Tropospheric ozone (O3) is an oxidant air pollutant formed from oxides of nitrogen and volatile organic compounds in the presence of sunlight.1,2 Approximately 115 million Americans live in areas that currently exceed the new 8-hour U.S. O3 standard of 80 ppb (3-year average of 4th highest).3
Ozone is largely an outdoor pollutant, and personal exposures are much lower than ambient concentrations.4 Nonetheless, a variety of health outcomes have been associated with exposure to ambient O3. Associations with short-term exposure have been reported for hospitalizations for respiratory illness,5 exacerbations of asthma6 and chronic obstructive pulmonary disease,7 total daily8 cardiovascular mortality (summertime levels9), decreases in lung function, and increased airway inflammation.10–14 Chronic exposure to high ambient O3 environments has been associated with the onset of asthma15,16 and mortality from cardiovascular disease (summertime concentrations).17
Chronic exposure to high concentrations of ambient O3 has been associated with decreased levels of 1-second forced expiratory volume (FEV1), maximum midexpiratory flow (FEF25–75), and forced expiratory flow after 75% of expired volume (FEF75).18–21 Growth of FEV1 and FEF25–75 during a 3-year period in first- and second-grade Austrian children was inversely associated with summertime O3 concentrations. In contrast, a study of children (10–18 years) from 12 Southern California communities did not find an association between lung growth and annual average community-specific O3 concentrations.22 However, the range of average concentrations across the 12 study communities was relatively small (factor of <2.5).
Previously, we reported that estimated lifetime exposure to ambient O3 concentrations in adolescents reared in the Los Angeles and San Francisco Bay areas of California were associated with decreased levels of FEF25–75 and FEF75.20 Effects were comparable whether exposure was based on an entire lifetime (∼18 years) or only on the first 6 years of life.20 These data were consistent with studies in monkeys23–25 and human O3 dosimetry26 that indicate that the impact of O3 on lung structure is at the level of the respiratory bronchioles and that measures that reflect small airway function take longer to recover than FEV1 after controlled human exposure to O3.27,28 The present study was undertaken to corroborate the previous findings with a larger sample and a more complete assessment of confounding from exposure to other ambient pollutants and second-hand tobacco smoke.
Design of Study
A convenience sample of freshman undergraduates between the ages of 16–19 years at the University of California, Berkeley (UCB) was recruited in 3 waves that began on 10 April 2000, 12 February 2001, and 6 February 2002. All waves ended in the first week of June. All students were from the Los Angeles area (LA—between latitudes 32° and 35° and longitudes 115.5° and 120.75°) or the San Francisco Bay area (SF—between latitudes 37° and 38.5° and longitudes 121.67° and 123°). (A map that shows locations is available with the online version of this article.) On the basis of sample size calculations, we sought to recruit approximately 200 subjects from LA and 100 from SF.
Students were eligible based on being a lifelong resident of LA or SF before enrollment at UCB, having a history of never smoking, no physical impairment that would hinder performance of spirometry, and no history of chronic respiratory disease. A history of asthma before age 12 years was permitted, provided that student had no symptoms and had not taken any medication at any time after age 12. Six students were in this category. Subjects were studied between February-May, when students from LA would not have been exposed to the high summertime O3 concentrations.
The protocol for this study was approved by the Committee for the Protection of Human Subjects, University of California, Berkeley and the Committee on Human Research, University of California, San Francisco. Written, informed consent was obtained from all subjects, once eligibility was established.
Residential and Health Histories
Lifetime residential history was reconstructed with a standardized questionnaire. To verify all addresses and time periods, subjects and parents received the same questionnaire. We used a standardized questionnaire for subjects and parents to obtain information on birth history, past history of pneumonia and other lower respiratory tract illnesses, allergy history, history of symptoms related to asthma and physician diagnosis of asthma, personal smoking history (tobacco and marijuana), second-hand exposure to tobacco smoke, and family history of chronic respiratory diseases. Discrepancies between subject and parental questionnaires were reconciled.
Height was measured with a wall-mounted stadiometer.29 Weight was measured without shoes with a digital scale. Subjects completed a questionnaire to determine the occurrence of a respiratory illness within the previous 3 weeks and their use of caffeinated beverages within the previous 24 hours. Subjects who had symptoms of a lower respiratory illness at the time of testing were rescheduled after lower respiratory symptoms had abated.
Forced expiratory volume (FEV) measurements were obtained in the sitting position with nose clip, using a Collins Survey rolling seal spirometer. Data were saved directly to a computer (Plus software; Warren E. Collins, Co. Braintree, MA). Two modifications were made to the American Thoracic Society criteria30: because of the young age of the subjects, tests that reached a plateau after 2 seconds in the absence of an abrupt termination were considered acceptable, and reproducibility criteria included peak expiratory flow rates (PEFR) within 10% of the maximum. Tracings were reviewed jointly by 2 investigators (J.B., I.T.). Forced vital capacity (FVC), FEV1, FEF25–75, FEF75 were recorded, and the FEF25–75/FVC ratio was calculated. This ratio estimates the reciprocal of the time constant of the lung31 and reflects intrinsic airway size.32
Geocoding of Residences and Pollutant Data
A geocoding service, TeleAtlas (TeleAtlas, Menlo Park, CA), was used to assign latitude and longitude coordinates to residence locations. Of 543 residences, 94% were geocoded with the highest-quality match, 3% were geocoded to a zip code centroid, and another 3% were geocoded to lesser-quality matches.
We acquired air quality data from the California Air Resources Board (CD No. PTSD-02-017-CD), the Aerometric Information Retrieval System (AIRS), and from special requests to the Air Resources Board. Monthly mean measures of O3 were derived from ambient air quality data that covered the lifetimes of all subjects. Averages were based on data from zip codes that corresponded to street addresses. We report only monthly 10 am to 6 pm average ozone. Monthly 24-hour averages were obtained for NO2 and particles with mass median aerodynamic diameter ≤10 μm (PM10). Measurements for PM10 were not widely available before 1988. For these years, a factor of 0.57 was used to scale total suspected particulates (TSP) to estimate PM10 concentrations (derived for the years 1988–1992 from collocated PM10 and TSP data for California). Particulate matter with a mass median aerodynamic diameter ≤2.5μ (PM2.5) data were not widely available until 1999; therefore, we did not study PM2.5.
Monthly values were interpolated spatially from air quality-monitoring stations to the residence locations with inverse distance weighting and a maximum of 3 monitoring stations for each interpolation (maximum interpolation radius of 50 km). Quality codes were provided for each interpolation.
Creation of Lifetime Residential Histories and Summary of Activity Data
The time period for each residence was defined by a “from” date and a “to” date. The last “to” date represented the time that the student matriculated at UCB. We used population-based estimates of the age-stratum-specific median values for time typically spent out-of-doors by children and adolescents.20,33–35
Assignment of Individual Exposures
The details and reliability of the exposure assignment method have been published.20,35,36 Briefly, we fit 2 basic models to estimate life-time pollutant exposure. The “time-outdoors” model included age-specific estimates of time spent outdoors at each residence obtained from an California Air Resources Board study.33,34 We used an indoor-outdoor O3 ratio of 0.2 in this model. This model was fit only to estimate monthly average lifetime exposure to O3. The “ecological” model omitted estimates of time spent outdoors and used only the residence-specific monthly average, interpolated pollutant concentrations. This model was used to estimate monthly average lifetime exposures to O3, NO2, PM10 prior to 1988, and PM10 concentrations from 1988 onward.
The “effective exposure” for a given residence was calculated as the average value across all monthly values for that residence.
where EXij indicates “effective exposure” for the ith subject at the jth residence20,35; Σ EXijkl indicates the sum of monthly effective exposures; summation over l months; and Dij indicates the duration that the ith subject lived at the jth residence.
The overall, effective lifetime exposure for the ith subject (EXi) was calculated as a weighted average of the residence specific “effective exposures” (EXij).
summed over j residences.
Pulmonary Function Data
To generate the “base” lung function model, we fit sex-specific linear regressions of each lung function measure on age, height, and weight. Model fitting was conducted for each measure (mean of 2 or 3 acceptable/reproducible trials) to determine the optimal model (based on Akaike's Information Criterion). Models included tests of natural log transformations of the function measures and the square of height, as well as evaluation of smooth functions of weight and height. Models with and without smooth functions provided comparable fit; therefore, only models without smoothes were used. In no case did age enter into the models. Model fit was evaluated with residual versus predicted plots and quantile-quantile plots.
Race-ethnicity (White, Asian, other [African-American, Hispanic, and Native American]) was added to each model. There were no consistent effects of this variable. Presence of any respiratory symptoms in the 3 weeks before testing or the use (type and amount) of caffeinated beverages had no association with any measure. There were no associations between any measure of pulmonary function and history of asthma before age 12 years, history of pneumonia, bronchitis, allergic conjunctivitis or rhinitis, or second-hand tobacco smoke exposure. The FEF25–75/FVC ratio was associated with all function measures. It was not retained in the base model as a main effect; rather it was used as a stratification variable (interaction with lifetime exposure to O3) to account for unmeasured differences related to race-ethnicity and to capture the effects of individual variability in intrinsic airway size on any observed effect of lifetime exposure to O3.
Analysis of Effects of Lifetime Exposure on Lung Function
We first added the lifetime estimates of O3 exposure to the base model along with an interaction term with FEF25–75/FVC ratio as single interaction term or as quartiles of the interaction. Inferences were the same for both; therefore, we present results for the single interaction term. Similar regression analyses were conducted for PM10 and NO2.
We added terms for the lifetime exposure to PM10 (separate terms for estimates before 1988 and from 1988 onward) and for NO2. We then added a variable that indicated whether subjects were from LA or SF to account for any exposure and other confounders not otherwise measured. In no case did the region variable meaningfully change the coefficients for lifetime exposure to O3 or the interaction with FEF25–75/FVC.
We made separate corrections for measurement error due to the estimates of PM10 exposure before 1988 based on linear regression with TSP and error in the estimates of lifetime exposure to O3 (Appendix 1, available with the online version of this article). For this latter correction, we used within- and between-subject variance estimates from our published reliability study.36 We could not estimate the joint effects or these sources of error, because we did not have estimates for the variance of the errors between the O3 and the pre-1988 PM10.
We enrolled 255 subjects of whom 58% were women. Approximately, 60% were life-long residents of the LA area (Table 1). Coefficients of variation for FEV1, FEF25–75, FEF75, and FEF25–75/FVC were consistent with our previously published data.37
There were no meaningful differences between men and women with regard to the lifetime exposure estimates for any of the pollutants. Subjects who grew up in the LA area had higher median estimated lifetime exposure to O3, PM10 and NO2 than did subjects from SF (as presented with the online version of this article). Distributions between these regions were overlapping, which resulted in a continuum of individual exposure terms across a broad range of individual estimated exposures.
We estimated the Spearman correlations between the lifetime exposure to O3 (from the ecological model) and PM10 prior to 1988, PM10 from 1988 until enrollment at UCB, and NO2; the correlations were 0.68, 0.81, and 0.57, respectively. Correlations between lifetime O3 from ecological and main models and the mean O3 levels 2, 3, 4, and 30 days prior to the time of lung function testing ranged between –0.03 and 0.01 (data not shown).
There were consistent inverse associations between increasing lifetime exposure to O3 and FEF75 and FEF25–75 for men and women (Table 2). Comparable regressions with lifetime exposure to PM10 and NO2 showed similar results (Table 3). The results indicate that the adverse impact of increased lifetime exposure to O3, PM10 and NO2 are decreased with increasing FEF25–75/FVC ratio. When PM10 (alone or with NO2) was added to the O3 ecological model for FEF75 (Table 4, columns labeled “none”), there was no meaningful change in the regression parameters for either lifetime exposure to O3 or the interaction term. The main effect parameter estimates for PM10 and NO2 were reduced substantially. The addition of FVC to the models, to account for difference in lung volumes, increased the magnitude and precision of the coefficients for O3 and the interaction terms, with little impact on the relative associations with PM10 and NO2 (data not shown). When models were fit without the interaction term, the O3 coefficients for FEF25–75 and FEF75 for men were in the negative direct but weak; for women, the coefficient for FEF25–75 was weakly positive (data not shown).
Figure 1 illustrates the modification of O3 effect by FEF25–75/FVC ratio. Men whose FEF24–75/FVC ratio was in the upper quartile of the male ratio distribution showed no relation between increasing lifetime exposure for O3 and FEF75, whereas those whose ratio was in the lowest quartile showed a progressive percentage decrease in FEF75 with increasing lifetime exposure (Fig. 1A). Similar relationships are shown for women (Fig. 1B). For the 17-ppb difference in lifetime exposure to O3 (difference in median lifetime exposure to O3 for students raised in LA vs. SF), the “no-effect” FEF24–75/FVC ratio is 1.17 for men and 1.04 for women (Fig. 1). For a man whose FEF24–75/FVC ratio is at the 25th percentile (0.783), the estimated effect of this 17 ppb difference is a 15% reduction in FEF75. For a women at the comparable percentile (0.929), the estimated reduction is 3%. Adjustment for the measurement errors due to estimation of PM10 from TSP up to 1988 and those related to the within-subject variation in the estimation of lifetime exposure to ozone did not change the results (Table 4).
There was a suggestion that the estimates based on ages 6 years and older are somewhat larger than those based on ages birth to 6 years; the confidence intervals (CI) for the O3 main effect and interaction terms overlap (eg, among men, the CI for O3 main effect was −0.019 to 0.031 for ages 0–5 and −0.023 to −0.039 for ages 6 and older).
Estimated lifetime exposure to ambient concentrations of ozone in adolescents (ages 18–20 years) is associated with reduced levels of lung function measures that reflect the function of the small airways. We have shown that the ratio of FEF25–75/FVC, a measure that reflects airway size,32 is an important physiological marker for susceptibility to effects of long-term exposure to O3 on lung function in adolescents; failure to include this measure in the analysis resulted in much less consistent results. The observation that FEF25–75/FVC is heritable, and that it is decreased in healthy nonsmoking and smoking first-degree relatives of persons with early-onset chronic obstructive pulmonary disease,38 supports the importance of this ratio as a marker for susceptibility to oxidant environmental exposures.
Although the overall results did not suggest a strong difference in the association between men and women, the level of the FEF25–75/FVC ratio at which “no effect” would be expected was lower for women than for men (1.04 and 1.17, respectively). This observation suggests that men may be more sensitive to the effects of long-term ozone exposure than women. Compared with those in the highest quartile of FEF25–75/FVC, men and women in the lowest quartile had estimated reductions of 38% and 37%, respectively, in their predicted FEF75 (based on medians for each quartile) for comparable estimated lifetime O3 exposures (median 38 ppb/mo). Thus, the results are unclear on this issue.
We have dealt with a number of factors that could have led to spurious associations with lifetime exposures to O3. We restricted the study to subjects who were lifetime never-smokers without history of chronic respiratory diseases. Self-reported race/ethnicity was not associated with measures of lung function, and the use of the FEF25–75/FVC ratio and of FVC controlled for potential differences in race that are related to small airways and lung volume. Second-hand exposure to tobacco smoke also was not associated with any measure of lung function. Inclusion of exposure estimates for PM10 and NO2 did not change the parameter estimates for O3, nor did the inclusion of an indicator variable to control for unmeasured effects due to residence in LA versus SF. Finally, there was no correlation between estimated lifetime exposure to O3 and average ambient O3 concentrations in the 2, 3, 4 and 30 days prior to spirometry, and most of the subjects performed spirometry after having been in Berkeley for several months, during a time when concentrations of O3, PM10 and NO2 are low (average 8-hour maximum ozone = 30 ppb, 24-hour NO2 = 12 ppb, and 24-hour PM10 = 17 μg/m3 in August–October).
We assessed the potential effect of 2 sources of measurement error (use of questionnaire responses to estimate exposure to O3 and estimation of PM10 from TSP prior to 1988). Neither measurement error correction had a meaningful effect on the magnitude of the association with O3 (Table 4). Thus, it seems unlikely that measurement error contributed substantially to the associations that we observed for O3.
We cannot state with certainty that O3 alone is responsible for the associations observed. However, in California, the O3 and PM2.5 seasons (the latter a result largely of combustion sources) do not overlap to any great extent,39,40 in contrast to the considerable overlap on the eastern part of the United States.41 Associations between PM2.5 and lung function have been observed in short-term exposure studies,10–14 but few data are available for the long-term exposures noted here. In contrast to PM2.5, the coarse PM (PM10-2.5) does overlap with the end of the O3 season in California.42 PM10-2.5 contains small amounts of material from combustion sources but, more importantly, it is a source of iron, a transition metal that participates in the generation of reactive oxygen species43 and endotoxin.44 The latter are potent stimulators of inflammation in the lung.45 Finally, in California, NO2 levels tend to increase towards the end of the O3 season. Although NO2, has not been associated with changes in lung function, NO2 is an oxidant with pulmonary deposition similar to that of O3.46 However, controlled exposure studies in humans suggest that NO2 may not be as toxic as O3, as measured by depletion of antioxidant activity and increases in inflammatory markers in respiratory tract lining fluid.47–49 Thus, our data are best interpreted as an expression of the oxidant environments to which the subjects were exposed over their lifetimes, as well as to effects specific to the oxidant properties of O3 itself.
That our data do reflect, at least in part, some effects that are specific to O3 relates also to the functional abnormalities observed. Primate models of cyclical, chronic exposures to O323–25 have established clearly that airway remodeling occurs at the level of the respiratory bronchiole as a consequence of these exposures. Controlled O3-exposure studies in humans suggest that a similar process could be occurring.28 Based on pathologic correlations with measures of lung function in humans,50 we expect that measures such as FEF75 (and to a lesser extent FEF25–75), which primarily reflect the function of small airways (<2 mm in diameter),51 would show the most consistent associations with lifetime exposure, as is the case with our data; this argument is strengthened further by the importance of the interaction between lifetime exposure and the FEF25–75/FVC ratio, which is a more direct surrogate for intrinsic airway size.31,32
Our observation on the similarity of the estimated exposure associations from birth through age 5 years and after the first 6 years of life suggest that the observed effects may have been driven by exposures very early in life. However, the correlations between exposures during these 2 age periods (range, 0.88–0.92 for ecological models) limit the certainty around this inference. Evidence does suggest that abnormalities of small airways are associated with early life exposures, such as in utero tobacco smoke exposure;52 and these abnormalities appear to persist into childhood.53 Levels of ambient air pollution have been associated with adverse birth outcomes that are similar to those observed for women who smoke, ie, low-birth-weight, small-for-gestational-age infants.54 Because ambient air pollution, such as cigarette smoke, is a potent inducer of oxidative stress,55 it is reasonable to expect that events very early in development and infancy could have lasting effect on lung function. The consequent reduction in the size of small airways of such exposures is thought to be related, in part, to increased risk of wheezing in childhood and to the association between second-hand smoke exposure and asthma in children.56 Thus, reduced small airway size, as reflected by the FEF25–75/FVC ratio may also be a marker of sensitivity to oxidant damage early in life and a risk marker for altered lung function during periods of growth and development.
We cannot account fully for the differences between the implications of our study and the failure of several longitudinal studies to observe decreases in lung growth related to O3 exposure.22,57 The studies differ substantially in design, methods of exposure assignment, and populations studied and, in the case of the Austrian studies,21,57 in pollutant environments. The failure of these studies to consider the FEF25–75/FVC ratio as a marker of susceptibility also could account for some of the differences.
In summary, we have observed an association between long-term exposure to ambient ozone in adolescents who have lived all of their lives in 1 of 2 regions of California and decreased measures of small airways function. The associations are independent of any effects related to PM and NO2. Our data further suggest that the associations observed may have their origins in early life and that underlying abnormality of small airways is a physiological marker for sensitivity to strongly oxidant environments.
We thank Lucas Carlton, Sarah Deamer, Jessie Murphy, and Dhara Thakar for the recruitment of the subjects and the collection of the data and Huaxia Qin for programming assistance. We thank Lincoln Diagnostics, Decatur, IL for the donation of the skin testing kits.
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