 ± 12

35

41 ± 2

40 ± 11

55 ± 19

48 ± 14

43 ± 5

40 ± 5

 Canada

37 ± 7

37 ± 8

35 ± 7

37 ± 10

43 ± 11

41 ± 11

38 ± 11

41 ± 13

 Czech Republic

40 ± 9

42 ± 8

40 ± 8

32 ± 4

34 ± 8

38 ± 9

34 ± 11

33 ± 6

 Denmark

37 ± 6

45

46 ± 7

41 ± 12

36 ± 12

40 ± 9

35 ± 4

43 ± 9

 Spain

42 ± 10

43 ± 8

41 ± 9

43 ± 5

44 ± 7

38 ± 9

43 ± 10

43 ± 10

 France

43 ± 10

41 ± 9

42 ± 9

42 ± 9

41 ± 9

40 ± 10

41 ± 10

41 ± 9

 Great Britain

38 ± 11

38 ± 9

38 ± 9

41 ± 11

39 ± 10

41 ± 10

39 ± 9

38 ± 10

 Germany

43 ± 10

43 ± 10

44 ± 10

43 ± 10

43 ± 10

44 ± 10

43 ± 10

43 ± 10

 Italy

42 ± 11

43 ± 10

41 ± 9

44 ± 10

42 ± 10

43 ± 10

42 ± 9

42 ± 9

 Japan

50 ± 17

45 ± 16

42 ± 14

42 ± 13

52 ± 14

53 ± 13

50 ± 9

47 ± 16

 Liechtenstein

42 ± 12

38 ± 10

40 ± 10

41 ± 10

39 ± 10

46 ± 10

43 ± 9

38 ± 9

 Luxembourg

41 ± 9

46 ± 12

38 ± 7

37 ± 9

37 ± 7

43 ± 9

41 ± 10

44 ± 12

 Netherlands

43 ± 9

46 ± 9

48 ± 10

43 ± 8

42 ± 9

50 ± 13

41 ± 8

46 ± 11

 Norway

47 ± 13

52 ± 13

56 ± 15

36 ± 14

41 ± 13

33 ± 6

49 ± 19

63 ± 2

 Portugal

42 ± 10

45 ± 11

48 ± 6

46 ± 5

36

41 ± 13

40 ± 4

46 ± 4

 Switzerland

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

 USA

38 ± 11

38 ± 10

38 ± 8

38 ± 11

42 ± 13

37 ± 9

38 ± 10

39 ± 10

 Australia

53 ± 12

35

41 ± 2

40 ± 11

55 ± 19

48 ± 14

43 ± 5

40 ± 5

 Belgium

43 ± 14

47 ± 12

39 ± 11

42 ± 10

43 ± 11

42 ± 6

44 ± 8

37 ± 8

 Hungary

48 ± 10

41

47 ± 9

47

47 ± 18

42 ± 8

51 ± 14

50 ± 12

 Ireland

32

49

33 ± 5

36 ± 10

32 ± 5

43 ± 4

40 ± 7

38 ± 11

 Poland

38 ± 6

33 ± 5

32 ± 7

45 ± 13

43 ± 10

44 ± 13

37 ± 9

43 ± 10

 Russia

38

33 ± 5

36 ± 8

34 ± 14

34 ± 6

34 ± 11

37 ± 16

36 ± 7

 Sweden

58 ± 11

44 ± 13

40 ± 14

37 ± 10

44 ± 12

41 ± 9

42 ± 13

41 ± 10

 Finland

48 ± 5

57 ± 2

48 ± 15

41 ± 9

54 ± 7

43 ± 10

47 ± 11

44 ± 8

 Greece

33 ± 1

45

47

40

33

34 ± 6

53 ± 14

40 ± 4

 South Africa

37 ± 7

48 ± 15

40 ± 5

 

52 ± 13

47 ± 14

39 ± 9

47

 Brazil

52 ± 26

45 ± 16

40 ± 15

41 ± 6

45 ± 7

43 ± 19

43 ± 9

39 ± 5

 Mexico

36 ± 2

43 ± 21

43 ± 5

41 ± 11

50 ± 5

39 ± 9

43

38 ± 5

 Argentina

36

 

28

43 ± 4

34

46 ± 11

40 ± 10

36 ± 2

 India

41 ± 15

 

25

 

35 ± 6

 

33 ± 5

42 ± 1

 Israel

  

28

31

52 ± 0

29

36 ± 11

44 ± 2

 Slovenia

41

 

47 ± 9

 

30 ± 4

  

42

Men

        

 Ethiopia

31 ± 5

30 ± 6

25 ± 6

27 ± 4

32 ± 7

33 ± 7

26 ± 5

27 ± 5

 Kenya

29 ± 4

27 ± 4

32 ± 13

30 ± 5

29 ± 7

29 ± 5

28 ± 4

31 ± 5

 Austria

40 ± 13

35 ± 6

35 ± 9

43 ± 11

36 ± 8

44 ± 15

41 ± 11

39 ± 8

 Canada

37 ± 13

36 ± 14

36 ± 10

41 ± 11

37 ± 14

42 ± 12

40 ± 10

39 ± 12

 Czech Republic

39 ± 12

41 ± 13

40 ± 12

37 ± 11

38 ± 13

36 ± 8

35 ± 10

41 ± 10

 Denmark

40 ± 11

40 ± 10

42 ± 7

45 ± 12

40 ± 10

44 ± 9

39 ± 10

43 ± 10

 Spain

42 ± 9

41 ± 11

40 ± 8

40 ± 10

41 ± 10

41 ± 9

40 ± 10

36 ± 8

 France

42 ± 10

42 ± 10

41 ± 10

42 ± 10

42 ± 10

42 ± 9

42 ± 9

42 ± 10

 Great Britain

41 ± 11

40 ± 11

41 ± 11

40 ± 10

41 ± 10

40 ± 10

40 ± 10

40 ± 11

 Germany

43 ± 10

43 ± 10

43 ± 10

43 ± 10

43 ± 10

44 ± 10

43 ± 10

43 ± 10

 Italy

42 ± 10

43 ± 9

43 ± 10

43 ± 10

43 ± 10

43 ± 9

43 ± 10

44 ± 10

 Japan

47 ± 17

49 ± 18

49 ± 16

46 ± 17

52 ± 16

50 ± 15

54 ± 15

48 ± 14

 Liechtenstein

42 ± 10

42 ± 9

42 ± 9

41 ± 8

43 ± 9

41 ± 9

41 ± 9

41 ± 9

 Luxembourg

41 ± 10

38 ± 8

38 ± 12

37 ± 10

39 ± 11

39 ± 6

46 ± 7

46 ± 9

 Netherlands

44 ± 12

45 ± 10

43 ± 11

42 ± 11

44 ± 10

42 ± 11

42 ± 11

43 ± 9

 Norway

45 ± 11

37 ± 11

44 ± 11

51 ± 14

41 ± 15

45 ± 10

51 ± 11

43 ± 12

 Portugal

38 ± 9

39 ± 10

42 ± 8

36 ± 9

39 ± 11

38 ± 8

42 ± 12

44 ± 8

 Switzerland

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

41 ± 10

 USA

38 ± 11

42 ± 11

39 ± 10

40 ± 9

38 ± 11

40 ± 12

39 ± 10

41 ± 10

 Australia

40 ± 13

35 ± 6

35 ± 9

43 ± 11

36 ± 8

44 ± 15

41 ± 11

39 ± 8

 Belgium

40 ± 11

39 ± 8

39 ± 10

42 ± 12

42 ± 10

44 ± 11

43 ± 10

44 ± 11

 Hungary

43 ± 14

43 ± 9

52 ± 16

45 ± 12

42 ± 15

46 ± 16

38 ± 15

47 ± 9

 Ireland

39 ± 9

45 ± 12

37 ± 8

39 ± 11

42 ± 9

41 ± 11

44 ± 11

43 ± 9

 Poland

40 ± 9

40 ± 13

38 ± 14

39 ± 13

39 ± 11

38 ± 11

38 ± 10

37 ± 11

 Russia

33 ± 6

42 ± 7

37 ± 10

35 ± 10

35 ± 7

37 ± 10

40 ± 12

36 ± 6

 Sweden

45 ± 9

41 ± 11

44 ± 12

42 ± 14

46 ± 12

45 ± 12

43 ± 13

43 ± 12

 Finland

41 ± 13

41 ± 8

46 ± 14

41 ± 9

43 ± 13

43 ± 12

40 ± 12

41 ± 11

 Greece

37 ± 8

43 ± 11

44 ± 14

43 ± 14

33 ± 7

52 ± 10

39 ± 11

44 ± 14

 South Africa

41 ± 9

30 ± 5

30 ± 5

44 ± 7

34 ± 4

37 ± 16

39 ± 9

38 ± 8

 Brazil

47 ± 10

43 ± 7

41 ± 7

45 ± 13

44 ± 11

44 ± 11

44 ± 8

47 ± 11

 Mexico

45 ± 12

36 ± 9

47 ± 3

41 ± 4

41 ± 8

40 ± 14

40 ± 7

41 ± 7

 Argentina

44

46

35 ± 4

38 ± 4

40 ± 5

42 ± 9

36 ± 5

41 ± 7

 India

38

33 ± 9

46 ± 11

42 ± 14

39 ± 6

32 ± 6

34 ± 7

37 ± 5

 Israel

39 ± 12

39 ± 12

42 ± 10

47 ± 17

43 ± 12

47 ± 15

41 ± 9

41 ± 10

 Slovenia

  

42 ± 21

41

39

43 ± 16

39 ± 11

 

Data for Non-African runners are sorted in order of the number of finishers of each country

Table 9

Results of the mixed-effects regression analyses for change in age across years in half-marathoners

Parameter

Estimate

SE

DF

T

p value

Ethiopia

     

 Constant term

−182.511370

314.486675

91.467

−0.580

0.563

 Female sex

1.680182

1.432541

72.982

1.173

0.245

 Calendar year

0.104919

0.156633

91.480

0.670

0.505

Kenya

     

 Constant term

8.235275

288.742638

208.395

0.029

0.977

 Female sex

−0.121674

1.317439

68.640

−0.092

0.927

 Calendar year

0.010794

0.143794

208.376

0.075

0.940

Austria

     

 Constant term

194.074686

73.655324

2996.146

2.635

0.008

 Female sex

−1.709831

0.481769

1362.215

−3.549

<0.0001

 Calendar year

−0.075364

0.036673

2996.074

−2.055

0.040

Canada

     

 Constant term

160.945071

202.099830

612.252

0.796

0.426

 Female sex

−1.870259

1.338345

281.258

−1.397

0.163

 Calendar year

−0.059563

0.100658

612.236

−0.592

0.554

Czech Republic

 Constant term

−103.672165

314.871371

203.897

−0.329

0.742

 Female sex

−1.866522

1.674310

123.397

−1.115

0.267

 Calendar year

0.070316

0.156835

203.856

0.448

0.654

Denmark

     

 Constant term

635.928991

345.802767

242.013

1.839

0.067

 Female sex

−1.207578

1.995708

124.433

−0.605

0.546

 Calendar year

−0.295499

0.172164

242.020

−1.716

0.087

Spain

     

 Constant term

4.345138

173.122867

707.441

0.025

0.980

 Female sex

−0.414857

0.961543

416.419

−0.431

0.666

 Calendar year

0.018514

0.086181

707.444

0.215

0.830

France

     

 Constant term

40.876029

30.739542

20,221.009

1.330

0.184

 Female sex

−0.363674

0.201893

9121.960

−1.801

0.072

 Calendar year

0.000558

0.015305

20,220.731

0.036

0.971

Great Britain

 Constant term

62.808682

86.098036

2964.716

0.730

0.466

 Female sex

−1.582820

0.555386

1329.593

−2.850

0.004

 Calendar year

−0.010529

0.042874

2964.669

−0.246

0.806

Germany

     

 Constant term

47.516840

32.418394

21,887.424

1.466

0.143

 Female sex

0.269587

0.192793

9869.455

1.398

0.162

 Calendar year

−0.002199

0.016141

21,888.087

−0.136

0.892

Italy

     

 Constant term

99.335607

63.935535

3599.246

1.554

0.120

 Female sex

−0.964511

0.478133

1789.232

−2.017

0.044

 Calendar year

−0.027856

0.031834

3599.102

−0.875

0.382

Japan

     

 Constant term

774.526324

242.816752

456.029

3.190

0.002

 Female sex

−0.297851

1.873820

298.110

−0.159

0.874

 Calendar year

−0.361601

0.120894

456.006

−2.991

0.003

Liechtenstein

 Constant term

86.887276

148.175736

975.830

0.586

0.558

 Female sex

−0.191866

0.758997

586.133

−0.253

0.801

 Calendar year

−0.022614

0.073778

975.840

−0.307

0.759

Luxembourg

     

 Constant term

−164.038413

297.385871

212.919

−0.552

0.582

 Female sex

−0.327141

1.355426

151.704

−0.241

0.810

 Calendar year

0.102236

0.148098

212.984

0.690

0.491

Netherlands

     

 Constant term

−523.086955

207.948527

597.809

−2.515

0.012

 Female sex

0.885014

1.109896

324.076

0.797

0.426

 Calendar year

0.281968

0.103524

597.796

2.724

0.007

Norway

     

 Constant term

−912.882656

459.239160

164.453

−1.988

0.048

 Female sex

6.870747

2.584284

91.195

2.659

0.009

 Calendar year

0.475098

0.228639

164.454

2.078

0.039

Portugal

     

 Constant term

−51.331697

261.757709

235.116

−0.196

0.845

 Female sex

1.523814

1.797020

119.389

0.848

0.398

 Calendar year

0.046577

0.130365

235.105

0.357

0.721

Switzerland

     

 Constant term

41.194097

0.025301

124,980.522

1.174

0.101

 Female sex

0.130365

0.045674

144,203.009

2.854

0.401

 Calendar year

−0.003405

0.004187

 

−0.813

0.759

United States of America

 Constant term

59.833065

149.760218

1239.031

0.400

0.690

 Female sex

−0.210582

0.907549

602.658

−0.232

0.817

 Calendar year

−0.009517

0.074571

1239.035

−0.128

0.898

Australia

     

 Constant term

352.823540

240.345850

102.968

1.468

0.145

 Female sex

0.724548

1.955842

120.491

0.370

0.712

 Calendar year

−0.155166

0.119654

102.965

−1.297

0.198

Belgium

     

 Constant term

32.115986

200.805249

711.224

0.160

0.873

 Female sex

0.194925

1.089004

423.817

0.179

0.858

 Calendar year

0.005088

0.099966

711.329

0.051

0.959

Hungary

     

 Constant term

306.588165

391.814434

209.053

0.782

0.435

 Female sex

1.793288

2.174815

181.126

0.825

0.411

 Calendar year

−0.129388

0.195061

209.050

−0.663

0.508

Ireland

     

 Constant term

−234.096789

266.979012

233.252

−0.877

0.381

 Female sex

−1.746638

1.660739

110.543

−1.052

0.295

 Calendar year

0.136751

0.132924

233.250

1.029

0.305

Poland

     

 Constant term

80.619356

304.876109

293.818

0.264

0.792

 Female sex

1.372858

1.636758

169.363

0.839

0.403

 Calendar year

−0.020831

0.151805

293.811

−0.137

0.891

Russia

     

 Constant term

172.423406

334.325523

166.780

0.516

0.607

 Female sex

−1.652883

1.736428

115.009

−0.952

0.343

 Calendar year

−0.067115

0.166487

166.786

−0.403

0.687

Sweden

     

 Constant term

289.316852

335.082052

353.960

0.863

0.388

 Female sex

−0.592306

1.563797

209.865

−0.379

0.705

 Calendar year

−0.122190

0.166817

353.950

−0.732

0.464

Finland

     

 Constant term

−59.142933

311.996766

307.703

−0.190

0.850

 Female sex

3.608451

1.778953

155.630

2.028

0.044

 Calendar year

0.049886

0.155324

307.703

0.321

0.748

Greece

     

 Constant term

−892.527239

519.331793

93.956

−1.719

0.089

 Female sex

−0.405076

2.897113

68.342

−0.140

0.889

 Calendar year

0.464430

0.258636

93.954

1.796

0.076

Republic of South Africa

 Constant term

636.290049

640.320419

75.353

0.994

0.324

 Female sex

2.142126

2.784791

44.423

0.769

0.446

 Calendar year

−0.296861

0.318625

75.353

−0.932

0.354

Brazil

     

 Constant term

390.737458

494.198576

122.510

0.791

0.431

 Female sex

−1.389051

2.469821

73.141

−0.562

0.576

 Calendar year

−0.171769

0.245978

122.514

−0.698

0.486

Mexico

     

 Constant term

342.919947

496.145544

92.343

0.691

0.491

 Female sex

−0.070202

2.152566

68.580

−0.033

0.974

 Calendar year

−0.150281

0.246976

92.326

−0.608

0.544

Argentina

     

 Constant term

−133.127127

591.831333

31.764

−0.225

0.823

 Female sex

−2.442123

2.570733

24.433

−0.950

0.351

 Calendar year

0.086027

0.294531

31.768

0.292

0.772

India

     

 Constant term

647.670352

567.767634

57.387

1.141

0.259

 Female sex

−0.840896

2.566219

39.798

−0.328

0.745

 Calendar year

−0.302860

0.282792

57.372

−1.071

0.289

Israel

     

 Constant term

369.720687

818.353267

61.363

0.452

0.653

 Female sex

2.219258

4.361460

43.335

0.509

0.613

 Calendar year

−0.162596

0.407397

61.348

−0.399

0.691

Slovenia

     

 Constant term

−780.162274

551.609835

27.991

−1.414

0.168

 Female sex

−7.106008

2.764787

23.422

−2.570

0.017

 Calendar year

0.409617

0.274536

27.999

1.492

0.147

Data for Non-African runners are sorted in order of the number of finishers of each country

Table 10

Age (years) with mean ± SD of female and male East-African and Non-African marathoners

 

1999

2000

2001

2002

2003

2004

2005

2006

Women

        

 Ethiopia

      

32

 

 Kenya

     

32

  

 Austria

47 ± 4

45 ± 15

32

26 ± 8

37 ± 4

45 ± 7

40 ± 11

41 ± 11

 France

40 ± 9

47 ± 7

45 ± 11

43 ± 9

47 ± 10

46 ± 9

45 ± 8

44 ± 8

 Great Britain

 

34 ± 4

42 ± 18

29 ± 12

43 ± 11

40 ± 9

40 ± 9

40 ± 12

 Germany

45 ± 9

46 ± 11

48 ± 12

48 ± 11

44 ± 10

45 ± 13

44 ± 10

44 ± 9

 Italy

43

61 ± 16

36 ± 16

52 ± 2

50 ± 4

48 ± 8

40 ± 6

33 ± 4

 Japan

63

66

42 ± 17

43 ± 30

57

47 ± 18

53 ± 17

52

 Switzerland

41 ± 11

42 ± 10

42 ± 11

41 ± 10

42 ± 10

42 ± 11

43 ± 11

41 ± 11

 Canada

   

38

49 ± 10

55 ± 1

54

48 ± 7

 Liechtenstein

 

44

52 ± 8

 

42 ± 11

 

48 ± 21

40 ± 4

 USA

 

51

   

29 ± 2

39 ± 14

40 ± 17

 Belgium

28

   

41

43 ± 18

41 ± 13

46 ± 13

 Spain

      

40

 

 Poland

   

25

30 ± 1

   

Men

        

 Ethiopia

  

28 ± 3

     

 Kenya

 

33

24 ± 4

 

29 ± 6

29 ± 8

29

 

 Austria

52 ± 4

43 ± 14

45 ± 10

45 ± 9

42 ± 7

45 ± 7

44 ± 8

44 ± 9

 France

43 ± 8

41 ± 10

44 ± 11

44 ± 10

44 ± 10

44 ± 9

44 ± 9

43 ± 9

 Great Britain

34 ± 8

38 ± 16

39 ± 11

46 ± 13

43 ± 12

39 ± 10

41 ± 11

43 ± 10

 Germany

40 ± 9

44 ± 9

44 ± 9

45 ± 9

44 ± 9

44 ± 9

43 ± 9

43 ± 9

 Italy

52 ± 10

45 ± 8

50 ± 8

42 ± 9

44 ± 9

43 ± 12

44 ± 13

41 ± 9

 Japan

41

64

36 ± 7

64

57 ± 8

51 ± 13

46 ± 17

45 ± 14

 Switzerland

42 ± 11

43 ± 11

42 ± 11

42 ± 11

42 ± 11

42 ± 10

42 ± 11

42 ± 11

 Canada

44 ± 6

45

33 ± 6

44 ± 5

41 ± 12

38 ± 12

43 ± 14

42 ± 16

 Liechtenstein

  

29

53 ± 15

44 ± 10

40 ± 8

41 ± 8

43 ± 7

 USA

45 ± 9

55 ± 8

41 ± 8

36 ± 14

37 ± 10

40 ± 11

44 ± 10

42 ± 13

 Belgium

 

38

 

44 ± 10

41 ± 12

37 ± 15

43 ± 18

43 ± 11

 Spain

 

54

45

28 ± 3

57 ± 9

44 ± 4

42 ± 10

41 ± 11

 Poland

 

31

 

27 ± 4

58

40 ± 12

49

30 ± 1

 

2007

2008

2009

2010

2011

2012

2013

2014

Women

        

 Ethiopia

    

21

26

  

 Kenya

    

35

   

 Austria

44 ± 7

39 ± 10

43 ± 7

43 ± 6

44 ± 4

45 ± 7

40 ± 3

41 ± 10

 France

41 ± 9

44 ± 9

42 ± 10

43 ± 10

45 ± 9

43 ± 8

43 ± 10

45 ± 9

 Great Britain

40 ± 10

37 ± 9

39 ± 10

38 ± 18

38 ± 7

45 ± 9

36 ± 8

40 ± 12

 Germany

43 ± 8

44 ± 10

43 ± 10

41 ± 11

44 ± 11

44 ± 10

41 ± 11

45 ± 10

 Italy

44 ± 13

44 ± 14

55 ± 16

45 ± 10

41 ± 19

55 ± 11

41 ± 23

44 ± 18

 Japan

54 ± 18

50 ± 18

61

50 ± 19

56 ± 13

49 ± 11

56 ± 8

57 ± 2

 Switzerland

42 ± 10

43 ± 11

42 ± 11

41 ± 11

42 ± 11

42 ± 10

42 ± 11

42 ± 11

 Canada

25

41 ± 17

41 ± 4

38 ± 10

41 ± 15

32 ± 0

35 ± 3

33 ± 7

 Liechtenstein

33 ± 10

33 ± 8

39 ± 9

42

53

39 ± 8

 

46 ± 21

 USA

44 ± 17

44 ± 22

37 ± 11

62 ± 8

50 ± 25

31

 

41 ± 20

 Belgium

52 ± 13

29

 

46

54

   

 Spain

46 ± 8

34

43 ± 7

 

41 ± 2

43 ± 10

44

40 ± 13

 Poland

  

18

38

52 ± 1

49 ± 13

40 ± 11

39 ± 2

Men

        

 Ethiopia

24 ± 4

26

32 ± 1

23 ± 8

32

 

28 ± 8

26

 Kenya

35 ± 13

28 ± 1

28 ± 3

32 ± 5

29 ± 6

24

27 ± 6

30 ± 2

 Austria

41 ± 10

42 ± 11

44 ± 10

43 ± 6

42 ± 8

42 ± 8

42 ± 7

45 ± 9

 France

43 ± 9

44 ± 10

42 ± 11

43 ± 10

44 ± 9

42 ± 10

42 ± 10

44 ± 10

 Great Britain

41 ± 8

41 ± 11

39 ± 11

41 ± 9

41 ± 9

42 ± 10

41 ± 11

35 ± 8

 Germany

44 ± 10

43 ± 9

44 ± 10

43 ± 10

43 ± 10

43 ± 10

44 ± 10

44 ± 10

 Italy

41 ± 8

42 ± 8

41 ± 9

47 ± 9

45 ± 12

43 ± 8

46 ± 9

43 ± 12

 Japan

48 ± 14

48 ± 14

48 ± 19

49 ± 17

49 ± 17

42 ± 16

46 ± 19

64 ± 7

 Switzerland

42 ± 11

42 ± 11

42 ± 11

42 ± 10

42 ± 11

42 ± 10

42 ± 11

42 ± 10

 Canada

35 ± 12

42 ± 9

49 ± 8

46 ± 14

41 ± 9

 

40 ± 7

50 ± 9

 Liechtenstein

36 ± 14

42 ± 10

43 ± 5

42 ± 7

37 ± 4

30 ± 4

31 ± 1

42 ± 13

 USA

45 ± 10

39 ± 10

41 ± 12

40 ± 9

41 ± 9

36 ± 7

41 ± 13

42 ± 10

 Belgium

39 ± 8

38 ± 10

43 ± 11

44 ± 10

48 ± 13

42 ± 12

44 ± 10

42 ± 11

 Spain

42 ± 10

47 ± 11

41 ± 9

35 ± 12

40 ± 7

33 ± 6

40 ± 12

44 ± 6

 Poland

47 ± 5

38 ± 8

42 ± 14

32 ± 9

38 ± 14

50 ± 16

35 ± 15

56

Data for Non-African runners are sorted in order of the number of finishers of each country

Table 11

Results of the mixed-effects regression analyses for change in age across years in marathoners

Parameter

Estimate

SE

DF

T

p value

Ethiopia

     

 Constant term

129.282320

508.886678

16.700

0.254

0.803

 Female sex

−0.243651

3.310608

12.319

−0.074

0.943

 Calendar year

−0.050632

0.253416

16.702

−0.200

0.844

Kenya

     

 Constant term

−112.654090

528.060345

30.357

−0.213

0.832

 Female sex

3.707084

4.569460

13.457

0.811

0.431

 Calendar year

0.070957

0.263161

30.291

0.270

0.789

Austria

     

 Constant term

203.368427

202.655612

491.365

1.004

0.316

 Female sex

−2.565643

1.122330

309.176

−2.286

0.023

 Calendar year

−0.079728

0.100942

491.362

−0.790

0.430

France

     

 Constant term

118.121641

83.994410

2805.626

1.406

0.160

 Female sex

0.044112

0.552283

1850.356

0.080

0.936

 Calendar year

−0.037087

0.041835

2805.619

−0.887

0.375

Great Britain

 Constant term

389.692562

249.759353

477.933

1.560

0.119

 Female sex

−1.714608

1.280914

348.174

−1.339

0.182

 Calendar year

−0.173769

0.124396

477.931

−1.397

0.163

Germany

     

 Constant term

107.789331

82.298718

3899.573

1.310

0.190

 Female sex

0.535367

0.472119

2458.948

1.134

0.257

 Calendar year

−0.032069

0.040991

3899.516

−0.782

0.434

Italy

     

 Constant term

556.010922

261.000704

423.965

2.130

0.034

 Female sex

1.394311

1.647994

289.562

0.846

0.398

 Calendar year

−0.255065

0.129966

423.965

−1.963

0.050

Japan

     

 Constant term

−933.316248

562.194049

154.231

−1.660

0.099

 Female sex

1.996612

3.315609

104.626

0.602

0.548

 Calendar year

0.488912

0.279931

154.230

1.747

0.083

Switzerland

     

 Constant term

37.165305

28.161538

39,125.737

1.320

0.187

 Female sex

0.130342

0.144640

24,925.454

0.901

0.368

 Calendar year

0.002333

0.014026

39,122.296

0.166

0.868

Canada

     

 Constant term

−113.393911

476.054030

132.791

−0.238

0.812

 Female sex

−2.046769

3.297757

73.295

−0.621

0.537

 Calendar year

0.077849

0.237227

132.790

0.328

0.743

Liechtenstein

 Constant term

1182.645518

516.645857

102.882

2.289

0.024

 Female sex

2.754826

2.269941

72.517

1.214

0.229

 Calendar year

−0.569271

0.257412

102.881

−2.212

0.029

United States of America

 Constant term

237.925017

383.185261

297.972

0.621

0.535

 Female sex

−1.592948

2.308567

180.960

−0.690

0.491

 Calendar year

−0.098054

0.190859

297.985

−0.514

0.608

Belgium

 Constant term

−304.145888

500.299320

132.133

−0.608

0.544

 Female sex

1.923155

3.303639

100.875

0.582

0.562

 Calendar year

0.172307

0.248996

132.127

0.692

0.490

Spain

     

 Constant term

519.395530

568.357363

74.188

0.914

0.364

 Female sex

−0.202724

2.587542

60.661

−0.078

0.938

 Calendar year

−0.237530

0.282985

74.188

−0.839

0.404

Poland

 Constant term

−2195.393095

875.131990

54.937

−2.509

0.015

 Female sex

−3.631775

3.857273

56.539

−0.942

0.350

 Calendar year

1.113417

0.435743

54.943

2.555

0.013

Data for Non-African runners are sorted in order of the number of finishers of each country

Performance of the fastest and age of the youngest

Table 12 presents running speed and age of female and male half-marathoners and marathoners sorted from the fastest to the slowest and from the youngest to the oldest. In absolute values, women from Kenya and Ethiopia were running the fastest. Kenyan women were not faster than Ethiopian women (p > 0.05) but they were significantly faster than all other women (p < 0.001 to p < 0.0001). Ethiopian women were not faster than women from Kenya, Portugal, Principality of Liechtenstein and Hungary (p > 0.05), but significantly faster than all other women (p < 0.001 to p < 0.0001). For men, Kenyans and Ethiopians were running the fastest regarding in absolute terms. Kenyan men were not faster than Ethiopian men (p > 0.05), but significantly faster than all other men (p < 0.001 to p < 0.0001). Ethiopian men were not faster than men from Portugal, Principality of Liechtenstein, Italy, Switzerland and Hungary (p > 0.05), but significantly faster than all other men (p < 0.001 to p < 0.0001).
Table 12

Running speed and age of half-marathoners and marathoners sorted by country

Running speed

Age

Country

Women

Country

Men

Country

Women

Country

Men

Half-marathon

 Kenya

14.2 ± 5.1

Kenya

12.7 ± 4.8

Ethiopia

29.8 ± 7.7

Ethiopia

28.0 ± 5.2

 Ethiopia

12.8 ± 5.1

Ethiopia

11.1 ± 4.4

Kenya

30.2 ± 6.0

Kenya

29.7 ± 8.3

 Portugal

11.4 ± 3.5

Portugal

11.1 ± 2.9

Russia

35.2 ± 9.3

Russia

37.1 ± 9.0

 Liechtenstein

10.9 ± 2.5

Liechtenstein

10.5 ± 2.7

Czech Republic

35.6 ± 8.1

Czech Republic

37.5 ± 10.7

 Hungary

10.7 ± 2.4

Italy

10.4 ± 3.2

Argentina

38.1 ± 6.9

Poland

38.3 ± 11.3

 Italy

10.7 ± 3.1

Switzerland

10.4 ± 2.9

India

38.3 ± 8.9

South Africa

38.7 ± 9.3

 Switzerland

10.4 ± 2.9

Hungary

9.9 ± 2.9

Slovenia

38.5 ± 2.1

Canada

38.9 ± 11.9

 India

10.2 ± 1.2

France

9.5 ± 3.3

Ireland

38.5 ± 7.5

Australia

38.9 ± 9.9

 Spain

10.0 ± 3.0

Netherlands

9.5 ± 3.3

USA

38.5 ± 10.9

Argentina

39.2 ± 6.3

 Ireland

9.8 ± 3.0

Australia

9.5 ± 2.9

Great Britain

38.8 ± 9.6

India

39.3 ± 8.6

 Argentina

9.6 ± 3.1

Spain

9.4 ± 3.0

Poland

39.1 ± 9.9

Portugal

39.5 ± 9.2

 France

9.5 ± 3.3

Norway

9.1 ± 3.0

Canada

39.2 ± 10.0

USA

39.9 ± 10.8

 Netherlands

9.5 ± 3.2

Great Britain

9.0 ± 3.2

Greece

39.5 ± 9.3

Greece

39.9 ± 11.2

 Russia

9.5 ± 2.8

Israel

8.9 ± 3.3

Denmark

40.4 ± 9.8

Ireland

40.2 ± 9.2

 Norway

9.5 ± 2.9

Belgium

8.8 ± 3.0

Spain

40.6 ± 9.2

Spain

40.3 ± 9.6

 Great Britain

9.2 ± 3.1

Czech Republic

8.8 ± 3.4

Mexico

40.6 ± 8.5

Great Britain

40.4 ± 10.4

 Brazil

9.2 ± 2.5

Ireland

8.7 ± 3.1

Luxembourg

41.0 ± 9.8

Mexico

40.8 ± 9.0

 Mexico

9.2 ± 2.4

India

8.7 ± 2.5

Austria

41.1 ± 8.5

Switzerland

41.2 ± 10.3

 Czech Republic

9.1 ± 3.6

Mexico

8.7 ± 3.3

Liechtenstein

41.1 ± 9.7

Liechtenstein

41.2 ± 9.2

 Greece

8.8 ± 2.7

Greece

8.6 ± 3.1

Switzerland

41.3 ± 10.3

Luxembourg

41.3 ± 9.2

 USA

8.7 ± 3.1

Poland

8.5 ± 3.6

France

41.4 ± 9.5

Denmark

41.6 ± 10.7

 Denmark

8.6 ± 3.0

USA

8.1 ± 3.0

Belgium

42.0 ± 10.4

France

41.6 ± 9.6

 Israel

8.6 ± 3.6

Germany

8.4 ± 3.2

Portugal

42.3 ± 8.7

Slovenia

41.6 ± 16.2

 South Africa

8.5 ± 2.7

Argentina

8.4 ± 3.0

Australia

42.3 ± 8.7

Netherlands

41.7 ± 10.6

 Poland

8.5 ± 3.5

Russia

8.3 ± 2.7

Italy

42.3 ± 9.6

Belgium

41.8 ± 10.7

 Belgium

8.4 ± 3.0

Denmark

8.2 ± 2.9

Israel

42.5 ± 12.8

Finland

42.1 ± 11.7

 Germany

8.4 ± 3.2

Sweden

8.1 ± 3.1

Sweden

42.6 ± 11.9

Austria

42.3 ± 9.1

 Australia

8.2 ± 2.9

Brazil

8.0 ± 2.9

South Africa

43.3 ± 9.9

Norway

42.5 ± 12.6

 Sweden

8.2 ± 3.1

Austria

7.9 ± 3.1

Germany

43.3 ± 9.7

Israel

42.6 ± 11.9

 Luxembourg

8.1 ± 2.8

Slovenia

7.9 ± 3.1

Brazil

43.7 ± 10.9

Italy

42.8 ± 9.5

 Austria

7.9 ± 3.1

South Africa

7.8 ± 3.2

Netherlands

44.1 ± 9.7

Greece

43.1 ± 9.9

 Canada

7.2 ± 3.3

Luxembourg

7.8 ± 2.9

Finland

45.6 ± 10.7

Sweden

43.4 ± 11.8

 Slovenia

7.1 ± 2.9

Canada

7.4 ± 3.1

Hungary

48.1 ± 11.5

Hungary

44.2 ± 13.1

 Finland

6.6 ± 2.8

Finland

7.0 ± 2.6

Norway

48.3 ± 13.5

Brazil

44.6 ± 9.9

 Japan

6.2 ± 2.6

Japan

6.5 ± 2.9

Japan

48.8 ± 14.2

Japan

49.5 ± 15.8

Marathon

 Ethiopia

18.8 ± 0.3

Kenya

17.8 ± 1.3

Ethiopia

26.3 ± 5.5

Ethiopia

27.2 ± 4.6

 Kenya

18.3 ± 0.1

Ethiopia

16.1 ± 1.6

Kenya

33.5 ± 2.1

Kenya

29.2 ± 6.0

 Liechtenstein

16.6 ± 3.5

Liechtenstein

16.6 ± 3.5

Poland

38.5 ± 11.6

Liechtenstein

40.3 ± 9.0

 Italy

15.8 ± 4.1

Switzerland

14.7 ± 4.0

Great Britain

39.0 ± 10.4

Great Britain

40.4 ± 10.2

 Switzerland

15.0 ± 4.1

Belgium

14.4 ± 3.9

Canada

40.2 ± 10.0

Poland

40.5 ± 13.1

 Japan

14.1 ± 4.4

Spain

14.2 ± 3.9

Liechtenstein

41.2 ± 10.3

USA

41.3 ± 10.6

 Spain

13.6 ± 2.8

Italy

13.6 ± 3.9

Austria

41.5 ± 8.5

Canada

41.4 ± 11.1

 France

13.4 ± 3.9

France

13.3 ± 3.8

Spain

41.8 ± 7.8

Switzerland

41.8 ± 10.5

 Great Britain

13.2 ± 3.9

Great Britain

13.3 ± 3.9

Switzerland

41.9 ± 10.7

Belgium

42.1 ± 11.0

 Poland

12.9 ± 3.4

Germany

12.9 ± 3.6

USA

43.3 ± 16.5

Spain

42.3 ± 9.5

 Germany

12.9 ± 3.8

USA

12.8 ± 3.9

Belgium

43.4 ± 11.7

Austria

42.9 ± 8.5

 Austria

12.4 ± 3.0

Austria

12.3 ± 2.9

France

43.6 ± 9.2

France

43.2 ± 9.7

 USA

12.3 ± 3.8

Japan

12.1 ± 4.1

Germany

43.8 ± 10.2

Germany

43.4 ± 9.6

 Canada

11.9 ± 4.4

Poland

11.9 ± 3.3

Italy

45.0 ± 12.2

Italy

43.5 ± 9.9

 Belgium

11.6 ± 2.6

Canada

11.8 ± 4.3

Japan

51.8 ± 14.9

Japan

48.0 ± 15.5

Considering age, women from Ethiopia and Kenya were the youngest in absolute terms. However, Ethiopian women were not younger than women from Russia, Czech Republic, Argentina, India, Slovenia, Ireland, USA, Great Britain, Poland, Canada, Greece, Denmark and Spain (p > 0.05). Considering athletes from the other countries, women from Ethiopia were significantly younger (p < 0.001 to p < 0.0001). For men, runners from Kenya and Ethiopia were the youngest in absolute values. However, they were not younger than athletes from Russia, Czech Republic, Poland, South Africa, Canada, Australia, Argentina, India, Portugal, USA and Greece (p > 0.05) but significantly younger than men from all other countries (p < 0.001 to p < 0.0001).

In marathon, women from Ethiopia and Kenya were faster than women from all other countries (p < 0.001 to p < 0.0001). However, Ethiopian women were not faster than Kenyan women (p > 0.05). For men, the fastest running speeds were achieved by athletes from Kenya, Ethiopia and Principality of Liechtenstein. Kenyan men were faster than men from all other countries (p < 0.001 to p < 0.0001) with the exception of Ethiopian men (p > 0.05). Ethiopian men were, however, not faster than men from Liechtenstein, Switzerland, Belgium, Spain, Italy, France, Great Britain, Germany and USA (p > 0.05).

Women from Ethiopia and Kenya were the youngest in absolute terms. However, only women from Japan were significantly older than women from Ethiopia (p = 0.001) but not all other women (p > 0.05). Considering Kenyan women, no statistical significant differences were found between the countries (p > 0.05). For men, Ethiopians and Kenyans were the youngest in absolute terms. Ethiopian men were not younger than Kenyan men (p > 0.05), but significantly younger than men from all other countries (p < 0.001 to p < 0.0001). Men from Kenya were not younger than men from Liechtenstein, Great Britain, Poland and the USA, but significantly younger than men from all other countries (p < 0.001 to p < 0.0001).

Discussion

This study intended to investigate performance and age of female and male Ethiopian and Kenyan half-marathoners and marathoners competing in races held in one country. The most important findings for female and male half-marathons and marathoners from Ethiopia and Kenya were that, (1) they accounted for less than 0.1 %, (2) they were running the fastest and, (3) they were the youngest.

Low participation of East African runners

A first important finding was that runners from Kenya and Ethiopia accounted for less than 0.1 % in both half-marathons and marathons. The small percentage of participants from these countries should be attributed partially to the distance between these countries and the place of race. Considering the nationality of participants, one might observe a very large number of local participants followed by participants from the neighbouring countries.

Although athletes from neighbouring countries such as Germany, France, Italy and Austria were very numerous, also athletes from very remote countries such as the United States, Japan and Australia competed more numerous than athletes from Ethiopia and Kenya. A very likely explanation could be the income of persons living in these countries since they need to spend money for the travel to and the stay in Switzerland. Costs of living are very high in Switzerland compared to other countries (www.numbeo.com/cost-of-living/country_result.jsp?country=Switzerland). When we compare the gross domestic product (GDP) per capita for persons living in East African countries such as Ethiopia (www.indexmundi.com/ethiopia/gdp_per_capita_%28ppp%29.html) and in Kenya (http://www.indexmundi.com/kenya/gdp_per_capita_%28ppp%29.html) with $1300 and $1800, respectively, persons from the other countries such as the United States of America (www.indexmundi.com/united_states/gdp_per_capita_%28ppp%29.html), Japan (www.indexmundi.com/japan/gdp_per_capita_%28ppp%29.html) and Australia (www.indexmundi.com/australia/gdp_per_capita_%28ppp%29.html) have a GDP of $52,800, $ 37,100, and $43,000, respectively. With these higher GDP, persons from the United States of America, Japan and Australia might easier travel to Switzerland for competing in a marathon than persons from Ethiopia and Kenya.

The finding that mainly local athletes compete in races followed by athletes from surrounding countries confirms recent findings for other races. For example, in long-distance triathletes competing in the ‘Ironman Hawaii’, women and men from the United States of America dominated both participation and performance (Dähler et al. 2014). In solo swimmers crossing the ‘English Channel’ between 1875 and 2013, the most representative nations in the ‘English Channel Swim’ were Great Britain, the United States of America, Australia and Ireland. The fastest swim times were, however, not achieved by local athletes but by athletes from the United States of America, Australia and Great Britain (Knechtle et al. 2014).

However, the most likely explanation for the very low participation of East African runners in half-marathons and marathons held in Switzerland are economic reasons. For Kenyan runners, marathon running is a means of making money to help their families, parents and siblings (Onywera et al. 2006; Onywera 2009). Onywera (2009) described economic reasons for Kenyan athletes as one of the most important factors to compete in marathon running, which might be undercharged so far (Hamilton and Weston 2000). Prize money in Swiss half-marathons and marathons is very low compared to prize money offered in the ‘World Marathon Majors’ (www.worldmarathonmajors.com). For the winner in the ‘Zurich Marathon’ in Switzerland, the prize money is 10,000 Swiss Francs (www.zurichmarathon.ch) which is very low in contrast to the prize money offered in large city marathons. Indeed, overall prize money in races of the ‘World Marathon Majors’ is considerably higher (www.worldmarathonmajors.com). In the ‘BMW Berlin Marathon‘, the ‘Tokyo Marathon’, and the ‘Virgin London Marathon’ the prize money is $1,000,000, in the ‘Boston Marathon’ $846,000, in the ‘TCS NYC Marathon’ $805,000 and in the ‘Bank of America Chicago Marathon’ $560,000 (www.bestroadraces.com/brr100.php/prizes). The differences in prize money seem very similar in half-marathon compared to marathon. In a large half-marathon held in Switzerland such as the ‘Hallwilerseelauf’, the prize money for both women and men for the top five is, however, only CHF 600, 400, 300, 200, and 100, respectively (www.hallwilerseelauf.ch). In an elite half-marathon such as the IAAF/AL-Bank World Half Marathon Championships’, a total prize purse of US$245,000 will be paid by the IAAF for the men’s and women’s races (www.iaaf.org/news/news/prize-money).

East African runners were the fastest in half-marathons and marathons

A second finding was that female and male runners from Kenya and Ethiopia were the fastest in both half-marathons and marathons. The dominance of East African runners was evident for both marathon and half-marathon but differed from longer distances. For instance, it has been shown that male Japanese runners were the best in 100-km ultra-marathons (Cejka et al. 2014). The trend in performance across years should be explained by a model showing that human speed after having progressed fast in the past has now reached a plateau and further progression should be attributed to an enlarged population of runners and improved training practices (Desgorces et al. 2012).

East African runners were the youngest in half-marathons and marathons

A third important finding was that women and men from Kenya and Ethiopia were the youngest in both half-marathons and marathons. Their mean age is considerably lower as has been reported for elite and recreational marathoners. The age of elite marathoners is at around 29–30 years when the nationality was not considered (Hunter et al. 2011). In female and male marathoners competing between 1979 and 2014 in the ‘Stockholm Marathon’, the age of the fastest marathon performance was even higher with 34.3 ± 2.6 years (Lehto 2015). In a study investigating runners competing in Swiss half-marathons and marathons from 2000 to 2010 and considering the top five African and Non-African runners, the mean age of the male runners was significantly higher for Non-African runners than for African runners in both half-marathons (Non-African runners 31.1 ± 6.4 years, African runners 26.2 ± 4.9 years) and marathons (Non-African runners 33.0 ± 4.8 years, African runners 28.6 ± 3.8 years). In marathons, the top five female Non-African runners (31.6 ± 4.8 years) were ~4 years older than the top five female African runners (27.8 ± 5.3 years) (Aschmann et al. 2013). The difference in age between East Africans and Europeans found in the present study was not in agreement with a previous comparison between African and non-African runners of marathons and half-marathons (Cribari et al. 2013) indicating that the younger age was a specific characteristic of East Africans and should not be generalized to all African runners.

Physiological interpretation

For the dominance of East African runners such as Kenyan runners, physiological aspects need to be considered (Larsen 2003; Larsen and Sheel 2015). It has been supported that running speed sustained over a prolonged time depends on the maximal sustainable VO2 (oxygen uptake) and running economy (Millet et al. 2012). A comparison between European and Eritrean long-distance runners showed that Eritreans, despite having a lower VO2max (maximum oxygen uptake), had a better running economy at 19 km h−1 (Santos-Concejero et al. 2015). A better running economy might explain the supremacy of East Africans in the marathon, and the delayed glycogen depletion and reduced thermal stress have been suggested to be associated with a better running economy (Millet et al. 2012). An exceptional biomechanical and metabolic economy, chronic exposition to altitude, sociocultural background and a strong psychological motivation were highlighted as other factors of this supremacy (Onywera 2009; Wilber and Pitsiladis 2012). Moreover, the impact of stereotypes has also been noticed because, independently from the possible existence of physiological advantages in East Africans, the belief that such differences exist can impact performance by creating a psychological atmosphere (Baker and Norton 2003). With regards to their nutritional habits, a research on the dietary intake of Ethiopian long distance runners has shown that they met most recommendations for endurance athletes (Beis et al. 2011). A study on the diet of Kenyan endurance runners revealed that it composed mostly by carbohydrates (~67 %) and less by protein (~15 %) or fat (~17 %) (Fudge et al. 2006).

In addition to the abovementioned physiological factors, Eastern African runners might differ from runners of other origin with regards to other specific anthropometric characteristics (Kohn et al. 2007; Lucia et al. 2006; Prommer et al. 2010; Vernillo et al. 2013). For instance, compared to elite German 10-km runners, elite Kenyan runners had a similar VO2max (ml min−1 kg−1) but were lighter by more than 9 kg (Prommer et al. 2010). Xhosa 10-km runners had also similar VO2max (ml min−1 kg−1) as their Caucasian counterparts, but they were lighter and shorter (Kohn et al. 2007). Eritrean distance runners had a lower body mass index and a better running economy at 21 km h−1 than Spanish runners, whereas their VO2max was similar (Lucia et al. 2006). In top class Kenyan marathoners, ectomorphy is dominant, but endomorphy and mesomorphy is more than one-half unit lower (Vernillo et al. 2013).

A review of genetic and lifestyle factors of the performance of the East Africans distance runners concluded that the findings on candidate genes linked to performance of Caucasian populations were not confirmed in East Africans showing research methods’ limitations and the polygenic nature of performance (Tucker et al. 2013). This was in agreement with another review showing that distance running success of East Africans was not based on a unique genetic profile (Wilber and Pitsiladis 2012). Another parameter that has not been studied previously as much as the abovementioned parameters might be the physical activity and inactivity levels when athletes did not practise their sport. Surprisingly, a study in marathon and half-marathon runners showed that these athletes trained for 6.5 h weekly, but they also spent much more time sitting (Whitfield et al. 2014). The aforementioned study found no relationship between sitting time and performance. However, potential differences in non-sport physical activities and inactivity levels between East Africans and Europeans should be examined in future studies.

Limitations

A limitation of this analysis is the fact that an athlete may have changed his/her nationality, where, for example, an athlete from an African country might have been naturalized in another country. As an example, the Swiss marathoner Tadesse Abraham was born in Eritrea but is now a Swiss citizen. He won three marathons and one half-marathon in Switzerland (www.tadesse-abraham.ch). On the other hand, the focus of the present study was on half-marathon runners’ characteristics (i.e. age, participation and performance) with regards to marathon. Since there was no evidence that the above-mentioned concern about the nationality appeared differently to the two events (half-marathon vs. marathon), it might be supported that it did not affect the overall findings.

Conclusions

In summary, women and men from Kenya and Ethiopia, despite they accounted for less than 0.1 % in half-marathons and marathons, achieved the fastest race times and were the youngest in both half-marathons and marathon. These findings confirmed in the case of half-marathon the trend previously observed in marathon races for a better performance and a younger age in East African runners compared to Non-African runners.

Declarations

Authors’ contributions

BK and MZ collected all data, BK, PN and VO drafted the manuscript, CR and PN performed the statistical analyses, CR and TR participated in the design and coordination and helped drafting the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Facharzt FMH für Allgemeinmedizin, Gesundheitszentrum St. Gallen
(2)
Institute of Primary Care, University of Zurich
(3)
Department of Physical and Cultural Education, Hellenic Army Academy
(4)
Department of Recreation Management and Exercise Science, Kenyatta University

References

  1. Anthony D, Rüst CA, Cribari M, Rosemann T, Lepers R, Knechtle B (2014) Differences in participation and performance trends in age group half and full marathoners. Chin J Physiol 57:209–219View ArticleGoogle Scholar
  2. Aschmann A, Knechtle B, Cribari M, Rüst CA, Onywera V, Rosemann T, Lepers R (2013) Performance and age of African and non-African runners in half- and full marathons held in Switzerland, 2000-2010. Open Access J Sports Med 4:183–192Google Scholar
  3. Baker J, Norton S (2003) East African running dominance revisited: a role for stereotype threat? Br J Sports Med 37:553–555View ArticleGoogle Scholar
  4. Beis LY, Willkomm L, Ross R, Bekele Z, Wolde B, Fudge B, Pitsiladis YP (2011) Food and macronutrient intake of elite Ethiopian distance runners. J Int Soc Sports Nutr 8:7View ArticleGoogle Scholar
  5. Cejka N, Rüst CA, Lepers R, Onywera V, Rosemann T, Knechtle B (2014) Participation and performance trends in 100-km ultra-marathons worldwide. J Sports Sci 32:354–366View ArticleGoogle Scholar
  6. Cribari M, Rüst CA, Rosemann T, Onywera V, Lepers R, Knechtle B (2013) Participation and performance trends of East-African runners in Swiss half-marathons and marathons held between 2000 and 2010. BMC Sports Sci Med Rehabil 5:24View ArticleGoogle Scholar
  7. Dähler P, Rüst CA, Rosemann T, Lepers R, Knechtle B (2014) Nation related participation and performance trends in ‘Ironman Hawaii’ from 1985 to 2012. BMC Sports Sci Med Rehabil 6:16View ArticleGoogle Scholar
  8. Desgorces FD, Berthelot G, Charmantier A, Tafflet M, Schaal K, Jarne P, Toussaint JF (2012) Similar slow down in running speed progression in species under human pressure. J Evol Biol 25:1792–1799View ArticleGoogle Scholar
  9. Fudge BW, Westerterp KR, Kiplamai FK, Onywera VO, Boit MK, Kayser B, Pitsiladis YP (2006) Evidence of negative energy balance using doubly labelled water in elite Kenyan endurance runners prior to competition. Br J Nutr 95:59–66View ArticleGoogle Scholar
  10. Hamilton B (2000) East African running dominance: what is behind it? Br J Sports Med 34:391–394View ArticleGoogle Scholar
  11. Hamilton B, Weston A (2000) Perspectives on East African middle and long distance running. J Sci Med Sport 3:6–8Google Scholar
  12. Hunter SK, Stevens AA, Magennis K, Skelton KW, Fauth M (2011) Is there a sex difference in the age of elite marathon runners? Med Sci Sports Exerc 43:656–664View ArticleGoogle Scholar
  13. Knechtle B, Rosemann T, Rüst CA (2014) Participation and performance trends by nationality in the ‘English Channel Swim’ from 1875 to 2013. BMC Sports Sci Med Rehabil 6:34View ArticleGoogle Scholar
  14. Kohn TA, Essén-Gustavsson B, Myburgh KH (2007) Do skeletal muscle phenotypic characteristics of Xhosa and Caucasian endurance runners differ when matched for training and racing distances? J Appl Physiol (1985) 103:932–940View ArticleGoogle Scholar
  15. Larsen HB (2003) Kenyan dominance in distance running. Comp Biochem Physiol A: Mol Integr Physiol 136:161–170View ArticleGoogle Scholar
  16. Larsen HB, Sheel AW (2015) The Kenyan runners. Scand J Med Sci Sports Suppl 4:110–118View ArticleGoogle Scholar
  17. Lehto N (2015) Effects of age on marathon finishing time among male amateur runners in Stockholm Marathon 1979–2014. J Sport Health Sci. doi:https://doi.org/10.1016/j.jshs.2015.01.008 Google Scholar
  18. Lucia A, Esteve-Lanao J, Oliván J, Gómez-Gallego F, San Juan AF, Santiago C, Pérez M, Chamorro-Viña C, Foster C (2006) Physiological characteristics of the best Eritrean runners—exceptional running economy. Appl Physiol Nutr Metab 31:530–540View ArticleGoogle Scholar
  19. Millet GY, Hoffman MD, Morin JB (2012) Sacrificing economy to improve running performance—a reality in the ultramarathon? J Appl Physiol (1985) 113:507–509View ArticleGoogle Scholar
  20. Onywera VO (2009) East African runners: their genetics, lifestyle and athletic prowess. Med Sport Sci 54:102–109View ArticleGoogle Scholar
  21. Onywera VO, Scott RA, Boit MK, Pitsiladis YP (2006) Demographic characteristics of elite Kenyan endurance runners. J Sports Sci 24:415–422View ArticleGoogle Scholar
  22. Prommer N, Thoma S, Quecke L, Gutekunst T, Völzke C, Wachsmuth N, Niess AM, Schmidt W (2010) Total hemoglobin mass and blood volume of Elite Kenyan runners. Med Sci Sports Exerc 42:791–797View ArticleGoogle Scholar
  23. Santos-Concejero J, Oliván J, Maté-Muñoz JL, Muniesa C, Montil M, Tucker R, Lucia A (2015) Gait-cycle characteristics and running economy in elite Eritrean and European runners. Int J Sports Physiol Perform 10:381–387View ArticleGoogle Scholar
  24. Scott RA, Georgiades E, Wilson RH, Goodwin WH, Wolde B, Pitsiladis YP (2003) Demographic characteristics of elite Ethiopian endurance runners. Med Sci Sports Exerc 35:1727–1732View ArticleGoogle Scholar
  25. Tucker R, Santos-Concejero J, Collins M (2013) The genetic basis for elite running performance. Br J Sports Med 47:545–549View ArticleGoogle Scholar
  26. Tucker R, Onywera VO, Santos-Concejero J (2015) Analysis of the Kenyan distance-running phenomenon. Int J Sports Physiol Perform 10:285–291View ArticleGoogle Scholar
  27. Vernillo G, Schena F, Berardelli C, Rosa G, Galvani C, Maggioni M, Agnello L, La Torre A (2013) Anthropometric characteristics of top-class Kenyan marathon runners. J Sports Med Phys Fitness 53:403–408Google Scholar
  28. Wegner CE, Ridinger LL, Jordan JS, Funk DC (2015) Get serious: gender and constraints to long-distance running. J Leis Res 47:305–321Google Scholar
  29. Whitfield G, Pettee Gabriel KK, Kohl HW 3rd (2014) Sedentary and active: self-reported sitting time among marathon and half-marathon participants. J Phys Act Health 11:165–172View ArticleGoogle Scholar
  30. Wilber RL, Pitsiladis YP (2012) Kenyan and Ethiopian distance runners: what makes them so good? Int J Sports Physiol Perform 7:92–102Google Scholar

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© Knechtle et al. 2016