Background: There is limited knowledge about the extent to which estimates of air pollution effects on health are affected by the choice for a specific exposure model.

Objectives: We aimed to evaluate the correlation between long-term air pollution exposure estimates using two commonly used exposure modeling techniques [dispersion and land use regression (LUR) models] and, in addition, to compare the estimates of the association between long-term exposure to air pollution and lung function in children using these exposure modeling techniques.

Methods: We used data of 1,058 participants of a Dutch birth cohort study with measured forced expiratory volume in 1 sec (FEV₁), forced vital capacity (FVC), and peak expiratory flow (PEF) measurements at 8 years of age. For each child, annual average outdoor air pollution exposure [nitrogen dioxide (NO₂), mass concentration of particulate matter with diameters ≤ 2.5 and ≤ 10 μm (PM_2.5, PM₁₀), and PM_2.5 soot] was estimated for the current addresses of the participants by a dispersion and a LUR model. Associations between exposures to air pollution and lung function parameters were estimated using linear regression analysis with confounder adjustment.

Results: Correlations between LUR- and dispersion-modeled pollution concentrations were high for NO₂, PM_2.5, and PM_2.5 soot ( R = 0.86–0.90) but low for PM₁₀ ( R = 0.57). Associations with lung function were similar for air pollutant exposures estimated using LUR and dispersion modeling, except for associations of PM_2.5 with FEV₁ and FVC, which were stronger but less precise for exposures based on LUR compared with dispersion model.

Conclusions: Predictions from LUR and dispersion models correlated very well for PM_2.5, NO₂, and PM_2.5 soot but not for PM₁₀. Health effect estimates did not depend on the type of model used to estimate exposure in a population of Dutch children.

Citation: Wang M, Gehring U, Hoek G, Keuken M, Jonkers S, Beelen R, Eeftens M, Postma DS, Brunekreef B. 2015. Air pollution and lung function in Dutch children: a comparison of exposure estimates and associations based on land use regression and dispersion exposure modeling approaches. Environ Health Perspect 123:847–851;  http://dx.doi.org/10.1289/ehp.1408541

Address correspondence to M. Wang, Institute for Risk Assessment Sciences, Division of Environmental Epidemiology, Utrecht University, P.O. Box 80178 3508 TD Utrecht, the Netherlands. Telephone: 31 (0)6 16697117. E-mail: M.Wang@uu.nl

The research leading to these results has received funding from the European Community’s Seventh Framework Program (FP7/2007–2011): ESCAPE (European Study of Cohorts for Air Pollution Effects; grant agreement no. 211250). The PIAMA (Prevention and Incidence of Asthma and Mite Allergy) study is supported by the Netherlands Organization for Health Research and Development; the Netherlands Organization for Scientific Research; the Netherlands Asthma Fund; the Netherlands Ministry of Spatial Planning, Housing, and the Environment; and the Netherlands Ministry of Health, Welfare, and Sport.

The authors declare they have no actual or potential competing financial interests.

Received: 10 April 2014 Accepted: 31 March 2015 Advance Publication: 3 April 2015 Final Publication: 1 August 2015

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