diabetes risk: The adjusted HR (95% CI) for an increase in C3c by 10 mg/dL was 1.12 (1.05–1.18) (p < 0.001). In exploratory analyses, we subdivided the study population according to their median C3c serum level at baseline and repeated the calculation of adjusted HRs and 95% CIs for incident type 2 diabetes (from Table 3) in both subgroups with low and high C3c at baseline (n = 617 and n = 634, respectively; Table 4). For most exposure variables, we found evidence for interaction between C3c at baseline and risk for type 2 diabetes. Stratified analyses showed that an elevated risk for type 2 diabetes was present only for women with high C3c at baseline, whereas for women with low C3c at baseline, no association between exposure to ambient air pollution and inci- dent type 2 diabetes could be revealed. Discussion To the best of our knowledge, this is the first prospective, population-based study that showed a statistically significant association between traffic-related air pollution and inci- dent type 2 diabetes. This association persisted when four different spatial scales were used to assess exposure levels and remained robust after adjustment for confounders including BMI, socioeconomic status, and exposure to several indoor sources of air pollution. Currently, data on air pollution and type 2 diabetes risk are scarce. The first evi- dence came from an ecological study that found a significant relationship between total state air emissions for all industries and prevalence of diabetes in the United States (Lockwood 2002). More recently, a cross- sectional study in Canada suggested a posi- tive association between NO2 exposure as a marker of traffic-related air pollution and type 2 diabetes among women (Brook et al. 2008). This study reported an increase in the adjusted odds of diabetes by nearly 17% for an increase in NO2 of 1 IQR, which is in line with our findings (adjusted HR: 1.15–1.42, depending on NO2 assessment). Furthermore, an experimental study in mice showed that fine PM in the air (PM2.5) induced insulin resistance, increased adi- pose tissue macrophages, altered the balance between macrophage subtypes in adipose tis- sue, and raised systemic levels of immune mediators that have previously been impli- cated in the development of type 2 diabetes (Sun et al. 2009). More evidence for such an association among humans comes from a recent population-based cross-sectional study of 10- to 18-year-old children in Isfahan, Iran (Kelishadi et al. 2009). The city of Isfahan currently faces a huge increase in air pollution from rapid industrial development and heavy traffic of motor vehicles. Air pol- lution (PM10, carbon monoxide, pollutant standard index) was independently associ- ated with insulin resistance (homoeostasis model assessment model), a hallmark of type 2 diabetes, and low-grade inflammation in children and young adults, even after adjust- ing for BMI, waist circumference, dietary intake, and physical activity (Kelishadi et al. 2009). Collectively, these data suggest that air pollutants may increase the risk of type 2 diabetes by impairing insulin sensitivity and point toward inflammatory processes as a mechanistic link. C3c may play a role in the development of air pollution–related insulin resistance and type 2 diabetes, because epithelial cells and macrophages at the airway surface produce multiple components of the complement sys- tem that exert a central role in innate immu- nity (Cole et al. 1983; Strunk et al. 1988). Airway exposure to PM activates C3 in mice (Walters et al. 2002), and C3c is a stable cleavage product of C3 that can be used as an indicator of the activation of the innate immunity. C3 is of interest for two reasons. First, we and others previously demonstrated higher C3c levels in inhabitants of areas with a higher degree of air pollution (Shima et al. 1999; Stiller-Winkler et al. 1989), which is in accordance with data from murine models (Walters et al. 2002). Second, elevated C3 levels were associated with incident type 2 diabetes in our study population, which con- firms results from a population-based cohort study in Sweden (Engström et al. 2005). It is biologically plausible that air pollution acti- vates the innate immunity in the lung and that this immune activation then spreads to other parts of the body and becomes appar- ent in chronically elevated levels of pro- inflammatory biomarkers in the circulation that have a negative impact on insulin sen- sitivity and beta-cell function. However, it should be noted that C3c represents only one of many activities of the immune system. Measurement of additional inflammatory markers would be necessary to substantiate this hypothesis. In addition to being part of the causal pathway between air pollution and insulin resistance or type 2 diabetes, it is also conceiv- able that a chronic activation of the immune system increases the susceptibility of indi- viduals to air pollution. Our data are in line with this latter interpretation. It has been reported before that individuals with insulin resistance or type 2 diabetes, both of which are proinflammatory conditions, are more vulnerable to ambient PM exposure and show stronger associations between exposure and cardiovascular risk factors such as reduced heart rate variability and impaired vascular reactivity (O’Neill et al. 2005; Whitsel et al. 2009). This interpretation, which considers C3c (and subclinical inflammation in general) Environmental Health Perspectives • volume 118 | number 9 | September 2010 Air pollution and type 2 diabetes as effect modifier rather than a mechanistic factor downstream of particle exposure, raises the question of which other factors are deter- minants of immune activation. Our study was not designed to answer this question, but we hypothesize that many variables, includ- ing genetic predisposition, lifestyle compo- nents, and presence of inflammation-related subclinical comorbidities like atherosclero- sis or nonalcoholic fatty liver disease, could be relevant contributors. Even if we cannot disentangle the relationship between air pol- lution, inflammation, and risk for type 2 dia- betes, our findings appear intriguing, because they indicate the presence of subgroups in the population that are more or less vulnerable to the impact of air pollution. Therefore, our results may stimulate further research to better understand the interaction of inflammation and air pollution for the incidence of adverse health outcomes and for the identification of at-risk individuals. We found slightly stronger associations with NO2 exposure than with PM-related exposure assessments. The main sources of NO2 are traffic related, whereas PM may also stem from industrial sources. Therefore, stron- ger associations with NO2 strengthen our view that traffic-related pollution is respon- sible for associations with incident diabetes. Our study has several strengths that should be mentioned briefly. The association between traffic-related air pollution and inci- dent type 2 diabetes was present when we used different indicators of traffic-related air pollu- tion and different spatial scales. Moreover, the availability of relevant non–traffic-related indicators of air pollution allowed us to adjust for potentially confounding effects. The main limitation of the study is the fact that type 2 diabetes was assessed by self- report only. The reliability of these reports, however, was high. An interview conducted 2 years after the questionnaire follow-up in 2006 showed 99% concordance. We also did not have glucose measurements. This may have led to outcome misclassification (under- diagnosis), but this is most likely unrelated to exposure. In theory, this misclassification might be related to exposure, for example, if women with cardiovascular diseases due to air pollution visited their physician more often and then had a diagnosis of diabetes. If this were true, we would expect stronger associations of pollution with cardiovascu- lar outcomes than with diabetes, which was not the case. In our study, the association of pollution with incident diabetes was much stronger than the association with myocardial infarction, stroke, or hypertension. The adjusted association of physician-diagnosed hypertension with NO2, for instance, was 1.09 (95% CI, 0.93–1.27) compared with 1.49 for physician-diagnosed diabetes (data 1277