Akihiko Yamaguchi1, Miku Shouji2, Akane Akizuki3, Koshiro Inoue4, Takemune Fukuie5, Kunihiro Sakuma6, Isao Morita7. 1. Department of Physical therapy, School of Rehabilitation Sciences, Health Sciences University of Hokkaido, Kanazawa, Ishikari-Tobetsu, Sapporo, Hokkaido, 061-0293, Japan. yama@hoku-iryo-u.ac.jp. 2. Department of Rehabilitation, Seiseikai Sapporo Hospital, Kawazoe 14-jo 1-chome, Minamiku, Sapporo, Japan. 3. Department of Early Childhood Education, Takushoku University Hokkaido Junior College, Memu, Fukagawa, Hokkaido, Japan. 4. Department of Physical therapy, School of Rehabilitation Sciences, Health Sciences University of Hokkaido, Kanazawa, Ishikari-Tobetsu, Sapporo, Hokkaido, 061-0293, Japan. 5. School of Nursing and Social Services, Health Sciences University of Hokkaido, Ishikari-Tobetsu, Sapporo, Hokkaido, Japan. 6. Institute for Liberal Arts, Environment and Society, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan. 7. School of Humanities, Hokusei Gakuen University, Ohyachi-Nishi, Atsubetsu-ku, Sapporo, Japan.
Abstract
PURPOSE: This study attempted to clarify the relationships between marathon time and monthly training volume, training frequency and the longest (LRD) or average running distance per workout (ARD), as well as their interactions. METHODS: Male recreational runners (n = 587) participating in the Hokkaido Marathon 2017 completed a questionnaire before the race; of these, 494 finished the race. We assessed age, running career, body height, body weight, body mass index (BMI), monthly training volume, training frequency, the LRD and the ARD. These indicators were each divided into 4 or 5 homogeneous subgroups to determine whether the other indicators in each subgroup predicted marathon time. RESULTS: In the training frequency subgroups, there were significant correlations between monthly training volume, the LRD or the ARD and marathon time, except for the subgroup that trained 2 times per week or less; in this subgroup, the relationship between the ARD and marathon time was not significant. In all monthly training volume subgroups, there were no significant relationships between training frequency, the LRD or the ARD and marathon time. In the ≥ 21 km LRD and ≥ 10 km ARD subgroups, there were significant correlations between monthly training volume and marathon time (all P < 0.01); these correlations were not significant in the 1-20 km LRD and < 10 km ARD subgroups. CONCLUSION: These results indicate that monthly training volume is the most important factor in predicting marathon time and that the influence of monthly training volume is only significant if the running distance per workout exceeded a certain level.
PURPOSE: This study attempted to clarify the relationships between marathon time and monthly training volume, training frequency and the longest (LRD) or average running distance per workout (ARD), as well as their interactions. METHODS: Male recreational runners (n = 587) participating in the Hokkaido Marathon 2017 completed a questionnaire before the race; of these, 494 finished the race. We assessed age, running career, body height, body weight, body mass index (BMI), monthly training volume, training frequency, the LRD and the ARD. These indicators were each divided into 4 or 5 homogeneous subgroups to determine whether the other indicators in each subgroup predicted marathon time. RESULTS: In the training frequency subgroups, there were significant correlations between monthly training volume, the LRD or the ARD and marathon time, except for the subgroup that trained 2 times per week or less; in this subgroup, the relationship between the ARD and marathon time was not significant. In all monthly training volume subgroups, there were no significant relationships between training frequency, the LRD or the ARD and marathon time. In the ≥ 21 km LRD and ≥ 10 km ARD subgroups, there were significant correlations between monthly training volume and marathon time (all P < 0.01); these correlations were not significant in the 1-20 km LRD and < 10 km ARD subgroups. CONCLUSION: These results indicate that monthly training volume is the most important factor in predicting marathon time and that the influence of monthly training volume is only significant if the running distance per workout exceeded a certain level.
Authors: Christoph Alexander Rüst; Beat Knechtle; Patrizia Knechtle; Ursula Barandun; Romuald Lepers; Thomas Rosemann Journal: Open Access J Sports Med Date: 2011-08-02
Authors: Ursula Barandun; Beat Knechtle; Patrizia Knechtle; Andreas Klipstein; Christoph Alexander Rüst; Thomas Rosemann; Romuald Lepers Journal: Open Access J Sports Med Date: 2012-07-02