INTRODUCTION
Cystic fibrosis (CF), an autosomal recessive disorder, is characterized by chronic endobronchial bacterial infection causing progressive pulmonary function decline and structural airway damage ultimately resulting in premature death. Pseudomonas aeruginosa (Pa), an environmentally ubiquitous Gram-negative bacterium, is the sentinel respiratory pathogen in CF patients. Chronic infection with this organism is seen in ~80% of US CF patients [Reference Demko, Byard and Davis1–4], and earlier Pa acquisition is associated with increased morbidity and mortality [Reference Emerson2]. Initial Pa acquisition typically occurs in the first few years of life [4]; these initial Pa clinical isolates typically resemble those found in the natural environment in that they are non-mucoid and antibiotic susceptible [Reference Burns5]. Subsequently, chronic Pa infection occurs through adaptation of Pa strains to the individual respiratory milieu [Reference Godard, Plesiat and Michel-Briand6–Reference Speert8] and is generally characterized by mucoid and antibiotic-resistant communities [Reference Burns5, Reference Speert9]. Therefore, early aggressive Pa eradication is recommended following initial infection [Reference Hoiby, Frederiksen and Pressler10].
Development of effective Pa prevention strategies outside of infection control guidelines in the clinical care setting [Reference Griffiths11, Reference Jones12] have been limited due to an incomplete understanding of both the aetiology of and risk factors for initial Pa acquisition. The basic defect in the cystic fibrosis transmembrane conductance regulator (CFTR) is clearly implicated in the pathophysiology of Pa infection [Reference Gibson, Burns and Ramsey13]; however, the numerous studies that have investigated demographic [Reference Kerem14–Reference Maselli16] and home environmental [Reference Rosenfeld17] factors, genetic modifiers [Reference Arkwright18, Reference Meyer, Braun and Roscher19], as well as newborn screening [Reference Baussano20, Reference Sims21] have yet to identify individual-level modifiable or non-modifiable risk factors that are highly predictive of Pa acquisition.
Recognition that the natural environment is the likely source of initial Pa acquisition has resulted in recent efforts to identify macroenvironmental factors that could potentially influence Pa acquisition [Reference Collaco22–Reference Psoter24], as these factors may influence incidence of infectious diseases by affecting the propagation and virulence of the microorganism in the environment, the host's immunity, and the interaction of the host with the natural environment [Reference Fisman25]. For young children with CF, previous studies have reported that seasonal differences for incident Pa acquisition vary by climatic zone [Reference Psoter24] and temperature is associated with prevalent Pa infection [Reference Collaco22], while geographical differences in time of initial Pa acquisition differ between urban and rural environments [Reference Ranganathan23] and within the United States [Reference Psoter26]. To date, no study has performed a comprehensive analysis of both meteorological and geographical variables and time to initial Pa acquisition.
In line with this research direction and to fill a current gap in our understanding of initial Pa acquisition, the objective of this study was to evaluate the association between specific meteorological, and geographical factors and the risk of initial Pa acquisition in young children with CF in the United States. Identification of meteorological and geographical factors associated with Pa acquisition could potentially contribute to our understanding of the aetiology of infection, as well as guide future Pa prevention strategies.
METHODS
Study population and design
We conducted a retrospective cohort study to evaluate the association of selected meteorological and geographical variables with time to initial Pa acquisition in young children with CF using data from the U.S. Cystic Fibrosis Foundation National Patient Registry from 2003 to 2009. The Registry contains detailed encounter based data on individual-level demographic and disease characteristics for approximately 80% of CF patients in the United States [Reference FitzSimmons27].
The study population included all children residing in the contiguous 48 states born after 31 December 2002 (all children were aged <7 years at study completion) with at least one respiratory culture recorded in the Registry prior to age 2 years. Additionally, to investigate incident Pa infection, children were excluded from the study population if Pa was isolated from the first recorded respiratory culture. This study was approved by the Institutional Review Board of the University of Washington and the Cystic Fibrosis Foundation Registry Committee.
Pa acquisition
The primary outcome of interest was time to initial Pa acquisition, defined as the date of first Pa-positive respiratory culture recorded in the Registry. Current clinical recommendations include quarterly (i.e. four times per year) respiratory culturing [28], which in this young population is usually performed by oropharyngeal swab. In children who acquired Pa, the exact date of Pa acquisition was unknown. Rather, Pa acquisition was only observed to have occurred within the time interval between the date of previous negative Pa culture (left-hand endpoint of acquisition interval) and the date of positive Pa culture (right-hand endpoint of acquisition interval).
Exposure variables
Using individual-level zip code data from the Registry, subjects were spatially referenced to the corresponding zip code centroid using ArcGIS version 10·1 (ESRI, USA). Individual zip code was taken as that recorded in the year in which Pa was acquired (for those children who acquired Pa) or year of last clinical visit (for those who remained Pa free). Data for the meteorological variables temperature (°C), dew point (a measure for absolute humidity; °C), and rainfall (mm) were obtained from the National Oceanic and Atmospheric Administration (NOAA) National Climate Data Center (NCDC) Cooperative Summary of the Day. This database includes location and daily summary measures of selected meteorological variables from a network of climate monitoring stations located throughout the United States. Daily summary measures were extracted for each day during the study period, from 1 January 2003 to 31 December 2009. Each monitoring station was then geocoded using ArcGIS; individual exposures were assigned based on data of the nearest monitor from the individual's zip code centroid, which was based on the shortest (linear) distance from zip code centroid to monitoring station. Data were limited to those stations with complete daily data over the time period.
Individual-level exposure was based on the mean daily average for each of the meteorological variables over the 365-day period prior to date of Pa acquisition, the left-hand endpoint of the acquisition interval (or last recorded negative culture). For those children who were observed for less than a 1-year period, either due to censoring or Pa acquisition, exposure included only those days for which the child was at risk for Pa acquisition.
For each zip code centroid the following residential geographical variables were collected: latitude, longitude, elevation (using the National Elevation Dataset; http://ned.usgs.gov) and distance to a freshwater body (defined as the shortest straight-line distance from zip code centroid to the nearest freshwater body using the National Hydrographic Dataset; http://nhd.usgs.gov). We evaluated several definitions of freshwater body: (1) river/stream, (2) lake, (3) wetland, and (4) any freshwater body. Urban/rural status was also determined using the Rural Urban Commuting Area Codes (RUCA, version 2.0) and categorized as urban, large rural, small rural, or isolated area [29].
Statistical analysis
Demographic and disease characteristics were compared between children who acquired Pa and those that remained Pa free during follow-up. Group comparisons were made using Student's t tests with unequal variances and χ 2 tests for continuous and categorical variables, respectively.
Time to Pa acquisition was analysed using Weibull regression with interval-censored outcomes, as previously described [Reference Psoter26]. Children entered risk sets upon first encounter recorded in the Registry. Patients who remained Pa free at last encounter recorded prior to 1 January 2010 were right-censored; censoring time was based on the date of last encounter. Initially, univariate analyses were performed to examine associations between each exposure variable of interest and time to Pa acquisition. Multivariable regression was then used to evaluate the association of each of the exposure variables after adjustment for individual-level demographic and disease characteristics. Each of these models was adjusted for a priori-identified variables that could potentially be associated with Pa acquisition including, sex, race [white vs. non-white (95% of US CF patients are white)], ethnicity (Hispanic vs. non-Hispanic), insurance status (any private vs. no private), CFTR gene functional class [high risk: CFTR mutations on both alleles resulting in minimal CFTR function (class 1, 2, or 3, including ΔF508); low risk: at least one allele with a mutation resulting in residual CFTR function (class 4 or 5); and unclassified: both alleles with unknown functional class, or one allele with minimal CFTR function and the second with unknown functional class] [Reference Green30–Reference Rowntree and Harris32], identified by CF newborn screening (yes/no), year of birth, and culture frequency (number of cultures performed divided by number of days under observation to censoring or Pa acquisition). Next, two separate multivariable regression models evaluated the associations between each set of predictor variables: (1) meteorological and (2) geographical and time to Pa acquisition, adjusting for the previously described individual characteristics and either meteorological or geographical factors; these will be referred to as the meteorological-only and geographical-only models. Finally, a fully adjusted analysis incorporating all meteorological and geographical predictors, as well as individual-level demographic and disease characteristics, was performed.
Results of regression models are presented as hazard ratios (HRs) with corresponding 95% confidence intervals (CIs). For these analyses, we report HRs for a 1 °C increase in temperature and dew point, and a 1 mm increase in rainfall, 1° increase in latitude (northing) and longitude (easting), a 100 m increase in elevation, and a 10 km increase in distance to a water body. A two-sided P value <0·05 was considered statistically significant for all analyses. All analyses were conducted using R version 3.0.1 [33].
RESULTS
A total of 3463 children met the eligibility criteria and were included in the final study population. Patients were followed for a median of 2·2 years (25th–75th percentiles: 1·1–3·8), during which time 1659 (48%) acquired Pa. The mean age of Pa acquisition in those that acquired Pa was 1·3 years (s.d. = 0·4 years). The demographic and disease characteristics of the study population by Pa acquisition status are presented in Table 1. Compared to those who remained Pa free during follow-up, children acquiring Pa were more likely to be female (52 vs. 49%), have a high risk CFTR genotype (76 vs. 62%) and not be identified with CF by newborn screening (36 vs. 51%).
Table 1. Distribution of demographic and disease characteristics in young children with cystic fibrosis from 2003 to 2009, by Pseudomonas aeruginosa acquisition status
Pa, Pseudomonas aeruginosa; s.d., standard deviation; CFTR, cystic fibrosis transmembrane conductance regulator.
* Based on χ 2 tests for categorical variables or t test with unequal variances for continuous variables.
† CFTR mutation class is defined as follows: High risk, includes children in which CFTR mutations on both alleles result in minimal CFTR function (class 1, 2, or 3), including ΔF508. Low risk, at least one allele with a mutation resulting in partial CFTR function (class 4 or 5). Unclassified, both alleles with unknown functional class, or one allele with high risk CFTR function and the second with unknown functional class.
Overall, the median distance of subjects to the nearest meteorological monitoring station was 5·8 km (95% CI 5·5–6·1 km). Table 2 compares the average daily meteorological and geographical characteristics between children who acquired Pa during follow-up and those that remained Pa free. Compared to children who remained Pa free, those acquiring Pa during follow-up were more likely to reside at locations with higher average daily temperature (13·8 vs. 12·9 °C), dew point (6·8 vs. 5·7 °C) and rainfall (0·14 vs. 0·12 mm). Children who acquired Pa during follow-up, on average, resided at lower latitudes and higher longitudes, resided at a closer distance to a water body and at a lower elevation.
Table 2. Distribution of meteorological and geographical variables for young children with cystic fibrosis from 2003 to 2009, overall and by Pseudomonas aeruginosa acquisition status
* Reflects a statistically significant (P<0·05) difference between children remaining Pa free and those acquiring Pa during follow-up, based on a two-sided t test with unequal variances.
Results of the regression analyses evaluating the associations between meteorological and geographical variables and time to initial Pa acquisition are presented in Table 3. In univariate analyses (‘unadjusted’), increased temperature (HR 1·04, 95% CI 1·03–1·05), dew point (HR 1·05, 95% CI 1·04–1·06) and rainfall (HR 1·11, 95% CI 1·09–1·14) were associated with increased risk of Pa, while increasing latitude (HR 0·97, 95% CI 0·96–0·98) and elevation (HR 0·98, 95% CI 0·96–0·99) were found to be protective for Pa acquisition. Distance to freshwater body was not associated with time to initial Pa acquisition. After adjustment for potential confounding demographic and clinical variables (‘adjusted’), similar magnitudes of association for these factors and Pa acquisition were found. Comparable results were also obtained in the multivariable meteorological- and geographical-group-adjusted regression models. In the meteorological-only group-adjusted model, inclusion of both temperature and dew point in the model resulted in a substantially attenuated risk estimate for temperature (HR 1·00, 95% CI 0·98–1·02) and minimal change for the point estimate of the dew point variable (HR 1·05, 95% CI 1·02–1·07). Temperature and dew point were highly correlated variables (ρ = 0·81). In the geographical-only group-adjusted model, a 1 unit (northing) increase in latitude was associated with a 2% decreased risk for Pa acquisition (95% CI 1·0–4·0), and there was a similar association per 100 m gain in elevation (HR 0·98, 95% CI 0·97–0·99). In this model, distance to any freshwater body was selected as the distance to water body variable and was not associated with Pa acquisition; results for distance to each specific water body type (river/stream, lake, wetland) were evaluated and resulted in nearly identical risk estimates. As distance to any or each individual water body type (river/stream, lake, wetland) resulted in similar, non-statistically significant risk estimates in models, we present results for distance to any freshwater body for this and the fully adjusted model, as this represents the shortest distance to a water body for each individual.
Table 3. Results of univariate and multivariable Weibull regression analyses evaluating the association between selected meteorological and geographical risk factors and time to initial Pseudomonas aeruginosa acquisition in young children with cystic fibrosis, 2003–2009
HR, Hazard ratio; CI, confidence interval; RUCA, Rural Urban Commuting Area Codes.
* Adjusted for individual-level demographic and disease characteristics, including sex, race, ethnicity, insurance status, CFTR functional class, identification by newborn screening, year of birth, and culture frequency.
† Meteorological and geographical predictors analysed in separate models (‘meteorological-only’ and ‘geographical-only’), adjusted for individual-level characteristics, and either meteorological or geographical factors.
‡ Meteorological and geographical predictors analysed in the same model, adjusted for individual-level, and both meteorological and geographical factors.
The fully adjusted regression model included both meteorological and geographical variables, as well as patient demographic and disease characteristics. After adjustment for geographical variables, the association of time to Pa acquisition and temperature (HR 1·13, 95% CI 1·08–1·17) and dew point (HR 1·10, 95% CI 1·07–1·13) were more prominent. Independent inclusion of temperature or dew point in this final model resulted in similar point estimates for these variables, 1·14 (95% CI 1·10–1·18) and 1·13 (95% CI 1·10–1·16), respectively, with no corresponding change in inference for other covariates. By contrast, in this model, increases in geographical variables (latitude and longitude) were found to be associated with increased risk of Pa acquisition.
DISCUSSION
In this study both meteorological factors, including increased temperature, dew point and rainfall and the residential geographical variables of latitude, longitude, and elevation, were associated with increased risk of initial Pa acquisition in a large cohort of young children with CF in the United States. These results suggest that meteorological and geographical factors, some previously unreported, may play a role in initial Pa infection in CF patients. Although these reported associations do not provide specific guidance for the development of Pa prevention strategies, they may guide future research focused on understanding the role of environmental factors in the aetiology of Pa infection. Strengths of the present study include a large national study population of Pa-negative children and data for meteorological and geographical exposure variables from a time period shortly preceding initial acquisition of Pa.
Comparison of the results obtained in this study to others is limited. Collaco et al. [Reference Collaco22], while focusing on Pa prevalence rather than incidence, found similar risk factors; they reported an association between increased ambient temperature and prevalence of Pa in young CF patients in both the United States and Australia. They used a 30-year (1961–1990) long-term monthly and annual summary for temperature and relative humidity. In the present study Pa incidence was evaluated in relation to short-term summary measures for temperature, dew point, and rainfall in the year preceding initial Pa acquisition, allowing for a more clear characterization of the temporality of these associations. Additionally, we have reported the associations for each of the meteorological and geographical factors after adjustment for both demographic and disease characteristics. The median age of initial Pa in the current study is younger than that reported in previous investigations [Reference Rosenfeld17, Reference Green34–Reference Tramper-Stranders36] and likely reflects the eligibility criteria for the current cohort. Children were only included in our study population if they were diagnosed with CF prior to age 2 years, whereas children in the prior cohorts were not required to be diagnosed in infancy.
Ranganathan et al. [Reference Ranganathan23] explored the geographical variation of initial Pa acquisition in 105 young children with CF in the Australian state of Victoria. In that study, the odds of Pa acquisition was increased in children residing outside Melbourne compared to those living in Melbourne (odds ratio 4·08, 95% CI 1·55–11·30), although the age of acquisition between these two groups did not significantly differ. Results obtained from an environmental questionnaire identified only one factor associated with increased odds of acquisition, i.e. water sprinkling system use. In the present study, we adjusted for urban/rural status, although no statistically significant associations were found for rural/urban status and risk of Pa acquisition. Kopp and colleagues [Reference Kopp37] have described a higher prevalence of Pa in CF patients in the CF National Patient Registry residing in the southern United States compared to other regions, concordant with our findings of earlier age at Pa acquisition in lower latitudes.
We have previously reported increased Pa acquisition in summer [incidence rate ratio (IRR): 1·22, 95% CI 1·07–1·40] and autumn (IRR 1·34, 95% CI 1·18–1·52) months compared to winter months in patients in the US CF Registry [Reference Psoter24]. These seasonal differences were also found to differ between climatic zones, suggesting that climatic factors may contribute to risk of initial Pa acquisition. Subsequently, we found that the risk of initial Pa acquisition differed geographically in US CF patients, with spatial variation accounting for approximately 45% of the residual risk for Pa acquisition [Reference Psoter26], further strengthening the hypothesis that environmental factors are implicated in initial Pa acquisition.
The present analysis accounted for geographical variability through adjustment for both latitude and longitude. Interestingly, when both meteorological and geographical variables were considered in the same model, larger effect sizes for meteorological variables were observed while point estimates for several of the geographical variables changed direction, indicating that both geographical and meteorological variables should be incorporated into models when evaluating the effects of other environmental factors on Pa acquisition. Although interpretation of the fully adjusted model becomes more difficult with the inclusion of additional variables, the association of geographical factors and the risk of Pa acquisition were influenced by inclusion of meteorological variables. These findings are likely due to the complex relationships between climate and geography. For example, in the geographical-only model, increasing elevation was found to be protective for Pa acquisition; however, this observed association may reflect a temperature effect as temperature generally increases with increasing elevation. After adjusting for temperature, the protective effect associated with increased elevation was no longer observed. Accordingly, when conditioning on all predictors, it is possible that other potential pathways of association were not captured by the included variables.
The importance of environmental conditions for understanding the epidemiology of many infectious disease processes has been well described [Reference Fisman25, Reference Fisman38], and includes impacts associated with both the host behaviours and susceptibility, as well as the pathogen proliferation within the environment [Reference Lafferty39–Reference McMichael, Woodruff and Hales41]. Although Pa is ubiquitous in the environment, little is known about the biogeography of Pa in the United States and elsewhere. Further, the geoepidemiology of Pa infections has not been well described, primarily due to infrequent infections in immunocompetent individuals.
There are several limitations of the present study. First, precise timing of Pa acquisition in the study population was unknown due to the non-acute, subclinical nature of Pa infection. However, US CF patients typically have respiratory cultures performed every 3 months and we used interval-censored outcomes to account for the uncertainty of acquisition date. Second, the observed effect size estimates for several of the meteorological and geographical risk factors were relatively modest and may reflect unmeasured confounding such as host behaviour (e.g. outdoor activity time). Third, zip code centroid was used as a proxy variable for residence location for the study population. This variable may have introduced misclassification of several of our exposures. However, this misclassification would likely be non-differential by outcome status. Fourth, this study only explored select meteorological and geographical risk factors and their association with initial Pa acquisition. Exposures in the home environment may also influence initial Pa acquisition and future studies may consider a comprehensive analysis of such factors. Similarly, while strains of Pa isolated at the time of initial infection of young CF patients are generally similar to those found in the natural environment [Reference Kidd42], cross-infection or nosocomial acquisition cannot be ruled out. Finally, the current results reflect upper airway (oropharyngeal) rather than lower airway culture results. Rosenfeld et al. [Reference Rosenfeld43] evaluated the diagnostic accuracy of oropharyngeal cultures compared to simultaneous bronchoalveolar lavage and found better specificity (95%) than sensitivity (44%) for detection of lower airway Pa. Nonetheless, oropharyngeal swabs are standard of care for assessment of respiratory cultures in pre-expectorating patients in the United States, and acquisition of Pa in the upper airway is generally considered an important clinical outcome.
In conclusion, meteorological and geographical factors, particularly increased temperature, dew point and rainfall were found to be associated with time to initial Pa acquisition in young children with CF. Future research to evaluate the manner in which these factors contribute to Pa acquisition may inform our understanding of the aetiology of initial Pa acquisition and provide insight for preventive strategies in this population.
ACKNOWLEDGEMENTS
The authors thank the Cystic Fibrosis Foundation for the use of CF Foundation Patient Registry data to conduct this study. Additionally, we thank the patients, care providers, and clinic coordinators at CF Centers throughout the United States for their contributions to the CF Foundation Patient Registry.
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
DECLARATION OF INTEREST
None.
