Exposure to outdoor air pollution may increase the risk of pulmonary infection. Long-term exposure to higher levels of air pollutants (particulate matter ≤2.5 μm in aerodynamic diameter [PM 2.5 ] and nitrogen dioxide [NO 2 ]) is associated with increased hospitalization for community-acquired pneumonia (CAP) in older adults (1). Short-term air pollution exposure (including fine and coarse particulate matter [PM], ozone (O 3 ), sulfur dioxide, NO 2 , carbon monoxide, and total suspended particles) has been associated with increased hospital admissions (2–9), emergency department (ED) visits (10), and outpatient visits (11) for pneumonia in adults. Prior observational studies have identified pneumonia using only International Classification of Diseases, Ninth Revision (ICD-9), codes, and all have lacked granular clinical data needed to examine associations between air quality and severity; many have examined all respiratory admissions as a single outcome (2–8, 10). The effect of short-term PM 2.5 , NO 2 , and O 3 exposure on pneumonia frequency, severity, and mortality remains incompletely understood.

The Wasatch Front is a metropolitan region in north-central Utah that is mostly surrounded by mountains. Consequently, the region experiences periodic high levels of outdoor air pollution during wintertime temperature inversions and summertime heat. This dramatic variation in air quality, coupled with a rich clinical database of patients presenting to the ED with pneumonia, provided a unique opportunity to investigate the relationship between short-term elevations of air pollutants and the frequency and severity of pneumonia. We hypothesized that short-term elevated levels of PM 2.5 , NO 2 , or O 3 would be associated with the following:

We then calculated the potential impact fraction ( 25 , 26 ) and the number of averted cases associated with a decrease of daily average PM 2.5 concentrations to less than 12 μg/m 3 on all days. Cases were split into three groups: those patients who presented to the ED but not hospitalized, those who were hospitalized with pneumonia not classified as severe, and those hospitalized with severe pneumonia. Reduction in direct costs was estimated by multiplying the expected number of cases averted from each group by the median direct costs per case within each group. Statistical analyses were conducted using SAS 9.4 (SAS Institute) and R ( www.r-project.org ) software. This study was approved by the Intermountain Healthcare and University of Utah institutional review boards. The need for individual patient consent was waived.

A time-stratified case–crossover study was performed using a symmetrical 21-day interval to estimate the association between short-term exposure to PM 2.5 , NO 2 , O 3 , and pneumonia outcomes ( 21 ). We used conditional logistic regression models to estimate adjusted odds ratios (aORs), controlling for daily average temperature, humidity, and holidays. We estimated the daily effect of PM 2.5 within one week before presentation on the outcomes of interest by using a piecewise linear distributed lag model with a knot at 12 μg/m 3 ( 22 , 23 ), corresponding to an Air Quality Index of 50, below which air quality is categorized as “good” ( 24 ). For each day preceding presentation, we estimated the aOR associated with a 10-μg/m 3 increase above 12 μg/m 3 . We estimated the daily effect of NO 2 and O 3 within one week of presentation using a linear distributed lag model to estimate the aOR associated with a 10–parts per billion (ppb) pollutant increase.

We extracted five primary outcomes: radiographically confirmed pneumonia ED cases, hospital admissions, intensive care unit (ICU) admissions within 72 hours, and severe pneumonia cases. Severity was estimated by two measures: eCURB (17), a previously validated, electronically calculable 30-day mortality prediction tool derived from the features of the CURB-65 severity assessment score (confusion defined as {Abbreviated Mental Test Score ≤ 8}, blood urea nitrogen, respiratory rate, systolic and diastolic blood pressure, and age); and the 2007 severe CAP minor criteria score (respiratory rate ≥30 breaths/min, ratio of arterial oxygen pressure to fraction of inspired oxygen ≤250, presence of multilobar infiltrates on chest imaging, blood urea nitrogen ≥20 mg/dl, confusion, white blood cell count <4,000 cells/mm 3 , platelet count <100,000 cells/mm 3 , temperature <36°C, or hypotension requiring fluid resuscitation) ( 18 , 19 ). We defined severe pneumonia as eCURB-estimated 30-day mortality risk greater than or equal to 5% or as meeting at least three severe CAP minor criteria ( 13 , 20 ). Secondary outcomes included inpatient mortality and 30-day all-cause mortality after pneumonia diagnosis, identified by Intermountain Healthcare electronic records and Utah death certificates.

Daily PM 2.5 , NO 2 , and O 3 concentration data from all stations in Utah were extracted from the U.S. Environmental Protection Agency Air Quality System Data Mart ( 14 ). Daily temperature and humidity data were extracted from the Meso West climate data repository at the University of Utah ( 15 ). Residential addresses based on hospital records were geocoded using ArcMap version 10.2 (ESRI). Most subjects (94.9%) resided in an urban core area, with 1.4% residing in rural areas or small towns. Ten air basins were delineated on the basis of topography to represent regions with limited lateral air movement, particularly during stagnant conditions, and to identify air monitoring stations whose data would estimate air quality conditions for patients residing in those basins ( 16 ). Daily mean PM 2.5 , NO 2 , and 8-hour mean O 3 concentrations at each subject’s residence were estimated using an inverse distance squared weighted average of mean concentration data available for that day from all monitoring stations in the same air basin as the residence. This constraint ensured that data from stations in an adjacent mountain valley were not used in the estimation of the weighted average. Figure 1 illustrates the geographical locations of the monitoring stations, air basins, study EDs, and the geographical extent of patient residences.

We performed a secondary analysis of an existing dataset of adult pneumonia cases generated for a separate study previously described ( 12 , 13 ). Briefly, we identified all patients presenting to seven Wasatch Front Intermountain Healthcare EDs during two 12-month periods (December 2009 to November 2010 and December 2011 to November 2012) with a primary ICD-9 code consistent with pneumonia, as well as those with a primary diagnosis of respiratory failure or sepsis with pneumonia as a secondary diagnosis. We excluded patients with immunocompromised conditions, subsequent episodes of pneumonia for each patient in a 12-month period, and lack of radiographic evidence of pneumonia in ED chest imaging reports reviewed by three physicians, including two of the authors (N.C.D., B.E.J.). We then excluded 422 individuals residing in areas lacking air quality data.

We estimate that if PM 2.5 levels remained below 12 μg/m 3 , 76 to 112 cases of pneumonia would be averted annually in the population served by these seven hospitals, with most cases being those admitted to the hospital or those admitted with severe pneumonia ( Table 2 ). The total facility cost estimates associated with adverted cases ranges between $476,000 and $807,000 annually.

For the entire cohort, we found no significant positive associations with O 3 exposure and pneumonia outcomes, as well as a small negative association between O 3 exposure and ICU admission at Lag Days 5–7 ( Figure 3 , Table E3). We found modest associations between O 3 exposure and pneumonia instances and severity limited to younger adults and warmer months. Among younger adults (aged <65 yr), we found positive relationships between increased O 3 exposure over the 1 to 3 days before presentation and severe pneumonia (by severe CAP criteria, Lag Day 1 aOR, 1.02 per 10 ppb O 3 ; 95% CI, 1.01–1.04; and by eCURB criteria, Lag Day 1 aOR, 1.03; 95% CI, 1.01–1.04). Interestingly, we found no associations among patients older than 65 years of age ( Figure 4 , Table E3). O 3 associations were found during the warmer months (May to October), when increased O 3 exposure over 4–7 days before presentation was associated with increased ED visits for pneumonia (Lag Day 4 aOR, 1.004 per 10 ppb O 3 ; 95% CI, 1.00–1.01; and over 1–4 days before presentation with severe pneumonia by severe CAP criteria, Lag Day 1 aOR, 1.02; 95% CI, 1.01–1.03) ( Figure 5 , Table E3). O 3 associations with 30-day mortality and severe pneumonia were significantly modified by age, whereas associations with pneumonia cases and severe pneumonia were significantly modified by season (Table E4).

For colder months, we observed increasing positive associations between NO 2 and the pneumonia outcomes with statistically significant aORs for Lag Day 4 and earlier. For the warmer months, however, the aORs decreased with increasing lag period and were less than one and significant from Lag Day 2 onward ( Figure 5 ). The effects of NO 2 were significantly modified by season (Table E4). Table E2 includes all results for NO 2 age- and season-stratified models.

Increased NO 2 exposure 5–6 days before presentation was modestly associated with increased cases of pneumonia (Lag Day 5 aOR, 1.02 per 10 ppb NO 2 ; 95% CI, 1.0–1.05), and increased NO 2 exposure over 3 to 4 days before presentation was associated with increased 30-day mortality (Lag Day 3 aOR, 1.10 per 10 ppb NO 2 ; 95% CI, 1.00–1.21) ( Figure 3 , Table E2). Among adults aged 65 years and older, we found small associations between increased NO 2 exposure over the 2 to 5 days before presentation and mortality after pneumonia diagnosis, including inpatient mortality (Lag Day 4 aOR, 1.01 per 10 ppb NO 2 ; 95% CI, 1.0–1.03) and 30-day mortality (Lag Day 2 aOR, 1.02; 95% CI, 1.0–1.03). We found no associations among patients younger than 65 years old ( Figure 4 , Table E2). In tests for effect modification, the NO 2 association with 30-day mortality was significantly modified by age (Table E4).

For the colder months, we found significant associations between PM 2.5 greater than 12 μg/m 3 and diagnoses of pneumonia (largest aOR for pneumonia cases, 1.08 per 10 μg/m 3 on Lag Day 2; 95% CI, 1.01–1.16), hospital admission (Lag Day 1 aOR, 1.18; 95% CI, 1.03–1.35), ICU admission (Lag Day 6 aOR, 1.18; 95% CI, 1.01–1.37), and severe pneumonia by severe CAP criteria (Lag Day 1 aOR, 1.30; 95% CI, 1.05–1.61) or eCURB (Lag Day 6 aOR, 1.18; 95% CI, 1.01–1.37) up to a lag day of 6 ( Figure 5 ). We were unable to estimate season-stratified PM 2.5 associations with mortality, owing to small numbers. Among the 1,722 cases occurring during the warmer months, we found no significant relationships between PM 2.5 exposure and other outcomes.

For the entire cohort, we found a significant positive relationship between exposure to PM 2.5 concentrations above 12 μg/m 3 within 4–5 days before presentation and cases of pneumonia, hospital admission, ICU admission, severe pneumonia, and inpatient mortality ( Figure 3 ). When we stratified data by age ( Figure 4 ), we found a consistently positive relationship for adults aged 65 years and older between exposure to PM 2.5 concentrations above 12 μg/m 3 in the preceding 6 days and cases of pneumonia, hospital admission, ICU admission, and severe pneumonia by either definition. For pneumonia diagnoses, we found the relationship to be strongest on Lag Day 1 (aOR, 1.35 per 10 μg/m 3 above 12 μg/m 3 ; 95% confidence interval [CI], 1.16–1.57) and decreasing with longer lag periods. A typical temperature inversion episode resulting in a PM 2.5 increase of 30 μg/m 3 would thus be associated with 2.46 increased odds of a pneumonia diagnosis. This pattern was also found for hospitalization (Lag Day 1 aOR, 1.33; 95% CI, 1.12–1.58), severe CAP (Lag Day 1 aOR, 1.38; 95% CI, 1.06–1.80), ICU admission, and eCURB predicted mortality greater than or equal to 5% ( Figure 4 ; see also Table E1 in the online supplement). We found a significantly positive relationship between PM 2.5 greater than 12 μg/m 3 on Lag Days 4–5 and inpatient mortality (Lag Day 5 aOR, 1.50; 95% CI, 1.03–2.16), but no significant relationship with 30-day mortality. Among the 2,413 patients younger than 65 years of age, we found no significant relationship between PM 2.5 levels and any of these outcomes ( Figure 4 , Table E1). In tests for effect modification, PM 2.5 associations were significantly modified by age (Table E4).

We also observed seasonal patterns of pollutant concentrations, shown in Figure 2 . Elevated PM 2.5 levels occurred more often during colder months, with daily mean levels up to 75.6 μg/m 3 . Median daily NO 2 levels were nearly twice as high during colder months (22.0 vs. 11.8 ppb), with daily mean levels up to 57.3 ppb. Elevated O 3 levels occurred more often during warmer months, with daily 8-hour mean levels up to 91 ppb.

We identified 4,336 ED visits meeting inclusion criteria after exclusions during the study periods. Patient characteristics and outcomes are shown in Table 1 . The mean number of ED visits for pneumonia was 6.6 per day, of which 59.7% resulted in hospitalization, and 24.1% of which resulted in ICU admission within 72 hours. Similar numbers of cases were classified as severe pneumonia on the basis of eCURB predicted mortality greater than or equal to 5% (24.7%) or the presence of at least three severe CAP criteria (24.1%). Inpatient mortality was 3.3%, and 30-day mortality was 6.3%. A majority of patients (60%) presented in colder months (November to April).

Discussion Section: Choose Top of page Abstract Methods Results Discussion << References CITING ARTICLES

Among a large cohort of patients presenting to EDs with pneumonia in an area with periodic high levels of air pollution, we found strong associations between recent acute exposure to particulate air pollution and increased ED visits and hospitalizations for pneumonia, severe pneumonia, and mortality, particularly among older adults (≥65 yr old). We found modest associations between NO 2 and O 3 exposure and pneumonia instance and severity. The relationship between pollutants and pneumonia incidence and severity is year-round with an evident dose response. Effects of PM 2.5 exposure were evident during the colder months, when PM 2.5 is highest, and effects of O 3 during warmer months, when O 3 levels are highest, whereas effects of NO 2 exposure were observed across seasons with significant effect modification by season.

To our knowledge, our present study is the first to demonstrate a relationship between short-term air pollution exposure and pneumonia severity, measured by two validated quantitative measures of severity (eCURB and the severe CAP criteria) and admission to the ICU. Previous studies have demonstrated increased risk for pneumonia associated with air pollution exposure in adults (2–8, 10, 11, 27, 28), although none has examined severity of illness. Results from studies examining seasonal differences vary. In studies in Taipei and Kaohsiung, researchers observed significant associations with PM and NO 2 during both warmer and cooler days (5, 6, 27). In contrast to our findings, Medina-Ramón and colleagues (3) and Zanobetti and colleagues (2), whose studies included multiple U.S. cities, observed stronger associations between PM and pneumonia during warmer months. In our study, the effects of PM were observed during the colder months, likely reflecting the conditions along the Wasatch Front and in other areas of the western United States, where wintertime temperature inversions trap pollutants, leading to multiday periods of high PM levels. Effects were not modified by season, suggesting that PM 2.5 levels are independently associated with pneumonia cases and outcomes. Associations of O 3 exposure with pneumonia outcomes were seen during warmer months, when sunlight and higher temperatures drive the photochemical reactions responsible for generation of ground-level O 3 (16). The associations between NO 2 and pneumonia outcomes were positive in colder months and increased with lag days, whereas in warmer months, the associations were positive for short lag times, becoming negative for longer lag times. Because a reverse pattern occurred with O 3 and pneumonia diagnosis in the summer, these inconsistent results may be the result of confounding between NO 2 and O 3 , given the high negative correlation between the concentrations of these pollutants. NO 2 associations were significantly modified by season, likely reflecting influences of weather and of other pollutants.

We found positive associations between PM 2.5 and pneumonia outcomes, as well as modest associations between NO 2 exposure and mortality, among patients aged 65 years and older. Older adults are recognized as a vulnerable population for exposure to air pollution (29–31). Studies of older individuals have consistently found associations between adverse health effects and air pollution (1–3). Qiu and colleagues (8) also found adverse effects of PM in patients aged 65 years and older. Pneumonia mortality has been associated with long-term exposure to ambient air pollutants, including particulate matter, sulfur dioxide, and NO 2 (32, 33). Similarly, Fischer and colleagues (34) found an association between short-term air pollution exposure and increased daily pneumonia-specific mortality in the elderly. Older adults are generally at increased risk for pneumonia and may be more susceptible to the immune and inflammatory effects of air pollution exposure. It is likely that the effects of air pollution on pulmonary innate immunity are synergistic with other challenges to host defense in older adults, whereas the effects on younger individuals may be more subtle. Interestingly, O 3 exposure was associated with more severe disease in younger adults. This may reflect increased exposure due to time spent outdoors during warmer months.

Our findings are consistent with experimental studies which suggest that exposure to air pollutants results in changes in pulmonary host defense leading to increased susceptibility to pneumonia through several mechanisms. Animal models have demonstrated increased susceptibility to both bacterial and viral infection with exposure to PM (35, 36), NO 2 (37–40), and O 3 (41, 42). Laboratory studies have shown that exposure to PM and NO 2 results in impaired function of alveolar macrophages (43–46). Experimental exposure to any of the three pollutants impairs ciliary function of bronchial epithelial cells (37, 41, 47, 48). Exposure to pollutants also impacts cytokine production, with both suppressed release of cytokines in response to pathogens and production of proinflammatory cytokines (49–54). Through these mechanisms, air pollutants may induce a maladaptive inflammatory response in the lung and modify immune response to subsequent stimuli, such as infectious pathogens. Once an infection occurs, increased pulmonary and systemic inflammation may also contribute to greater pneumonia severity. Exposure to air pollution has been associated with increased markers of systemic (55–59) and pulmonary inflammation (56, 60–62). Particulate pollution therefore both disrupts pulmonary host defense and causes dysregulated responses that may contribute to increased severity of pneumonia in the infected individual.

Our study extends existing knowledge in several ways. The temporal variations in ambient air pollution levels that occur along the Wasatch Front during the winter allowed us to study the effects of short-term air pollution exposure in a single population. We used more rigorous inclusion criteria for cases of pneumonia and extracted granular patient-level clinical data that allowed us to define severe pneumonia objectively rather than based on clinician decisions, such as hospitalization or ICU admission (20). Confirmation of diagnosis using physician review of chest imaging reports excluded 30% of the cases identified by ICD-9 codes alone. This method of pneumonia case definition was 68% sensitive and 99% specific compared with the gold standard of physician review of ED case records (12). We coupled these case identification and clinical outcome measures with granular pollutant estimates based on patient residence. Using a distributed lag model enabled us to elucidate the multiple-day effects of a single day’s exposure, as has been demonstrated in prior studies of air pollution effects (23). This provides a more detailed estimation of effect and suggests that multiple-day exposures might lead to even stronger effects.

We also estimated the burden of illness and direct medical costs potentially attributable to air pollution. The system of seven hospitals in the present study had an estimated 76–112 additional cases of pneumonia annually that were attributable to high PM 2.5 levels, representing over $800,000 in annual direct medical costs. This is likely a fraction of the full economic burden of increased pneumonia cases attributable to air pollution when considering physician services, post–acute care costs, and indirect costs. The patient population studied represents approximately half of the population of the Wasatch Front, so our study suggests that short-term air pollution is a major economic and social burden for the entire valley due to its impact on respiratory disease. Our study thus has implications for policy pertaining to efforts to reduce PM 2.5 emissions.

We recognize several limitations to our study. We relied on ICD-9 codes to initially screen potential cases of pneumonia, and we identified only patients who presented to EDs. Our dataset excluded immunosuppressed patients and cases of recurrent pneumonia, and therefore we did not assess effects of air pollution exposure on these more complicated types of pneumonia. This is an opportunity for future study. Our study was observational, and thus unmeasured confounders such as seasonal variation in pathogens responsible for pneumonia may have contributed to the associations found. However, our study’s case–crossover design took into consideration this potential confounding by generating referent patients in the time span of 21 days. Exposure measures were imperfect because they were based on observations from a small number of stations. Similarly, the pollutant concentration estimates were made only for the place of residence and did not capture variability in exposure due to time spent indoors and at locations other than the primary residence. Compounds other than PM 2.5 , NO 2 , and O 3 may also have contributed to the pneumonia cases identified, and confounding may have been present because our models included only one pollutant at a time. The number of correlated parameters to be estimated relative to the sample size precluded estimating multipollutant models. Furthermore, our limited sample size did not allow us to incorporate more flexible lag effect structure, such as quadratic or cubic distributed lag. This limitation in model structure may contribute to artificial findings of protective seasonal effects of air pollution, especially NO 2 . In addition, given the large number of analyses conducted, false-positive findings due to multiplicity of analysis were a possibility. However, the consistent associations between pollutants, particularly PM 2.5 , and several pneumonia outcomes that remained after examination of effect modifications suggest a positive association that is consistent with other studies.