The impact of resistance training on distance running performance

Traditionally, distance running performance was thought to be determined by several characteristics, including maximum oxygen consumption ((V) over dot O (2max)), lactate threshold (LT), and running economy. Improvements in these areas are primarily achieved through endurance training. Recently, however, it has been shown that anaerobic factors may also play an important role in distance running performance. As a result, some researchers have theorised that resistance training may benefit distance runners. Because resistance training is unlikely to elicit an aerobic stimulus of greater than 50% Of (V) over dot O-2max, it is unlikely that resistance training would improve (V) over dot O-2max in trained distance runners. However, it appears that (V) over dot O-2max is not compromised when resistance training is added to an endurance programme. Similarly, LT is likely not improved as a result of resistance training in trained endurance runners; however, improvements in LT have been observed in untrained individuals as a result of resistance training. Trained distance runners have shown improvements of up to 8% in running economy following a period of resistance training. Even a small improvement in running economy could have a large impact on distance running performance, particularly in longer events, such as marathons or ultra-marathons. The improvement in running economy has been theorised to be a result of improvements in neuromuscular characteristics, including motor unit recruitment and reduced ground contact time. Although largely theoretical at this point, if resistance training is to improve distance running performance, it will likely have the largest impact on anaerobic capacity and/or neuromuscular characteristics. The primary purpose of this review is to consider the impact of resistance training on the factors that are known to impact distance running performance. A second purpose is to consider different modes of resistance exercise to determine if an optimal protocol exists.