Small proline rich protein 2B (SPRR2B) is a skin and lung epithelial protein associated with allergic inflammation in mice that has not been evaluated in human atopic diseases.
To determine whether single-nucleotide polymorphisms (SNPs) in SPRR2B are associated with childhood eczema and with the phenotype of childhood eczema combined with asthma.
Genotyping for SPRR2B and filaggrin (FLG) was performed in 2 independent populations: the Cincinnati Childhood Allergy & Air Pollution Study (CCAAPS; N = 762; birth-age, 4 years) and the Greater Cincinnati Pediatric Clinical Repository (GCPCR;N = 1152; ages 5–10 years). Eczema and eczema plus asthma were clinical outcomes based on parental report and clinician’s diagnosis. Genetic analyses were restricted to whites and adjusted for sex in both cohorts and adjusted for environmental covariates in CCAAPS.
Variants in SPRR2B were not significantly associated with eczema in either cohort after Bonferroni adjustment. Children from both cohorts with the CC genotype of the SPRR2B rs6693927 SNP were at 4 times the risk for eczema plus asthma (adjusted odds ratio, 4.1; 95% confidence interval, 1.5– 10.9; P = .005 in CCAAPS; and adjusted odds ratio, 4.0; 95% confidence interval, 1.8 –9.1; P <.001 in the GCPCR), however. SNPs in SPRR2B were not in strong linkage disequilibrium with the R501X and del2282 FLG mutations, and these findings were independent of FLG.
An SNP in SPRR2B was predictive of asthma among white children with eczema from 2 independent populations. SPRR2B polymorphisms may serve as important predictive markers for the combined eczema plus asthma phenotype.
The specific cause(s) of asthma development must be identified in order to prevent this disease.
Our hypothesis was that specific mold exposures are associated with childhood asthma development.
Infants were identified from birth certificates. Dust samples were collected from 289 homes when the infants were age eight months. Samples were analyzed for concentrations of 36 molds that comprise the Environmental Relative Moldiness Index (ERMI) and endotoxin, house dust mite, cat, dog, and cockroach allergens. Children were evaluated at age seven for asthma based on reported symptoms and objective measures of lung function. Host, environmental exposures and home characteristics evaluated included history of parental asthma, race, gender, upper and lower respiratory symptoms, season of birth, family income, cigarette smoke exposure, air conditioning, dehumidifier, carpeting, age of home, and visible mold at age one and child positive skin prick test (SPT) to aeroallergens and molds at age seven.
Asthma was diagnosed in 24% of the children at age seven. A statistically significant increase in asthma risk at age seven was associated with high ERMI levels in the child’s home in infancy (adjusted risk ratio (aRR) for a 10-unit increase in ERMI = 1.8, 95% CI=1.5, 2.2). The summation of levels of three mold species, Aspergillus ochraceus, Aspergillus unguis, and Penicillium variabile was significantly associated with asthma (aRR = 2.2, 95% CI=1.8, 2.7).
In this birth cohort study, exposure during infancy to three mold species common to water-damaged buildings was associated with childhood asthma at age seven.
Asthma; molds; speciation; infants; Environmental Relative Moldiness Index
Discovery of new adverse drug events (ADEs) in the post-approval period is an important goal of the health system. Data mining methods that can transform data into meaningful knowledge to inform patient safety have proven to be essential. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used in support of ADE discovery and analysis.
Pharmacovigilance; Adverse Drug Events; Data Mining
Background: There is increasing concern about the potential effects of traffic-related air pollution (TRAP) on the developing brain. The impact of TRAP exposure on childhood behavior is not fully understood because of limited epidemiologic studies.
Objective: We explored the association between early-life exposure to TRAP using a surrogate, elemental carbon attributed to traffic (ECAT), and attention deficit/hyperactivity disorder (ADHD) symptoms at 7 years of age.
Methods: From the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) birth cohort we collected data on exposure to ECAT during infancy and behavioral scores at 7 years of age. Children enrolled in CCAAPS had at least one atopic parent and a birth residence either < 400 m or > 1,500 m from a major highway. Children were followed from infancy through 7 years of age. ECAT exposure during the first year of life was estimated based on measurements from 27 air sampling sites and land use regression modeling. Parents completed the Behavioral Assessment System for Children, 2nd Edition, when the child was 7 years of age. ADHD-related symptoms were assessed using the Hyperactivity, Attention Problems, Aggression, Conduct Problems, and Atypicality subscales.
Results: Exposure to the highest tertile of ECAT during the child’s first year of life was significantly associated with Hyperactivity T-scores in the “at risk” range at 7 years of age, after adjustment [adjusted odds ratio (aOR) = 1.7; 95% CI: 1.0, 2.7]. Stratification by maternal education revealed a stronger association in children whose mothers had higher education (aOR = 2.3; 95% CI: 1.3, 4.1).
Conclusions: ECAT exposure during infancy was associated with higher Hyperactivity scores in children; this association was limited to children whose mothers had more than a high school education.
attention deficit/hyperactivity disorder; child behavior; epidemiology; land use regression; traffic-related air pollution
The panel addresses the urgent need to ensure that comparative effectiveness research (CER) findings derived from diverse and distributed data sources are based on credible, high-quality data; and that the methods used to assess and report data quality are consistent, comprehensive, and available to data consumers. The panel consists of representatives from four teams leveraging electronic clinical data for CER, patient centered outcomes research (PCOR), and quality improvement (QI) and seeks to change the current paradigm where data quality assessment (DQA) is performed “behind the scenes” using one-off project specific methods. The panelists will present their process of harmonizing existing models for describing and measuring clinical data quality and will describe a comprehensive integrated framework for assessing and reporting DQA findings. The collaborative project is supported by the Electronic Data Methods (EDM) Forum, a three-year grant from the Agency for Healthcare Research and Quality (AHRQ) to facilitate learning and foster collaboration across a set of CER, PCOR, and QI projects designed to build infrastructure and methods for collecting and analyzing prospective data from electronic clinical data
When defining allergic outcomes in epidemiology studies results of the skin prick test (SPT) panel is often dichotomized as positive/negative or categorized based on the number of positive responses. Item Response Theory (IRT) models, however, may prove to be a better alternative with the ability to generate scores that account for both type and number of positive SPTs. IRT was applied to SPT responses administered to 537 children at age two in order to determine predictability of allergic disease at age four. The children received SPTs to 15 aeroallergens and two foods. Atopy predisposition scores were obtained from the IRT model using the posterior distribution of the latent trait, atopy. These scores were used to predict persistent wheeze, rhino-conjunctivitis, and eczema at age four. Results were compared to the dichotomized and categorical (positive to ≥ 2, positive to one, versus negative to all allergens) SPT variables. At age two, 39% of children had at least one positive SPT. All three allergic disease outcomes were significantly associated with IRT atopy scores: persistent wheeze odds ratio (OR)=1.7 (95% confidence interval (CI): 1.2, 2.3); rhino-conjunctivitis OR=1.7 (95% CI:1.2, 2.3); eczema OR=1.6 (95% CI: 1.2, 2.3). In contrast, rhino-conjunctivitis was the only outcome significantly associated with the dichotomized SPT variable with an OR=1.9 (95% CI:1.2, 3.0). For the categorical SPT variable, all three allergic symptoms were significantly associated with positive to ≥ 2 allergens compared to negative to all, but no difference was observed between those with positive to one compared to negative to all. The IRT model proved to be an informative methodology to assess the predictability of early SPT responses and identify the allergens most associated with atopy predisposition.
Item Response Theory; Skin Prick Test; Allergy; Atopy; Asthma; Wheeze; Rhino-conjunctivitis; Eczema; Predicting allergies
Systematic analysis of observational medical databases for active safety surveillance is hindered by the variation in data models and coding systems. Data analysts often find robust clinical data models difficult to understand and ill suited to support their analytic approaches. Further, some models do not facilitate the computations required for systematic analysis across many interventions and outcomes for large datasets. Translating the data from these idiosyncratic data models to a common data model (CDM) could facilitate both the analysts' understanding and the suitability for large-scale systematic analysis. In addition to facilitating analysis, a suitable CDM has to faithfully represent the source observational database. Before beginning to use the Observational Medical Outcomes Partnership (OMOP) CDM and a related dictionary of standardized terminologies for a study of large-scale systematic active safety surveillance, the authors validated the model's suitability for this use by example.
Validation by example
To validate the OMOP CDM, the model was instantiated into a relational database, data from 10 different observational healthcare databases were loaded into separate instances, a comprehensive array of analytic methods that operate on the data model was created, and these methods were executed against the databases to measure performance.
There was acceptable representation of the data from 10 observational databases in the OMOP CDM using the standardized terminologies selected, and a range of analytic methods was developed and executed with sufficient performance to be useful for active safety surveillance.
Developing/using computerized provider order entry; Systems to support and improve diagnostic accuracy; other specific EHR applications (results review); medication administration; disease progression and image managem; data exchange; communication and integration across care settings (inter- and intraenterprise); measuring/improving patient safety and reducing medical errors; improving healthcare workflow and process efficiency
Observational healthcare databases represent a valuable resource for health economics, outcomes research, quality of care, drug safety, epidemiology and comparative effectiveness research. The methods used to identify a population for study in an observational healthcare database with the desired drug exposures of interest are complex and not consistent nor apparent in the published literature. Our research evaluates three drug classification systems and their impact on prevalence in the analysis of observational healthcare databases using opioids as a case in point. The standard terminologies compiled in the Observational Medical Outcomes Partnership’s Common Data Model vocabulary were used to facilitate the identification of populations with opioid exposures. This study analyzed three distinct observational healthcare databases and identified patients with at least one exposure to an opioid as defined by drug codes derived through the application of three classification systems. Opioid code sets were created for each of the three classification systems and the number of identified codes was summarized. We estimated the prevalence of opioid exposure in three observational healthcare databases using the three defined code sets. In addition we compared the number of drug codes and distinct ingredients that were identified using these classification systems. We found substantial variation in the prevalence of opioid exposure identified using an individual classification system versus a composite method using multiple classification systems. To ensure transparent and reproducible research publications should include a description of the process used to develop code sets and the complete code set used in studies.
Observational databases; Classification systems; Coding standards; Drug exposures; OMOP
Allergic disorders, including asthma, allergic rhinitis, atopic dermatitis, eosinophilic esophagitis, and food allergy, are a major global health burden. The study and management of allergic disorders is complicated by the considerable heterogeneity in both the presentation and natural history of these disorders. Biorepositories serve as an excellent source of data and biospecimens for delineating subphenotypes of allergic disorders, but such resources are lacking.
In order to define subphenotypes of allergic disease accurately, we established an infrastructure to link and efficiently utilize clinical and epidemiologic data with biospecimens into a single biorepository called the Greater Cincinnati Pediatric Clinic Repository (GCPCR). Children with allergic disorders as well as healthy controls are followed longitudinally at hospital clinic, emergency department, and inpatient visits. Subjects' asthma, allergy, and skin symptoms; past medical, family, social, diet, and environmental histories; physical activity; medication adherence; perceived quality of life; and demographics are ascertained. DNA is collected from all participants, and other biospecimens such as blood, hair, and nasal epithelial cells are collected on a subset.
To date, the GCPCR has 6,317 predominantly Caucasian and African American participants, and 93% have banked DNA. This large sample size supports adequately powered genetic, epidemiologic, environmental, and health disparities studies of childhood allergic diseases.
The GCPCR is a unique biorepository that is continuously evaluated and refined to achieve and maintain rigorous clinical phenotype and biological data. Development of similar disease-specific repositories using common data elements is necessary to enable studies across multiple populations of comprehensively phenotyped patients.
Active drug safety surveillance may be enhanced by analysis of multiple observational healthcare databases, including administrative claims and electronic health records. The objective of this study was to develop and evaluate a common data model (CDM) enabling rapid, comparable, systematic analyses across disparate observational data sources to identify and evaluate the effects of medicines.
The CDM uses a person-centric design, with attributes for demographics, drug exposures, and condition occurrence. Drug eras, constructed to represent periods of persistent drug use, are derived from available elements from pharmacy dispensings, prescriptions written, and other medication history. Condition eras aggregate diagnoses that occur within a single episode of care. Drugs and conditions from source data are mapped to biomedical ontologies to standardize terminologies and enable analyses of higher-order effects.
The CDM was applied to two source types: an administrative claims and an electronic medical record database. Descriptive statistics were used to evaluate transformation rules. Two case studies demonstrate the ability of the CDM to enable standard analyses across disparate sources: analyses of persons exposed to rofecoxib and persons with an acute myocardial infarction.
Over 43 million persons, with nearly 1 billion drug exposures and 3.7 billion condition occurrences from both databases were successfully transformed into the CDM. An analysis routine applied to transformed data from each database produced consistent, comparable results.
A CDM can normalize the structure and content of disparate observational data, enabling standardized analyses that are meaningfully comparable when assessing the effects of medicines.
Pharmacoepidemiology; product surveillance, Postmarketing; drug safety, medical records systems, computerized; Epidemiologic methods; drug Toxicity; databases, Factual; medical Informatics Computing
The efficacy of thrombolytic therapy for acute ischemic stroke remains controversial in emergency medicine and has not been fully endorsed by either the American College of Emergency Physicians or the American Academy of emergency medicine. A growing recognition exists of the influence of pharmaceutical sponsorship on the reported findings of published clinical trials. Sponsorship bias has been suggested as a potential criticism of the literature and guidelines favoring thrombolytic therapy.
The objective of this study is to review the most influential literature regarding thrombolytic therapy for acute ischemic stroke and document the presence or absence of pharmaceutical sponsorship.
A publication-citation analysis was performed to identify the most frequently cited articles pertaining to thrombolytic therapy for acute ischemic stroke. Identified articles were reviewed for disclosures of pharmaceutical funding.
Of the 20 most-cited articles pertaining to thrombolytic therapy for acute stroke, 17 (85%) disclosed pharmaceutical sponsorship. These disclosures range from general sponsorship to direct employment of authors by pharmaceutical companies.
An overwhelming predominance of the most influential literature regarding thrombolytic therapy for acute ischemic stroke is susceptible to sponsorship bias. This potential bias may provide a basis for physician concern regarding the efficacy and safety of thrombolytic therapy. Further, large, independent, placebo-controlled studies may be required to guide therapy and professional guidelines definitively for acute ischemic stroke.
Using intrachoroidal injection of the transneuronal retrograde tracer pseudorabies virus (PRV) in rats, we previously localized preganglionic neurons in the superior salivatory nucleus (SSN) that regulate choroidal blood flow (ChBF) via projections to the pterygopalatine ganglion (PPG). In the present study, we used higher order transneuronal retrograde labeling following intrachoroidal PRV injection to identify central neuronal cell groups involved in parasympathetic regulation of ChBF via input to the SSN. These prominently included the hypothalamic paraventricular nucleus (PVN) and the nucleus of the solitary tract (NTS), both of which are responsive to systemic BP, and are involved in systemic sympathetic vasoconstriction. Conventional pathway tracing methods were then used to determine if the PVN and/or NTS project directly to the choroidal subdivision of the SSN. Following retrograde tracer injection into SSN (biotinylated dextran amine 3K or Fluorogold), labeled perikarya were found in PVN and NTS. Injection of the anterograde tracer, biotinylated dextran amine 10K (BDA10K) into PVN or NTS resulted in densely packed BDA10K+ terminals in prechoroidal SSN (as defined by its enrichment in nitric oxide synthase-containing perikarya). Double-label studies showed these inputs ended directly on prechoroidal nitric oxide synthase-containing neurons of SSN. Our study thus establishes that PVN and NTS project directly to the part of SSN involved in parasympathetic vasodilatory control of the choroid via the PPG. These results suggest that control of ChBF may be linked to systemic blood pressure and central control of the systemic vasculature.
biotinylated dextran amine (BDA); pseudorabies virus (PRV); choroidal blood flow (ChBF); superior salivatory nucleus (SSN); paraventricular nucleus (PVN); nucleus of solitary tract (NTS)
The main study objective was to compare different methods for assessing mold exposure in conjunction with an epidemiologic study on the development of children’s asthma. Homes of 184 children were assessed for mold by visual observations and dust sampling at child’s age 1 (Year 1). Similar assessment supplemented with air sampling was conducted in Year 7. Samples were analyzed for endotoxin, (1–3)-β-D-glucan, and fungal spores. The Mold Specific Quantitative Polymerase Chain Reaction assay was used to analyze 36 mold species in dust samples, and the Environmental Relative Moldiness Index (ERMI) was calculated. Homes were categorized based on three criteria: 1) visible mold damage, 2) moldy odor, and 3) ERMI. Even for homes where families had not moved, Year 7 endotoxin and (1–3)-β-D-glucan exposures were significantly higher than those in Year 1 (p<0.001), whereas no difference was seen for ERMI (p=0.78). Microbial concentrations were not consistently associated with visible mold damage categories, but were consistently higher in homes with moldy odor and in homes that had high ERMI. Low correlations between results in air and dust samples indicate different types or durations of potential microbial exposures from dust vs. air. Future analysis will indicate which, if any, of the assessment methods is associated with the development of asthma.
endotoxin; (1–3)-β-D-glucan; fungi; polymerase chain reaction; house dust; air sampling
Manganese (Mn) is an essential element, yet is neurotoxic in excess. The majority of Mn research has been conducted on occupationally exposed adults with few studies focused on an environmentally exposed population. Marietta, Ohio is home to one of the largest airborne Mn emission sources in the United States, a ferromanganese refinery. In preparation for a community-based participatory research study, a preliminary pilot study was initiated to characterize the community’s exposure to Mn in ambient air and to evaluate the relationship between biological indices of Mn exposure and genes associated with Mn metabolism in Marietta area residents. Participants in the pilot study were recruited through newspaper advertisement, fliers and direct mailing. Exposure to ambient Mn was estimated using an air pollution dispersion model, AERMOD. A total of 141 residents participated in the pilot study ranging in age from 2-81 years. Estimated annual average ambient air Mn concentrations in the study area obtained from AERMOD varied from 0.02-2.61 μg/m3. Mean blood and hair Mn values were 9.12 μg/L (SD 3.90) and 5.80 μg/g (SD 6.40 μg/g), respectively and were significantly correlated (r=0.30, p<0.01). Blood and hair Mn was significantly associated within families (r=0.27, p=<0.02 and r=0.43, p<0.01), respectively. The relationship between hair Mn and estimated ambient air Mn became significant when genes for iron metabolism were included in linear models. The preliminary ambient air and biological concentrations of Mn found in this population demonstrate the need for further research into potential health effects. A comprehensive study of neurobehavioral performance and environmental exposure to Mn in children residing in Marietta and a control community is currently underway.
manganese; lead; community-based; exposure; dispersion model; air pollution
Evaluating performance characteristics of analytic methods developed to identify treatment effects in longitudinal healthcare data has been hindered by lack of an objective benchmark to measure performance. Relationships between drugs and subsequent treatment effects are not precisely quantified in real-world data, and simulated data offer potential to augment method development by providing data with known, measurable characteristics. However, the use of simulated data has been limited due to its inability to adequately reflect the complexities inherent in real-world databases that are necessary for effective method development. The goal of this study was to develop and evaluate a model for simulating longitudinal healthcare data that adequately captures these complexities. An empiric design was chosen that utilizes the characteristics of a real healthcare database as simulation input. This model demonstrates the potential for simulated data with known characteristics to adequately reflect complex relationships among diseases and treatments as recorded in healthcare databases.
Rationale: Murine models demonstrate a synergistic production of reactive oxygen species on coexposure to diesel exhaust particles and endotoxin.
Objectives: It was hypothesized that coexposure to traffic-related particles and endotoxin would have an additive effect on persistent wheezing during early childhood.
Methods: Persistent wheezing at age 36 months was assessed in the Cincinnati Childhood Allergy and Air Pollution Study, a high-risk birth cohort. A time-weighted average exposure to traffic-related particles was determined by applying a land-use regression model to the homes, day cares, and other locations where children spent time from birth through age 36 months. Indoor levels of endotoxin were measured from dust samples collected before age 12 months. The relationship between dichotomized (≥75th percentile) traffic-related particle and endotoxin exposure and persistent wheezing, controlling for potential covariates, was examined.
Measurements and Main Results: Persistent wheezing at age 36 months was significantly associated with exposure to increased levels of traffic-related particles before age 12 months (OR = 1.75; 95% confidence interval, 1.07–2.87). Coexposure to endotoxin had a synergistic effect with traffic exposure on persistent wheeze (OR = 5.85; 95% confidence interval, 1.89–18.13) after adjustment for significant covariates.
Conclusions: The association between traffic-related particle exposure and persistent wheezing at age 36 months is modified by exposure to endotoxin. This finding supports prior toxicological studies demonstrating a synergistic production of reactive oxygen species after coexposure to diesel exhaust particles and endotoxin. The effect of early versus later exposure to traffic-related particles, however, remains to be studied because of the high correlation between exposure throughout the first 3 years of life.
particles; diesel; land-use regression; wheeze; endotoxin
To determine the impact of environmental exposures (diesel exhaust particle (DEP), environmental tobacco smoke (ETS), and mold) that may contribute to oxidative stress on persistent wheezing in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) birth cohort and to determine how the impact of these exposures is modified by the GST-P1 Ile105Val polymorphism.
A land-use regression model was used to derive an estimate of each child’s DEP exposure. ETS exposure was determined by questionnaire data. Each child’s home was evaluated for visible mold by a trained professional. Children in the CCAAPS cohort were genotyped for the GST-P1 polymorphism (N=570). Persistent wheezing was defined as wheezing at both 12 and 24 months.
High DEP exposure conferred increased risk for wheezing phenotypes but only among the Val105 allele carriers. Infants with multiple exposures were significantly more likely to persistently wheeze despite their genotype.
There is evidence for an environmental effect of DEP among carriers of the GST-P1 Val105 allele in the development of persistent wheezing in children. The protective effect of the GST-P1 Ile105 genotype may be overwhelmed by multiple environmental exposures that converge on oxidative stress pathways.
oxidative stress; gene:environment; diesel; smoking; children; Mold; ROS
Concerns over patient safety have made adequacy of clinical supervision an important component of care in teaching settings. Yet, few studies have examined residents' perceptions about the quality and adequacy of their supervision. We reanalyzed data from a survey conducted in 1999 to explore residents' perspectives on their supervision.
A national, multispecialty survey was distributed in 1999 to a 14.5% random sample of postgraduate year 2 (PGY-2) and PGY-3 residents. The response rate was 64.4%. Residents (n = 3604) were queried about how often they had cared for patients “without adequate supervision” during their preceding year of training.
Of responding residents, 21% (n = 737) reported having seen patients without adequate supervision at least once a week, with 4.5% saying this occurred almost daily. Differences were found across specialties, with 45% of residents in ophthalmology, 46% in neurology, and 44% in neurosurgery stating that they had experienced inadequate supervision at least once a week throughout the year, compared with 1.5% of residents in pathology and 3% in dermatology. Inadequate supervision was found to be inversely correlated with residents' positive ratings of their learning, time with attendings, and overall residency experience (P < .001 for all), and positively correlated with negative features of training, including medical errors, sleep deprivation, stress, conflict with other medical personnel, falsifying patient records, and working while impaired (P < .001).
In residents' self-report, inadequate clinical supervision correlates with other reported negative aspects of training. Collectively, this may detrimentally affect resident learning and patient safety.
Eczema is very common and increasing in prevalence. Prospective studies investigating environmental and genetic risk factors for eczema in a birth cohort are lacking. We evaluated risk factors that may promote development of childhood eczema in the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) birth cohort (n = 762) of infants with at least one atopic parent. Objective environmental exposure data were available for each participant. At annual physical examinations, children underwent skin prick tests (SPTs), eczema was diagnosed by a clinician, and DNA was collected. Among Caucasian children, 39% developed eczema by age 3. Children with a pet dog were significantly less likely to have eczema at age one (odds ratio (OR) 0.62, 95% confidence interval (CI): 0.40–0.97) or at both ages 2 and 3 (OR = 0.54, 95% CI: 0.30–0.97). This finding was most significant among children carrying the CD14–159C/T CC genotype. Carriers of the CD14–159C/T and IL4Rα I75V single-nucleotide polymorphisms (SNPs) had an increased risk of eczema at ages 2 and 3 (OR 3.44, 95% CI: 1.56–7.57), especially among children who were SPT+. These results provide new insights into the pathogenesis of eczema in high-risk children and support a protective role for early exposure to dog, especially among those carrying the CD14–159C/T SNP. The results also demonstrate a susceptible effect of the combination of CD14 and IL4Rα SNPs with eczema.
Previous studies of allergic rhinitis in children have not documented the environmental risk factors for infants at age one. We examined the relationship of environmental tobacco smoke (ETS) and visible mold exposures on the development of allergic rhinitis, rhinitis and upper respiratory infection (URI) in a birth cohort where at least one parent was skin prick test (SPT) positive. ETS exposure and upper respiratory symptoms were obtained by questionnaires. Visible mold was classified as none, low or high during home visit. Infants had a SPT at age one. After adjustment for potential confounders, exposure to >20 cigarettes per day was associated with an increased risk of developing allergic rhinitis at age one [odds ratio (OR) =2.7; 95% CI 1.04–6.8] and rhinitis symptoms during the first year (OR =1.9; 95% CI 1.1–3.2). Infants with low (OR =1.5; 95% CI 1.1–2.3) or high (OR =5.1; 95% CI 2.2–12.1) levels of visible mold in their homes were more likely to have more frequent URI during the first year. Older siblings were protective for development of both rhinitis symptoms and allergic rhinitis. This study suggests that ETS exposure, rather than visible mold, is associated with rhinitis and allergic rhinitis in infants. The analysis also suggests that mold may be a stronger risk factor for URI that ETS.
environmental tobacco smoke; mold; allergic rhinitis; rhinitis; infant; upper respiratory infection
Epidemiologic studies of air pollution require accurate exposure assessments at unmonitored locations in order to minimize exposure misclassification. One approach gaining considerable interest is the land-use regression (LUR) model. Generally, the LUR model has been utilized to characterize air pollution exposure and health effects for individuals residing within urban areas. The objective of this article is to briefly summarize the history and application of LUR models to date outlining similarities and differences of the variables included in the model, model development, and model validation. There were 6 studies available for a total of 12 LUR models. Our findings indicated that among these studies, the four primary classes of variables used were road type, traffic count, elevation, and land cover. Of these four, traffic count was generally the most important. The model R2 explaining the variability in the exposure estimates for these LUR models ranged from .54 to .81. The number of air sampling sites generating the exposure estimates, however, was not correlated with the model R2 suggesting that the locations of the sampling sites may be of greater importance than the total number of sites. The primary conclusion of this study is that LUR models are an important tool for integrating traffic and geographic information to characterize variability in exposures.
To present methodology to identify atopic parents and determine the prevalence of sensitization to 15 aeroallergens in their infant offspring.
A birth cohort of infants was identified from birth records; an infant was enrolled if 1 of the parents reported allergy respiratory symptoms and had a positive skin prick test (SPT) to a common aeroallergen. At age 1 year, these infants were tested to the same aeroallergens.
Of the 680 enrolled infants, 28.4% were SPT+ to 1 or more aeroallergens and/or food, and 18.0% were positive to 1 or more aeroallergens. By category of allergens, 9.7% were sensitized to pollens, 7.5% to molds, 4.3% to house dust mite and/or cockroach, and 3.4% to dog and/or cat. Of the infants who were positive to an aeroallergen, 65.7% remained positive at age 2 years.
Infants born to atopic parents with percutaneous sensitization to aeroallergens are at increased risk for aeroallergen sensitization during infancy, which persists to age 2 years. These findings suggest that current clinical practices, which generally avoid skin testing before age 2 years, be reassessed in this population of high-risk children.
In most studies that investigate the association of mold or water damage and respiratory disorders in infants, the analysis is not adjusted for exposure to house dust mite (HDM), which is also a known cause of respiratory illnesses.
To investigate the relationship between visually observable mold or water damage and HDM (Der f 1) levels and the prevalence of lower respiratory tract symptoms and allergen sensitization in infants of atopic parents as part of a prospective birth cohort study.
On-site home visits (at the infants’ age of 8 months) were performed to evaluate observable mold or water damage and HDM exposure. At a clinic visit near the infant’s first birthday, medical histories, including parent-reported wheezing episodes, and a skin prick test to food and 15 common aeroallergens were conducted in 640 infants.
More than half of the homes were found to have mold or water damage, and 5% had major mold or water damage with visible mold at 0.2 m2 or more. Only 16% of homes had a HDM allergen (Der f 1) concentration of more than 2 μg/g. Major mold or water damage increased the risk of recurrent wheezing nearly 2 times in infants, 5 times in food or aeroallergen-sensitized infants, and 6 times in aeroallergen-sensitized infants. Neither visible mold or water damage nor HDM exposure was associated with sensitization to either mold or aeroallergens.
Visible mold was shown to be a significant risk factor for recurrent wheezing in infants at high risk of developing atopic disorders, whereas HDM exposure did not significantly increase the risk.
We previously reported an association between infant wheezing and residence < 100 m from stop-and-go bus and truck traffic. The use of a proximity model, however, may lead to exposure misclassification.
Results obtained from a land use regression (LUR) model of exposure to truck and bus traffic are compared with those obtained with a proximity model. The estimates derived from the LUR model were then related to infant wheezing.
We derived a marker of diesel combustion—elemental carbon attributable to traffic sources (ECAT)—from ambient monitoring results of particulate matter with aerodynamic diameter < 2.5 μm. We developed a multiple regression model with ECAT as the outcome variable. Variables included in the model were locations of major roads, bus routes, truck traffic count, and elevation. Model parameter estimates were applied to estimate individual ECAT levels at infants’ homes.
The levels of estimated ECAT at the monitoring stations ranged from 0.20 to 1.02 μg/m3. A LUR model of exposure with a coefficient of determination (R2) of 0.75 was applied to infants’ homes. The mean (± SD) ambient exposure of ECAT for infants previously categorized as unexposed, exposed to stop-and-go traffic, or exposed to moving traffic was 0.32 ± 0.06, 0.42 ± 0.14, and 0.49 ± 0.14 μg/m3, respectively. Levels of ECAT from 0.30 to 0.90 μg/m3 were significantly associated with infant wheezing.
The LUR model resulted in a range of ECAT individually derived for all infants’ homes that may reduce the exposure misclassification that can arise from a proximity model.
diesel; land; model; proximity; regression; spatial; traffic; use