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Outdoor Environment and Pediatric Asthma: An Update on the Evidence from North America.

1. Introduction

A scientific and political discourse on climate change and its impact on human health has captured substantial attention during the past decade [1-10]. In the United States, a chief driver behind the contemporary interest in climate change and human health is arguably the formal reports issued from The White House and federal agencies (e.g., National Institutes of Health, Environmental Protection Agency) [11-13]. These reports raise an alarm to increasing ground-level ozone levels, increasing pollution such as particulate matter (PM), carbon monoxide (CO), nitrogen dioxide (N[O.sub.2]) through wildfires, extreme heat events, and higher aeroallergen concentrations, all of which may impact the health of at-risk populations, especially children suffering from asthma, respiratory allergies, and airway disease [12]. Academia and medical societies have also contributed to the ongoing discussion by outlining the threats of climate change on respiratory diseases and related illness, specifically highlighting the burden on children [14,15].

Much of the concern on climate change is about the influence of a changing outdoor environment in relation to children living with asthma and respiratory diseases. Asthma, compounded with the common comorbid condition of allergic rhinitis, is one of the most prevalent chronic diseases among children worldwide [16,17]. Children have immature lungs and airways which are more susceptible to inflammation than their adult counterparts; children between 6 and 18 years, as compared with adults, are at high risk for emergency hospitalization for asthma [18]. Asthma continues to pose a substantial burden to child and adult health, with approximately 9.6% of children in the United States living with the disease [19,20]. Asthma appears to disproportionately affect children from minority and impoverished communities [19, 21]. A review of the scientific literature, covering periods of 2006-2009, explored the relationship between outdoor air pollution and asthma in children [22]. This 2011 review evaluated a total of 25 articles found using the key search words "outdoor air pollution, asthma, and children" in PubMed and included children ranging from birth to 18 years of age [22]. Findings from this review found general associations between chronic ozone, nitrogen dioxide (N[O.sub.2]), particular matters (PMs), wood smoke, and traffic exhaust exposure and exacerbation of asthma symptoms across the board. Suggestions for future studies included directing research towards specific pollutants for a more informative association of outdoor exposures and asthma exacerbation. The evidence that suggests an established associated link between outdoor air pollution and pediatric asthma exacerbation is compelling [22,23]. However, without confirmed link between specific aeroallergens and asthma outcomes under specific weather settings, it remains difficult to infer the associated relation between climate change and changes in asthma prevalence. The suggested associated pathway between the recent warming by latitude and the longer ragweed-pollen season in North America might be a plausible hypothesis to explain higher prevalence of pediatric asthma [24], yet whether this longer ragweed-pollen season has led to more asthma attacks remains untested. With the advancement in technology [25] and data availability [26], however, the research community has been able to examine more specific association between outdoor aeroallergens and health outcomes [27,28] under different spatial-temporal settings. A narrative review that updates the recent literature is necessary to summarize the recent findings about outdoor environment and pediatric asthma.

The authors aim to review the recent scientific literature related to outdoor environment and pediatric asthma by (1) providing a narrative review of the recent literature studying associations between factors in the outdoor environment and pediatric asthma, with special attention to the possible spatial-temporal variations of these associations, (2) identifying possible gaps between current research and the impact of climate change on asthma in children outlined in federal reports, and (3) providing recommendations on how the use of health information technology and "big data" might enhance current and future research.

2. Methods

We conducted our review by searching the PubMed search engine. We included all indexed scientific literature, published between years 2010 and 2015, on outdoor environmental factors and asthma in children. We incorporated the following MeSH terms and condition in our search: (("Asthma/chemically induced" [Mesh] OR "Asthma/ epidemiology" [Mesh] OR "Asthma/etiology" [Mesh] OR "Asthma/immunology" [Mesh] OR "Asthma/pathology" [Mesh] OR "Asthma/physiology" [Mesh] OR "Asthma/prevention and control" [Mesh]) AND ("humans" [MeSH Terms] AND English [lang])) AND (environmental factors [TI] OR ("Environmental Exposure" [Mesh] OR "Environmental Illness" [Mesh])) AND "2010/02/26" [PDat]: "2015/02/24" [PDat].

To ensure rigor we developed a review protocol that two of our three authors (Jenna Pollock and Ronald W. Gimbel) followed in the review process. The protocol included our search terms and inclusion/exclusion criteria.

2.1. Inclusion and Exclusion Criteria. Studies were included if they met the following criteria: (1) research conducted in North America, (2) research participants or focus was on children (<18 years of age), (3) manuscripts incorporated a scientific collection and analysis of data to include, but not limited to, randomized controlled trials, cross-sectional data analysis case controls, cohort prospective studies, epidemiological studies literature reviews (systematic and narrative), or cohort retrospective trials, and (4) published between 2010-2015. Studies were excluded if (1) manuscript were not considered research (e.g., opinion papers) and (2) manuscripts were not written in English.

2.2. Review Process. Two authors (Jenna Pollock and Ronald W. Gimbel) incorporated a three-step review process that included an initial title review, abstract review, and full-text review. Both authors conducted independent reviews and compared findings. When a finding differed between authors, each collectively reviewed points of differentiation and a consensus vote was achieved. We eliminated duplicate titles and titles that did not meet the inclusion criteria or met exclusion criteria. Then we repeated this procedure in our abstract review and full-text review.

3. Results

Our literature search yielded a total of 530 manuscripts with 356 being excluded in title review. The remaining 174 manuscripts were assessed through abstract review; 128 were excluded at this stage. The final full-text review of 46 manuscripts resulted in the exclusion of 13 manuscripts, leaving 33 manuscripts included in this manuscript (Figure 1). Tables 1-3 identify each paper reviewed and includes environmental variables studied, age group, sample size, climate region, and any methods used during the study. Given the complexity and heterogeneity in defining asthma outcomes, we stratify these studies into four categories in our tables (Tables 1-3): asthma diagnosis and symptoms, asthma symptoms, asthma symptom and care utilization, and asthma cost. These three tables include both the findings and the limits of each included study. These included manuscripts are identified in three focused areas below, followed by a review of identified literature review (narrative and systematic) and intervention studies.

3.1. Research Focused Primarily on General Traffic-Related Air Pollution "TRAP" (Table 1). Traffic-related air pollution is a collective concept that includes the various pollutants associated with traffic. It has been challenging to determine the impact of the specific types of pollutants on respiratory function [29]. Table 1 summarizes the findings about child asthma and the aggregate measure of traffic-related air pollution (TRAP). Other studies measured impacts of specific pollutants of TRAP such as carbon monoxide, ultrafine particles, ozone, nitrogen dioxide, black carbon, sulfide dioxide, and other lesser-mentioned pollutants on asthma outcomes [30]. Because these studies examined specific pollutants associated with traffic-related air pollution, the associations between these pollutants and pediatric asthma were reported separately in Table 2.

Five studies focused on generalized TRAP as a whole unit rather than specific TRAP markers as described above. While the methods and types of asthmatic markers measured differ between the studies, the results from McConnell et al., Bernstein, Eckel et al., Newman et al., and Sucharew et al. [29, 31-34] consistently uphold what has been shown in earlier work regarding the link between TRAP and asthma. Of the studies adding evidence to the association between TRAP and asthma, McConnell et al. [29] found that asthma risk increased with modeled traffic-related pollution exposure from roadways near homes [Hazard Ratio (HR): 1.51; 95% confidence interval (CI), 1.25-1.82] and near schools [HR 1.45; 95% CI, 1.06-1.98]. Bernstein [31] found that one's exposure to "stop and go" traffic was associated with wheezing during infancy. Eckel et al. [32] found that the length of road was positively associated with fractional exhaled nitric oxide (FeNO) among pediatric patients, a marker commonly used to measure oxidative stress and airway inflammation. Sucharew et al. (2010) found that children exposed to the highest tertile of traffic exhaust had an estimated 45% increase in risk of recurrent night cough (RNC), compared with children exposed to the lowest tertile [adjusted Odds Ratio 1.45, 95% CI: 1.09, 1.94]. Finally, we did identify one study that did not report a significant association between TRAP exposure and asthma, while Newman et al. [33] reported that higher TRAP exposure was associated with a higher hospital readmission rate (21% versus 16%; P = 0.05); this association was not significant after adjusting for covariates [OR, 1.4; 95% CI, 0.9-2.2]. It may be noteworthy that this 2013 paper was the only study that explored hospital readmission rates as the marker for asthma outcome, which could be a function of treatment and management besides environmental triggers. The study's relatively small sample (758 children, 19% of whom had a hospital readmission) might also explain its lack of statistical significance after controlling for the covariates.

3.2. Research on Specific Air Pollutants (Table 2)

3.2.1. Particulate Matter (PM). Studies about particular matter and asthma among children examined the impact from three major types: [PM.sub.2.5], [PM.sub.10-2.5], and [PM.sub.10]. Eleven studies concluded that [PM.sub.2.5] was associated with worsening asthma symptoms and/or increased oxidative stress as determined by biomarkers in pediatric patients [35-46]. For instance, a study by Delfino et al. [37] of 11,390 asthma-related hospital encounters among 7492 subjects aged 0-18 found significant and positive associations between [PM.sub.2.5] and child asthma regardless of outdoor temperature (e.g., warm or cold season). On the other hand, Evans et al. and Patel et al. [30,47] found neither significant nor positive association between asthma and [PM.sub.2.5]. For instance, Patel et al. [47] found no significant link between [PM.sub.2.5] exposure and asthma in children in their 2013 paper, the only study that has studied 8-isoprostane as the asthma biomarker among our reviewed studies.

While [PM.sub.2.5] is made up of several different components, among all our reviewed studies the one by Strickland et al. in 2010 [41] was the only team that made an association between asthma and [PM.sub.2.5] components, including [PM.sub.2.5] sulfate, [PM.sub.2.5] elemental carbon, [PM.sub.2.5] organic carbon, and [PM.sub.2.5] water soluble metals within one location. Five papers examined the association between [PM.sub.10-2.5] and asthma with different results [39,41,42,45,47]. Out of the five review papers, Lewis et al. and Patel et al. [39,47] found no association; Patel et al. [47] found nonsignificant but positive association, while Strickland et al. and Sarnat et al. [41,45] found positive and significant association. Among the seven studies specifically investigating [PM.sub.10] and asthma in children there were also mixed results [35,36,39,40,42,47,48], with Berhane et al., Nishimura et al., and Patel et al. reporting no association [36,40,47], Akinbami et al., Lewis et al., and Lemke et al. reporting a significant and positive association [35,39,48], and Zora et al. reporting a nonsignificant but positive correlation [42].

In summary, there was a positive association, established in most (eleven out of thirteen) studies, between [PM.sub.2.5] and asthma in children. On the other hand, research on the association between [PM.sub.10-2.5] and [PM.sub.10] with asthma in children recorded inconsistent findings. These results may be inconsistent due to failure to stratify between particulate matter subtypes, length of symptom tracking (ranging from 4 weeks to 11 years), or differences in the measurement of asthma severity. Some of these studies used a questionnaire to determine quality of asthma severity, while others used FeNO concentrations, 8-isoprostane concentrations, or number of emergency department visits to determine severity of asthma may be leading to variation of outcomes observed for larger PM sizes.

3.2.2. Ozone ([O.sub.3]). Children's exposure to ozone was a commonly studied risk factor and was measured to explore its associations with asthma outcomes in 10 of the 25 studies [30,35-41,49,50]. Chronic exposure to ozone was found to increase asthma outcomes in studies by Akinbami et al., Lewis et al., Nishimura et al., and Perez et al. [35,39,40, 50] and increase costs in pediatric asthma outcomes in a study by Brandt et al. [49]. While the majority of evidence pointed towards a positive association between pediatric asthma and ozone exposure, there was little agreement as to the seasonality pattern in the association between ozone exposure and pediatric asthma. In Orange County of California, Delfino et al.'s study [37] of 11,390 asthma-related hospital encounters among 7492 subjects aged 0-18 found that asthma-related emergency department (ED) admissions was positively associated with ozone during the warm season, but not during the cool season. Meanwhile, Habre et al.'s longitudinal study [38] of 36 children found exposure was significantly associated with severe wheezing, especially during Fall and Spring. In Strickland et al.'s study [41] where daily counts of emergency department visits for asthma or wheeze among children aged 5-17 during 1993-2004 were collected from hospitals in Metropolitan Atlanta area, these ED visits were associated with ozone in both cold and warm seasons. In contrast to all these findings, Evans et al. [30] actually found a negative association between increased ozone concentration and asthma exacerbation among urban children, which the authors attributed to the negative correlation of ozone with nitrogen dioxide at the site of the study. Finally, Berhane et al. [36] found that ozone was not statistically significantly associated with FeNO asthma biomarker, yet this study did not take into account the season of measurement.

3.2.3. Nitrogen Dioxide (N[O.sub.2]). Eleven studies examined associations of N[O.sub.2] and asthma [35-37,40,42,44,47-51]. The one study by Delfino et al. investigating N[O.sub.2] by season found that during the cold season peaks in asthma cases were correlated [37] with N[O.sub.2]. Overall, of 11 papers which examined the association between N[O.sub.2] and asthma, 10 found statistically significant and positive associations [35-37,40, 42,44,47-51] and Akinbami et al. found a nonsignificant association [35]. In Nishimura et al.'s study [40] that took account of regional variations, there was association between N[O.sub.2] and subsequent asthma events within 5 different urban regions in mainland United States and Puerto Rico. The one study by Akinbami et al. [35] finding no significant association studied 12-month N[O.sub.2] levels in relation to the self-reported asthma outcomes in the National Health Interview Survey.

3.2.4. Carbon Monoxide (CO) and Sulfur Dioxide (S[O.sub.2]). Six studies studied S[O.sub.2] [30,35,40,41,43,48], among which Nishimura et al.'s study found that the significance of associations between S[O.sub.2] and asthma varied among regions in the United States [40]. Evans et al., Akinbami et al., Spira-Cohen et al., and Lemke et al. found no significant association between S[O.sub.2] and asthma [30,35,43,48]. Strickland et al. [41] found S[O.sub.2] to be associated during the warm season only. Meanwhile, the evidence about the link between carbon monoxide and asthma is much more consistent: all four papers (by Evans et al., Delfino et al., Strickland et al., and Vette et al.) [30,37,41,44] that studied CO's impact found associations with asthma.

3.2.5. Other Variables. Possible impacts from polycyclic aromatic hydrocarbons were explored in 4 studies: Lemke et al., Jung et al., Miller et al., and Padula et al. [48,52-54], among which only the study by Lemke et al. [48] found positive, statistically significant impact from benzene and toluene (independently) on pediatric asthma. The other three studies all confirmed significant positive associations between pediatric asthma and polycyclic aromatic hydrocarbons [48,52,53]. Ratnapradipa et al. [55] found that children exposed to "wood, oil, smoke, soot, or exhaust" were at higher risk for early asthma diagnosis. A study by Tse et al. [56] on wildfires and asthma found that exposure to catastrophic wildfire smoke was associated with worsening asthma outcomes particularly in obese children. In a study of patients with atopy and a history of wheezing by Jerschow [57], asthma morbidity is associated with high urinary dichlorophenol levels, suggesting that plant pesticide with dichlorophenol might be another symptom trigger for asthma patients. Finally, the outdoor fungal exposure was found to be associated with increased asthma symptoms and increased risk of exacerbations according to a 2010 study of inner-city children by Pongracic et al. [58], adding to the literature about the possible link between fungal spore and asthma severity [59].

As urbanization may affect health through certain environmental exposures that may be more prevalent in urban environments (e.g., traffic pollution, industrial emissions, and noise), urban land use was found by Ebisu et al. [51] to significantly increase the wheezing severity among infants; the effects were mostly associated with TRAP rather than noise or stress though the latter two still played a minor factor in wheezing severity.

3.3. Research on Aeroallergens and Other Exposures (Table 3)

3.3.1. Plant-Related Aeroallergens. Three manuscripts by Dellavalle et al., Jariwala et al., and Sheehan et al. [60-62] focused on the exposure to plant-based aeroallergens and asthma among children (Table 3), and all three studies identified strong correlations between tree pollen (even at low levels) and pediatric asthma, especially during the spring seasons. The correlation between tree pollen count and asthma-related emergency department visit peak in an urban area was not significant during the fall and winter season, as found by Jariwala et al. [61]. Grass and ragweed were the least common sensitizers in younger children (0-4 years), yet these aeroallergens became more prevalent in the older age groups (10-14 years), as found by Sheehan et al. [62].

3.3.2. Effect of Race/Ethnicity and Socioeconomic Status on Outdoor Exposures and Asthma. It is possible that sociodemographic factors such as race/ethnicity and socioeconomic status play a confounding role between outdoor environment and asthma outcomes. Three studies by McConnell et al., Nishimura et al., and Ratnapradipa et al. [29,40, 55] examined the role of race on the outcomes of various environmental variables on asthma. A study by Newman et al. on the readmission rates [33] found Caucasian children had a 3 times higher rate of readmission with high TRAP while African American children had no increased rate. Meanwhile, a 2013 study by Ratnapradipa et al. [55] showed a 31% increase in asthma prevalence among African American children related to "wood or oil smoke, soot, or exhaust." According to the study by McConnell et al., [29] Hispanic children had the lowest rates of TRAP-based asthma and African American children the highest based on a small population of 1437 kindergarten students and first-graders in Southern California. One study studied the impact of environmental factors on the asthma outcome among minority children [40], but not at the differences across races/ethnicities and socioeconomic statuses [40]. No studies specifically explored the possible variation of the association between environmental factors and asthma outcomes across socioeconomic statuses.

3.4. Literature Reviews and Implementation Studies. A literature review by McGwin Jr. et al. [63] found evidence among seven studies linking formaldehyde exposure to worsening asthma in children but cited a need for further epidemiological studies on this topic to find conclusive evidence. A 2011 review by Tzivian about asthma and pollution between 2006 and 2009 confirmed a link between pollutants and asthma exacerbation but found variations of this link between the different age groups studied and discussed limitations in the measurement of outdoor pollutants [22].

Among studies with a theme of interventions and implementation, one study by Youssef-Agha et al. [64] about the feasibility of environmental monitoring examined the integration of daily environmental health surveillance as a tool in predicting when best to apply precautionary measures for children. Focusing on the temporal pattern of asthma exacerbation, the authors found that the prior day CO, S[O.sub.2], N[O.sub.2], nitrogen monoxide (NO), [PM.sub.2.5], and [O.sub.3] had significant effects on asthma exacerbations among elementary school students in Pennsylvania, and they concluded that monitoring of air pollutants over time could be a reliable new means for predicting asthma exacerbations. With special attention to spatial variation of asthma triggers, an ongoing study by Vette et al. [44] explored new ways of measuring urban air pollutants by integrating measurement and modeling to quantify contribution of traffic sources to predict where pollutants would pose the greatest risk to children. More ambitiously, Gallagher et al.'s [65] ongoing study among Detroit children incorporated exposure metrics and clinical indicators to decipher the biological complexity with etiology related to gene-environment interactions, aiming to provide an opportunity to evaluate complex relationships between environmental factors, physiological biomarkers, genetic susceptibility, and asthma/cardiovascular outcomes.

Finally, while most of the discussion about intervention has been centered on environmental monitoring, Perez et al. pointed out that [50] encouraging compact growth in urban planning has also been suggested as an intersectoral approach, which would reduce pollution by making long vehicle travel less necessary.

4. Discussion

This review found 33 studies between 2010 and 2015 on outdoor environmental impacts on pediatric asthma. These studies have strengthened the evidence about the roles of [PM.sub.2.5], TRAP, CO, and pollen in pediatric asthma, while the evidence for roles of [PM.sub.10-2.5], [PM.sub.10], [O.sub.3], N[O.sub.2], S[O.sub.2], and polycyclic aromatic hydrocarbon in asthma has been less consistent. The link between an outdoor environment and childhood asthma has not been adequately examined with regard to the regional and temporal variation of the environment. Thus, spatial-temporal details of the environment are needed in future studies of asthma and environment, particularly if researchers want to examine the hypothesized impact of climate change on asthma. It is worth noting that some of the null results from our reviewed studies might be a result of study design rather than a lack of etiological link. For instance, Brandt et al. and Perez et al. [49,50] found that risk assessment focusing on the effects of regional pollutants may underestimate the impact and the burden of air pollution due to challenges such as measurement and model specification.

One notable contribution of the recent studies about CO by Evans et al., Delfino et al., Strickland et al., and Vette et al. [30,37,41,44] is the consistent association between carbon monoxide and asthma symptoms. While particular matter and ozone have been used for monitoring air quality as related to asthma outcome, carbon monoxide has been less often monitored and reported. It might be worthwhile to enhance the monitoring and reporting of carbon monoxide density as an air quality measure, especially for geographic areas where its density is often elevated.

There was a lack of studies regarding early childhood development and asthma. Asthma is difficult to diagnose in early childhood [66], an age when outdoor environment could pose a more serious threat to the exacerbation. Standardized research over age groups plus the adoption of diverse diagnostic tools for early childhood asthma will help clarify the differences between age groups as well as the exact role of pollution in asthma development.

In each of our three tables, the geographic location was specified to the distinct climate regions as defined by the National Centers for Environmental Information. These specifications protect against broad generalizations about environmental impacts on asthma, while limiting a study's relevance to the population's climate region. Only one study, the one by Nishimura et al. [40], explored differences between climate regions finding differences across 5 urban regions for the examined pollutant. So far, the geographic variation of pediatric asthma prevalence has been documented by Malhotra et al. [67] yet not fully understood. Future studies that explore the possible variation between asthma trends in different climate regions would help us understand better the possible role climate change might have played in asthma prevalence (via worsening ambient air pollution and altered local and regional pollen production, according to Shea et al. [68], which varies across different climate regions).

Only one study in our review, the one by Strickland et al. [41], broke down fine PM into its components. Reviewing the impact of the different components of particulate matter may help shape policy and research in the future pertaining to PM-induced asthma exacerbation. Compared with studies about PM and pediatric asthma, there are an insufficient number of studies exploring non-PM factors such as variations in temperature, seasonal environmental impact, pollen/weed levels, socioeconomic status, and race/ethnicity. Finding the precise impact of temperature on pediatric asthma is especially relevant as increasing bodies of evidence show rising temperatures across the globe [23], a significant proportion of which is based on human activities. Vette et al., Youssef-Agha et al., and Gallagher et al. [44,64,65] discussed new ways to measure urban air pollution and design preventative plan. More research on these solutions will help to fine-tune and optimize policy actions addressing these outdoor environmental triggers of child asthma.

4.1. Gap between Federal Reports and Current Literature. There exists a research gap between the above-mentioned federal reports about climate changes' possible impact on respiratory diseases and the current literature as we reviewed; the link between outdoor environment and child asthma has not been adequately studied with regard to the regional and temporal variation of the environment. There is virtually no study about the exact temperature in the pediatric patient's location and asthma-related events. Without these spatial-temporal details about the outdoor environment for the study population, it is difficult to empirically examine the impact of climate change on child asthma outcome, even though the hypotheses about these associated pathways (wild fires, change in aeroallergen density, mold, insect population increase, etc.) are plausible. For instance, one climate-related factor, thunderstorm, has been shown as a significant trigger of asthma in England and Iran [69,70], augmenting the previous findings about thunderstorm asthma [71]. Yet, after one 2008 paper from Atlanta, Georgia by Grundstein et al. [72], there has been little (if any) recent empirical study updating the evidence about thunderstorm and asthma in the United States and Canada.

4.2. Recommendations to Enhance Future Research Efforts. The increasingly affordable computational resources and the diversity of mobile health devices in recent years have enabled researchers to collect real-time health data from the very location where medical events take place. For example, obtaining the exact time and location of an asthma attack via mobile devices has become feasible [73] given the current stage of telecommunication technology, opening the door to constructing an "asthma registry" [74-76] where pieces of user-supplied geospatial and temporal input about asthma episodes are entered for surveillance and analysis. Piloting these kinds of data collections in places with high asthma prevalence could be the next feasible step in monitoring the impact of changing outdoor environment on child asthma.

5. Conclusion

Consistent with those studies documented prior to 2010, findings from this review of studies between 2010 and 2015 show that the associations between traffic-related air pollutants (including N[O.sub.2], particulate matter, and S[O.sub.2]) and pediatric asthma are well supported. Seasonal and regional variations in certain outdoor factors were rarely accounted for, even though the studies that did study this found the variation to be significant. Future documentation about the specific composition of particulate matter and polycyclic aromatic hydrocarbons would add to studies that did not have the resources available to examine the underlying components of these environmental triggers. A surveillance system with standardized reporting of environmental effects across different age groups and geographic regions will clarify gaps in current knowledge on environmental impacts on pediatric asthma. New studies expanding the spatial dimension and temporal dimension of monitoring ambient levels of known environmental triggers and exacerbating agents are promising in the goal to prevent pediatric asthma ED visits and hospitalizations, enriching the toolkit for parents and community health stakeholders.

Competing Interests

None of the authors have conflicts of interest to declare.


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<ADD> Jenna Pollock, Lu Shi, and Ronald W. Gimbel Department of Public Health Sciences, Clemson University, Clemson, SC, USA </ADD>

Correspondence should be addressed to Lu Shi;

Received 10 August 2016; Revised 9 November 2016; Accepted 20 December 2016; Published 23 January 2017

Academic Editor: Shyamali C. Dharmage

Caption: Figure 1: Flow diagram of our manuscript selection.
Table 1: Studies focused on traffic-related air pollution (TRAP).

                 Outdoor        Age    Sample   Climate      Study
Source/year     variables      group    size     region      design

Asthma symptom

Bernstein,         TRAP         1-7     700     Central,    Cohort/
2012              (ECAT)       years               US       adjusted

McConnell         TRAP,        K-1st   2,497    Western,    Cohort/
et al.,        [PM.sub.10],    grade               US       adjusted
2010          [PPM.sub.2.5],

Sucharew et       TRAP,         1-3     550     Central,    Cohort/
al., 2010      [PM.sub.10],    years               US       adjusted

Eckel et       TRAP, roads,    7-11    2,143    Western,     Cross-
al., 2011        traffic       years               US      sectional/
                densities,                                  adjusted
              NO, N[O.sub.2]

Asthma-related symptom and care utilization

Newman et          TRAP        1-16     758     Central,    Cohort/
al., 2014                      years               US       adjusted

Source/year   Assessment method            Findings and limits

Asthma symptom

Bernstein,         Medical        Higher TRAP associated with wheezing
2012          evaluations, skin    during infancy and at age 3. Limit:
                  testing,        parental reports of wheezing at 3 are
               proximity, and         not strong asthma predictors
              LUR modeling (a)

McConnell       Baseline and       Asthma risk increased with modeled
et al.,            annual           TRAP exposure1, from roadway near
2010           questionnaires,    home (HR 1.51; 95% CI: 1.25-1.82) and
              community ambient    near school (HR 1.45; 95% CI: 1.06-
               air pollution,     1.98). Limit: short 3-year follow-up
              variables, local

Sucharew et    Questionnaires,    Children exposed to higher levels of
al., 2010     skin prick test,       TRAP are more likely to suffer
                 air quality      recurrent night cough (OR, 1.45, 95%
                 monitoring,        CI, 1.09-1.94) than children less
                  clinical        exposed. Limit: sample is limited to
              evaluation, home            those with high risk
                visits, house

Eckel et      Breath collection      Length of roads positively was
al., 2011         technique            associated with FeNO, with
                (offline and        significant associations in small
                  online),         buffers: 46.7% [95% CI, 14.3-88.4]
                  geocoding         higher FeNO for increases in the
                distance from     length of all roads in 50 m buffers.
                residence to        Limit: rely on parent report for
                 roads, road         medication use as a confounding
                 class, and                      factor
                density data,
                modeling (c),
              body mass index,

Asthma-related symptom and care utilization

Newman et     Administrative      Higher TRAP exposure was associated
al., 2014     data (ICD-9-CM)      with higher readmission rate (21%
               for hospital       versus 16%; P = 0.05), association
                readmission       was not significant after adjusting
                (primary or        for covariates (aOR, 1.4; 95% CI,
                 secondary       0.9-2.2). Limit: sample was from one
                diagnosis),               single institution
               serum sample,
               specific IgE

aOR: adjusted Odds Ratio; HR: Hazard Ratio; LUR: land use regression;
ECAT: elemental carbon attributed to traffic. Note. (a) TRAP exposure
estimated using a qualitative proximity model and quantitative LUR
model; (b) modeled annual concentration estimates based on surrounding
area characteristics (c) used several models including line source
dispersion and regression models to map estimates.

Table 2: Association between specific pollutants and pediatic asthma.

Source/year     Outdoor variables         group          Sample size

Asthma diagnosis and symptom

Akinbami et      S[O.sub.2], NO,       3-17 years          34,073
al., 2010           [O.sub.3],

Berhane et         N[O.sub.2],          5-7 years           1,211
al., 2014          [PM.sub.10],

Cornell et       BC, [PM.sub.2.5]                            240
al., 2012

Ebisu et       Urban land use, TRAP     0-1 years            680
al., 2011      modeling, N[O.sub.2]

Habre et          [PM.sub.2.5],        6-14 years            36
al., 2014           [O.sub.3],

Jerschow,        Dichlorophenols      [greater than     2,125 sample
2015               (pesticide)        or equal to]     (% of children
                                         6 years          unclear)

Jung et al.,   Polycyclic aromatic      5-6 years            354
2012            hydrocarbons (PAH)

Lewis et           [PM.sub.10],        5-12 years            298
al., 2013         [PM.sub.2.5],

Miller et      Polycyclic aromatic    [greater than          222
al., 2010       hydrocarbons (PAH)    or equal to]
                                         5 years

Nishimura et        [O.sub.3],         8-20 years           4,320
al., 2013          N[O.sub.2],

Padula et              PAH             9-18 years            467
al., 2015

Patel et            [O.sub.3],         14-19 years           36
al., 2013          [PM.sub.10],
               [PM.sub.10-2.5], BC

Perez et           N[O.sub.2],          <18 years          2.54M +
al., 2012           [O.sub.3]

Pongracic et     Fungal allergen       5-11 years       936 children
al., 2010            exposure                         (moderate-severe

Ratnapradipa   Soot, exhaust, wood     <5-6 (pre-            691
et al.,            or oil smoke          school)

Sarnat et            BC, PM,           6-12 years            58
al., 2012        [PM.sub.10-2.5],

Spira-            [PM.sub.2.5],        10-12 years           40
Cohen et           S[O.sub.2],
al., 2011        Elemental carbon

Vette et         [PM.sub.25], BC,      14-16 years           139
al., 2013          N[O.sub.2],
                 N[O.sub.x], CO,

Zora et          [PM.sub.10-2.5],      6-11 years            36
al., 2013         [PM.sub.2.5],
               [PM.sub.10], markers
                  for TRAP (BC,

Asthma cost

Brandt et            NO2, O3           0-17 years           1,290
al., 2012

Asthma-related symptoms and care utilization

Strickland       [PM.sub.10-2.5],      5-17 years          91,386
et al.,             [O.sub.3],
2010               N[O.sub.2],
                S[O.sub.2], CO, as
                 markers for TRAP

Tse et al.,     Wildfire exposure                       2,195, 3,965

Lemke et           N[O.sub.2],         5-89 years           2,900
al., 2014        S[O.sub.2], VOC,
                 [PM.sub.10], PAH

Evans et         [PM.sub.25], CO,      3-10 years            74
al., 2014          S[O.sub.2],

Delfino et       CO, N[O.sub.x],       0-18 years      11,390 visits/
al., 2014         [PM.sub.2.5],                        7,492 patients
                  [O.sub.3], as
                 markers for TRAP

Source/year        Climate region             Study design

Asthma diagnosis and symptom

Akinbami et         National, US            Cross-sectional/
al., 2010                                       adjusted

Berhane et           Western, US            Cohort/adjusted
al., 2014

Cornell et          Northeast, US           Cross-sectional/
al., 2012                                       adjusted

Ebisu et            Northeast, US           Cross-sectional/
al., 2011                                       adjusted

Habre et            Northeast, US           Cohort/adjusted
al., 2014

Jerschow,             National              Cross-sectional/
2015                                            adjusted

Jung et al.,        Northeast, US           Cohort/adjusted

Lewis et          Upper Midwest, US         Cohort/adjusted
al., 2013

Miller et           Northeast, US           Cohort/adjusted
al., 2010

Nishimura et   South, Northeast, West,      Cohort/adjusted
al., 2013       Upper Midwest, Puerto
                      Rico, US

Padula et             West, US              Cross-sectional/
al., 2015                                       adjusted

Patel et            Northeast, US           Cross-sectional/
al., 2013                                       adjusted

Perez et             Western, US            Cross-sectional/
al., 2012                                       adjusted

Pongracic et        National, US          Cohort/Adjusted for
al., 2010                                      covariates

Ratnapradipa        Northeast, US           Cross-sectional/
et al.,                                         adjusted

Sarnat et         South, US, Mexico         Cross-sectional/
al., 2012                                       adjusted

Spira-              Northeast, US           Cohort/adjusted
Cohen et
al., 2011

Vette et             Midwest, US            Cohort/adjusted
al., 2013

Zora et               South, US             Cross-sectional/
al., 2013                                       adjusted

Asthma cost

Brandt et            Western, US            Cross-sectional/
al., 2012                                       adjusted

Asthma-related symptoms and care utilization

Strickland          Southeast, US           Cross-sectional/
et al.,                                         adjusted

Tse et al.,           West, US              Cross-sectional/
2015                                            adjusted

Lemke et         Upper Midwest, US &        Cross-sectional/
al., 2014              Canada                   adjusted

Evans et            Northeast, US           Cross-sectional/
al., 2014                                       adjusted

Delfino et           Western, US            Cross-sectional/
al., 2014                                       adjusted

Source/year       Assessment method           Findings and limits

Asthma diagnosis and symptom

Akinbami et        National Health        aORs for current asthma for
al., 2010      Interview Survey (NHIS)      the highest quartile of
                database; stratified     estimated ozone exposure: 1.56
                 multistage sampling      (95% CI: 1.15, 2.10) and for
                                         recent asthma attack 1.38 (95%
                                         CI: 0.99,1.91). Limit: county-
                                           level 12-month averages of
                                            pollution are imprecise
                                             measures of children's
                                             exposure to pollution.

Berhane et       Questionnaire, FeNO          Increases in annual
al., 2014       measurement, ambient        concentrations of 24-hr
               air monitoring stations       average N[O.sub.2] and
                                          [PM.sub.2.5] were associated
                                         with increase in FeNO. Limit:
                                          lack of information on time-
                                           activity patterns for the
                                             subjects could lead to
                                         misclassification of exposure

Cornell et     FeNO test, portable air      BC higher in high-asthma
al., 2012       sampling units, fixed    neighborhoods (1.59 [micro]g-
               BC monitor, PFT, Serum    [m.sup.3] [95% CI 1.45-1.73])
                         IgE                   than in low-asthma
                                         neighborhoods (1.16 [micro]g-
                                         [m.sup.3] [1.06-1.27]) with P
                                           < 0.001. Limit: sample was
                                            limited to middle-income

Ebisu et       Interview, asthma diary    10% increase in urban land-
al., 2011                                 use within 1,540 m buffer of
                                         infant's residence associated
                                           with 1.09-fold increase in
                                           wheeze severity. This link
                                           becames insignificant with
                                         TRAP modeling proxy (a) added.
                                         Limit: NO2 as an indicator of
                                           overall TRAP misses other

Habre et        Symptoms diary, skin      2 of the 3 highest frequency
al., 2014      test, air sampling, air     reactions were for ragweed
                     monitoring,             (48%) and birch (39%).
                  temperature, and       Exposure to O3 and particular
                      humidity             matters was significantly
                                             associated with severe
                                          wheezing. Limit: reliance on
                                              central-site ambient
                                         measurements to assign outdoor
                                               exposure category

Jerschow,      NHANES, dichlorophenols    Higher dichlorophenol levels
2015              measured in urine         were linked with asthma
                                               diagnosis, asthma
                                          prescriptions, missing work-
                                            school, exercise-induced
                                          wheezing in atopic wheezers.
                                             No association between
                                           dichlorophenol levels and
                                         asthma morbidity in nonatopic
                                          wheezers. Limit: reliance on
                                            self-reported data about
                                               wheezing problems.

Jung et al.,   Questionnaires, PAH air     Repeated high exposure to
2012             monitoring devices,       pyrene was associated with
                    blood samples         report of asthma. Limit: PAH
                                         exposure was assessed only by
                                           2 repeated measures 5 to 6
                                         years apart, which could lead
                                              to misclassification

Lewis et         Respiratory symptom         Outdoor [PM.sub.2.5],
al., 2013        diary, ambient air        [PM.sub.10], and [O.sub.3]
                monitoring, caregiver    concentrations were associated
                      interview              with increased odds of
                                             respiratory symptoms,
                                         particularly in children using
                                          steroid medication. Similar
                                         associations were not realized
                                             with PM10-2.5. Limit:
                                            measuring symptoms using
                                             handwritten diaries by
                                         caregiver and the child could
                                                lead to errors.

Miller et       Questionnaires, urine     Widely varying levels of 10
al., 2010             testing,            PAH urinary metabolites were
                immunoglobulintesting      detected in all children.
                                         Levels of PAH metabolites were
                                              not associated with
                                          respiratory symptoms. Limit:
                                             the half-lives of PAH
                                         metabolites are short and thus
                                         variations in exposure across
                                               time may be large.

Nishimura et       Questionnaires,           Early life exposure to
al., 2013       regional ambient air     N[O.sub.2 ]was associated with
                   pollution data,        risk for asthma [OR = 1.17;
                                          95% CI 1.04-1.31] in Latino
                                         and African American children
                                           across 5 US regions. Other
                                           pollutants' impact varied
                                             across regions. Limit:
                                         measurement of PM2.5 was less
                                          complete than that of other
                                            pollutants, leading to a
                                                smaller sample.

Padula et      PFTs, spirometry, skin       Significant association
al., 2015        testing, fixed air      between PAH and lung function
                monitoring, wind and        testing in nonasthmatic
                      humidity            children: increase in PAH456
                                          was associated with decrease
                                         in [FEV.sub.1]. Limit: change
                                           in pulmonary function over
                                              time wasn't assessed

Patel et          Aethalometers to         BC and NO2 were positively
al., 2013      measure BC, EPA systems       associated with airway
                  database, R-Tube,        inflammation and oxidative
                immunosorbent assays       stress. Limit: the use of
                                           central-site PM2.5 and O3
                                          measurements could bias the
                                           effect estimate from them
                                                  toward null.

Perez et       ACS, local surveys, EPA      8% of asthma cases were
al., 2012        air quality system,      partially caused by resident
                ambient air monitors,    proximity to major road. Link
                proximity to traffic       between proximity to major
                                         road and asthma exacerbations
                                          is positive. Limit: traffic
                                             density and vehicular
                                         emissions are not reflected in
                                             this metric oftraffic

Pongracic et    Interviews, portable       Excess symptom days per 2
al., 2010        air sampling, site      weeks associated with increase
                  inspections, dust         in outdoor fungi level;
                       samples             increases in total fungal
                                          exposure was associated with
                                         increases in symptom days and
                                           asthma-related unscheduled
                                          visits. Limit: the study did
                                             not have children not
                                         sensitized to fungal allergens

Ratnapradipa    Structured interviews      Exposure to soot, exhaust,
et al.,                                      wood, or oil smoke was
2013                                     associated with higher risk of
                                            asthma than those never
                                           exposed. Limit: the cross-
                                         sectional nature of the study
                                            and the recall bias were
                                           associated with interview-
                                                   based data

Sarnat et         eNO testing, air       There exists significant link
al., 2012          monitoring, air       between eNO and measures of PM
               monitors, passive badge    and BC. PM pollutant levels
                    samplers, BMI          predict acute respiratory
                     measurement             responses better than
                                            N[O.sub.2] measurements.
                                          Limit: clinical significance
                                         of the estimated increases in
                                          eNO with pollutant levels as
                                           observed here is unclear.

Spira-           Questionnaires, air        Elevated risk of wheeze,
Cohen et          monitoring, time-      shortness of breath, and total
al., 2011       activity daily diary,    symptoms were associated with
                    aethalometer,         same-day increased personal
                     spirometry            EC, but not with personal
                                          PM2.5 mass. No associations
                                           with school-site PM2.5 or,
                                           S[O.sub.2]. Limit: a small
                                          sample size of only 40 study

Vette et         FeNO testing, nasal     This paper is a protocol, yet
al., 2013            lavage, F2-            preliminary data provide
                 isoprostances, air      evidence of roadway impacts on
                monitoring, diaries,      the measured concentrations
                   air monitoring         and indicate that variations
                                           in exposures between study
                                           participants are evident.
                                          Limit: full detailed results
                                          are yet to come, not in this

Zora et        Questionnaire, ambient          Positive (but not
al., 2013          air monitoring,         statistically significant)
                  meteorology data,      association between asthma and
                 pulmonary function      each single pollutant. Limit:
                       testing            use the questionnaire-based
                                         data as outcome variable could
                                          bring in recall bias, social
                                            desirability bias, etc.

Asthma cost

Brandt et      MEPS, CHIS, nhts, hcup,   Nearly 50% is due to regional
al., 2012        published averages        air pollution-attributable
                    of NO2 and O3         exacerbations among children
                                         with asthma. Limit: costs are
                                          usually difficult to measure

Asthma-related symptoms and care utilization

Strickland       Administrative data      Asthma ED visits associated
et al.,        (ICD-9) from ED visits,     with [O.sub.3] during warm
2010             ambient air quality      season and cold season (Nov-
               monitors, pollen counts   Apr), several TRAP measures in
                                         warm season, [PM.sub.2.5] and
                                           S[O.sub.2] in warm season,
                                            [PM.sub.10-2.5] in cold
                                          season; associations with ED
                                          visits present at relatively
                                         low ambient concentrations of
                                           studied variables. Limit:
                                            difficult to draw causal
                                             inference from cross-
                                                sectional design

Tse et al.,     Short-acting [beta]-     SABA use increased (+16%, P <
2015            agonist (SABA) use in    0.05) in obese children (BMI >
                   obese children        30) compared to nonobese (BMI
                                          < 30) in 2003; increased but
                                           nonsignificant difference
                                         (+10.5%, N.S.) in SABA use in
                                             2007. Limit: asthmatic
                                            patients may have taken
                                         preventive action to minimize
                                                  the exposure

Lemke et        Geospatial data, air         Intraurban air quality
al., 2014      sampling station data,    variations related to adverse
                 ICD-9 codes with ED          respiratory events;
                     visits and           N[O.sub.2], [PM.sub.10], and
                  hospitalizations       VOC positively correlated with
                                          ED visits. Limit: relatively
                                         coarse temporal resolution in
                                            study design compromises

Evans et        Physician visits, ER        Increases in UFP and CO
al., 2014              visits            concentration were associated
                                         with pediatric asthma visits.
                                          Increases in [O.sub.3] were
                                          associated with less asthma
                                          visits. No associations for
                                            mode particles, BC, fine
                                           particles, or S[O.sub.2].
                                         Limit: the monitoring station
                                           is located on a diesel bus
                                           route, which could lead to
                                           higher measured pollutant
                                         concentrations than the actual
                                           exposure among some of the
                                                study subjects.

Delfino et      Emergency Department      ED visits and admissions for
al., 2014         visits, inpatient          asthma were positively
               admissions; ambient air    associated with ambient air
                    station data          pollution (i.e., [O.sub.3],
                                         [PM.sub.2.5]) during the warm
                                          season, and CO, N[O.sub.2],
                                            [PM.sub.2.5] in the cool
                                            season. Limit: insurance
                                         status is the only individual-
                                             level sociodemographic

BC: black carbon; ED/ER: emergency department/emergency room; eNO:
exhaled nitric oxide; SABA: Short-Acting Beta-Agonists; UFP: ultrafine
particles; VOC: volatile organic compound. Note. (a) estimated exposure
levels using LUR modeling.

Table 3: Association between pediatric asthma and aeroallergens and
other exposures.

                 Outdoor                       Sample
Source/year     variables       Age group       size         Region

Asthma symptoms

Dellavalle     Tree, grass,    4-12 years       430       Northeast, US
et al.,       weed, and all-
2012           type pollen

Asthma-related symptoms and care utlization

Jariwala       Tree pollen,    0-18 years;   52 (weekly   Northeast, US
et al. 2011      ragweed,      and adults     mean ED
                 mugwort                      visits)

Asthma sensitivity tests

Sheehan et    Trees (birch,    0-21 years      1,394      Northeast, US
al., 2010      oak, maple,
               elm), grass,
               ragweed mix,

Source/year   Study design       method          Findings and limits

Asthma symptoms

Dellavalle       Cross/      Questionnaire,       Weed pollen at low
et al.,        sectional/     daily diary,      levels (6/9 grains/m3)
2012          adjusted for      allergen-        was associated with
               covariates     specific IgE       shortness of breath,
                             panel for grass   chest tightness, rescue
                              and ragweed;     medication use, wheeze,
                               pollen and       and persistent cough;
                                exposure        grass pollen ([greater
                              modeling (a)       than or equal to] 2
                                                grains/[m.sup.3]) was
                                               associated with wheeze,
                                                   night symptoms,
                                               shortness of breath, and
                                               persistent cough. Limit:
                                                  the study did not
                                                investigate the effect
                                                  of tree pollen on
                                                 sensitized children

Asthma-related symptoms and care utlization

Jariwala         Cross/       ED visit data        ED visits highly
et al. 2011    sectional/       (ICD-9-CM        correlated with tree
              adjusted for       codes),        pollen (r = 0.90, P =
               covariates    hospitalization     0.03) during Spring
                              data, pollen         (March-May). No
                                  count        statistical association
                             (particles per        of pollen (i.e.,
                              cubic meter)     ragweed, mugwort) during
                                                summer or fall. Limit:
                                                data limited to seven
                                                major hospitals in New
                                                York City, borough of
                                                      the Bronx.

Asthma sensitivity tests

Sheehan et       Cross/        Skin prick       Grass and ragweed were
al., 2010      sectional/        testing       least common sensitizers
              adjusted for      database         in younger children,
               covariates                      with rates of 1.0% (0-2
                                                 years) and 2.8% (2-4
                                                 years) for grass and
                                                 1.0% (0-2 years) and
                                                 5.7% (2-4 years) for
                                               ragweed. The rates were
                                               higher among those aged
                                                 10-12 with rates of
                                                 28.8% for grass and
                                              34.2% for ragweed. Trees
                                                were common outdoor
                                               exposure sensitizers in
                                                all age groups. Limit:
                                               given the retrospective
                                                   not all patients
                                                  received the same

NHANES: National Health and Nutrition Examination Survey. Note.
(a) used modeling to estimate ambient pollen exposure.
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Author:Pollock, Jenna; Shi, Lu; Gimbel, Ronald W.
Publication:Canadian Respiratory Journal
Article Type:Report
Geographic Code:100NA
Date:Jan 1, 2017
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