The purpose of this research was to investigate the potential relationship between annual estimates of ambient concentrations of fine particulate matter (as reported by USEPA Airdata) and the prevalence of self-reported respiratory conditions from adult respondents 18 years of age and older from the NHIS. Analyses using the general study population did not find associations between increases in fine particulate matter and self-reported current asthma status or recent asthma attacks, though recent report of sinusitis was found to be significantly associated with increases in ambient PM2.5 concentrations. Stratified analyses performed as part of this research suggests that, in non-Hispanic black persons, especially those living in urban areas, asthma-related morbidity is associated with higher concentrations of fine particulate matter averaged over a year.
It is difficult to determine whether the observed differences across racial/ethnic strata are due to difficulties in classification of exposures and outcomes, physiologic variations across race/ethnicity in response to particulate matter, other confounding factors that were uncontrollable in the present study, or a combination of these. Even with the ability of the NHIS to account for a variety of pertinent covariates, many of these influential factors were only able to be addressed at a crude level in the current study.
It is unavoidable that use of ambient monitoring data to characterize exposure to air pollution and self-reported morbidity data will result in measurement error that introduces uncertainties into the interpretation of findings. Data from ambient monitors are not an ideal surrogate for personal exposure measurements, as ambient air is only useful in prediction of air quality in some microenvironments. Despite this shortcoming, relative differences in ambient exposures across persons may be informative for comparisons with health outcomes. Further, ambient concentrations of PM have been found to be highly correlated to personal exposures to ambient-generated PM [57
]. Consequently, residence-based non-ambient generated sources of PM (such as environmental tobacco smoke and cooking) and occupational sources (such as diesel exhaust) that we were unable to account for in this study are likely to result in non-differential misclassifications of total personal exposure to PM, ultimately biasing associations towards the null. Further, use of annual average PM2.5
concentrations may mask important shorter-term variations in true exposure profiles relevant to respiratory morbidity. While USEPA PM2.5
data are available at finer temporal resolution, the temporal nature and frequency of collection of outcome data from NHIS precluded evaluation of potential relationships at a finer temporal scale.
Our sensitivity analyses by urbanicity were suggestive of different effects across locations, but were not definitive. Fine particulate matter is a heterogeneous mixture that tends to vary in constituency over time and across space [58
]. Given the nature of the exposure and outcome measurements used in this study, the ability to evaluate the influence of temporal changes in (or seasonality of) PM2.5
species was limited. It has been shown in a variety of locales that the composition of fine particulate matter varies between urban and rural settings [52
], potentially as a function of particulate sources [59
]. The composition of fine particulate matter in urban settings has been shown to be higher in elemental carbon (EC) content [54
], an indicator of diesel exhaust [60
] that has been shown to adversely influence indicators of respiratory capacity in the general population [61
] and in asthmatics [62
]. Variability in particulate composition across these settings, especially of constituents known to exacerbate asthma, may help explain our finding of stronger relationships between PM2.5
exposure and reporting asthma outcomes in urban settings. There is also suggestive evidence that urban residence, independent of race and income, predicts asthma morbidity [63
The outcomes data used in this assessment also require careful consideration. Self-reported health prevalence data are subject to information biases that may be differential across a variety of factors. Interpretation of these data as prevalence of health outcomes is complicated by the fact that some survey questions query whether a health professional has informed the respondent that he or she has the outcome of interest. Such a query inherently makes assumptions about the respondent's resources to acquire health care that may be faulty and ultimately lead to an underreporting of health outcomes. Further, diagnosis-related difficulties for asthma stemming from the lack of a definitive clinical test and issues with consistency across health practitioners to non-specific case definitions may result in inaccurate identification of cases [19
]. Beyond diagnosis-related issues are concerns related to specificity of the outcomes. In particular, the asthma attack query requires subjective judgment. Is an exacerbation of symptoms that is quickly remedied by use of asthma medication considered to be an attack? Or is there some symptomatic severity threshold that constitutes an asthma attack? Misclassification of outcomes may introduce bias into the assessment of association, though the direction of the bias (if any) is difficult to predict.
Given the dependence of the outcomes on physician diagnoses, analyses were performed to determine model sensitivity to stratification by health insurance type; these analyses found stratum-specific effect estimate magnitudes to be stable for both asthma outcomes.
Racial disparities in asthma-related hospitalization and mortality among children have been repeatedly identified in the literature [66
], though far fewer evaluations of potential disparities among adults have been published. An analysis of NHIS asthma prevalence data from 1980 to 2004 reported varying disparities in asthma prevalence between blacks and whites by age group, with a five percent difference in children and less than a single percent difference in adults [19
]. Hasselkorn et al. (2008) [67
] found that, as compared to whites, an increase in asthma control problems among black persons persisted after controlling for factors related to demographics, asthma severity and co-morbidities. Few studies of gene associations have been performed among persons of African ancestry [68
], though existing research has suggested variability in genetic pathogenesis of asthma across racial/ethnic groups [22
]. However, in a review of racial disparities in asthma prevalence, Wright and Subramanian (2007) argued that the simultaneously growing disparities and increases in asthma prevalence and severity over the past twenty to thirty years are evidence against this variability being the most important factor in asthma pathogenesis, suggesting that genetic shifts capable of these observed differences would be unlikely in such a short time period. Instead, the authors argue that gene-environment interactions are likely strong factors in the observed changes in asthma burden [69
]; accordingly, an underlying genetic susceptibility to asthma development may help explain observed differences that were not able to be explained solely by variations in exposures to environmental pollution. Race/ethnic differences in distributions of atopy have been observed [70
], and climate-related factors specific to geographic areas have been demonstrated to interact with exposure to air pollution in prediction of asthma and allergic rhinitis [71
], suggesting the possible cumulative contribution of allergy and regional climate variation to the observed differences. This assertion may provide support for our finding of increased susceptibility of non-Hispanic black respondents to asthma-related outcomes as a result of higher exposures to PM2.5
One limitation of this study is its lack of ability to draw inferences regarding the relationship between PM exposure and asthma outcomes in Hispanic persons. Research has shown that the Hispanic race/ethnicity group is comprised of persons of varied backgrounds, and that rates of asthma within these subgroups are highly inconsistent [72
]. The collapsing of these multiple subgroups with different rates of asthma into a single race/ethnic stratum is likely to obscure our ability to capture any potential effect of PM on the studied outcomes.
In addition to PM, nitrogen dioxide, ozone, and sulfur dioxide are criteria pollutants that have also been demonstrated to have an effect on asthmatics [74
]. The robustness of the USEPA AQS PM2.5
monitoring network and the spatially homogenous nature of particulate matter made possible the kriging of annual concentrations to allow for exposure estimations for participants with residences further away from monitored locations. However, the characteristics of the AQS monitoring network size and data collection schedule, as well as the spatial representativeness of monitored concentrations of these other pollutants precluded their estimation at respondent locations and subsequent inclusion as covariates in our models. Similarly, some non-criteria hazardous air pollutants have also been suspected to be influential in the development and exacerbation of asthma [76
], but monitoring networks for these toxics are typically more limited than those for criteria pollutants and may not support prediction of exposure for NHIS respondents. It is not possible to predict the influence of the exclusion of these pollutants from our investigation; future study is warranted to delineate the potential joint contributions of ambient air contaminants.
The social environment has been demonstrated to be an influential factor in the exacerbation of asthma and severity of asthma attacks [77
], and evidence in adolescents and young adults exists to suggest that stress may alter or induce asthma-related immune response [78
]. Recent literature has identified the potential for interaction between environmental and social stressors in causing morbidity [81
]. Chen et al. (2008) [83
] evaluated the interaction between exposures to traffic-related air pollution and chronic family stress in exacerbation of asthma, and found that in children exposed to relatively lower levels of air pollution, high levels of chronic family stress increased child- and parent-reported asthma symptoms and reduced clinical measures of respiratory capacity. More recently, researchers have used genomic methods to determine that genes relevant to asthma-related inflammatory mechanisms were overexpressed in children of lower socioeconomic standing [84
]. Measures of these factors were unavailable in the NHIS, though an attempt was made to account for this through adjustment for urbanicity, education and poverty ratio. Despite this, it is likely that the effect estimates are influenced by residual confounding and are likely attenuated.