We demonstrate a strong association between PM2.5 exposure and diabetes prevalence, suggesting that ambient air pollution may contribute to the increased prevalence of diabetes in the adult U.S. population. Advances in both data collection and statistical techniques (20
) permitted this first large-scale population-based analysis of the relationship between PM2.5 and diabetes prevalence. Our findings are consistent with the few studies of geographically small areas that have also suggested a relationship between diabetes and air pollution from either road traffic or industrial facilities (21
). Our results are also consistent with previous evidence from animal models (9
). A growing body of epidemiological and laboratory-based literature connects air pollution, particularly PM2.5, and deterioration of cardiovascular health (2
). Therefore, although unique by scope, our study is not without precedent.
Chronic inflammation has been suggested to be a mechanism promoting increased insulin resistance in mice with diet-induced obesity after increased PM2.5 exposure (9
). Sun et al. (9
) demonstrated that whole-body glucose homeostasis was reduced with PM2.5 exposure, whereas proinflammatory M1 adipose tissue macrophage activity was upregulated and anti-inflammatory M2 adipose tissue macrophage activity was suppressed. Furthermore, pollutants promote catabolic inflammatory action while inhibiting anabolic responses to insulin (24
). In contrast, lean mice show little change in insulin sensitivity or lipid profile in response to PM2.5 exposure (9
). Thus, increasing exposure to ambient air pollution in Westernized countries may be particularly problematic in the setting of the obesity epidemic. Similarly, O'Neill et al. (4
) found that obese diabetic patients demonstrated a greater inflammatory response than nonobese diabetic patients upon exposure to pollutants. Taken together, these studies suggest that obesity may play a critical permissive role in priming the body for pollution-induced inflammation and disordered metabolism. Although our study cannot provide additional insights on mechanisms underlying the association or confirm causality, we clearly demonstrated a strong relationship between PM2.5 exposure and diabetes prevalence within our modeled dataset similar to that in other studies (4
Throughout our multiple datasets and models, we find a consistent and significant association between ambient air pollution PM2.5 and diabetes prevalence. Additions of behavioral, ethnic, and socioeconomic covariates only modestly alter the magnitude of the impact of PM2.5 on diabetes prevalence. In addition, removal of highly polluted regions with high diabetes prevalence did not alter the relationship in a significant manner.
Although we found that increased PM2.5 was associated with increased diabetes prevalence, our design does not allow us to conclude whether this is a causal relationship. Ecological studies assume that characteristics of a study group within a certain area represent characteristics of the entire population for that area. A potential ecological bias would be most prominent within our study for diabetes, socioeconomic, and assessed behavioral risk factor covariates because they are based on aggregate survey datasets. It is challenging to exclude potential confounding introduced earlier in time, including diabetic or pre-diabetic individuals selecting residence in relatively more polluted neighborhoods. It is also possible that the best institutions for diabetes care may be located in areas of high pollution. Additional studies are warranted to further elucidate this relationship. Importantly, the study assesses 2 years independently for confirmation, yet we are not able to draw any conclusions regarding effects of sustained pollution exposure over time or of prior exposure on incident disease. This will be possible only when data have been available over several years, permitting time-lag analysis.
Our studies only capture diagnosed cases of diabetes; 2007 estimates suggest that there were 6.3 million adults in the U.S. with undiagnosed diabetes (1
). In addition, our data do not distinguish between types 1 and 2 diabetes. However, type 2 diabetes accounts for >90–95% of all cases of diagnosed diabetes in U.S. adults (1
EPA air quality reference data report the worst air quality monitor in each county. To overcome potential biases inherent in such a measurement we repeated analyses using both the worst air quality monitor in each county and the average of the annual means of all monitors in each county, with similar findings. In the EPA-modeled datasets (36-km and 12-km), some error could be introduced from the geospatial interpolation of the two datasets within ArcGIS. In addition, we could not verify the uniform distribution of pollution across our study areas because we were limited by the resolution of the EPA datasets and the placement of ground monitors.
As noted earlier, we used 2005 health insurance estimates for the 2004 analysis because reliable county-level health insurance estimates for 2004 were unavailable. Furthermore, we used 2000 Census data for 2004 and 2005 primary analyses to expand our sample size, as 2004 and 2005 covariate data were not available for all counties, whereas the 2000 Census provided covariate data for all counties. Thus, we assumed that the socioeconomic and demographic profile of the U.S. did not change dramatically between 2000 and 2004 and between 2000 and 2005. These were years of relative economic stability in the U.S. However, repeat analysis with the more limited datasets for the same year did not alter conclusions.
Although this article focuses specifically on the relationship between PM2.5 and diabetes, other pollutants not mentioned here have been reported to share a similar relationship with insulin resistance and diabetes prevalence (21
). Brook et al. (21
) previously observed a relationship between NO2
exposure and diabetes among patients with respiratory disease in two Canadian cities. It is possible that our analysis has omitted variable bias and that other copollutants account in part for the relationship between PM2.5 and diabetes.
In this study, we demonstrate an increase in diabetes risk even among areas that are below the EPA legal limits for PM2.5. Populations living in areas that are near, but still below, the EPA limits show a >20% higher diabetes prevalence compared with those in cleaner areas. Although EPA limits have resulted in reduced exposure to PM2.5, workers who commute experience highway levels of PM2.5, that often exceed locally measured values (22
). Although outside the scope of our study, increasing commutes for U.S. workers may contribute to chronic disease through increased pollutant exposure, in addition to increased sedentary time, and reduced time for physical activity (21
). Outside the U.S., the risk may be far greater as air pollution limits are often not enforced or are nonexistent, with some countries, notably in Asia and Latin America, showing PM2.5 levels >10 times higher than the U.S. EPA limits (25
Our results, although associative, demonstrate that additional research is needed to understand the role that PM2.5 plays in the inflammatory pathway or other pollution-mediated mechanisms giving rise to diabetes. Such research could lead to novel therapeutic approaches to reduce pollution-induced inflammation. Preventative measures should be considered to reduce exposure to PM2.5 from those at highest risk. Furthermore, evidence based on this study and others suggests that current limits on particulate matter exposure may not adequately mitigate the public health consequences.