Impact of Ad Libitum Versus Programmed Drinking on Endurance Performance: A Systematic Review with Meta-Analysis
Debate continues on how athletes should hydrate during exercise. Several studies have recently been published comparing the effect of ad libitum (ALD) and programmed drinking (PD) on endurance performance (EP).
This work examined whether one drinking strategy offers an EP advantage over the other.
Systematic review and meta-analysis of crossover controlled trials.
PubMed and SPORTDiscus database searches.
Eligibility Criteria for Selecting Studies
Key criteria were (1) experiments performed under controlled settings; (2) exercise lasting ≥ 1 h; (3) exercise initiated in an euhydrated state; (4) fluid intake during PD > ALD; (5) fluid composition matched for electrolytes; and (6) carbohydrate intake varied by > 25% between conditions when the exercise was 1 h and matched for exercise > 1 h.
Seven publications, producing eight effect estimates, including cycling and running exercises and representing 82 subjects, were included. Mean (± standard deviation) ambient temperature, exercise intensity and duration of the experiments were 28 ± 6 °C, 81 ± 12% of maximal heart rate and 96 ± 25 min, respectively. Mean rate of fluid consumption for the PD and ALD conditions was 1073 ± 247 mL/h and 505 ± 156 mL/h, respectively. Mean change in body mass for the PD and ALD conditions was − 1.0 ± 0.5% and − 2.1 ± 0.7%, respectively. Compared with PD, ALD improved EP by 0.98 ± 0.44% (95% confidence interval 0.11–1.84%). The greater EP conferred by ALD is likely trivial.
Despite ALD being associated with an hourly rate of fluid consumption half as much as PD, and resulting in a dehydration level considered sufficient to impair EP, both strategies were found to similarly impact 1–2 h cycling or running performances conducted at moderate to high intensity and under temperate to warm ambient conditions.
Compliance with Ethical Standards
No funding was received for the conduct of this work or the preparation of this article.
Conflict of Interest
Eric D. B. Goulet and Martin D. Hoffman declare they have no potential conflicts of interest that are directly relevant to the content of this article.
- 5.Casa DJ, Armstrong LE, Hillman SK, Montain SJ, Reiff RV, Rich BS, et al. National athletic trainers’ association position statement: fluid replacement for athletes. J Athl Train. 2000;35(2):212–24.Google Scholar
- 30.Zoladz JA, Szkutnik Z, Majerczak J, Duda K. Non-linear relationship between oxygen uptake and power output in the Astrand nomogram: old data revisited. J Physiol Pharmacol. 2007;58(2):265–73.Google Scholar
- 34.Hopkins WG. How to interpret changes in an athletic performance test. Sportscience. 2004;8:1–7.Google Scholar
- 36.Lipsey M, Wilson D. Practical meta-analysis. Thousand Oaks: Sage Publications; 2000.Google Scholar
- 38.Hopkins WG. A spreadsheet for deriving a confidence interval, mechanistic inference and clinical inference from a p value. Sportscience. 2007;11:16–20.Google Scholar