The effect of Los Angeles' oxidizing type of air pollu. tion on athletic performance was studied in 21 competitive meets of high school cross-country track runners from 1959 to 1954. Since running times tend to improve throughout the season, team performance at a meet was evaluated by determining the percent of boys who failed to improve when their running time was compared to that run at the previous meet on the same course. The highest correlation to team performance is that of the oxidant level in the licur before the race. Neither carbon monoxide, temperature, nor humidity shows any relationship to performance. The specificity of the effect to a biologically meaningful time and the very high correlation are convincing evidence of a cause and effect relationship. The mechanism by which oxidants affect performance may be directly physiological or may be decreased motivation due to discomfort.

Air

ir pollution in the Los Angeles area, in contrast to most other cities, is composed predominately of oxidizing compounds that arise from photochemical reactions among various combustion products of motor vehicle fuel. Effects of this smog on human health, other than eye irritation and chest discomfort, have never been clearly demonstrated. If other effects cccur, they might well be more readily detected in the presence of other stresses such as illness, or fatigue due to exertion. To our knowledge, no type of air pollution has been studied in relation to athletic performance. Long-distance races would seem to be most likely to reveal auch effects since they in

From the Hosth Effects Research Program, National Center for Air 'lution Control, US Public Health Service, Cincinnati (Miss Wayn and Dr. Cerroll), and the Department of Pediatrics. UniVerw of Southern California School of Medicine and the las Angeles County General Hospital, Los Angeles (Dr. Wehrle). Reprint requests to 5008 Federal Office Bldg, Cincinnati 45202 (Dr. Carroll).

volve a maximal effort with considerable pulmonary air exchange.

Methods

Because of the meticulous records of running times kept by the coach, the performance of the cross-country track team at San Marino (California) High School was studied. All competitive meets on the team's home course during the sixyear period from 1959 to 1964 were included in the analysis.

To minimize the effect of differences in training and experience between the boys, only boys who ran in all the home meets during a year were studied. The running time of each athlete on a specific day was compared with his performance at the previous home meet. The group performance for each meet (after the first meet of the year) was expressed as the percent of the group members who failed to improve when their running time was compared to that of the previous meet.

Air pollution data were supplied by the Los Angeles County Air Pollution Control District. All measurements are from station 64, which is located approximately 2 miles north of the track. The hourly levels used for this report are the arithmetic averages of the readings taken during the hours.

All meets began at approximately 3 PM except the second meet of 1963, which was held at 6 PM. The air pollution data are only available for clock hours. Thus, the average pollutant concentration between 2 PM and 3 PM is considered to be the level for the hour preceding the race, even if the race actually began at 3:15 PM. In this case, the hour during which the race occurred would be from 3 PM to 4 PM; however, since the races only last about 12 minutes, most of the measured pollution for the hour of the race actually was present after the race was completed.

Correlation Coefficients Between Cross-Country Track Performance and Air Pollutants

Results

As expected, the average running time for the group of boys who ran in all the home meets for a year tended to improve throughout the season (Fig 1). The four meets in which the average team time did not improve were the four worst days of the series for air pollution as measured by oxidant level in the hour before the race.

The percent of team members who failed to im prove their performance is highly correlated to the level of oxidant in the air (Fig 2). This correlation is highest during the hour before the meets (product moment correlation coefficient [r] = 0.88). Oxidant levels at hours further from the time of the meet show progressively lower correlations (Table).

Correlations with other measures of air pollution are less striking or absent. Total suspended particulate matter in the hour before the races has a lower correlation than oxidant (r = 0.62). Correlations with particulates at other hours are even lower. Carbon monoxide levels show no relationship to performance (r = 0.08). Too few dcterminations for oxides of nitrogen are available for calculation of meaningful hourly correlations: however, the average level for the day shows no relationship at all. Neither temperature, relative humidity, wind velocity, nor wind direction shows any relationship to performance.

Although all of the oxidant concentrations are significantly different from zero, the differences between them are not statistically significant by the usual test. The consistent trend, however, of decreasing correlations at times further away from

2 hr before race 3 hr before race Hour of race

Particulates

1 hr before race 2 hr before race Carbon monoxide

1 hr before race Total of 21 meets analyzed, 1959 to 1964. Number varies because of missing values for some pollutant levels

the race implies that the differences probably are real and that the maximum effect was during the hour before the race.

Because the pollution at one hour is highly dependent on the level at the preceding hour, the intercorrelations between various measurements must be considered before a causal relationship can be assumed. For example, even if the oxidant effect on performance was limited to the hour before the race, some correlation of performance with the level two hours before would be expected because of the high intercorrelation between the two oxidant levels. When these interrelationships are examined by the use of partial correlation tech

niques, the effect on performance appears to be limited to oxidant in the hour before the race. That is, the correlation with performance of all the measurements except oxidant in the hour before the race can be fully explained by the correlations between pollutant levels.

Examination of plots for each of the years indicates a. difference in the oxidant to perform.nce relationship between the first and last three years of the study. When the races in the periods 1959 to 1961 and 1962 to 1964 are analyzed separately, each group has correlation with oxicant of 0.945 (Fig 3). The slopes of the two regression lines are almost identical, but for a given oxidant level during the period 1962 to 1964 a larger percent of the team decreased their performance than during the earlier three years. We do not have any simple explanation for this difference. The method of measuring oxidant did not change during the six years, and the running-time curves in Fig 1 do not show this grouping. Differences in intensity of preseason training or changes

10 20 30 Oxidant (pphm)

I hr_before r⚫.08

Carbon monoxide (ppm)

2. Correlations between selected pollutant levels and the percent of team members whose performance decreased compared to that in the previous home meet (pphm signifies parts per hundred million).

in individuals on the team could be responsible. Comment

Becaus improvement in performance is somewhat cas to accomplish early in the season, a tensio r the days with high pollution to con late.. the season could produce a spurious por❤ tive correlation. Days with high pollution, how ever, appear to be scattered randomly through. the two-month cross-country running season each cf the six years. For example, in 1962 the worst pollution was during the first meet, whereas in 1963 the highest level was reached in the sixti. meet. Futhermore, the average pollution level for meets held in the first half of the season is almost identical to the average for the last half. A bias also might result if the opposing team were the same on days of similar pollution; however, this was not the case.

AL

10

20

Oxidant (pphm) hour before meet

30

3. Oxidant level in the hour before the meet by percent of team members with decreased performance.

An attempt to identify individual runners who were particularly susceptible to the effects of air pollution was unsuccessful. Careful examination of the team roster for each year indicated that none of the boys were consistently affected when they ran on heavily polluted days. Nor was there any tendency for the runners whose performance decreased to come from any particular school grade; seniors were affected as often as sophomores. Actually, this finding is not surprising since a boy whose performance drops at one meet may be strongly motivated to do well in succeeding meets. Also, any boy who showed frequent decreases in performance would hardly be desirable on a competitive team.

If the observed marked association of oxidant levels were for less specific measures of pollution, such as daily averages, then an explanation other than that oxidants were directly causal might be plausible. For example, other variables such as day of the week might be related to both performance air pollution. Our results, however, indicate

the relationship is app rently limited to the oudant level in the hour before the race. This specificity to a biologically meaningful time and the extremely high correlation (r=0.95) are conviting evidence that some omponent of the air which is measured as oxidant has a causal effect on team performance. That a long-range, chronic effect of air pollution is not also operative can not be inferred, since the study was designed to detect immediate effects only.

The level of oxidant in the air reflects the con