Personal and ambient air pollution exposures and lung function decrements in children with asthma

Abstract

Background: Epidemiologic studies have shown associations between asthma outcomes and outdoor air pollutants such as nitrogen dioxide and particulate matter mass < 2.5 microm in diameter (PM(2.5)). Independent effects of specific pollutants have been difficult to detect because most studies have relied on highly correlated central-site measurements.

Objectives: This study was designed to evaluate the relationship of daily changes in percent-predicted forced expiratory volume in 1 sec (FEV(1)) with personal and ambient air pollutant exposures.

Methods: For 10 days each, we followed 53 subjects with asthma who were 9-18 years of age and living in the Los Angeles, California, air basin. Subjects self-administered home spirometry in themorning, afternoon, and evening. We measured personal hourly PM(2.5) mass, 24-hr PM(2.5) elemental and organic carbon (EC-OC), and 24-hr NO(2), and the same 24-hr average outdoor central-site(ambient) exposures. We analyzed data with transitional mixed models controlling for personal temperature and humidity, and as-needed beta(2)-agonist inhaler use.

Results: FEV(1) decrements were significantly associated with increasing hourly peak and daily average personal PM(2.5), but not ambient PM(2.5). Personal NO(2) was also inversely associated with FEV(1). Ambient NO(2) was more weakly associated. We found stronger associations among 37 subjects not taking controller bronchodilators as follows: Personal EC-OC was inversely associated with morning FEV(1); for an interquartile increase of 71 microg/m(3) 1-hr maximum personal PM(2.5), overall percent-predicted FEV(1) decreased by 1.32% [95% confidence interval (CI), -2.00 to -0.65%]; and for an interquartile increase of 16.8 ppb 2-day average personal NO(2), overall percent-predicted FEV(1) decreased by 2.45% (95% CI, -3.57 to -1.33%). Associations of both personal PM(2.5) and NO(2) with FEV(1) remained when co-regressed, and both confounded ambient NO(2).

Conclusions: Independent pollutant associations with lung function might be missed using ambient data alone. Different sets of causal components are suggested by independence of FEV(1) associations with personal PM(2.5) mass from associations with personal NO(2).

Keywords: asthma; epidemiology; forced expiratory flow rates; longitudinal data analysis; nitrogen dioxide; panel study; particulate air pollution.

Figure 1

Hourly average concentration of personal PM_2.5 across 51 subjects for all days, weekdays, and weekends.

Figure 2

Adjusted single- and two-pollutant models (coefficient and 95% CIs) for change in FEV₁ in relation to personal 1-hr maximum PM_2.5 the last 24 hr, and 2-day average NO₂ measurements. Expected change in FEV₁ corresponds to an IQR change in the air pollutant (Table 2), and estimates are plotted by open symbols for single-pollutant models and solid symbols for models adjusting for the indicated co-pollutant. Single-pollutant models are for the subset of nonmissing observations for the other co-pollutant, and thus exclude two subjects who did not have personal PM_2.5 data.

Figure 3

Adjusted single- and two-pollutant models (coefficient and 95% CIs) for change in FEV₁ in relation to lag day 0 personal 24-hr average NO₂ (pNO₂) or PM_2.5 (pPM_2.5), with ambient 24-hr average NO₂ (aNO₂). Expected change in FEV₁ corresponds to an IQR change in the air pollutant (Table 2), and estimates are plotted by open symbols for single-pollutant models and solid symbols for models adjusting for the indicated co-pollutant. Single-pollutant models are for the subset of nonmissing observations for the other co-pollutant in 51 subjects with pPM_2.5 data.

Figure 4

Estimated lag effect of hourly personal PM_2.5 on FEV₁ in the full cohort of 51 subjects. (A) Not adjusted for maneuver; (B) adjusted for maneuver. Estimates are based on a 5th-degree linear mixed-effects polynomial distributed lag model with AR(1) correlation structure. Expected change in FEV₁ for each hour corresponds to an IQR change (21.6 μg/m³) in 24-hr average PM_2.5 and estimates are plotted by solid circles. Pointwise 95% CIs are plotted by error bars. All estimates are adjusted for the previous FEV₁ measurement, personal temperature, personal relative humidity, cumulative inhaler use on the previous day, and inhaler use during the last night, and excluding observations where there was use of inhaled as-needed bronchodilators in the preceding 4 hr.

Figure 5

Estimated lag effect of hourly personal PM_2.5 on FEV₁ by session period in 37 subjects with no controller bronchodilator use. (A) morning; (B) afternoon; and (C) evening. Estimates are based on a 5th-degree linear mixed-effects polynomial distributed lag model with AR(1) correlation structure. Expected change in FEV₁ for each hour corresponds to an IQR change (21.6 μg/m³) in 24-hr average PM_2.5, and estimates are plotted by solid circles. Pointwise 95% CIs are plotted by error bars. All estimates are adjusted for the previous FEV₁ measurement, personal temperature, personal relative humidity, cumulative inhaler use on the previous day, and inhaler use during the last night, and excluding observations where there was use of inhaled as-needed bronchodilators in the preceding 4 hr.