Rationale: Although elevated air pollution exposure impairs lung-function development in childhood, it remains a challenge to use this information to estimate the potential public health benefits of air pollution interventions in exposed populations. Objectives: Apply G-computation to estimate hypothetical effects of several realistic scenarios for future air pollution reductions on lung growth. Methods: Mixed-effects linear regression was used to estimate FEV1 and FVC from age 11 to 15 years in 2,120 adolescents across 3 cohorts (1993-2001, 1997-2004, and 2007-2011). Models included regional pollutants (nitrogen dioxide [NO2] or particulate matter with an aerodynamic diameter ≤2.5 μm [PM2.5]) and other important covariates. Using G-computation, a causal inference-based method, we then estimated changes in mean lung growth in our population for hypothetical interventions on either NO2 or PM2.5. Confidence intervals (CIs) were computed by bootstrapping (N = 1,000).Measurements and Main Results: Compared with the effects of exposure from observed NO2 concentrations during the study period, had communities remained at 1994 to 1997 NO2 levels, FEV1 and FVC growth were estimated to have been reduced by 2.7% (95% CI, -3.6 to -1.8) and 4.2% (95% CI, -5.2 to -3.4), respectively. If NO2 concentrations had been reduced by 30%, we estimated a 4.4% increase in FEV1 growth (95% CI, 2.8-5.9) and a 7.1% increase in FVC growth (95% CI, 5.7-8.6). Comparable results were observed for PM2.5 interventions.Conclusions: We estimated that substantial increases in lung function would occur as a result of interventions that reduce NO2 or PM2.5 concentrations. These findings provide a quantification of potential health benefits of air quality improvement.
Rationale: Although elevated air pollution exposure impairs lung-function development in childhood, it remains a challenge to use this information to estimate the potential public health benefits of air pollution interventions in exposed populations. Objectives: Apply G-computation to estimate hypothetical effects of several realistic scenarios for future air pollution reductions on lung growth. Methods: Mixed-effects linear regression was used to estimate FEV1 and FVC from age 11 to 15 years in 2,120 adolescents across 3 cohorts (1993-2001, 1997-2004, and 2007-2011). Models included regional pollutants (nitrogen dioxide [NO2] or particulate matter with an aerodynamic diameter ≤2.5 μm [PM2.5]) and other important covariates. Using G-computation, a causal inference-based method, we then estimated changes in mean lung growth in our population for hypothetical interventions on either NO2 or PM2.5. Confidence intervals (CIs) were computed by bootstrapping (N = 1,000).Measurements and Main Results: Compared with the effects of exposure from observed NO2 concentrations during the study period, had communities remained at 1994 to 1997 NO2 levels, FEV1 and FVC growth were estimated to have been reduced by 2.7% (95% CI, -3.6 to -1.8) and 4.2% (95% CI, -5.2 to -3.4), respectively. If NO2 concentrations had been reduced by 30%, we estimated a 4.4% increase in FEV1 growth (95% CI, 2.8-5.9) and a 7.1% increase in FVC growth (95% CI, 5.7-8.6). Comparable results were observed for PM2.5 interventions.Conclusions: We estimated that substantial increases in lung function would occur as a result of interventions that reduce NO2 or PM2.5 concentrations. These findings provide a quantification of potential health benefits of air quality improvement.
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Keywords:
air pollution; children; lung function; nitrogen dioxide; particulate matter
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