Driving simulators are used in a wide range of research settings to help develop an understanding of driver behavior in complex environments. Acute alcohol impairment is an important research topic for traffic safety and a large number of studies have indicated levels of simulated driving impairment imposed by alcohol across a range of performance outcome variables. The aim of the present study was to examine the impact of acute alcohol consumption on simulated driving performance by conducting a systematic review and meta-analysis of the available evidence. The online databases PubMed (MEDLINE), Web of Science (via Thomas Reuters) and Scopus were searched to identify studies that measured simulated car driving performance under control ('no alcohol' or 'placebo alcohol' ingestion) and intervention (acute alcohol ingestion) conditions, using repeated-measures experimental designs. Primary research outcomes were standard deviation of lane position (SDLP) and standard deviation of speed (SDSP); (total number of lane crossings (LC) and average speed (Speed) were secondary research outcomes). Meta-analytic procedures were used to quantify the effect of acute alcohol consumption on vehicle control, and to determine the influence of methodological variables (i.e. the duration of the simulated driving task, the limb of the BAC curve (ascending vs. descending) and the type of driving simulator employed (i.e. car vs. PC-based)) on the magnitude of the performance change due to alcohol consumption. 423 records were screened, and 50 repeated-measures trials (n=962 participants, 62% male) derived from 17 original publications were reviewed. 37 trials (n=721 participants) used a 'placebo alcohol' comparator to determine the effect of alcohol consumption on SDLP (32/37) and SDSP (22/37). Alcohol consumption significantly increased SDLP by 4.0±0.5cm (95% CI: 3.0, 5.1) and SDSP by 0.38±0.10km⋅h (95% CI: 0.19, 0.57). Regression analyses indicate BAC (p=0.004) and driving simulator platform (p<0.001) influence the magnitude of the SDLP change, such that higher BAC levels and the use of PC-based driving simulators were associated with larger performance decrements (R=0.80). The limb of the BAC curve and the duration of the driving task did not significantly alter the magnitude of the performance change. Eleven trials (n=205 participants) used a 'no alcohol' comparator to measure the effect of alcohol consumption on SDLP (10/11); few trials assessed SDSP (3/11). Alcohol consumption resulted in a small significant increase in SDLP under these conditions (standardized difference in means=0.23, 95% CI: 0.06, 0.39). These results demonstrate that lateral (SDLP and LC) and longitudinal (SDSP) vehicle control measures in a driving simulator are impaired with acute alcohol consumption. However, SDLP appears to be a more sensitive indicator of driving impairment than other driving performance variables and the results of the present study support its use as a performance outcome when examining alcohol-induced simulated driving impairment.

Introduction: This study compared the effects of ad libitum consumption of different beverages and

This study investigated the effects of aerobic exercise, fluid loss and rehydration on cognitive performance in well-trained athletes. Ten endurance-trained males (25 ± 5 years; 175 ± 5 cm; 70.35 ± 5.46 kg; VO, 62.95 ± 7.20 ml · kg.min) lost ~2.5 ± 0.6% body mass via continuous cycling exercise at ~65% peak sustainable power output (60 min duration) before consuming different beverages (Water = W1 and W2, Sustagen Sport = SS, Powerade = PD) and food ad libitum on four separate occasions. Cognitive function using a four-choice reaction time task (CRT), body mass, fluid consumption volumes, urine samples and subjective ratings (alertness, concentration, energy) were obtained before and after exercise, and hourly during recovery (for 4 h). CRT latency was significantly reduced immediately after exercise compared to pre-exercise measures for all trials (W1 = -16 ± 18 ms, W2 = -22 ± 21 ms, PD = -22 ± 22 ms, SS = -19 ± 26 ms). However, this effect was short-lived with subsequent measures not different from pre-exercise values. No difference in CRT accuracy was observed at any time across all trials. Subjective ratings were not different at any time across all trials. Aerobic exercise, hypohydration or an interaction between these two may provide a small cognitive performance benefit. However, these effects are temporary and confined to the immediate post-exercise period.

This study assessed voluntary dietary intake when different beverages were provided within a recovery area following recreational exercise. Participants completed two 10-km runs 1 week apart. Immediately after the first run, “beer drinkers” (n = 54; mean ± SD: age = 23.9 ± 5.8 years, body mass [BM] = 76 ± 13 kg) randomly received low-alcohol beer (Hahn Ultra® [Lion Co.], 0.9% alcohol by volume) or sports drink (SD; Gatorade® [PepsiCo]), whereas “nonbeer drinkers” (n = 78; age = 21.8 ± 2.2 years, BM = 71 ± 13 kg) received water or SD. Participants remained in a recovery area for 30–60 min with fluid consumption monitored. The following week, participants received the alternate beverage. Participants recorded all food/fluid consumed for the remainder of both trial days (diary and photographs). Fluid balance was assessed via BM change and urine specific gravity. Paired t tests were used to assess differences in hydration and dietary variables. No differences were observed in preexercise urine specific gravity (∼1.01) or BM loss (∼2%) between intervention groups (ps > .05). Water versus SD: No difference in acute fluid intake was noted (water = 751 ± 259 ml, SD = 805 ± 308 ml, p = .157). SD availability influenced total energy and carbohydrate intakes (water = 5.7 ± 2.5 MJ and 151 ± 77 g, SD = 6.5 ± 2.7 MJ and 187 ± 87 g, energy p = .002, carbohydrate p < .001). SD versus beer: SD availability resulted in greater acute fluid intake (SD = 1,047 ± 393 ml, beer = 850 ± 630 ml; p = .004), which remained evident at the end of trial days (SD = 3,337 ± 1,100 ml, beer = 2,982 ± 1,191 ml; p < .01). No differences in dietary variables were observed. Next day, urine specific gravity values were not different between water versus SD. However, a small difference was detected between SD versus beer (SD = 1.021 ± 0.009, beer = 1.016 ± 0.008, p = .002). Consuming calorie-containing drinks postexercise appears to increase daily energy and carbohydrate intake but has minimal impact on next-day hydration.

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