Patterns and determinants of exhaled nitric oxide trajectories in schoolchildren over a 7-year period.

Fractional exhaled nitric oxide (F ENO50 ), a marker of allergic airway inflammation, is used in respiratory research and asthma clinical care; however, its trajectory with increasing age during childhood has not been well characterised. We examined F ENO50 longitudinally during a period of important somatic growth to describe trajectories across childhood and adolescence in healthy participants and evaluate clinical factors as potential determinants of trajectories.F ENO50 was collected at six visits over 8 years in a population-based cohort of 1791 schoolchildren without asthma (median age at entry 8.4 years). Smooth sex-specific F ENO50 trajectories were estimated using generalised additive mixed models, with participant-level random effects. We evaluated whether sex-specific trajectories were influenced by race/ethnicity, body mass index (BMI) percentile, allergic rhinitis or puberty.Different F ENO50 patterns were observed by sex in later childhood and several factors were associated with either F ENO50 level or change in F ENO50 as participants aged. F ENO50 -age trajectories were similar by sex until age ∼11.5 years, after which males had greater F ENO50 change than females. This divergence in F ENO50 -age trajectories coincides with puberty. Males with higher starting BMI percentile had attenuated F ENO50 -age slopes. Among males, F ENO50 levels were lower in non-Hispanic white subjects. Among both sexes, participants with rhinitis had higher F ENO50 F ENO50 levels within individuals tracked over time; however, there was considerable variation in F ENO50 patterns across participants.F ENO50 trajectories from longitudinal data provide evidence of sex differences coinciding with puberty, suggesting potential hormone link. Improved understanding of determinants of F ENO50 trajectories is needed to realise the potential for using individualised predicted F ENO50 trajectories.

Association of improved air quality with lung development in children.

BACKGROUND: Air-pollution levels have been trending downward progressively over the past several decades in southern California, as a result of the implementation of air quality-control policies. We assessed whether long-term reductions in pollution were associated with improvements in respiratory health among children. METHODS: As part of the Children's Health Study, we measured lung function annually in 2120 children from three separate cohorts corresponding to three separate calendar periods: 1994-1998, 1997-2001, and 2007-2011. Mean ages of the children within each cohort were 11 years at the beginning of the period and 15 years at the end. Linear-regression models were used to examine the relationship between declining pollution levels over time and lung-function development from 11 to 15 years of age, measured as the increases in forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) during that period (referred to as 4-year growth in FEV1 and FVC). RESULTS: Over the 13 years spanned by the three cohorts, improvements in 4-year growth of both FEV1 and FVC were associated with declining levels of nitrogen dioxide (P<0.001 for FEV1 and FVC) and of particulate matter with an aerodynamic diameter of less than 2.5 µm (P= 0.008 for FEV1 and P<0.001 for FVC) and less than 10 µm (P<0.001 for FEV1 and FVC). These associations persisted after adjustment for several potential confounders. Significant improvements in lung-function development were observed in both boys and girls and in children with asthma and children without asthma. The proportions of children with clinically low FEV1 (defined as <80% of the predicted value) at 15 years of age declined significantly, from 7.9% to 6.3% to 3.6% across the three periods, as the air quality improved (P = 0.001). CONCLUSIONS: We found that long-term improvements in air quality were associated with statistically and clinically significant positive effects on lung-function growth in children. (Funded by the Health Effects Institute and others.).

Constrained Mixed-Effect Models with Ensemble Learning for Prediction of Nitrogen Oxides Concentrations at High Spatiotemporal Resolution.

Spatiotemporal models to estimate ambient exposures at high spatiotemporal resolutions are crucial in large-scale air pollution epidemiological studies that follow participants over extended periods. Previous models typically rely on central-site monitoring data and/or covered short periods, limiting their applications to long-term cohort studies. Here we developed a spatiotemporal model that can reliably predict nitrogen oxide concentrations with a high spatiotemporal resolution over a long time span (>20 years). Leveraging the spatially extensive highly clustered exposure data from short-term measurement campaigns across 1-2 years and long-term central site monitoring in 1992-2013, we developed an integrated mixed-effect model with uncertainty estimates. Our statistical model incorporated nonlinear and spatial effects to reduce bias. Identified important predictors included temporal basis predictors, traffic indicators, population density, and subcounty-level mean pollutant concentrations. Substantial spatial autocorrelation (11-13%) was observed between neighboring communities. Ensemble learning and constrained optimization were used to enhance reliability of estimation over a large metropolitan area and a long period. The ensemble predictions of biweekly concentrations resulted in an R2 of 0.85 (RMSE: 4.7 ppb) for NO2 and 0.86 (RMSE: 13.4 ppb) for NOx. Ensemble learning and constrained optimization generated stable time series, which notably improved the results compared with those from initial mixed-effects models.

Genetic and epigenetic susceptibility of airway inflammation to PM2.5 in school children: new insights from quantile regression.

BACKGROUND: The fractional concentration of exhaled nitric oxide (FeNO) is a biomarker of airway inflammation that has proved to be useful in investigations of genetic and epigenetic airway susceptibility to ambient air pollutants. For example, susceptibility to airway inflammation from exposure to particulate matter with aerodynamic diameter < =2.5 µm (PM2.5) varies by haplotypes and promoter region methylation in inducible nitric oxide synthase (iNOS encoded by NOS2). We hypothesized that PM2.5 susceptibility associated with these epigenetic and genetic variants may be greater in children with high FeNO from inflamed airways. In this study, we investigated genetic and epigenetic susceptibility to airborne particulate matter by examining whether the joint effects of PM2.5, NOS2 haplotypes and iNOS promoter methylation significantly vary across the distribution of FeNO in school children. METHODS: The study included 940 school children in the southern California Children's Health Study who provided concurrent buccal samples and FeNO measurements. We used quantile regression to examine susceptibility by estimating the quantile-specific joint effects of PM2.5, NOS2 haplotype and methylation on FeNO. RESULTS: We discovered striking differences in susceptibility to PM2.5 in school children. The joint effects of short-term PM2.5 exposure, NOS2 haplotypes and methylation across the FeNO distribution were significantly larger in the upper tail of the FeNO distribution, with little association in its lower tail, especially among children with asthma and Hispanic white children. CONCLUSION: School-aged children with higher FeNO have greater genetic and epigenetic susceptibility to PM2.5, highlighting the importance of investigating effects across the entire distribution of FeNO.

Traffic-related air pollution and alveolar nitric oxide in southern California children.

Mechanisms for the adverse respiratory effects of traffic-related air pollution (TRAP) have yet to be established. We evaluated the acute effects of TRAP exposure on proximal and distal airway inflammation by relating indoor nitric oxide (NO), a marker of TRAP exposure in the indoor microenvironment, to airway and alveolar sources of exhaled nitric oxide (FeNO).FeNO was collected online at four flow rates in 1635 schoolchildren (aged 12-15 years) in southern California (USA) breathing NO-free air. Indoor NO was sampled hourly and linearly interpolated to the time of the FeNO test. Estimated parameters quantifying airway wall diffusivity (DawNO) and flux (J'awNO) and alveolar concentration (CANO) sources of FeNO were related to exposure using linear regression to adjust for potential confounders.We found that TRAP exposure indoors was associated with elevated alveolar NO. A 10 ppb higher indoor NO concentration at the time of the FeNO test was associated with 0.10 ppb higher average CANO (95% CI 0.04-0.16) (equivalent to a 7.1% increase from the mean), 4.0% higher J'awNO (95% CI -2.8-11.3) and 0.2% lower DawNO (95% CI -4.8-4.6).These findings are consistent with an airway response to TRAP exposure that was most marked in the distal airways.

Spirometry effects on conventional and multiple flow exhaled nitric oxide in children.

OBJECTIVE: Clinical and research settings often require sequencing multiple respiratory tests in a brief visit. Guidelines recommend measuring the concentration of exhaled nitric oxide (FeNO) before spirometry, but evidence for a spirometry carryover effect on FeNO is mixed. Only one study has investigated spirometry carryover effects on multiple flow FeNO analysis. The objective of this study was to evaluate evidence for carryover effects of recent spirometry on three exhaled NO summary measures: FeNO at 50 ml/s, airway wall NO flux [J'awNO] and alveolar NO concentration [CANO] in a population-based sample of schoolchildren. METHODS: Participants were 1146 children (191 with asthma), ages 12-15, from the Southern California Children's Health Study who performed spirometry and multiple flow FeNO on the same day. Approximately, half the children performed spirometry first. Multiple linear regression was used to estimate differences in exhaled NO summary measures associated with recent spirometry testing, adjusting for potential confounders. RESULTS: In the population-based sample, we found no evidence of spirometry carryover effects. However, for children with asthma, there was a suggestion that exhaled NO summary measures assessed ≤6 min after spirometry were lower (FeNO: 25.8% lower, 95% CI: -6.2%, 48.2%; J'awNO: 15.1% lower 95% CI: -26.5%, 43.0%; and CANO 0.43 parts per billion lower, 95% CI: -0.12, 0.98). CONCLUSIONS: In clinical settings, it is prudent to assess multiple flow FeNO before spirometry. In studies of healthy subjects, it may not be necessary to assess FeNO first.

Associations of children's lung function with ambient air pollution: joint effects of regional and near-roadway pollutants.

BACKGROUND: Previous studies have reported adverse effects of either regional or near-roadway air pollution (NRAP) on lung function. However, there has been little study of the joint effects of these exposures. OBJECTIVES: To assess the joint effects of NRAP and regional pollutants on childhood lung function in the Children's Health Study. METHODS: Lung function was measured on 1811 children from eight Southern Californian communities. NRAP exposure was assessed based on (1) residential distance to the nearest freeway or major road and (2) estimated near-roadway contributions to residential nitrogen dioxide (NO2), nitric oxide (NO) and total nitrogen oxides (NOx). Exposure to regional ozone (O3), NO2, particulate matter with aerodynamic diameter <10 µm (PM10) and 2.5 µm (PM2.5) was measured continuously at community monitors. RESULTS: An increase in near-roadway NOx of 17.9 ppb (2 SD) was associated with deficits of 1.6% in forced vital capacity (FVC) (p=0.005) and 1.1% in forced expiratory volume in 1 s (FEV1) (p=0.048). Effects were observed in all communities and were similar for NO2 and NO. Residential proximity to a freeway was associated with a reduction in FVC. Lung function deficits of 2-3% were associated with regional PM10 and PM2.5 (FVC and FEV1) and with O3 (FEV1), but not NO2 across the range of exposure between communities. Associations with regional pollution and NRAP were independent in models adjusted for each. The effects of NRAP were not modified by regional pollutant concentrations. CONCLUSIONS: The results indicate that NRAP and regional air pollution have independent adverse effects on childhood lung function.

Longitudinal effects of air pollution on exhaled nitric oxide: the Children's Health Study.

OBJECTIVES: To assess the effects of long-term variations in ambient air pollutants on longitudinal changes in exhaled nitric oxide (FeNO), a potentially useful biomarker of eosinophilic airway inflammation, based on data from the southern California Children's Health Study. METHODS: Based on a cohort of 1211 schoolchildren from eight Southern California communities with FeNO measurements in 2006-2007 and 2007-2008, regression models adjusted for short-term effects of air pollution were fitted to assess the association between changes in annual long-term exposures and changes in FeNO. RESULTS: Increases in annual average concentrations of 24-h average NO2 and PM2.5 (scaled to the IQR of 1.8 ppb and 2.4 µg/m(3), respectively) were associated with a 2.29 ppb (CI 0.36 to 4.21; p=0.02) and a 4.94 ppb (CI 1.44 to 8.47; p=0.005) increase in FeNO, respectively, after adjustments for short-term effects of the respective pollutants. In contrast, changes in annual averages of PM10 and O3 were not significantly associated with changes in FeNO. These findings did not differ significantly by asthma status. CONCLUSIONS: Changes in annual average exposure to current levels of ambient air pollutants are significantly associated with changes in FeNO levels in children, independent of short-term exposures and asthma status. Use of this biomarker in population-based epidemiological research has great potential for assessing the impact of changing real world mixtures of ambient air pollutants on children's respiratory health.

Impact of different fixed flow sampling protocols on flow-independent exhaled nitric oxide parameter estimates using the Bayesian dynamic two-compartment model.

Exhaled nitric oxide (FeNO) is an established respiratory biomarker with clinical applications in the diagnosis and management of asthma. Because FeNO depends strongly on the flow (exhalation) rate, early protocols specified that measurements should be taken when subjects exhaled at a fixed rate of 50 ml/s. Subsequently, multiple flow (or "extended") protocols were introduced which measure FeNO across a range of fixed flow rates, allowing estimation of parameters including Caw NO and CA NO which partition the physiological sources of NO into proximal airway wall tissue and distal alveolar regions (respectively). A recently developed dynamic model of FeNO uses flow-concentration data from the entire exhalation maneuver rather than plateau means, permitting estimation of Caw NO and CA NO from a wide variety of protocols. In this paper, we use a simulation study to compare Caw NO and CA NO estimation from a variety of fixed flow protocols, including: single maneuvers (30, 50,100, or 300 ml/s) and three established multiple maneuver protocols. We quantify the improved precision with multiple maneuvers and the importance of low flow maneuvers in estimating Caw NO. We conclude by applying the dynamic model to FeNO data from 100 participants of the Southern California Children's Health Study, establishing the feasibility of using the dynamic method to reanalyze archived online FeNO data and extract new information on Caw NO and CA NO in situations where these estimates would have been impossible to obtain using traditional steady-state two compartment model estimation methods.

Exhaled nitric oxide in a population-based study of southern California schoolchildren.

BACKGROUND: Determinants of exhaled nitric oxide (FeNO) need to be understood better to maximize the value of FeNO measurement in clinical practice and research. Our aim was to identify significant predictors of FeNO in an initial cross-sectional survey of southern California schoolchildren, part of a larger longitudinal study of asthma incidence. METHODS: During one school year, we measured FeNO at 100 ml/sec flow, using a validated offline technique, in 2568 children of age 7-10 yr. We estimated online (50 ml/sec flow) FeNO using a prediction equation from a separate smaller study with adjustment for offline measurement artifacts, and analyzed its relationship to clinical and demographic characteristics. RESULTS: FeNO was lognormally distributed with geometric means ranging from 11 ppb in children without atopy or asthma to 16 ppb in children with allergic asthma. Although effects of atopy and asthma were highly significant, ranges of FeNO for children with and without those conditions overlapped substantially. FeNO was significantly higher in subjects aged > 9, compared to younger subjects. Asian-American boys showed significantly higher FeNO than children of all other sex/ethnic groups; Hispanics and African-Americans of both sexes averaged slightly higher than non-Hispanic whites. Increasing height-for-age had no significant effect, but increasing weight-for-height was associated with decreasing FeNO. CONCLUSION: FeNO measured offline is a useful biomarker for airway inflammation in large population-based studies. Further investigation of age, ethnicity, body-size, and genetic influences is needed, since they may contribute to substantial variation in FeNO.

Cluster-based bagging of constrained mixed-effects models for high spatiotemporal resolution nitrogen oxides prediction over large regions.

BACKGROUND: Accurate estimation of nitrogen dioxide (NO2) and nitrogen oxide (NOx) concentrations at high spatiotemporal resolutions is crucial for improving evaluation of their health effects, particularly with respect to short-term exposures and acute health outcomes. For estimation over large regions like California, high spatial density field campaign measurements can be combined with more sparse routine monitoring network measurements to capture spatiotemporal variability of NO2 and NOx concentrations. However, monitors in spatially dense field sampling are often highly clustered and their uneven distribution creates a challenge for such combined use. Furthermore, heterogeneities due to seasonal patterns of meteorology and source mixtures between sub-regions (e.g. southern vs. northern California) need to be addressed. OBJECTIVES: In this study, we aim to develop highly accurate and adaptive machine learning models to predict high-resolution NO2 and NOx concentrations over large geographic regions using measurements from different sources that contain samples with heterogeneous spatiotemporal distributions and clustering patterns. METHODS: We used a comprehensive Kruskal-K-means method to cluster the measurement samples from multiple heterogeneous sources. Spatiotemporal cluster-based bootstrap aggregating (bagging) of the base mixed-effects models was then applied, leveraging the clusters to obtain balanced and less correlated training samples for less bias and improvement in generalization. Further, we used the machine learning technique of grid search to find the optimal interaction of temporal basis functions and the scale of spatial effects, which, together with spatiotemporal covariates, adequately captured spatiotemporal variability in NO2 and NOx at the state and local levels. RESULTS: We found an optimal combination of four temporal basis functions and 200 m scale spatial effects for the base mixed-effects models. With the cluster-based bagging of the base models, we obtained robust predictions with an ensemble cross validation R2 of 0.88 for both NO2 and NOx [RMSE (RMSEIQR): 3.62 ppb (0.28) and 9.63 ppb (0.37) respectively]. In independent tests of random sampling, our models achieved similarly strong performance (R2 of 0.87-0.90; RMSE of 3.97-9.69 ppb; RMSEIQR of 0.21-0.27), illustrating minimal over-fitting. CONCLUSIONS: Our approach has important implications for fusing data from highly clustered and heterogeneous measurement samples from multiple data sources to produce highly accurate concentration estimates of air pollutants such as NO2 and NOx at high resolution over a large region.

Exposure measurement error in air pollution studies: A framework for assessing shared, multiplicative measurement error in ensemble learning estimates of nitrogen oxides.

BACKGROUND: Increasingly ensemble learning-based spatiotemporal models are being used to estimate residential air pollution exposures in epidemiological studies. While these machine learning models typically have improved performance, they suffer from exposure measurement error that is inherent in all models. Our objective is to develop a framework to formally assess shared, multiplicative measurement error (SMME) in our previously published three-stage, ensemble learning-based nitrogen oxides (NOx) model to identify its spatial and temporal patterns and predictors. METHODS: By treating the ensembles as an external dosimetry system, we quantified shared and unshared, multiplicative and additive (SUMA) measurement error components in our exposure model. We used generalized additive models (GAMs) with a smooth term for location to identify geographic locations with significantly elevated SMME and explain their spatial and temporal determinants. RESULTS: We found evidence of significant shared and unshared multiplicative error (p < 0.0001) in our ensemble-learning based spatiotemporal NOx model predictions. Unshared multiplicative error was 26 times larger than SMME. We observed significant geographic (p < 0.0001) and temporal variation in SMME with the majority (43%) of predictions with elevated SMME occurring in the earliest time-period (1992-2000). Densely populated urban prediction regions with complex air pollution sources generally exhibited highest odds of elevated SMME. CONCLUSIONS: We developed a novel statistical framework to formally evaluate the magnitude and drivers of SMME in ensemble learning-based exposure models. Our framework can be used to inform building future improved exposure models.

Significance of green granules in neutrophils and monocytes.

Intracytoplasmic green granules in neutrophils have been the subject of conjecture and discussion. Sometimes nicknamed "death cells," these granules are often associated with severe liver disease and have been said to predict acute bad outcomes in severely ill patients. Some recommend that the laboratory community report these granules to treating clinicians as an indication of poor prognosis. We report two patients presenting with secondary liver disease who were found to have blue-green neutrophilic inclusions on the peripheral blood smear. One patient died, while the other patient recovered. We propose that this morphologic finding is likely transient and is related to liver disease and that recovery is possible. Additionally, prognosis in intensive care units continues to be determined by a number of variables, such as age, comorbidities, and severity of illness.

Short-term effects of airport-associated ultrafine particle exposure on lung function and inflammation in adults with asthma.

BACKGROUND: Exposure to ultrafine particles (UFP, particles with aerodynamic diameter < 100 nm) is associated with reduced lung function and airway inflammation in individuals with asthma. Recently, elevated UFP number concentrations (PN) from aircraft landing and takeoff activity were identified downwind of the Los Angeles International Airport (LAX) but little is known about the health impacts of airport-related UFP exposure. METHODS: We conducted a randomized crossover study of 22 non-smoking adults with mild to moderate asthma in Nov-Dec 2014 and May-Jul 2015 to investigate short-term effects of exposure to LAX airport-related UFPs. Participants conducted scripted, mild walking activity on two occasions in public parks inside (exposure) and outside (control) of the high UFP zone. Spirometry, multiple flow exhaled nitric oxide, and circulating inflammatory cytokines were measured before and after exposure. Personal UFP PN and lung deposited surface area (LDSA) and stationary UFP PN, black carbon (BC), particle-bound PAHs (PB-PAH), ozone (O3), carbon dioxide (CO2) and particulate matter (PM2.5) mass were measured. Source apportionment analysis was conducted to distinguish aircraft from roadway traffic related UFP sources. Health models investigated within-subject changes in outcomes as a function of pollutants and source factors. RESULTS: A high two-hour walking period average contrast of ~34,000 particles·cm-3 was achieved with mean (std) PN concentrations of 53,342 (25,529) and 19,557 (11,131) particles·cm-3 and mean (std) particle size of 28.7 (9.5) and 33.2 (11.5) at the exposure and control site, respectively. Principal components analysis differentiated airport UFPs (PN), roadway traffic (BC, PB-PAH), PM mass (PM2.5, PM10), and secondary photochemistry (O3) sources. A standard deviation increase in the 'Airport UFPs' factor was significantly associated with IL-6, a circulating marker of inflammation (single-pollutant model: 0.21, 95% CI = 0.08-0.34; multi-pollutant model: 0.18, 0.04-0.32). The 'Traffic' factor was significantly associated with lower Forced Expiratory Volume in 1 s (FEV1) (single-pollutant model: -1.52, -2.28 to -0.77) and elevated sTNFrII (single-pollutant model: 36.47; 6.03-66.91; multi-pollutant model: 64.38; 6.30-122.46). No consistent associations were observed with exhaled nitric oxide. CONCLUSIONS: To our knowledge, our study is the first to demonstrate increased acute systemic inflammation following exposure to airport-related UFPs. Health effects associated with roadway traffic exposure were distinct. This study emphasizes the importance of multi-pollutant measurements and modeling techniques to disentangle sources of UFPs contributing to the complex urban air pollution mixture and to evaluate population health risks.

The effect of air pollution on lung development from 10 to 18 years of age.

BACKGROUND: Whether exposure to air pollution adversely affects the growth of lung function during the period of rapid lung development that occurs between the ages of 10 and 18 years is unknown. METHODS: In this prospective study, we recruited 1759 children (average age, 10 years) from schools in 12 southern California communities and measured lung function annually for eight years. The rate of attrition was approximately 10 percent per year. The communities represented a wide range of ambient exposures to ozone, acid vapor, nitrogen dioxide, and particulate matter. Linear regression was used to examine the relationship of air pollution to the forced expiratory volume in one second (FEV(1)) and other spirometric measures. RESULTS: Over the eight-year period, deficits in the growth of FEV(1) were associated with exposure to nitrogen dioxide (P=0.005), acid vapor (P=0.004), particulate matter with an aerodynamic diameter of less than 2.5 microm (PM(2.5)) (P=0.04), and elemental carbon (P=0.007), even after adjustment for several potential confounders and effect modifiers. Associations were also observed for other spirometric measures. Exposure to pollutants was associated with clinically and statistically significant deficits in the FEV(1) attained at the age of 18 years. For example, the estimated proportion of 18-year-old subjects with a low FEV(1) (defined as a ratio of observed to expected FEV(1) of less than 80 percent) was 4.9 times as great at the highest level of exposure to PM(2.5) as at the lowest level of exposure (7.9 percent vs. 1.6 percent, P=0.002). CONCLUSIONS: The results of this study indicate that current levels of air pollution have chronic, adverse effects on lung development in children from the age of 10 to 18 years, leading to clinically significant deficits in attained FEV(1) as children reach adulthood.

Bayesian estimation of physiological parameters governing a dynamic two-compartment model of exhaled nitric oxide.

The fractional concentration of nitric oxide in exhaled breath (feNO) is a biomarker of airway inflammation with applications in clinical asthma management and environmental epidemiology. feNO concentration depends on the expiratory flow rate. Standard feNO is assessed at 50 mL/sec, but "extended NO analysis" uses feNO measured at multiple different flow rates to estimate parameters quantifying proximal and distal sources of NO in the lower respiratory tract. Most approaches to modeling multiple flow feNO assume the concentration of NO throughout the airway has achieved a "steady-state." In practice, this assumption demands that subjects maintain sustained flow rate exhalations, during which both feNO and expiratory flow rate must remain constant, and the feNO maneuver is summarized by the average feNO concentration and average flow during a small interval. In this work, we drop the steady-state assumption in the classic two-compartment model. Instead, we have developed a new parameter estimation approach based on measuring and adjusting for a continuously varying flow rate over the entire feNO maneuver. We have developed a Bayesian inference framework for the parameters of the partial differential equation underlying this model. Based on multiple flow feNO data from the Southern California Children's Health Study, we use observed and simulated NO concentrations to demonstrate that our approach has reasonable computation time and is consistent with existing steady-state approaches, while our inferences consistently offer greater precision than current methods.

Dog ownership enhances symptomatic responses to air pollution in children with asthma.

BACKGROUND: Experimental data suggest that asthma exacerbation by ambient air pollutants is enhanced by exposure to endotoxin and allergens; however, there is little supporting epidemiologic evidence. METHODS: We evaluated whether the association of exposure to air pollution with annual prevalence of chronic cough, phlegm production, or bronchitis was modified by dog and cat ownership (indicators of allergen and endotoxin exposure). The study population consisted of 475 Southern California children with asthma from a longitudinal cohort of participants in the Children's Health Study. We estimated average annual ambient exposure to nitrogen dioxide, ozone, particulate matter < 10, 2.5, and 10-2.5 microm in aerodynamic diameter (PM10, PM2.5, and PM10-2.5, respectively), elemental and organic carbon, and acid vapor from monitoring stations in each of the 12 study communities. Multivariate models were used to examine the effect of yearly variation of each pollutant. Effects were scaled to the variability that is common for each pollutant in representative communities in Southern California. RESULTS: Among children owning a dog, there were strong associations between bronchitic symptoms and all pollutants examined. Odds ratios ranged from 1.30 per 4.2 microg/m3 for PM10-2.5 [95% confidence interval (CI), 0.91-1.87) to 1.91 per 1.2 microg/m3 for organic carbon (95% CI, 1.34-2.71). Effects were somewhat larger among children who owned both a cat and dog. There were no effects or small effects with wide CIs among children without a dog and among children who owned only a cat. CONCLUSION: Our results suggest that dog ownership, a source of residential exposure to endotoxin, may worsen the relationship between air pollution and respiratory symptoms in asthmatic children.

Childhood determination of Hodgkin lymphoma among U.S. servicemen.

BACKGROUND: Hodgkin lymphoma in young adults is inexplicably linked to economic development. METHODS: We conducted a nested case-control study of the 656 servicemen with Hodgkin lymphoma diagnosed between ages 17 to 32 while on active duty in the U.S. military during 1950-68. Controls, chosen randomly from the servicemen on duty at the time, were matched on service, birth year, and induction date. Information came from preinduction records and military records for the period ending at onset or the equivalent date. RESULTS: Risk was independently increased with small sib-ship size [OR, 2.3; confidence interval (CI), 1.6-3.5], low birth order (OR, 1.9; CI, 1.4-2.6), and an interval of at least 5 years between birth and that of a previous or subsequent sibling (OR, 2.1; CI, 1.5-3.1). Other factors independently and significantly associated with elevated risk of Hodgkin lymphoma were: tallness, high body mass index, more education (but not higher income) in the county of birth, BB or AB blood type, and past infectious mononucleosis (but a deficit of other childhood viral infections). Early fatherhood conveyed high risk (OR, 2.6; CI, 1.4-4.8), especially if with a high-risk sibling configuration. Factors unrelated to risk included personal education, preinduction or military occupation, induction test score, and rank. Findings were similar for nodular sclerosis and mixed cell histologic subtypes. CONCLUSIONS: Protection from the environment in childhood, but not in adulthood, increases the likelihood of young adult Hodgkin lymphoma, which may result from nonspecific isolation from early infections and/or exposure to late infection by a specific but unidentified ubiquitous childhood virus. IMPACT: Events in childhood protect against later Hodgkin lymphoma.

Determinants of Children's Exhaled Nitric Oxide: New Insights from Quantile Regression.

While the fractional concentration of exhaled nitric oxide (FeNO) has proven useful in asthma research, its exact role in clinical care remains unclear, in part due to unexplained inter-subject heterogeneity. In this study, we assessed the hypothesis that the effects of determinants of the fractional concentration of exhaled nitric oxide (FeNO) vary with differing levels of FeNO. In a population-based cohort of 1542 school children aged 12-15 from the Southern California Children's Health Study, we used quantile regression to investigate if the relationships of asthma, socio-demographic and clinical covariates with FeNO vary across its distribution. Differences in FeNO between children with and without asthma increased steeply as FeNO increased (Estimated asthma effects (in ppb) at selected 20th, 50th and 80th percentiles of FeNO are 2.4, 6.3 and 22.2, respectively) but the difference was steeper with increasing FeNO in boys and in children with active rhinitis (p-values<0.01). Active rhinitis also showed significantly larger effects on FeNO at higher concentrations of FeNO (Estimated active rhinitis effects (in ppb) at selected 20th, 50th and 80th percentiles of FeNO are 2.1, 5.7 and 14.3, respectively). Boys and children of Asian descent had higher FeNO than girls and non-Hispanic whites; these differences were significantly larger in those with higher FeNO (p-values<0.01). In summary, application of quantile regression techniques provides new insights into the determinants of FeNO showing substantially varying effects in those with high versus low concentrations.