In 2006 I published the findings of a year long study into the effects of hydration on body mass, performance (skills) and injuries in Australian Rules Football (ARF). Whilst this paper is specifically related to ARF, the findings could be applied to almost any sport. Before you read the abstract, you may find the following of use:
Euhydration = in water balance
Hyperhydration = excess water
Hypohydration = water deficit
Dehydration = losing water
Rehydration = adding water
Refractometer Guidelines for hydration status
<1.010 = Fully hydrated. Maintain normal fluid intake (M)
1.011 – 1.020 = Low dehydration. Recommend M + 500mL
1.021 – 1.023 = High dehydration. Recommend M + 750mL
1.024 – 1.025 = Very high dehydration. Recommend M + 1L
1.026 – 1.027 = Severe dehydration. Recommend M + 1.25L
1.028 – 1.031 = Extreme dehydration. Recommend M + 1.5L
Hypohydration has been shown to occur during training and competition in the various football codes (1).
Hypohydration has been associated with reduced endurance performance, intermittent sprint performance, muscular strength, perceptive discrimination and decision making ability (1-4). Each of these factors are important for optimal performance in ARF.
Due to the climatic conditions in Australia and the high physical demands of ARF (5), players may be at risk of hypohydration.
To minimize deleterious effects of hypohydration on match performance, many top level ARF teams monitor hydration status with urine specific gravity (Usg) and changes in body mass (∆BM).
The purpose of this study was to assess the practical usefulness of these measures and to determine if relationships exist between pre-match Usg, match ∆BM and match-related skill and injuries in elite ARF
Thirty four elite ARF players participated in this study (age: 22.8±3.7 y; body mass (BM): 89.4±8.6 kg; height: 188±6 cm).
The hydration status of each selected player for each match (N=22) was determined by Usg (N=471), as well as changes in ∆BM for an entire season (N=415).
Usg, BM and ∆BM results were then compared to match-related skill performance and injury data.
Body mass measures
All players were required to record their BM approximately 15 min prior to and immediately following each match using calibrated digital platform scales accurate to 0.05 kg accurate (Model UC-321. A&D Co. Ltd., Australia).
For the logistical reasons, BM was taken with players in football clothing (and boots). To account for the trapped sweat, the mass of this attire was measured pre- and post-match and then subtracted from the BM measures. No measures of fluid intake were taken.
The ∆BM during each match was calculated according to the following equation: ∆BM = (corrected BMpost – corrected BMpre)
Urine specific gravity measures
Each player provided a urine sample 2 hr prior to each match for Usg analysis. Usg was measured from a 2 mL urine sample using a calibrated handheld refractometer (Figure 1) (Model URC-NE, Atago Inc, Japan). Staff members responsible for fluid distribution were notified of any player with Usg >1.020 mg/L.
Staff were then required to offer the identified player(s) the opportunity to drink more both prior to, and during the match.
Match-related skill statistics were obtained from the official league statistics (Champion Data, Melbourne, Australia). Only players who spent > 75% of total match time on the field were included in this analysis.
The match skill performance indicators were:
Effective Possessions – the number of kicks or hand passes that reached the intended target; and,
Ineffective Possessions – kicks or hand passes that did not reach the intended target.
Injuries were classified according to the number of matches missed as a result of that injury according to the methods of Orchard (6).
Pearson’s correlations and independent sample t-tests were used to assess the relationships between each of the variables with SPSS Version 12.1 was set at 0.05.
Usg was 1.005±0.004 mg/L (median: 1.004 mg/L, range: 1.001–1.023 mg/L).
BM was 90.8±8.1 kg pre-match, and 89.6±8.0 kg post-match. The ∆BM for the players who played more than 75% of match time (N=415) was 1.0± 0.8 kg (1.13±0.68% BM), with wide individual player variability (range: 0.0-3.62% BM).
There was a low incidence (8/471) of players with ∆BM >3%.
There were 21 match-related injuries that caused players to miss subsequent matches. The severity of injury ranged from 1–7 matches missed (mean: 2.71.8).
There were no differences in the Usg measures of the injured (N=21) vs. the non-injured players (N=463).
The players averaged 13.7±6.4 effective possessions and 2.7±2.7 ineffective possessions each match.
There was a significant relationship between ∆BM and total effective possessions when ∆BM exceeded 3% (r=0.60, p<0.05).
There were no other significant relationships between any of the measured variables.
Discussion & Conclusions
This study is the first to investigate the relationships between pre-match Usg, ∆BM, and match-related skill and injury measures.
In agreement with most prior research on other football codes (1), the present results show that elite ARF players only incur a mild fluid deficit during each match.
All pre-match Usg were within the normal range (1.013–1.029 mg/L ). The low Usgindicate that most players from this team may have started each match with excess body water (7).
A possible explanation for lack of relationships between Usg, ∆BM, injury incidence and skill-involvement is that the hydration strategies adopted by this team were effective in ensuring good pre-match hydration.
Most studies suggest that fluid losses >1.8% BM are required to show significant decreases in physical and mental performance (1). This may explain why only players with ∆BM of >3% showed an association with decreased skill involvement.
The high variability in match ∆BM in this study suggests that monitoring of ∆BM and Usg should be done on an individual basis.
The results of this study can be used to guide future hydration monitoring strategies for elite ARF players.
1. Burke, L. M., et al. (1997). Sports Medicine(1): 38-54
2. McGregor, S. J., et al. (1999). Journal of Sports Sciences(11): 895-903
3. Schoffstall, J. E., et al. (2001). Journal of Strength and Conditioning Research(1): 102-8
4. Cian, C., et al. (2001). International Journal of Psychophysiology(3): 243-51
5. Dawson, B., et al. (2004). Journal of Science and Medicine in Sport(3): 278-91
6. Orchard, J. (2002). Journal of Science and Medicine in Sport(2): v-vii
7. Armstrong, L. E. (2005). Nutrition Reviews(6 Pt 2): S40-54