A case report of the female world record holder from 1,500 m to the marathon in the 75+ age category.

This study assessed the cardiorespiratory fitness, running biomechanics, muscle architecture, and training characteristics of a 76-yr-old female runner who currently holds the world record 1,500 m to marathon in the women's 75-79 yr age category. Maximum oxygen uptake (V̇o), running economy (RE), lactate threshold (LT), lactate turnpoint (LTP), maximal heart rate (HR), and running biomechanics were measured during a discontinuous treadmill protocol followed by a maximal incremental test. Muscle architecture was assessed using ultrasound. The testing was done in close proximity to her world record marathon performance in 2024. V̇o was 47.9 mL·kg·min, and HR was 180 beats·min. At marathon speed (11.9 km·h) her RE was 210 mL·kg·km and her fractional utilization was 88% of V̇o. Fractional utilization at LT (11.1 km·h) and LTP (12.5 km·h) were 83% and 92% of V̇o, respectively. Average weekly distance was 115 and 84 km·wk in the 6 wk prior to the marathon world record, and 2024 World Masters Athletics Championships (where she achieved 6 gold medals out of 6 events), respectively, with on average 90%, 9%, and 1% of training time performed in the moderate, heavy, and severe intensity domain, respectively. The 76-yr-old female world-record holder 1,500 m to marathon showed the highest V̇o ever recorded for a female >75 yr old, a very high fractional utilization of V̇o at LT, LTP, and marathon pace, while RE was found to be modest compared with other world-class master and younger elite runners. This case study investigates the physiological determinants of exceptional performance in a 76-yr-old female world-record holder across distances from 1,500 m to the marathon. It reveals the highest V̇o ever recorded in females aged >75 yr and exceptional fractional utilization at metabolic thresholds and marathon speed, comparable to younger world-class distance runners. The modest running economy found can be partially explained by biomechanical and training data.